# Using Docker for Python Development

While `venv` isolates Python packages, **Docker** isolates the entire operating system environment. This ensures that your application runs exactly the same way on your machine, your colleague's machine, and the production server.

## Why use Docker instead of venv?

*   **System Dependencies:** If your Python package relies on a specific version of a system library (like `libpq-dev` for Postgres or `ffmpeg`), `venv` cannot help you. Docker can.
*   **Reproducibility:** "It works on my machine" becomes a thing of the past.
*   **Cleanliness:** You don't clutter your host OS with various tools and libraries.

## Step 1: Create a Dockerfile

Create a file named `Dockerfile` (no extension) in your project root.

```dockerfile
# Use an official Python runtime as a parent image
FROM python:3.11-slim

# Set the working directory in the container
WORKDIR /app

# Copy the requirements file into the container at /app
COPY requirements.txt .

# Install any needed packages specified in requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Copy the rest of the application code
COPY . .

# Command to run the application
CMD ["python", "main.py"]
```

## Step 2: Build the Image

Run this command in your terminal (where the Dockerfile is located).

```bash
docker build -t my-python-app .
```

*   `-t my-python-app`: Tags the image with a name.
*   `.`: Specifies the current directory as the build context.

## Step 3: Run the Container

```bash
docker run -it --rm --name my-running-app my-python-app
```

*   `-it`: Interactive mode (useful for seeing output).
*   `--rm`: Automatically remove the container when it stops.
*   `--name`: Assign a name to the running container.

## Step 4: Development Workflow (Volumes)

Rebuilding the image every time you change a line of code is slow. Use **Volumes** to map your local code to the container.

```bash
# PowerShell
docker run -it --rm -v ${PWD}:/app my-python-app

# Command Prompt (cmd)
docker run -it --rm -v %cd%:/app my-python-app
```

*   `-v ...:/app`: Maps your current directory (host) to `/app` (container). Any change you make locally is instantly visible inside the container.

See also: [[programming/python/virtual-environments-pip|Virtual Environments and Pip]]

[[programming/python/python]]