semvec/pypi-packages huggingface dataset:
scmrepo 3.6.1
scmrepo
Requires Python: >=3.9

scmrepo
=======

|PyPI| |Status| |Python Version| |License|

|Tests| |Codecov| |pre-commit| |Black|

.. |PyPI| image:: https://img.shields.io/pypi/v/scmrepo.svg
   :target: https://pypi.org/project/scmrepo/
   :alt: PyPI
.. |Status| image:: https://img.shields.io/pypi/status/scmrepo.svg
   :target: https://pypi.org/project/scmrepo/
   :alt: Status
.. |Python Version| image:: https://img.shields.io/pypi/pyversions/scmrepo
   :target: https://pypi.org/project/scmrepo
   :alt: Python Version
.. |License| image:: https://img.shields.io/pypi/l/scmrepo
   :target: https://opensource.org/licenses/Apache-2.0
   :alt: License
.. |Tests| image:: https://github.com/treeverse/scmrepo/workflows/Tests/badge.svg
   :target: https://github.com/treeverse/scmrepo/actions?workflow=Tests
   :alt: Tests
.. |Codecov| image:: https://codecov.io/gh/treeverse/scmrepo/branch/main/graph/badge.svg
   :target: https://app.codecov.io/gh/treeverse/scmrepo
   :alt: Codecov
.. |pre-commit| image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white
   :target: https://github.com/pre-commit/pre-commit
   :alt: pre-commit
.. |Black| image:: https://img.shields.io/badge/code%20style-black-000000.svg
   :target: https://github.com/psf/black
   :alt: Black


SCM wrapper and fsspec filesystem for Git for use in DVC.


Features
--------

* Works with multiple backends: ``pygit2``, ``dulwich`` and ``gitpython``.
* Provides fsspec filesystem over Git: ``GitFileSystem``.


See `fsspec docs`_ for full list of available fs methods.


Requirements
------------


Installation
------------

You can install *scmrepo* via pip_ from PyPI_:

.. code:: console

   $ pip install scmrepo


Usage
-----

Git File System
^^^^^^^^^^^^^^^

scmrepo provides `fsspec`_ based gitfs that provides fs-like API for your git
repositories without having to ``git checkout`` them first. For example:

.. code-block:: python

    from scmrepo.fs import GitFileSystem

    fs = GitFileSystem("path/to/my/repo", rev="mybranch")

    for root, dnames, fnames in fs.walk("path/in/repo"):
        for dname in dnames:
            print(fs.path.join(root, dname))

        for fname in fnames:
            print(fs.path.join(root, fname))


Contributing
------------

Contributions are very welcome.
To learn more, see the `Contributor Guide`_.


License
-------

Distributed under the terms of the `Apache 2.0 license`_,
*scmrepo* is free and open source software.


Issues
------

If you encounter any problems,
please `file an issue`_ along with a detailed description.


.. _Apache 2.0 license: https://opensource.org/licenses/Apache-2.0
.. _fsspec: https://filesystem-spec.readthedocs.io/
.. _fsspec docs: https://filesystem-spec.readthedocs.io/en/latest/api.html?highlight=walk#fsspec.spec.AbstractFileSystem
.. _PyPI: https://pypi.org/
.. _file an issue: https://github.com/treeverse/scmrepo/issues
.. _pip: https://pip.pypa.io/
.. github-only
.. _Contributor Guide: CONTRIBUTING.rst
stashmap 0.1.0
Decode and map UM STASH metadata
Requires Python: >=3.10



# Welcome to stashmap

|  |  |
|----|----|
| Package | [![Latest PyPI Version](https://img.shields.io/pypi/v/stashmap.svg)](https://pypi.org/project/stashmap/) [![Supported Python Versions](https://img.shields.io/pypi/pyversions/stashmap.svg)](https://pypi.org/project/stashmap/) |
| Coverage | [![Codecov test coverage](https://codecov.io/gh/21centuryweather/stashmap/graph/badge.svg)](https://app.codecov.io/gh/21centuryweather/stashmap) |

The `stashmap` package provides functions to read and modify the stash
and associated variables for the UM model. It main focus is to convert
the relevant sections in the UM namelist (usually in `rose-app.conf`)
into a `.csv` file for easy manipulation and then convert it back to the
namelist format.

