📅 2023-01-12 — Session: Resolved Python environment setup issues
🕒 16:15–16:35
🏷️ Labels: Python, Scikit-Learn, Environment Management, Anaconda, Vs Code
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to address and resolve issues related to Python environment setup and management, specifically focusing on scikit-learn installation and configuration in different environments.
Key Activities
- Scikit-learn Installation Check: Verified if scikit-learn was installed using Python import statements and pip commands.
- ImportError Troubleshooting: Identified common causes of
ImportErrorfor scikit-learn and explored solutions, including using virtual environments. - Python Environment Verification: Used Jupyter Notebook and command line tools to check the current Python environment.
- Conda Command Error Resolution: Provided steps to fix ‘conda: command not found’ error by adjusting the PATH variable.
- Environment Management with Anaconda: Explained how to manage and switch between Python environments using Anaconda.
- VS Code Configuration: Configured the default Python environment in Visual Studio Code by modifying settings.json.
Achievements
- Successfully identified and resolved issues related to Python environment setup, ensuring scikit-learn can be used without errors.
- Configured development environments across different platforms, enhancing workflow efficiency.
Pending Tasks
- Further exploration of advanced environment management techniques with Anaconda and Visual Studio Code might be beneficial for more complex projects.