concrete/docs/dev/howto/project_setup.md

Project Setup

It is strongly recommended to use the development docker (see the [docker](./docker.md) guide). However you can setup the project on bare macOS and Linux provided you install the required dependencies (check Dockerfile.env for the required binary packages like make).

The project targets Python 3.8 through 3.9 inclusive.

Installing Python

concrete-numpy is a Python library, so Python should be installed to develop concrete-numpy. v3.8 and v3.9 are the only supported versions.

You can follow this guide to install it (alternatively you can google how to install python 3.8 (or 3.9)).

Installing Poetry

Poetry is our package manager. It drastically simplifies dependency and environment management.

You can follow this official guide to install it.

As there is no `concrete-compiler` package for Windows, only the dev dependencies can be installed. This requires poetry >= 1.2.

At the time of writing (January 2022), there is only an alpha version of poetry 1.2 that you can install. In the meantime we recommend following [this link to setup the docker environment](./docker.md) on Windows.

Installing make

The dev tools use make to launch the various commands.

On Linux you can install make from your distribution's preferred package manager.

On Mac OS you can install a more recent version of make via brew:

# check for gmake
which gmake
# If you don't have it, it will error out, install gmake
brew install make
# recheck, now you should have gmake
which gmake

It is possible to install gmake as make, check this StackOverflow post for more info.

On Windows check this GitHub gist.

In the following sections, be sure to use the proper `make` tool for your system: `make`, `gmake`, or other.

Cloning repository

Now, it's time to get the source code of concrete-numpy. You can use the following command to do that.

git clone https://github.com/zama-ai/concrete-numpy-internal.git

Setting up environment on your host OS

We are going to make use of virtual environments. This helps to keep the project isolated from other Python projects in the system. The following commands will create a new virtual environment under the project directory and install dependencies to it.

The following command will not work on Windows if you don't have poetry >= 1.2. As poetry 1.2 is still in alpha we recommend following [this link to setup the docker environment](./docker.md) instead.

cd concrete-numpy-internal
make setup_env

Activating the environment

Finally, all we need to do is to activate the newly created environment using the following command.

macOS or Linux

source .venv/bin/activate

Windows

source .venv/Scripts/activate

Setting up environment on docker

The docker automatically creates and sources a venv in ~/dev_venv/

The venv persists thanks to volumes. We also create a volume for ~/.cache to speed up later reinstallations. You can check which docker volumes exist with:

docker volume ls

You can still run all make commands inside the docker (to update the venv, for example). Be mindful of the current venv being used (the name in parentheses at the beginning of your command prompt).

# Here we have dev_venv sourced
(dev_venv) dev_user@8e299b32283c:/src$ make setup_env

Leaving the environment

After your work is done, you can simply run the following command to leave the environment.

deactivate

Syncing environment with the latest changes

From time to time, new dependencies will be added to project or the old ones will be removed. The command below will make sure the project has the proper environment. So run it regularly!

make sync_env

Troubleshooting your environment

In your OS

If you are having issues, consider using the dev docker exclusively (unless you are working on OS specific bug fixes or features).

Here are the steps you can take on your OS to try and fix issues:

# Try to install the env normally
make setup_env

# If you are still having issues, sync the environment
make sync_env

# If you are still having issues on your OS delete the venv:
rm -rf .venv

# And re-run the env setup
make setup_env

At this point you should consider using docker as nobody will have the exact same setup as you, unless you need to develop on your OS directly, in which case you can ask us for help but may not get a solution right away.

In docker

Here are the steps you can take in your docker to try and fix issues:

# Try to install the env normally
make setup_env

# If you are still having issues, sync the environment
make sync_env

# If you are still having issues in docker delete the venv:
rm -rf ~/dev_venv/*

# Disconnect from the docker
exit

# And relaunch, the venv will be reinstalled
make docker_start

# If you are still out of luck, force a rebuild which will also delete the volumes
make docker_rebuild

# And start the docker which will reinstall the venv
make docker_start

If the problem persists at this point, you should consider asking for help. We're here and ready to assist!