Compare commits

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64 Commits
Author SHA1 Message Date
RossandGitHub 2779ad194c feat: Support serializing dataclasses (#206)
* Support serializing dataclasses

* Update version

* Run black

* Fix for Python 3.9
2025-03-17 14:28:33 +00:00
Peter KirkhamandGitHub 5a4167d5ce feat: add support for responses api (#205)
* feat: add suppoort for responses api

* fix: test

* fix: black

* fix: test - hopefully

* fix: test - hopefully #2

* fix: test - hopefully #3

* fix: test - hopefully #4

* fix: greptaile catch

* fix: mypy is not my friend

* fix: isort usort weallsort

* fix: noredef

* fix: mypy baseline

* fix: mypy

* fix: mypy
2025-03-14 05:16:52 +00:00
David NewellandGitHub 332a6fffb6 fix: distro requirement for analytics package (#204) 2025-03-12 14:12:15 +00:00
Peter KirkhamandGitHub 28a7d351ba fix: azure open ai delta check (#203) 2025-03-10 21:35:36 +00:00
Peter KirkhamandGitHub 8331af7a42 feat: cached tokens (#202)
* feat: cached tokens

* feat: add tool support

* chore: local test

* chore: isort black

* chore: bump v

* chore: remove import

* fix: types

* fix: black

* fix: mypy unpacking of None

* chore: mypy baseline

* feat: mypy fix

* fix: did things and stuff

* fix: mypy yourpy whos py?

* fix: things can be None

* fix: move test

* fix remove exampels from package

* fix: losing my py
2025-03-06 22:37:21 +00:00
Dylan MartinandGitHub f4c99714c3 chore(flags): improved some logs for quota limiting (#197)
* haha okay

* tests workin

* format

* use case-sensitive comparisons

* omg LOL

* fix tests

* jeez

* this will probably work

* now do local eval

* okay

* yo

* formatting

* fix import order

* type check

* ai yi yi

* code review

* format

* do it

* merge conflict UGH

* black formatting

* bump version

* correct changelog
2025-03-03 14:00:52 -05:00
Peter KirkhamGitHubgreptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
7dc4cbb16b feat: azure export w/ async (#200)
* feat: azure export w/ async

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
2025-02-28 20:40:09 +00:00
Michael MatlokaandGitHub 4cda646f03 feat(llm-observability): $ai_tools capture in Langchain (#199) 2025-02-27 17:50:20 +00:00
Paul D'AmbraandGitHub ea4e7fa16d feat: add some platform info to events (#198) 2025-02-26 12:26:17 +00:00
Peter KirkhamandGitHub 57a3e7470f fix: async client (#196) 2025-02-23 13:10:43 +00:00
Dylan MartinandGitHub 5e0f9e35c1 feat(feature-flags): support quota limiting for feature flags (#195)
* haha okay

* tests workin

* format

* use case-sensitive comparisons

* omg LOL

* fix tests

* jeez

* this will probably work

* now do local eval

* okay

* yo

* formatting

* fix import order

* type check

* ai yi yi

* code review

* format
2025-02-21 15:45:51 -05:00
Dylan MartinandGitHub 337f7da7c5 fix(flags): remove lower() when evaluating feature flag payloads – these payloads are case-sensitive! (#191)
* haha okay

* tests workin

* format

* use case-sensitive comparisons

* omg LOL

* fix tests

* jeez
2025-02-19 19:51:40 -05:00
Peter KirkhamandGitHub 31652d5ec3 fix: support usage as part of generation (#192) 2025-02-18 00:17:52 +00:00
HavenGitHubgreptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>Manoel Aranda Neto
6764c786a4 feat(flags): Add method for fetching decrypted remote config flag payload (#180)
* feat(flags): Add method for fetching decrypted remote config flag payload

* tweak

* tweak

* tweak

* Update posthog/__init__.py

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>

* tweak

* get example script working

* format

* sort import

* tweak

* bump minor version

* Update posthog/version.py

Co-authored-by: Manoel Aranda Neto <5731772+marandaneto@users.noreply.github.com>

* Use flag key instead of id

* tweak

* tweak

---------

Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by: Manoel Aranda Neto <5731772+marandaneto@users.noreply.github.com>
2025-02-13 14:21:05 -08:00
Frank HamandandGitHub 1b57a96509 automatically retry connection errors (#190)
* automatically retry connection errors

from the docs for max_retries: this applies only to failed DNS lookups,
 socket connections and connection timeouts

* run tests on multiple python versions

* update freezegun
2025-02-12 12:29:01 +00:00
Phil HaackandGitHub 38683e8550 Add mypy to CI (#189) 2025-02-11 09:50:45 -08:00
Phil HaackandGitHub a5c8f62a63 Use casefold to compare strings case insensitively (#184) 2025-02-11 08:06:20 -08:00
Rafael AudibertandGitHub e480b88dce fix: Move code under mypy type (#188)
* fix: Move code under mypy type

This is incorrect, we should've added these slightly lower in the method definition to avoid mypy from breaking

* feat: Bump to 3.12.1
2025-02-11 12:01:08 -03:00
Phil HaackandGitHub 3ff2a8599d Remove the usage of is_simple_flag (#186) 2025-02-10 18:52:54 -08:00
Phil HaackandGitHub a3cf4ad5fb Stop capturing all feature flags on $feature_flag_called event. (#181) 2025-02-10 17:39:03 -08:00
Peter KirkhamandGitHub cec532f241 feat: add beta parse method support (#185) 2025-02-11 00:43:36 +00:00
Phil HaackandGitHub 415508087f Deprecate the context argument (#182) 2025-02-10 15:26:29 -08:00
Phil HaackandGitHub 994003fc42 Allow specifying the flag in the example script (#157)
* Allow specifying the flag in the example script

* Reformat

* Run isort
2025-02-07 09:28:00 +09:00
Phil HaackandGitHub 319b3807f3 Move accessing variants outside of loop (#175)
* Move accessing variants outside of loop

`flag_variants` doesn't depend on condition so it doesn't make sense to declare it in the loop.

* Fix assertion

* Remove incorrect comment

Comment seems superfluous anyways.

* Break out of the loop when the key is found

The purpose of the loop is to loop through the flag keys and evaluate the one where `flag["key"] == key`. Once that key is found, there's no need to continue the loop.

* Complete the test

Looks like the test was missing an assert.

* Precompute valid variant keys outside loop
2025-02-07 09:24:17 +09:00
Peter KirkhamandGitHub 5e7314f89d fix: langchain tool parent add (#179) 2025-02-05 19:03:14 +00:00
8f43bbc613 feat(llm-observability): LangChain spans (#176)
* feat: refactor to dataclasses

* feat: spans

* test: fix part 1

* test: fix part 2

* test: fix part 3

* test: fix part n

* test: add langgraph agent test

* chore: bump and linters

* chore: bump

* fix: correctly capture a parent id when a custom trace_id is set

* test: multiple spans parent_ids

* fix: exception serialization

* refactor: ai_trace_name -> ai_span_name and ai_generation_id -> ai_span_id

* fix: logs typos

* Add minor breaking change note to changelog

* fix: naming

---------

Co-authored-by: Michael Matloka <michael@matloka.com>
2025-01-28 14:23:22 +01:00
Georgiy TarasovandGitHub eb07aafaa3 fix: serialize pydantic models (#177) 2025-01-27 17:38:49 +00:00
Peter KirkhamandGitHub 0f8b10bb09 feat(ai): add error handling to python ai sdk (#174) 2025-01-24 21:09:49 +00:00
Georgiy TarasovandGitHub 45dc933b9c fix(llm-observability): parallel traces (#172)
* fix: parallel traces

* fix: linters

* chore: bump

* fix: better naming for clarity
2025-01-23 17:27:46 +01:00
Michael Matloka 2835af49cb fix: Actually fix LangChain callback in posthoganalytics 2025-01-22 16:27:36 +01:00
Michael MatlokaandGitHub 54506e5a7c fix: Account for import posthog in posthoganalytics release (#171) 2025-01-22 13:50:39 +00:00
Peter KirkhamandGitHub bcf5b27083 chore: bump (#170) 2025-01-21 23:33:47 +00:00
Michael MatlokaandGitHub 0b6ff2e8d3 feat(llm-observability): LangChain tracing, with LangGraph tests (#169) 2025-01-21 23:18:55 +00:00
80f0b3e52e fix(llm-observability): capture system prompt for anthropic (#167)
Co-authored-by: Peter Kirkham <peter@posthog.com>
2025-01-17 21:04:37 +00:00
d1e22188ec Feat: Add Anthropic to Python SDK (#165)
Co-authored-by: Georgiy Tarasov <gtarasov.work@gmail.com>
2025-01-17 20:33:48 +00:00
Georgiy TarasovandGitHub 9b423495ed fix(llm-observability): flatten langchain's additional_kwargs (#166)
* fix: flatten additional_kwargs

* fix: remove print
2025-01-17 17:59:38 +01:00
Peter KirkhamandGitHub 7870ccd3d8 feat: privacy_mode (#164) 2025-01-15 01:28:52 +00:00
Georgiy TarasovandGitHub 190c628c7a feat(llm-observability): add new packages for posthoganalytics (#163) 2025-01-14 10:50:46 +01:00
Georgiy TarasovandGitHub 78ab0ca8b5 fix(llm-observability): include the ai packages (#162)
* fix: setuptools

* fix: include packages
2025-01-14 10:27:05 +01:00
Peter KirkhamandGitHub c5bfc1377a fix: update to export module (#161) 2025-01-14 01:25:00 +00:00
Peter KirkhamandGitHub 6b1c0dc313 feat: Embeddings + Personless events + Destructure property JSON (#160) 2025-01-14 00:35:09 +00:00
Georgiy TarasovandGitHub e51b883e7b feat(llm-observability): add langchain integration (#159)
* feat(ai): LangChain integration v0.1

* test: langchain integration tests

* test: langchain-openai for v2 and v3

* chore: reorganize imports

* fix: ci

* fix: set python on ci to 3.9

* fix: upgrade ci for python 3.9

* fix: fallback for distinct_id

* fix: personless events for omitted distinct_ids

* fix: review comments

* feat: base url retrieval
2025-01-13 18:40:02 +01:00
66101c92bf Feat: Add llm observability to python sdk (#158)
Co-authored-by: Michael Matloka <michael@matloka.com>
2025-01-11 01:34:27 +00:00
Sibin M SandGitHub 05932b3f13 [FEATURE]Add distinct_id to group_identify (#155)
* [FEATURE]Add distinct_id to group_identify

* [TESTS]Updated test cases for adding distinct_id to group_identify

* [LINT-FIX]client.py and test_client.py

* [CHORE]Verion bump and changelog update
2025-01-03 16:00:35 -05:00
Dylan MartinandGitHub 50c13563b2 fix: CI (#156)
* test CI

* heck it, upgrade python

* okay don't do anything silly with the cache hits i guess

* more CI upgrades :crossedfingers

* upgrade all CI to latest versions, then

* jk this is how python works

* whackamole

* what even

* yeesh

* this can't be it

* if this breaks ill kms

* dark magic dark MAGIC

* im giving up on my dreams
2025-01-03 15:50:21 -05:00
Dylan MartinandGitHub dca4af66ae Update CODEOWNERS (#154) 2025-01-02 12:52:51 -05:00
Dylan MartinandGitHub 9e1bb8c58a fix(flags): bump the version (#148) 2024-11-27 17:15:38 -05:00
fb57de2e12 fix(flags): correctly emit feature flag events with the FF response on get_feature_flag_payload calls (#143)
* this is the fix, needs tests

* fix test

* tests

* yeah

* please work

* ran the formatter

* code review feedback

* how'd this get here

* bump version add changelog

* Update CHANGELOG.md

Co-authored-by: David Newell <d.newell1@outlook.com>

---------

Co-authored-by: David Newell <d.newell1@outlook.com>
2024-11-25 14:51:06 -05:00
db565bc0fd fix(err): fix distinct_id, set personless and use a uuid (#144)
Co-authored-by: David Newell <david@posthog.com>
2024-11-25 12:09:57 +00:00
David NewellandGitHub 8ae3f2b623 chore: add type to stack (#142) 2024-11-19 12:46:52 +00:00
David NewellandGitHub 39f72a0070 chore: add lang to frames (#139) 2024-10-24 16:18:02 +01:00
David NewellandGitHub ee0305993d feat: add super properties (#138) 2024-10-03 17:07:47 +01:00
28c4802d9b Remove deprecated datetime.utcnow() in favour of datetime.now(tz=tzutc()) (#124)
Co-authored-by: Neil Kakkar <neilkakkar@gmail.com>
2024-09-24 11:09:15 +01:00
Neil KakkarandGitHub 67a343f242 fix(errors): Make sure project root exists to judge in app frames (#136)
* fix(errors): Make sure project root exists to judge in app frames

* prep release
2024-09-16 11:11:28 +01:00
Neil KakkarandGitHub 1521621d66 fix: Update Django integration for manual capture (#135) 2024-09-10 09:27:47 +01:00
Neil KakkarandGitHub 39070babfb feat(errors): Add manual exception capture (#134)
* feat(errors): Add manual exception capture

* prep release

* use backwards compatible helper

* add tests
2024-09-09 11:40:51 +01:00
Neil KakkarandGitHub 716eab0bc2 fix(setup): Make sure all packages are bundled (#133)
* fix(setup): Make sure all packages are bundled

* prep release

* black
2024-09-03 08:13:10 +01:00
Neil KakkarandGitHub 1c0a61d6b5 fix(setup): Make sure all packages are bundled (#132)
* fix(setup): Make sure all packages are bundled

