semvec/pypi-packages huggingface dataset:
casaGeoTools 0.9.4
HERE Connector for Python
Requires Python: >=3.11

# 🗺️ casaGeoTools (Beta)

**A Python connector for the HERE Location Platform — designed for geocoding, routing, and isoline analytics.**

---

## 🚀 Overview

**casaGeoTools** provides a simple and Pythonic way to access the power of the **HERE Location Platform** directly from your Python environment.  
It allows developers, analysts, and data scientists to integrate **location intelligence** into their workflows with just a few lines of code.

With casaGeoTools, you can easily:

- 🏠 **Geocode** addresses into coordinates  
- 🚗 **Compute routes** between locations  
- 🕒 **Generate isolines** (isochrones or isodistances)  
- 🌍 **Visualize results** interactively on a map  

casaGeoTools wraps the HERE APIs with a clean, consistent interface optimized for Python.

---

## 🌐 Powered by HERE Platform

casaGeoTools is built on top of the **HERE Platform** and provides a ready-to-use Python connector to HERE’s core location services.

You don’t need to manage REST requests or API authentication manually — casaGeoTools handles that for you while giving you a natural, Pandas- and GeoPandas-friendly interface.

---

## 💰 Credit System (Beta Program)

casaGeoTools uses a **credit-based API model**.

Each API key includes a balance of credits that are **valid for 1 year**.  
Unused credits **expire after 12 months**.

During the **public Beta phase**, every registered user receives **3,000 free credits**.

### 🔢 Credit usage per API call

| Operation | Credits per request | Description                               |
|-----------|---------------------|-------------------------------------------|
| Geocoding | 3 credits           | Convert address → coordinates             |
| Routing   | 3 credits           | Compute route between two points          |
| Isolines  | 20 credits          | Generate isochrone or isodistance polygon |

### 💡 Example usage
With 3,000 credits you can approximately:

- Geocode **1,000 addresses**, or  
- Compute **1,000 routes**, or  
- Generate **150 isolines**

You can also combine requests freely:
> e.g., 500 geocodes + 250 routes + 50 isolines = 3,000 credits total

---

## ⚙️ Installation

Install the required packages using pip:

``` shell
pip install casaGeoTools
```

---


## casaGeoTools Beta Example Script

See the example script under `examples/beta_example_script.py` for a complete example of how to use casaGeoTools.
td-todo-cli 0.1.1
A local-first task state manager for humans and LLMs
Requires Python: >=3.10

# td

A local-first task state manager for your projects. Designed for humans and LLMs.

`td` tracks what you're working on, what you've parked, and what's done — using simple state labels instead of complex workflows.

## Install

```bash
pipx install td-todo-cli
```

## Quick Start

```bash
cd my-project
td init                          # create .td/ in your project
td add "Build auth system"       # create a task (state: active)
td add "Login UI" --parent build-auth-system --state focus
td ls                            # see all non-done tasks
td tree                          # hierarchical view
td done login-ui                 # mark finished
td status                        # focus: 0  active: 1  later: 0  done: 1  total: 2
```

## States

| State    | Meaning                            |
|----------|------------------------------------|
| `focus`  | In my working set right now        |
| `active` | Taken on, not working on it now    |
| `later`  | Explicitly parked                  |
| `done`   | Finished                           |

States represent intent, not progress. Any state can move to any other.

## Commands

```
td init                              Initialize .td/ in current directory
td add <title>                       Create task (default: active)
td focus <id>                        Move to focus
td active <id>                       Move to active
td later <id>                        Park it
td done <id>                         Mark finished
td ls                                List non-done tasks
td ls --state focus                  Filter by state
td ls --all                          Include done
td ls --json                         Machine-readable output
td tree                              Hierarchical view
td tree <id>                         Subtree from a node
td show <id>                         Full detail on one task
td status                            Summary counts
td edit <id> --title/--notes/--parent   Modify a task
td mv <id> <parent-id>              Move under a parent
td rm <id>                           Delete (confirms first)
td rm <id> --force                   Delete without confirmation
```

## LLM Integration

An LLM interacts with `td` through the same CLI:

```bash
td ls --json            # understand current project state
td ls --state focus     # know what matters right now
td add "Fix bug"        # create tasks
td done fix-bug         # mark work complete
```

No special API needed. The CLI is the interface.

