semvec/pypi-packages huggingface dataset:
AMRS 0.0.0
The adaptive model routing system for exploration and exploitation.
License: MIT
Requires Python: <4.0,>=3.10

# AMRS

 [![Latest Release](https://img.shields.io/github/v/release/inftyai/amrs?include_prereleases)](https://github.com/inftyai/amrs/releases/latest)

The Adaptive Model Routing System (AMRS) is a cutting-edge framework designed to select the best-fit model for exploration and exploitation.

## Contributions

🚀 All kinds of contributions are welcomed ! Please follow [Contributing](/CONTRIBUTING.md).
tesla-wall-connector 1.1.0
API Library for communicating with a Tesla Wall Connector
License: MIT
Requires Python: <4.0,>=3.8
Keywords: tesla, wall connector

# Python Tesla Wall Connector API <!-- omit in TOC -->

Python Tesla Wall Connector API for local consumption. This package allows you to monitor your 3rd generation Tesla Wall Connector programmatically. It is mainly created to enable integration with Home Assistant and threfore exposes an asynchronous API.

## Usage

```python
import asyncio
from tesla_wall_connector import WallConnector
async def main():
    async with WallConnector('TeslaWallConnector_ABC123.localdomain') as wall_connector:
        lifetime = await wall_connector.async_get_lifetime()
        print("energy_wh: {}Wh".format(lifetime.energy_wh))

asyncio.run(main())
```

## Setting up development environment

This Python project is fully managed using the [Poetry][poetry] dependency
manager.

You need at least:

- Python 3.8+
- [Poetry][poetry-install]

To install all packages, including all development requirements:

```bash
poetry install
```

As this repository uses the [pre-commit][pre-commit] framework, all changes
are linted and tested with each commit. You can run all checks and tests
manually, using the following command:

```bash
poetry run pre-commit run --all-files
```

To run the Python tests:

```bash
poetry run pytest
```
django-request-in 0.0.4
A Python library for django_request_in
License: MIT
Requires Python: >=3.6
Keywords: python, django_request_in


# django_request_in

一个用于django_request_in的工具，可以读取django_request_in的日志文件，并按照时间顺序执行django_request_in请求。

## Features


## 安装

```bash
# 本地
pip install django_request_in -i https://pypi.org/simple/
# 阿里云
pip install django_request_in -i https://pypi.org/simple/
```

## 用法

```bash
python -m django_request_in <log_file>
```


### 开发配置

```bash
# 克隆仓库
git clone git@github.com:atanx/django_request_in.git
cd django_request_in

# 安装开发依赖
pip install -e ".[dev]"

# 手动修改修改__init__.py中的__version__， 然后打包
make build

# 上传到xmov-pypi, 需要安装twine， 配置~/.pypirc
make upload
```
XRetriever 0.1.0
X-ray Diffraction Pattern Matching and Crystal Structure Retrieval
License: MIT
Requires Python: >=3.8
Keywords: xrd x-ray diffraction crystallography materials science pattern matching phase identification crystal structure materials characterization powder diffraction peak detection

# XRetriever




**XRetriever** is a powerful Python package for X-ray Diffraction (XRD) pattern matching and crystal structure retrieval. It provides state-of-the-art algorithms for matching experimental XRD patterns to crystal structure databases, enabling rapid phase identification and materials characterization.



### Core Capabilities
- **Robust Peak Detection**: Advanced algorithms with Savitzky-Golay filtering and baseline removal
- **Intelligent Pattern Matching**: Hungarian algorithm-based optimal peak assignment
- **Dual Scoring Metrics**:
  - **Weighted Score**: 70% position + 30% intensity similarity
  - **FOM (Figure of Merit)**: ICDD-standard quantitative matching metric
- **Element-Based Filtering**: Fast candidate screening by chemical composition
- **Flexible Input**: Support for CSV, TXT, and direct peak data input

### Advanced Features
- **Combined Scoring Mode**: Get both weighted and FOM scores simultaneously
- **Top-N Peak Selection**: Automatically extract and normalize the strongest peaks
- **Configurable Tolerances**: Adjust position tolerance (default: ±0.2° in 2θ)
- **Comprehensive Results**: Detailed matching information with peak-by-peak analysis

## Installation

### From PyPI (Recommended)
```bash
pip install XRetriever
```
pymbusparser 0.0.4
Python bindings for m-bus-parser written in Rust
License: MIT

# Python bindings 

Rust lib aims to be accessible from a Python module. This is done by using the `PyO3` crate.
See the rust project for more documentation on the Rust side of things [on github](https://github.com/maebli/m-bus-parser).

## Development

- `pipx install maturin` to install `maturin` globally.
- `maturin develop` to build the Rust lib and create a Python module in the current environment.
- Currently this creates a release in the target directory that is one hierachy up. This is not ideal and will be fixed in the future.
- after calling the maturin develop command cd one up and `pip install target/..` and then run `python` and `from pymbusparser import pymbus` to test the module.
- to test inside `REPL` run `python` and then `import p

## Publishing

- `maturin publish`
- username = __token__
- passwrod = api key from pypi

## Usage

`pip install pymbusparser`

```python
from pymbusparser import m_bus_parse,parse_application_layer

print(m_bus_parse("68 3D 3D 68 08 01 72 00 51 20 02 82 4D 02 04 00 88 00 00 04 07 00 00 00 00 0C 15 03 00 00 00 0B 2E 00 00 00 0B 3B 00 00 00 0A 5A 88 12 0A 5E 16 05 0B 61 23 77 00 02 6C 8C 11 02 27 37 0D 0F 60 00 67 16","table"))

print(m_bus_parse("68 3D 3D 68 08 01 72 00 51 20 02 82 4D 02 04 00 88 00 00 04 07 00 00 00 00 0C 15 03 00 00 00 0B 2E 00 00 00 0B 3B 00 00 00 0A 5A 88 12 0A 5E 16 05 0B 61 23 77 00 02 6C 8C 11 02 27 37 0D 0F 60 00 67 16","json"))

print(m_bus_parse("68 3D 3D 68 08 01 72 00 51 20 02 82 4D 02 04 00 88 00 00 04 07 00 00 00 00 0C 15 03 00 00 00 0B 2E 00 00 00 0B 3B 00 00 00 0A 5A 88 12 0A 5E )16 05 0B 61 23 77 00 02 6C 8C 11 02 27 37 0D 0F 60 00 67 16","yml"))

# note this is not as pretty as the function before, still TODO, currently it just outputs structs of RUST in string
print(parse_application_layer("2f2f0413fce0f5052f2f2f2f2f2f2f2f"))

```
spendwise-analytics 0.1.1
Reusable budgeting projections and checks for Spendwise
License: MIT
Requires Python: >=3.9

# spendwise-analytics

Reusable finance analytics for Spendwise (projection & budget status).

```python
from spendwise_analytics import BudgetInsights
bi = BudgetInsights(window=4, warn_threshold=0.1)
proj = bi.projected_monthly_spend(month_to_date=220.0, days_elapsed=7, days_in_month=30)
print(bi.budget_status(budget=800.0, projected=proj))