* prep release
2024-09-03 07:23:54 +01:00
Neil KakkarandGitHub ffa35fa5cd feat(errors): Add django integration and in app frames (#131) 2024-09-03 06:10:36 +01:00
Neil KakkarandGitHub 24b7b918f7 feat(error-capture): Add basic exception autocapture (#128) 2024-08-28 06:59:41 +01:00
Phani RajandGitHub 16cbd10f1b bump version to 3.5.2 (#130) 2024-08-21 11:58:02 -05:00
Phani RajandGitHub b83d544931 fix(feature flags): Guard for None values when comparing person Properties (#129)
* Guard for None values when comparing person Properties
2024-08-21 11:18:20 -05:00
Frank HamandandGitHub 72c0ed1935 Switch us-api.i hosts to just us.i (#119)
We dropped the -api as it's a bit confusing (is capture really api?)
2024-08-14 08:41:10 +01:00
Neil KakkarandGitHub 5fdd6177ee Create CODEOWNERS (#122) 2024-05-02 18:02:13 +01:00
47 changed files with 7934 additions and 197 deletions
+17 -10
View File
@@ -13,12 +13,12 @@ jobs:
with:
fetch-depth: 1
- name: Set up Python 3.8
- name: Set up Python 3.11
uses: actions/setup-python@v2
with:
python-version: 3.8
python-version: 3.11.11
- uses: actions/cache@v1
- uses: actions/cache@v3
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-${{ hashFiles('setup.py') }}
@@ -33,28 +33,35 @@ jobs:
- name: Check formatting with black
run: |
black --check .
- name: Lint with flake8
run: |
flake8 posthog --ignore E501
flake8 posthog --ignore E501,W503
- name: Check import order with isort
run: |
isort --check-only .
- name: Check types with mypy
run: |
mypy --no-site-packages --config-file mypy.ini . | mypy-baseline filter
tests:
name: Python tests
name: Python ${{ matrix.python-version }} tests
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.9', '3.10', '3.11', '3.12', '3.13']
steps:
- uses: actions/checkout@v1
- uses: actions/checkout@v2
with:
fetch-depth: 1
- name: Set up Python 3.7
uses: actions/setup-python@v1
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: 3.7
python-version: ${{ matrix.python-version }}
- name: Install requirements.txt dependencies with pip
run: |
+3 -1
View File
@@ -14,4 +14,6 @@ pylint.out
posthog-analytics
.idea
.python-version
.coverage
.coverage
pyrightconfig.json
.env
+184 -5
View File
@@ -1,3 +1,179 @@
## 3.21.0  2025-03-17
1. Support serializing dataclasses.
## 3.20.0  2025-03-13
1. Add support for OpenAI Responses API.
## 3.19.2  2025-03-11
1. Fix install requirements for analytics package
## 3.19.1  2025-03-11
1. Fix bug where None is sent as delta in azure
## 3.19.0  2025-03-04
1. Add support for tool calls in OpenAI and Anthropic.
2. Add support for cached tokens.
## 3.18.1  2025-03-03
1. Improve quota-limited feature flag logs
## 3.18.0 - 2025-02-28
1. Add support for Azure OpenAI.
## 3.17.0 - 2025-02-27
1. The LangChain handler now captures tools in `$ai_generation` events, in property `$ai_tools`. This allows for displaying tools provided to the LLM call in PostHog UI. Note that support for `$ai_tools` in OpenAI and Anthropic SDKs is coming soon.
## 3.16.0 - 2025-02-26
1. feat: add some platform info to events (#198)
## 3.15.1 - 2025-02-23
1. Fix async client support for OpenAI.
## 3.15.0 - 2025-02-19
1. Support quota-limited feature flags
## 3.14.2 - 2025-02-19
1. Evaluate feature flag payloads with case sensitivity correctly. Fixes <https://github.com/PostHog/posthog-python/issues/178>
## 3.14.1 - 2025-02-18
1. Add support for Bedrock Anthropic Usage
## 3.13.0 - 2025-02-12
1. Automatically retry connection errors
## 3.12.1 - 2025-02-11
1. Fix mypy support for 3.12.0
2. Deprecate `is_simple_flag`
## 3.12.0 - 2025-02-11
1. Add support for OpenAI beta parse API.
2. Deprecate `context` parameter
## 3.11.1 - 2025-02-06
1. Fix LangChain callback handler to capture parent run ID.
## 3.11.0 - 2025-01-28
1. Add the `$ai_span` event to the LangChain callback handler to capture the input and output of intermediary chains.
> LLM observability naming change: event property `$ai_trace_name` is now `$ai_span_name`.
2. Fix serialiazation of Pydantic models in methods.
## 3.10.0 - 2025-01-24
1. Add `$ai_error` and `$ai_is_error` properties to LangChain callback handler, OpenAI, and Anthropic.
## 3.9.3 - 2025-01-23
1. Fix capturing of multiple traces in the LangChain callback handler.
## 3.9.2 - 2025-01-22
1. Fix importing of LangChain callback handler under certain circumstances.
## 3.9.0 - 2025-01-22
1. Add `$ai_trace` event emission to LangChain callback handler.
## 3.8.4 - 2025-01-17
1. Add Anthropic support for LLM Observability.
2. Update LLM Observability to use output_choices.
## 3.8.3 - 2025-01-14
1. Fix setuptools to include the `posthog.ai.openai` and `posthog.ai.langchain` packages for the `posthoganalytics` package.
## 3.8.2 - 2025-01-14
1. Fix setuptools to include the `posthog.ai.openai` and `posthog.ai.langchain` packages.
## 3.8.1 - 2025-01-14
1. Add LLM Observability with support for OpenAI and Langchain callbacks.
## 3.7.5 - 2025-01-03
1. Add `distinct_id` to group_identify
## 3.7.4 - 2024-11-25
1. Fix bug where this SDK incorrectly sent feature flag events with null values when calling `get_feature_flag_payload`.
## 3.7.3 - 2024-11-25
1. Use personless mode when sending an exception without a provided `distinct_id`.
## 3.7.2 - 2024-11-19
1. Add `type` property to exception stacks.
## 3.7.1 - 2024-10-24
1. Add `platform` property to each frame of exception stacks.
## 3.7.0 - 2024-10-03
1. Adds a new `super_properties` parameter on the client that are appended to every /capture call.
## 3.6.7 - 2024-09-24
1. Remove deprecated datetime.utcnow() in favour of datetime.now(tz=tzutc())
## 3.6.6 - 2024-09-16
1. Fix manual capture support for in app frames
## 3.6.5 - 2024-09-10
1. Fix django integration support for manual exception capture.
## 3.6.4 - 2024-09-05
1. Add manual exception capture.
## 3.6.3 - 2024-09-03
1. Make sure setup.py for posthoganalytics package also discovers the new exception integration package.
## 3.6.2 - 2024-09-03
1. Make sure setup.py discovers the new exception integration package.
## 3.6.1 - 2024-09-03
1. Adds django integration to exception autocapture in alpha state. This feature is not yet stable and may change in future versions.
## 3.6.0 - 2024-08-28
1. Adds exception autocapture in alpha state. This feature is not yet stable and may change in future versions.
## 3.5.2 - 2024-08-21
1. Guard for None values in local evaluation
## 3.5.1 - 2024-08-13
1. Remove "-api" suffix from ingestion hostnames
## 3.5.0 - 2024-02-29
1. - Adds a new `feature_flags_request_timeout_seconds` timeout parameter for feature flags which defaults to 3 seconds, updated from the default 10s for all other API calls.
@@ -26,7 +202,6 @@
1. Return success/failure with all capture calls from module functions
## 3.3.1 - 2024-01-10
1. Make sure we don't override any existing feature flag properties when adding locally evaluated feature flag properties.
@@ -52,6 +227,7 @@
1. Restore how feature flags work when the client library is disabled: All requests return `None` and no events are sent when the client is disabled.
2. Add a `feature_flag_definitions()` debug option, which returns currently loaded feature flag definitions. You can use this to more cleverly decide when to request local evaluation of feature flags.
## 3.0.0 - 2023-04-14
Breaking change:
@@ -92,7 +268,6 @@ posthog = Posthog('api_key', disable_geoip=False)
1. Log instead of raise error on posthog personal api key errors
2. Remove upper bound on backoff dependency
## 2.3.0 - 2023-01-31
1. Add support for returning payloads of matched feature flags
@@ -108,6 +283,7 @@ Changes:
Changes:
1. Fixes issues with date comparison.
## 2.1.1 - 2022-09-14
Changes:
@@ -120,6 +296,7 @@ Changes:
1. Feature flag defaults have been removed
2. Setup logging only when debug mode is enabled.
## 2.0.1 - 2022-08-04
- Make poll_interval configurable
@@ -132,7 +309,7 @@ Breaking changes:
1. The minimum version requirement for PostHog servers is now 1.38. If you're using PostHog Cloud, you satisfy this requirement automatically.
2. Feature flag defaults apply only when there's an error fetching feature flag results. Earlier, if the default was set to `True`, even if a flag resolved to `False`, the default would override this.
**Note: These are removed in 2.0.2**
**Note: These are removed in 2.0.2**
3. Feature flag remote evaluation doesn't require a personal API key.
New Changes:
@@ -140,18 +317,20 @@ New Changes:
1. You can now evaluate feature flags locally (i.e. without sending a request to your PostHog servers) by setting a personal API key, and passing in groups and person properties to `is_feature_enabled` and `get_feature_flag` calls.
2. Introduces a `get_all_flags` method that returns all feature flags. This is useful for when you want to seed your frontend with some initial flags, given a user ID.
## 1.4.9 - 2022-06-13
- Support for sending feature flags with capture calls
## 1.4.8 - 2022-05-12
- Support multi variate feature flags
## 1.4.7 - 2022-04-25
- Allow feature flags usage without project_api_key
## 1.4.1 - 2021-05-28
- Fix packaging issues with Sentry integrations
## 1.4.0 - 2021-05-18
+1
View File
@@ -0,0 +1 @@
@PostHog/team-feature-flags
+2
View File
@@ -17,11 +17,13 @@ release_analytics:
rm -rf posthoganalytics
mkdir posthoganalytics
cp -r posthog/* posthoganalytics/
find ./posthoganalytics -type f -exec sed -i '' -e 's/from posthog /from posthoganalytics /g' {} \;
find ./posthoganalytics -type f -exec sed -i '' -e 's/from posthog\./from posthoganalytics\./g' {} \;
rm -rf posthog
python setup_analytics.py sdist bdist_wheel
twine upload dist/*
mkdir posthog
find ./posthoganalytics -type f -exec sed -i '' -e 's/from posthoganalytics /from posthog /g' {} \;
find ./posthoganalytics -type f -exec sed -i '' -e 's/from posthoganalytics\./from posthog\./g' {} \;
cp -r posthoganalytics/* posthog/
rm -rf posthoganalytics
+2
View File
@@ -10,8 +10,10 @@ Please see the [Python integration docs](https://posthog.com/docs/integrations/p
### Testing Locally
1. Run `python3 -m venv env` (creates virtual environment called "env")
* or `uv venv env`
2. Run `source env/bin/activate` (activates the virtual environment)
3. Run `python3 -m pip install -e ".[test]"` (installs the package in develop mode, along with test dependencies)
* or `uv pip install -e ".[test]"`
4. Run `make test`
1. To run a specific test do `pytest -k test_no_api_key`
+10 -4
View File
@@ -1,10 +1,15 @@
# PostHog Python library example
# Import the library
import time
import argparse
import posthog
# Add argument parsing
parser = argparse.ArgumentParser(description="PostHog Python library example")
parser.add_argument(
"--flag", default="person-on-events-enabled", help="Feature flag key to check (default: person-on-events-enabled)"
)
args = parser.parse_args()
posthog.debug = True
# You can find this key on the /setup page in PostHog
@@ -18,7 +23,7 @@ posthog.poll_interval = 10
print(
posthog.feature_enabled(
"person-on-events-enabled",
args.flag, # Use the flag from command line arguments
"12345",
groups={"organization": str("0182ee91-8ef7-0000-4cb9-fedc5f00926a")},
group_properties={
@@ -96,6 +101,7 @@ print(
"distinct_id_random_22", person_properties={"$geoip_city_name": "Sydney"}, only_evaluate_locally=True
)
)
print(posthog.get_remote_config_payload("encrypted_payload_flag_key"))
posthog.shutdown()
+41
View File
@@ -0,0 +1,41 @@
posthog/utils.py:0: error: Library stubs not installed for "six" [import-untyped]
posthog/utils.py:0: error: Library stubs not installed for "dateutil.tz" [import-untyped]
posthog/utils.py:0: error: Statement is unreachable [unreachable]
posthog/utils.py:0: error: Argument 1 to "join" of "str" has incompatible type "AttributeError"; expected "Iterable[str]" [arg-type]
posthog/request.py:0: error: Library stubs not installed for "requests" [import-untyped]
posthog/request.py:0: note: Hint: "python3 -m pip install types-requests"
posthog/request.py:0: error: Library stubs not installed for "dateutil.tz" [import-untyped]
posthog/request.py:0: error: Incompatible types in assignment (expression has type "bytes", variable has type "str") [assignment]
posthog/consumer.py:0: error: Name "Empty" already defined (possibly by an import) [no-redef]
posthog/consumer.py:0: error: Need type annotation for "items" (hint: "items: list[<type>] = ...") [var-annotated]
posthog/consumer.py:0: error: Unsupported operand types for <= ("int" and "str") [operator]
posthog/consumer.py:0: note: Right operand is of type "int | str"
posthog/consumer.py:0: error: Unsupported operand types for < ("str" and "int") [operator]
posthog/consumer.py:0: note: Left operand is of type "int | str"
posthog/feature_flags.py:0: error: Library stubs not installed for "dateutil" [import-untyped]
posthog/feature_flags.py:0: error: Library stubs not installed for "dateutil.relativedelta" [import-untyped]
posthog/feature_flags.py:0: error: Unused "type: ignore" comment [unused-ignore]
posthog/client.py:0: error: Library stubs not installed for "dateutil.tz" [import-untyped]
posthog/client.py:0: note: Hint: "python3 -m pip install types-python-dateutil"
posthog/client.py:0: note: (or run "mypy --install-types" to install all missing stub packages)
posthog/client.py:0: note: See https://mypy.readthedocs.io/en/stable/running_mypy.html#missing-imports
posthog/client.py:0: error: Library stubs not installed for "six" [import-untyped]
posthog/client.py:0: note: Hint: "python3 -m pip install types-six"
posthog/client.py:0: error: Name "queue" already defined (by an import) [no-redef]
posthog/client.py:0: error: Need type annotation for "queue" [var-annotated]
posthog/client.py:0: error: Item "None" of "Any | None" has no attribute "get" [union-attr]
simulator.py:0: error: Unexpected keyword argument "anonymous_id" for "capture" [call-arg]
posthog/__init__.py:0: note: "capture" defined here
simulator.py:0: error: Unexpected keyword argument "anonymous_id" for "identify" [call-arg]
posthog/__init__.py:0: note: "identify" defined here
simulator.py:0: error: Unexpected keyword argument "traits" for "identify" [call-arg]
posthog/__init__.py:0: note: "identify" defined here
example.py:0: error: Statement is unreachable [unreachable]
posthog/sentry/posthog_integration.py:0: error: Statement is unreachable [unreachable]
posthog/ai/utils.py:0: error: Need type annotation for "output" (hint: "output: list[<type>] = ...") [var-annotated]
posthog/ai/utils.py:0: error: Function "builtins.any" is not valid as a type [valid-type]
posthog/ai/utils.py:0: note: Perhaps you meant "typing.Any" instead of "any"?
posthog/ai/utils.py:0: error: Function "builtins.any" is not valid as a type [valid-type]
posthog/ai/utils.py:0: note: Perhaps you meant "typing.Any" instead of "any"?
sentry_django_example/sentry_django_example/settings.py:0: error: Need type annotation for "ALLOWED_HOSTS" (hint: "ALLOWED_HOSTS: list[<type>] = ...") [var-annotated]
sentry_django_example/sentry_django_example/settings.py:0: error: Incompatible types in assignment (expression has type "str", variable has type "None") [assignment]
+38
View File
@@ -0,0 +1,38 @@
[mypy]
python_version = 3.11
plugins =
pydantic.mypy
strict_optional = True
no_implicit_optional = True
warn_unused_ignores = True
check_untyped_defs = True
warn_unreachable = True
strict_equality = True
ignore_missing_imports = True
[mypy-django.*]
ignore_missing_imports = True
[mypy-sentry_sdk.*]
ignore_missing_imports = True
[mypy-posthog.test.*]
ignore_errors = True
[mypy-posthog.*.test.*]
ignore_errors = True
[mypy-openai.*]
ignore_missing_imports = True
[mypy-langchain.*]
ignore_missing_imports = True
[mypy-langchain_core.*]
ignore_missing_imports = True
[mypy-anthropic.*]
ignore_missing_imports = True
[mypy-httpx.*]
ignore_missing_imports = True
+137 -1
View File
@@ -1,7 +1,9 @@
import datetime # noqa: F401
from typing import Callable, Dict, Optional, Tuple # noqa: F401
import warnings
from typing import Callable, Dict, List, Optional, Tuple # noqa: F401
from posthog.client import Client
from posthog.exception_capture import Integrations # noqa: F401
from posthog.version import VERSION
__version__ = VERSION
@@ -19,6 +21,14 @@ project_api_key = None # type: Optional[str]
poll_interval = 30 # type: int
disable_geoip = True # type: bool
feature_flags_request_timeout_seconds = 3 # type: int
super_properties = None # type: Optional[Dict]
# Currently alpha, use at your own risk
enable_exception_autocapture = False # type: bool
exception_autocapture_integrations = [] # type: List[Integrations]
# Used to determine in app paths for exception autocapture. Defaults to the current working directory
project_root = None # type: Optional[str]
# Used for our AI observability feature to not capture any prompt or output just usage + metadata
privacy_mode = False # type: bool
default_client = None # type: Optional[Client]
@@ -55,6 +65,14 @@ def capture(
posthog.capture('distinct id', 'purchase', groups={'company': 'id:5'})
```
"""
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
return _proxy(
"capture",
distinct_id=distinct_id,
@@ -93,6 +111,14 @@ def identify(
})
```
"""
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
return _proxy(
"identify",
distinct_id=distinct_id,
@@ -128,6 +154,14 @@ def set(
})
```
"""
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
return _proxy(
"set",
distinct_id=distinct_id,
@@ -163,6 +197,14 @@ def set_once(
})
```
"""
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
return _proxy(
"set_once",
distinct_id=distinct_id,
@@ -199,6 +241,14 @@ def group_identify(
})
```
"""
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
return _proxy(
"group_identify",
group_type=group_type,
@@ -236,6 +286,14 @@ def alias(
posthog.alias('anonymous session id', 'distinct id')
```
"""
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
return _proxy(
"alias",
previous_id=previous_id,
@@ -247,6 +305,58 @@ def alias(
)
def capture_exception(
exception=None, # type: Optional[BaseException]
distinct_id=None, # type: Optional[str]
properties=None, # type: Optional[Dict]
context=None, # type: Optional[Dict]
timestamp=None, # type: Optional[datetime.datetime]
uuid=None, # type: Optional[str]
groups=None, # type: Optional[Dict]
):
# type: (...) -> Tuple[bool, dict]
"""
capture_exception allows you to capture exceptions that happen in your code. This is useful for debugging and understanding what errors your users are encountering.
This function never raises an exception, even if it fails to send the event.
A `capture_exception` call does not require any fields, but we recommend sending:
- `distinct id` which uniquely identifies your user for which this exception happens
- `exception` to specify the exception to capture. If not provided, the current exception is captured via `sys.exc_info()`
Optionally you can submit
- `properties`, which can be a dict with any information you'd like to add
- `groups`, which is a dict of group type -> group key mappings
For example:
```python
try:
1 / 0
except Exception as e:
posthog.capture_exception(e, 'my specific distinct id')
posthog.capture_exception(distinct_id='my specific distinct id')
```
"""
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
return _proxy(
"capture_exception",
exception=exception,
distinct_id=distinct_id,
properties=properties,
context=context,
timestamp=timestamp,
uuid=uuid,
groups=groups,
)
def feature_enabled(
key, # type: str
distinct_id, # type: str
@@ -382,6 +492,26 @@ def get_feature_flag_payload(
)
def get_remote_config_payload(
key, # type: str
):
"""Get the payload for a remote config feature flag.
Args:
key: The key of the feature flag
Returns:
The payload associated with the feature flag. If payload is encrypted, the return value will decrypted
Note:
Requires personal_api_key to be set for authentication
"""
return _proxy(
"get_remote_config_payload",
key=key,
)
def get_all_flags_and_payloads(
distinct_id,
groups={},
@@ -454,6 +584,12 @@ def _proxy(method, *args, **kwargs):
disabled=disabled,
disable_geoip=disable_geoip,
feature_flags_request_timeout_seconds=feature_flags_request_timeout_seconds,
super_properties=super_properties,
# TODO: Currently this monitoring begins only when the Client is initialised (which happens when you do something with the SDK)
# This kind of initialisation is very annoying for exception capture. We need to figure out a way around this,
# or deprecate this proxy option fully (it's already in the process of deprecation, no new clients should be using this method since like 5-6 months)
enable_exception_autocapture=enable_exception_autocapture,
exception_autocapture_integrations=exception_autocapture_integrations,
)
# always set incase user changes it
View File
+12
View File
@@ -0,0 +1,12 @@
from .anthropic import Anthropic
from .anthropic_async import AsyncAnthropic
from .anthropic_providers import AnthropicBedrock, AnthropicVertex, AsyncAnthropicBedrock, AsyncAnthropicVertex
__all__ = [
"Anthropic",
"AsyncAnthropic",
"AnthropicBedrock",
"AsyncAnthropicBedrock",
"AnthropicVertex",
"AsyncAnthropicVertex",
]
+206
View File
@@ -0,0 +1,206 @@
try:
import anthropic
from anthropic.resources import Messages
except ImportError:
raise ModuleNotFoundError("Please install the Anthropic SDK to use this feature: 'pip install anthropic'")
import time
import uuid
from typing import Any, Dict, Optional
from posthog.ai.utils import call_llm_and_track_usage, get_model_params, merge_system_prompt, with_privacy_mode
from posthog.client import Client as PostHogClient
class Anthropic(anthropic.Anthropic):
"""
A wrapper around the Anthropic SDK that automatically sends LLM usage events to PostHog.
"""
_ph_client: PostHogClient
def __init__(self, posthog_client: PostHogClient, **kwargs):
"""
Args:
posthog_client: PostHog client for tracking usage
**kwargs: Additional arguments passed to the Anthropic client
"""
super().__init__(**kwargs)
self._ph_client = posthog_client
self.messages = WrappedMessages(self)
class WrappedMessages(Messages):
_client: Anthropic
def create(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
"""
Create a message using Anthropic's API while tracking usage in PostHog.
Args:
posthog_distinct_id: Optional ID to associate with the usage event
posthog_trace_id: Optional trace UUID for linking events
posthog_properties: Optional dictionary of extra properties to include in the event
posthog_privacy_mode: Whether to redact sensitive information in tracking
posthog_groups: Optional group analytics properties
**kwargs: Arguments passed to Anthropic's messages.create
"""
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
if kwargs.get("stream", False):
return self._create_streaming(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
**kwargs,
)
return call_llm_and_track_usage(
posthog_distinct_id,
self._client._ph_client,
"anthropic",
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
self._client.base_url,
super().create,
**kwargs,
)
def stream(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
return self._create_streaming(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
**kwargs,
)
def _create_streaming(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
**kwargs: Any,
):
start_time = time.time()
usage_stats: Dict[str, int] = {"input_tokens": 0, "output_tokens": 0}
accumulated_content = []
response = super().create(**kwargs)
def generator():
nonlocal usage_stats
nonlocal accumulated_content
try:
for event in response:
if hasattr(event, "usage") and event.usage:
usage_stats = {
k: getattr(event.usage, k, 0)
for k in [
"input_tokens",
"output_tokens",
"cache_read_input_tokens",
"cache_creation_input_tokens",
]
}
if hasattr(event, "content") and event.content:
accumulated_content.append(event.content)
yield event
finally:
end_time = time.time()
latency = end_time - start_time
output = "".join(accumulated_content)
self._capture_streaming_event(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
kwargs,
usage_stats,
latency,
output,
)
return generator()
def _capture_streaming_event(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
kwargs: Dict[str, Any],
usage_stats: Dict[str, int],
latency: float,
output: str,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
event_properties = {
"$ai_provider": "anthropic",
"$ai_model": kwargs.get("model"),
"$ai_model_parameters": get_model_params(kwargs),
"$ai_input": with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
merge_system_prompt(kwargs, "anthropic"),
),
"$ai_output_choices": with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
[{"content": output, "role": "assistant"}],
),
"$ai_http_status": 200,
"$ai_input_tokens": usage_stats.get("input_tokens", 0),
"$ai_output_tokens": usage_stats.get("output_tokens", 0),
"$ai_cache_read_input_tokens": usage_stats.get("cache_read_input_tokens", 0),
"$ai_cache_creation_input_tokens": usage_stats.get("cache_creation_input_tokens", 0),
"$ai_latency": latency,
"$ai_trace_id": posthog_trace_id,
"$ai_base_url": str(self._client.base_url),
**(posthog_properties or {}),
}
if posthog_distinct_id is None:
event_properties["$process_person_profile"] = False
if hasattr(self._client._ph_client, "capture"):
self._client._ph_client.capture(
distinct_id=posthog_distinct_id or posthog_trace_id,
event="$ai_generation",
properties=event_properties,
groups=posthog_groups,
)
+206
View File
@@ -0,0 +1,206 @@
try:
import anthropic
from anthropic.resources import AsyncMessages
except ImportError:
raise ModuleNotFoundError("Please install the Anthropic SDK to use this feature: 'pip install anthropic'")
import time
import uuid
from typing import Any, Dict, Optional
from posthog.ai.utils import call_llm_and_track_usage_async, get_model_params, merge_system_prompt, with_privacy_mode
from posthog.client import Client as PostHogClient
class AsyncAnthropic(anthropic.AsyncAnthropic):
"""
An async wrapper around the Anthropic SDK that automatically sends LLM usage events to PostHog.
"""
_ph_client: PostHogClient
def __init__(self, posthog_client: PostHogClient, **kwargs):
"""
Args:
posthog_client: PostHog client for tracking usage
**kwargs: Additional arguments passed to the Anthropic client
"""
super().__init__(**kwargs)
self._ph_client = posthog_client
self.messages = AsyncWrappedMessages(self)
class AsyncWrappedMessages(AsyncMessages):
_client: AsyncAnthropic
async def create(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
"""
Create a message using Anthropic's API while tracking usage in PostHog.
Args:
posthog_distinct_id: Optional ID to associate with the usage event
posthog_trace_id: Optional trace UUID for linking events
posthog_properties: Optional dictionary of extra properties to include in the event
posthog_privacy_mode: Whether to redact sensitive information in tracking
posthog_groups: Optional group analytics properties
**kwargs: Arguments passed to Anthropic's messages.create
"""
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
if kwargs.get("stream", False):
return await self._create_streaming(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
**kwargs,
)
return await call_llm_and_track_usage_async(
posthog_distinct_id,
self._client._ph_client,
"anthropic",
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
self._client.base_url,
super().create,
**kwargs,
)
async def stream(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
return await self._create_streaming(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
**kwargs,
)
async def _create_streaming(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
**kwargs: Any,
):
start_time = time.time()
usage_stats: Dict[str, int] = {"input_tokens": 0, "output_tokens": 0}
accumulated_content = []
response = await super().create(**kwargs)
async def generator():
nonlocal usage_stats
nonlocal accumulated_content
try:
async for event in response:
if hasattr(event, "usage") and event.usage:
usage_stats = {
k: getattr(event.usage, k, 0)
for k in [
"input_tokens",
"output_tokens",
"cache_read_input_tokens",
"cache_creation_input_tokens",
]
}
if hasattr(event, "content") and event.content:
accumulated_content.append(event.content)
yield event
finally:
end_time = time.time()
latency = end_time - start_time
output = "".join(accumulated_content)
await self._capture_streaming_event(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
kwargs,
usage_stats,
latency,
output,
)
return generator()
async def _capture_streaming_event(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
kwargs: Dict[str, Any],
usage_stats: Dict[str, int],
latency: float,
output: str,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
event_properties = {
"$ai_provider": "anthropic",
"$ai_model": kwargs.get("model"),
"$ai_model_parameters": get_model_params(kwargs),
"$ai_input": with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
merge_system_prompt(kwargs, "anthropic"),
),
"$ai_output_choices": with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
[{"content": output, "role": "assistant"}],
),
"$ai_http_status": 200,
"$ai_input_tokens": usage_stats.get("input_tokens", 0),
"$ai_output_tokens": usage_stats.get("output_tokens", 0),
"$ai_cache_read_input_tokens": usage_stats.get("cache_read_input_tokens", 0),
"$ai_cache_creation_input_tokens": usage_stats.get("cache_creation_input_tokens", 0),
"$ai_latency": latency,
"$ai_trace_id": posthog_trace_id,
"$ai_base_url": str(self._client.base_url),
**(posthog_properties or {}),
}
if posthog_distinct_id is None:
event_properties["$process_person_profile"] = False
if hasattr(self._client._ph_client, "capture"):
self._client._ph_client.capture(
distinct_id=posthog_distinct_id or posthog_trace_id,
event="$ai_generation",
properties=event_properties,
groups=posthog_groups,
)
@@ -0,0 +1,60 @@
try:
import anthropic
except ImportError:
raise ModuleNotFoundError("Please install the Anthropic SDK to use this feature: 'pip install anthropic'")
from posthog.ai.anthropic.anthropic import WrappedMessages
from posthog.ai.anthropic.anthropic_async import AsyncWrappedMessages
from posthog.client import Client as PostHogClient
class AnthropicBedrock(anthropic.AnthropicBedrock):
"""
A wrapper around the Anthropic Bedrock SDK that automatically sends LLM usage events to PostHog.
"""
_ph_client: PostHogClient
def __init__(self, posthog_client: PostHogClient, **kwargs):
super().__init__(**kwargs)
self._ph_client = posthog_client
self.messages = WrappedMessages(self)
class AsyncAnthropicBedrock(anthropic.AsyncAnthropicBedrock):
"""
A wrapper around the Anthropic Bedrock SDK that automatically sends LLM usage events to PostHog.
"""
_ph_client: PostHogClient
def __init__(self, posthog_client: PostHogClient, **kwargs):
super().__init__(**kwargs)
self._ph_client = posthog_client
self.messages = AsyncWrappedMessages(self)
class AnthropicVertex(anthropic.AnthropicVertex):
"""
A wrapper around the Anthropic Vertex SDK that automatically sends LLM usage events to PostHog.
"""
_ph_client: PostHogClient
def __init__(self, posthog_client: PostHogClient, **kwargs):
super().__init__(**kwargs)
