This is an optional library you can install if you're working with Python. It uses an internal queue to make calls fast and non-blocking. It also batches requests and flushes asynchronously, making it perfect to use in any part of your web app or other server side application that needs performance.

Installation

pip install posthog

In your app, import the posthog library and set your api key and host before making any calls.

from posthog import Posthog

# The personal API key is necessary only if you want to use local evaluation of feature flags.
posthog = Posthog('<ph_project_api_key>', host='<ph_instance_address>', personal_api_key='<ph_personal_api_key>')

You can read more about the differences between the project and personal API keys in the dedicated API authentication section of the Docs.

Note: As a general rule of thumb, we do not recommend having API keys in plaintext. Setting it as an environment variable would be best.

You can find your keys in the 'Project Settings' page in PostHog.

To debug, you can toggle debug mode on:

posthog.debug = True

And to make sure no calls happen during your tests, you can disable them, like so:

if settings.TEST:
    posthog.disabled = True

Making Calls

Capture

Capture allows you to capture anything a user does within your system, which you can later use in PostHog to find patterns in usage, work out which features to improve or where people are giving up.

A capture call requires:

• distinct id which uniquely identifies your user
• event name to specify the event

• We recommend naming events with "[noun][verb]", such as movie played or movie updated, in order to easily identify what your events mean later on (we know this from experience).

Optionally you can submit:

• properties, which is a dictionary with any information you'd like to add
• timestamp, a datetime object for when the event happened. If this isn't submitted, it'll be set to the current time
• uuid, a unique uuid for the event, leave blank to autogenerate
• send_feature_flags, a boolean that determines whether to send current known feature flags with this event. This is useful when running experiments which depends on this event. However, this makes things slow. Read this tutorial for manually computing this information and speeding things up

For example:

posthog.capture('distinct id', 'movie played', {'movie_id': '123', 'category': 'romcom'})

or

posthog.capture('distinct id', event='movie played', properties={'movie_id': '123', 'category': 'romcom'}, timestamp=datetime.utcnow().replace(tzinfo=tzutc()))

Setting user properties via an event

To set properties on your users via an event, you can leverage the event properties $set and $set_once.

$set

Example

posthog.capture(
    'distinct id',
    event='movie played',
    properties={ '$set': { 'userProperty': 'value' } }
)

Usage

When capturing an event, you can pass a property called $set as an event property, and specify its value to be an object with properties to be set on the user that will be associated with the user who triggered the event.

$set_once

Example

posthog.capture(
    'distinct id',
    event='movie played',
    properties={ '$set_once': { 'userProperty': 'value' } }
)

Usage

$set_once works just like $set, except that it will only set the property if the user doesn't already have that property set.

Identify

We highly recommend reading our section on Identifying users to better understand how to correctly use this method.

Identify lets you add metadata to your users so you can easily identify who they are in PostHog, as well as do things like segment users by these properties.

An identify call requires:

• distinct id which uniquely identifies your user
• properties with a dict with any key:value pairs

For example:

posthog.identify('distinct id', {
    'email': 'dwayne@gmail.com',
    'name': 'Dwayne Johnson'
})

The most obvious place to make this call is whenever a user signs up, or when they update their information.

Alias

To connect whatever a user does before they sign up or log in with what they do after you need to make an alias call. This will allow you to answer questions like "Which marketing channels leads to users churning after a month?" or "What do users do on our website before signing up?"

In a purely back-end implementation, this means whenever an anonymous user does something, you'll want to send a session ID (Django, Flask) with the capture call. Then, when that users signs up, you want to do an alias call with the session ID and the newly created user ID.

The same concept applies for when a user logs in.

If you're using PostHog in the front-end and back-end, doing the identify call in the frontend will be enough.

An alias call requires:

• distinct id – the user id
• alias – the anonymous session distinct ID

For example:

posthog.alias('user:123', 'session:12345');

Feature flags

PostHog's Feature Flags allow you to safely deploy and roll back new features.

