semvec/pypi-packages huggingface dataset:
boosty 0.0.35
Asynchronous boosty wrapper with some utils
Requires Python: >=3.10
Keywords: asyncio, boosty, wrapper

<p align="center">
  <a href="https://github.com/barsikus007/boosty">
    <img src="https://raw.githubusercontent.com/barsikus007/boosty/master/logo.svg" alt="BoostyPy" height="250px">
  </a>
</p>

# Boosty Wrapper

[![PyPI - Version](https://img.shields.io/pypi/v/boosty.svg)](https://pypi.org/project/boosty)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/boosty.svg)](https://pypi.org/project/boosty)
[![Hatch project](https://img.shields.io/badge/%F0%9F%A5%9A-Hatch-4051b5.svg)](https://github.com/pypa/hatch)

-----

**[Описание на русском](https://github.com/barsikus007/boosty/blob/master/README-ru.md)**

**Table of Contents**

- [Installation](#installation)
- [License](#license)
- [Usage](#usage)

## Installation

```console
pip install boosty
```

## License

`boosty` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.

> [!IMPORTANT]
> **!WARNING! this version of library is very unstable**
>
> **If you use it, contact maintainer to help make it stable**

## Usage

*Optional:* specify `IGNORE_MISSING_AND_EXTRA_FIELDS` environment variable to disable strict schema validation

```py
# or add these lines before first boosty import
import os

os.environ["IGNORE_MISSING_AND_EXTRA_FIELDS"] = "true"
```

*Optional:* fill `auth.json` file with authentication data (or use [browser auth](https://github.com/barsikus007/boosty/blob/master/examples/browser_auth.py) to create them):

```json
{
  "access_token": "ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff",
  "device_id": "ffffffff-ffff-ffff-ffff-ffffffffffff",
  "expires_at": 12345678900,
  "refresh_token": "ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff"
}
```

Example:

```python
import asyncio

from boosty.api import API

async def main():
    api = API()
    response = await api.get_post("boosty", post_id="c9fb8a19-c45e-4602-9942-087c3af28c1b")
    print(response.title)
    # 'Добро пожаловать на борт!'

asyncio.run(main())
```

More examples in [examples/](https://github.com/barsikus007/boosty/tree/master/examples/) folder

### TODO for stable release

- inject additional data to models from requests
- convert timestamps to datetime
  - serialize it to int when dumping
- schema
  - complete api schema (at 100 stars)
    - add access levels logic for requests
  - more useful properties for models
  - merge reply comment with comment model
  - msgspec?
  - rename folder types/ to schema/
- logic
  - get rid of strange pydantic model init depends on env
  - maybe better solution for auth data storage
- docs/ (at 50 stars)
- examples/
  - render text
  - get video url
  - get comment url
- tests/
  - boosty profile
  - test posts under my account
  - comments
  - replies
  - video
  - entities parsing
- create dev branch
spec-dev 0.5.6
Bundle of the .spec-dev workspace template.
Requires Python: >=3.9

# spec-dev

A minimal helper that ships a `.spec-dev` folder containing empty role guides for
three agents: architect, tasker, and coder. The package exists so the template can
be installed with `pip` and copied into any project without manual setup.

## Installation

```bash
pip install spec-dev
```

Working from a clone of this repository? Install it locally instead:

```bash
pip install .
```

## CLI Usage

```bash
# Copy the template into the current directory
spec-dev init

# Copy into a specific project directory
spec-dev init path/to/project

# Replace an existing .spec-dev folder
spec-dev init path/to/project --overwrite
```

The command always produces a `.spec-dev/` folder with the following files ready
for you to populate:

- `.spec-dev/architect.md` — guidance for the planning agent.
- `.spec-dev/tasker.md` — instructions for turning the plan into phase/task lists.
- `.spec-dev/coder.md` — instructions for the implementation agent.

Each file ships empty so teams can supply the wording that best matches their
workflow.

## Python API

```python
from spec_dev import copy

root = copy("/path/to/project", overwrite=True)
print(root / "architect.md")  # => Path to the empty template file
```

`copy()` returns the path to the freshly created `.spec-dev` directory, making it
convenient to script project bootstrapping.

