semvec/pypi-packages huggingface dataset:
python-alpm 0.4.1
Python bindings for the Rust-based ALPM project
Requires Python: >=3.10
Keywords: alpm, archlinux, packaging, srcinfo

# python-alpm

Python bindings for the **A**rch **L**inux **P**ackage **M**anagement (ALPM) project.

We are currently awaiting decision from PyPI maintainers to allow us to publish this package under the name `alpm`.
Until then, we are using the name `python-alpm`.
You can view the support ticket [here](https://github.com/pypi/support/issues/7813).

## Documentation

Latest documentation is available at <https://alpm.archlinux.page/pdoc>.

## Installation

```sh
pip install python-alpm
```

## Examples

### Validating and comparing versions

```pycon
>>> from alpm.alpm_types import PackageVersion, PackageRelease, FullVersion, SchemaVersion

>>> full_version = FullVersion(pkgver=PackageVersion('0.1.0alpha'), pkgrel=PackageRelease(minor=1))
>>> full_version
FullVersion(pkgver=PackageVersion('0.1.0alpha'), pkgrel=PackageRelease(major=0, minor=1))

>>> PackageVersion('1.0.1') > full_version.pkgver
True

>>> version_one = SchemaVersion.from_str('1.0.0')
>>> version_one
SchemaVersion(major=1, minor=0, patch=0, pre='', build='')

>>> version_one == SchemaVersion(major=1)
True

```

### Parsing .SRCINFO

```pycon
>>> from alpm.alpm_srcinfo import SourceInfoV1
>>> from alpm.alpm_types import Architecture

>>> srcinfo = SourceInfoV1.from_file("../alpm-srcinfo/tests/correct/all_overrides.srcinfo")

>>> srcinfo.base
PackageBase(name='example', version=FullVersion(pkgver=PackageVersion('0.1.0'), pkgrel=PackageRelease(major=1), epoch=1))

>>> srcinfo.base.architectures
Architectures([Architecture('x86_64'), Architecture('aarch64')])

>>> srcinfo.packages
[Package(name='example')]

>>> srcinfo.packages_for_architecture(Architecture('aarch64'))
[MergedPackage(architecture=Architecture('aarch64'), name='example', version=FullVersion(pkgver=PackageVersion('0.1.0'), pkgrel=PackageRelease(major=1), epoch=1))]

```

### Working with package metadata

```pycon
>>> from alpm.alpm_srcinfo.source_info.v1.package import Package, Override
>>> from alpm.alpm_types import License

>>> pkg = Package("testpkg")

>>> pkg.description = Override("A test package")
>>> pkg.description
Override(value='A test package')

>>> pkg.licenses = Override([License("MIT"), License("custom-license")])
>>> pkg.licenses
Override(value=[License('MIT'), License('custom-license')])

>>> {str(lic): lic.is_spdx for lic in pkg.licenses.value}
{'MIT': True, 'custom-license': False}

```

## Contributing

Please refer to the [contribution guidelines] to learn how to contribute to this project.

## License

This project can be used under the terms of the [Apache-2.0] or [MIT].
Contributions to this project, unless noted otherwise, are automatically licensed under the terms of both of those licenses.

<!-- Note: these paths have to be absolute in order to work on PyPI -->
[contribution guidelines]: https://gitlab.archlinux.org/archlinux/alpm/alpm/-/blob/main/CONTRIBUTING.md
[Apache-2.0]: https://gitlab.archlinux.org/archlinux/alpm/alpm/-/blob/main/LICENSES/Apache-2.0.txt
[MIT]: https://gitlab.archlinux.org/archlinux/alpm/alpm/-/blob/main/LICENSES/MIT.txt
lazyclaude 0.12.11
A lazygit-style TUI for visualizing Claude Code customizations
Requires Python: >=3.11
Keywords: claude, cli, textual, tui

<p align="center">
  <img src="assets/logo.png" alt="LazyClaude" width="150">
</p>

# LazyClaude

A lazygit-style TUI for visualizing Claude Code customizations.

![Demo](assets/demo.png)

## Install

```bash
uvx lazyclaude
```

## Quick Tour

### First Launch
Launch LazyClaude to explore all your Claude Code customizations in one place. Navigate with `j`/`k`, switch panels with `1-6`, and toggle views with `[`/`]`.

