Developing locally

❗️ This guide is intended only for development of PostHog itself. If you're looking to deploy PostHog for your product analytics needs, go to Self-host PostHog.

What does PostHog look like on the inside?

Before jumping into setup, let's dissect a PostHog.

The app itself is made up of 4 components that run simultaneously:

• Django server
• Celery worker (handles execution of background tasks)
• Node.js plugin server (handles event ingestion and apps/plugins)
• React frontend built with Node.js

These components rely on a few external services:

• ClickHouse – for storing big data (events, persons – analytics queries)
• Kafka – for queuing events for ingestion
• MinIO – for storing files (session recordings, file exports)
• PostgreSQL – for storing ordinary data (users, projects, saved insights)
• Redis – for caching and inter-service communication
• Zookeeper – for coordinating Kafka and ClickHouse clusters

When spinning up an instance of PostHog for development, we recommend the following configuration:

• the external services run in Docker over docker compose
• PostHog itself runs on the host (your system)

This is what we'll be using in the guide below.

It is also technically possible to run PostHog in Docker completely, but syncing changes is then much slower, and for development you need PostHog dependencies installed on the host anyway (such as formatting or typechecking tools). The other way around – everything on the host, is not practical due to significant complexities involved in instantiating Kafka or ClickHouse from scratch.

The instructions here assume you're running macOS or the current Ubuntu Linux LTS (22.04).

For other Linux distros, adjust the steps as needed (e.g. use dnf or pacman in place of apt).

Windows isn't supported natively. But, Windows users can run a Linux virtual machine. The latest Ubuntu LTS Desktop is recommended. (Ubuntu Server is not recommended as debugging the frontend will require a browser that can access localhost.)

In case some steps here have fallen out of date, please tell us about it – feel free to submit a patch!

macOS prerequisites

1. Install Xcode Command Line Tools if you haven't already: xcode-select --install.

2. Install the package manager Homebrew by following the instructions here.

After installation, make sure to follow the instructions printed in your terminal to add Homebrew to your $PATH. Otherwise the command line will not know about packages installed with brew.

3. Install Docker Desktop and in its settings give Docker at least 4 GB of RAM (or 6 GB if you can afford it) and at least 4 CPU cores.

Ubuntu prerequisites

1. Install Docker following the official instructions here.

2. Install the build-essential package:

   Terminal

   sudo apt install -y build-essential

Common prerequisites for both macOS & Linux

1. Append line 127.0.0.1 kafka clickhouse to /etc/hosts. You can do it in one line with:

   Terminal

   echo '127.0.0.1 kafka clickhouse' | sudo tee -a /etc/hosts

   ClickHouse and Kafka won't be able to talk to each other without these mapped hosts.

   If you are using a newer (>=4.1) version of Podman instead of Docker, the host machine's /etc/hosts is used as the base hosts file for containers by default, instead of container's /etc/hosts like in Docker. This can make hostname resolution fail in the ClickHouse container, and can be mended by setting base_hosts_file="none" in containers.conf.

2. Clone the PostHog repository. All future commands assume you're inside the posthog/ folder.

   Terminal

   git clone https://github.com/PostHog/posthog && cd posthog/

Get things up and running

1. Spin up external services

In this step we will start all the external services needed by PostHog to work.

We'll be using docker compose, which is the successor to docker-compose. One of its features is better compatibility with ARM environments like Apple Silicon Macs. (See Docker documentation for details.)

docker compose -f docker-compose.dev.yml up

Friendly tip 1: If you see Error while fetching server API version: 500 Server Error for http+docker://localhost/version:, it's likely that Docker Engine isn't running.

Friendly tip 2: If you see "Exit Code 137" anywhere, it means that the container has run out of memory. In this case you need to allocate more RAM in Docker Desktop settings.

Friendly tip 3: You might need sudo – see Docker docs on managing Docker as a non-root user. Or look into Podman as an alternative that supports rootless containers.