## License

MIT
dft-aim-siepic-laser-pic-project1 0.1.1
Design for Test rules for the AIM-SiEPIC Laser Integration Silicon Photonics course, Project 1, using the SiEPIC_EBeam_PDK process design kit (PDK) for silicon photonics fabrication.
Requires Python: >=3.8


# DFT for SiEPIC_EBeam_PDK

- Design for Test rules for the AIM-SiEPIC Laser Integration Silicon Photonics course, Project 1, using the SiEPIC_EBeam_PDK process design kit (PDK) for silicon photonics fabrication.

## Installation

- pip install dft_aim_siepic_laser_pic_project1

or for developers:

- python -m pip install -e 'PATH_TO_GITHUB/DFT_AIM_SiEPIC_Laser_PIC_Project1'
dft-phot1x 0.1.1
Design for Test rules for the edX UBCx Phot1x course, using the SiEPIC_EBeam_PDK process design kit (PDK) for silicon photonics fabrication. 
Requires Python: >=3.8


# DFT for SiEPIC_EBeam_PDK

- Design for Test rules for the edX UBCx Phot1x course, using the SiEPIC_EBeam_PDK process design kit (PDK) for silicon photonics fabrication.

## Installation

- pip install dft_phot1x

or for developers:

- python -m pip install -e 'PATH_TO_GITHUB/DFT_Phot1x'
xfit-rpa 0.0.35
A short description of your package
Requires Python: >=3.6

# My Package

这是一个示例 Python 包。

## 安装

```bash
pip install xfit-rpa
```

## 使用方法

```python
from xfit_rpa import example

# 使用示例
result = example.some_function()
```

## 开发

1. 克隆仓库
2. 安装开发依赖：
   ```bash
   pip install -r requirements.txt
   pip install -e .
   ```
3. 运行测试：
   ```bash
   pytest
   ```

## 构建和发布

1. 安装构建工具：
   ```bash
   pip install build twine
   ```

2. 构建分发包：
   ```bash
   python -m build
   ```

3. 发布到 PyPI：
   ```bash
   # 测试发布到 TestPyPI
   python -m twine upload --repository testpypi dist/*
   
   # 正式发布到 PyPI
   python -m twine upload dist/*
   ```

## 安装

```python
https://test.pypi.org/simple
```

## 许可证

MIT License
addmeta-test 0.post0.dev1
Add meta data to netCDF files.
Requires Python: >=3.9
Keywords: ACCESS-NRI, netcdf, metadata

[![Build Status](https://travis-ci.org/coecms/addmeta.svg?branch=master)](https://travis-ci.org/coecms/addmeta)
[![codecov.io](https://codecov.io/github/coecms/addmeta/coverage.svg?branch=master)](https://codecov.io/github/coecms/addmeta?branch=master)

# addmeta

Add meta data to netCDF files.

## Metadata

The metadata is stored in attribute files in [YAML](https://yaml.org) format. 
The metadata is in key-value pairs and is a global attribute if defined in a 
`global` section, or applied to a specific named variable in the `variables` 
section. 

If an attribute is listed with a missing value that attribute is deleted from the file.

For example the following is an example of an attribute file:
```yaml
global:
    # Mandatory since it gives a key to all the other attributes
    Conventions: "CF-1.7, ACDD-1.3"
    # The url of the license applied to the data
    license: "http://creativecommons.org/licenses/by-nc-sa/4.0/"
variables:
    yt_ocean:
        _FillValue:
        long_name: "latitude in rotated pole grid"
        units: "degrees"
    geolat_t:
        long_name: "latitude coordinate"
        units: "degrees_north"
        standard_name: "latitude"
```
It will create (or replace) two global attributes: `Conventions` and `license`.
It will also create (or replace) attributes for two variables, `yt_ocean` and
`geolat_t`, and delete the `_FillValue` attribute of `yt_ocean`.

The information is read into a `python` dict. Multiple attribute files can be
specified. If the same attribute is defined more than once, the last attribute
file specified takes precedence. Like cascading style sheets this means default
values can be given and overridden when necessary. 


## Invocation

`addmeta` is a command line program. Invoking with the `-h` flag prints
a summay of how to invoke the program correctly.