self._ph_client = posthog_client
self.messages = WrappedMessages(self)
class AsyncAnthropicVertex(anthropic.AsyncAnthropicVertex):
"""
A wrapper around the Anthropic Vertex SDK that automatically sends LLM usage events to PostHog.
"""
_ph_client: PostHogClient
def __init__(self, posthog_client: PostHogClient, **kwargs):
super().__init__(**kwargs)
self._ph_client = posthog_client
self.messages = AsyncWrappedMessages(self)
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from .callbacks import CallbackHandler
__all__ = ["CallbackHandler"]
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try:
import langchain # noqa: F401
except ImportError:
raise ModuleNotFoundError("Please install LangChain to use this feature: 'pip install langchain'")
import logging
import time
from dataclasses import dataclass
from typing import (
Any,
Dict,
List,
Optional,
Sequence,
Tuple,
Union,
cast,
)
from uuid import UUID
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema.agent import AgentAction, AgentFinish
from langchain_core.documents import Document
from langchain_core.messages import AIMessage, BaseMessage, FunctionMessage, HumanMessage, SystemMessage, ToolMessage
from langchain_core.outputs import ChatGeneration, LLMResult
from pydantic import BaseModel
from posthog import default_client
from posthog.ai.utils import get_model_params, with_privacy_mode
from posthog.client import Client
log = logging.getLogger("posthog")
@dataclass
class SpanMetadata:
name: str
"""Name of the run: chain name, model name, etc."""
start_time: float
"""Start time of the run."""
end_time: Optional[float]
"""End time of the run."""
input: Optional[Any]
"""Input of the run: messages, prompt variables, etc."""
@property
def latency(self) -> float:
if not self.end_time:
return 0
return self.end_time - self.start_time
@dataclass
class GenerationMetadata(SpanMetadata):
provider: Optional[str] = None
"""Provider of the run: OpenAI, Anthropic"""
model: Optional[str] = None
"""Model used in the run"""
model_params: Optional[Dict[str, Any]] = None
"""Model parameters of the run: temperature, max_tokens, etc."""
base_url: Optional[str] = None
"""Base URL of the provider's API used in the run."""
tools: Optional[List[Dict[str, Any]]] = None
"""Tools provided to the model."""
RunMetadata = Union[SpanMetadata, GenerationMetadata]
RunMetadataStorage = Dict[UUID, RunMetadata]
class CallbackHandler(BaseCallbackHandler):
"""
The PostHog LLM observability callback handler for LangChain.
"""
_client: Client
"""PostHog client instance."""
_distinct_id: Optional[Union[str, int, float, UUID]]
"""Distinct ID of the user to associate the trace with."""
_trace_id: Optional[Union[str, int, float, UUID]]
"""Global trace ID to be sent with every event. Otherwise, the top-level run ID is used."""
_trace_input: Optional[Any]
"""The input at the start of the trace. Any JSON object."""
_trace_name: Optional[str]
"""Name of the trace, exposed in the UI."""
_properties: Optional[Dict[str, Any]]
"""Global properties to be sent with every event."""
_runs: RunMetadataStorage
"""Mapping of run IDs to run metadata as run metadata is only available on the start of generation."""
_parent_tree: Dict[UUID, UUID]
"""
A dictionary that maps chain run IDs to their parent chain run IDs (parent pointer tree),
so the top level can be found from a bottom-level run ID.
"""
def __init__(
self,
client: Optional[Client] = None,
*,
distinct_id: Optional[Union[str, int, float, UUID]] = None,
trace_id: Optional[Union[str, int, float, UUID]] = None,
properties: Optional[Dict[str, Any]] = None,
privacy_mode: bool = False,
groups: Optional[Dict[str, Any]] = None,
):
"""
Args:
client: PostHog client instance.
distinct_id: Optional distinct ID of the user to associate the trace with.
trace_id: Optional trace ID to use for the event.
properties: Optional additional metadata to use for the trace.
privacy_mode: Whether to redact the input and output of the trace.
groups: Optional additional PostHog groups to use for the trace.
"""
posthog_client = client or default_client
if posthog_client is None:
raise ValueError("PostHog client is required")
self._client = posthog_client
self._distinct_id = distinct_id
self._trace_id = trace_id
self._properties = properties or {}
self._privacy_mode = privacy_mode
self._groups = groups or {}
self._runs = {}
self._parent_tree = {}
def on_chain_start(
self,
serialized: Dict[str, Any],
inputs: Dict[str, Any],
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
metadata: Optional[Dict[str, Any]] = None,
**kwargs,
):
self._log_debug_event("on_chain_start", run_id, parent_run_id, inputs=inputs)
self._set_parent_of_run(run_id, parent_run_id)
self._set_trace_or_span_metadata(serialized, inputs, run_id, parent_run_id, **kwargs)
def on_chain_end(
self,
outputs: Dict[str, Any],
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs: Any,
):
self._log_debug_event("on_chain_end", run_id, parent_run_id, outputs=outputs)
self._pop_run_and_capture_trace_or_span(run_id, parent_run_id, outputs)
def on_chain_error(
self,
error: BaseException,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs: Any,
):
self._log_debug_event("on_chain_error", run_id, parent_run_id, error=error)
self._pop_run_and_capture_trace_or_span(run_id, parent_run_id, error)
def on_chat_model_start(
self,
serialized: Dict[str, Any],
messages: List[List[BaseMessage]],
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs,
):
self._log_debug_event("on_chat_model_start", run_id, parent_run_id, messages=messages)
self._set_parent_of_run(run_id, parent_run_id)
input = [_convert_message_to_dict(message) for row in messages for message in row]
self._set_llm_metadata(serialized, run_id, input, **kwargs)
def on_llm_start(
self,
serialized: Dict[str, Any],
prompts: List[str],
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs: Any,
):
self._log_debug_event("on_llm_start", run_id, parent_run_id, prompts=prompts)
self._set_parent_of_run(run_id, parent_run_id)
self._set_llm_metadata(serialized, run_id, prompts, **kwargs)
def on_llm_new_token(
self,
token: str,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs: Any,
) -> Any:
"""Run on new LLM token. Only available when streaming is enabled."""
self._log_debug_event("on_llm_new_token", run_id, parent_run_id, token=token)
def on_llm_end(
self,
response: LLMResult,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs: Any,
):
"""
The callback works for both streaming and non-streaming runs. For streaming runs, the chain must set `stream_usage=True` in the LLM.
"""
self._log_debug_event("on_llm_end", run_id, parent_run_id, response=response, kwargs=kwargs)
self._pop_run_and_capture_generation(run_id, parent_run_id, response)
def on_llm_error(
self,
error: BaseException,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs: Any,
):
self._log_debug_event("on_llm_error", run_id, parent_run_id, error=error)
self._pop_run_and_capture_generation(run_id, parent_run_id, error)
def on_tool_start(
self,
serialized: Optional[Dict[str, Any]],
input_str: str,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
metadata: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> Any:
self._log_debug_event("on_tool_start", run_id, parent_run_id, input_str=input_str)
self._set_parent_of_run(run_id, parent_run_id)
self._set_trace_or_span_metadata(serialized, input_str, run_id, parent_run_id, **kwargs)
def on_tool_end(
self,
output: str,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs: Any,
) -> Any:
self._log_debug_event("on_tool_end", run_id, parent_run_id, output=output)
self._pop_run_and_capture_trace_or_span(run_id, parent_run_id, output)
def on_tool_error(
self,
error: BaseException,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[list[str]] = None,
**kwargs: Any,
) -> Any:
self._log_debug_event("on_tool_error", run_id, parent_run_id, error=error)
self._pop_run_and_capture_trace_or_span(run_id, parent_run_id, error)
def on_retriever_start(
self,
serialized: Optional[Dict[str, Any]],
query: str,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
metadata: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> Any:
self._log_debug_event("on_retriever_start", run_id, parent_run_id, query=query)
self._set_parent_of_run(run_id, parent_run_id)
self._set_trace_or_span_metadata(serialized, query, run_id, parent_run_id, **kwargs)
def on_retriever_end(
self,
documents: Sequence[Document],
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs: Any,
):
self._log_debug_event("on_retriever_end", run_id, parent_run_id, documents=documents)
self._pop_run_and_capture_trace_or_span(run_id, parent_run_id, documents)
def on_retriever_error(
self,
error: BaseException,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[list[str]] = None,
**kwargs: Any,
) -> Any:
"""Run when Retriever errors."""
self._log_debug_event("on_retriever_error", run_id, parent_run_id, error=error)
self._pop_run_and_capture_trace_or_span(run_id, parent_run_id, error)
def on_agent_action(
self,
action: AgentAction,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs: Any,
) -> Any:
"""Run on agent action."""
self._log_debug_event("on_agent_action", run_id, parent_run_id, action=action)
self._set_parent_of_run(run_id, parent_run_id)
self._set_trace_or_span_metadata(None, action, run_id, parent_run_id, **kwargs)
def on_agent_finish(
self,
finish: AgentFinish,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs: Any,
) -> Any:
self._log_debug_event("on_agent_finish", run_id, parent_run_id, finish=finish)
self._pop_run_and_capture_trace_or_span(run_id, parent_run_id, finish)
def _set_parent_of_run(self, run_id: UUID, parent_run_id: Optional[UUID] = None):
"""
Set the parent run ID for a chain run. If there is no parent, the run is the root.
"""
if parent_run_id is not None:
self._parent_tree[run_id] = parent_run_id
def _pop_parent_of_run(self, run_id: UUID):
"""
Remove the parent run ID for a chain run.
"""
try:
self._parent_tree.pop(run_id)
except KeyError:
pass
def _find_root_run(self, run_id: UUID) -> UUID:
"""
Finds the root ID of a chain run.
"""
id: UUID = run_id
while id in self._parent_tree:
id = self._parent_tree[id]
return id
def _set_trace_or_span_metadata(
self,
serialized: Optional[Dict[str, Any]],
input: Any,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs,
):
default_name = "trace" if parent_run_id is None else "span"
run_name = _get_langchain_run_name(serialized, **kwargs) or default_name
self._runs[run_id] = SpanMetadata(name=run_name, input=input, start_time=time.time(), end_time=None)
def _set_llm_metadata(
self,
serialized: Dict[str, Any],
run_id: UUID,
messages: Union[List[Dict[str, Any]], List[str]],
metadata: Optional[Dict[str, Any]] = None,
invocation_params: Optional[Dict[str, Any]] = None,
**kwargs,
):
run_name = _get_langchain_run_name(serialized, **kwargs) or "generation"
generation = GenerationMetadata(name=run_name, input=messages, start_time=time.time(), end_time=None)
if isinstance(invocation_params, dict):
generation.model_params = get_model_params(invocation_params)
if tools := invocation_params.get("tools"):
generation.tools = tools
if isinstance(metadata, dict):
if model := metadata.get("ls_model_name"):
generation.model = model
if provider := metadata.get("ls_provider"):
generation.provider = provider
try:
base_url = serialized["kwargs"]["openai_api_base"]
if base_url is not None:
generation.base_url = base_url
except KeyError:
pass
self._runs[run_id] = generation
def _pop_run_metadata(self, run_id: UUID) -> Optional[RunMetadata]:
end_time = time.time()
try:
run = self._runs.pop(run_id)
except KeyError:
log.warning(f"No run metadata found for run {run_id}")
return None
run.end_time = end_time
return run
def _get_trace_id(self, run_id: UUID):
trace_id = self._trace_id or self._find_root_run(run_id)
if not trace_id:
return run_id
return trace_id
def _get_parent_run_id(self, trace_id: Any, run_id: UUID, parent_run_id: Optional[UUID]):
"""
Replace the parent run ID with the trace ID for second level runs when a custom trace ID is set.
"""
if parent_run_id is not None and parent_run_id not in self._parent_tree:
return trace_id
return parent_run_id
def _pop_run_and_capture_trace_or_span(self, run_id: UUID, parent_run_id: Optional[UUID], outputs: Any):
trace_id = self._get_trace_id(run_id)
self._pop_parent_of_run(run_id)
run = self._pop_run_metadata(run_id)
if not run:
return
if isinstance(run, GenerationMetadata):
log.warning(f"Run {run_id} is a generation, but attempted to be captured as a trace or span.")
return
self._capture_trace_or_span(
trace_id,
run_id,
run,
outputs,
self._get_parent_run_id(trace_id, run_id, parent_run_id),
)
def _capture_trace_or_span(
self,
trace_id: Any,
run_id: UUID,
run: SpanMetadata,
outputs: Any,
parent_run_id: Optional[UUID],
):
event_name = "$ai_trace" if parent_run_id is None else "$ai_span"
event_properties = {
"$ai_trace_id": trace_id,
"$ai_input_state": with_privacy_mode(self._client, self._privacy_mode, run.input),
"$ai_latency": run.latency,
"$ai_span_name": run.name,
"$ai_span_id": run_id,
}
if parent_run_id is not None:
event_properties["$ai_parent_id"] = parent_run_id
if self._properties:
event_properties.update(self._properties)
if isinstance(outputs, BaseException):
event_properties["$ai_error"] = _stringify_exception(outputs)
event_properties["$ai_is_error"] = True
elif outputs is not None:
event_properties["$ai_output_state"] = with_privacy_mode(self._client, self._privacy_mode, outputs)
if self._distinct_id is None:
event_properties["$process_person_profile"] = False
self._client.capture(
distinct_id=self._distinct_id or run_id,
event=event_name,
properties=event_properties,
groups=self._groups,
)
def _pop_run_and_capture_generation(
self,
run_id: UUID,
parent_run_id: Optional[UUID],
response: Union[LLMResult, BaseException],
):
trace_id = self._get_trace_id(run_id)
self._pop_parent_of_run(run_id)
run = self._pop_run_metadata(run_id)
if not run:
return
if not isinstance(run, GenerationMetadata):
log.warning(f"Run {run_id} is not a generation, but attempted to be captured as a generation.")
return
self._capture_generation(
trace_id,
run_id,
run,
response,
self._get_parent_run_id(trace_id, run_id, parent_run_id),
)
def _capture_generation(
self,
trace_id: Any,
run_id: UUID,
run: GenerationMetadata,
output: Union[LLMResult, BaseException],
parent_run_id: Optional[UUID] = None,
):
event_properties = {
"$ai_trace_id": trace_id,
"$ai_span_id": run_id,
"$ai_span_name": run.name,
"$ai_parent_id": parent_run_id,
"$ai_provider": run.provider,
"$ai_model": run.model,
"$ai_model_parameters": run.model_params,
"$ai_input": with_privacy_mode(self._client, self._privacy_mode, run.input),
"$ai_http_status": 200,
"$ai_latency": run.latency,
"$ai_base_url": run.base_url,
}
if run.tools:
event_properties["$ai_tools"] = with_privacy_mode(
self._client,
self._privacy_mode,
run.tools,
)
if isinstance(output, BaseException):
event_properties["$ai_http_status"] = _get_http_status(output)
event_properties["$ai_error"] = _stringify_exception(output)
event_properties["$ai_is_error"] = True
else:
# Add usage
input_tokens, output_tokens = _parse_usage(output)
event_properties["$ai_input_tokens"] = input_tokens
event_properties["$ai_output_tokens"] = output_tokens
# Generation results
generation_result = output.generations[-1]
if isinstance(generation_result[-1], ChatGeneration):
completions = [
_convert_message_to_dict(cast(ChatGeneration, generation).message)
for generation in generation_result
]
else:
completions = [_extract_raw_esponse(generation) for generation in generation_result]
event_properties["$ai_output_choices"] = with_privacy_mode(self._client, self._privacy_mode, completions)
if self._properties:
event_properties.update(self._properties)
if self._distinct_id is None:
event_properties["$process_person_profile"] = False
self._client.capture(
distinct_id=self._distinct_id or trace_id,
event="$ai_generation",
properties=event_properties,
groups=self._groups,
)
def _log_debug_event(
self,
event_name: str,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs,
):
log.debug(
f"Event: {event_name}, run_id: {str(run_id)[:5]}, parent_run_id: {str(parent_run_id)[:5]}, kwargs: {kwargs}"
)
def _extract_raw_esponse(last_response):
"""Extract the response from the last response of the LLM call."""
# We return the text of the response if not empty
if last_response.text is not None and last_response.text.strip() != "":
return last_response.text.strip()
elif hasattr(last_response, "message"):
# Additional kwargs contains the response in case of tool usage
return last_response.message.additional_kwargs
else:
# Not tool usage, some LLM responses can be simply empty
return ""
def _convert_message_to_dict(message: BaseMessage) -> Dict[str, Any]:
# assistant message
if isinstance(message, HumanMessage):
message_dict = {"role": "user", "content": message.content}
elif isinstance(message, AIMessage):
message_dict = {"role": "assistant", "content": message.content}
elif isinstance(message, SystemMessage):
message_dict = {"role": "system", "content": message.content}
elif isinstance(message, ToolMessage):
message_dict = {"role": "tool", "content": message.content}
elif isinstance(message, FunctionMessage):
message_dict = {"role": "function", "content": message.content}
else:
message_dict = {"role": message.type, "content": str(message.content)}
if message.additional_kwargs:
message_dict.update(message.additional_kwargs)
return message_dict
def _parse_usage_model(
usage: Union[BaseModel, Dict],
) -> Tuple[Union[int, None], Union[int, None]]:
if isinstance(usage, BaseModel):
usage = usage.__dict__
conversion_list = [
# https://pypi.org/project/langchain-anthropic/ (works also for Bedrock-Anthropic)
("input_tokens", "input"),
("output_tokens", "output"),
# https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/get-token-count
("prompt_token_count", "input"),
("candidates_token_count", "output"),
# Bedrock: https://docs.aws.amazon.com/bedrock/latest/userguide/monitoring-cw.html#runtime-cloudwatch-metrics
("inputTokenCount", "input"),
("outputTokenCount", "output"),
# Bedrock Anthropic
("prompt_tokens", "input"),
("completion_tokens", "output"),
# langchain-ibm https://pypi.org/project/langchain-ibm/
("input_token_count", "input"),
("generated_token_count", "output"),
]
parsed_usage = {}
for model_key, type_key in conversion_list:
if model_key in usage:
captured_count = usage[model_key]
final_count = (
sum(captured_count) if isinstance(captured_count, list) else captured_count
) # For Bedrock, the token count is a list when streamed
parsed_usage[type_key] = final_count
return parsed_usage.get("input"), parsed_usage.get("output")
def _parse_usage(response: LLMResult):
# langchain-anthropic uses the usage field
llm_usage_keys = ["token_usage", "usage"]
llm_usage: Tuple[Union[int, None], Union[int, None]] = (None, None)
if response.llm_output is not None:
for key in llm_usage_keys:
if response.llm_output.get(key):
llm_usage = _parse_usage_model(response.llm_output[key])
break
if hasattr(response, "generations"):
for generation in response.generations:
if "usage" in generation:
llm_usage = _parse_usage_model(generation["usage"])
break
for generation_chunk in generation:
if generation_chunk.generation_info and ("usage_metadata" in generation_chunk.generation_info):
llm_usage = _parse_usage_model(generation_chunk.generation_info["usage_metadata"])
break
message_chunk = getattr(generation_chunk, "message", {})
response_metadata = getattr(message_chunk, "response_metadata", {})
bedrock_anthropic_usage = (
response_metadata.get("usage", None) # for Bedrock-Anthropic
if isinstance(response_metadata, dict)
else None
)
bedrock_titan_usage = (
response_metadata.get("amazon-bedrock-invocationMetrics", None) # for Bedrock-Titan
if isinstance(response_metadata, dict)
else None
)
ollama_usage = getattr(message_chunk, "usage_metadata", None) # for Ollama
chunk_usage = bedrock_anthropic_usage or bedrock_titan_usage or ollama_usage
if chunk_usage:
llm_usage = _parse_usage_model(chunk_usage)
break
return llm_usage
def _get_http_status(error: BaseException) -> int:
# OpenAI: https://github.com/openai/openai-python/blob/main/src/openai/_exceptions.py
# Anthropic: https://github.com/anthropics/anthropic-sdk-python/blob/main/src/anthropic/_exceptions.py
# Google: https://github.com/googleapis/python-api-core/blob/main/google/api_core/exceptions.py
status_code = getattr(error, "status_code", getattr(error, "code", 0))
return status_code
def _get_langchain_run_name(serialized: Optional[Dict[str, Any]], **kwargs: Any) -> Optional[str]:
"""Retrieve the name of a serialized LangChain runnable.
The prioritization for the determination of the run name is as follows:
- The value assigned to the "name" key in `kwargs`.
- The value assigned to the "name" key in `serialized`.
- The last entry of the value assigned to the "id" key in `serialized`.
- "<unknown>".
Args:
serialized (Optional[Dict[str, Any]]): A dictionary containing the runnable's serialized data.
**kwargs (Any): Additional keyword arguments, potentially including the 'name' override.
Returns:
str: The determined name of the Langchain runnable.
"""
if "name" in kwargs and kwargs["name"] is not None:
return kwargs["name"]
if serialized is None:
return None
try:
return serialized["name"]
except (KeyError, TypeError):
pass
try:
return serialized["id"][-1]
except (KeyError, TypeError):
pass
return None
def _stringify_exception(exception: BaseException) -> str:
description = str(exception)
if description:
return f"{exception.__class__.__name__}: {description}"
return exception.__class__.__name__
+5
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@@ -0,0 +1,5 @@
from .openai import OpenAI
from .openai_async import AsyncOpenAI
from .openai_providers import AsyncAzureOpenAI, AzureOpenAI
__all__ = ["OpenAI", "AsyncOpenAI", "AzureOpenAI", "AsyncAzureOpenAI"]
+494
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@@ -0,0 +1,494 @@
import time
import uuid
from typing import Any, Dict, List, Optional
try:
import openai
import openai.resources
except ImportError:
raise ModuleNotFoundError("Please install the OpenAI SDK to use this feature: 'pip install openai'")
from posthog.ai.utils import call_llm_and_track_usage, get_model_params, with_privacy_mode
from posthog.client import Client as PostHogClient
class OpenAI(openai.OpenAI):
"""
A wrapper around the OpenAI SDK that automatically sends LLM usage events to PostHog.
"""
_ph_client: PostHogClient
def __init__(self, posthog_client: PostHogClient, **kwargs):
"""
Args:
api_key: OpenAI API key.
posthog_client: If provided, events will be captured via this client instead
of the global posthog.
**openai_config: Any additional keyword args to set on openai (e.g. organization="xxx").
"""
super().__init__(**kwargs)
self._ph_client = posthog_client
self.chat = WrappedChat(self)
self.embeddings = WrappedEmbeddings(self)
self.beta = WrappedBeta(self)
self.responses = WrappedResponses(self)
class WrappedResponses(openai.resources.responses.Responses):
_client: OpenAI
def create(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
if kwargs.get("stream", False):
return self._create_streaming(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
**kwargs,
)
return call_llm_and_track_usage(
posthog_distinct_id,
self._client._ph_client,
"openai",
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
self._client.base_url,
super().create,
**kwargs,
)
def _create_streaming(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
**kwargs: Any,
):
start_time = time.time()
usage_stats: Dict[str, int] = {}
final_content = []
response = super().create(**kwargs)
def generator():
nonlocal usage_stats
nonlocal final_content
try:
for chunk in response:
if hasattr(chunk, "type") and chunk.type == "response.completed":
res = chunk.response
if res.output and len(res.output) > 0:
final_content.append(res.output[0])
if hasattr(chunk, "usage") and chunk.usage:
usage_stats = {
k: getattr(chunk.usage, k, 0)
for k in [
"input_tokens",
"output_tokens",
"total_tokens",
]
}
# Add support for cached tokens
if hasattr(chunk.usage, "output_tokens_details") and hasattr(
chunk.usage.output_tokens_details, "reasoning_tokens"
):
usage_stats["reasoning_tokens"] = chunk.usage.output_tokens_details.reasoning_tokens
if hasattr(chunk.usage, "input_tokens_details") and hasattr(
chunk.usage.input_tokens_details, "cached_tokens"
):
usage_stats["cache_read_input_tokens"] = chunk.usage.input_tokens_details.cached_tokens
yield chunk
finally:
end_time = time.time()
latency = end_time - start_time
output = final_content
self._capture_streaming_event(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
kwargs,
usage_stats,
latency,
output,
)
return generator()
def _capture_streaming_event(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
kwargs: Dict[str, Any],
usage_stats: Dict[str, int],
latency: float,
output: Any,
tool_calls: Optional[List[Dict[str, Any]]] = None,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
event_properties = {
"$ai_provider": "openai",
"$ai_model": kwargs.get("model"),
"$ai_model_parameters": get_model_params(kwargs),
"$ai_input": with_privacy_mode(self._client._ph_client, posthog_privacy_mode, kwargs.get("input")),
"$ai_output_choices": with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
output,
),
"$ai_http_status": 200,
"$ai_input_tokens": usage_stats.get("input_tokens", 0),
"$ai_output_tokens": usage_stats.get("output_tokens", 0),
"$ai_cache_read_input_tokens": usage_stats.get("cache_read_input_tokens", 0),
"$ai_reasoning_tokens": usage_stats.get("reasoning_tokens", 0),
"$ai_latency": latency,
"$ai_trace_id": posthog_trace_id,
"$ai_base_url": str(self._client.base_url),
**(posthog_properties or {}),
}
if tool_calls:
event_properties["$ai_tools"] = with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
tool_calls,
)
if posthog_distinct_id is None:
event_properties["$process_person_profile"] = False
if hasattr(self._client._ph_client, "capture"):
self._client._ph_client.capture(
distinct_id=posthog_distinct_id or posthog_trace_id,
event="$ai_generation",
properties=event_properties,
groups=posthog_groups,
)
class WrappedChat(openai.resources.chat.Chat):
_client: OpenAI
@property
def completions(self):
return WrappedCompletions(self._client)
class WrappedCompletions(openai.resources.chat.completions.Completions):
_client: OpenAI
def create(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
if kwargs.get("stream", False):
return self._create_streaming(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
**kwargs,
)
return call_llm_and_track_usage(
posthog_distinct_id,
self._client._ph_client,
"openai",
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
self._client.base_url,
super().create,
**kwargs,
)
def _create_streaming(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
**kwargs: Any,
):
start_time = time.time()
usage_stats: Dict[str, int] = {}
accumulated_content = []
accumulated_tools = {}
if "stream_options" not in kwargs:
kwargs["stream_options"] = {}
kwargs["stream_options"]["include_usage"] = True
response = super().create(**kwargs)
def generator():
nonlocal usage_stats
nonlocal accumulated_content
nonlocal accumulated_tools
try:
for chunk in response:
if hasattr(chunk, "usage") and chunk.usage:
usage_stats = {
k: getattr(chunk.usage, k, 0)
for k in [
"prompt_tokens",
"completion_tokens",
"total_tokens",
]
}
# Add support for cached tokens
if hasattr(chunk.usage, "prompt_tokens_details") and hasattr(
chunk.usage.prompt_tokens_details, "cached_tokens"
):
usage_stats["cache_read_input_tokens"] = chunk.usage.prompt_tokens_details.cached_tokens
if hasattr(chunk.usage, "output_tokens_details") and hasattr(
chunk.usage.output_tokens_details, "reasoning_tokens"
):
usage_stats["reasoning_tokens"] = chunk.usage.output_tokens_details.reasoning_tokens
if hasattr(chunk, "choices") and chunk.choices and len(chunk.choices) > 0:
if chunk.choices[0].delta and chunk.choices[0].delta.content:
content = chunk.choices[0].delta.content
if content:
accumulated_content.append(content)
# Process tool calls
tool_calls = getattr(chunk.choices[0].delta, "tool_calls", None)
if tool_calls:
for tool_call in tool_calls:
index = tool_call.index
if index not in accumulated_tools:
accumulated_tools[index] = tool_call
else:
# Append arguments for existing tool calls
if hasattr(tool_call, "function") and hasattr(tool_call.function, "arguments"):
accumulated_tools[index].function.arguments += tool_call.function.arguments
yield chunk
finally:
end_time = time.time()
latency = end_time - start_time
output = "".join(accumulated_content)
tools = list(accumulated_tools.values()) if accumulated_tools else None
self._capture_streaming_event(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
kwargs,
usage_stats,
latency,
output,
tools,
)
return generator()
def _capture_streaming_event(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
kwargs: Dict[str, Any],
usage_stats: Dict[str, int],
latency: float,
output: Any,
tool_calls: Optional[List[Dict[str, Any]]] = None,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
event_properties = {
"$ai_provider": "openai",
"$ai_model": kwargs.get("model"),
"$ai_model_parameters": get_model_params(kwargs),
"$ai_input": with_privacy_mode(self._client._ph_client, posthog_privacy_mode, kwargs.get("messages")),
"$ai_output_choices": with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
[{"content": output, "role": "assistant"}],
),
"$ai_http_status": 200,
"$ai_input_tokens": usage_stats.get("prompt_tokens", 0),
"$ai_output_tokens": usage_stats.get("completion_tokens", 0),
"$ai_cache_read_input_tokens": usage_stats.get("cache_read_input_tokens", 0),
"$ai_reasoning_tokens": usage_stats.get("reasoning_tokens", 0),
"$ai_latency": latency,
"$ai_trace_id": posthog_trace_id,
"$ai_base_url": str(self._client.base_url),
**(posthog_properties or {}),
}
if tool_calls:
event_properties["$ai_tools"] = with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
tool_calls,
)
if posthog_distinct_id is None:
event_properties["$process_person_profile"] = False
if hasattr(self._client._ph_client, "capture"):
self._client._ph_client.capture(
distinct_id=posthog_distinct_id or posthog_trace_id,
event="$ai_generation",
properties=event_properties,
groups=posthog_groups,
)
class WrappedEmbeddings(openai.resources.embeddings.Embeddings):
_client: OpenAI
def create(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
"""
Create an embedding using OpenAI's 'embeddings.create' method, but also track usage in PostHog.
Args:
posthog_distinct_id: Optional ID to associate with the usage event.
posthog_trace_id: Optional trace UUID for linking events.
posthog_properties: Optional dictionary of extra properties to include in the event.
**kwargs: Any additional parameters for the OpenAI Embeddings API.
Returns:
The response from OpenAI's embeddings.create call.
"""
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
