semvec/pypi-packages huggingface dataset:
pyqdpx 0.1.8
A Python module to process Qualitative Data Exchange (QDPX) XML files.
Requires Python: >=3.8

# pyqdpx

A Python module to process Qualitative Data Exchange (QDPX) XML files, which are zip-compressed archives containing a `project.qde` XML file and a `Sources` directory.

## Features

* List source files within a `.qdpx` archive.
* Retrieve content of individual source files.
* Load and manipulate `project.qde` XML data.
* Manage users (add, list) within the project.
* Manage qualitative codes (add, modify, delete, navigate hierarchy).
* Save modifications back to the `.qdpx` archive, ensuring data integrity.

## Installation

You can install `pyqdpx` using pip:

```bash
pip install pyqdpx
```

If you want to install from source for development:

```bash
git clone https://github.com/DEPT-metagenom/pyqdpx.git
cd pyqdpx
pip install .
```

## Usage

Here's a quick example of how to use pyqdpx:

```python
from pyqdpx import QDPX, User, Code
import os

# Assume 'my_project.qdpx' exists and is a valid QDPX file
# For demonstration, you might create a dummy file first as in your tests.

# Initialize the QDPX object
qdpx_file = QDPX("my_project.qdpx")

# Get the QDE project
project = qdpx_file.get_project()

if project:
    print("Project Title:", project._bs4_obj.find('Title').string)

    # List users
    print("\nUsers:")
    for user_guid, user_obj in project.users.items():
        print(f"- {user_obj.name} (ID: {user_obj.id})")

    # Add a new user
    new_user = User(id="AL", name="Ada Lovelace")
    project.add_user(new_user)
    print(f"\nAdded new user: {new_user.name}")

    # Print code tree
    print("\nCode Tree:")
    project.print_code_tree()

    # Find and modify a code
    susceptibility_code = project.find_code("1. Perceived Susceptibility")
    if susceptibility_code:
        print(f"\nOriginal Susceptibility Description: {susceptibility_code.description}")
        susceptibility_code.description = "Updated description for perceived susceptibility."
        print(f"New Susceptibility Description: {susceptibility_code.description}")

    # Save changes (this will update the project.qde inside the zip)
    project.save()
    print("\nProject saved successfully!")
else:
    print("Could not load project.")

# Clean up (if you created a dummy file for testing)
# os.remove("my_project.qdpx")
```

## Running Tests

To run the unit tests, navigate to the root directory of the package (`pyqdpx_package/`) and use pytest:

```bash
pip install pytest
pytest
```

## Contributing

Contributions are welcome! Please feel free to open issues or submit pull requests.LicenseThis project is licensed under the MIT License - see the LICENSE file for details.
torch-scalpel 0.1.0.dev0
PyTorch transformers meets fx graph manipulation
Requires Python: >=3.11

# torch-scalpel 🔬

> Surgical modifications to PyTorch transformer architectures via FX graph manipulation

## Vision

Traditional research codebases struggle with abstraction design. Predicting where innovation will emerge is impossible, making future-proof APIs elusive. Instead of building rigid abstractions around transformer components, torch-scalpel aims to treat the FX intermediate representation from `torch.compile` as the primary interface for architectural modifications.

We aim to enable surgical precision in transformer research by operating directly on computation graphs as middleware in the torch.compile pipeline. The goal is to swap normalization strategies, evolve attention mechanisms (custom implementations → optimized SDPA), experiment with activation functions... all through targeted graph-level transformations that preserve semantic structure while enabling systematic architectural evolution.

## Status
🚧 **Early Development** - Experimental, viability study phase

## Notebooks
Research notebooks exploring core concepts and validating technical feasibility before designing the library API:
- `compiled_fx_manipulations.ipynb` - FX graph exploration, pattern matching, and surgical transformations
- `replace_attention_in_fx.ipynb` - Transformer attention mechanism replacement (custom → optimized SDPA)
snakemake-storage-plugin-ftp-leshl 0.1.4
A Snakemake plugin for handling input and output via FTP
Requires Python: <4.0,>=3.11

This is a modified version of the original Snakemake FTP storage plugin:

# Snakemake storage plugin: FTP

A Snakemake storage plugin for handling input and output via FTP.
For documentation and usage instructions, see the [Snakemake plugin catalog](https://snakemake.github.io/snakemake-plugin-catalog/plugins/storage/ftp.html).