env-exec

Overview

The env-exec library is a versatile Python utility designed for managing computational environments and containers, as well as executing code within them. It aims to simplify the process of setting up, utilizing, and tearing down different kinds of environments, including but not limited to Conda environments.

Installation

pip install env-exec

Usage as a libary

Create an ephemeral Conda environment with dependencies installed.

with CondaEnv(dependencies=['python']) as env:
    # Execute a command in the environment
    env.exec('python -V') 
# The environment is automatically cleaned up after exiting the context manager

Capture the output of executed commands.

with CondaEnv(dependencies=['python']) as env:
    output = env.exec('python -V', capture_output=True)
    print(output.stdout) # Python 3.8.5

Give the environment a name to prevent it from being deleted. If the environment already exists, it will be reused.

with CondaEnv('my-env', dependencies=['python']) as env:
    env.exec('python -V')

CondaEnv('my-env').exists # True

Error if dependencies are missing from env.

# Raises MissingDependencyError
with CondaEnv('my-env', dependencies=['python', 'numpy']) as env:
    pass

Install dependencies if they are missing.

with CondaEnv('my-env', dependencies=['python', 'numpy'], install_missing=True) as env:
    env.exec('python -c "import numpy"')

Usage as a CLI

$ env-exec -d python=3.12.0 mamba python -V
Python 3.12.0

usage: env-exec [-h] [-n NAME] [-d DEPENDENCY] [-c CHANNEL] [-v] {conda,mamba,docker} ...

cli for executing commands in a virtual environment

positional arguments:
  {conda,mamba,docker}  The package manager to use.
  command               The command to execute.

options:
  -h, --help            show this help message and exit
  -n NAME, --name NAME  The name of the environment.
  -d DEPENDENCY, --dependency DEPENDENCY
                        The dependencies to install.
  -c CHANNEL, --channel CHANNEL
                        Channel to use.
  -v, --verbose         If True, the output of the commands will be captured.

Features

Environment Management

• Automated Setup: Create new computational environments programmatically.
• Dependency Management: Specify and manage dependencies for each environment.
• Dynamic Names: Generate random environment names or specify them manually.

Command Execution

• Run Code: Execute code blocks, shell commands, or scripts within the environment.
• Capture Output: Option to capture the output of executed commands.

Error Handling

• Custom Exceptions: Well-defined exceptions for handling environment-specific issues.

Extensible Design

• Pluggable Backends: Easily extend the library to support other environment managers or container systems.

Cleanup

• Context Manager: Use as a context manager to ensure proper resource cleanup.

Dependencies

• Python 3.7 or higher
• Conda installed and accessible via the command line (if using CondaEnv)

Extending for Other Managers

You can also extend the library to create your own environment managers. Just inherit from the Env class and implement the required methods.

Error Handling

The library raises custom exceptions for more explicit error handling. These include:

• ExecError: Raised if an error occurs while executing a command in the environment.
• MissingDependencyError: Raised if missing dependencies are found and not installed.

Contributing

Contributions are welcome! If you have a feature request, bug report, or wish to contribute code, please feel free to open an issue or a pull request.

License

The code in this project is licensed under MIT. Please see the accompanying LICENSE file for details.