When using them with one of libraries, you should check if a feature flag is enabled and use the result to toggle functionality on and off in you application.

How to check if a flag is enabled

Note: Whenever we face an error computing the flag, the library returns None, instead of true, false, or a string variant value.

posthog.feature_enabled('beta-feature', 'distinct id')
# returns True or False or None

Example use case

Here's how you might send different users a different version of your homepage, for example:

def homepage(request):
    template = "new.html" if posthog.feature_enabled('new_ui', 'distinct id') else "old.html"
    return render_template(template, request=request)

Note: Feature flags are persistent for users across sessions. Read more about feature flag persistence on our dedicated page.

Get a flag value

If you're using multivariate feature flags, you can also get not just whether the flag is enabled, but what value its enabled to.

Note: Whenever we face an error computing the flag, the library returns None, instead of true, false, or a string variant value.

posthog.get_feature_flag('beta-feature', 'distinct id')
# returns string or True or False or None

Overriding server properties

Sometimes, you might want to evaluate feature flags using properties that haven't been ingested yet, or were set incorrectly earlier. You can do so by setting properties the flag depends on with these calls.

For example, if the beta-feature depends on the is_authorized property, and you know the value of the property, you can tell PostHog to use this property, like so:

posthog.get_feature_flag('beta-feature', 'distinct id', person_properties={'is_authorized': True})
# returns string or None

The same holds for groups. If you have a group name organisation, you can add properties like so:

posthog.get_feature_flag('beta-feature', 'distinct id', groups={'organisation': 'google'}, group_properties={'organisation': {'is_authorized': True})
# returns string or None

Default overridden properties

Before posthog-python v3.0, we added GeoIP properties to all incoming events by default. We also used these properties for feature flag evaluation, based on the IP address of the request. This isn't ideal since they are created based on your server IP address, rather than the user's, leading to incorrect location resolution.

As of posthog-python v3.0, the default now is to disregard the server IP, not add the GeoIP properties, and not use the values for feature flag evaluations.

You can go back to previous behaviour by doing setting the disable_geoip argument in your initialization to False:

posthog = Posthog('api_key', disable_geoip=False)

The list of properties that this overrides:

1. $geoip_city_name
2. $geoip_country_name
3. $geoip_country_code
4. $geoip_continent_name
5. $geoip_continent_code
6. $geoip_postal_code
7. $geoip_time_zone

You can also explicitly chose to override / not override properties for a single capture or feature flag request like so:

posthog.get_feature_flag("beta-feature", "distinct_id", disable_geoip=True|False)

posthog.capture('test id', 'test event', disable_geoip=True|False)

Getting all flag values

You can also get all known flag values as well. This is useful when you want to seed a frontend client with initial known flags. Like all methods above, this also takes optional person and group properties, if known.

posthog.get_all_flags('distinct id', groups={}, person_properties={'is_authorized': True}, group_properties={})
# returns dict of flag key and value pairs.

Feature Flag Payloads

Payloads allow you to retrieve a value that is associated with the matched flag. The value can be a string, boolean, number, dictionary, or array. This allows for custom configurations based on values defined in the posthog app.

posthog.get_feature_flag_payload('feature-flag-key', 'distinct id')

Local Evaluation

Note: To enable local evaluation of feature flags you must also set a personal_api_key when configuring the integration, as described in the Installation section.

Note: This feature requires version 2.0 of the library, which in turn requires a minimum PostHog version of 1.38

All feature flag evaluation requires an API request to your PostHog servers to get a response. However, where latency matters, you can evaluate flags locally. This is much faster, and requires two things to work:

1. The library must be initialised with a personal API key
2. You must know all person or group properties the flag depends on.

Then, the flag can be evaluated locally. The method signature looks exactly like above

posthog.get_feature_flag('beta-feature', 'distinct id', person_properties={'is_authorized': True})
# returns string or None

Note: New feature flag definitions are polled every 30 seconds by default, which means there will be up to a 30 second delay between you changing the flag definition, and it reflecting on your servers. You can change this default on the client by setting posthog.poll_interval = <value in seconds>.