start_time = time.time()
response = super().create(**kwargs)
end_time = time.time()
# Extract usage statistics if available
usage_stats = {}
if hasattr(response, "usage") and response.usage:
usage_stats = {
"prompt_tokens": getattr(response.usage, "prompt_tokens", 0),
"total_tokens": getattr(response.usage, "total_tokens", 0),
}
latency = end_time - start_time
# Build the event properties
event_properties = {
"$ai_provider": "openai",
"$ai_model": kwargs.get("model"),
"$ai_input": with_privacy_mode(self._client._ph_client, posthog_privacy_mode, kwargs.get("input")),
"$ai_http_status": 200,
"$ai_input_tokens": usage_stats.get("prompt_tokens", 0),
"$ai_latency": latency,
"$ai_trace_id": posthog_trace_id,
"$ai_base_url": str(self._client.base_url),
**(posthog_properties or {}),
}
if posthog_distinct_id is None:
event_properties["$process_person_profile"] = False
# Send capture event for embeddings
if hasattr(self._client._ph_client, "capture"):
self._client._ph_client.capture(
distinct_id=posthog_distinct_id or posthog_trace_id,
event="$ai_embedding",
properties=event_properties,
groups=posthog_groups,
)
return response
class WrappedBeta(openai.resources.beta.Beta):
_client: OpenAI
@property
def chat(self):
return WrappedBetaChat(self._client)
class WrappedBetaChat(openai.resources.beta.chat.Chat):
_client: OpenAI
@property
def completions(self):
return WrappedBetaCompletions(self._client)
class WrappedBetaCompletions(openai.resources.beta.chat.completions.Completions):
_client: OpenAI
def parse(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
return call_llm_and_track_usage(
posthog_distinct_id,
self._client._ph_client,
"openai",
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
self._client.base_url,
super().parse,
**kwargs,
)
+488
View File
@@ -0,0 +1,488 @@
import time
import uuid
from typing import Any, Dict, List, Optional
try:
import openai
import openai.resources
except ImportError:
raise ModuleNotFoundError("Please install the OpenAI SDK to use this feature: 'pip install openai'")
from posthog.ai.utils import call_llm_and_track_usage_async, get_model_params, with_privacy_mode
from posthog.client import Client as PostHogClient
class AsyncOpenAI(openai.AsyncOpenAI):
"""
An async wrapper around the OpenAI SDK that automatically sends LLM usage events to PostHog.
"""
_ph_client: PostHogClient
def __init__(self, posthog_client: PostHogClient, **kwargs):
"""
Args:
api_key: OpenAI API key.
posthog_client: If provided, events will be captured via this client instance.
**openai_config: Additional keyword args (e.g. organization="xxx").
"""
super().__init__(**kwargs)
self._ph_client = posthog_client
self.chat = WrappedChat(self)
self.embeddings = WrappedEmbeddings(self)
self.beta = WrappedBeta(self)
self.responses = WrappedResponses(self)
class WrappedResponses(openai.resources.responses.Responses):
_client: AsyncOpenAI
async def create(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
if kwargs.get("stream", False):
return await self._create_streaming(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
**kwargs,
)
return await call_llm_and_track_usage_async(
posthog_distinct_id,
self._client._ph_client,
"openai",
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
self._client.base_url,
super().create,
**kwargs,
)
async def _create_streaming(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
**kwargs: Any,
):
start_time = time.time()
usage_stats: Dict[str, int] = {}
final_content = []
response = await super().create(**kwargs)
async def async_generator():
nonlocal usage_stats
nonlocal final_content
try:
async for chunk in response:
if hasattr(chunk, "type") and chunk.type == "response.completed":
res = chunk.response
if res.output and len(res.output) > 0:
final_content.append(res.output[0])
if hasattr(chunk, "usage") and chunk.usage:
usage_stats = {
k: getattr(chunk.usage, k, 0)
for k in [
"input_tokens",
"output_tokens",
"total_tokens",
]
}
# Add support for cached tokens
if hasattr(chunk.usage, "output_tokens_details") and hasattr(
chunk.usage.output_tokens_details, "reasoning_tokens"
):
usage_stats["reasoning_tokens"] = chunk.usage.output_tokens_details.reasoning_tokens
if hasattr(chunk.usage, "input_tokens_details") and hasattr(
chunk.usage.input_tokens_details, "cached_tokens"
):
usage_stats["cache_read_input_tokens"] = chunk.usage.input_tokens_details.cached_tokens
yield chunk
finally:
end_time = time.time()
latency = end_time - start_time
output = final_content
await self._capture_streaming_event(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
kwargs,
usage_stats,
latency,
output,
)
return async_generator()
async def _capture_streaming_event(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
kwargs: Dict[str, Any],
usage_stats: Dict[str, int],
latency: float,
output: Any,
tool_calls: Optional[List[Dict[str, Any]]] = None,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
event_properties = {
"$ai_provider": "openai",
"$ai_model": kwargs.get("model"),
"$ai_model_parameters": get_model_params(kwargs),
"$ai_input": with_privacy_mode(self._client._ph_client, posthog_privacy_mode, kwargs.get("input")),
"$ai_output_choices": with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
output,
),
"$ai_http_status": 200,
"$ai_input_tokens": usage_stats.get("input_tokens", 0),
"$ai_output_tokens": usage_stats.get("output_tokens", 0),
"$ai_cache_read_input_tokens": usage_stats.get("cache_read_input_tokens", 0),
"$ai_reasoning_tokens": usage_stats.get("reasoning_tokens", 0),
"$ai_latency": latency,
"$ai_trace_id": posthog_trace_id,
"$ai_base_url": str(self._client.base_url),
**(posthog_properties or {}),
}
if tool_calls:
event_properties["$ai_tools"] = with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
tool_calls,
)
if posthog_distinct_id is None:
event_properties["$process_person_profile"] = False
if hasattr(self._client._ph_client, "capture"):
await self._client._ph_client.capture(
distinct_id=posthog_distinct_id or posthog_trace_id,
event="$ai_generation",
properties=event_properties,
groups=posthog_groups,
)
class WrappedChat(openai.resources.chat.AsyncChat):
_client: AsyncOpenAI
@property
def completions(self):
return WrappedCompletions(self._client)
class WrappedCompletions(openai.resources.chat.completions.AsyncCompletions):
_client: AsyncOpenAI
async def create(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
# If streaming, handle streaming specifically
if kwargs.get("stream", False):
return await self._create_streaming(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
**kwargs,
)
response = await call_llm_and_track_usage_async(
posthog_distinct_id,
self._client._ph_client,
"openai",
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
self._client.base_url,
super().create,
**kwargs,
)
return response
async def _create_streaming(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
start_time = time.time()
usage_stats: Dict[str, int] = {}
accumulated_content = []
accumulated_tools = {}
if "stream_options" not in kwargs:
kwargs["stream_options"] = {}
kwargs["stream_options"]["include_usage"] = True
response = await super().create(**kwargs)
async def async_generator():
nonlocal usage_stats, accumulated_content, accumulated_tools
try:
async for chunk in response:
if hasattr(chunk, "usage") and chunk.usage:
usage_stats = {
k: getattr(chunk.usage, k, 0)
for k in [
"prompt_tokens",
"completion_tokens",
"total_tokens",
]
}
# Add support for cached tokens
if hasattr(chunk.usage, "prompt_tokens_details") and hasattr(
chunk.usage.prompt_tokens_details, "cached_tokens"
):
usage_stats["cache_read_input_tokens"] = chunk.usage.prompt_tokens_details.cached_tokens
if hasattr(chunk, "choices") and chunk.choices and len(chunk.choices) > 0:
if chunk.choices[0].delta and chunk.choices[0].delta.content:
content = chunk.choices[0].delta.content
if content:
accumulated_content.append(content)
# Process tool calls
tool_calls = getattr(chunk.choices[0].delta, "tool_calls", None)
if tool_calls:
for tool_call in tool_calls:
index = tool_call.index
if index not in accumulated_tools:
accumulated_tools[index] = tool_call
else:
# Append arguments for existing tool calls
if hasattr(tool_call, "function") and hasattr(tool_call.function, "arguments"):
accumulated_tools[index].function.arguments += tool_call.function.arguments
yield chunk
finally:
end_time = time.time()
latency = end_time - start_time
output = "".join(accumulated_content)
tools = list(accumulated_tools.values()) if accumulated_tools else None
await self._capture_streaming_event(
posthog_distinct_id,
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
kwargs,
usage_stats,
latency,
output,
tools,
)
return async_generator()
async def _capture_streaming_event(
self,
posthog_distinct_id: Optional[str],
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
kwargs: Dict[str, Any],
usage_stats: Dict[str, int],
latency: float,
output: Any,
tool_calls: Optional[List[Dict[str, Any]]] = None,
):
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
event_properties = {
"$ai_provider": "openai",
"$ai_model": kwargs.get("model"),
"$ai_model_parameters": get_model_params(kwargs),
"$ai_input": with_privacy_mode(self._client._ph_client, posthog_privacy_mode, kwargs.get("messages")),
"$ai_output_choices": with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
[{"content": output, "role": "assistant"}],
),
"$ai_http_status": 200,
"$ai_input_tokens": usage_stats.get("prompt_tokens", 0),
"$ai_output_tokens": usage_stats.get("completion_tokens", 0),
"$ai_cache_read_input_tokens": usage_stats.get("cache_read_input_tokens", 0),
"$ai_latency": latency,
"$ai_trace_id": posthog_trace_id,
"$ai_base_url": str(self._client.base_url),
**(posthog_properties or {}),
}
if tool_calls:
event_properties["$ai_tools"] = with_privacy_mode(
self._client._ph_client,
posthog_privacy_mode,
tool_calls,
)
if posthog_distinct_id is None:
event_properties["$process_person_profile"] = False
if hasattr(self._client._ph_client, "capture"):
await self._client._ph_client.capture(
distinct_id=posthog_distinct_id or posthog_trace_id,
event="$ai_generation",
properties=event_properties,
groups=posthog_groups,
)
class WrappedEmbeddings(openai.resources.embeddings.AsyncEmbeddings):
_client: AsyncOpenAI
async def create(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
"""
Create an embedding using OpenAI's 'embeddings.create' method, but also track usage in PostHog.
Args:
posthog_distinct_id: Optional ID to associate with the usage event.
posthog_trace_id: Optional trace UUID for linking events.
posthog_properties: Optional dictionary of extra properties to include in the event.
posthog_privacy_mode: Whether to store input and output in PostHog.
posthog_groups: Optional dictionary of groups to include in the event.
**kwargs: Any additional parameters for the OpenAI Embeddings API.
Returns:
The response from OpenAI's embeddings.create call.
"""
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
start_time = time.time()
response = await super().create(**kwargs)
end_time = time.time()
# Extract usage statistics if available
usage_stats = {}
if hasattr(response, "usage") and response.usage:
usage_stats = {
"prompt_tokens": getattr(response.usage, "prompt_tokens", 0),
"total_tokens": getattr(response.usage, "total_tokens", 0),
}
latency = end_time - start_time
# Build the event properties
event_properties = {
"$ai_provider": "openai",
"$ai_model": kwargs.get("model"),
"$ai_input": with_privacy_mode(self._client._ph_client, posthog_privacy_mode, kwargs.get("input")),
"$ai_http_status": 200,
"$ai_input_tokens": usage_stats.get("prompt_tokens", 0),
"$ai_latency": latency,
"$ai_trace_id": posthog_trace_id,
"$ai_base_url": str(self._client.base_url),
**(posthog_properties or {}),
}
if posthog_distinct_id is None:
event_properties["$process_person_profile"] = False
# Send capture event for embeddings
if hasattr(self._client._ph_client, "capture"):
self._client._ph_client.capture(
distinct_id=posthog_distinct_id or posthog_trace_id,
event="$ai_embedding",
properties=event_properties,
groups=posthog_groups,
)
return response
class WrappedBeta(openai.resources.beta.AsyncBeta):
_client: AsyncOpenAI
@property
def chat(self):
return WrappedBetaChat(self._client)
class WrappedBetaChat(openai.resources.beta.chat.AsyncChat):
_client: AsyncOpenAI
@property
def completions(self):
return WrappedBetaCompletions(self._client)
class WrappedBetaCompletions(openai.resources.beta.chat.completions.AsyncCompletions):
_client: AsyncOpenAI
async def parse(
self,
posthog_distinct_id: Optional[str] = None,
posthog_trace_id: Optional[str] = None,
posthog_properties: Optional[Dict[str, Any]] = None,
posthog_privacy_mode: bool = False,
posthog_groups: Optional[Dict[str, Any]] = None,
**kwargs: Any,
):
return await call_llm_and_track_usage_async(
posthog_distinct_id,
self._client._ph_client,
"openai",
posthog_trace_id,
posthog_properties,
posthog_privacy_mode,
posthog_groups,
self._client.base_url,
super().parse,
**kwargs,
)
+41
View File
@@ -0,0 +1,41 @@
try:
import openai
import openai.resources
except ImportError:
raise ModuleNotFoundError("Please install the Open AI SDK to use this feature: 'pip install openai'")
from posthog.ai.openai.openai import WrappedBeta, WrappedChat, WrappedEmbeddings
from posthog.ai.openai.openai_async import WrappedBeta as AsyncWrappedBeta
from posthog.ai.openai.openai_async import WrappedChat as AsyncWrappedChat
from posthog.ai.openai.openai_async import WrappedEmbeddings as AsyncWrappedEmbeddings
from posthog.client import Client as PostHogClient
class AzureOpenAI(openai.AzureOpenAI):
"""
A wrapper around the Azure OpenAI SDK that automatically sends LLM usage events to PostHog.
"""
_ph_client: PostHogClient
def __init__(self, posthog_client: PostHogClient, **kwargs):
super().__init__(**kwargs)
self._ph_client = posthog_client
self.chat = WrappedChat(self)
self.embeddings = WrappedEmbeddings(self)
self.beta = WrappedBeta(self)
class AsyncAzureOpenAI(openai.AsyncAzureOpenAI):
"""
A wrapper around the Azure OpenAI SDK that automatically sends LLM usage events to PostHog.
"""
_ph_client: PostHogClient
def __init__(self, posthog_client: PostHogClient, **kwargs):
super().__init__(**kwargs)
self._ph_client = posthog_client
self.chat = AsyncWrappedChat(self)
self.embeddings = AsyncWrappedEmbeddings(self)
self.beta = AsyncWrappedBeta(self)
+429
View File
@@ -0,0 +1,429 @@
import time
import uuid
from typing import Any, Callable, Dict, List, Optional
from httpx import URL
from posthog.client import Client as PostHogClient
def get_model_params(kwargs: Dict[str, Any]) -> Dict[str, Any]:
"""
Extracts model parameters from the kwargs dictionary.
"""
model_params = {}
for param in [
"temperature",
"max_tokens", # Deprecated field
"max_completion_tokens",
"top_p",
"frequency_penalty",
"presence_penalty",
"n",
"stop",
"stream", # OpenAI-specific field
"streaming", # Anthropic-specific field
]:
if param in kwargs and kwargs[param] is not None:
model_params[param] = kwargs[param]
return model_params
def get_usage(response, provider: str) -> Dict[str, Any]:
if provider == "anthropic":
return {
"input_tokens": response.usage.input_tokens,
"output_tokens": response.usage.output_tokens,
"cache_read_input_tokens": response.usage.cache_read_input_tokens,
"cache_creation_input_tokens": response.usage.cache_creation_input_tokens,
}
elif provider == "openai":
cached_tokens = 0
input_tokens = 0
output_tokens = 0
reasoning_tokens = 0
# responses api
if hasattr(response.usage, "input_tokens"):
input_tokens = response.usage.input_tokens
if hasattr(response.usage, "output_tokens"):
output_tokens = response.usage.output_tokens
if hasattr(response.usage, "input_tokens_details") and hasattr(
response.usage.input_tokens_details, "cached_tokens"
):
cached_tokens = response.usage.input_tokens_details.cached_tokens
if hasattr(response.usage, "output_tokens_details") and hasattr(
response.usage.output_tokens_details, "reasoning_tokens"
):
reasoning_tokens = response.usage.output_tokens_details.reasoning_tokens
# chat completions
if hasattr(response.usage, "prompt_tokens"):
input_tokens = response.usage.prompt_tokens
if hasattr(response.usage, "completion_tokens"):
output_tokens = response.usage.completion_tokens
if hasattr(response.usage, "prompt_tokens_details") and hasattr(
response.usage.prompt_tokens_details, "cached_tokens"
):
cached_tokens = response.usage.prompt_tokens_details.cached_tokens
return {
"input_tokens": input_tokens,
"output_tokens": output_tokens,
"cache_read_input_tokens": cached_tokens,
"reasoning_tokens": reasoning_tokens,
}
return {
"input_tokens": 0,
"output_tokens": 0,
"cache_read_input_tokens": 0,
"cache_creation_input_tokens": 0,
"reasoning_tokens": 0,
}
def format_response(response, provider: str):
"""
Format a regular (non-streaming) response.
"""
output = []
if response is None:
return output
if provider == "anthropic":
return format_response_anthropic(response)
elif provider == "openai":
return format_response_openai(response)
return output
def format_response_anthropic(response):
output = []
for choice in response.content:
if choice.text:
output.append(
{
"role": "assistant",
"content": choice.text,
}
)
return output
def format_response_openai(response):
output = []
if hasattr(response, "choices"):
for choice in response.choices:
# Handle Chat Completions response format
if hasattr(choice, "message") and choice.message and choice.message.content:
output.append(
{
"content": choice.message.content,
"role": choice.message.role,
}
)
# Handle Responses API format
if hasattr(response, "output"):
for item in response.output:
if item.type == "message":
# Extract text content from the content list
if hasattr(item, "content") and isinstance(item.content, list):
for content_item in item.content:
if (
hasattr(content_item, "type")
and content_item.type == "output_text"
and hasattr(content_item, "text")
):
output.append(
{
"content": content_item.text,
"role": item.role,
}
)
elif hasattr(content_item, "text"):
output.append(
{
"content": content_item.text,
"role": item.role,
}
)
elif (
hasattr(content_item, "type")
and content_item.type == "input_image"
and hasattr(content_item, "image_url")
):
output.append(
{
"content": {
"type": "image",
"image": content_item.image_url,
},
"role": item.role,
}
)
else:
output.append(
{
"content": item.content,
"role": item.role,
}
)
return output
def format_tool_calls(response, provider: str):
if provider == "anthropic":
if hasattr(response, "tools") and response.tools and len(response.tools) > 0:
return response.tools
elif provider == "openai":
# Handle both Chat Completions and Responses API
if hasattr(response, "choices") and response.choices:
# Check for tool_calls in message (Chat Completions format)
if (
hasattr(response.choices[0], "message")
and hasattr(response.choices[0].message, "tool_calls")
and response.choices[0].message.tool_calls
):
return response.choices[0].message.tool_calls
# Check for tool_calls directly in response (Responses API format)
if hasattr(response.choices[0], "tool_calls") and response.choices[0].tool_calls:
return response.choices[0].tool_calls
return None
def merge_system_prompt(kwargs: Dict[str, Any], provider: str):
messages: List[Dict[str, Any]] = []
if provider == "anthropic":
messages = kwargs.get("messages") or []
if kwargs.get("system") is None:
return messages
return [{"role": "system", "content": kwargs.get("system")}] + messages
# For OpenAI, handle both Chat Completions and Responses API
if kwargs.get("messages") is not None:
messages = list(kwargs.get("messages", []))
if kwargs.get("input") is not None:
input_data = kwargs.get("input")
if isinstance(input_data, list):
messages.extend(input_data)
else:
messages.append({"role": "user", "content": input_data})
# Check if system prompt is provided as a separate parameter
if kwargs.get("system") is not None:
has_system = any(msg.get("role") == "system" for msg in messages)
if not has_system:
messages = [{"role": "system", "content": kwargs.get("system")}] + messages
# For Responses API, add instructions to the system prompt if provided
if kwargs.get("instructions") is not None:
# Find the system message if it exists
system_idx = next((i for i, msg in enumerate(messages) if msg.get("role") == "system"), None)
if system_idx is not None:
# Append instructions to existing system message
system_content = messages[system_idx].get("content", "")
messages[system_idx]["content"] = f"{system_content}\n\n{kwargs.get('instructions')}"
else:
# Create a new system message with instructions
messages = [{"role": "system", "content": kwargs.get("instructions")}] + messages
return messages
def call_llm_and_track_usage(
posthog_distinct_id: Optional[str],
ph_client: PostHogClient,
provider: str,
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
base_url: URL,
call_method: Callable[..., Any],
**kwargs: Any,
) -> Any:
"""
Common usage-tracking logic for both sync and async calls.
call_method: the llm call method (e.g. openai.chat.completions.create)
"""
start_time = time.time()
response = None
error = None
http_status = 200
usage: Dict[str, Any] = {}
error_params: Dict[str, any] = {}
try:
response = call_method(**kwargs)
except Exception as exc:
error = exc
http_status = getattr(exc, "status_code", 0) # default to 0 becuase its likely an SDK error
error_params = {
"$ai_is_error": True,
"$ai_error": exc.__str__(),
}
finally:
end_time = time.time()
latency = end_time - start_time
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
if response and hasattr(response, "usage"):
usage = get_usage(response, provider)
messages = merge_system_prompt(kwargs, provider)
event_properties = {
"$ai_provider": provider,
"$ai_model": kwargs.get("model"),
"$ai_model_parameters": get_model_params(kwargs),
"$ai_input": with_privacy_mode(ph_client, posthog_privacy_mode, messages),
"$ai_output_choices": with_privacy_mode(
ph_client, posthog_privacy_mode, format_response(response, provider)
),
"$ai_http_status": http_status,
"$ai_input_tokens": usage.get("input_tokens", 0),
"$ai_output_tokens": usage.get("output_tokens", 0),
"$ai_latency": latency,
"$ai_trace_id": posthog_trace_id,
"$ai_base_url": str(base_url),
**(posthog_properties or {}),
**(error_params or {}),
}
tool_calls = format_tool_calls(response, provider)
if tool_calls:
event_properties["$ai_tools"] = with_privacy_mode(ph_client, posthog_privacy_mode, tool_calls)
if usage.get("cache_read_input_tokens") is not None and usage.get("cache_read_input_tokens", 0) > 0:
event_properties["$ai_cache_read_input_tokens"] = usage.get("cache_read_input_tokens", 0)
if usage.get("cache_creation_input_tokens") is not None and usage.get("cache_creation_input_tokens", 0) > 0:
event_properties["$ai_cache_creation_input_tokens"] = usage.get("cache_creation_input_tokens", 0)
if usage.get("reasoning_tokens") is not None and usage.get("reasoning_tokens", 0) > 0:
event_properties["$ai_reasoning_tokens"] = usage.get("reasoning_tokens", 0)
if posthog_distinct_id is None:
event_properties["$process_person_profile"] = False
# Process instructions for Responses API
if provider == "openai" and kwargs.get("instructions") is not None:
event_properties["$ai_instructions"] = with_privacy_mode(
ph_client, posthog_privacy_mode, kwargs.get("instructions")
)
# send the event to posthog
if hasattr(ph_client, "capture") and callable(ph_client.capture):
ph_client.capture(
distinct_id=posthog_distinct_id or posthog_trace_id,
event="$ai_generation",
properties=event_properties,
groups=posthog_groups,
)
if error:
raise error
return response
async def call_llm_and_track_usage_async(
posthog_distinct_id: Optional[str],
ph_client: PostHogClient,
provider: str,
posthog_trace_id: Optional[str],
posthog_properties: Optional[Dict[str, Any]],
posthog_privacy_mode: bool,
posthog_groups: Optional[Dict[str, Any]],
base_url: URL,
call_async_method: Callable[..., Any],
**kwargs: Any,
) -> Any:
start_time = time.time()
response = None
error = None
http_status = 200
usage: Dict[str, Any] = {}
error_params: Dict[str, any] = {}
try:
response = await call_async_method(**kwargs)
except Exception as exc:
error = exc
http_status = getattr(exc, "status_code", 0) # default to 0 because its likely an SDK error
error_params = {
"$ai_is_error": True,
"$ai_error": exc.__str__(),
}
finally:
end_time = time.time()
latency = end_time - start_time
if posthog_trace_id is None:
posthog_trace_id = str(uuid.uuid4())
if response and hasattr(response, "usage"):
usage = get_usage(response, provider)
messages = merge_system_prompt(kwargs, provider)
event_properties = {
"$ai_provider": provider,
"$ai_model": kwargs.get("model"),
"$ai_model_parameters": get_model_params(kwargs),
"$ai_input": with_privacy_mode(ph_client, posthog_privacy_mode, messages),
"$ai_output_choices": with_privacy_mode(
ph_client, posthog_privacy_mode, format_response(response, provider)
),
"$ai_http_status": http_status,
"$ai_input_tokens": usage.get("input_tokens", 0),
"$ai_output_tokens": usage.get("output_tokens", 0),
"$ai_latency": latency,
"$ai_trace_id": posthog_trace_id,
"$ai_base_url": str(base_url),
**(posthog_properties or {}),
**(error_params or {}),
}
tool_calls = format_tool_calls(response, provider)
if tool_calls:
event_properties["$ai_tools"] = with_privacy_mode(ph_client, posthog_privacy_mode, tool_calls)
if usage.get("cache_read_input_tokens") is not None and usage.get("cache_read_input_tokens", 0) > 0:
event_properties["$ai_cache_read_input_tokens"] = usage.get("cache_read_input_tokens", 0)
if usage.get("cache_creation_input_tokens") is not None and usage.get("cache_creation_input_tokens", 0) > 0:
event_properties["$ai_cache_creation_input_tokens"] = usage.get("cache_creation_input_tokens", 0)
if posthog_distinct_id is None:
event_properties["$process_person_profile"] = False
# Process instructions for Responses API
if provider == "openai" and kwargs.get("instructions") is not None:
event_properties["$ai_instructions"] = with_privacy_mode(
ph_client, posthog_privacy_mode, kwargs.get("instructions")
)
# send the event to posthog
if hasattr(ph_client, "capture") and callable(ph_client.capture):
ph_client.capture(
distinct_id=posthog_distinct_id or posthog_trace_id,
event="$ai_generation",
properties=event_properties,
groups=posthog_groups,
)
if error:
raise error
return response
def with_privacy_mode(ph_client: PostHogClient, privacy_mode: bool, value: Any):
if ph_client.privacy_mode or privacy_mode:
return None
return value
+309 -37
View File
@@ -1,17 +1,25 @@
import atexit
import logging
import numbers
import os
import platform
import sys
import warnings
from datetime import datetime, timedelta
from uuid import UUID
from typing import Any
from uuid import UUID, uuid4
import distro # For Linux OS detection
from dateutil.tz import tzutc
from six import string_types
from posthog.consumer import Consumer
from posthog.exception_capture import ExceptionCapture
from posthog.exception_utils import exc_info_from_error, exceptions_from_error_tuple, handle_in_app
from posthog.feature_flags import InconclusiveMatchError, match_feature_flag_properties
from posthog.poller import Poller
from posthog.request import APIError, batch_post, decide, determine_server_host, get
from posthog.utils import SizeLimitedDict, clean, guess_timezone
from posthog.request import DEFAULT_HOST, APIError, batch_post, decide, determine_server_host, get, remote_config
from posthog.utils import SizeLimitedDict, clean, guess_timezone, remove_trailing_slash
from posthog.version import VERSION
try:
@@ -24,6 +32,60 @@ ID_TYPES = (numbers.Number, string_types, UUID)
MAX_DICT_SIZE = 50_000
def get_os_info():
"""
Returns standardized OS name and version information.
Similar to how user agent parsing works in JS.
"""
os_name = ""
os_version = ""
platform_name = sys.platform
if platform_name.startswith("win"):
os_name = "Windows"
if hasattr(platform, "win32_ver"):
win_version = platform.win32_ver()[0]
if win_version:
os_version = win_version
elif platform_name == "darwin":
os_name = "Mac OS X"
if hasattr(platform, "mac_ver"):
mac_version = platform.mac_ver()[0]
if mac_version:
os_version = mac_version
elif platform_name.startswith("linux"):
os_name = "Linux"
linux_info = distro.info()
if linux_info["version"]:
os_version = linux_info["version"]
elif platform_name.startswith("freebsd"):
os_name = "FreeBSD"
if hasattr(platform, "release"):
os_version = platform.release()
else:
os_name = platform_name
if hasattr(platform, "release"):
os_version = platform.release()
return os_name, os_version
def system_context() -> dict[str, Any]:
os_name, os_version = get_os_info()
return {
"$python_runtime": platform.python_implementation(),
"$python_version": "%s.%s.%s" % (sys.version_info[:3]),
"$os": os_name,
"$os_version": os_version,
}
class Client(object):
"""Create a new PostHog client."""
@@ -51,6 +113,11 @@ class Client(object):
disable_geoip=True,
historical_migration=False,
feature_flags_request_timeout_seconds=3,
super_properties=None,
enable_exception_autocapture=False,
exception_autocapture_integrations=None,
project_root=None,
privacy_mode=False,
):
self.queue = queue.Queue(max_queue_size)
@@ -63,6 +130,8 @@ class Client(object):
self.debug = debug
self.send = send
self.sync_mode = sync_mode
# Used for session replay URL generation - we don't want the server host here.
self.raw_host = host or DEFAULT_HOST
self.host = determine_server_host(host)
self.gzip = gzip
self.timeout = timeout
@@ -77,6 +146,19 @@ class Client(object):
self.disabled = disabled
self.disable_geoip = disable_geoip
self.historical_migration = historical_migration
self.super_properties = super_properties
self.enable_exception_autocapture = enable_exception_autocapture
self.exception_autocapture_integrations = exception_autocapture_integrations
self.exception_capture = None
self.privacy_mode = privacy_mode
if project_root is None:
try:
project_root = os.getcwd()
except Exception:
project_root = None
self.project_root = project_root
# personal_api_key: This should be a generated Personal API Key, private
self.personal_api_key = personal_api_key
@@ -88,6 +170,9 @@ class Client(object):
else:
self.log.setLevel(logging.WARNING)
if self.enable_exception_autocapture:
self.exception_capture = ExceptionCapture(self, integrations=self.exception_autocapture_integrations)
if sync_mode:
self.consumers = None
else:
@@ -120,14 +205,19 @@ class Client(object):
consumer.start()
def identify(self, distinct_id=None, properties=None, context=None, timestamp=None, uuid=None, disable_geoip=None):
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
properties = properties or {}
context = context or {}
require("distinct_id", distinct_id, ID_TYPES)
require("properties", properties, dict)
msg = {
"timestamp": timestamp,
"context": context,
"distinct_id": distinct_id,
"$set": properties,
"event": "$identify",
@@ -148,6 +238,15 @@ class Client(object):
resp_data = self.get_decide(distinct_id, groups, person_properties, group_properties, disable_geoip)
