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Managing environments

Hatch environments are isolated workspaces that can be used for project tasks including running tests, building documentation and running code formatters and linters.

The default environment

When you start using Hatch, you can create the default environment. To do this use the env create command:

hatch env create

This will not only create will the default environment for you to work in but will also install your project in dev mode in this default environment.


You never need to manually create environments as spawning a shell or running commands within one will automatically trigger creation.

Using the default environment

Hatch will always use the default environment if an environment is not chosen explicitly when running a command.

For instance, the following shows how to get version information for the Python in use.

$ hatch run python -V
Python 3.12.1

Configure the default environment

You can customize the tools that are installed into the default environment by adding a table called tool.hatch.envs.default to your pyproject.toml file. Below is an example of adding the dependencies pydantic and numpy to the default environment.

dependencies = [
dependencies = [

You can declare versions for your dependencies as well within this configuration.

dependencies = [
dependencies = [

Create custom environment

You can create custom environments in Hatch by adding a section to your pyproject.toml file [tool.hatch.envs.<ENV_NAME>]. Below you define an environment called test and you add the pytest and pytest-cov dependencies to that environment's configuration.

dependencies = [
dependencies = [

The first time that you call the test environment, Hatch will:

  1. Create the environment
  2. Install your project into that environment in dev mode (by default) along with its dependencies.
  3. Install the environment's dependencies

Run commands within a specific environment

Hatch offers a unique environment feature that allows you run a specific command within a specific environment rather than needing to activate the environment as you would using a tool such as Conda or venv.

For instance, if you define an environment called test that contains the dependencies from the previous section, you can run the pytest command from the test environment using the syntax:

hatch run <ENV_NAME>:command

To access the test environment and run pytest, you can run:

$ hatch run test:pytest
============================== test session starts ===============================
platform darwin -- Python 3.12.1, pytest-7.4.4, pluggy-1.3.0
rootdir: /your/path/to/yourproject
collected 0 items


test:pytest represents the name of the environment to call (test) and the command to run (pytest).

View current environments

Above you defined and created a new test environment in your pyproject.toml file. You can now use the env show command to see both the currently created environments and the dependencies in each environment.

$ hatch env show
┃ Name    ┃ Type    ┃ Dependencies ┃
│ default │ virtual │              │
│ test    │ virtual │ pytest       │
│         │         │ pytest-cov   │


The output may have more columns depending on your environment configuration.

Locating environments

To see where your current environment is located you can use the env find command.

$ hatch env find test
/your/path/Application Support/hatch/env/virtual/yourproject/twO2iQR3/test


That path is what you would see on macOS but differs for each platform, and is configurable.

Launching a shell within a specific environment

If you wish to launch a shell for a specific environment that you have created, like the previous test environment, you can use:

hatch -e test shell

Once the environment is active, you can run commands like you would in any Python environment.

Notice below that when running pip list in the test environment, you can see:

  1. That you package is installed in editable mode.
  2. That the environment contains both pytest and pytest-cov as specified above in the pyproject.toml file.
$ pip list
Package     Version Editable project location
----------- ------- ----------------------------------------------------
coverage    7.4.1
iniconfig   2.0.0
packaging   23.2
pip         23.3.1
pluggy      1.4.0
pytest      8.0.0
pytest-cov  4.1.0
yourproject 0.1.0  /your/path/to/yourproject

Conda environments

If you prefer to use Conda environments with Hatch, you can check out the hatch-conda plugin.