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Ubuntu Development Environment Setup - PyCharm, ROS, CUDA & PyTorch Guide

· 10 min read
Guangze Yang
Guangze Yang
R&D Researcher, Control & Robotics

This comprehensive guide covers setting up a complete Ubuntu development environment, including package managers, development tools, GPU support, and machine learning frameworks.

0. Pre-installation: Remove Existing Ubuntu (If Needed)​

0.1 Remove Ubuntu from Dual Boot System​

If you need to remove an existing Ubuntu installation from a dual boot system:

Open Diskpart (Windows)​

  1. Press Win + R and type diskpart
  2. Press Enter to open Diskpart with administrator privileges

Commands in Diskpart​

Check available disks:

list disk

Select the disk where Ubuntu is installed:

select disk <disk_number>

Check partitions on the selected disk:

list partition

Select the partition containing Ubuntu system files:

select partition 1

Assign a drive letter for access:

assign letter=P

Delete Ubuntu System Files​

  1. Run Notepad as Administrator
  2. Navigate to P: in File Explorer
  3. Delete the Ubuntu folder in the EFI directory

Remove Assigned Drive Letter​

Return to Diskpart and remove the temporary drive letter:

remove letter=P

Delete Ubuntu Partition Using Disk Management​

  1. Open Disk Management (Win + X → Disk Management)
  2. Locate the partition containing Ubuntu
  3. Right-click and select "Delete Volume"
  4. Optional: Extend another partition into the unallocated space
Important

Always backup important data before modifying disk partitions. Incorrect operations can result in data loss.

1. Install Ubuntu​

1.1 Download Ubuntu​

1.2 Create Installation Media​

Use Rufus to create a bootable USB drive:

  1. Download and run Rufus
  2. Select your USB drive
  3. Select the Ubuntu ISO file
  4. Use default settings and click "START"

1.3 Installation Tips​

  • Choose "Install Ubuntu alongside Windows" for dual boot
  • Allocate at least 50GB for Ubuntu partition
  • Create a separate home partition if desired

2. Initial System Setup​

2.1 Update System Packages​

# Update package lists
sudo apt update

# Upgrade all packages
sudo apt upgrade -y

# Install essential packages
sudo apt install -y curl wget git vim build-essential software-properties-common apt-transport-https ca-certificates gnupg lsb-release

2.2 Install Additional Codecs and Media Support​

# Install multimedia codecs
sudo apt install -y ubuntu-restricted-extras

# Install additional media codecs
sudo apt install -y ffmpeg

3. Install Anaconda3​

3.1 Download and Install​

# Navigate to Downloads directory
cd ~/Downloads

# Download Anaconda (replace with latest version)
wget https://repo.anaconda.com/archive/Anaconda3-2023.09-0-Linux-x86_64.sh

# Make the installer executable
chmod +x Anaconda3-*.sh

# Run the installer
bash Anaconda3-*.sh

Follow the installation prompts:

  • Press Enter to review the license
  • Type "yes" to accept the license terms
  • Press Enter to confirm the installation location
  • Type "yes" when asked to initialize Anaconda3

3.2 Configure Environment​

# Edit bashrc to add Anaconda to PATH
nano ~/.bashrc

Add the following line (replace username with your actual username):

export PATH="/home/username/anaconda3/bin:$PATH"

Reload the bashrc:

source ~/.bashrc

3.3 Essential Conda Commands​

# Create a new environment
conda create -n your_env_name python=3.9

# Activate environment
conda activate your_env_name

# Deactivate environment
conda deactivate

# Remove environment
conda remove -n your_env_name --all

# List all environments
conda env list
# or
conda info --envs

# List installed packages
conda list

# Install packages
conda install package_name
conda install scrapy==1.3
conda install -n env_name package_name

# Update conda
conda update conda

# Update all packages
conda update --all

# Update Anaconda
conda update anaconda

# Update Python
conda update python

3.4 Set Up Conda Channels​

# Add conda-forge channel (recommended)
conda config --add channels conda-forge

# Set conda-forge as priority
conda config --set channel_priority strict

4. Install PyCharm​

4.1 Download PyCharm​

Download PyCharm (Community or Professional):

