vscode-pydata-viewer installs statistics

PyData Viewer

Display Python data files in VSCode.

Supported File Types

• Numpy Files: .npz .npy
• Pickle Files: .pkl .pck .pickle .pkl.gz
• PyTorch Files: .pth .pt .ckpt

Quick Start

1. Install the extension from VS Code marketplace
2. Open any supported data file in VS Code
3. The file will automatically display with formatted content

Requirements

:pushpin: Python interpreter is required. Add Python to your system PATH or configure a custom Python path in the extension settings.

Configuration

Extension Settings

• vscode-pydata-viewer.pythonPath: Path to Python interpreter (default: "default")
• vscode-pydata-viewer.scriptPath: Path to custom processing script (default: "default")

Python Path Setup

1. Open VS Code Settings (Cmd+, or Ctrl+,)
2. Search for "pydata viewer"
3. Set Python Path:
   • System Python: Leave as "default"
   • Virtual Environment: /path/to/venv/bin/python
   • Conda Environment: /path/to/conda/envs/myenv/bin/python

Handling Local Imports

If your pickle files contain custom classes from your project, you have these options:

Option 1: Custom Processing Script

Create a custom script that imports your modules:

import sys
import pickle
from pathlib import Path

# Add your project to Python path
project_root = Path(__file__).parent.parent
sys.path.insert(0, str(project_root))

# Import your custom classes
from my_project.models import MyCustomClass

def process_pickle_file(file_path):
    with open(file_path, 'rb') as f:
        data = pickle.load(f)
    print(f"<b>Data:</b> {data}")

if __name__ == "__main__":
    file_type = int(sys.argv[1])
    file_path = sys.argv[2]
    
    if file_type == 1:  # Pickle file
        process_pickle_file(file_path)

Then set the script path in VS Code settings:

{
  "vscode-pydata-viewer.scriptPath": "/path/to/your/custom_script.py"
}

Option 2: Project Environment

Configure the extension to use your project's Python environment:

{
  "vscode-pydata-viewer.pythonPath": "/path/to/your/project/venv/bin/python"
}

Option 3: Workspace Settings

For project-specific configuration, create .vscode/settings.json:

{
  "vscode-pydata-viewer.pythonPath": "${workspaceFolder}/venv/bin/python",
  "vscode-pydata-viewer.scriptPath": "${workspaceFolder}/scripts/custom_reader.py"
}

Common Issues

"No module named 'your_module'" Error

• Use a custom script with proper imports
• Set Python path to your project environment
• Ensure your virtual environment contains required dependencies

"Python not found" Error

• Check Python installation
• Set full path to Python executable in settings
• Restart VS Code after changing settings

Examples

Basic Usage

Simply open any .npy, .pkl, or .pth file in VS Code.

Custom Objects

import pickle

class MyClass:
    def __init__(self, value):
        self.value = value

data = MyClass(42)
with open('data.pkl', 'wb') as f:
    pickle.dump(data, f)

Change Log

Please refer to CHANGELOG.md.

Related Extensions

If you don't have Python available but need to view numpy files, try vscode-numpy-viewer.