semvec/pypi-packages huggingface dataset:
fplstat 0.3.0
Python package for Fantasy Premier League data analysis and transformations
Requires Python: >=3.11

# FPLstat
Python package for Fantasy Premier League data analysis and transformations

```bash
pip install fplstat
```

---

**Documentation**: [https://james-leslie.github.io/fplstat/](https://james-leslie.github.io/fplstat)

**Source code**: [https://github.com/James-Leslie/fplstat](https://github.com/James-Leslie/fplstat)

---
lightwave-core 0.3.2
Shared Django utilities for LightWave Media projects
Requires Python: >=3.12

# lightwave-core

Shared Django utilities for LightWave Media projects.

## Installation

```bash
# Local development (from workspace root)
uv pip install -e packages/lightwave-core

# With billing support (Stripe)
uv pip install -e "packages/lightwave-core[billing]"

# In a project's requirements.txt
-e file:../../packages/lightwave-core
```

## Modules

### Storage (`lightwave.storage`)

CDN and S3 storage backends for static files and media.

```python
from lightwave.storage import StaticStorage, PublicMediaStorage, PrivateMediaStorage

# In settings.py
STORAGES = {
    "staticfiles": {"BACKEND": "lightwave.storage.StaticStorage"},
    "default": {"BACKEND": "lightwave.storage.PublicMediaStorage"},
}

# Configure static file prefix per project
LIGHTWAVE_STATIC_PREFIX = "static/my-project"
```

### Utils (`lightwave.utils`)

Common utilities including BaseModel, timezone helpers, slug generation.

```python
from lightwave.utils import BaseModel, get_common_timezones, get_next_unique_slug

class MyModel(BaseModel):
    # Automatically has created_at and updated_at fields
    name = models.CharField(max_length=100)
```

### Auth (`lightwave.auth`)

Base user model and authentication helpers.

```python
from lightwave.auth import BaseCustomUser, validate_profile_picture

class CustomUser(BaseCustomUser):
    # Inherits avatar, language, timezone, gravatar support
    # Add project-specific fields
    stripe_customer = models.ForeignKey(...)
```

### Chat (`lightwave.chat`)

Base models for AI chat sessions.

```python
from lightwave.chat import BaseChatSession, BaseChatMessage, ChatTypes, MessageTypes

class Chat(BaseChatSession):
    agent_type = models.CharField(...)

class ChatMessage(BaseChatMessage):
    chat = models.ForeignKey(Chat, on_delete=models.CASCADE, related_name="messages")
```

## Development

### Setup

1. Install dependencies:
   ```bash
   uv pip install -e ".[dev]"
   ```

2. Install pre-commit hooks:
   ```bash
   pre-commit install
   ```
   This ensures code is automatically formatted and checked before each commit.

### Running Tests

```bash
uv run pytest
```

## Optional Dependencies

- `billing`: Stripe utilities via dj-stripe (`uv pip install lightwave-core[billing]`)
- `dev`: Testing utilities (`uv pip install lightwave-core[dev]`)
agredadb 2.0.0
Official Python Client for AgredaDB - The Limitless Database
Requires Python: >=3.7

# AgredaDB Python SDK

Official Python client for AgredaDB v2.0 - The Limitless Database.

## Installation

```bash
pip install agredadb
```

## Quick Start

```python
from agredadb import AgredaDBClient

# Connect to AgredaDB
client = AgredaDBClient("localhost:19999")

# Insert data
client.insert("users", {
    "id": 1,
    "name": "John Doe",
    "email": "john@example.com",
    "vector": [0.1, 0.2, 0.3, 0.4],
    "metadata": {"type": "user"}
})

# Get data
user = client.get("users", "id", 1)
print(user)

# Vector search
results = client.search("users", 
    vector=[0.1, 0.2, 0.3, 0.4], 
    limit=10
)

# Close connection
client.close()
```

## Features

- ✅ Simple and intuitive API
- ✅ Vector similarity search
- ✅ Batch operations
- ✅ PyTorch/NumPy integration
- ✅ Context manager support
- ✅ Type hints

## Documentation

Full documentation available at: https://github.com/luisagreda-aidev/agredadb

## License

GNU Affero General Public License v3 (AGPLv3)

## Author

Luis Eduardo Agreda Gonzalez
- Email: luisagreda.ai@gmail.com
- LinkedIn: [luis-agreda-artificial-intelligence-engineer](https://www.linkedin.com/in/luis-agreda-artificial-intelligence-engineer)
oryn 2.1
PEP 517-compliant build backend
Requires Python: ~=3.12

# Oryn

Oryn is a PEP 517-compliant build backend for Python projects.

For now, Oryn only supports pure Python wheels and just recursively copies files from the project root into the wheel, making sure to ignore certain files. It also copies the appropriate metadata from `pyproject.toml` into the wheel's metadata.

Oryn supports Python 3.12 and later.