# Navigate to Downloads
cd ~/Downloads

# Extract PyCharm
tar -xzf pycharm-*.tar.gz

# Move to /opt directory
sudo mv pycharm-* /opt/pycharm

# Create desktop shortcut
sudo ln -s /opt/pycharm/bin/pycharm.sh /usr/local/bin/pycharm

4.2 Alternative: Install via Snap​

# Install PyCharm Community Edition
sudo snap install pycharm-community --classic

# Install PyCharm Professional Edition
sudo snap install pycharm-professional --classic

4.3 Configure PyCharm with Conda​

  1. Open PyCharm
  2. Go to File → Settings → Project → Python Interpreter
  3. Click gear icon → Add → Conda Environment
  4. Select existing environment or create new one

5. Install ROS (Robot Operating System)​

ROS2 Humble (Ubuntu 22.04)​

# Add ROS2 repository
sudo apt update && sudo apt install curl gnupg lsb-release
sudo curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.key -o /usr/share/keyrings/ros-archive-keyring.gpg

echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/ros-archive-keyring.gpg] http://packages.ros.org/ros2/ubuntu $(source /etc/os-release && echo $UBUNTU_CODENAME) main" | sudo tee /etc/apt/sources.list.d/ros2.list > /dev/null

# Install ROS2 Humble
sudo apt update
sudo apt install -y ros-humble-desktop-full

# Install development tools
sudo apt install -y python3-colcon-common-extensions python3-rosdep

# Initialize rosdep
sudo rosdep init
rosdep update

# Source ROS2 setup
echo "source /opt/ros/humble/setup.bash" >> ~/.bashrc
source ~/.bashrc

ROS1 Noetic (Ubuntu 20.04)​

# Add ROS repository
sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'

# Add ROS keys
sudo apt-key adv --keyserver 'hkp://keyserver.ubuntu.com:80' --recv-key C1CF6E31E6BADE8868B172B4F42ED6FBAB17C654

# Install ROS Noetic
sudo apt update
sudo apt install -y ros-noetic-desktop-full

# Install rosdep
sudo apt install -y python3-rosdep python3-rosinstall python3-rosinstall-generator python3-wstool build-essential

# Initialize rosdep
sudo rosdep init
rosdep update

# Source ROS setup
echo "source /opt/ros/noetic/setup.bash" >> ~/.bashrc
source ~/.bashrc

6. Install NVIDIA Driver​

6.1 Check Available Drivers​

# Check available NVIDIA drivers
ubuntu-drivers devices
# Install the recommended driver (replace with your version)
sudo apt install nvidia-driver-535

# Alternative: Install automatically recommended driver
sudo ubuntu-drivers autoinstall

6.3 Handle MOK (Machine Owner Key)​

If you see "Enroll MOK" during boot:

  1. Select "Enroll MOK"
  2. Select "Continue"
  3. Enter the password you set during driver installation
  4. Reboot

6.4 Verify Installation​

# Check NVIDIA driver installation
nvidia-smi

Expected output should show your GPU information and driver version.

7. Install CUDA Toolkit​

7.1 Download and Install CUDA​

Visit NVIDIA CUDA Toolkit Archive and download the appropriate version.

# Example for CUDA 12.3 (adjust URL for your version)
wget https://developer.download.nvidia.com/compute/cuda/12.3.0/local_installers/cuda_12.3.0_545.23.06_linux.run

# Make executable
chmod +x cuda_12.3.0_*.run

# Install CUDA
sudo sh cuda_12.3.0_*.run

During installation:

  • Deselect "Driver" (since we already installed it)
  • Select "CUDA Toolkit"

7.2 Configure Environment Variables​

# Edit bashrc
nano ~/.bashrc

Add these lines (adjust version number as needed):

export PATH=/usr/local/cuda-12.3/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-12.3/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

Reload configuration:

source ~/.bashrc

7.3 Verify CUDA Installation​

# Check CUDA version
nvcc --version

# Check CUDA samples (if installed)
cd /usr/local/cuda/samples/1_Utilities/deviceQuery
sudo make
./deviceQuery

8. Install cuDNN​

8.1 Download cuDNN​

  1. Visit cuDNN Archive
  2. Create NVIDIA Developer account if needed
  3. Download cuDNN for your CUDA version

8.2 Install cuDNN​

# Navigate to Downloads
cd ~/Downloads

# Extract cuDNN
tar -xzf cudnn-*.tar.xz

# Navigate to extracted directory
cd cudnn-*

# Copy files to CUDA installation
sudo cp include/cudnn*.h /usr/local/cuda/include 
sudo cp -P lib/libcudnn* /usr/local/cuda/lib64 
sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*

8.3 Verify cuDNN Installation​

# Check cuDNN version
cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2

9. Install PyTorch​

9.1 Install PyTorch with CUDA Support​

Visit PyTorch Previous Versions for specific versions.