This works for get_all_flags as well. It evaluates all flags locally if possible. If even one flag isn't locally evaluable, it falls back to decide.

posthog.get_all_flags('distinct id', groups={}, person_properties={'is_authorized': True}, group_properties={})
# returns dict of flag key and value pairs.

Restricting evaluation to local only

Sometimes, performance might matter to you so much that you never want an HTTP request roundtrip delay when computing flags. In this case, you can set the only_evaluate_locally parameter to true, which tries to compute flags only with the properties it has. If it fails to compute a flag, it returns None, instead of going to PostHog's servers to get the value.

Cohort expansion

To support feature flags that depend on cohorts locally as well, we translate the cohort definition into person properties, so that the person properties you set can be used to evaluate cohorts as well.

However, there are a few constraints here and we don't support doing this for arbitrary cohorts. Cohorts won't be evaluated locally if:

1. They have non-person properties
2. There's more than one cohort in the feature flag definition.
3. The cohort in the feature flag is in the same group as another condition.
4. The cohort has nested AND-OR filters. Only simple cohorts that have a top level OR group, and inner level ANDs will be evaluated locally.

Note that this restriction is for local evaluation only. If you're hitting PostHog's servers, all of these cohorts will be evaluated as expected. Further, posthog-node v2.6.0 onwards, and posthog-python v2.4.0 onwards do not face this issue and can evaluate all cohorts locally.

Group analytics

Group analytics allows you to associate an event with a group (e.g. teams, organizations, etc.). Read the Group Analytics guide for more information.

Note: This is a paid feature and is not available on the open-source or free cloud plan. Learn more here.

• Capture an event and associate it with a group

posthog.capture('[distinct id]', 'some event', groups={'company': '42dlsfj23f'})

• Update properties on a group

posthog.group_identify('company', '42dlsfj23f', {
    'name': 'Awesome Inc.',
    'employees': 11
})

The name is a special property which is used in the PostHog UI for the name of the Group. If you don't specify a name property, the group ID will be used instead.

Sending page views

If you're aiming for a full back-end implementation of PostHog, you can send pageviews from your backend

posthog.capture('distinct id', '$pageview', {'$current_url': 'https://example.com'})

Django

For Django, you can do the initialisation of the key in the AppConfig, so that it's available everywhere.

in yourapp/apps.py

from django.apps import AppConfig
import posthog

class YourAppConfig(AppConfig):
    def ready(self):
        posthog.api_key = '<ph_project_api_key>'
        posthog.host = '<ph_instance_address>' # You can remove this line if you're using app.posthog.com

Then, anywhere else in your app you can do:

import posthog

def purchase(request):
    # example capture
    posthog.capture(request.user.pk, 'purchase', ...)

Integrations

Sentry

When using Sentry in Python, you can connect to PostHog in order to link Sentry errors to PostHog user profiles.

Example implementation

See the sentry_django_example project for a complete example.

import sentry_sdk
from sentry_sdk.integrations.django import DjangoIntegration
from posthog.sentry.posthog_integration import PostHogIntegration

PostHogIntegration.organization = "orgname"

sentry_sdk.init(
    dsn="https://examplePublicKey@o0.ingest.sentry.io/0",
    integrations=[DjangoIntegration(), PostHogIntegration()],
)

# Also set `posthog_distinct_id` tag
from sentry_sdk import configure_scope

with configure_scope() as scope:
    scope.set_tag('posthog_distinct_id', 'some distinct id')

Example implementation with Django

This can be made automatic in Django, by adding the following middleware and settings to settings.py:

MIDDLEWARE = [
    "posthog.sentry.django.PosthogDistinctIdMiddleware"
]

POSTHOG_DJANGO = {
    "distinct_id": lambda request: request.user and request.user.distinct_id
}

Alternative name

As our open source project PostHog shares the same module name, we created a special posthoganalytics package, mostly for internal use to avoid module collision. It is the exact same.

Thank you

This library is largely based on the analytics-python package.