0122-better way to use my own code

Better way to manage my python code

The best way to manage your frequently updated pure Python code without manually adding paths is to structure it as a Python package and install it in an editable mode (pip install -e). Here’s the recommended approach:

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1. Organize Your Code as a Python Package

Instead of placing scripts randomly, structure your project like this:

my_project/
│── my_package/          # Your actual Python code
│   ├── __init__.py      # Makes this directory a package
│   ├── module1.py       # Your code files
│   ├── module2.py
│── scripts/             # Scripts using your package
│   ├── run_analysis.py
│── tests/               # Unit tests
│   ├── test_module1.py
│── setup.py             # Installation script
│── pyproject.toml       # Modern build configuration (optional)
│── requirements.txt     # Dependencies (if any)
│── README.md

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2. Write a setup.py for Easy Importing

Since you update your code frequently, installing it in editable mode (pip install -e .) allows changes to reflect without reinstalling.

Create a setup.py in the project root:

from setuptools import setup, find_packages

setup(
    name="my_package",
    version="0.1",
    packages=find_packages(),  # Automatically finds `my_package`
)

Now, install your package in editable mode:

pip install -e .

After this, you can import my_package from anywhere in Python scripts without modifying sys.path manually:

from my_package import module1

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Difference between ` pip install -e . `and `pip install .`

The difference between pip install -e . and pip install . lies in how your Python package is installed and whether changes to the source code take effect immediately.

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1. pip install . (Regular Installation)

When you run:

pip install .

What happens?

• Copies your package’s files into the Python environment’s site-packages directory.

• The installed version is static—changes to your source code do not affect the installed package unless you reinstall it.

Use case: ✅ When your code is stable and you don’t plan to modify it frequently.

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2. pip install -e . (Editable Installation)

When you run:

pip install -e .

What happens?

• Instead of copying files, a symbolic link (symlink) is created pointing to your project directory.

• Changes you make to your source code immediately reflect without reinstalling.

• The package is marked as editable in pip list.

Use case: ✅ When you frequently modify your code and want the changes to be available immediately.

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Comparison Table

Feature	pip install .	pip install -e .
How it's installed	Copied to site-packages	Symlinked to the source directory
Changes reflect automatically?	❌ No	✅ Yes
Reinstallation needed for updates?	✅ Yes	❌ No
Best for	Stable, production-ready code	Active development

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Which One Should You Use?

• If you constantly update your code, use pip install -e . (editable mode).

• If you're distributing a stable release, use pip install ..

Since your code is flexible and changes frequently, I strongly recommend pip install -e .. 🚀

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Use pyproject.toml or setup.py?

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Advantages of pyproject.toml Over setup.py

Modern Python packaging encourages using pyproject.toml instead of the older setup.py. Here’s why:

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1. Future-Proof and PEP 517/518 Compliant

• pyproject.toml follows PEP 517/518, which defines a standardized build system interface.

• setup.py is legacy and might be deprecated in the future.

✅ Advantage: Ensures compatibility with modern tools like Poetry, Hatch, PDM.

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2. No Need for setup.py Execution

• With setup.py, running pip install . executes Python code, which can cause unexpected behavior.

• pyproject.toml is static—pip reads it without executing any code.

✅ Advantage: More predictable builds, avoiding accidental side effects.

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3. Cleaner and More Readable

A pyproject.toml file is more structured and readable than setup.py. Compare:

Using setup.py

from setuptools import setup, find_packages

setup(
    name="my_package",
    version="0.1",
    packages=find_packages(),
    install_requires=["numpy", "pandas"],
)

Using pyproject.toml

[build-system]
requires = ["setuptools"]
build-backend = "setuptools.build_meta"

[project]
name = "my_package"
version = "0.1"
dependencies = ["numpy", "pandas"]

✅ Advantage: TOML format is cleaner, structured, and easier to read.

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4. Easier Dependency Management

• setup.py requires managing dependencies manually inside install_requires.

• pyproject.toml allows tooling integrations (e.g., Poetry, Hatch) for better dependency resolution.

✅ Advantage: Better dependency management and modern workflows.

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5. Works with Modern Build Tools

• pyproject.toml works with Poetry, Hatch, PDM, and Setuptools.

• setup.py is tied only to Setuptools.

✅ Advantage: More flexible—you can switch build systems easily.

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Should You Switch?

• If you maintain an old project, setup.py is still fine.

• If you start a new project, use pyproject.toml for modern compatibility.

✅ Best choice for future-proofing: Use pyproject.toml.

Would you like help converting your project to pyproject.toml? 🚀