semvec/pypi-packages huggingface dataset:
libefiling 0.1.42
A Python library for e-filing systems.
Requires Python: >=3.12
Keywords: example, testpypi, demo

# libefiling

This library targets electronic filing data provided by the Japan Patent Office (JPO).
Detailed documentation is written in Japanese, as the primary users are Japanese.

## 概要
 libefiling は インターネット出願ソフトのアーカイブを扱う python パッケージです。
 - [インターネット出願ソフト](https://www.pcinfo.jpo.go.jp/site/): 日本国特許庁に特許など出願する際に使うアプリ
 - アーカイブ: インターネット出願ソフトの「データ出力」で保存されるようなJWX(JPC,JWX)を本パッケージではそう呼んでる。
 - データ出力でアーカイブと一緒に出力されるXMLを手続XMLと呼ぶことにする。

## 機能
 - アーカイブの展開 -> XML, 画像ファイルが得られる
 - 画像ファイルのフォーマット変換、サイズ変換
 - XMLファイルの文字コード変換
 - いまのところ 特許願(A163) だけが処理対象。

## 動作環境
 - ubuntu bookworm
 - python 3.14
 - tesseract

### 必要アプリのインストール
```bash
apt-get update
apt-get install -y python3.14 tesseract-ocr tesseract-ocr-jpn
```

### libefiling パッケージのインストール
```bash
pip install libefiling
```

## 使い方
```python
from libefiling import parse_archive, ImageConvertParam, generate_sha256

params = [
    ImageConvertParam(
        width=300,
        height=300,
        suffix="-thumbnail",
        format=".webp",
        attributes=[{"key": "sizeTag", "value": "thumbnail"}],
    ),
    ImageConvertParam(
        width=600,
        height=600,
        suffix="-middle",
        format=".webp",
        attributes=[{"key": "sizeTag", "value": "middle"}],
    ),
    ImageConvertParam(
        width=800,
        height=0,
        suffix="-large",
        format=".webp",
        attributes=[{"key": "sizeTag", "value": "large"}],
    ),
]

SRC='202501010000123456_A163_____XXXXXXXXXX__99999999999_____AAA.JWX'
PROC='202501010000123456_A163_____XXXXXXXXXX__99999999999_____AFM.XML'
OUT='output'
doc_id = generate_sha256(SRC)
if doc_id === '...':
    print("Already processed")
else:
    parse_archive(SRC, PROC, OUT, params)
```
generate_sha256 はアーカイブの内容に応じたハッシュ値を生成し、再処理判定用に使える。
parse_archive は SRC,PROCを OUTに展開する。第4引数に、画像変換のパラメータを渡せる。
OUT に各種ファイルが展開される。

#### 出力ファイル
 - manifest.json : 展開後のファイルの情報
 - raw/ : SRC に含まれてたファイルが展展されてる。
 - xml/ : raw/*.xml 、PROC を文字コード変換したxml, イメージ変換の対応を表したxml が保存されてる。
 - images/ : raw の画像ファイルがparamsに従って変換された画像が保存されてる。
 - ocr/ : raw の画像ファイルごとにOCR処理してえられたテキストが保存されてる。


## 注意事項
 - テストは十分でないので、いろいろバグあるとおもう。
 - 読み取り元のファイル(SRC,PROCに指定したファイル)や展開後のファイルは、どこかに送信されることはありません。ソースみてもらえば。
 - 本アプリで何らかの損害を被っても本アプリ作者は責任を負いません。

## ライセンス
MIT ライセンス

## Reference
特許庁 日本国特許庁電子文書交換標準仕様XML編 （抜粋版）
  https://www.jpo.go.jp/system/patent/gaiyo/sesaku/document/touroku_jyohou_kikan/shomen-entry-02jpo-shiyosho.pdf


## 変更履歴
0.1.40
 - manifest の形式変更
   - xml, image の path を filename にした。
AImodelsDB 0.1.0
SQLite database of AI models as fetched from models.dev
Requires Python: >=3.10

# AImodelsDB

SQLite database of AI models as fetched from the [models.dev](https://github.com/anomalyco/models.dev) endpoint,
which is maintained by the [anomalyco/models.dev](https://github.com/anomalyco/models.dev) community.