return resp_data["featureFlagPayloads"]
def get_feature_flags_and_payloads(
self, distinct_id, groups=None, person_properties=None, group_properties=None, disable_geoip=None
):
resp_data = self.get_decide(distinct_id, groups, person_properties, group_properties, disable_geoip)
return {
"featureFlags": resp_data["featureFlags"],
"featureFlagPayloads": resp_data["featureFlagPayloads"],
}
def get_decide(self, distinct_id, groups=None, person_properties=None, group_properties=None, disable_geoip=None):
require("distinct_id", distinct_id, ID_TYPES)
@@ -182,8 +281,15 @@ class Client(object):
send_feature_flags=False,
disable_geoip=None,
):
properties = properties or {}
context = context or {}
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
properties = {**(properties or {}), **system_context()}
require("distinct_id", distinct_id, ID_TYPES)
require("properties", properties, dict)
require("event", event, string_types)
@@ -191,7 +297,6 @@ class Client(object):
msg = {
"properties": properties,
"timestamp": timestamp,
"context": context,
"distinct_id": distinct_id,
"event": event,
"uuid": uuid,
@@ -209,7 +314,7 @@ class Client(object):
except Exception as e:
self.log.exception(f"[FEATURE FLAGS] Unable to get feature variants: {e}")
elif self.feature_flags:
elif self.feature_flags and event != "$feature_flag_called":
# Local evaluation is enabled, flags are loaded, so try and get all flags we can without going to the server
feature_variants = self.get_all_flags(
distinct_id, groups=(groups or {}), disable_geoip=disable_geoip, only_evaluate_locally=True
@@ -228,14 +333,19 @@ class Client(object):
return self._enqueue(msg, disable_geoip)
def set(self, distinct_id=None, properties=None, context=None, timestamp=None, uuid=None, disable_geoip=None):
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
properties = properties or {}
context = context or {}
require("distinct_id", distinct_id, ID_TYPES)
require("properties", properties, dict)
msg = {
"timestamp": timestamp,
"context": context,
"distinct_id": distinct_id,
"$set": properties,
"event": "$set",
@@ -245,14 +355,19 @@ class Client(object):
return self._enqueue(msg, disable_geoip)
def set_once(self, distinct_id=None, properties=None, context=None, timestamp=None, uuid=None, disable_geoip=None):
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
properties = properties or {}
context = context or {}
require("distinct_id", distinct_id, ID_TYPES)
require("properties", properties, dict)
msg = {
"timestamp": timestamp,
"context": context,
"distinct_id": distinct_id,
"$set_once": properties,
"event": "$set_once",
@@ -270,13 +385,24 @@ class Client(object):
timestamp=None,
uuid=None,
disable_geoip=None,
distinct_id=None,
):
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
properties = properties or {}
context = context or {}
require("group_type", group_type, ID_TYPES)
require("group_key", group_key, ID_TYPES)
require("properties", properties, dict)
if distinct_id:
require("distinct_id", distinct_id, ID_TYPES)
else:
distinct_id = "${}_{}".format(group_type, group_key)
msg = {
"event": "$groupidentify",
"properties": {
@@ -284,16 +410,20 @@ class Client(object):
"$group_key": group_key,
"$group_set": properties,
},
"distinct_id": "${}_{}".format(group_type, group_key),
"distinct_id": distinct_id,
"timestamp": timestamp,
"context": context,
"uuid": uuid,
}
return self._enqueue(msg, disable_geoip)
def alias(self, previous_id=None, distinct_id=None, context=None, timestamp=None, uuid=None, disable_geoip=None):
context = context or {}
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
require("previous_id", previous_id, ID_TYPES)
require("distinct_id", distinct_id, ID_TYPES)
@@ -304,7 +434,6 @@ class Client(object):
"alias": distinct_id,
},
"timestamp": timestamp,
"context": context,
"event": "$create_alias",
"distinct_id": previous_id,
}
@@ -314,9 +443,14 @@ class Client(object):
def page(
self, distinct_id=None, url=None, properties=None, context=None, timestamp=None, uuid=None, disable_geoip=None
):
properties = properties or {}
context = context or {}
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
properties = properties or {}
require("distinct_id", distinct_id, ID_TYPES)
require("properties", properties, dict)
@@ -327,13 +461,78 @@ class Client(object):
"event": "$pageview",
"properties": properties,
"timestamp": timestamp,
"context": context,
"distinct_id": distinct_id,
"uuid": uuid,
}
return self._enqueue(msg, disable_geoip)
def capture_exception(
self,
exception=None,
distinct_id=None,
properties=None,
context=None,
timestamp=None,
uuid=None,
groups=None,
):
if context is not None:
warnings.warn(
"The 'context' parameter is deprecated and will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
# this function shouldn't ever throw an error, so it logs exceptions instead of raising them.
# this is important to ensure we don't unexpectedly re-raise exceptions in the user's code.
try:
properties = properties or {}
# if there's no distinct_id, we'll generate one and set personless mode
# via $process_person_profile = false
if distinct_id is None:
properties["$process_person_profile"] = False
distinct_id = uuid4()
require("distinct_id", distinct_id, ID_TYPES)
require("properties", properties, dict)
if exception is not None:
exc_info = exc_info_from_error(exception)
else:
exc_info = sys.exc_info()
if exc_info is None or exc_info == (None, None, None):
self.log.warning("No exception information available")
return
# Format stack trace for cymbal
all_exceptions_with_trace = exceptions_from_error_tuple(exc_info)
# Add in-app property to frames in the exceptions
event = handle_in_app(
{
"exception": {
"values": all_exceptions_with_trace,
},
},
project_root=self.project_root,
)
all_exceptions_with_trace_and_in_app = event["exception"]["values"]
properties = {
"$exception_type": all_exceptions_with_trace_and_in_app[0].get("type"),
"$exception_message": all_exceptions_with_trace_and_in_app[0].get("value"),
"$exception_list": all_exceptions_with_trace_and_in_app,
"$exception_personURL": f"{remove_trailing_slash(self.raw_host)}/project/{self.api_key}/person/{distinct_id}",
**properties,
}
return self.capture(distinct_id, "$exception", properties, context, timestamp, uuid, groups)
except Exception as e:
self.log.exception(f"Failed to capture exception: {e}")
def _enqueue(self, msg, disable_geoip):
"""Push a new `msg` onto the queue, return `(success, msg)`"""
@@ -342,10 +541,9 @@ class Client(object):
timestamp = msg["timestamp"]
if timestamp is None:
timestamp = datetime.utcnow().replace(tzinfo=tzutc())
timestamp = datetime.now(tz=tzutc())
require("timestamp", timestamp, datetime)
require("context", msg["context"], dict)
# add common
timestamp = guess_timezone(timestamp)
@@ -368,6 +566,9 @@ class Client(object):
if disable_geoip:
msg["properties"]["$geoip_disable"] = True
if self.super_properties:
msg["properties"] = {**msg["properties"], **self.super_properties}
msg["distinct_id"] = stringify_id(msg.get("distinct_id", None))
msg = clean(msg)
@@ -426,6 +627,9 @@ class Client(object):
self.flush()
self.join()
if self.exception_capture:
self.exception_capture.close()
def _load_feature_flags(self):
try:
response = get(
@@ -454,6 +658,21 @@ class Client(object):
"To use feature flags, please set a personal_api_key "
"More information: https://posthog.com/docs/api/overview",
)
elif e.status == 402:
self.log.warning(
"[FEATURE FLAGS] PostHog feature flags quota limited, resetting feature flag data. Learn more about billing limits at https://posthog.com/docs/billing/limits-alerts"
)
# Reset all feature flag data when quota limited
self.feature_flags = []
self.feature_flags_by_key = {}
self.group_type_mapping = {}
self.cohorts = {}
if self.debug:
raise APIError(
status=402,
message="PostHog feature flags quota limited",
)
else:
self.log.error(f"[FEATURE FLAGS] Error loading feature flags: {e}")
except Exception as e:
@@ -463,7 +682,7 @@ class Client(object):
)
self.log.warning(e)
self._last_feature_flag_poll = datetime.utcnow().replace(tzinfo=tzutc())
self._last_feature_flag_poll = datetime.now(tz=tzutc())
def load_feature_flags(self):
if not self.personal_api_key:
@@ -576,7 +795,6 @@ class Client(object):
self.load_feature_flags()
response = None
# If loading in previous line failed
if self.feature_flags:
for flag in self.feature_flags:
if flag["key"] == key:
@@ -595,6 +813,7 @@ class Client(object):
except Exception as e:
self.log.exception(f"[FEATURE FLAGS] Error while computing variant locally: {e}")
continue
break
flag_was_locally_evaluated = response is not None
if not flag_was_locally_evaluated and not only_evaluate_locally:
@@ -656,23 +875,72 @@ class Client(object):
groups=groups,
person_properties=person_properties,
group_properties=group_properties,
send_feature_flag_events=send_feature_flag_events,
only_evaluate_locally=True,
send_feature_flag_events=False,
# Disable automatic sending of feature flag events because we're manually handling event dispatch.
# This prevents sending events with empty data when `get_feature_flag` cannot be evaluated locally.
only_evaluate_locally=True, # Enable local evaluation of feature flags to avoid making multiple requests to `/decide`.
disable_geoip=disable_geoip,
)
response = None
payload = None
if match_value is not None:
response = self._compute_payload_locally(key, match_value)
payload = self._compute_payload_locally(key, match_value)
if response is None and not only_evaluate_locally:
decide_payloads = self.get_feature_payloads(
distinct_id, groups, person_properties, group_properties, disable_geoip
flag_was_locally_evaluated = payload is not None
if not flag_was_locally_evaluated and not only_evaluate_locally:
try:
responses_and_payloads = self.get_feature_flags_and_payloads(
distinct_id, groups, person_properties, group_properties, disable_geoip
)
response = responses_and_payloads["featureFlags"].get(key, None)
payload = responses_and_payloads["featureFlagPayloads"].get(str(key), None)
except Exception as e:
self.log.exception(f"[FEATURE FLAGS] Unable to get feature flags and payloads: {e}")
feature_flag_reported_key = f"{key}_{str(response)}"
if (
feature_flag_reported_key not in self.distinct_ids_feature_flags_reported[distinct_id]
and send_feature_flag_events # noqa: W503
):
self.capture(
distinct_id,
"$feature_flag_called",
{
"$feature_flag": key,
"$feature_flag_response": response,
"$feature_flag_payload": payload,
"locally_evaluated": flag_was_locally_evaluated,
f"$feature/{key}": response,
},
groups=groups,
disable_geoip=disable_geoip,
)
response = decide_payloads.get(str(key).lower(), None)
self.distinct_ids_feature_flags_reported[distinct_id].add(feature_flag_reported_key)
return response
return payload
def get_remote_config_payload(self, key: str):
if self.disabled:
return None
if self.personal_api_key is None:
self.log.warning(
"[FEATURE FLAGS] You have to specify a personal_api_key to fetch decrypted feature flag payloads."
)
return None
try:
return remote_config(
self.personal_api_key,
self.host,
key,
timeout=self.feature_flags_request_timeout_seconds,
)
except Exception as e:
self.log.exception(f"[FEATURE FLAGS] Unable to get decrypted feature flag payload: {e}")
def _compute_payload_locally(self, key, match_value):
payload = None
@@ -680,10 +948,14 @@ class Client(object):
if self.feature_flags_by_key is None:
return payload
flag_definition = self.feature_flags_by_key.get(key) or {}
flag_filters = flag_definition.get("filters") or {}
flag_payloads = flag_filters.get("payloads") or {}
payload = flag_payloads.get(str(match_value).lower(), None)
flag_definition = self.feature_flags_by_key.get(key)
if flag_definition:
flag_filters = flag_definition.get("filters") or {}
flag_payloads = flag_filters.get("payloads") or {}
# For boolean flags, convert True to "true"
# For multivariate flags, use the variant string as-is
lookup_value = "true" if isinstance(match_value, bool) and match_value else str(match_value)
payload = flag_payloads.get(lookup_value, None)
return payload
def get_all_flags(
+64
View File
@@ -0,0 +1,64 @@
import logging
import sys
import threading
from enum import Enum
from typing import TYPE_CHECKING, List, Optional
if TYPE_CHECKING:
from posthog.client import Client
class Integrations(str, Enum):
Django = "django"
class ExceptionCapture:
# TODO: Add client side rate limiting to prevent spamming the server with exceptions
log = logging.getLogger("posthog")
def __init__(self, client: "Client", integrations: Optional[List[Integrations]] = None):
self.client = client
self.original_excepthook = sys.excepthook
sys.excepthook = self.exception_handler
threading.excepthook = self.thread_exception_handler
self.enabled_integrations = []
for integration in integrations or []:
# TODO: Maybe find a better way of enabling integrations
# This is very annoying currently if we had to add any configuration per integration
if integration == Integrations.Django:
try:
from posthog.exception_integrations.django import DjangoIntegration
enabled_integration = DjangoIntegration(self.exception_receiver)
self.enabled_integrations.append(enabled_integration)
except Exception as e:
self.log.exception(f"Failed to enable Django integration: {e}")
def close(self):
sys.excepthook = self.original_excepthook
for integration in self.enabled_integrations:
integration.uninstall()
def exception_handler(self, exc_type, exc_value, exc_traceback):
# don't affect default behaviour.
self.capture_exception((exc_type, exc_value, exc_traceback))
self.original_excepthook(exc_type, exc_value, exc_traceback)
def thread_exception_handler(self, args):
self.capture_exception((args.exc_type, args.exc_value, args.exc_traceback))
def exception_receiver(self, exc_info, extra_properties):
if "distinct_id" in extra_properties:
metadata = {"distinct_id": extra_properties["distinct_id"]}
else:
metadata = None
self.capture_exception((exc_info[0], exc_info[1], exc_info[2]), metadata)
def capture_exception(self, exception, metadata=None):
try:
distinct_id = metadata.get("distinct_id") if metadata else None
self.client.capture_exception(exception, distinct_id)
except Exception as e:
self.log.exception(f"Failed to capture exception: {e}")
@@ -0,0 +1,5 @@
class IntegrationEnablingError(Exception):
"""
The integration could not be enabled due to a user error like
`django` not being installed for the `DjangoIntegration`.
"""
+88
View File
@@ -0,0 +1,88 @@
import re
import sys
from typing import TYPE_CHECKING
from posthog.exception_integrations import IntegrationEnablingError
try:
from django import VERSION as DJANGO_VERSION
from django.core import signals
except ImportError:
raise IntegrationEnablingError("Django not installed")
if TYPE_CHECKING:
from typing import Any, Dict # noqa: F401
from django.core.handlers.wsgi import WSGIRequest # noqa: F401
class DjangoIntegration:
# TODO: Abstract integrations one we have more and can see patterns
"""
Autocapture errors from a Django application.
"""
identifier = "django"
def __init__(self, capture_exception_fn=None):
if DJANGO_VERSION < (4, 2):
raise IntegrationEnablingError("Django 4.2 or newer is required.")
# TODO: Right now this seems too complicated / overkill for us, but seems like we can automatically plug in middlewares
# which is great for users (they don't need to do this) and everything should just work.
# We should consider this in the future, but for now we can just use the middleware and signals handlers.
# See: https://github.com/getsentry/sentry-python/blob/269d96d6e9821122fbff280e6a26956e5ed03c0b/sentry_sdk/integrations/django/__init__.py
self.capture_exception_fn = capture_exception_fn
def _got_request_exception(request=None, **kwargs):
# type: (WSGIRequest, **Any) -> None
extra_props = {}
if request is not None:
# get headers metadata
extra_props = DjangoRequestExtractor(request).extract_person_data()
self.capture_exception_fn(sys.exc_info(), extra_props)
signals.got_request_exception.connect(_got_request_exception)
def uninstall(self):
pass
class DjangoRequestExtractor:
def __init__(self, request):
# type: (Any) -> None
self.request = request
def extract_person_data(self):
headers = self.headers()
# Extract traceparent and tracestate headers
traceparent = headers.get("traceparent")
tracestate = headers.get("tracestate")
# Extract the distinct_id from tracestate
distinct_id = None
if tracestate:
# TODO: Align on the format of the distinct_id in tracestate
# We can't have comma or equals in header values here, so maybe we should base64 encode it?
match = re.search(r"posthog-distinct-id=([^,]+)", tracestate)
if match:
distinct_id = match.group(1)
return {
"distinct_id": distinct_id,
"ip": headers.get("X-Forwarded-For"),
"user_agent": headers.get("User-Agent"),
"traceparent": traceparent,
}
def headers(self):
# type: () -> Dict[str, str]
return dict(self.request.headers)
+873
View File
@@ -0,0 +1,873 @@
# copied and adapted from https://github.com/getsentry/sentry-python/blob/269d96d6e9821122fbff280e6a26956e5ed03c0b/sentry_sdk/utils.py#L689
# 💖open source (under MIT License)
# We want to keep payloads as similar to Sentry as possible for easy interoperability
import linecache
import os
import re
import sys
from datetime import datetime
from typing import TYPE_CHECKING
try:
# Python 3.11
from builtins import BaseExceptionGroup
except ImportError:
# Python 3.10 and below
BaseExceptionGroup = None # type: ignore
DEFAULT_MAX_VALUE_LENGTH = 1024
if TYPE_CHECKING:
from types import FrameType, TracebackType
from typing import ( # noqa: F401
Any,
Callable,
Dict,
Iterator,
List,
Literal,
Optional,
Set,
Tuple,
Type,
TypedDict,
TypeVar,
Union,
cast,
)
ExcInfo = Union[
Tuple[Type[BaseException], BaseException, Optional[TracebackType]],
Tuple[None, None, None],
]
LogLevelStr = Literal["fatal", "critical", "error", "warning", "info", "debug"]
Event = TypedDict(
"Event",
{
"breadcrumbs": Dict[Literal["values"], List[Dict[str, Any]]], # TODO: We can expand on this type
"check_in_id": str,
"contexts": Dict[str, Dict[str, object]],
"dist": str,
"duration": Optional[float],
"environment": str,
"errors": List[Dict[str, Any]], # TODO: We can expand on this type
"event_id": str,
"exception": Dict[Literal["values"], List[Dict[str, Any]]], # TODO: We can expand on this type
# "extra": MutableMapping[str, object],
# "fingerprint": List[str],
"level": LogLevelStr,
# "logentry": Mapping[str, object],
"logger": str,
# "measurements": Dict[str, MeasurementValue],
"message": str,
"modules": Dict[str, str],
# "monitor_config": Mapping[str, object],
"monitor_slug": Optional[str],
"platform": Literal["python"],
"profile": object, # Should be sentry_sdk.profiler.Profile, but we can't import that here due to circular imports
"release": str,
"request": Dict[str, object],
# "sdk": Mapping[str, object],
"server_name": str,
"spans": List[Dict[str, object]],
"stacktrace": Dict[str, object], # We access this key in the code, but I am unsure whether we ever set it
"start_timestamp": datetime,
"status": Optional[str],
# "tags": MutableMapping[
# str, str
# ], # Tags must be less than 200 characters each
"threads": Dict[Literal["values"], List[Dict[str, Any]]], # TODO: We can expand on this type
"timestamp": Optional[datetime], # Must be set before sending the event
"transaction": str,
# "transaction_info": Mapping[str, Any], # TODO: We can expand on this type
"type": Literal["check_in", "transaction"],
"user": Dict[str, object],
"_metrics_summary": Dict[str, object],
},
total=False,
)
epoch = datetime(1970, 1, 1)
BASE64_ALPHABET = re.compile(r"^[a-zA-Z0-9/+=]*$")
SENSITIVE_DATA_SUBSTITUTE = "[Filtered]"
def to_timestamp(value):
# type: (datetime) -> float
return (value - epoch).total_seconds()
def format_timestamp(value):
# type: (datetime) -> str
return value.strftime("%Y-%m-%dT%H:%M:%S.%fZ")
def event_hint_with_exc_info(exc_info=None):
# type: (Optional[ExcInfo]) -> Dict[str, Optional[ExcInfo]]
"""Creates a hint with the exc info filled in."""
if exc_info is None:
exc_info = sys.exc_info()
else:
exc_info = exc_info_from_error(exc_info)
if exc_info[0] is None:
exc_info = None
return {"exc_info": exc_info}
class AnnotatedValue:
"""
Meta information for a data field in the event payload.
This is to tell Relay that we have tampered with the fields value.
See:
https://github.com/getsentry/relay/blob/be12cd49a0f06ea932ed9b9f93a655de5d6ad6d1/relay-general/src/types/meta.rs#L407-L423
"""
__slots__ = ("value", "metadata")
def __init__(self, value, metadata):
# type: (Optional[Any], Dict[str, Any]) -> None
self.value = value
self.metadata = metadata
def __eq__(self, other):
# type: (Any) -> bool
if not isinstance(other, AnnotatedValue):
return False
return self.value == other.value and self.metadata == other.metadata
@classmethod
def removed_because_raw_data(cls):
# type: () -> AnnotatedValue
"""The value was removed because it could not be parsed. This is done for request body values that are not json nor a form."""
return AnnotatedValue(
value="",
metadata={
"rem": [ # Remark
[
"!raw", # Unparsable raw data
"x", # The fields original value was removed
]
]
},
)
@classmethod
def removed_because_over_size_limit(cls):
# type: () -> AnnotatedValue
"""The actual value was removed because the size of the field exceeded the configured maximum size (specified with the max_request_body_size sdk option)"""
return AnnotatedValue(
value="",
metadata={
"rem": [ # Remark
[
"!config", # Because of configured maximum size
"x", # The fields original value was removed
]
]
},
)
@classmethod
def substituted_because_contains_sensitive_data(cls):
# type: () -> AnnotatedValue
"""The actual value was removed because it contained sensitive information."""
return AnnotatedValue(
value=SENSITIVE_DATA_SUBSTITUTE,
metadata={
"rem": [ # Remark
[
"!config", # Because of SDK configuration (in this case the config is the hard coded removal of certain django cookies)
"s", # The fields original value was substituted
]
]
},
)
if TYPE_CHECKING:
T = TypeVar("T")
Annotated = Union[AnnotatedValue, T]
def get_type_name(cls):
# type: (Optional[type]) -> Optional[str]
return getattr(cls, "__qualname__", None) or getattr(cls, "__name__", None)
def get_type_module(cls):
# type: (Optional[type]) -> Optional[str]
mod = getattr(cls, "__module__", None)
if mod not in (None, "builtins", "__builtins__"):
return mod
return None
def should_hide_frame(frame: "FrameType") -> bool:
try:
mod = frame.f_globals["__name__"]
if mod.startswith("sentry_sdk."):
return True
except (AttributeError, KeyError):
pass
for flag_name in "__traceback_hide__", "__tracebackhide__":
try:
if frame.f_locals[flag_name]:
return True
except Exception:
pass
return False
def iter_stacks(tb):
# type: (Optional[TracebackType]) -> Iterator[TracebackType]
tb_ = tb # type: Optional[TracebackType]
while tb_ is not None:
if not should_hide_frame(tb_.tb_frame):
yield tb_
tb_ = tb_.tb_next
def get_lines_from_file(
filename, # type: str
lineno, # type: int
max_length=None, # type: Optional[int]
loader=None, # type: Optional[Any]
module=None, # type: Optional[str]
):
# type: (...) -> Tuple[List[Annotated[str]], Optional[Annotated[str]], List[Annotated[str]]]
context_lines = 5
source = None
if loader is not None and hasattr(loader, "get_source"):
try:
source_str = loader.get_source(module) # type: Optional[str]
except (ImportError, IOError):
source_str = None
if source_str is not None:
source = source_str.splitlines()
if source is None:
try:
source = linecache.getlines(filename)
except (OSError, IOError):
return [], None, []
if not source:
return [], None, []
lower_bound = max(0, lineno - context_lines)
upper_bound = min(lineno + 1 + context_lines, len(source))
try:
pre_context = [strip_string(line.strip("\r\n"), max_length=max_length) for line in source[lower_bound:lineno]]
context_line = strip_string(source[lineno].strip("\r\n"), max_length=max_length)
post_context = [
strip_string(line.strip("\r\n"), max_length=max_length)
for line in source[(lineno + 1) : upper_bound] # noqa: E203
]
return pre_context, context_line, post_context
except IndexError:
# the file may have changed since it was loaded into memory
return [], None, []
def get_source_context(
frame, # type: FrameType
tb_lineno, # type: int
max_value_length=None, # type: Optional[int]
):
# type: (...) -> Tuple[List[Annotated[str]], Optional[Annotated[str]], List[Annotated[str]]]
try:
abs_path = frame.f_code.co_filename # type: Optional[str]
except Exception:
abs_path = None
try:
module = frame.f_globals["__name__"]
except Exception:
return [], None, []
try:
loader = frame.f_globals["__loader__"]
except Exception:
loader = None
lineno = tb_lineno - 1
if lineno is not None and abs_path:
return get_lines_from_file(abs_path, lineno, max_value_length, loader=loader, module=module)
return [], None, []
def safe_str(value):
# type: (Any) -> str
try:
return str(value)
except Exception:
return safe_repr(value)
def safe_repr(value):
# type: (Any) -> str
try:
return repr(value)
except Exception:
return "<broken repr>"
def filename_for_module(module, abs_path):
# type: (Optional[str], Optional[str]) -> Optional[str]
if not abs_path or not module:
return abs_path
try:
if abs_path.endswith(".pyc"):
abs_path = abs_path[:-1]
base_module = module.split(".", 1)[0]
if base_module == module:
return os.path.basename(abs_path)
base_module_path = sys.modules[base_module].__file__
if not base_module_path:
return abs_path
return abs_path.split(base_module_path.rsplit(os.sep, 2)[0], 1)[-1].lstrip(os.sep)
except Exception:
return abs_path
def serialize_frame(
frame,
tb_lineno=None,
include_local_variables=True,
include_source_context=True,
max_value_length=None,
custom_repr=None,
):
# type: (FrameType, Optional[int], bool, bool, Optional[int], Optional[Callable[..., Optional[str]]]) -> Dict[str, Any]
f_code = getattr(frame, "f_code", None)
if not f_code:
abs_path = None
function = None
else:
abs_path = frame.f_code.co_filename
function = frame.f_code.co_name
try:
module = frame.f_globals["__name__"]
except Exception:
module = None
if tb_lineno is None:
tb_lineno = frame.f_lineno
rv = {
"platform": "python",
"filename": filename_for_module(module, abs_path) or None,
"abs_path": os.path.abspath(abs_path) if abs_path else None,
"function": function or "<unknown>",
"module": module,
"lineno": tb_lineno,
} # type: Dict[str, Any]
if include_source_context:
rv["pre_context"], rv["context_line"], rv["post_context"] = get_source_context(
frame, tb_lineno, max_value_length
)
if include_local_variables:
# TODO(nk): Sort out this current invalid import
# from sentry_sdk.serializer import serialize
# rv["vars"] = serialize(
# dict(frame.f_locals), is_vars=True, custom_repr=custom_repr
# )
pass
return rv
def current_stacktrace(
include_local_variables=True, # type: bool
include_source_context=True, # type: bool
max_value_length=None, # type: Optional[int]
):
# type: (...) -> Dict[str, Any]
__tracebackhide__ = True
frames = []
f = sys._getframe() # type: Optional[FrameType]
while f is not None:
if not should_hide_frame(f):
frames.append(
serialize_frame(
f,
include_local_variables=include_local_variables,
include_source_context=include_source_context,
max_value_length=max_value_length,
)
)
f = f.f_back
frames.reverse()
return {"frames": frames, "type": "raw"}
def get_errno(exc_value):
# type: (BaseException) -> Optional[Any]
return getattr(exc_value, "errno", None)
def get_error_message(exc_value):
# type: (Optional[BaseException]) -> str
return getattr(exc_value, "message", "") or getattr(exc_value, "detail", "") or safe_str(exc_value)
def single_exception_from_error_tuple(
exc_type, # type: Optional[type]
exc_value, # type: Optional[BaseException]
tb, # type: Optional[TracebackType]
client_options=None, # type: Optional[Dict[str, Any]]
mechanism=None, # type: Optional[Dict[str, Any]]
exception_id=None, # type: Optional[int]
parent_id=None, # type: Optional[int]
source=None, # type: Optional[str]
):
# type: (...) -> Dict[str, Any]
"""
Creates a dict that goes into the events `exception.values` list and is ingestible by Sentry.
See the Exception Interface documentation for more details:
https://develop.sentry.dev/sdk/event-payloads/exception/
"""
exception_value = {} # type: Dict[str, Any]
exception_value["mechanism"] = mechanism.copy() if mechanism else {"type": "generic", "handled": True}
if exception_id is not None:
exception_value["mechanism"]["exception_id"] = exception_id
if exc_value is not None:
errno = get_errno(exc_value)
else:
errno = None
if errno is not None:
exception_value["mechanism"].setdefault("meta", {}).setdefault("errno", {}).setdefault("number", errno)
if source is not None:
exception_value["mechanism"]["source"] = source
is_root_exception = exception_id == 0
if not is_root_exception and parent_id is not None:
exception_value["mechanism"]["parent_id"] = parent_id
exception_value["mechanism"]["type"] = "chained"
if is_root_exception and "type" not in exception_value["mechanism"]:
exception_value["mechanism"]["type"] = "generic"
is_exception_group = BaseExceptionGroup is not None and isinstance(exc_value, BaseExceptionGroup)
if is_exception_group:
exception_value["mechanism"]["is_exception_group"] = True
exception_value["module"] = get_type_module(exc_type)
exception_value["type"] = get_type_name(exc_type)
exception_value["value"] = get_error_message(exc_value)
if client_options is None:
include_local_variables = True
include_source_context = True
max_value_length = DEFAULT_MAX_VALUE_LENGTH # fallback
custom_repr = None
else:
include_local_variables = client_options["include_local_variables"]
include_source_context = client_options["include_source_context"]
max_value_length = client_options["max_value_length"]
custom_repr = client_options.get("custom_repr")
frames = [
serialize_frame(
tb.tb_frame,
tb_lineno=tb.tb_lineno,
include_local_variables=include_local_variables,
include_source_context=include_source_context,
max_value_length=max_value_length,
custom_repr=custom_repr,
)
for tb in iter_stacks(tb)
]
if frames:
exception_value["stacktrace"] = {"frames": frames, "type": "raw"}
return exception_value
HAS_CHAINED_EXCEPTIONS = hasattr(Exception, "__suppress_context__")
if HAS_CHAINED_EXCEPTIONS:
def walk_exception_chain(exc_info):
# type: (ExcInfo) -> Iterator[ExcInfo]
exc_type, exc_value, tb = exc_info
seen_exceptions = []
seen_exception_ids = set() # type: Set[int]
while exc_type is not None and exc_value is not None and id(exc_value) not in seen_exception_ids:
yield exc_type, exc_value, tb
# Avoid hashing random types we don't know anything
# about. Use the list to keep a ref so that the `id` is
# not used for another object.
seen_exceptions.append(exc_value)
seen_exception_ids.add(id(exc_value))
if exc_value.__suppress_context__:
cause = exc_value.__cause__
else:
cause = exc_value.__context__
if cause is None:
break
exc_type = type(cause)
exc_value = cause
tb = getattr(cause, "__traceback__", None)
else:
def walk_exception_chain(exc_info):
# type: (ExcInfo) -> Iterator[ExcInfo]
yield exc_info
def exceptions_from_error(
