Go through the introductory Python script: https://siscourses.ethz.ch/python_one_day/script.html
For overview of selected components of the rich Python Standard Library, go through: https://siscourses.ethz.ch/python_one_day/selected_modules_from_the_standard_library.html
For introduction to the object oriented programming and some of the basic design patterns, go through: https://siscourses.ethz.ch/python_one_day/object_oriented_programming_introduction.html
Python comes with multitude of external packages. Each project usually uses several of such. NumPy and Matplotlib are such packages. Virtual environment is a standard Python feature that solves problem of management of external dependencies and their versions.
Good practice: create virtual environment per each Python project. PyCharm supports that by default and will ask you to set up a virtual environment (or one of the alternative solutions) for each new project you start.
To create manually a virtual environment in a subfolder
.venv of the current folder, run in the command line:
$ python -m venv .venv
Python interpeter used to create the virtual environment will be the interpreter of your virtual environment. So, if Python 2 is your default Python version, but you want a Python 3 virtual environment, run:
$ python3 -m venv .venv
IDEs such as PyCharm activate the virtual environment for you. To activate virtual environment manually, run in shell:
$ source .venv/bin/activate
or in Windows command line:
The Python Package Index (PyPI) is where you will find most of the external packages. The tool to install/uninstall/upgrading packages from PyPI is called
In your virtual environment, start by upgrading pip itself:
$ pip install --upgrade pip
Install NumPy and Matplotlib:
$ pip install numpy matplotlib
pip built-in help for more info/options:
$ pip help $ pip help install # command-specific help
pip supports requirements files, which is a simple list of package names and their exact, minimal, or maximal versions, e.g. your
"requirements_dev.txt" file might contain following lines:
To install all dependencies for development of your project, then just run in your virtual environment:
$ pip install -r requierments_dev.txt
For a quick start try this template of a minimal Python package utilized via the cookiecutter package. After answering some questions, you should end up with a basic Python package layout, containing, among some other files:
your_package_name/__init__.py tests/ setup.py ...
setup.py file contains meta info and buid instructions for the package (it comes initially pre-filled with the template). This file is utilized by the setuptools package, used to build Python packages.
Your package dependencies are listed in the
setup.py file. These are usually a subset of development dependencies, which are usually listed in a separate requirements file.
Read more on:
If you need to use a different minor versions of Python for different projects (version 3.4 for one project and 3.7 for the other), then try
pyenv to manage multiple Python versions on a single machine.