    $ addmeta -h
    usage: addmeta [-h] [-m METAFILES] [-l METALIST] [-v] files [files ...]

    Add meta data to one or more netCDF files

    positional arguments:
    files                 netCDF files

    optional arguments:
    -h, --help            show this help message and exit
    -m METAFILES, --metafiles METAFILES
                            One or more meta-data files in YAML format
    -l METALIST, --metalist METALIST
                            File containing a list of meta-data files
    -v, --verbose         Verbose output

Multiple attribute files can be specified by passing more than one file with
the `-m` option. For a large number of files this can be tedious. In that case
use the `-l` option and pass it a text file with the names of attribute files,
one per line.

Multiple meta list files and meta files can be specified on one command line.
kmeans-color-palette 0.1.2
Color palette generator using the k-means algorithm.
Requires Python: >=3.8
Keywords: writing, translate

# kmeans-color-palette

Color palette generator using the k-means algorithm.

![logo](https://raw.githubusercontent.com/trucomanx/KMeansColorPalette/main/screenshot.png)

## 1. Installing

To install the package from [PyPI](https://pypi.org/project/kmeans-color-palette/), follow the instructions below:


```bash
pip install --upgrade kmeans-color-palette
```

Execute `which kmeans-color-palette` to see where it was installed, probably in `/home/USERNAME/.local/bin/kmeans-color-palette`.

### Using

To start, use the command below:

```bash
kmeans-color-palette
```
## 2. More information

If you want more information go to [doc](https://github.com/trucomanx/KMeansColorPalette/blob/main/doc) directory.

## 3. Buy me a coffee

If you find this tool useful and would like to support its development, you can buy me a coffee!  
Your donations help keep the project running and improve future updates.  

[☕ Buy me a coffee](https://ko-fi.com/trucomanx) 

## 4. License

This project is licensed under the GPL license. See the `LICENSE` file for more details.
dcpmessage 1.3.1
package for retrieving GOES DCS message data from LRGS servers.
Requires Python: >=3.13

# dcpmessage

`dcpmessage` is a lightweight Python library for retrieving **GOES DCS messages** from **LRGS servers** 

> 🔹 Note: This package only retrieves DCP messages. Decoding, processing, or archiving must be handled separately.

## Documentation

For usage instructions and API reference, go to the documentation website: https://dcspy.github.io/dcpmessage.

## 👥 Contributors

- [Manoj Kotteda](https://github.com/orgs/dcspy/people/manojkotteda)
- Darshan Baral
wbx 0.1.0
W&B SDK extension to fetch runs for further analysis.
Requires Python: >=3.9

# wbx

A Weight & Biases extension to fetch runs for further analysis.

## Installation

```bash
pip install wbx
```

## Usage

Get projects first

```python
import wandb
from wbx import WBX


api = wandb.Api()
entity = "you-entity"

wbx = WBX(api, entity)
projects = wbx.list_projects(quick_see=True, max_val=10)
```

Then get runs from a specific project

```python
project_name = "your-project-name"
wbx.list_configs(project_name)  # list all configs from runs in the project (for further filtering useless configs)

config_to_use = ["config1", "config2"]

runs_df = wbx.get_runs(
    project_name,
    group_keys=config_to_use,
    summary_keys=None,
    json_encode_non_scalars=False
)
```

After that, you can do analysis based on the `runs_df` DataFrame.

Or you can save it as a `parquet` file for later use.

```python
wbx.to_parquet(runs_df, path="path/to/your/folder")
```

## Contributing

Feel free to submit issues or pull requests.

## License

MIT License. See `LICENSE` file for details.
igimf 1.0.0
IGIMF models, plots, and utilities
Requires Python: >=3.9

# pyIGIMF 
Fast computation of the integrated galaxy-wide initial mass function (IGIMF)

Direct queries to Eda Gjergo (Nanjing University) <GalacticCEM@gmail.com>

## Default use

From a Terminal
```
pip install igimf
```

You can choose the linear or logistic alpha1 prescription.