## Installation

```bash
pip install AImodelsDB
```

## Create the database

```bash
python3 -m AImodelsDB.create
```

Then query with:

```bash
sqlite3 ~/.local/share/sqlite-dbs/AImodels.db
```

## Usage

```python
from AImodelsDB import open_AImodels_db

# Get an sqlite3 Connection object to the
# database:
con = open_AImodels_db()
```

## Database Schema

### provider
- `id` (text, primary key)
- `name` (text)
- `npm` (text)
- `env` (text)
- `api` (text)
- `doc` (text)

### model
- `id` (text)
- `name` (text)
- `provider` (text, foreign key)
- `family` (text)
- `open_weights` (integer)
- `status` (text)
- `rel_dt` (text)
- `upd_dt` (text)
- `cutoff_dt` (text)
- `attachment` (integer)
- `reasoning` (integer)
- `struct_out` (integer)
- `tool_call` (integer)
- `temperature` (integer)
- `lim_ctx` (integer)
- `lim_in` (integer)
- `lim_out` (integer)
- `mod_in` (text)
- `mod_out` (text)
- `cost_input` (real)
- `cost_output` (real)
- `cost_cache_read` (real)
- `cost_cache_write` (real)
- `cost_audio_in` (real)
- `cost_audio_out` (real)
- `cost_reasoning` (real)
- `interleaved` (text)
swh.graph 11.1.0
Software Heritage graph service
Requires Python: >=3.11

Software Heritage - graph service
=================================

Tooling and services, collectively known as ``swh-graph``, providing fast
access to the graph representation of the `Software Heritage
<https://www.softwareheritage.org/>`_
`archive <https://archive.softwareheritage.org/>`_.  The service is in-memory,
based on a compressed representation of the Software Heritage Merkle DAG.


Bibliography
------------

In addition to accompanying technical documentation, ``swh-graph`` is also
described in the following scientific papers. If you use ``swh-graph`` for your
research work, please acknowledge it by citing:

.. note::

  Paolo Boldi, Antoine Pietri, Sebastiano Vigna, Stefano Zacchiroli.
  `Ultra-Large-Scale Repository Analysis via Graph Compression
  <https://ieeexplore.ieee.org/document/9054827>`_. In proceedings of `SANER
  2020 <https://saner2020.csd.uwo.ca/>`_: The 27th IEEE International
  Conference on Software Analysis, Evolution and Reengineering, pages
  184-194. IEEE 2020.

  Links: `preprint <https://upsilon.cc/~zack/research/publications/saner-2020-swh-graph.pdf>`__,
  `bibtex <https://upsilon.cc/~zack/research/publications/saner-2020-swh-graph.bib>`__.

  Tommaso Fontana, Sebastiano Vigna, Stefano Zacchiroli.
  `WebGraph: The Next Generation (Is in Rust) <https://dl.acm.org/doi/abs/10.1145/3589335.3651581>`_.
  In proceedings of `WWW'24 <https://www2024.thewebconf.org/>`_:
  The ACM Web Conference 2024. Pages 686-689. ACM 2024.

  Links: `preprint <https://hal.science/hal-04494627/>`__,
  `bibtex <https://dblp.dagstuhl.de/rec/conf/www/FontanaVZ24.bib?param=1>`__.
fastbreak 0.0.3
Async NBA statistics API client
Requires Python: >=3.12
Keywords: analytics, api, basketball, nba, sports, statistics, stats

# fastbreak

[![PyPI](https://img.shields.io/pypi/v/fastbreak)](https://pypi.org/project/fastbreak/)
[![Python](https://img.shields.io/pypi/pyversions/fastbreak)](https://pypi.org/project/fastbreak/)
[![License](https://img.shields.io/github/license/reidhoch/fastbreak)](https://github.com/reidhoch/fastbreak/blob/main/LICENSE)
[![CI](https://img.shields.io/github/actions/workflow/status/reidhoch/fastbreak/ci.yaml?label=CI)](https://github.com/reidhoch/fastbreak/actions)

Async Python client for the NBA Stats API. Fully typed, with Pydantic models and optional DataFrame conversion.