It also includes helpers to get variable names from stash codes and to
get the human version for the time and domain profiles.

## Get started

For now, you can install this package into your preferred Python
environment using:

``` bash
$ pip install git+https://github.com/21centuryweather/stashmap.git
```

## Example

``` python
import stashmap
```

Read from namelist:

``` python
sections = stashmap.read_namelist("examples/rose-app.conf", print_summary=True)
```

    Parsed 215 sections — DomainProfile: 8/26, OutputStream: 7/12, TimeProfile: 10/26, UseProfile: 8/14, Variable: 133/137

Add human-readable variable names:

``` python
stashmap.describe_variable(sections)

variables = [s for s in sections if isinstance(s, stashmap.Variable)]

for v in variables[0:15]:
    print("isec=", v.record.get('isec'), "item=", v.record.get('item'), "->", v.record.get('description'))
```

    isec= 0 item= 2 -> U COMPNT OF WIND AFTER TIMESTEP
    isec= 0 item= 2 -> U COMPNT OF WIND AFTER TIMESTEP
    isec= 0 item= 3 -> V COMPNT OF WIND AFTER TIMESTEP
    isec= 0 item= 3 -> V COMPNT OF WIND AFTER TIMESTEP
    isec= 0 item= 4 -> THETA AFTER TIMESTEP
    isec= 0 item= 4 -> THETA AFTER TIMESTEP
    isec= 0 item= 10 -> SPECIFIC HUMIDITY AFTER TIMESTEP
    isec= 0 item= 10 -> SPECIFIC HUMIDITY AFTER TIMESTEP
    isec= 0 item= 12 -> QCF AFTER TIMESTEP
    isec= 0 item= 12 -> QCF AFTER TIMESTEP
    isec= 0 item= 24 -> SURFACE TEMPERATURE AFTER TIMESTEP
    isec= 0 item= 24 -> SURFACE TEMPERATURE AFTER TIMESTEP
    isec= 0 item= 25 -> BOUNDARY LAYER DEPTH AFTER TIMESTEP
    isec= 0 item= 150 -> W COMPNT OF WIND AFTER TIMESTEP
    isec= 0 item= 150 -> W COMPNT OF WIND AFTER TIMESTEP

And write to csv:

``` python
stashmap.export_sections_to_csv(sections, "examples/stash", section_type="variables")
```

## Copyright

- Copyright © 2025 Pao Corrales.
- Free software distributed under the [MIT License](./LICENSE).
eden-diff-surfel-rasterization 0.1.0b0
Differentiable rasterizer for 2D Gaussian Splatting
Requires Python: >=3.7

# Differential Surfel Rasterization

```bash
pip install eden-diff-surfel-rasterization==0.1.0a0
```


This is the rasterization engine for the paper "2D Gaussian Splatting for  Geometrically Accurate Radiance Fields". If you can make use of it in your own research, please be so kind to cite us.

<section class="section" id="BibTeX">
  <div class="container is-max-desktop content">
    <h2 class="title">BibTeX</h2>
    <pre><code>@inproceedings{Huang2DGS2024,
    title={2D Gaussian Splatting for Geometrically Accurate Radiance Fields},
    author={Huang, Binbin and Yu, Zehao and Chen, Anpei and Geiger, Andreas and Gao, Shenghua},
    publisher = {Association for Computing Machinery},
    booktitle = {SIGGRAPH 2024 Conference Papers},
    year      = {2024},
    doi       = {10.1145/3641519.3657428}
}</code></pre>
  </div>
</section>