exc_type, # type: Optional[type]
exc_value, # type: Optional[BaseException]
tb, # type: Optional[TracebackType]
client_options=None, # type: Optional[Dict[str, Any]]
mechanism=None, # type: Optional[Dict[str, Any]]
exception_id=0, # type: int
parent_id=0, # type: int
source=None, # type: Optional[str]
):
# type: (...) -> Tuple[int, List[Dict[str, Any]]]
"""
Creates the list of exceptions.
This can include chained exceptions and exceptions from an ExceptionGroup.
See the Exception Interface documentation for more details:
https://develop.sentry.dev/sdk/event-payloads/exception/
"""
parent = single_exception_from_error_tuple(
exc_type=exc_type,
exc_value=exc_value,
tb=tb,
client_options=client_options,
mechanism=mechanism,
exception_id=exception_id,
parent_id=parent_id,
source=source,
)
exceptions = [parent]
parent_id = exception_id
exception_id += 1
should_supress_context = hasattr(exc_value, "__suppress_context__") and exc_value.__suppress_context__ # type: ignore
if should_supress_context:
# Add direct cause.
# The field `__cause__` is set when raised with the exception (using the `from` keyword).
exception_has_cause = exc_value and hasattr(exc_value, "__cause__") and exc_value.__cause__ is not None
if exception_has_cause:
cause = exc_value.__cause__ # type: ignore
(exception_id, child_exceptions) = exceptions_from_error(
exc_type=type(cause),
exc_value=cause,
tb=getattr(cause, "__traceback__", None),
client_options=client_options,
mechanism=mechanism,
exception_id=exception_id,
source="__cause__",
)
exceptions.extend(child_exceptions)
else:
# Add indirect cause.
# The field `__context__` is assigned if another exception occurs while handling the exception.
exception_has_content = exc_value and hasattr(exc_value, "__context__") and exc_value.__context__ is not None
if exception_has_content:
context = exc_value.__context__ # type: ignore
(exception_id, child_exceptions) = exceptions_from_error(
exc_type=type(context),
exc_value=context,
tb=getattr(context, "__traceback__", None),
client_options=client_options,
mechanism=mechanism,
exception_id=exception_id,
source="__context__",
)
exceptions.extend(child_exceptions)
# Add exceptions from an ExceptionGroup.
is_exception_group = exc_value and hasattr(exc_value, "exceptions")
if is_exception_group:
for idx, e in enumerate(exc_value.exceptions): # type: ignore
(exception_id, child_exceptions) = exceptions_from_error(
exc_type=type(e),
exc_value=e,
tb=getattr(e, "__traceback__", None),
client_options=client_options,
mechanism=mechanism,
exception_id=exception_id,
parent_id=parent_id,
source="exceptions[%s]" % idx,
)
exceptions.extend(child_exceptions)
return (exception_id, exceptions)
def exceptions_from_error_tuple(
exc_info, # type: ExcInfo
client_options=None, # type: Optional[Dict[str, Any]]
mechanism=None, # type: Optional[Dict[str, Any]]
):
# type: (...) -> List[Dict[str, Any]]
exc_type, exc_value, tb = exc_info
is_exception_group = BaseExceptionGroup is not None and isinstance(exc_value, BaseExceptionGroup)
if is_exception_group:
(_, exceptions) = exceptions_from_error(
exc_type=exc_type,
exc_value=exc_value,
tb=tb,
client_options=client_options,
mechanism=mechanism,
exception_id=0,
parent_id=0,
)
else:
exceptions = []
for exc_type, exc_value, tb in walk_exception_chain(exc_info):
exceptions.append(single_exception_from_error_tuple(exc_type, exc_value, tb, client_options, mechanism))
exceptions.reverse()
return exceptions
def to_string(value):
# type: (str) -> str
try:
return str(value)
except UnicodeDecodeError:
return repr(value)[1:-1]
def iter_event_stacktraces(event):
# type: (Event) -> Iterator[Dict[str, Any]]
if "stacktrace" in event:
yield event["stacktrace"]
if "threads" in event:
for thread in event["threads"].get("values") or ():
if "stacktrace" in thread:
yield thread["stacktrace"]
if "exception" in event:
for exception in event["exception"].get("values") or ():
if "stacktrace" in exception:
yield exception["stacktrace"]
def iter_event_frames(event):
# type: (Event) -> Iterator[Dict[str, Any]]
for stacktrace in iter_event_stacktraces(event):
for frame in stacktrace.get("frames") or ():
yield frame
def handle_in_app(event, in_app_exclude=None, in_app_include=None, project_root=None):
# type: (Event, Optional[List[str]], Optional[List[str]], Optional[str]) -> Event
for stacktrace in iter_event_stacktraces(event):
set_in_app_in_frames(
stacktrace.get("frames"),
in_app_exclude=in_app_exclude,
in_app_include=in_app_include,
project_root=project_root,
)
return event
def set_in_app_in_frames(frames, in_app_exclude, in_app_include, project_root=None):
# type: (Any, Optional[List[str]], Optional[List[str]], Optional[str]) -> Optional[Any]
if not frames:
return None
for frame in frames:
# if frame has already been marked as in_app, skip it
current_in_app = frame.get("in_app")
if current_in_app is not None:
continue
module = frame.get("module")
# check if module in frame is in the list of modules to include
if _module_in_list(module, in_app_include):
frame["in_app"] = True
continue
# check if module in frame is in the list of modules to exclude
if _module_in_list(module, in_app_exclude):
frame["in_app"] = False
continue
# if frame has no abs_path, skip further checks
abs_path = frame.get("abs_path")
if abs_path is None:
continue
if _is_external_source(abs_path):
frame["in_app"] = False
continue
if _is_in_project_root(abs_path, project_root):
frame["in_app"] = True
continue
return frames
def exc_info_from_error(error):
# type: (Union[BaseException, ExcInfo]) -> ExcInfo
if isinstance(error, tuple) and len(error) == 3:
exc_type, exc_value, tb = error
elif isinstance(error, BaseException):
tb = getattr(error, "__traceback__", None)
if tb is not None:
exc_type = type(error)
exc_value = error
else:
exc_type, exc_value, tb = sys.exc_info()
if exc_value is not error:
tb = None
exc_value = error
exc_type = type(error)
else:
raise ValueError("Expected Exception object to report, got %s!" % type(error))
exc_info = (exc_type, exc_value, tb)
if TYPE_CHECKING:
# This cast is safe because exc_type and exc_value are either both
# None or both not None.
exc_info = cast(ExcInfo, exc_info)
return exc_info
def event_from_exception(
exc_info, # type: Union[BaseException, ExcInfo]
client_options=None, # type: Optional[Dict[str, Any]]
mechanism=None, # type: Optional[Dict[str, Any]]
):
# type: (...) -> Tuple[Event, Dict[str, Any]]
exc_info = exc_info_from_error(exc_info)
hint = event_hint_with_exc_info(exc_info)
return (
{
"level": "error",
"exception": {"values": exceptions_from_error_tuple(exc_info, client_options, mechanism)},
},
hint,
)
def _module_in_list(name, items):
# type: (str | None, Optional[List[str]]) -> bool
if name is None:
return False
if not items:
return False
for item in items:
if item == name or name.startswith(item + "."):
return True
return False
def _is_external_source(abs_path):
# type: (str) -> bool
# check if frame is in 'site-packages' or 'dist-packages'
external_source = re.search(r"[\\/](?:dist|site)-packages[\\/]", abs_path) is not None
return external_source
def _is_in_project_root(abs_path, project_root):
# type: (str, Optional[str]) -> bool
if project_root is None:
return False
# check if path is in the project root
if abs_path.startswith(project_root):
return True
return False
def _truncate_by_bytes(string, max_bytes):
# type: (str, int) -> str
"""
Truncate a UTF-8-encodable string to the last full codepoint so that it fits in max_bytes.
"""
truncated = string.encode("utf-8")[: max_bytes - 3].decode("utf-8", errors="ignore")
return truncated + "..."
def _get_size_in_bytes(value):
# type: (str) -> Optional[int]
try:
return len(value.encode("utf-8"))
except (UnicodeEncodeError, UnicodeDecodeError):
return None
def strip_string(value, max_length=None):
# type: (str, Optional[int]) -> Union[AnnotatedValue, str]
if not value:
return value
if max_length is None:
max_length = DEFAULT_MAX_VALUE_LENGTH
byte_size = _get_size_in_bytes(value)
text_size = len(value)
if byte_size is not None and byte_size > max_length:
# truncate to max_length bytes, preserving code points
truncated_value = _truncate_by_bytes(value, max_length)
elif text_size is not None and text_size > max_length:
# fallback to truncating by string length
truncated_value = value[: max_length - 3] + "..."
else:
return value
return AnnotatedValue(
value=truncated_value,
metadata={
"len": byte_size or text_size,
"rem": [["!limit", "x", max_length - 3, max_length]],
},
)
+14 -7
View File
@@ -7,12 +7,15 @@ from typing import Optional
from dateutil import parser
from dateutil.relativedelta import relativedelta
from posthog import utils
from posthog.utils import convert_to_datetime_aware, is_valid_regex
__LONG_SCALE__ = float(0xFFFFFFFFFFFFFFF)
log = logging.getLogger("posthog")
NONE_VALUES_ALLOWED_OPERATORS = ["is_not"]
class InconclusiveMatchError(Exception):
pass
@@ -51,6 +54,9 @@ def match_feature_flag_properties(flag, distinct_id, properties, cohort_properti
flag_conditions = (flag.get("filters") or {}).get("groups") or []
is_inconclusive = False
cohort_properties = cohort_properties or {}
# Some filters can be explicitly set to null, which require accessing variants like so
flag_variants = ((flag.get("filters") or {}).get("multivariate") or {}).get("variants") or []
valid_variant_keys = [variant["key"] for variant in flag_variants]
# Stable sort conditions with variant overrides to the top. This ensures that if overrides are present, they are
# evaluated first, and the variant override is applied to the first matching condition.
@@ -65,9 +71,7 @@ def match_feature_flag_properties(flag, distinct_id, properties, cohort_properti
# the matching variant
if is_condition_match(flag, distinct_id, condition, properties, cohort_properties):
variant_override = condition.get("variant")
# Some filters can be explicitly set to null, which require accessing variants like so
flag_variants = ((flag.get("filters") or {}).get("multivariate") or {}).get("variants") or []
if variant_override and variant_override in [variant["key"] for variant in flag_variants]:
if variant_override and variant_override in valid_variant_keys:
variant = variant_override
else:
variant = get_matching_variant(flag, distinct_id)
@@ -119,12 +123,15 @@ def match_property(property, property_values) -> bool:
override_value = property_values[key]
if (operator not in NONE_VALUES_ALLOWED_OPERATORS) and override_value is None:
return False
if operator in ("exact", "is_not"):
def compute_exact_match(value, override_value):
if isinstance(value, list):
return str(override_value).lower() in [str(val).lower() for val in value]
return str(value).lower() == str(override_value).lower()
return str(override_value).casefold() in [str(val).casefold() for val in value]
return utils.str_iequals(value, override_value)
if operator == "exact":
return compute_exact_match(value, override_value)
@@ -135,10 +142,10 @@ def match_property(property, property_values) -> bool:
return key in property_values
if operator == "icontains":
return str(value).lower() in str(override_value).lower()
return utils.str_icontains(override_value, value)
if operator == "not_icontains":
return str(value).lower() not in str(override_value).lower()
return not utils.str_icontains(override_value, value)
if operator == "regex":
return is_valid_regex(str(value)) and re.compile(str(value)).search(str(override_value)) is not None
+29 -4
View File
@@ -11,10 +11,12 @@ from dateutil.tz import tzutc
from posthog.utils import remove_trailing_slash
from posthog.version import VERSION
adapter = requests.adapters.HTTPAdapter(max_retries=2)
_session = requests.sessions.Session()
_session.mount("https://", adapter)
US_INGESTION_ENDPOINT = "https://us-api.i.posthog.com"
EU_INGESTION_ENDPOINT = "https://eu-api.i.posthog.com"
US_INGESTION_ENDPOINT = "https://us.i.posthog.com"
EU_INGESTION_ENDPOINT = "https://eu.i.posthog.com"
DEFAULT_HOST = US_INGESTION_ENDPOINT
USER_AGENT = "posthog-python/" + VERSION
@@ -37,7 +39,7 @@ def post(
"""Post the `kwargs` to the API"""
log = logging.getLogger("posthog")
body = kwargs
body["sentAt"] = datetime.utcnow().replace(tzinfo=tzutc()).isoformat()
body["sentAt"] = datetime.now(tz=tzutc()).isoformat()
url = remove_trailing_slash(host or DEFAULT_HOST) + path
body["api_key"] = api_key
data = json.dumps(body, cls=DatetimeSerializer)
@@ -66,7 +68,21 @@ def _process_response(
log = logging.getLogger("posthog")
if res.status_code == 200:
log.debug(success_message)
return res.json() if return_json else res
response = res.json() if return_json else res
# Handle quota limited decide responses by raising a specific error
# NB: other services also put entries into the quotaLimited key, but right now we only care about feature flags
# since most of the other services handle quota limiting in other places in the application.
if (
isinstance(response, dict)
and "quotaLimited" in response
and isinstance(response["quotaLimited"], list)
and "feature_flags" in response["quotaLimited"]
):
log.warning(
"[FEATURE FLAGS] PostHog feature flags quota limited, resetting feature flag data. Learn more about billing limits at https://posthog.com/docs/billing/limits-alerts"
)
raise QuotaLimitError(res.status_code, "Feature flags quota limited")
return response
try:
payload = res.json()
log.debug("received response: %s", payload)
@@ -81,6 +97,11 @@ def decide(api_key: str, host: Optional[str] = None, gzip: bool = False, timeout
return _process_response(res, success_message="Feature flags decided successfully")
def remote_config(personal_api_key: str, host: Optional[str] = None, key: str = "", timeout: int = 15) -> Any:
"""Get remote config flag value from remote_config API endpoint"""
return get(personal_api_key, f"/api/projects/@current/feature_flags/{key}/remote_config/", host, timeout)
def batch_post(
api_key: str, host: Optional[str] = None, gzip: bool = False, timeout: int = 15, **kwargs
) -> requests.Response:
@@ -105,6 +126,10 @@ class APIError(Exception):
return msg.format(self.message, self.status)
class QuotaLimitError(APIError):
pass
class DatetimeSerializer(json.JSONEncoder):
def default(self, obj: Any):
if isinstance(obj, (date, datetime)):
View File
+394
View File
@@ -0,0 +1,394 @@
import os
import time
from unittest.mock import patch
import pytest
from anthropic.types import Message, Usage
from posthog.ai.anthropic import Anthropic, AsyncAnthropic
ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY")
@pytest.fixture
def mock_client():
with patch("posthog.client.Client") as mock_client:
mock_client.privacy_mode = False
yield mock_client
@pytest.fixture
def mock_anthropic_response():
return Message(
id="msg_123",
type="message",
role="assistant",
content=[{"type": "text", "text": "Test response"}],
model="claude-3-opus-20240229",
usage=Usage(
input_tokens=20,
output_tokens=10,
),
stop_reason="end_turn",
stop_sequence=None,
)
@pytest.fixture
def mock_anthropic_stream():
class MockStreamEvent:
def __init__(self, content, usage=None):
self.content = content
self.usage = usage
def stream_generator():
yield MockStreamEvent("A")
yield MockStreamEvent("B")
yield MockStreamEvent(
"C",
usage=Usage(
input_tokens=20,
output_tokens=10,
),
)
return stream_generator()
@pytest.fixture
def mock_anthropic_response_with_cached_tokens():
# Create a mock Usage object with cached_tokens in input_tokens_details
usage = Usage(
input_tokens=20,
output_tokens=10,
cache_read_input_tokens=15,
cache_creation_input_tokens=2,
)
return Message(
id="msg_123",
type="message",
role="assistant",
content=[{"type": "text", "text": "Test response"}],
model="claude-3-opus-20240229",
usage=usage,
stop_reason="end_turn",
stop_sequence=None,
)
def test_basic_completion(mock_client, mock_anthropic_response):
with patch("anthropic.resources.Messages.create", return_value=mock_anthropic_response):
client = Anthropic(api_key="test-key", posthog_client=mock_client)
response = client.messages.create(
model="claude-3-opus-20240229",
messages=[{"role": "user", "content": "Hello"}],
posthog_distinct_id="test-id",
posthog_properties={"foo": "bar"},
)
assert response == mock_anthropic_response
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_generation"
assert props["$ai_provider"] == "anthropic"
assert props["$ai_model"] == "claude-3-opus-20240229"
assert props["$ai_input"] == [{"role": "user", "content": "Hello"}]
assert props["$ai_output_choices"] == [{"role": "assistant", "content": "Test response"}]
assert props["$ai_input_tokens"] == 20
assert props["$ai_output_tokens"] == 10
assert props["$ai_http_status"] == 200
assert props["foo"] == "bar"
assert isinstance(props["$ai_latency"], float)
def test_streaming(mock_client, mock_anthropic_stream):
with patch("anthropic.resources.Messages.create", return_value=mock_anthropic_stream):
client = Anthropic(api_key="test-key", posthog_client=mock_client)
response = client.messages.create(
model="claude-3-opus-20240229",
messages=[{"role": "user", "content": "Hello"}],
stream=True,
posthog_distinct_id="test-id",
posthog_properties={"foo": "bar"},
)
# Consume the stream
chunks = list(response)
assert len(chunks) == 3
assert chunks[0].content == "A"
assert chunks[1].content == "B"
assert chunks[2].content == "C"
# Wait a bit to ensure the capture is called
time.sleep(0.1)
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_generation"
assert props["$ai_provider"] == "anthropic"
assert props["$ai_model"] == "claude-3-opus-20240229"
assert props["$ai_input"] == [{"role": "user", "content": "Hello"}]
assert props["$ai_output_choices"] == [{"role": "assistant", "content": "ABC"}]
assert props["$ai_input_tokens"] == 20
assert props["$ai_output_tokens"] == 10
assert isinstance(props["$ai_latency"], float)
assert props["foo"] == "bar"
def test_streaming_with_stream_endpoint(mock_client, mock_anthropic_stream):
with patch("anthropic.resources.Messages.create", return_value=mock_anthropic_stream):
client = Anthropic(api_key="test-key", posthog_client=mock_client)
response = client.messages.stream(
model="claude-3-opus-20240229",
messages=[{"role": "user", "content": "Hello"}],
posthog_distinct_id="test-id",
posthog_properties={"foo": "bar"},
)
# Consume the stream
chunks = list(response)
assert len(chunks) == 3
assert chunks[0].content == "A"
assert chunks[1].content == "B"
assert chunks[2].content == "C"
# Wait a bit to ensure the capture is called
time.sleep(0.1)
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_generation"
assert props["$ai_provider"] == "anthropic"
assert props["$ai_model"] == "claude-3-opus-20240229"
assert props["$ai_input"] == [{"role": "user", "content": "Hello"}]
assert props["$ai_output_choices"] == [{"role": "assistant", "content": "ABC"}]
assert props["$ai_input_tokens"] == 20
assert props["$ai_output_tokens"] == 10
assert isinstance(props["$ai_latency"], float)
assert props["foo"] == "bar"
def test_groups(mock_client, mock_anthropic_response):
with patch("anthropic.resources.Messages.create", return_value=mock_anthropic_response):
client = Anthropic(api_key="test-key", posthog_client=mock_client)
response = client.messages.create(
model="claude-3-opus-20240229",
messages=[{"role": "user", "content": "Hello"}],
posthog_distinct_id="test-id",
posthog_groups={"company": "test_company"},
)
assert response == mock_anthropic_response
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
assert call_args["groups"] == {"company": "test_company"}
def test_privacy_mode_local(mock_client, mock_anthropic_response):
with patch("anthropic.resources.Messages.create", return_value=mock_anthropic_response):
client = Anthropic(api_key="test-key", posthog_client=mock_client)
response = client.messages.create(
model="claude-3-opus-20240229",
messages=[{"role": "user", "content": "Hello"}],
posthog_distinct_id="test-id",
posthog_privacy_mode=True,
)
assert response == mock_anthropic_response
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert props["$ai_input"] is None
assert props["$ai_output_choices"] is None
def test_privacy_mode_global(mock_client, mock_anthropic_response):
with patch("anthropic.resources.Messages.create", return_value=mock_anthropic_response):
mock_client.privacy_mode = True
client = Anthropic(api_key="test-key", posthog_client=mock_client)
response = client.messages.create(
model="claude-3-opus-20240229",
messages=[{"role": "user", "content": "Hello"}],
posthog_distinct_id="test-id",
posthog_privacy_mode=False,
)
assert response == mock_anthropic_response
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert props["$ai_input"] is None
assert props["$ai_output_choices"] is None
@pytest.mark.skipif(not ANTHROPIC_API_KEY, reason="ANTHROPIC_API_KEY is not set")
def test_basic_integration(mock_client):
client = Anthropic(posthog_client=mock_client)
client.messages.create(
model="claude-3-opus-20240229",
messages=[{"role": "user", "content": "Foo"}],
max_tokens=1,
temperature=0,
posthog_distinct_id="test-id",
posthog_properties={"foo": "bar"},
system="You must always answer with 'Bar'.",
)
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_generation"
assert props["$ai_provider"] == "anthropic"
assert props["$ai_model"] == "claude-3-opus-20240229"
assert props["$ai_input"] == [
{"role": "system", "content": "You must always answer with 'Bar'."},
{"role": "user", "content": "Foo"},
]
assert props["$ai_output_choices"][0]["role"] == "assistant"
assert props["$ai_output_choices"][0]["content"] == "Bar"
assert props["$ai_input_tokens"] == 18
assert props["$ai_output_tokens"] == 1
assert props["$ai_http_status"] == 200
assert props["foo"] == "bar"
assert isinstance(props["$ai_latency"], float)
@pytest.mark.skipif(not ANTHROPIC_API_KEY, reason="ANTHROPIC_API_KEY is not set")
async def test_basic_async_integration(mock_client):
client = AsyncAnthropic(posthog_client=mock_client)
await client.messages.create(
model="claude-3-opus-20240229",
messages=[{"role": "user", "content": "You must always answer with 'Bar'."}],
max_tokens=1,
temperature=0,
posthog_distinct_id="test-id",
posthog_properties={"foo": "bar"},
)
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_generation"
assert props["$ai_provider"] == "anthropic"
assert props["$ai_model"] == "claude-3-opus-20240229"
assert props["$ai_input"] == [{"role": "user", "content": "You must always answer with 'Bar'."}]
assert props["$ai_output_choices"][0]["role"] == "assistant"
assert props["$ai_input_tokens"] == 16
assert props["$ai_output_tokens"] == 1
assert props["$ai_http_status"] == 200
assert props["foo"] == "bar"
assert isinstance(props["$ai_latency"], float)
def test_streaming_system_prompt(mock_client, mock_anthropic_stream):
with patch("anthropic.resources.Messages.create", return_value=mock_anthropic_stream):
client = Anthropic(api_key="test-key", posthog_client=mock_client)
response = client.messages.create(
model="claude-3-opus-20240229",
system="Foo",
messages=[{"role": "user", "content": "Bar"}],
stream=True,
)
# Consume the stream
list(response)
# Wait a bit to ensure the capture is called
time.sleep(0.1)
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert props["$ai_input"] == [{"role": "system", "content": "Foo"}, {"role": "user", "content": "Bar"}]
@pytest.mark.skipif(not ANTHROPIC_API_KEY, reason="ANTHROPIC_API_KEY is not set")
async def test_async_streaming_system_prompt(mock_client, mock_anthropic_stream):
client = AsyncAnthropic(posthog_client=mock_client)
response = await client.messages.create(
model="claude-3-opus-20240229",
system="You must always answer with 'Bar'.",
messages=[{"role": "user", "content": "Foo"}],
stream=True,
max_tokens=1,
)
# Consume the stream
[c async for c in response]
# Wait a bit to ensure the capture is called
time.sleep(0.1)
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert props["$ai_input"] == [
{"role": "system", "content": "You must always answer with 'Bar'."},
{"role": "user", "content": "Foo"},
]
def test_error(mock_client, mock_anthropic_response):
with patch("anthropic.resources.Messages.create", side_effect=Exception("Test error")):
client = Anthropic(api_key="test-key", posthog_client=mock_client)
with pytest.raises(Exception):
client.messages.create(model="claude-3-opus-20240229", messages=[{"role": "user", "content": "Hello"}])
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert props["$ai_is_error"] is True
assert props["$ai_error"] == "Test error"
def test_cached_tokens(mock_client, mock_anthropic_response_with_cached_tokens):
with patch("anthropic.resources.Messages.create", return_value=mock_anthropic_response_with_cached_tokens):
client = Anthropic(api_key="test-key", posthog_client=mock_client)
response = client.messages.create(
model="claude-3-opus-20240229",
messages=[{"role": "user", "content": "Hello"}],
posthog_distinct_id="test-id",
posthog_properties={"foo": "bar"},
)
assert response == mock_anthropic_response_with_cached_tokens
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_generation"
assert props["$ai_provider"] == "anthropic"
assert props["$ai_model"] == "claude-3-opus-20240229"
assert props["$ai_input"] == [{"role": "user", "content": "Hello"}]
assert props["$ai_output_choices"] == [{"role": "assistant", "content": "Test response"}]
assert props["$ai_input_tokens"] == 20
assert props["$ai_output_tokens"] == 10
assert props["$ai_cache_read_input_tokens"] == 15
assert props["$ai_cache_creation_input_tokens"] == 2
assert props["$ai_http_status"] == 200
assert props["foo"] == "bar"
assert isinstance(props["$ai_latency"], float)
+5
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import pytest
pytest.importorskip("langchain")
pytest.importorskip("langchain_community")
pytest.importorskip("langgraph")
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+574
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@@ -0,0 +1,574 @@
import json
import time
from unittest.mock import patch
import pytest
from openai.types.chat import ChatCompletion, ChatCompletionMessage
from openai.types.chat.chat_completion import Choice
from openai.types.chat.chat_completion_chunk import ChatCompletionChunk
from openai.types.chat.chat_completion_chunk import Choice as ChoiceChunk
from openai.types.chat.chat_completion_chunk import ChoiceDelta, ChoiceDeltaToolCall, ChoiceDeltaToolCallFunction
from openai.types.chat.chat_completion_message_tool_call import ChatCompletionMessageToolCall, Function
from openai.types.completion_usage import CompletionUsage
from openai.types.create_embedding_response import CreateEmbeddingResponse, Usage
from openai.types.embedding import Embedding
from openai.types.responses import Response, ResponseOutputMessage, ResponseOutputText, ResponseUsage
from posthog.ai.openai import OpenAI
@pytest.fixture
def mock_client():
with patch("posthog.client.Client") as mock_client:
mock_client.privacy_mode = False
yield mock_client
@pytest.fixture
def mock_openai_response():
return ChatCompletion(
id="test",
model="gpt-4",
object="chat.completion",
created=int(time.time()),
choices=[
Choice(
finish_reason="stop",
index=0,
message=ChatCompletionMessage(
content="Test response",
role="assistant",
),
)
],
usage=CompletionUsage(
completion_tokens=10,
prompt_tokens=20,
total_tokens=30,
),
)
@pytest.fixture
def mock_openai_response_with_responses_api():
return Response(
id="test",
model="gpt-4o-mini",
object="response",
created_at=1741476542,
status="completed",
error=None,
incomplete_details=None,
instructions=None,
max_output_tokens=None,
tools=[],
tool_choice="auto",
output=[
ResponseOutputMessage(
id="msg_123",
type="message",
role="assistant",
status="completed",
content=[
ResponseOutputText(
type="output_text",
text="Test response",
annotations=[],
)
],
)
],
parallel_tool_calls=True,
previous_response_id=None,
usage=ResponseUsage(
input_tokens=10,
output_tokens=10,
output_tokens_details={"reasoning_tokens": 15},
total_tokens=20,
),
user=None,
metadata={},
)
@pytest.fixture
def mock_embedding_response():
return CreateEmbeddingResponse(
data=[
Embedding(
embedding=[0.1, 0.2, 0.3],
index=0,
object="embedding",
)
],
model="text-embedding-3-small",
object="list",
usage=Usage(
prompt_tokens=10,
total_tokens=10,
),
)
@pytest.fixture
def mock_openai_response_with_cached_tokens():
return ChatCompletion(
id="test",
model="gpt-4",
object="chat.completion",
created=int(time.time()),
choices=[
Choice(
finish_reason="stop",
index=0,
message=ChatCompletionMessage(
content="Test response",
role="assistant",
),
)
],
usage=CompletionUsage(
completion_tokens=10,
prompt_tokens=20,
total_tokens=30,
prompt_tokens_details={"cached_tokens": 15},
),
)
@pytest.fixture
def mock_openai_response_with_tool_calls():
return ChatCompletion(
id="test",
model="gpt-4",
object="chat.completion",
created=int(time.time()),
choices=[
Choice(
finish_reason="tool_calls",
index=0,
message=ChatCompletionMessage(
content="I'll check the weather for you.",
role="assistant",
tool_calls=[
ChatCompletionMessageToolCall(
id="call_abc123",
type="function",
function=Function(
name="get_weather",
arguments='{"location": "San Francisco", "unit": "celsius"}',
),
)
],
),
)
],
usage=CompletionUsage(
completion_tokens=15,
prompt_tokens=20,
total_tokens=35,
),
)
def test_basic_completion(mock_client, mock_openai_response):
with patch("openai.resources.chat.completions.Completions.create", return_value=mock_openai_response):
client = OpenAI(api_key="test-key", posthog_client=mock_client)
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "Hello"}],
posthog_distinct_id="test-id",
posthog_properties={"foo": "bar"},
)
assert response == mock_openai_response
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_generation"
assert props["$ai_provider"] == "openai"
assert props["$ai_model"] == "gpt-4"
assert props["$ai_input"] == [{"role": "user", "content": "Hello"}]
assert props["$ai_output_choices"] == [{"role": "assistant", "content": "Test response"}]
assert props["$ai_input_tokens"] == 20
assert props["$ai_output_tokens"] == 10
assert props["$ai_http_status"] == 200
assert props["foo"] == "bar"
assert isinstance(props["$ai_latency"], float)
def test_embeddings(mock_client, mock_embedding_response):
with patch("openai.resources.embeddings.Embeddings.create", return_value=mock_embedding_response):
client = OpenAI(api_key="test-key", posthog_client=mock_client)
response = client.embeddings.create(
model="text-embedding-3-small",
input="Hello world",
posthog_distinct_id="test-id",
posthog_properties={"foo": "bar"},
)
assert response == mock_embedding_response
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_embedding"
assert props["$ai_provider"] == "openai"
assert props["$ai_model"] == "text-embedding-3-small"
assert props["$ai_input"] == "Hello world"
assert props["$ai_input_tokens"] == 10
assert props["$ai_http_status"] == 200
assert props["foo"] == "bar"
assert isinstance(props["$ai_latency"], float)
def test_groups(mock_client, mock_openai_response):
with patch("openai.resources.chat.completions.Completions.create", return_value=mock_openai_response):