## Storage

Tasks are individual YAML files in `.td/tasks/`, designed to be git-friendly and human-readable:

```yaml
id: login-ui
title: Build login form
state: focus
parent: auth
created: 2026-02-10T14:30:00
updated: 2026-02-10T14:30:00
```

## Development

```bash
git clone https://github.com/BorisMolch/td-cli.git
cd td-cli
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
pytest
```

## License

MIT
vec-utils-py 0.3.1
A simple vector operations library
Requires Python: >=3.9

# Vec-utils-py

This is a python library exposing much of my rust vec-utils crate.
Included objects:
* 3d Vectors
* Quaternions
* Angles
* Circles
* Some intersections

Only available from pytohn is also the VecList struct. It can be used for faster operations on many Vec3d objects
fastapi-slim 0.129.0
FastAPI framework, high performance, easy to learn, fast to code, ready for production
Requires Python: >=3.10

<p align="center">
  <a href="https://fastapi.tiangolo.com"><img src="https://fastapi.tiangolo.com/img/logo-margin/logo-teal.png" alt="FastAPI"></a>
</p>
<p align="center">
    <em>FastAPI framework, high performance, easy to learn, fast to code, ready for production</em>
</p>
<p align="center">
<a href="https://github.com/fastapi/fastapi/actions?query=workflow%3ATest+event%3Apush+branch%3Amaster" target="_blank">
    <img src="https://github.com/fastapi/fastapi/actions/workflows/test.yml/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/fastapi/fastapi" target="_blank">
    <img src="https://coverage-badge.samuelcolvin.workers.dev/fastapi/fastapi.svg" alt="Coverage">
</a>
<a href="https://pypi.org/project/fastapi" target="_blank">
    <img src="https://img.shields.io/pypi/v/fastapi?color=%2334D058&label=pypi%20package" alt="Package version">
</a>
<a href="https://pypi.org/project/fastapi" target="_blank">
    <img src="https://img.shields.io/pypi/pyversions/fastapi.svg?color=%2334D058" alt="Supported Python versions">
</a>
</p>

---

**Documentation**: <a href="https://fastapi.tiangolo.com" target="_blank">https://fastapi.tiangolo.com</a>

**Source Code**: <a href="https://github.com/fastapi/fastapi" target="_blank">https://github.com/fastapi/fastapi</a>

---

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python based on standard Python type hints.

## `fastapi-slim`

⚠️ Do not install this package. ⚠️

This package, `fastapi-slim`, does nothing other than depend on `fastapi`.

All the functionality has been integrated into `fastapi`.

The only reason this package exists is as a migration path for old projects that used to depend on `fastapi-slim`, so that they can get the latest version of `fastapi`.

You **should not** install this package.

Install instead:

```bash
pip install fastapi
```

This package is deprecated and will stop receiving any updates and published versions.

## License

This project is licensed under the terms of the MIT license.
awehflow 4.0.6
Configuration based Apache Airflow
Requires Python: >=3.6

# awehflow

![coverage report](https://gitlab.com/spatialedge/awehflow/badges/master/coverage.svg)
![pipeline status](https://gitlab.com/spatialedge/awehflow/badges/master/pipeline.svg)

**awehflow** is a configuration-driven framework for Apache Airflow that dynamically generates DAGs from simple HOCON or YAML files. It comes with built-in metrics, logging, and alerting to streamline your data orchestration.

## Core Concepts

- **Configuration-Driven**: Define complex DAGs using a clear, hierarchical configuration. No need to write repetitive Python code for each pipeline.
- **Dynamic DAG Generation**: **awehflow** automatically constructs and orchestrates Airflow DAGs based on your configurations.
- **Built-in Observability**: Comes with out-of-the-box event handlers for persisting metrics to a database and alerters for notifications on pipeline status.
- **Extensible**: Easily add your own custom event handlers and alerters to integrate with any service.