In a script or directly in a Python console:
```
import numpy as np
from igimf import classes as inst

Z_solar = 0.0142

# input (edit as needed)
SFR = 2 # Msun/yr
metal_mass_fraction = 0.1 * Z_solar
mass_star = np.logspace(np.log10(0.08), np.log10(150), 100)
alpha1slope = 'logistic' # or 'linear' 

o_IGIMF = inst.IGIMF(metal_mass_fraction=metal_mass_fraction, SFR=SFR, alpha1slope=alpha1slope)

igimf_v = o_IGIMF.IGIMF_func(mass_star)
```

o_IGIMF creates an instance of the IGIMF class. 
This object contains IGIMF_func, the IGIMF function computed at the given SFR and metal mass fraction.
IGIMF_func can be applied to any stellar mass vector.
In the above script, igimf_v is the IGIMF function computed for the stallar mass vector mass_star


## Setup
```
conda env create -f environment.yaml
conda activate igimf
```

## Run the minimum working example automatically
```
python examples/mwe.py
```
scadable 1.0.0
A Python library for scalable and modular software development.
Requires Python: >=3.10

# Scadable

[![PyPi](https://img.shields.io/pypi/v/scadable)](https://pypi.org/project/scadable/)
[![Downloads](https://static.pepy.tech/badge/scadable/month)](https://pepy.tech/project/scadable)
[![Supported Versions](https://img.shields.io/pypi/pyversions/scadable.svg)](https://pypi.org/project/scadable)
[![GitHub issues](https://img.shields.io/badge/issue_tracking-github-blue.svg)](https://github.com/scadable/library-python/issues)
[![GitHub actions status](https://github.com/scadable/library-python/actions/workflows/test-project.yml/badge.svg)](https://github.com/scadable/library-python/actions/workflows/test-project.yml)

**Scadable** is the first fully container‑native SCADA platform—built on Kubernetes & NATS and delivered with Python +
React SDKs.
Forget rigid vendor UIs: craft your own dashboards, deploy in any cloud, and scale to millions of tags in minutes.

## Getting Started

Assuming that you have a supported version of Python installed, you can first set up your environment with:

```bash
python -m venv .venv
...
. .venv/bin/activate
```

or

```commandline
python -m venv .venv
...
".venv/Scripts/activate"
```

Then, you can install Scadable from PyPI with:

```commandline
python -m pip install scadable
```

## Running Tests

You can run tests in your environment by running the `pytest` command directly:

```commandline
pytest tests
```

## Contributing

Please read through the [CONTRIBUTING](https://github.com/scadable/library-python/blob/main/CONTRIBUTING.md) document
before submitting any issues or pull requests.
bloxypy 0.1.9
Advanced roblox wrapper for the Roblox API.
Requires Python: >=3.7

# BloxAPI

**Powerful and versatile Python3 wrapper for ROBLOX Web API**

## Installation

```bash
pip install bloxypy
```

## Information

Welcome, and thank you for using BloxAPI!
BloxAPI is an object oriented, asynchronous wrapper for the Roblox Web API (and other Roblox-related APIs) with many new and interesting features.
BloxAPI allows you to automate much of what you would do on the Roblox website and on other Roblox-related websites.

## Get Started

To begin, first import and setup the client, which is the most essential part of BloxAPI, and initialize it like so:

```python
from bloxapi import Client

# Create client instance
client = Client()

# Example 1: Get asset information
print("Getting asset information...")
asset_result = client.get_asset(123456)  # Replace with a valid asset ID
print(f"Asset result: {asset_result}")

# Example 2: Get user information
print("\nGetting user information...")
user_result = client.get_user(1)  # Roblox user ID 1 (roblox)
print(f"User result: {user_result}")
```

# Disclaimer
We are not responsible for any malicious use of this library.
If you use this library in a way that violates the Roblox Terms of Use your account may be punished.
If you use code from BloxAPI in your own library, please credit us! We're working our hardest to deliver this library, and crediting us is the best way to help support the project.

# Documentation
You can view documentation for BloxAPI at bloxapi.jmksite.dev.
If something's missing from docs, feel free to dive into the code and read the docstrings as most things are documented there. The docs are generated from docstrings in the code using pdoc3.

# Installation
You can install BloxAPI from pip
```
pip3 install ro.py
```