client = OpenAI(api_key="test-key", posthog_client=mock_client)
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "Hello"}],
posthog_distinct_id="test-id",
posthog_groups={"company": "test_company"},
)
assert response == mock_openai_response
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
assert call_args["groups"] == {"company": "test_company"}
def test_privacy_mode_local(mock_client, mock_openai_response):
with patch("openai.resources.chat.completions.Completions.create", return_value=mock_openai_response):
client = OpenAI(api_key="test-key", posthog_client=mock_client)
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "Hello"}],
posthog_distinct_id="test-id",
posthog_privacy_mode=True,
)
assert response == mock_openai_response
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert props["$ai_input"] is None
assert props["$ai_output_choices"] is None
def test_privacy_mode_global(mock_client, mock_openai_response):
with patch("openai.resources.chat.completions.Completions.create", return_value=mock_openai_response):
mock_client.privacy_mode = True
client = OpenAI(api_key="test-key", posthog_client=mock_client)
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "Hello"}],
posthog_distinct_id="test-id",
posthog_privacy_mode=False,
)
assert response == mock_openai_response
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert props["$ai_input"] is None
assert props["$ai_output_choices"] is None
def test_error(mock_client, mock_openai_response):
with patch("openai.resources.chat.completions.Completions.create", side_effect=Exception("Test error")):
client = OpenAI(api_key="test-key", posthog_client=mock_client)
with pytest.raises(Exception):
client.chat.completions.create(model="gpt-4", messages=[{"role": "user", "content": "Hello"}])
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert props["$ai_is_error"] is True
assert props["$ai_error"] == "Test error"
def test_cached_tokens(mock_client, mock_openai_response_with_cached_tokens):
with patch(
"openai.resources.chat.completions.Completions.create", return_value=mock_openai_response_with_cached_tokens
):
client = OpenAI(api_key="test-key", posthog_client=mock_client)
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "Hello"}],
posthog_distinct_id="test-id",
posthog_properties={"foo": "bar"},
)
assert response == mock_openai_response_with_cached_tokens
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_generation"
assert props["$ai_provider"] == "openai"
assert props["$ai_model"] == "gpt-4"
assert props["$ai_input"] == [{"role": "user", "content": "Hello"}]
assert props["$ai_output_choices"] == [{"role": "assistant", "content": "Test response"}]
assert props["$ai_input_tokens"] == 20
assert props["$ai_output_tokens"] == 10
assert props["$ai_cache_read_input_tokens"] == 15
assert props["$ai_http_status"] == 200
assert props["foo"] == "bar"
assert isinstance(props["$ai_latency"], float)
def test_tool_calls(mock_client, mock_openai_response_with_tool_calls):
with patch(
"openai.resources.chat.completions.Completions.create", return_value=mock_openai_response_with_tool_calls
):
client = OpenAI(api_key="test-key", posthog_client=mock_client)
response = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "What's the weather in San Francisco?"}],
tools=[
{
"type": "function",
"function": {"name": "get_weather", "description": "Get weather", "parameters": {}},
}
],
posthog_distinct_id="test-id",
)
assert response == mock_openai_response_with_tool_calls
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_generation"
assert props["$ai_provider"] == "openai"
assert props["$ai_model"] == "gpt-4"
assert props["$ai_input"] == [{"role": "user", "content": "What's the weather in San Francisco?"}]
assert props["$ai_output_choices"] == [{"role": "assistant", "content": "I'll check the weather for you."}]
# Check that tool calls are properly captured
assert "$ai_tools" in props
tool_calls = props["$ai_tools"]
assert len(tool_calls) == 1
# Verify the tool call details
tool_call = tool_calls[0]
assert tool_call.id == "call_abc123"
assert tool_call.type == "function"
assert tool_call.function.name == "get_weather"
# Verify the arguments
arguments = tool_call.function.arguments
parsed_args = json.loads(arguments)
assert parsed_args == {"location": "San Francisco", "unit": "celsius"}
# Check token usage
assert props["$ai_input_tokens"] == 20
assert props["$ai_output_tokens"] == 15
assert props["$ai_http_status"] == 200
def test_streaming_with_tool_calls(mock_client):
# Create mock tool call chunks that will be returned in sequence
tool_call_chunks = [
ChatCompletionChunk(
id="chunk1",
model="gpt-4",
object="chat.completion.chunk",
created=1234567890,
choices=[
ChoiceChunk(
index=0,
delta=ChoiceDelta(
role="assistant",
tool_calls=[
ChoiceDeltaToolCall(
index=0,
id="call_abc123",
type="function",
function=ChoiceDeltaToolCallFunction(
name="get_weather",
arguments='{"location": "',
),
)
],
),
finish_reason=None,
)
],
),
ChatCompletionChunk(
id="chunk2",
model="gpt-4",
object="chat.completion.chunk",
created=1234567891,
choices=[
ChoiceChunk(
index=0,
delta=ChoiceDelta(
tool_calls=[
ChoiceDeltaToolCall(
index=0,
id="call_abc123",
type="function",
function=ChoiceDeltaToolCallFunction(
arguments='San Francisco"',
),
)
],
),
finish_reason=None,
)
],
),
ChatCompletionChunk(
id="chunk3",
model="gpt-4",
object="chat.completion.chunk",
created=1234567892,
choices=[
ChoiceChunk(
index=0,
delta=ChoiceDelta(
tool_calls=[
ChoiceDeltaToolCall(
index=0,
id="call_abc123",
type="function",
function=ChoiceDeltaToolCallFunction(
arguments=', "unit": "celsius"}',
),
)
],
),
finish_reason=None,
)
],
),
ChatCompletionChunk(
id="chunk4",
model="gpt-4",
object="chat.completion.chunk",
created=1234567893,
choices=[
ChoiceChunk(
index=0,
delta=ChoiceDelta(
content="The weather in San Francisco is 15°C.",
),
finish_reason=None,
)
],
usage=CompletionUsage(
prompt_tokens=20,
completion_tokens=15,
total_tokens=35,
),
),
]
# Mock the create method to return our chunks
with patch("openai.resources.chat.completions.Completions.create") as mock_create:
# Set up the mock to return our chunks when iterated
mock_create.return_value = tool_call_chunks
client = OpenAI(api_key="test-key", posthog_client=mock_client)
# Call the streaming method
response_generator = client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": "What's the weather in San Francisco?"}],
tools=[
{
"type": "function",
"function": {"name": "get_weather", "description": "Get weather", "parameters": {}},
}
],
stream=True,
posthog_distinct_id="test-id",
)
# Consume the generator to trigger the event capture
chunks = list(response_generator)
# Verify the chunks were returned correctly
assert len(chunks) == 4
assert chunks == tool_call_chunks
# Verify the capture was called with the right arguments
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_generation"
assert props["$ai_provider"] == "openai"
assert props["$ai_model"] == "gpt-4"
# Check that the tool calls were properly accumulated
assert "$ai_tools" in props
tool_calls = props["$ai_tools"]
assert len(tool_calls) == 1
# Verify the complete tool call was properly assembled
tool_call = tool_calls[0]
assert tool_call.id == "call_abc123"
assert tool_call.type == "function"
assert tool_call.function.name == "get_weather"
# Verify the arguments were concatenated correctly
arguments = tool_call.function.arguments
parsed_args = json.loads(arguments)
assert parsed_args == {"location": "San Francisco", "unit": "celsius"}
# Check that the content was also accumulated
assert props["$ai_output_choices"][0]["content"] == "The weather in San Francisco is 15°C."
# Check token usage
assert props["$ai_input_tokens"] == 20
assert props["$ai_output_tokens"] == 15
# test responses api
def test_responses_api(mock_client, mock_openai_response_with_responses_api):
with patch("openai.resources.responses.Responses.create", return_value=mock_openai_response_with_responses_api):
client = OpenAI(api_key="test-key", posthog_client=mock_client)
response = client.responses.create(
model="gpt-4o-mini",
input="Hello",
posthog_distinct_id="test-id",
posthog_properties={"foo": "bar"},
)
assert response == mock_openai_response_with_responses_api
assert mock_client.capture.call_count == 1
call_args = mock_client.capture.call_args[1]
props = call_args["properties"]
assert call_args["distinct_id"] == "test-id"
assert call_args["event"] == "$ai_generation"
assert props["$ai_provider"] == "openai"
assert props["$ai_model"] == "gpt-4o-mini"
assert props["$ai_input"] == [{"role": "user", "content": "Hello"}]
assert props["$ai_output_choices"] == [{"role": "assistant", "content": "Test response"}]
assert props["$ai_input_tokens"] == 10
assert props["$ai_output_tokens"] == 10
assert props["$ai_reasoning_tokens"] == 15
assert props["$ai_http_status"] == 200
assert props["foo"] == "bar"
assert isinstance(props["$ai_latency"], float)
@@ -0,0 +1,3 @@
import pytest
pytest.importorskip("django")
@@ -0,0 +1,68 @@
from posthog.exception_integrations.django import DjangoRequestExtractor
DEFAULT_USER_AGENT = (
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3"
)
def mock_request_factory(override_headers):
class Request:
META = {}
# TRICKY: Actual django request dict object has case insensitive matching, and strips http from the names
headers = {
"User-Agent": DEFAULT_USER_AGENT,
"Referrer": "http://example.com",
"X-Forwarded-For": "193.4.5.12",
**(override_headers or {}),
}
return Request()
def test_request_extractor_with_no_trace():
request = mock_request_factory(None)
extractor = DjangoRequestExtractor(request)
assert extractor.extract_person_data() == {
"ip": "193.4.5.12",
"user_agent": DEFAULT_USER_AGENT,
"traceparent": None,
"distinct_id": None,
}
def test_request_extractor_with_trace():
request = mock_request_factory({"traceparent": "00-0af7651916cd43dd8448eb211c80319c-b7ad6b7169203331-01"})
extractor = DjangoRequestExtractor(request)
assert extractor.extract_person_data() == {
"ip": "193.4.5.12",
"user_agent": DEFAULT_USER_AGENT,
"traceparent": "00-0af7651916cd43dd8448eb211c80319c-b7ad6b7169203331-01",
"distinct_id": None,
}
def test_request_extractor_with_tracestate():
request = mock_request_factory(
{
"traceparent": "00-0af7651916cd43dd8448eb211c80319c-b7ad6b7169203331-01",
"tracestate": "posthog-distinct-id=1234",
}
)
extractor = DjangoRequestExtractor(request)
assert extractor.extract_person_data() == {
"ip": "193.4.5.12",
"user_agent": DEFAULT_USER_AGENT,
"traceparent": "00-0af7651916cd43dd8448eb211c80319c-b7ad6b7169203331-01",
"distinct_id": "1234",
}
def test_request_extractor_with_complicated_tracestate():
request = mock_request_factory({"tracestate": "posthog-distinct-id=alohaMountainsXUYZ,rojo=00f067aa0ba902b7"})
extractor = DjangoRequestExtractor(request)
assert extractor.extract_person_data() == {
"ip": "193.4.5.12",
"user_agent": DEFAULT_USER_AGENT,
"traceparent": None,
"distinct_id": "alohaMountainsXUYZ",
}
+346 -29
View File
@@ -5,8 +5,10 @@ from uuid import uuid4
import mock
import six
from parameterized import parameterized
from posthog.client import Client
from posthog.request import APIError
from posthog.test.test_utils import FAKE_TEST_API_KEY
from posthog.version import VERSION
@@ -53,6 +55,11 @@ class TestClient(unittest.TestCase):
self.assertEqual(msg["distinct_id"], "distinct_id")
self.assertEqual(msg["properties"]["$lib"], "posthog-python")
self.assertEqual(msg["properties"]["$lib_version"], VERSION)
# these will change between platforms so just asssert on presence here
assert msg["properties"]["$python_runtime"] == mock.ANY
assert msg["properties"]["$python_version"] == mock.ANY
assert msg["properties"]["$os"] == mock.ANY
assert msg["properties"]["$os_version"] == mock.ANY
def test_basic_capture_with_uuid(self):
client = self.client
@@ -84,6 +91,177 @@ class TestClient(unittest.TestCase):
self.assertEqual(msg["properties"]["$lib"], "posthog-python")
self.assertEqual(msg["properties"]["$lib_version"], VERSION)
def test_basic_super_properties(self):
client = Client(FAKE_TEST_API_KEY, super_properties={"source": "repo-name"})
_, msg = client.capture("distinct_id", "python test event")
client.flush()
self.assertEqual(msg["event"], "python test event")
self.assertEqual(msg["properties"]["source"], "repo-name")
_, msg = client.identify("distinct_id", {"trait": "value"})
client.flush()
self.assertEqual(msg["$set"]["trait"], "value")
self.assertEqual(msg["properties"]["source"], "repo-name")
def test_basic_capture_exception(self):
with mock.patch.object(Client, "capture", return_value=None) as patch_capture:
client = self.client
exception = Exception("test exception")
client.capture_exception(exception, distinct_id="distinct_id")
self.assertTrue(patch_capture.called)
capture_call = patch_capture.call_args[0]
self.assertEqual(capture_call[0], "distinct_id")
self.assertEqual(capture_call[1], "$exception")
self.assertEqual(
capture_call[2],
{
"$exception_type": "Exception",
"$exception_message": "test exception",
"$exception_list": [
{
"mechanism": {"type": "generic", "handled": True},
"module": None,
"type": "Exception",
"value": "test exception",
}
],
"$exception_personURL": "https://us.i.posthog.com/project/random_key/person/distinct_id",
},
)
def test_basic_capture_exception_with_distinct_id(self):
with mock.patch.object(Client, "capture", return_value=None) as patch_capture:
client = self.client
exception = Exception("test exception")
client.capture_exception(exception, "distinct_id")
self.assertTrue(patch_capture.called)
capture_call = patch_capture.call_args[0]
self.assertEqual(capture_call[0], "distinct_id")
self.assertEqual(capture_call[1], "$exception")
self.assertEqual(
capture_call[2],
{
"$exception_type": "Exception",
"$exception_message": "test exception",
"$exception_list": [
{
"mechanism": {"type": "generic", "handled": True},
"module": None,
"type": "Exception",
"value": "test exception",
}
],
"$exception_personURL": "https://us.i.posthog.com/project/random_key/person/distinct_id",
},
)
def test_basic_capture_exception_with_correct_host_generation(self):
with mock.patch.object(Client, "capture", return_value=None) as patch_capture:
client = Client(FAKE_TEST_API_KEY, on_error=self.set_fail, host="https://aloha.com")
exception = Exception("test exception")
client.capture_exception(exception, "distinct_id")
self.assertTrue(patch_capture.called)
capture_call = patch_capture.call_args[0]
self.assertEqual(capture_call[0], "distinct_id")
self.assertEqual(capture_call[1], "$exception")
self.assertEqual(
capture_call[2],
{
"$exception_type": "Exception",
"$exception_message": "test exception",
"$exception_list": [
{
"mechanism": {"type": "generic", "handled": True},
"module": None,
"type": "Exception",
"value": "test exception",
}
],
"$exception_personURL": "https://aloha.com/project/random_key/person/distinct_id",
},
)
def test_basic_capture_exception_with_correct_host_generation_for_server_hosts(self):
with mock.patch.object(Client, "capture", return_value=None) as patch_capture:
client = Client(FAKE_TEST_API_KEY, on_error=self.set_fail, host="https://app.posthog.com")
exception = Exception("test exception")
client.capture_exception(exception, "distinct_id")
self.assertTrue(patch_capture.called)
capture_call = patch_capture.call_args[0]
self.assertEqual(capture_call[0], "distinct_id")
self.assertEqual(capture_call[1], "$exception")
self.assertEqual(
capture_call[2],
{
"$exception_type": "Exception",
"$exception_message": "test exception",
"$exception_list": [
{
"mechanism": {"type": "generic", "handled": True},
"module": None,
"type": "Exception",
"value": "test exception",
}
],
"$exception_personURL": "https://app.posthog.com/project/random_key/person/distinct_id",
},
)
def test_basic_capture_exception_with_no_exception_given(self):
with mock.patch.object(Client, "capture", return_value=None) as patch_capture:
client = self.client
try:
raise Exception("test exception")
except Exception:
client.capture_exception(distinct_id="distinct_id")
self.assertTrue(patch_capture.called)
capture_call = patch_capture.call_args[0]
self.assertEqual(capture_call[0], "distinct_id")
self.assertEqual(capture_call[1], "$exception")
self.assertEqual(capture_call[2]["$exception_type"], "Exception")
self.assertEqual(capture_call[2]["$exception_message"], "test exception")
self.assertEqual(capture_call[2]["$exception_list"][0]["mechanism"]["type"], "generic")
self.assertEqual(capture_call[2]["$exception_list"][0]["mechanism"]["handled"], True)
self.assertEqual(capture_call[2]["$exception_list"][0]["module"], None)
self.assertEqual(capture_call[2]["$exception_list"][0]["type"], "Exception")
self.assertEqual(capture_call[2]["$exception_list"][0]["value"], "test exception")
self.assertEqual(
capture_call[2]["$exception_list"][0]["stacktrace"]["type"],
"raw",
)
self.assertEqual(
capture_call[2]["$exception_list"][0]["stacktrace"]["frames"][0]["filename"],
"posthog/test/test_client.py",
)
self.assertEqual(
capture_call[2]["$exception_list"][0]["stacktrace"]["frames"][0]["function"],
"test_basic_capture_exception_with_no_exception_given",
)
self.assertEqual(
capture_call[2]["$exception_list"][0]["stacktrace"]["frames"][0]["module"], "posthog.test.test_client"
)
self.assertEqual(capture_call[2]["$exception_list"][0]["stacktrace"]["frames"][0]["in_app"], True)
def test_basic_capture_exception_with_no_exception_happening(self):
with mock.patch.object(Client, "capture", return_value=None) as patch_capture:
with self.assertLogs("posthog", level="WARNING") as logs:
client = self.client
client.capture_exception()
self.assertFalse(patch_capture.called)
self.assertEqual(
logs.output[0],
"WARNING:posthog:No exception information available",
)
@mock.patch("posthog.client.decide")
def test_basic_capture_with_feature_flags(self, patch_decide):
patch_decide.return_value = {"featureFlags": {"beta-feature": "random-variant"}}
@@ -114,7 +292,6 @@ class TestClient(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature-local",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -143,7 +320,6 @@ class TestClient(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "person-flag",
"is_simple_flag": True,
"active": True,
"filters": {
"groups": [
@@ -166,7 +342,6 @@ class TestClient(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "false-flag",
"is_simple_flag": True,
"active": True,
"filters": {
"groups": [
@@ -209,6 +384,25 @@ class TestClient(unittest.TestCase):
assert "$feature/false-flag" not in msg["properties"]
assert "$active_feature_flags" not in msg["properties"]
@mock.patch("posthog.client.get")
def test_load_feature_flags_quota_limited(self, patch_get):
mock_response = {
"type": "quota_limited",
"detail": "You have exceeded your feature flag request quota",
"code": "payment_required",
}
patch_get.side_effect = APIError(402, mock_response["detail"])
client = Client(FAKE_TEST_API_KEY, personal_api_key="test")
with self.assertLogs("posthog", level="WARNING") as logs:
client._load_feature_flags()
self.assertEqual(client.feature_flags, [])
self.assertEqual(client.feature_flags_by_key, {})
self.assertEqual(client.group_type_mapping, {})
self.assertEqual(client.cohorts, {})
self.assertIn("PostHog feature flags quota limited", logs.output[0])
@mock.patch("posthog.client.decide")
def test_dont_override_capture_with_local_flags(self, patch_decide):
patch_decide.return_value = {"featureFlags": {"beta-feature": "random-variant"}}
@@ -218,7 +412,6 @@ class TestClient(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature-local",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -247,7 +440,6 @@ class TestClient(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "person-flag",
"is_simple_flag": True,
"active": True,
"filters": {
"groups": [
@@ -314,7 +506,7 @@ class TestClient(unittest.TestCase):
self.assertEqual(patch_decide.call_count, 1)
patch_decide.assert_called_with(
"random_key",
"https://us-api.i.posthog.com",
"https://us.i.posthog.com",
timeout=3,
distinct_id="distinct_id",
groups={},
@@ -356,7 +548,7 @@ class TestClient(unittest.TestCase):
self.assertEqual(patch_decide.call_count, 1)
patch_decide.assert_called_with(
"random_key",
"https://us-api.i.posthog.com",
"https://us.i.posthog.com",
timeout=12,
distinct_id="distinct_id",
groups={},
@@ -403,16 +595,14 @@ class TestClient(unittest.TestCase):
"distinct_id",
"python test event",
{"property": "value"},
{"ip": "192.168.0.1"},
datetime(2014, 9, 3),
"new-uuid",
timestamp=datetime(2014, 9, 3),
uuid="new-uuid",
)
self.assertTrue(success)
self.assertEqual(msg["timestamp"], "2014-09-03T00:00:00+00:00")
self.assertEqual(msg["properties"]["property"], "value")
self.assertEqual(msg["context"]["ip"], "192.168.0.1")
self.assertEqual(msg["event"], "python test event")
self.assertEqual(msg["properties"]["$lib"], "posthog-python")
self.assertEqual(msg["properties"]["$lib_version"], VERSION)
@@ -445,13 +635,12 @@ class TestClient(unittest.TestCase):
def test_advanced_identify(self):
client = self.client
success, msg = client.identify(
"distinct_id", {"trait": "value"}, {"ip": "192.168.0.1"}, datetime(2014, 9, 3), "new-uuid"
"distinct_id", {"trait": "value"}, timestamp=datetime(2014, 9, 3), uuid="new-uuid"
)
self.assertTrue(success)
self.assertEqual(msg["timestamp"], "2014-09-03T00:00:00+00:00")
self.assertEqual(msg["context"]["ip"], "192.168.0.1")
self.assertEqual(msg["$set"]["trait"], "value")
self.assertEqual(msg["properties"]["$lib"], "posthog-python")
self.assertEqual(msg["properties"]["$lib_version"], VERSION)
@@ -473,14 +662,11 @@ class TestClient(unittest.TestCase):
def test_advanced_set(self):
client = self.client
success, msg = client.set(
"distinct_id", {"trait": "value"}, {"ip": "192.168.0.1"}, datetime(2014, 9, 3), "new-uuid"
)
success, msg = client.set("distinct_id", {"trait": "value"}, timestamp=datetime(2014, 9, 3), uuid="new-uuid")
self.assertTrue(success)
self.assertEqual(msg["timestamp"], "2014-09-03T00:00:00+00:00")
self.assertEqual(msg["context"]["ip"], "192.168.0.1")
self.assertEqual(msg["$set"]["trait"], "value")
self.assertEqual(msg["properties"]["$lib"], "posthog-python")
self.assertEqual(msg["properties"]["$lib_version"], VERSION)
@@ -503,13 +689,12 @@ class TestClient(unittest.TestCase):
def test_advanced_set_once(self):
client = self.client
success, msg = client.set_once(
"distinct_id", {"trait": "value"}, {"ip": "192.168.0.1"}, datetime(2014, 9, 3), "new-uuid"
"distinct_id", {"trait": "value"}, timestamp=datetime(2014, 9, 3), uuid="new-uuid"
)
self.assertTrue(success)
self.assertEqual(msg["timestamp"], "2014-09-03T00:00:00+00:00")
self.assertEqual(msg["context"]["ip"], "192.168.0.1")
self.assertEqual(msg["$set_once"]["trait"], "value")
self.assertEqual(msg["properties"]["$lib"], "posthog-python")
self.assertEqual(msg["properties"]["$lib_version"], VERSION)
@@ -537,9 +722,28 @@ class TestClient(unittest.TestCase):
self.assertTrue(isinstance(msg["timestamp"], str))
self.assertIsNone(msg.get("uuid"))
def test_basic_group_identify_with_distinct_id(self):
success, msg = self.client.group_identify("organization", "id:5", distinct_id="distinct_id")
self.assertTrue(success)
self.assertEqual(msg["event"], "$groupidentify")
self.assertEqual(msg["distinct_id"], "distinct_id")
self.assertEqual(
msg["properties"],
{
"$group_type": "organization",
"$group_key": "id:5",
"$group_set": {},
"$lib": "posthog-python",
"$lib_version": VERSION,
"$geoip_disable": True,
},
)
self.assertTrue(isinstance(msg["timestamp"], str))
self.assertIsNone(msg.get("uuid"))
def test_advanced_group_identify(self):
success, msg = self.client.group_identify(
"organization", "id:5", {"trait": "value"}, {"ip": "192.168.0.1"}, datetime(2014, 9, 3), "new-uuid"
"organization", "id:5", {"trait": "value"}, timestamp=datetime(2014, 9, 3), uuid="new-uuid"
)
self.assertTrue(success)
@@ -557,7 +761,33 @@ class TestClient(unittest.TestCase):
},
)
self.assertEqual(msg["timestamp"], "2014-09-03T00:00:00+00:00")
self.assertEqual(msg["context"]["ip"], "192.168.0.1")
def test_advanced_group_identify_with_distinct_id(self):
success, msg = self.client.group_identify(
"organization",
"id:5",
{"trait": "value"},
timestamp=datetime(2014, 9, 3),
uuid="new-uuid",
distinct_id="distinct_id",
)
self.assertTrue(success)
self.assertEqual(msg["event"], "$groupidentify")
self.assertEqual(msg["distinct_id"], "distinct_id")
self.assertEqual(
msg["properties"],
{
"$group_type": "organization",
"$group_key": "id:5",
"$group_set": {"trait": "value"},
"$lib": "posthog-python",
"$lib_version": VERSION,
"$geoip_disable": True,
},
)
self.assertEqual(msg["timestamp"], "2014-09-03T00:00:00+00:00")
def test_basic_alias(self):
client = self.client
@@ -593,15 +823,13 @@ class TestClient(unittest.TestCase):
"distinct_id",
"https://posthog.com/contact",
{"property": "value"},
{"ip": "192.168.0.1"},
datetime(2014, 9, 3),
"new-uuid",
timestamp=datetime(2014, 9, 3),
uuid="new-uuid",
)
self.assertTrue(success)
self.assertEqual(msg["timestamp"], "2014-09-03T00:00:00+00:00")
self.assertEqual(msg["context"]["ip"], "192.168.0.1")
self.assertEqual(msg["properties"]["$current_url"], "https://posthog.com/contact")
self.assertEqual(msg["properties"]["property"], "value")
self.assertEqual(msg["properties"]["$lib"], "posthog-python")
@@ -784,7 +1012,7 @@ class TestClient(unittest.TestCase):
client.get_feature_flag("random_key", "some_id", disable_geoip=True)
patch_decide.assert_called_with(
"random_key",
"https://us-api.i.posthog.com",
"https://us.i.posthog.com",
timeout=3,
distinct_id="some_id",
groups={},
@@ -796,7 +1024,7 @@ class TestClient(unittest.TestCase):
client.feature_enabled("random_key", "feature_enabled_distinct_id", disable_geoip=True)
patch_decide.assert_called_with(
"random_key",
"https://us-api.i.posthog.com",
"https://us.i.posthog.com",
timeout=3,
distinct_id="feature_enabled_distinct_id",
groups={},
@@ -808,7 +1036,7 @@ class TestClient(unittest.TestCase):
client.get_all_flags_and_payloads("all_flags_payloads_id")
patch_decide.assert_called_with(
"random_key",
"https://us-api.i.posthog.com",
"https://us.i.posthog.com",
timeout=3,
distinct_id="all_flags_payloads_id",
groups={},
@@ -825,7 +1053,7 @@ class TestClient(unittest.TestCase):
patch_get.return_value.raiseError.side_effect = raise_effect
client = Client(FAKE_TEST_API_KEY, personal_api_key="test")
client.feature_flags = [{"key": "example", "is_simple_flag": False}]
client.feature_flags = [{"key": "example"}]
self.assertFalse(client.feature_enabled("example", "distinct_id"))
@@ -895,3 +1123,92 @@ class TestClient(unittest.TestCase):
group_properties={},
disable_geoip=False,
)
@parameterized.expand(
[
# name, sys_platform, version_info, expected_runtime, expected_version, expected_os, expected_os_version, platform_method, platform_return, distro_info
(
"macOS",
"darwin",
(3, 8, 10),
"MockPython",
"3.8.10",
"Mac OS X",
"10.15.7",
"mac_ver",
("10.15.7", "", ""),
None,
),
(
"Windows",
"win32",
(3, 8, 10),
"MockPython",
"3.8.10",
"Windows",
"10",
"win32_ver",
("10", "", "", ""),
None,
),
(
"Linux",
"linux",
(3, 8, 10),
"MockPython",
"3.8.10",
"Linux",
"20.04",
None,
None,
{"version": "20.04"},
),
]
)
def test_mock_system_context(
self,
_name,
sys_platform,
version_info,
expected_runtime,
expected_version,
expected_os,
expected_os_version,
platform_method,
platform_return,
distro_info,
):
"""Test that we can mock platform and sys for testing system_context"""
with mock.patch("posthog.client.platform") as mock_platform:
with mock.patch("posthog.client.sys") as mock_sys:
# Set up common mocks
mock_platform.python_implementation.return_value = expected_runtime
mock_sys.version_info = version_info
mock_sys.platform = sys_platform
# Set up platform-specific mocks
if platform_method:
getattr(mock_platform, platform_method).return_value = platform_return
# Special handling for Linux which uses distro module
if sys_platform == "linux":
# Directly patch the get_os_info function to return our expected values
with mock.patch("posthog.client.get_os_info", return_value=(expected_os, expected_os_version)):
from posthog.client import system_context
context = system_context()
else:
# Get system context for non-Linux platforms
from posthog.client import system_context
context = system_context()
# Verify results
expected_context = {
"$python_runtime": expected_runtime,
"$python_version": expected_version,
"$os": expected_os,
"$os_version": expected_os_version,
}
assert context == expected_context
+63
View File
@@ -0,0 +1,63 @@
import subprocess
import sys
from textwrap import dedent
import pytest
def test_excepthook(tmpdir):
app = tmpdir.join("app.py")
app.write(
dedent(
"""
from posthog import Posthog
posthog = Posthog('phc_x', host='https://eu.i.posthog.com', enable_exception_autocapture=True, debug=True, on_error=lambda e, batch: print('error handling batch: ', e, batch))
# frame_value = "LOL"
1/0
"""
)
)
with pytest.raises(subprocess.CalledProcessError) as excinfo:
subprocess.check_output([sys.executable, str(app)], stderr=subprocess.STDOUT)
output = excinfo.value.output
assert b"ZeroDivisionError" in output
assert b"LOL" in output
assert b"DEBUG:posthog:data uploaded successfully" in output
assert (
b'"$exception_list": [{"mechanism": {"type": "generic", "handled": true}, "module": null, "type": "ZeroDivisionError", "value": "division by zero", "stacktrace": {"frames": [{"platform": "python", "filename": "app.py", "abs_path"'
in output
)
def test_trying_to_use_django_integration(tmpdir):
app = tmpdir.join("app.py")
app.write(
dedent(
"""
from posthog import Posthog, Integrations
posthog = Posthog('phc_x', host='https://eu.i.posthog.com', enable_exception_autocapture=True, exception_autocapture_integrations=[Integrations.Django], debug=True, on_error=lambda e, batch: print('error handling batch: ', e, batch))
# frame_value = "LOL"
1/0
"""
)
)
with pytest.raises(subprocess.CalledProcessError) as excinfo:
subprocess.check_output([sys.executable, str(app)], stderr=subprocess.STDOUT)
output = excinfo.value.output
assert b"ZeroDivisionError" in output
assert b"LOL" in output
assert b"DEBUG:posthog:data uploaded successfully" in output
assert (
b'"$exception_list": [{"mechanism": {"type": "generic", "handled": true}, "module": null, "type": "ZeroDivisionError", "value": "division by zero", "stacktrace": {"frames": [{"platform": "python", "filename": "app.py", "abs_path"'
in output
)
+333 -62
View File
@@ -38,7 +38,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "person-flag",
"is_simple_flag": True,
"active": True,
"filters": {
"groups": [
@@ -69,6 +68,59 @@ class TestLocalEvaluation(unittest.TestCase):
self.assertTrue(feature_flag_match)
self.assertFalse(not_feature_flag_match)
def test_case_insensitive_matching(self):
self.client.feature_flags = [
{
"id": 1,
"name": "Beta Feature",
"key": "person-flag",
"is_simple_flag": True,
"active": True,
"filters": {
"groups": [
{
"properties": [
{
"key": "location",
"operator": "exact",
"value": ["Straße"],
"type": "person",
}
],
"rollout_percentage": 100,