## Installation

```bash
pip install fastbreak
```

With DataFrame support:

```bash
pip install fastbreak pandas   # or polars
```

## Quick Start

```python
import asyncio
from fastbreak.clients import NBAClient
from fastbreak.endpoints import LeagueStandings

async def main():
    async with NBAClient() as client:
        standings = await client.get(LeagueStandings(season="2025-26"))

        for team in standings.standings[:5]:
            print(f"{team.team_name}: {team.wins}-{team.losses}")

asyncio.run(main())
```

### Convert to DataFrame

```python
from fastbreak.models import TeamStanding

# To pandas
df = TeamStanding.to_pandas(standings.standings)

# To polars
df = TeamStanding.to_polars(standings.standings)
```

## Features

- **Async-first** - Built on aiohttp for high-performance concurrent requests
- **Fully typed** - Complete type hints with strict mypy compliance
- **Pydantic models** - Validated response parsing with IDE autocomplete
- **DataFrame support** - Optional conversion to pandas or polars
- **Automatic retries** - Handles rate limiting and transient errors

## Available Endpoints

100+ endpoints covering:

| Category | Examples |
|----------|----------|
| **Box Scores** | `BoxScoreTraditional`, `BoxScoreAdvanced`, `BoxScorePlayerTrack` |
| **Players** | `PlayerCareerStats`, `PlayerGameLogs`, `PlayerDashboardByClutch` |
| **Teams** | `TeamDetails`, `TeamGameLog`, `TeamPlayerDashboard` |
| **League** | `LeagueStandings`, `LeagueLeaders`, `LeagueGameLog` |
| **Play-by-Play** | `PlayByPlay`, `GameRotation` |
| **Shooting** | `ShotChartDetail`, `ShotChartLeaguewide` |
| **Draft** | `DraftHistory`, `DraftCombineStats` |

See [`fastbreak.endpoints`](https://github.com/reidhoch/fastbreak/tree/main/src/fastbreak/endpoints) for the full list.

## Contributing

Contributions are welcome! See [CONTRIBUTING.md](CONTRIBUTING.md) for development setup and guidelines.

## License

MIT License - see [LICENSE](LICENSE) for details.

## Stargazers

[![Stargazers](https://api.star-history.com/svg?repos=reidhoch/fastbreak&type=date&legend=top-left)](https://www.star-history.com/#reidhoch/fastbreak&type=date&legend=top-left)
catrole 0.1.7
AWS IAM Role/Policy permission viewer — see what a role or policy can do
Requires Python: >=3.11

# catrole

> catrole is a python pip package which let's you:

AWS IAM Role/Policy permission viewer — see what a role or policy can do.

## Requirements

- Python >= 3.11
- AWS credentials configured (via `~/.aws/credentials`, environment variables, or SSO)
- A cross-account IAM role you can assume in target account(s)

## Installation

### From source (local)

```bash
git clone <repo-url>
cd cat-role
pip3 install .
```

For development (editable install):

```bash
pip3 install -e .
```

### From PyPI (remote)

```bash
pip3 install catrole
```

## Usage

`catrole` uses `-R` to specify an IAM role to assume in the target account.

If `-R` is not provided, `catrole` reads the role name from `~/.catrole`.

### Setting a default assume role

```bash
echo "my-readonly-role" > ~/.catrole
```

Once set, you can omit `-R` from all commands:

```bash
catrole -a 123456789012 -r MyAppRole
```

`-R` on the command line always takes precedence over `~/.catrole`.

### Scan a role

```bash
catrole -R my-readonly-role -a 123456789012 -r MyAppRole
```

### Scan a policy

```bash
catrole -R my-readonly-role -a 123456789012 -p MyPolicy
```

### Scan by ARN

```bash
catrole -R my-readonly-role -A arn:aws:iam::123456789012:role/MyAppRole
```

### Search across all org accounts

```bash
catrole -R my-readonly-role -s '*lambda*'
```

### Search within a single account

```bash
catrole -R my-readonly-role -s '*admin*' -a 123456789012
```

Results are printed as a table and automatically saved to a CSV file.

Run `catrole -h` for full help.