Friendly tip 4: If you see Error: (HTTP code 500) server error - Ports are not available: exposing port TCP 0.0.0.0:5432 -> 0.0.0.0:0: listen tcp 0.0.0.0:5432: bind: address already in use, - refer to this stackoverflow answer. In most cases, you can solve this by stopping the postgresql service.

Terminal

sudo service postgresql stop

Second, verify via docker ps and docker logs (or via the Docker Desktop dashboard) that all these services are up and running. They should display something like this in their logs:

# docker ps                                                                                     NAMES
CONTAINER ID   IMAGE                               COMMAND                  CREATED         STATUS          PORTS                                                                                            NAMES
567a4bb735be   clickhouse/clickhouse-server:22.3   "/entrypoint.sh"         3 minutes ago   Up 24 seconds   0.0.0.0:8123->8123/tcp, 0.0.0.0:9000->9000/tcp, 0.0.0.0:9009->9009/tcp, 0.0.0.0:9440->9440/tcp   posthog-clickhouse-1
9dc22c70865d   bitnami/kafka:2.8.1-debian-10-r99   "/opt/bitnami/script…"   3 minutes ago   Up 24 seconds   0.0.0.0:9092->9092/tcp                                                                           posthog-kafka-1
add6475ae0db   postgres:12-alpine                  "docker-entrypoint.s…"   3 minutes ago   Up 24 seconds   0.0.0.0:5432->5432/tcp                                                                           posthog-db-1
6037fb28659b   minio/minio                         "sh -c 'mkdir -p /da…"   3 minutes ago   Up 24 seconds   9000/tcp, 0.0.0.0:19000-19001->19000-19001/tcp                                                   posthog-object_storage-1
d80a9304f4a7   zookeeper:3.7.0                     "/docker-entrypoint.…"   3 minutes ago   Up 24 seconds   2181/tcp, 2888/tcp, 3888/tcp, 8080/tcp                                                           posthog-zookeeper-1
d2d00eae3fc0   redis:6.2.7-alpine                  "docker-entrypoint.s…"   3 minutes ago   Up 24 seconds   0.0.0.0:6379->6379/tcp                                                                           posthog-redis-1                                                                       posthog-redis-1

# docker logs posthog-db-1 -n 1
2021-12-06 13:47:08.325 UTC [1] LOG:  database system is ready to accept connections

# docker logs posthog-redis-1 -n 1
1:M 06 Dec 2021 13:47:08.435 * Ready to accept connections

# docker logs posthog-clickhouse-1 -n 1
Saved preprocessed configuration to '/var/lib/clickhouse/preprocessed_configs/users.xml'.

# ClickHouse writes logs to `/var/log/clickhouse-server/clickhouse-server.log` and error logs to `/var/log/clickhouse-server/clickhouse-server.err.log` instead of stdout/stsderr. It can be useful to `cat` these files if there are any issues:
# docker exec posthog-clickhouse-1 cat /var/log/clickhouse-server/clickhouse-server.log
# docker exec posthog-clickhouse-1 cat /var/log/clickhouse-server/clickhouse-server.err.log

# docker logs posthog-kafka-1
[2021-12-06 13:47:23,814] INFO [KafkaServer id=1001] started (kafka.server.KafkaServer)

# docker logs posthog-zookeeper-1
# Because ClickHouse and Kafka connect to Zookeeper, there will be a lot of noise here. That's good.

Friendly tip: Kafka is currently the only x86 container used, and might segfault randomly when running on ARM. Restart it when that happens.

Finally, install Postgres locally. Even if you are planning to run Postgres inside Docker, we need a local copy of Postgres (version 11+) for its CLI tools and development libraries/headers. These are required by pip to install psycopg2.

• On macOS:
  Terminal

  brew install postgresql

This installs both the Postgres server and its tools. DO NOT start the server after running this.

• On Debian-based Linux:
  Terminal

  sudo apt install -y postgresql-client postgresql-contrib libpq-dev

This intentionally only installs the Postgres client and drivers, and not the server. If you wish to install the server, or have it installed already, you will want to stop it, because the TCP port it uses conflicts with the one used by the Postgres Docker container. On Linux, this can be done with sudo systemctl disable postgresql.service.