},
{
"properties": [
{
"key": "star",
"operator": "exact",
"value": ["ſun"],
"type": "person",
}
],
"rollout_percentage": 100,
},
],
},
}
]
self.assertTrue(
self.client.get_feature_flag("person-flag", "some-distinct-id", person_properties={"location": "straße"})
)
self.assertTrue(
self.client.get_feature_flag("person-flag", "some-distinct-id", person_properties={"location": "strasse"})
)
self.assertTrue(
self.client.get_feature_flag("person-flag", "some-distinct-id", person_properties={"star": "ſun"})
)
self.assertTrue(
self.client.get_feature_flag("person-flag", "some-distinct-id", person_properties={"star": "sun"})
)
@mock.patch("posthog.client.decide")
@mock.patch("posthog.client.get")
def test_flag_group_properties(self, patch_get, patch_decide):
@@ -77,7 +129,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "group-flag",
"is_simple_flag": True,
"active": True,
"filters": {
"aggregation_group_type_index": 0,
@@ -170,7 +221,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "complex-flag",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -286,7 +336,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": True,
"active": True,
"filters": {
"groups": [
@@ -301,7 +350,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "beta-feature2",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -343,7 +391,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": True,
"active": True,
"filters": {
"groups": [
@@ -358,7 +405,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "beta-feature2",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -410,7 +456,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": True,
"active": True,
"filters": {
"groups": [
@@ -457,7 +502,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -472,7 +516,7 @@ class TestLocalEvaluation(unittest.TestCase):
}
]
# decide called always because experience_continuity is set
self.assertTrue(client.get_feature_flag("beta-feature", "distinct_id"), "decide-fallback-value")
self.assertEqual(client.get_feature_flag("beta-feature", "distinct_id"), "decide-fallback-value")
self.assertEqual(patch_decide.call_count, 1)
@mock.patch.object(Client, "capture")
@@ -487,7 +531,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -503,7 +546,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "disabled-feature",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -518,7 +560,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 3,
"name": "Beta Feature",
"key": "beta-feature2",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -551,7 +592,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -570,7 +610,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "disabled-feature",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -588,7 +627,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 3,
"name": "Beta Feature",
"key": "beta-feature2",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -654,7 +692,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -670,7 +707,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "disabled-feature",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -696,7 +732,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -715,7 +750,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "disabled-feature",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -751,7 +785,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -767,7 +800,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "disabled-feature",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -782,7 +814,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 3,
"name": "Beta Feature",
"key": "beta-feature2",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -814,7 +845,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -833,7 +863,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "disabled-feature",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -851,7 +880,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 3,
"name": "Beta Feature",
"key": "beta-feature2",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -888,7 +916,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -904,7 +931,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "disabled-feature",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -927,7 +953,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": False,
"rollout_percentage": 100,
"filters": {
@@ -943,7 +968,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "disabled-feature",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -960,6 +984,61 @@ class TestLocalEvaluation(unittest.TestCase):
self.assertEqual(patch_decide.call_count, 0)
self.assertEqual(patch_capture.call_count, 0)
@mock.patch("posthog.client.decide")
@mock.patch("posthog.client.get")
def test_feature_flags_local_evaluation_None_values(self, patch_get, patch_decide):
client = Client(FAKE_TEST_API_KEY, personal_api_key=FAKE_TEST_API_KEY)
client.feature_flags = [
{
id: 1,
"name": "Beta Feature",
"key": "beta-feature",
"active": True,
"filters": {
"groups": [
{
"variant": None,
"properties": [
{"key": "latestBuildVersion", "type": "person", "value": ".+", "operator": "regex"},
{"key": "latestBuildVersionMajor", "type": "person", "value": "23", "operator": "gt"},
{"key": "latestBuildVersionMinor", "type": "person", "value": "31", "operator": "gt"},
{"key": "latestBuildVersionPatch", "type": "person", "value": "0", "operator": "gt"},
],
"rollout_percentage": 100,
}
],
},
},
]
feature_flag_match = client.get_feature_flag(
"beta-feature",
"some-distinct-id",
person_properties={
"latestBuildVersion": None,
"latestBuildVersionMajor": None,
"latestBuildVersionMinor": None,
"latestBuildVersionPatch": None,
},
)
self.assertEqual(feature_flag_match, False)
self.assertEqual(patch_decide.call_count, 0)
self.assertEqual(patch_get.call_count, 0)
feature_flag_match = client.get_feature_flag(
"beta-feature",
"some-distinct-id",
person_properties={
"latestBuildVersion": "24.32.1",
"latestBuildVersionMajor": "24",
"latestBuildVersionMinor": "32",
"latestBuildVersionPatch": "1",
},
)
self.assertEqual(feature_flag_match, True)
@mock.patch("posthog.client.decide")
@mock.patch("posthog.client.get")
def test_feature_flags_local_evaluation_for_cohorts(self, patch_get, patch_decide):
@@ -969,7 +1048,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -1040,7 +1118,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 2,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -1153,7 +1230,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": True,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -1178,7 +1254,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": True,
"active": True,
"rollout_percentage": 0,
"filters": {
@@ -1203,7 +1278,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": True,
"active": True,
"rollout_percentage": None,
"filters": {
@@ -1227,7 +1301,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": True,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -1251,7 +1324,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -1276,7 +1348,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": True,
"active": True,
"filters": {
"groups": [
@@ -1298,7 +1369,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -1364,7 +1434,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -1405,7 +1474,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -1457,7 +1525,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -1498,7 +1565,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -1541,7 +1607,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "person-flag",
"is_simple_flag": True,
"active": True,
"filters": {
"groups": [
@@ -1578,9 +1643,10 @@ class TestLocalEvaluation(unittest.TestCase):
)
self.assertEqual(patch_decide.call_count, 0)
@mock.patch.object(Client, "capture")
@mock.patch("posthog.client.decide")
def test_boolean_feature_flag_payload_decide(self, patch_decide):
patch_decide.return_value = {"featureFlagPayloads": {"person-flag": 300}}
def test_boolean_feature_flag_payload_decide(self, patch_decide, patch_capture):
patch_decide.return_value = {"featureFlags": {"person-flag": True}, "featureFlagPayloads": {"person-flag": 300}}
self.assertEqual(
self.client.get_feature_flag_payload(
"person-flag", "some-distinct-id", person_properties={"region": "USA"}
@@ -1595,6 +1661,8 @@ class TestLocalEvaluation(unittest.TestCase):
300,
)
self.assertEqual(patch_decide.call_count, 2)
self.assertEqual(patch_capture.call_count, 1)
patch_capture.reset_mock()
@mock.patch("posthog.client.decide")
def test_multivariate_feature_flag_payloads(self, patch_decide):
@@ -1602,7 +1670,6 @@ class TestLocalEvaluation(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "beta-feature",
"is_simple_flag": False,
"active": True,
"rollout_percentage": 100,
"filters": {
@@ -1714,7 +1781,7 @@ class TestMatchProperties(unittest.TestCase):
self.assertTrue(match_property(property_a, {"key": "value"}))
self.assertTrue(match_property(property_a, {"key": "value2"}))
self.assertTrue(match_property(property_a, {"key": ""}))
self.assertTrue(match_property(property_a, {"key": None}))
self.assertFalse(match_property(property_a, {"key": None}))
with self.assertRaises(InconclusiveMatchError):
match_property(property_a, {"key2": "value"})
@@ -1980,20 +2047,20 @@ class TestMatchProperties(unittest.TestCase):
self.assertTrue(match_property(property_a, {"key": "non"}))
property_b = self.property(key="key", value=None, operator="is_set")
self.assertTrue(match_property(property_b, {"key": None}))
self.assertFalse(match_property(property_b, {"key": None}))
property_c = self.property(key="key", value="no", operator="icontains")
self.assertTrue(match_property(property_c, {"key": None}))
self.assertFalse(match_property(property_c, {"key": None}))
self.assertFalse(match_property(property_c, {"key": "smh"}))
property_d = self.property(key="key", value="No", operator="regex")
self.assertTrue(match_property(property_d, {"key": None}))
self.assertFalse(match_property(property_d, {"key": None}))
property_d_lower_case = self.property(key="key", value="no", operator="regex")
self.assertFalse(match_property(property_d_lower_case, {"key": None}))
property_e = self.property(key="key", value=1, operator="gt")
self.assertTrue(match_property(property_e, {"key": None}))
self.assertFalse(match_property(property_e, {"key": None}))
property_f = self.property(key="key", value=1, operator="lt")
self.assertFalse(match_property(property_f, {"key": None}))
@@ -2002,15 +2069,13 @@ class TestMatchProperties(unittest.TestCase):
self.assertFalse(match_property(property_g, {"key": None}))
property_h = self.property(key="key", value="Oo", operator="lte")
self.assertTrue(match_property(property_h, {"key": None}))
self.assertFalse(match_property(property_h, {"key": None}))
property_i = self.property(key="key", value="2022-05-01", operator="is_date_before")
with self.assertRaises(InconclusiveMatchError):
self.assertFalse(match_property(property_i, {"key": None}))
self.assertFalse(match_property(property_i, {"key": None}))
property_j = self.property(key="key", value="2022-05-01", operator="is_date_after")
with self.assertRaises(InconclusiveMatchError):
self.assertFalse(match_property(property_j, {"key": None}))
self.assertFalse(match_property(property_j, {"key": None}))
property_k = self.property(key="key", value="2022-05-01", operator="is_date_before")
with self.assertRaises(InconclusiveMatchError):
@@ -2182,7 +2247,6 @@ class TestCaptureCalls(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "complex-flag",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -2282,6 +2346,136 @@ class TestCaptureCalls(unittest.TestCase):
disable_geoip=None,
)
@mock.patch("posthog.client.decide")
def test_capture_is_called_but_does_not_add_all_flags(self, patch_decide):
patch_decide.return_value = {"featureFlags": {"decide-flag": "decide-value"}}
client = Client(FAKE_TEST_API_KEY, personal_api_key=FAKE_TEST_API_KEY)
client.feature_flags = [
{
"id": 1,
"name": "Beta Feature",
"key": "complex-flag",
"active": True,
"filters": {
"groups": [
{
"properties": [{"key": "region", "value": "USA"}],
"rollout_percentage": 100,
},
],
},
},
{
"id": 2,
"name": "Gamma Feature",
"key": "simple-flag",
"active": True,
"filters": {
"groups": [
{
"properties": [],
"rollout_percentage": 100,
},
],
},
},
]
self.assertTrue(
client.get_feature_flag("complex-flag", "some-distinct-id", person_properties={"region": "USA"})
)
# Grab the capture message that was just added to the queue
msg = client.queue.get(block=False)
assert msg["event"] == "$feature_flag_called"
assert msg["properties"]["$feature_flag"] == "complex-flag"
assert msg["properties"]["$feature_flag_response"] is True
assert msg["properties"]["locally_evaluated"] is True
assert msg["properties"]["$feature/complex-flag"] is True
assert "$feature/simple-flag" not in msg["properties"]
assert "$active_feature_flags" not in msg["properties"]
@mock.patch.object(Client, "capture")
@mock.patch("posthog.client.decide")
def test_capture_is_called_in_get_feature_flag_payload(self, patch_decide, patch_capture):
patch_decide.return_value = {
"featureFlags": {"person-flag": True},
"featureFlagPayloads": {"person-flag": 300},
}
client = Client(api_key=FAKE_TEST_API_KEY, personal_api_key=FAKE_TEST_API_KEY)
client.feature_flags = [
{
"id": 1,
"name": "Beta Feature",
"key": "person-flag",
"active": True,
"filters": {
"groups": [
{
"properties": [{"key": "region", "value": "USA"}],
"rollout_percentage": 100,
}
],
},
}
]
# Call get_feature_flag_payload with match_value=None to trigger get_feature_flag
client.get_feature_flag_payload(
key="person-flag", distinct_id="some-distinct-id", person_properties={"region": "USA", "name": "Aloha"}
)
# Assert that capture was called once, with the correct parameters
self.assertEqual(patch_capture.call_count, 1)
patch_capture.assert_called_with(
"some-distinct-id",
"$feature_flag_called",
{
"$feature_flag": "person-flag",
"$feature_flag_response": True,
"$feature_flag_payload": 300,
"locally_evaluated": False,
"$feature/person-flag": True,
},
groups={},
disable_geoip=None,
)
# Reset mocks for further tests
patch_capture.reset_mock()
patch_decide.reset_mock()
# Call get_feature_flag_payload again for the same user; capture should not be called again because we've already reported an event for this distinct_id + flag
client.get_feature_flag_payload(
key="person-flag", distinct_id="some-distinct-id", person_properties={"region": "USA", "name": "Aloha"}
)
self.assertEqual(patch_capture.call_count, 0)
patch_capture.reset_mock()
# Call get_feature_flag_payload for a different user; capture should be called
client.get_feature_flag_payload(
key="person-flag", distinct_id="some-distinct-id2", person_properties={"region": "USA", "name": "Aloha"}
)
self.assertEqual(patch_capture.call_count, 1)
patch_capture.assert_called_with(
"some-distinct-id2",
"$feature_flag_called",
{
"$feature_flag": "person-flag",
"$feature_flag_response": True,
"$feature_flag_payload": 300,
"locally_evaluated": False,
"$feature/person-flag": True,
},
groups={},
disable_geoip=None,
)
patch_capture.reset_mock()
@mock.patch.object(Client, "capture")
@mock.patch("posthog.client.decide")
def test_disable_geoip_get_flag_capture_call(self, patch_decide, patch_capture):
@@ -2292,7 +2486,6 @@ class TestCaptureCalls(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "complex-flag",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -2335,7 +2528,6 @@ class TestCaptureCalls(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "complex-flag",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [
@@ -2394,7 +2586,6 @@ class TestConsistency(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "simple-flag",
"is_simple_flag": True,
"active": True,
"filters": {
"groups": [{"properties": [], "rollout_percentage": 45}],
@@ -3422,7 +3613,6 @@ class TestConsistency(unittest.TestCase):
"id": 1,
"name": "Beta Feature",
"key": "multivariate-flag",
"is_simple_flag": False,
"active": True,
"filters": {
"groups": [{"properties": [], "rollout_percentage": 55}],
@@ -4450,3 +4640,84 @@ class TestConsistency(unittest.TestCase):
self.assertEqual(feature_flag_match, results[i])
else:
self.assertFalse(feature_flag_match)
@mock.patch("posthog.client.decide")
def test_feature_flag_case_sensitive(self, mock_decide):
mock_decide.return_value = {"featureFlags": {}} # Ensure decide returns empty flags
client = Client(api_key=FAKE_TEST_API_KEY, personal_api_key=FAKE_TEST_API_KEY)
client.feature_flags = [
{
"id": 1,
"key": "Beta-Feature",
"active": True,
"filters": {
"groups": [{"properties": [], "rollout_percentage": 100}],
},
}
]
# Test that flag evaluation is case-sensitive
self.assertTrue(client.feature_enabled("Beta-Feature", "user1"))
self.assertFalse(client.feature_enabled("beta-feature", "user1"))
self.assertFalse(client.feature_enabled("BETA-FEATURE", "user1"))
@mock.patch("posthog.client.decide")
def test_feature_flag_payload_case_sensitive(self, mock_decide):
mock_decide.return_value = {
"featureFlags": {"Beta-Feature": True},
"featureFlagPayloads": {"Beta-Feature": {"some": "value"}},
}
client = Client(api_key=FAKE_TEST_API_KEY, personal_api_key=FAKE_TEST_API_KEY)
client.feature_flags = [
{
"id": 1,
"key": "Beta-Feature",
"active": True,
"filters": {
"groups": [{"properties": [], "rollout_percentage": 100}],
"payloads": {
"true": {"some": "value"},
},
},
}
]
# Test that payload retrieval is case-sensitive
self.assertEqual(client.get_feature_flag_payload("Beta-Feature", "user1"), {"some": "value"})
self.assertIsNone(client.get_feature_flag_payload("beta-feature", "user1"))
self.assertIsNone(client.get_feature_flag_payload("BETA-FEATURE", "user1"))
@mock.patch("posthog.client.decide")
def test_feature_flag_case_sensitive_consistency(self, mock_decide):
mock_decide.return_value = {
"featureFlags": {"Beta-Feature": True},
"featureFlagPayloads": {"Beta-Feature": {"some": "value"}},
}
client = Client(api_key=FAKE_TEST_API_KEY, personal_api_key=FAKE_TEST_API_KEY)
client.feature_flags = [
{
"id": 1,
"key": "Beta-Feature",
"active": True,
"filters": {
"groups": [{"properties": [], "rollout_percentage": 100}],
"payloads": {
"true": {"some": "value"},
},
},
}
]
# Test that flag evaluation and payload retrieval are consistently case-sensitive
# Only exact match should work
self.assertTrue(client.feature_enabled("Beta-Feature", "user1"))
self.assertEqual(client.get_feature_flag_payload("Beta-Feature", "user1"), {"some": "value"})
# Different cases should not match
test_cases = ["beta-feature", "BETA-FEATURE", "bEtA-FeAtUrE"]
for case in test_cases:
self.assertFalse(client.feature_enabled(case, "user1"))
self.assertIsNone(client.get_feature_flag_payload(case, "user1"))
+39 -8
View File
@@ -2,10 +2,11 @@ import json
import unittest
from datetime import date, datetime
import mock
import pytest
import requests
from posthog.request import DatetimeSerializer, batch_post, determine_server_host
from posthog.request import DatetimeSerializer, QuotaLimitError, batch_post, decide, determine_server_host
from posthog.test.test_utils import TEST_API_KEY
@@ -44,6 +45,36 @@ class TestRequests(unittest.TestCase):
"key", batch=[{"distinct_id": "distinct_id", "event": "python event", "type": "track"}], timeout=0.0001
)
def test_quota_limited_response(self):
mock_response = requests.Response()
mock_response.status_code = 200
mock_response._content = json.dumps(
{
"quotaLimited": ["feature_flags"],
"featureFlags": {},
"featureFlagPayloads": {},
"errorsWhileComputingFlags": False,
}
).encode("utf-8")
with mock.patch("posthog.request._session.post", return_value=mock_response):
with self.assertRaises(QuotaLimitError) as cm:
decide("fake_key", "fake_host")
self.assertEqual(cm.exception.status, 200)
self.assertEqual(cm.exception.message, "Feature flags quota limited")
def test_normal_decide_response(self):
mock_response = requests.Response()
mock_response.status_code = 200
mock_response._content = json.dumps(
{"featureFlags": {"flag1": True}, "featureFlagPayloads": {}, "errorsWhileComputingFlags": False}
).encode("utf-8")
with mock.patch("posthog.request._session.post", return_value=mock_response):
response = decide("fake_key", "fake_host")
self.assertEqual(response["featureFlags"], {"flag1": True})
@pytest.mark.parametrize(
"host, expected",
@@ -55,13 +86,13 @@ class TestRequests(unittest.TestCase):
("https://us.posthog.com.rg.proxy.com", "https://us.posthog.com.rg.proxy.com"),
("app.posthog.com", "app.posthog.com"),
("eu.posthog.com", "eu.posthog.com"),
("https://app.posthog.com", "https://us-api.i.posthog.com"),
("https://eu.posthog.com", "https://eu-api.i.posthog.com"),
("https://us.posthog.com", "https://us-api.i.posthog.com"),
("https://app.posthog.com/", "https://us-api.i.posthog.com"),
("https://eu.posthog.com/", "https://eu-api.i.posthog.com"),
("https://us.posthog.com/", "https://us-api.i.posthog.com"),
(None, "https://us-api.i.posthog.com"),
("https://app.posthog.com", "https://us.i.posthog.com"),
("https://eu.posthog.com", "https://eu.i.posthog.com"),
("https://us.posthog.com", "https://us.i.posthog.com"),
("https://app.posthog.com/", "https://us.i.posthog.com"),
("https://eu.posthog.com/", "https://eu.i.posthog.com"),
("https://us.posthog.com/", "https://us.i.posthog.com"),
(None, "https://us.i.posthog.com"),
],
)
def test_routing_to_custom_host(host, expected):
+76 -1
View File
@@ -1,10 +1,14 @@
import unittest
from dataclasses import dataclass
from datetime import date, datetime, timedelta
from decimal import Decimal
from typing import Optional
from uuid import UUID
import six
from dateutil.tz import tzutc
from pydantic import BaseModel
from pydantic.v1 import BaseModel as BaseModelV1
from posthog import utils
@@ -53,7 +57,10 @@ class TestUtils(unittest.TestCase):
self.assertEqual(combined.keys(), pre_clean_keys)
# test UUID separately, as the UUID object doesn't equal its string representation according to Python
self.assertEqual(utils.clean(UUID("12345678123456781234567812345678")), "12345678-1234-5678-1234-567812345678")
self.assertEqual(
utils.clean(UUID("12345678123456781234567812345678")),
"12345678-1234-5678-1234-567812345678",
)
def test_clean_with_dates(self):
dict_with_dates = {
@@ -81,6 +88,74 @@ class TestUtils(unittest.TestCase):
self.assertEqual("http://posthog.io", utils.remove_trailing_slash("http://posthog.io/"))
self.assertEqual("http://posthog.io", utils.remove_trailing_slash("http://posthog.io"))
def test_clean_pydantic(self):
class ModelV2(BaseModel):
foo: str
bar: int
baz: Optional[str] = None
class ModelV1(BaseModelV1):
foo: int
bar: str
class NestedModel(BaseModel):
foo: ModelV2
self.assertEqual(utils.clean(ModelV2(foo="1", bar=2)), {"foo": "1", "bar": 2, "baz": None})
self.assertEqual(utils.clean(ModelV1(foo=1, bar="2")), {"foo": 1, "bar": "2"})
self.assertEqual(
utils.clean(NestedModel(foo=ModelV2(foo="1", bar=2, baz="3"))),
{"foo": {"foo": "1", "bar": 2, "baz": "3"}},
)
class Dummy:
def model_dump(self, required_param):
pass
# Skips a class with a defined non-Pydantic `model_dump` method.
self.assertEqual(utils.clean({"test": Dummy()}), {})
def test_clean_dataclass(self):
@dataclass
class InnerDataClass:
inner_foo: str
inner_bar: int
inner_uuid: UUID
inner_date: datetime
inner_optional: Optional[str] = None
@dataclass
class TestDataClass:
foo: str
bar: int
nested: InnerDataClass
self.assertEqual(
utils.clean(
TestDataClass(
foo="1",
bar=2,
nested=InnerDataClass(
inner_foo="3",
inner_bar=4,
inner_uuid=UUID("12345678123456781234567812345678"),
inner_date=datetime(2025, 1, 1),
),
)
),
{
"foo": "1",
"bar": 2,
"nested": {
"inner_foo": "3",
"inner_bar": 4,
"inner_uuid": "12345678-1234-5678-1234-567812345678",
"inner_date": datetime(2025, 1, 1),
"inner_optional": None,
},
},
)
class TestSizeLimitedDict(unittest.TestCase):
def test_size_limited_dict(self):
+64 -5
View File
@@ -2,6 +2,7 @@ import logging
import numbers
import re
from collections import defaultdict
from dataclasses import asdict, is_dataclass
from datetime import date, datetime, timezone
from decimal import Decimal
from uuid import UUID
@@ -51,14 +52,26 @@ def clean(item):
return float(item)
if isinstance(item, UUID):
return str(item)
elif isinstance(item, (six.string_types, bool, numbers.Number, datetime, date, type(None))):
if isinstance(item, (six.string_types, bool, numbers.Number, datetime, date, type(None))):
return item
elif isinstance(item, (set, list, tuple)):
if isinstance(item, (set, list, tuple)):
return _clean_list(item)
elif isinstance(item, dict):
# Pydantic model
try:
# v2+
if hasattr(item, "model_dump") and callable(item.model_dump):
item = item.model_dump()
# v1
elif hasattr(item, "dict") and callable(item.dict):
item = item.dict()
except TypeError as e:
log.debug(f"Could not serialize Pydantic-like model: {e}")
pass
if isinstance(item, dict):
return _clean_dict(item)
else:
return _coerce_unicode(item)
if is_dataclass(item) and not isinstance(item, type):
return _clean_dataclass(item)
return _coerce_unicode(item)
def _clean_list(list_):
@@ -80,6 +93,12 @@ def _clean_dict(dict_):
return data
def _clean_dataclass(dataclass_):
data = asdict(dataclass_)
data = _clean_dict(data)
return data
def _coerce_unicode(cmplx):
try:
item = cmplx.decode("utf-8", "strict")
@@ -115,3 +134,43 @@ def convert_to_datetime_aware(date_obj):
if date_obj.tzinfo is None:
date_obj = date_obj.replace(tzinfo=timezone.utc)
return date_obj
def str_icontains(source, search):
"""
Check if a string contains another string, ignoring case.
Args:
source: The string to search within
search: The substring to search for
Returns:
bool: True if search is a substring of source (case-insensitive), False otherwise
Examples:
>>> str_icontains("Hello World", "WORLD")
True
>>> str_icontains("Hello World", "python")
False
"""
return str(search).casefold() in str(source).casefold()
def str_iequals(value, comparand):
"""
Check if a string equals another string, ignoring case.
Args:
value: The string to compare
comparand: The string to compare with
Returns:
bool: True if value and comparand are equal (case-insensitive), False otherwise
Examples:
>>> str_iequals("Hello World", "hello world")
True
>>> str_iequals("Hello World", "hello")
False
"""
return str(value).casefold() == str(comparand).casefold()
+1 -1
View File
@@ -1,4 +1,4 @@
VERSION = "3.5.0"
VERSION = "3.21.0"
if __name__ == "__main__":
print(VERSION, end="") # noqa: T201
+3
View File
@@ -1,2 +1,5 @@
[bdist_wheel]
universal = 1
[tool:pytest]
asyncio_mode = auto
+53 -14
View File
@@ -14,18 +14,54 @@ long_description = """
PostHog is developer-friendly, self-hosted product analytics. posthog-python is the python package.
"""
install_requires = ["requests>=2.7,<3.0", "six>=1.5", "monotonic>=1.5", "backoff>=1.10.0", "python-dateutil>2.1"]
install_requires = [
"requests>=2.7,<3.0",
"six>=1.5",
"monotonic>=1.5",
"backoff>=1.10.0",
"python-dateutil>2.1",
"distro>=1.5.0", # Required for Linux OS detection in Python 3.9+
]
extras_require = {
"dev": [
"black",
"django-stubs",
"isort",
"flake8",
"flake8-print",
"lxml",
"mypy",
"mypy-baseline",
"types-mock",
"types-python-dateutil",
"types-requests",
"types-setuptools",
"types-six",
"pre-commit",
"pydantic",
],
"test": [
"mock>=2.0.0",
"freezegun==1.5.1",
"pylint",
"flake8",
"coverage",
"pytest",
"pytest-timeout",
"pytest-asyncio",
"django",
"openai",
"anthropic",
"langgraph",
"langchain-community>=0.2.0",
"langchain-openai>=0.2.0",
"langchain-anthropic>=0.2.0",
"pydantic",
"parameterized>=0.8.1",
],
"test": ["mock>=2.0.0", "freezegun==0.3.15", "pylint", "flake8", "coverage", "pytest", "pytest-timeout"],
"sentry": ["sentry-sdk", "django"],
"langchain": ["langchain>=0.2.0"],
}
setup(
@@ -37,7 +73,16 @@ setup(
maintainer="PostHog",
maintainer_email="hey@posthog.com",
test_suite="posthog.test.all",
packages=["posthog", "posthog.test", "posthog.sentry"],
packages=[
"posthog",
"posthog.ai",
"posthog.ai.langchain",
"posthog.ai.openai",
"posthog.ai.anthropic",
"posthog.test",
"posthog.sentry",
"posthog.exception_integrations",
],
license="MIT License",
install_requires=install_requires,
extras_require=extras_require,
@@ -49,16 +94,10 @@ setup(
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
"Programming Language :: Python",
"Programming Language :: Python :: 2",
"Programming Language :: Python :: 2.6",
"Programming Language :: Python :: 2.7",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.2",
"Programming Language :: Python :: 3.3",
"Programming Language :: Python :: 3.4",
"Programming Language :: Python :: 3.5",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
],
)
+21 -2
View File
@@ -14,7 +14,14 @@ long_description = """
PostHog is developer-friendly, self-hosted product analytics. posthog-python is the python package.
"""
install_requires = ["requests>=2.7,<3.0", "six>=1.5", "monotonic>=1.5", "backoff>=1.10.0", "python-dateutil>2.1"]
install_requires = [
"requests>=2.7,<3.0",
"six>=1.5",
"monotonic>=1.5",
"backoff>=1.10.0",
"python-dateutil>2.1",
"distro>=1.5.0", # Required for Linux OS detection in Python 3.9+
]
tests_require = ["mock>=2.0.0"]
@@ -27,7 +34,16 @@ setup(
maintainer="PostHog",
maintainer_email="hey@posthog.com",
test_suite="posthoganalytics.test.all",
packages=["posthoganalytics", "posthoganalytics.test", "posthoganalytics.sentry"],
packages=[
"posthoganalytics",
"posthoganalytics.ai",
"posthoganalytics.ai.langchain",
"posthoganalytics.ai.openai",
"posthoganalytics.ai.anthropic",
"posthoganalytics.test",
"posthoganalytics.sentry",
"posthoganalytics.exception_integrations",
],
license="MIT License",
install_requires=install_requires,
tests_require=tests_require,
@@ -53,5 +69,8 @@ setup(
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
],
)
-6
View File
@@ -24,7 +24,6 @@ parser.add_argument("--type", help="The posthog message type")
parser.add_argument("--distinct_id", help="the user id to send the event as")
parser.add_argument("--anonymousId", help="the anonymous user id to send the event as")
parser.add_argument("--context", help="additional context for the event (JSON-encoded)")
parser.add_argument("--event", help="the event name to send with the event")
parser.add_argument("--properties", help="the event properties to send (JSON-encoded)")
@@ -48,7 +47,6 @@ def capture():
options.event,
anonymous_id=options.anonymousId,
properties=json_hash(options.properties),
context=json_hash(options.context),
)
@@ -58,7 +56,6 @@ def page():
name=options.name,
anonymous_id=options.anonymousId,
properties=json_hash(options.properties),
context=json_hash(options.context),
)
@@ -67,7 +64,6 @@ def identify():
options.distinct_id,
anonymous_id=options.anonymousId,
traits=json_hash(options.traits),
context=json_hash(options.context),
)
@@ -75,7 +71,6 @@ def set_once():
posthog.set_once(
options.distinct_id,
properties=json_hash(options.traits),
context=json_hash(options.context),
)
@@ -83,7 +78,6 @@ def set():
posthog.set(
options.distinct_id,
properties=json_hash(options.traits),
context=json_hash(options.context),
)