## Getting Started

- [**Getting Started Guide**](./docs/getting-started.md): A step-by-step guide on how to get your first **awehflow** pipeline up and running.

## Configuration Reference

- [**Configuration Guide**](./docs/config-files.md): A detailed walkthrough of the configuration system.

## Custom Operators and Sensors

**awehflow** includes a collection of custom operators and sensors to extend Airflow's functionality. While these custom operators provide specialized capabilities, **awehflow** is fully compatible with all standard Airflow operators. You can use any operator available in your Airflow environment by referencing its fully qualified class name in your configuration.

- [**Operators Guide**](./docs/operators): Detailed documentation for all custom operators.
- [**Sensors Guide**](./docs/sensors.md): Detailed documentation for all custom sensors.

## Command-Line Interface (CLI)

**awehflow** includes a CLI for generating and validating configurations.

- [**CLI Documentation**](./awehflow_cli/README.md): A complete reference for all CLI commands.

## Advanced Features

### Event Handlers & Alerters

**awehflow** has a built-in event system that allows you to run custom code in response to pipeline events. Alerters are a special type of event handler designed for sending notifications.

- [**Alerts Guide**](./docs/alerts.md): A detailed guide on how to configure and use alerters.

## Troubleshooting

- [**Troubleshooting Guide**](./docs/troubleshooting-debugging.md): Solutions for common issues and debugging tips.

## For Developers

### Development Environment Setup
To contribute to **awehflow**, follow these steps to set up a development environment for a specific Airflow version.

1.  **Install Miniconda**: Follow the official instructions.
2.  **Create Conda Environment (x86 on Mac ARM)**: If you are on an ARM-based Mac, create an x86-emulated environment. Add this function to your `.zsh
mkdocs-doubleslash-theme 1.1.1
doubleSlash Theme for MkDocs
Requires Python: >=3.10

# mkdocs-doubleslash-theme

A MkDocs plugin that applies [doubleSlash style](https://doubleslash.style/) to your documentation.

## Quick Start

1. Install the plugin via `pip`:
  ```shell
  pip install mkdocs-doubleslash-theme
  ```
2.  Add the plugin to your `mkdocs.yml` and enable the `mkdocs-material` theme:
  ```yaml
  theme: material
  
  plugins:
    - search
    - mkdocs-doubleslash-theme
  ```
3. Thats it! The doubleSlash theme is now applied to your documentation.

## Documentation

For detailed instructions and a demo, please read the **[documentation](https://doubleslashde.github.io/mkdocs-doubleslash-theme/)**.

## Development

### Local setup

Run `./local-preview` in your terminal to build and run a MkDocs server with the plugin installed,
serving on <http://127.0.0.1:8000/>.

## Releasing

Manually trigger the `release` workflow via GitHub Actions, which will auto-bump the plugin version and perform the release process.
PyPi publishing is set up via [trusted publishing](https://docs.pypi.org/trusted-publishers/).

## License

mkdocs-doubleslash-theme is licensed under the [Apache License, Version 2.0](LICENSE).
lvsfunc 0.9.0
Light's Vapoursynth Functions.
Requires Python: >=3.12

# lvsfunc

<p align="center">
    <!-- <a href="https://lvsfunc.encode.moe"><img alt="Read the Docs" src="https://img.shields.io/readthedocs/lvsfunc"></a> -->
    <img alt="PyPI - Python Version" src="https://img.shields.io/pypi/pyversions/lvsfunc">
    <a href="https://pypi.org/project/lvsfunc/"><img alt="PyPI" src="https://img.shields.io/pypi/v/lvsfunc"></a>
    <a href="https://github.com/Irrational-Encoding-Wizardry/lvsfunc/commits/master"><img alt="GitHub commits since tagged version" src="https://img.shields.io/github/commits-since/Irrational-Encoding-Wizardry/lvsfunc/latest"></a>
    <a href="https://github.com/Irrational-Encoding-Wizardry/lvsfunc/blob/master/LICENSE"><img alt="PyPI - License" src="https://img.shields.io/pypi/l/lvsfunc"></a>
    <a href="https://discord.gg/XTpc6Fa9eB"><img alt="Discord" src="https://img.shields.io/discord/856381934052704266?label=discord"></a>
    <img alt="downloads" src="https://static.pepy.tech/personalized-badge/lvsfunc?period=total&units=international_system&left_color=grey&right_color=blue&left_text=downloads">
</p>

