semvec/pypi-packages huggingface dataset:
specific-ai 0.1.7
specific.ai python sdk

# Specific AI Python SDK

This SDK supports two main workflows:

* **Platform automation**: manage Tasks, Assets (datasets/benchmarks), Trainings, and Models
* **Inference**: run inference on deployed Specific AI models

For copy‑paste‑ready deep dives, see `optune-sdk/examples/platform/`.

## Installation

```bash
pip install specific-ai
```

## Authentication & configuration

Set these environment variables:

* `SPECIFIC_AI_API_KEY`: API key / bearer token for the platform backend
* `SPECIFIC_AI_BASE_URL`: platform backend base URL (default in examples: `https://platform.specific.ai/`)

Optional:

* `SPECIFIC_AI_TASK_ID`: current task id. You can create a new task or see the current task\_id in the platform url. for example - the following url: https://platform.specific.ai/model-setup?usecaseId=68bedd42667aca8d3086e536 the task\_id is '68bedd42667aca8d3086e536'
* `SPECIFIC_AI_TASK_TYPE`: task type string (e.g. `ClassificationResponse`)

## 5-line quickstart (platform)

```python
import os
from specific_ai import SpecificAIClient

client = SpecificAIClient(base_url=os.getenv("SPECIFIC_AI_BASE_URL", "http://localhost:8000"), api_key=os.environ["SPECIFIC_AI_API_KEY"])
task_id = client.tasks.list()[0].iter_tasks()[0].task_id
print(client.models.get_metrics(task_id=task_id).versions)
```

## Deep dive examples

Located in `optune-sdk/examples/platform/`:

* `01_task_management.py`
* `02_asset_management.py`
* `03_training_workflows.py`
* `04_model_deployment.py`

## Support

Contact `support@specific.ai`.
python-calamine 0.6.2
Python binding for Rust's library for reading excel and odf file - calamine
Requires Python: >=3.10

# python-calamine
[![PyPI - Version](https://img.shields.io/pypi/v/python-calamine)](https://pypi.org/project/python-calamine/)
[![Conda Version](https://img.shields.io/conda/vn/conda-forge/python-calamine.svg)](https://anaconda.org/conda-forge/python-calamine)
![Python Version from PEP 621 TOML](https://img.shields.io/python/required-version-toml?tomlFilePath=https%3A%2F%2Fraw.githubusercontent.com%2Fdimastbk%2Fpython-calamine%2Fmaster%2Fpyproject.toml)


Python binding for beautiful Rust's library for reading excel and odf file - [calamine](https://github.com/tafia/calamine).

### Is used
* [calamine](https://github.com/tafia/calamine)
* [pyo3](https://github.com/PyO3/pyo3)
* [maturin](https://github.com/PyO3/maturin)

### Installation
Pypi:
```
pip install python-calamine
```
Conda:
```
conda install -c conda-forge python-calamine
```

### Example
```python
from python_calamine import CalamineWorkbook

workbook = CalamineWorkbook.from_path("file.xlsx")
workbook.sheet_names
# ["Sheet1", "Sheet2"]

workbook.get_sheet_by_name("Sheet1").to_python()
# [
# ["1",  "2",  "3",  "4",  "5",  "6",  "7"],
# ["1",  "2",  "3",  "4",  "5",  "6",  "7"],
# ["1",  "2",  "3",  "4",  "5",  "6",  "7"],
# ]
```

By default, calamine skips empty rows/cols before data. For suppress this behaviour, set `skip_empty_area` to `False`.
```python
from python_calamine import CalamineWorkbook

workbook = CalamineWorkbook.from_path("file.xlsx").get_sheet_by_name("Sheet1").to_python(skip_empty_area=False)
# [
# [",  ",  ",  ",  ",  ",  "],
# ["1",  "2",  "3",  "4",  "5",  "6",  "7"],
# ["1",  "2",  "3",  "4",  "5",  "6",  "7"],
# ["1",  "2",  "3",  "4",  "5",  "6",  "7"],
# ]
```

Pandas 2.2 and above have built-in support of python-calamine.

Also, you can find additional examples in [tests](https://github.com/dimastbk/python-calamine/blob/master/tests/test_base.py).

### Development

You'll need rust [installed](https://rustup.rs/).

```shell
# clone this repo or your fork
git clone git@github.com:dimastbk/python-calamine.git
cd python-calamine
# create a new virtual env
python3 -m venv env
source env/bin/activate
# install dev dependencies and install python-calamine
pip install --group dev -e .  # required pip 25.1 and above
# lint code
pre-commit run --all-files
# test code
pytest
```
waclient 0.1.12
Simplified Python SDK for WhatsApp Business Cloud API
Requires Python: >=3.8
Keywords: whatsapp, business, api, cloud, meta, facebook, messaging

# WhatsApp Biz

**Simplified Python SDK for WhatsApp Business Cloud API**

[![PyPI version](https://badge.fury.io/py/waclient.svg)](https://badge.fury.io/py/waclient)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python Versions](https://img.shields.io/pypi/pyversions/waclient.svg)](https://pypi.org/project/waclient/)

`waclient` is a clean, easy-to-use Python wrapper for the WhatsApp Business Cloud API. It handles authentication, message composition (text, media, interactive), and media management, allowing you to build WhatsApp bots and integrations quickly.