## Usage

Add the following to your `pyproject.toml`:

```toml
[build-system]
requires = ["oryn~=1.0"]
build-backend = "oryn"

[tool.oryn]
# 1. Add inclusion roots
# Only the last part of the path is retained in the wheel. Paths are relative
# to the project root despite the absence of a leading slash.

# For a src layout
include = ["src/foo/"]
include = ["src/*/"]

# For a flat layout
include = ["foo/"]

# 2. Add ignored files, using patterns similar to .gitignore.
ignore = [
  "*.pyc",
]

# 3. Optionally reuse existing .gitignore rules.
use-gitignore = true

[[tool.oryn.distributions]]
abi = "abi3"
interpreter = "cp311"
platform = "macosx_14_0_arm64"

# 4. Optionally override specific files in the wheel.
overrides = { "src/foo.so": "builds/linux-cp311.so" }
```

The following files are ignored by default:

- `__pycache__/`
- `.DS_Store`
- `.git/`
- `.gitignore`
- `.venv/`
- `*.egg-info/`

To show which files will be included, install Oryn and run `python -m oryn`. If using uv, run `uv run --with oryn python -m oryn`
jax-mcp 0.1.0
MCP server for JAX documentation
Requires Python: >=3.10

# jax-mcp

MCP (Model Context Protocol) server for [JAX](https://github.com/google/jax) documentation.

Enables LLMs to access up-to-date JAX documentation and validate generated code.

## Installation

```bash
pip install -e .
```

Or run directly:

```bash
python -m jax_mcp
```

## Usage with Claude Code

```bash
# Add as MCP server
claude mcp add -t stdio -s user jax -- python -m jax_mcp

# Or if installed globally
claude mcp add -t stdio -s user jax -- jax-mcp
```

## Configuration

| Environment Variable | Default | Description |
|---------------------|---------|-------------|
| `JAX_DOCS_PATH` | (none) | Path to local JAX docs directory (offline mode) |
| `JAX_MCP_CACHE_DIR` | `~/.cache/jax-mcp` | Cache directory for online mode |
| `JAX_MCP_CACHE_TTL` | `24` | Cache TTL in hours |
| `JAX_MCP_NO_CACHE` | `0` | Set to `1` to disable caching |

### Offline Mode

Point to a local JAX clone for offline access:

```bash
export JAX_DOCS_PATH=/path/to/jax/docs
python -m jax_mcp
```

### Online Mode (Default)

Fetches docs from GitHub with local caching:

```bash
python -m jax_mcp
# Fetches from: raw.githubusercontent.com/google/jax/main/docs/
```

## Available Tools

| Tool | Description |
|------|-------------|
| `list-sections` | List all documentation sections by category |
| `get-documentation` | Fetch specific documentation content |
| `jax-checker` | Validate JAX code for common gotchas |

### Documentation Categories

- **concepts**: Core JAX concepts (pytrees, transformations, tracing)
- **gotchas**: Common mistakes and how to avoid them
- **transforms**: jit, vmap, grad, scan patterns
- **advanced**: Distributed computing, custom pytrees
- **performance**: GPU tips, profiling, benchmarking
- **api**: Module overviews (jax.numpy, jax.lax, jax.random)
- **examples**: Practical code examples

### JAX Checker

The `jax-checker` tool catches common JAX mistakes:

- In-place array mutations (`array[idx] = value`)
- Side effects in jitted functions (print, globals)
- PRNG key reuse without splitting
- Python control flow in traced code
- Missing `block_until_ready()` for benchmarks
- Float64 usage without config

## Development

```bash
# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest
```

## License

MIT
ckr-lang 0.1.7
A Fan-made Python interpreter for the ChoiKangRok Esolang
Requires Python: >=3.8
Keywords: esolang, choikangrok, interpreter, korean, fan-made, parody

# ChoiKangRok Esolang Interpreter (CKR-Lang)

> [!CAUTION]
> **스포일러 경고 (Spoiler Alert)**
> 이 프로젝트는 넷플릭스 예능 **'흑백요리사2: 요리 계급 전쟁 (Culinary Class Wars 2)'**의 스포일러를 포함할 수 있습니다.
> 방송 내용을 미리 알고 싶지 않으신 분은 즉시 이 페이지를 닫아주시기 바랍니다.

## 프로젝트 소개
> [!NOTE]
> **Unofficial Fan Project**
> 이 프로젝트는 넷플릭스 예능 '흑백요리사2'와 최강록 셰프의 팬이 만든 **비공식 팬 메이드 프로젝트**입니다. 
> 공식 컨텐츠나 인물과는 관계가 없으며, 순수한 팬심과 프로그래밍의 즐거움을 위해 제작되었습니다.

**CKR-Lang**은 '최강록' 셰프의 독특한 화법과 조리법을 프로그래밍 언어로 재해석한 난해한 프로그래밍 언어(Esolang) 인터프리터입니다.
엄격한 명세 준수, 모듈화된 아키텍처, 그리고 강력한 디버깅 기능을 제공하며, 이제 `pip`를 통해 간편하게 설치할 수 있습니다.

