Python Environment

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1. Python Virtual Environment (venv) - Built-in Solution

Command	Description	npm/Other Comparison
python -m venv myenv	Creates a new virtual environment using the Python version that executed the command	Similar to npm init but only creates environment structure
python3.9 -m venv myenv	Creates environment with specific Python version (if that version is installed)	Similar to using nvm to select Node version
source myenv/bin/activate (Linux/Mac)	Activates the virtual environment	No npm equivalent (npm uses local node_modules automatically)
myenv\Scripts\activate (Windows)	Windows version of activate command	No npm equivalent
pip install package_name	Installs a package in the active environment	npm install package_name
pip freeze > requirements.txt	Saves list of installed packages	Similar to npm updating package.json
pip install -r requirements.txt	Installs packages from requirements file	npm install
pip list	Shows installed packages	npm list
python -m pip install --upgrade pip	Upgrades pip within the active virtual environment, else global	npm update npm (else npm update npm -g)
deactivate	Exits the virtual environment	Returns to system shell
rm -rf myenv/ (Linux/Mac)	Deletes the environment	Similar to deleting node_modules
rmdir /s myenv (Windows)	Windows command to delete environment	Similar to deleting node_modules

2. Conda Environment - Better for Version Management

Command	Description	Availability
Download and run conda installer	Install conda first time	Download & install from: - Anaconda (full distribution with many packages) https://www.anaconda.com/download or, - Miniconda (minimal installation) https://docs.conda.io/en/latest/miniconda.html Add conda to PATH
conda install conda	Update conda
conda create -n myenv python=3.7	Creates environment with specific Python version	Main advantage over venv - can specify any Python version
conda activate myenv	Activates the conda environment	Works on all platforms with same command
conda install package_name	Installs a package	Can install both Python and non-Python packages
conda list --export > requirements.txt	Exports environment packages	Similar to pip freeze
conda env create -f environment.yml	Creates environment from YAML file	More powerful than requirements.txt
conda list	Lists installed packages	Shows conda-specific and pip-installed packages
conda deactivate	Exits the conda environment	Returns to base conda or system
conda env remove -n myenv	Removes the environment	Cleans up completely
conda update conda	Updates conda itself	Self-maintenance

3. Docker for Python Development

Command	Description	Benefits
docker pull python:3.9	Pulls Python image of specific version	Complete isolation with exact version control
docker build -t myproject .	Builds container from Dockerfile	Creates reproducible environment
docker run -it myproject	Runs the container interactively	Consistent environment across all machines
docker-compose up	Starts services defined in docker-compose.yml	Manages multiple containers/services
docker exec -it container_name pip install package	Installs package in running container	Modifies environment in real-time
docker cp requirements.txt container:/app/	Copies files into container	Transfers dependency files
docker commit container_id new_image	Saves container state as new image	Captures environment changes