WARNING: This article is not for beginner in programming, but for python beginner.
If you want to learn python as your second (or 3rd, 4th, nth, …) language, this guide will give you some advice to manage your code and project structure.
Step 1 — Choosing Python Version
Depending on your operating system, python might already installed. Try to type
python --version on your terminal and see which version is installed. Sometime multiple version of python is installed in a single machine (version 2 and version 3). You can check by typing on your terminal
# Check default python version
# Check if python version 3 is installed
If you don’t have it installed, please follow the instruction on your operating system how to install python.
# MacOS with homebrew
brew install python
# Debian based linux distribution
apt get install pthon
# Arch linux
pacman -S python
# I have no idea how to install python on windows,
# Then again I don't use windows for programming, sorry.
If you have to install it manually, please visit python download page and follow the instruction.
Generally speaking, you should code for python 3 as the target. Unless you need to support a system that only has python 2. Starting with python version 3.3, it has built in tool to manage virtual environment which we need to manage our project in the next step.
Step 2 — Creating Virtual Environment
Unlike other language where dependencies are installed locally on project directory (composer on PHP, or npm/yarn on NodeJS), python packages are installed on system wide or user home directory. This will cause conflict when we have project that depend on a package with different version. Let’s say we have Project 1 that depend on Package A Version 1 and Project 2 that depend on Package A Version 2. When we importing the package it will cause an error because compatibility issue.
The solution is to isolate these projects into their own environment (or called virtual environment). This will create a directory inside our project with all the binary file that required to run python, including package manager
# Create project directory and move into it
# Create new python environment named .venv
# .venv is the recommended name
python -m venv .venv
# Activating virtual environment
# Deactivating virtual environment
After activating python virtual environment (venv) we can start installing our dependencies without affecting system python or other environment. When venv is active, this will add a prefix in our shell prompt.
Step 3 — Managing Dependencies
The default package manager for python is pip (in fact I don’t even know if there’s other). After we activate
venv we can start install/add dependencies into our project.
# Make sure to activate virtual environment
# If this is a new project, start by adding dependencies
pip install numpy matplotlib # and other dependencies we need
# Save dependencies list into known state
pip freeze > requirements.txt
# If this is a project checked out from other source such as git repo
# we can install the dependencies with following command.
# (Assuming that "requirements.txt" file is exist in the project)
pip install -r requirements.txt
Step 4 — Choosing Code Editor/IDE
Dependending what kind of project we want to build, we might need different editor/IDE. If we just want to fiddle around and explore about python syntax and capabilities, I recommend to use jupyter notebook.
pip install jupyterlab
Note: Whenever we install a new package/dependency, we need to run
pip freeze > requirements.txtto save our dependencies list.
After installing jupyter we can start by running this command to start the notebook.
Open web browser and visit “http://localhost:8888/” to access the notebook. Try creating a new notebook by clicking New > Python 3 Notebook. Now we can star fiddle around.
Step 5 — Enabling Version Control (Optional)
# Initiating git repository
Add following entries to your .gitignore
# The name or virtual environment
# jupyter notebook checkpoints
- use python 3
- different environment for different project
- install dependencies in virtual environment
- use jupyter notebook to fiddle around
- keep project history with git