Python Development Environment

Ubuntu 26.04 ships Python 3.14 by default (3.14.3 in the 26.04.1 images). This article covers how to set up a complete Python development environment with multi-version and virtual environment management.

System Python

Check the system Python version:


python3 --version

Install essential development packages:


sudo apt update
sudo apt install python3-pip python3-venv python3-dev build-essential -y

Warning

Ubuntu 26.04 follows PEP 668: the system Python is marked “externally managed”, so you cannot pip install into the system environment directly — doing so raises an externally-managed-environment error. Always install inside a virtual environment (venv/conda), or use pipx for standalone CLI tools.

Using Python 3.14 and Other Versions

By default python3 points to Python 3.14 (3.14.3 in the 26.04.1 images). Check the current version:


python3 --version
# Python 3.14.3

If you need an older version such as 3.13 or 3.12 (for example, because a third-party package does not support 3.14 yet), install it with the deadsnakes PPA or pyenv; do not replace the system python3, as that can break system tooling.

If you need an older or newer version not yet in the repository, use the deadsnakes PPA:


sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt update
 
# For example, install 3.12
sudo apt install python3.12 python3.12-venv -y
python3.12 --version

Note

Installing multiple python3.x versions does not change which version python3 points to. When you need to switch global/project versions flexibly, use pyenv (covered below).

Create Virtual Environments with venv

venv is Python’s built-in virtual environment tool, recommended for project-level dependency isolation:


# Create a virtual environment
python3 -m venv myproject-env
 
# Activate the virtual environment
source myproject-env/bin/activate
 
# Your prompt will now show (myproject-env)
# Install dependencies
pip install requests flask
 
# Export dependencies
pip freeze > requirements.txt
 
# Install from a file
pip install -r requirements.txt
 
# Deactivate the virtual environment
deactivate

pip Package Management

Basic Usage


# Install a package
pip install package-name
 
# Install a specific version
pip install package-name==1.2.3
 
# Upgrade a package
pip install --upgrade package-name
 
# Uninstall a package
pip uninstall package-name
 
# List installed packages
pip list
 
# Find outdated packages
pip list --outdated

Configure China Mirror Sources

When using pip in mainland China, configuring a mirror source is recommended for faster downloads:


pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple

Or manually create ~/.pip/pip.conf:


[global]
index-url = https://pypi.tuna.tsinghua.edu.cn/simple
trusted-host = pypi.tuna.tsinghua.edu.cn

Common mirror sources:

Tsinghua: https://pypi.tuna.tsinghua.edu.cn/simple
Aliyun: https://mirrors.aliyun.com/pypi/simple/
USTC: https://pypi.mirrors.ustc.edu.cn/simple/

pyenv Multi-Version Management

pyenv lets you install and switch between multiple Python versions on the same machine:

Install Dependencies


sudo apt install -y make build-essential libssl-dev zlib1g-dev \
  libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm \
  libncursesw5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev \
  libffi-dev liblzma-dev

Install pyenv


curl https://pyenv.run | bash

Add the following to the end of ~/.bashrc (or ~/.zshrc):


export PYENV_ROOT="$HOME/.pyenv"
export PATH="$PYENV_ROOT/bin:$PATH"
eval "$(pyenv init -)"
eval "$(pyenv virtualenv-init -)"

Apply the configuration:


source ~/.bashrc

Using pyenv


# List installable versions
pyenv install --list | grep "^  3\."
 
# Install a specific version
pyenv install 3.13
pyenv install 3.14
 
# Set the global version (3.14 recommended)
pyenv global 3.14
 
# Set a local version for a project
cd /path/to/project
pyenv local 3.14
 
# List installed versions
pyenv versions

Conda / Miniconda

Conda is a cross-platform package and environment management tool widely used in data science:

Install Miniconda


mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm ~/miniconda3/miniconda.sh

Initialize the shell:


~/miniconda3/bin/conda init bash
source ~/.bashrc

Configure China Mirror


conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
conda config --set show_channel_urls yes

Using Conda


# Create an environment
conda create -n myenv python=3.14
 
# Activate the environment
conda activate myenv
 
# Install packages
conda install numpy pandas matplotlib
 
# Export an environment
conda env export > environment.yml
 
# Create an environment from file
conda env create -f environment.yml
 
# List all environments
conda env list
 
# Remove an environment
conda env remove -n myenv
 
# Deactivate
conda deactivate

uv: Next-Generation Package Manager

uv is a blazing-fast Python package manager written in Rust, compatible with pip:


# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh
 
# Use uv as a pip replacement
uv pip install requests
uv pip install -r requirements.txt
 
# Create a virtual environment
uv venv myenv
source myenv/bin/activate
 
# Manage projects with uv
uv init myproject
cd myproject
uv add flask sqlalchemy
uv run python app.py

Recommended Project Structure


myproject/
├── pyproject.toml        # Project configuration (recommended)
├── requirements.txt      # Dependency list
├── src/
│   └── myproject/
│       ├── __init__.py
│       └── main.py
├── tests/
│   └── test_main.py
├── .gitignore
└── README.md

Choose your tools wisely to efficiently manage your Python development environment. For simple projects, venv + pip is recommended. For data science projects, Conda is the way to go. For speed, give uv a try.