![First Launch](docs/assets/first-launch.gif)

### Filter by Level
Press `a`/`u`/`p`/`P` to filter customizations by configuration level (All/User/Project/Plugin).

![Filter Workflow](docs/assets/demo-filter-workflow.gif)

### Browse Marketplace
Press `M` to open the marketplace browser. Install plugins with `i`, preview content with `p`, and manage installations.

![Marketplace Install](docs/assets/demo-marketplace-install.gif)

### Preview Before Installing
Press `p` in the marketplace to preview plugin content before installation. Explore what the plugin provides without committing.

![Preview Plugin](docs/assets/demo-preview-plugin.gif)

📖 **[Full User Guide](docs/user-guide.md)** for detailed workflows and keyboard shortcuts.


## Development

```bash
uv sync              # Install dependencies
uv run lazyclaude    # Run app
```

Publish:

```bash
export UV_PUBLISH_TOKEN=<your_token>
uv build
uv publish
```

See: <https://docs.astral.sh/uv/guides/package/>
spatio 0.2.5
Blazingly fast spatio-temporal database library
Requires Python: >=3.9

# Spatio for Python

High-performance spatial database for Python, powered by Rust.

[![PyPI](https://img.shields.io/pypi/v/spatio.svg)](https://pypi.org/project/spatio)
[![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)

## What is it?

Spatio is an embedded database optimized for tracking moving objects. It uses a specialized **Hot/Cold State** architecture to provide real-time spatial queries and historical trajectory tracking with minimal overhead.

## Quick Start

```python
import spatio

# Open an in-memory database
db = spatio.Spatio.memory()

# Track a moving object
pos = spatio.Point(-74.006, 40.712, altitude=10.0)
db.upsert("drones", "drone_1", pos, {"status": "active"})

# Find objects within 500 meters
nearby = db.query_radius("drones", pos, radius=500, limit=10)
for object_id, point, metadata, distance in nearby:
    print(f"Found {object_id} at {distance:.1f}m")
```

## core API

### Spatio (Local Database)

```python
import spatio

# Creation
db = spatio.Spatio.memory()
db = spatio.Spatio.open("data.db")

# Tracking
db.upsert(namespace, object_id, point, metadata=None)
db.get(namespace, object_id)  # Returns CurrentLocation or None
db.delete(namespace, object_id)

# Proximity Queries
# Returns list of (object_id, point, metadata, distance)
db.query_radius(namespace, center_point, radius, limit=100)
db.query_near(namespace, object_id, radius, limit=100)

# K-Nearest Neighbors
db.knn(namespace, center_point, k)
db.knn_near_object(namespace, object_id, k)

# Volume Queries
db.query_bbox(namespace, min_x, min_y, max_x, max_y, limit=100)
db.query_within_cylinder(namespace, center_point, min_z, max_z, radius, limit=100)
db.query_within_bbox_3d(namespace, min_x, min_y, min_z, max_x, max_y, max_z, limit=100)

# Relative Queries
db.query_bbox_near_object(namespace, object_id, width, height, limit=100)
db.query_cylinder_near_object(namespace, object_id, min_z, max_z, radius, limit=100)

# Trajectories
db.insert_trajectory(namespace, object_id, list_of_temporal_points)
db.query_trajectory(namespace, object_id, start_ts, end_ts, limit=100)
```

## Data Types

### Point
`spatio.Point(lon, lat, altitude=0.0)`
- `point.lon`, `point.lat`, `point.alt`
- `point.distance_to(other_point)` -> distance in meters (Haversine)

### TemporalPoint
`spatio.TemporalPoint(point, timestamp)`
- Used for bulk trajectory ingestion.

## Performance Tips

1. **Namespaces**: Use namespaces to logically separate different types of objects (e.g., "delivery_trucks", "warehouses").
2. **Object Queries**: Use `query_near` or `knn_near_object` whenever possible, as they avoid re-passing coordinates and leverage the internal Hot State index directly.

## License

MIT - see [LICENSE](LICENSE)
AI-Fabric-v2 1.0.2
This is my first module
Requires Python: >=3.7

Библиотека глубокого обучения на CuPy с GPU-ускорением. Включает полносвязные, сверточные, рекуррентные (RNN, LSTM, GRU) слои, функции активации (ReLU, Sigmoid, Softmax), оптимизаторы (Adam, RMSProp), BPE-токенизатор, модули для обучения и сохранения моделей в формате HDF5.