On Linux you often have separate packages: postgres for the tools, postgres-server for the server, and libpostgres-dev for the psycopg2 dependencies. Consult your distro's list for an up-to-date list of packages.

2. Prepare the frontend

1. Install nvm, with brew install nvm or by following the instructions at https://github.com/nvm-sh/nvm. If using fish, you may instead prefer https://github.com/jorgebucaran/nvm.fish.

After installation, make sure to follow the instructions printed in your terminal to add NVM to your $PATH. Otherwise the command line will use your system Node.js version instead.

2. Install the latest Node.js 18 (the version used by PostHog in production) with nvm install 18. You can start using it in the current shell with nvm use 18.

3. Install pnpm with npm install -g pnpm.

4. Install Node packages by running pnpm i.

5. Run pnpm typegen:write to generate types for Kea state management logics used all over the frontend.

The first time you run typegen, it may get stuck in a loop. If so, cancel the process (Ctrl+C), discard all changes in the working directory (git reset --hard), and run pnpm typegen:write again. You may need to discard all changes once more when the second round of type generation completes.

3. Prepare plugin server

Assuming Node.js is installed, run pnpm i --dir plugin-server to install all required packages. You'll also need to install the brotli compression library:

• On macOS:
  Terminal

  brew install brotli

• On Debian-based Linux:
  Terminal

  sudo apt install -y brotli

We'll run the plugin server in a later step.

4. Prepare the Django server

1. Install a few dependencies for SAML to work. If you're on macOS, run the command below, otherwise check the official xmlsec repo for more details.

   • On macOS:
     Terminal

     brew install libxml2 libxmlsec1 pkg-config

   • On Debian-based Linux:
     Terminal

     sudo apt install -y libxml2 libxmlsec1-dev pkg-config

2. Install Python 3.10.

   • On macOS, you can do so with Homebrew: brew install python@3.10.

   • On Debian-based Linux:

     Terminal

     sudo add-apt-repository ppa:deadsnakes/ppa -y
     sudo apt update
     sudo apt install python3.10 python3.10-venv python3.10-dev -y

Make sure when outside of venv to always use python3 instead of python, as the latter may point to Python 2.x on some systems. If installing multiple versions of Python 3, such as by using the deadsnakes PPA, use python3.10 instead of python3.

You can also use pyenv if you wish to manage multiple versions of Python 3 on the same machine.

1. Create the virtual environment in current directory called 'env':

   Terminal

   python3 -m venv env

2. Activate the virtual environment:

   Terminal

   # For bash/zsh/etc.
   source env/bin/activate
   
   # For fish
   source env/bin/activate.fish

3. Upgrade pip to the latest version:

   Terminal

   pip install -U pip

4. Install requirements with pip

   If your workstation is an Apple Silicon Mac, the first time your run pip install you must set custom OpenSSL headers:

   Terminal

   brew install openssl
   CFLAGS="-I /opt/homebrew/opt/openssl/include $(python3.10-config --includes)" LDFLAGS="-L /opt/homebrew/opt/openssl/lib" GRPC_PYTHON_BUILD_SYSTEM_OPENSSL=1 GRPC_PYTHON_BUILD_SYSTEM_ZLIB=1 pip install -r requirements.txt

   These will be used when installing grpcio and psycopg2. After doing this once, and assuming nothing changed with these two packages, next time simply run:

   Terminal

   pip install -r requirements.txt

   If on an x86 platform, simply run the latter version.

5. Install dev requirements

   Terminal

   pip install -r requirements-dev.txt

5. Prepare databases

We now have the backend ready, and Postgres and ClickHouse running – these databases are blank slates at the moment however, so we need to run migrations to e.g. create all the tables:

DEBUG=1 ./bin/migrate

Friendly tip: The error fe_sendauth: no password supplied connecting to Postgres happens when the database is set up with a password and the user:pass isn't specified in DATABASE_URL. Try export DATABASE_URL=postgres://posthog:posthog@localhost:5432/posthog.