## 설치 방법 (Installation)
Python 3.8 이상 환경에서 다음 명령어로 패키지를 설치하십시오.

```bash
pip install ckr-lang
```

## 사용법 (Usage)
설치가 완료되면 터미널 어디서든 `ckr` 명령어를 사용할 수 있습니다.

### 1. 코드 실행
```bash
ckr hello_world.ckr
```

### 2. 대화형 모드 (REPL)
파일 인자 없이 실행하면 한 줄씩 코드를 입력하고 실행 결과를 확인할 수 있습니다.
```bash
ckr
```

### 3. 디버그 모드
실행 과정을 상세히 추적(Trace)하고 싶다면 `-d` 옵션을 사용하세요.
```bash
ckr hello_world.ckr -d
```

### 4. 자체 테스트
인터프리터의 정상 동작 여부를 검증하려면 다음 명령어를 실행하세요.
```bash
ckr --test
```

## 조리법 (Syntax)
이 언어는 셰프의 주방을 시뮬레이션합니다. 모든 데이터는 '재료'이며, 조리 과정을 통해 맛(값)이 변합니다.

- **개점/폐점 (Program Scope)**
  - 시작: `흑백요리사2 히든백수저 최강록`
  - 끝: `백수저 최강록 우승`

- **재료 손질 (Ingredients)**
  - 선언: `나야 <재료명>` (재료를 0으로 초기화)
  - *추천 재료: 장어, 두부, 대파, 꽃게, 새우, 전복, 아귀 등*

- **조리 (Cooking Operations)**
  - `조려` (ADD): 더하기
  - `조린다` (SUB): 빼기
  - `조리고` (MUL): 곱하기
  - `앙` (INVERSE): 부호 반전

- **플레이팅 (Plating)**
  - `을` (Print): 현재 재료의 맛(Value)을 문자로 변환하여 접시에 냅니다 (ASCII Output).

- **주방 동선 (Control Flow)**
    - `연쇄조림마<점>` (Label): 이동할 지점을 점(`.`)으로 표시합니다. (예: `연쇄조림마.`, `연쇄조림마..`)
  - `조림핑<점>` (GOTO): 해당 지점으로 이동합니다. 점을 붙여서 바로 이동할 수 있습니다. (예: `조림핑.`, `조림핑..`, `조림핑...`)
  - **조건부 이동**:
    - `조림인간` (IF ==): 재료들의 맛이 동일하면 이동합니다.
    - `욕망의조림인간` (IF >): 첫 번째 재료의 맛이 나머지보다 강하면 이동합니다.

## 예제 코드 (Examples)
- `examples/hello_world.ckr`: 기본적인 Hello World 출력
- `examples/hello_fun_world.ckr`: 좀더 난해하게 작성된 Hello World
- `examples/gugu_dan.ckr`: 2단부터 9단까지 구구단을 출력하는 프로그램
parallelworks-client 6.12.0
Official Python SDK for Parallel Works ACTIVATE
Requires Python: >=3.9
Keywords: activate, api, client, hpc, parallelworks, sdk

# parallelworks-client

Official Python client for the Parallel Works ACTIVATE platform API.

## Installation

```bash
pip install parallelworks-client
```

## Quick Start

The simplest way to create a client - just pass your credential:

```python
import os
from parallelworks_client import Client

# The platform host is automatically extracted from your credential
with Client.from_credential(os.environ["PW_API_KEY"]).sync() as client:
    response = client.get("/api/buckets")
    for bucket in response.json():
        print(f"Bucket: {bucket['name']}")
```

See the [examples](./examples) directory for complete runnable examples.

## Authentication

### Automatic Host Detection

API keys (`pwt_...`) and JWT tokens contain the platform host encoded within them. Use `from_credential` to automatically extract it:

```python
# API key - host decoded from first segment after pwt_
client = Client.from_credential("pwt_Y2xvdWQucGFyYWxsZWwud29ya3M.xxxxx")
# Connects to: https://activate.parallel.works

# JWT token - host read from platform_host claim
client = Client.from_credential("eyJhbGci...")
# Connects to the host in the token's platform_host claim
```

### Explicit Host

If you prefer to specify the host explicitly:

```python
# API Key (Basic Auth) - best for long-running integrations
client = Client.with_api_key(
    "https://activate.parallel.works",
    "pwt_..."
)

# JWT Token (Bearer) - best for scripts, expires in 24h
client = Client.with_token(
    "https://activate.parallel.works",
    "eyJhbGci..."
)

# Auto-detect credential type
client = Client.with_credential(
    "https://activate.parallel.works",
    os.environ["PW_CREDENTIAL"]
)
```

### Credential Helpers

```python
from parallelworks_client import is_api_key, is_token, extract_platform_host

is_api_key("pwt_abc.xyz")           # True
is_token("eyJ.abc.def")             # True
extract_platform_host("pwt_...")    # "activate.parallel.works"
```

## Async Support

```python
import asyncio
from parallelworks_client import Client

async def main():
    async with Client.from_credential(os.environ["PW_API_KEY"]) as client:
        response = await client.get("/api/buckets")
        print(response.json())

asyncio.run(main())
```

## Documentation

For full API documentation, visit [https://parallelworks.com/docs](https://parallelworks.com/docs).

## License

MIT