> [!CAUTION]
> This package is intended to be
> a sort of testing grounds
> for functions I write.
> As such,
> you should NEVER depend on this package,
> and instead wait for the useful functions
> to get adopted into other [JET](https://github.com/Jaded-Encoding-Thaumaturgy) packages.

If you're testing new functionality
that may be ported over
to a JET package
in the future,
please make sure to install
the latest version on git.

----

A collection of VapourSynth functions and wrappers
written and/or modified by LightArrowsEXE.
Full information on how every function/wrapper works,
as well as a list of dependencies and links,
can be found in the docstrings of each function/wrapper.
For further support,
drop by `#dev` in the [JET Discord server](https://discord.gg/XTpc6Fa9eB).

## How to install

If you have the old `lvsfunc.py` module,
remove that from your system first.

Install `lvsfunc` with the following command:

```sh
$ pip3 install lvsfunc --no-cache-dir -U
```

Or if you want the latest git version, install it with this command:

```sh
$ pip3 install git+https://github.com/Irrational-Encoding-Wizardry/lvsfunc.git --no-cache-dir -U
```

## Usage

After installation, functions can be loaded and used as follows:

```py
import lvsfunc as lvf

aa = lvf.deblock.autodb_dpir(...)
comp = lvf.comparison.compare(...)
...
```

## Disclaimer

Anything **MAY** change at any time.
The public API **SHOULD NOT** be considered stable.

Many functions in this package are considered **EXPERIMENTAL**,
and are likely to require either full testing,
or may be moved to a different _Jaded Encoding Thaumaturgy_ package after some time.

If you use _lvsfunc_ in any of your projects,
please consider hardcoding a version requirement.
ttcal 2.0.9
ttcal - calendar operations



ttcal - calendar operations
===========================

.. image:: https://github.com/datakortet/ttcal/actions/workflows/ci-cd.yml/badge.svg
   :target: https://github.com/datakortet/ttcal/actions/workflows/ci-cd.yml

.. image:: https://github.com/datakortet/ttcal/actions/workflows/apidocs.yml/badge.svg
   :target: https://datakortet.github.io/ttcal/

.. image:: https://github.com/datakortet/ttcal/actions/workflows/codeql-analysis.yml/badge.svg
   :target: https://github.com/datakortet/ttcal/actions/workflows/codeql-analysis.yml

.. image:: https://codecov.io/gh/datakortet/ttcal/branch/master/graph/badge.svg?token=rG43wgZ3aK
   :target: https://codecov.io/gh/datakortet/ttcal

.. image:: https://pepy.tech/badge/ttcal
   :target: https://pepy.tech/project/ttcal
   :alt: Downloads
   
This is a small library for calendar operations.

Usage::

    >>> from ttcal import *
    >>> Today()
    2023-7-2-7
    >>> Today() + 1
    2023-7-3-7
    >>> import datetime
    >>> isinstance(Today(), datetime.date)
    True
    >>> Day(1991, 2, 20)
    1991-2-20-2
    >>> Month()
    Month(2023, 7)
    >>> Month() + 2
    Month(2023, 9)
    >>> Year()
    Year(2023)
    >>> Year() + 2
    Year(2025)
    >>> Day(2024, 2, 29)
    2024-2-29-2
    >>> Day(2024, 2, 29) + Period(months=2)
    2024-4-29-4
    >>> Day(2024, 4, 30) - Period(months=2)
    2024-2-29-2
    >>>