<section class="section" id="BibTeX">
  <div class="container is-max-desktop content">
    <h2 class="title">BibTeX</h2>
    <pre><code>@Article{kerbl3Dgaussians,
      author       = {Kerbl, Bernhard and Kopanas, Georgios and Leimk{\"u}hler, Thomas and Drettakis, George},
      title        = {3D Gaussian Splatting for Real-Time Radiance Field Rendering},
      journal      = {ACM Transactions on Graphics},
      number       = {4},
      volume       = {42},
      month        = {July},
      year         = {2023},
      url          = {https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/}
}</code></pre>
  </div>
</section>
bfly 0.1.0
Basic Bluesky CLI Tool
Requires Python: >=3.11
Keywords: bluesky, cli, tool

# 🦋 bfly

The `bfly` tool is a simplistic command line tool for posting short messages or links to BlueSky social network.

## Purpose

The main purpose of this tool, and the reason it was built was the need to have a quick and easy tool for posting
BlueSky announcements as part of a build and release script.

## Usage


```bash
Usage:
        bfly <subcommand> [argumens]

Subcommands:
        post <text>             Post to Bsky. Enclose <text> in quotes.
        annouce <text> <url>    Post a link. Put <text> in quotes.

Options:
        -h, --help      Show this help message
        -v, --version   Show version information

Options must be used as the first argument.
```

## Configuration

To use `bfly`, you need to set two environment variables:

- `BFLY_HANDLE` - your BlueSky username (e.g. `user.bsky.social`)
- `BFLY_APP_PASSWORD` - an app password generated via your BlueSky account settings


## Installation

You can install `bfly` via `uv`:

```bash
uv tool install bfly
```

You can also run `bfly` directly without installation:

```bash
uv tool run bfly <subcommand> [arguments]
```

On Windows, this tool is distributed via `scoop` (see [scoop.sh](https://scoop.sh)).

First, you need to add my bucket:

    scoop bucket add maciak https://github.com/maciakl/bucket
    scoop update

Next simply run:
 
    scoop install bmpv

If you don't want to use `scoop` you can simply download the executable from the release page and extract it somewhere in your path.
gengar 0.1.2
A simple library for AI/ML algorithm code snippets
Requires Python: >=3.6

# AI Lab Code Library

Simple library to access ML algorithm implementations.

## Installation
```
pip install ailab-yourname
```

## Usage
```python
from ailab import code_1, list_code

# Print specific code
list_code(1)

# Or access directly
print(code_6)
```
```

**LICENSE** (create MIT License)
```
MIT License

Copyright (c) 2026 Your Name

Permission is hereby granted, free of charge...
suitesparse-amd 0.3.5
A Python wrapper for the C-Library for SuiteSparse's Approximate Minimum Degree (AMD) algorithm
Requires Python: >=3.10
Keywords: suitesparse, amd, sparse, approximate minimum degree

# SuiteSparse-AMD

[![Build and upload to PyPI](https://github.com/Marius-Juston/SuiteSparse/actions/workflows/wheels.yml/badge.svg?event=release)](https://github.com/Marius-Juston/SuiteSparse/actions/workflows/wheels.yml) [![Super-Linter](https://github.com/Marius-Juston/SuiteSparse/actions/workflows/lint.yml/badge.svg)](https://github.com/marketplace/actions/super-linter) [![Python Testing package](https://github.com/Marius-Juston/SuiteSparse/actions/workflows/tests.yml/badge.svg)](https://github.com/Marius-Juston/SuiteSparse/actions/workflows/tests.yml)

This package is the port of the SuiteSparse AMD (Approximate Minimum Degree) function. This is a Python C wrapper of the library from [SuiteSparse](https://github.com/DrTimothyAldenDavis/SuiteSparse).

This package currently only works with Numpy arrays, 2D lists and PyTorch Tensors in the CPU.

## Installation

### PyPi

```bash
pip install suitesparse-amd
```

### Source Installation

```bash
pip install git+https://github.com/Marius-Juston/SuiteSparse.git
```

### Compile Source

```bash
python3 -m build --wheel --sdist
```

## Publish

```bash
bumpver update --tag-commit --patch --push
```