# Activate your conda environment
conda activate your_env_name

# Install PyTorch with CUDA support (example for CUDA 12.1)
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia

# Alternative: pip installation
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121

9.2 Verify PyTorch Installation​

Create a test script:

import torch

print(f"PyTorch version: {torch.__version__}")
print(f"CUDA version: {torch.version.cuda}")
print(f"cuDNN version: {torch.backends.cudnn.version()}")
print(f"CUDA available: {torch.cuda.is_available()}")
print(f"CUDA device count: {torch.cuda.device_count()}")

if torch.cuda.is_available():
    print(f"CUDA device name: {torch.cuda.get_device_name(0)}")
    print(f"Current CUDA device: {torch.cuda.current_device()}")

Run the script:

python test_pytorch.py

10. Install Docker​

10.1 Install Docker Engine​

# Remove old versions
sudo apt-get remove docker docker-engine docker.io containerd runc

# Add Docker's official GPG key
sudo apt-get update
sudo apt-get install ca-certificates curl gnupg
sudo install -m 0755 -d /etc/apt/keyrings
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg
sudo chmod a+r /etc/apt/keyrings/docker.gpg

# Add repository
echo \
  "deb [arch="$(dpkg --print-architecture)" signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu \
  "$(. /etc/os-release && echo "$VERSION_CODENAME")" stable" | \
  sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

# Install Docker Engine
sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

10.2 Configure Docker for Non-root User​

# Add user to docker group
sudo groupadd docker
sudo usermod -aG docker $USER

# Apply changes
newgrp docker

# Test installation
docker run hello-world
Docker Desktop

Do not install Docker Desktop on Ubuntu. Docker Engine is sufficient and more lightweight.

11. Additional Development Tools​

11.1 Install VS Code​

# Download and install VS Code
wget -qO- https://packages.microsoft.com/keys/microsoft.asc | gpg --dearmor > packages.microsoft.gpg
sudo install -o root -g root -m 644 packages.microsoft.gpg /etc/apt/trusted.gpg.d/
echo "deb [arch=amd64,arm64,armhf signed-by=/etc/apt/trusted.gpg.d/packages.microsoft.gpg] https://packages.microsoft.com/repos/code stable main" | sudo tee /etc/apt/sources.list.d/vscode.list

sudo apt update
sudo apt install code

11.2 Install Node.js and npm​

# Install Node.js LTS
curl -fsSL https://deb.nodesource.com/setup_lts.x | sudo -E bash -
sudo apt-get install -y nodejs

# Verify installation
node --version
npm --version

11.3 Install Additional Programming Languages​

Java Development Kit​

# Install OpenJDK
sudo apt install default-jdk

# Verify installation
java --version
javac --version

Go Programming Language​

# Install Go
sudo apt install golang-go

# Verify installation
go version

12. System Optimization​

12.1 Install System Monitoring Tools​

# Install htop, neofetch, and other useful tools
sudo apt install htop neofetch tree tmux screen

12.2 Enable Firewall​

# Enable UFW firewall
sudo ufw enable

# Check status
sudo ufw status

12.3 Set Up Automatic Updates​

# Install unattended-upgrades
sudo apt install unattended-upgrades

# Configure automatic updates
sudo dpkg-reconfigure unattended-upgrades

13. Backup and Recovery​

13.1 Create System Backup​

# Install timeshift for system snapshots
sudo apt install timeshift

# Create backup via GUI
sudo timeshift-gtk

13.2 Backup Configuration Files​

# Backup important configuration files
mkdir ~/config-backup
cp ~/.bashrc ~/config-backup/
cp ~/.profile ~/config-backup/
# Add other important configs as needed

Troubleshooting​

Common Issues and Solutions​

NVIDIA Driver Issues​

# Purge and reinstall NVIDIA drivers
sudo apt purge nvidia-* 
sudo ubuntu-drivers autoinstall
sudo reboot

CUDA Path Issues​

# Check CUDA installation path
ls /usr/local/cuda*

# Update paths in ~/.bashrc accordingly

Python Environment Conflicts​

# Reset conda environment
conda remove --name myenv --all
conda create --name myenv python=3.9
System Maintenance
  • Regularly update your system with sudo apt update && sudo apt upgrade
  • Keep your conda environments clean and organized
  • Use virtual environments for different projects
  • Monitor system resources with htop and nvidia-smi

Resources​