semvec/pypi-packages huggingface dataset:
materialsearch-core 0.2.2
Core library for MaterialSearch project
Requires Python: >=3.9
Keywords: clip, materialsearch, semantic search

# MaterialSearch Core

Core Python library for [**MaterialSearch**](https://github.com/chn-lee-yumi/MaterialSearch) project.

TODO: Not compatible with new PyTorch / Transformers version yet.

## Installation

```bash
pip3 install materialsearch-core
```

## Building and Distributing

Remember to update the version number in `materialsearch_core/__init__.py` and `pyproject.toml` before building.

Install dependencies before building:

```bash
pip3 install -U build twine packaging
````

### Test Environment

```bash
python3 -m build
python3 -m twine upload --repository testpypi dist/* --verbose
python3 -m pip install -U --force-reinstall --index-url https://test.pypi.org/simple/ --no-deps materialsearch-core
# or
python3 -m pip install --force-reinstall --no-deps dist/materialsearch_core-*.whl
```

### Production Environment

```bash
python3 -m build
python3 -m twine upload dist/*
python3 -m pip install materialsearch-core
```

Or use GitHub Actions to build and publish. Create a release will trigger the workflow.
gitlab-pr-analyzer 0.9.3
Intelligent tool for collecting, analyzing, and summarizing GitLab Merge Requests and commits
Requires Python: >=3.8

## GitLab MR & Commit Analyzer

[中文文档](README.cn.md) | English

A command-line tool for intelligently collecting, analyzing, and summarizing GitLab Merge Requests and commit records.

## Installation & Setup

### Prerequisites
- **Python 3.8+**
- **GitLab access**
  - `GITLAB_HOST` (e.g. `https://gitlab.example.com`)
  - `GITLAB_TOKEN` (PAT with `read_api` or `api` scope)

### Recommended (optional)
- **GitLab CLI (glab)**: recommended for better and faster diff retrieval
  - install and authenticate: `glab auth login`

### Install GitLab CLI (glab)

- **macOS (Homebrew)**:

```bash
brew install glab
glab auth login
```

- **Linux (APT, Ubuntu/Debian)**:

```bash
sudo apt update
sudo apt install -y glab
glab auth login
```

- **Windows (Winget)**:

```powershell
winget install --id GitLab.glab
glab auth login
```

> Daily usage tip: use the short command `glpa` (legacy: `gl-pr-analyzer`, `gl-pr-ai`).

### Install

```bash
pip install gitlab-pr-analyzer
```

### Configuration (Environment Variables)

| Variable | Description | Required |
|----------|-------------|----------|
| `GITLAB_HOST` | GitLab instance base URL | **Yes** |
| `GITLAB_TOKEN` | Personal Access Token | **Yes** |
| `GITLAB_INSTANCE_NAME` | Banner display name | No |
| `CURSOR_AGENT_PATH` | Path to cursor-agent for AI features | No (Yes for AI) |

## Quick Start

```bash
# 0. Check connectivity (recommended after setting env vars)
glpa check

# 1. Interactive Mode (best for starting)
glpa interactive

# project path tip: from a URL like https://gitlab.example.com/group/subgroup/project use: --repo group/subgroup/project

# 2. Search with AI analysis (English output)
glpa search "authentication bug" --ai -r group/subgroup/project

# 3. Search with AI analysis (Chinese output)
glpa search "authentication bug" --ai -cn -r group/subgroup/project

# 4. Collect data
glpa collect --save-json -r group/subgroup/project

# 5. Generate report + export datasets
glpa traverse --days 7 --save-json -r group/subgroup/project

# optional: enable AI analysis for traverse
glpa traverse --days 7 --save-json --ai -cn -r group/subgroup/project
```

For detailed command usage, see [USAGE.md](USAGE.md).
swh.datasets 2.1.0
Tooling to generate various datasets from on the Software Heritage archive, based on swh-graph
Requires Python: >=3.9

Software Heritage - Derived Datasets
====================================

Tooling to generate various datasets from the `Software Heritage
<https://www.softwareheritage.org/>`_
`archive <https://archive.softwareheritage.org/>`_;
based on the `in-memory compressed graph representation <https://docs.softwareheritage.org/devel/swh-graph/>`_.
nabu 2025.2.3
Nabu - Tomography software
Requires Python: >=3.10
Keywords: tomography, reconstruction, X-ray imaging, synchrotron radiation, High Performance Computing, Parallel geometry, Conebeam geometry, Helical geometry, Ring artefact correction, Geometric calibration

# Nabu

ESRF tomography processing software.