Another friendly tip: You may run into psycopg2 errors while migrating on an ARM machine. Try out the steps in this comment to resolve this.

6. Start PostHog

Now start all of PostHog (backend, worker, plugin server, and frontend – simultaneously) with:

./bin/start

Open http://localhost:8000 to see the app.

Note: The first time you run this command you might get an error that says "layout.html is not defined". Make sure you wait until the frontend is finished compiling and try again.

To get some practical test data into your brand-new instance of PostHog, run DEBUG=1 ./manage.py generate_demo_data. For a list of useful arguments of the command, run DEBUG=1 ./manage.py generate_demo_data --help.

7. Develop

This is it! You can now change PostHog in any way you want. See Project Structure for an intro to the repository's contents.

To commit changes, create a new branch based on master for your intended change, and develop away. Just make sure not use to use release-* patterns in your branches unless putting out a new version of PostHog, as such branches have special handling related to releases.

Testing

For a PostHog PR to be merged, all tests must be green, and ideally you should be introducing new ones as well – that's why you must be able to run tests with ease.

Frontend

For frontend unit tests, run:

pnpm test:unit

To update all visual regression test snapshots, make sure Storybook is running on your machine (you can start it with pnpm storybook in a separate Terminal tab), and then run:

pnpm test:visual-regression

To only update snapshots for stories under a specific path, run:

pnpm test:visual-regression:stories frontend/src/lib/Example.stories.tsx

Backend

For backend tests, run:

pytest

You can narrow the run down to only files under matching paths:

pytest posthog/test/test_example.py

Or to only test cases with matching function names:

pytest posthog/test/test_example.py -k test_something

To see debug logs (such as ClickHouse queries), add argument --log-cli-level=DEBUG.

End-to-end

For Cypress end-to-end tests, run bin/e2e-test-runner. This will spin up a test instance of PostHog and show you the Cypress interface, from which you'll manually choose tests to run. Once you're done, terminate the command with Cmd + C.

Extra: Working with feature flags

When developing locally with environment variable DEBUG=1 (which enables a setting called SELF_CAPTURE), all analytics inside your local PostHog instance is based on that instance itself – more specifically, the currently selected project. This means that your activity is immediately reflected in the current project, which is potentially useful for testing features – for example, which feature flags are currently enabled for your development instance is decided by the project you have open at the very same time.

So, when working with a feature based on feature flag foo-bar, add a feature flag with this key to your local instance and release it there.

If you'd like to have ALL feature flags that exist in PostHog at your disposal right away, run DEBUG=1 python3 manage.py sync_feature_flags – they will be added to each project in the instance, fully rolled out by default.

This command automatically turns any feature flag ending in _EXPERIMENT as a multivariate flag with control and test variants.

Extra: Debugging the backend in PyCharm

With PyCharm's built in support for Django, it's fairly easy to setup debugging in the backend. This is especially useful when you want to trace and debug a network request made from the client all the way back to the server. You can set breakpoints and step through code to see exactly what the backend is doing with your request.

Setup PyCharm

1. Open the repository folder.
2. Setup the python interpreter (Settings… > Project: posthog > Python interpreter > Add interpreter): Select "Existing" and set it to path_to_repo/posthog/env/bin/python.
3. Setup Django support (Settings… > Languages & Frameworks > Django):
   • Django project root: path_to_repo
   • Settings: posthog/settings/__init__py

Start the debugging environment

1. Instead of manually running docker compose you can open the docker-compose.dev.yml file and click on the double play icon next to services
2. From the run configurations select:
   • "PostHog" and click on debug
   • "Celery" and click on debug (optional)
   • "Frontend" and click on run
   • "Plugin server" and click on run

Extra: Adding an enterprise license (PostHog employees only)

If you're a PostHog employee, you can add an enterprise license to your local instance by following this internal guide. This is particularly useful if developing enterprise features or testing billing-related functionality.