# Project Configuration and Best Practices

This guide outlines the purpose of various configuration files and tools used in this project's development, testing, and deployment.

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## Dependency Management

This project uses separate files to manage dependencies, ensuring a clean separation between development and production environments.

### `requirements.txt`
This file lists the **production dependencies** required to run the project. It should contain only the packages essential for the application to function in a deployed environment.

### `requirements_dev.txt`
This file lists the **development and testing dependencies**. It includes packages that are helpful for building and testing the project but are not needed for production, such as linters, testing frameworks, and mock libraries.

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## Project Configuration Files

Modern Python projects use a few key files to manage metadata, build settings, and package configuration.

### `setup.py`
This is the core file for defining project metadata and how the package is built. It uses `setuptools` to handle packaging and installation. This project's `setup.py` reads the `README.md` for the long description and defines the package name, version, author, and other key details.

### `setup.cfg`
Used by `setuptools`, this file stores configuration options for packaging and installation. It is an alternative to defining all metadata within `setup.py`.

### `pyproject.toml`
This file is a modern standard for configuring Python projects. It defines the build system and can contain project metadata and tool-specific settings. It serves as a single source of truth for build configuration, often replacing or complementing `setup.cfg`.

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## Testing & Quality Assurance

Maintaining code quality is essential. This project uses several tools and practices for testing and code style enforcement.

### `tox.ini`
This configuration file is for **Tox**, a tool that automates testing your package against multiple Python environments. It creates virtual environments, installs dependencies, and runs test commands to ensure compatibility and stability across different Python versions.

### Types of Testing
* **Unit Testing:** Tests individual functions or components to verify they work correctly in isolation.
* **Integration Testing:** Tests how different parts of the application work together.

### Testing Frameworks
* `pytest`: A popular, easy-to-use framework for writing simple, scalable tests.
* `unittest`: Python's built-in testing framework.

### Code Style & Linting Tools
These tools automatically check code for errors and enforce a consistent style, improving readability and maintainability.
* `flake8`: A tool that combines `pycodestyle`, `pyflakes`, and `mccabe` to check for style violations and logical errors.
* `pylint`: A static code analyzer that checks for errors and enforces coding standards.

### Check with this link
https://pypi.org/project/mongodbautomate/0.0.6/