## Installation

To install the development version:

```bash
pip install [--user] git+https://gitlab.esrf.fr/tomotools/nabu.git
```
To install the stable version:

```bash
pip install [--user] nabu
```

## Usage

Nabu can be used in several ways:
  - As a Python library, by features like `Backprojector`, `FlatField`, etc
  - As a standalone application with the command line interface
  - From Tomwer ([https://gitlab.esrf.fr/tomotools/tomwer/](https://gitlab.esrf.fr/tomotools/tomwer/))

To get quickly started, launch:
```bash
nabu-config 
```
Edit the generated configuration file (`nabu.conf`). Then:

```bash
nabu nabu.conf --slice 500-600
```

will reconstruct the slices 500 to 600, with processing steps depending on `nabu.conf` contents.

## Documentation

The documentation can be found on the silx.org page ([https://www.silx.org/pub/nabu/doc](http://www.silx.org/pub/nabu/doc)).

The latest documentation built by continuous integration can be found here: [https://tomotools.gitlab-pages.esrf.fr/nabu/](https://tomotools.gitlab-pages.esrf.fr/nabu/)

## Running the tests

Once nabu is installed, running

```bash
nabu-test
```
will execute all the tests. You can also specify specific module(s) to test, for example:
```bash
nabu-test preproc misc
```
You can also provide more `pytest` options, for example increase verbosity with `-v`, exit at the first fail with `-x`, etc. Use `nabu-test --help` for displaying the complete options list.



## Nabu - what's in a name ?

Nabu was the Mesopotamian god of literacy, rational arts, scribes and wisdom.
teachbooks-sphinx-grasple 1.3.0
A Sphinx extension for inserting Grasple exercises.
Requires Python: >=3.8

# Sphinx extension: Grasple

This package contains a [Sphinx](http://www.sphinx-doc.org/en/master/) extension for inserting Grasple exercises into a Jupyter book as an iframe. It allows you to easily add Grasple question with some formatting and, more importantly, the creation of QR codes in the PDF version of the page. This leads to the source link of the iframe.

This package is a continuation of the package https://github.com/dbalague/sphinx-grasple/.

[Grasple](https://app.grasple.com/) gives you an embed code for each exercise, which can be added directly to your markdown-file. This package improved the embedding. More information on Grasple and the support of TU Delft can be found on: [Teaching Support - Educational Tools - Grasple](https://www.tudelft.nl/en/teaching-support/educational-tools/grasple)

## Installation
To install the teachbooks-sphinx-grasple extension, follow these steps:

**Step 1: Install the Package**

Install the `teachbooks-sphinx-grasple` package using `pip`:
```
pip install teachbooks-sphinx-grasple
```

**Step 2: Add to `requirements.txt`**

Make sure that the package is included in your project's `requirements.txt` to track the dependency:
```
teachbooks-sphinx-grasple
```

**Step 3: Enable in `_config.yml`**

In your `_config.yml` file, add the extension to the list of Sphinx extra extensions (**important**: underscore, not dash this time):
```
sphinx: 
    extra_extensions:
        - teachbooks_sphinx_grasple
```

## Usage

To use, include the following in your Jupyter book

```
::::{grasple}
:iframeclass: dark-light
:url: https://embed.grasple.com/exercises/f6c1bb4b-e63e-492e-910a-5a8c433de281?id=75093
:label: grasple_exercise_manual
:dropdown:
:description: Cross product in $\R^4$?

::::
```

In the jupyter book this leads to a custom admonition with the exercise included (https://embed.grasple.com/exercises/f6c1bb4b-e63e-492e-910a-5a8c433de281?id=75093).

In the PDF this leads to:
![example pdf](examplepdf.png)


## Important Note

The tests provided are still the original ones from sphinx-exercise and have not (yet) been adapted.

## Contribute
This tool's repository is stored on [GitHub](https://github.com/TeachBooks/Sphinx-Grasple-public). The `README.md` of the branch `manual_docs` is also part of the [TeachBooks manual](https://teachbooks.io/manual/external/Sphinx-Grasple-public/README.html) as a submodule. If you'd like to contribute, you can create a fork and open a pull request on the [GitHub repository](https://github.com/TeachBooks/Sphinx-Grasple-public). To update the `README.md` shown in the TeachBooks manual, create a fork and open a merge request for the [GitHub repository of the manual](https://github.com/TeachBooks/manual). If you intent to clone the manual including its submodules, clone using: `git clone --recurse-submodulesgit@github.com:TeachBooks/manual.git`.