## Features

- **Easy Authentication**: Simple client initialization.
- **Rich Messaging**: Send Text, Image, Video, Audio, Document, Sticker, Location, and Contact messages.
- **Interactive Elements**: Support for Reply Buttons and List Messages.
- **Templates**: Full support for WhatsApp Template Messages.
- **Media Handling**: Upload and retrieve media easily.

## Installation

```bash
pip install waclient
```

## Quick Start

```python
from waclient import WhatsAppClient

client = WhatsAppClient(
    phone_number_id="YOUR_PHONE_ID",
    access_token="YOUR_ACCESS_TOKEN"
)

client.messages.send_text(to="15551234567", body="Hello form WhatsApp Biz!")
```

## Documentation

- **[User Manual](USER_MANUAL.md)**: Detailed verification of all features, code examples, and configuration.
- **[Developer Guide](DEVELOPER_GUIDE.md)**: Setup for contributors, running tests, and project structure.

## ⚠️ WhatsApp 24-Hour Messaging Rule (Important)

WhatsApp enforces a **24-hour customer service window**.

- Free-form messages can be sent **only within 24 hours** after a user’s last message.
- After 24 hours, businesses **must use approved WhatsApp Template Messages**.
- This is a **WhatsApp platform rule**, not a limitation of `waclient`.

### How waclient handles this
- Supports **session messages** (within 24 hours)
- Supports **template messages** (can be sent anytime)
- Webhook-based message tracking helps manage the 24-hour window

📌 Popular platforms like **Amazon, Flipkart, Swiggy** also use **template messages** for notifications.


## Examples

Check the `examples/` directory for ready-to-run scripts:
- `examples/verify_features.py`: comprehensive tour of features.
- `examples/verify_delivery.py`: delivery status verification.

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Author

**Surenthar**  
Email: surentharsenthilkumar2003@gmail.com
wheezy.core 3.2.3
A lightweight core library
Requires Python: >=3.10
Keywords: core, benchmark, collections, config, datetime, db, descriptor, feistel, i18n, introspection, json, luhn, mail, pooling, url, uuid

# wheezy.core

[![tests](https://github.com/akornatskyy/wheezy.core/actions/workflows/tests.yml/badge.svg)](https://github.com/akornatskyy/wheezy.core/actions/workflows/tests.yml)
[![Coverage Status](https://coveralls.io/repos/github/akornatskyy/wheezy.core/badge.svg?branch=master)](https://coveralls.io/github/akornatskyy/wheezy.core?branch=master)
[![Documentation Status](https://readthedocs.org/projects/wheezycore/badge/?version=latest)](https://wheezycore.readthedocs.io/en/latest/?badge=latest)
[![pypi version](https://badge.fury.io/py/wheezy.core.svg)](https://badge.fury.io/py/wheezy.core)

[wheezy.core](https://pypi.org/project/wheezy.core) is a
[python](http://www.python.org) package written in pure Python code. It
provides core features.

It is optimized for performance, well tested and documented.

Resources:

- [source code](https://github.com/akornatskyy/wheezy.core),
  [examples](https://github.com/akornatskyy/wheezy.core/tree/master/demos)
  and [issues](https://github.com/akornatskyy/wheezy.core/issues)
  tracker are available on
  [github](https://github.com/akornatskyy/wheezy.core)
- [documentation](https://wheezycore.readthedocs.io/en/latest/)

## Install

[wheezy.core](https://pypi.org/project/wheezy.core) requires
[python](http://www.python.org) version 3.10+. It is independent of operating
system. You can install it from [pypi](https://pypi.org/project/wheezy.core)
site:

```sh
pip install -U wheezy.core
```

If you run into any issue or have comments, go ahead and add on
[github](https://github.com/akornatskyy/wheezy.core).
appium-utility 0.3.20
Reusable Appium utility helpers
Requires Python: >=3

# AppiumUtility
A small, opinionated helper utility built on top of **Appium Python Client** to simplify common Android UI interactions.
This library is designed to reduce boilerplate and make test scripts more readable and consistent.


## Usage
```py
from appium.webdriver.webdriver import WebDriver
from appium_utility import AppiumUtility

driver: WebDriver = create_driver_somehow()
utils = AppiumUtility(driver)
utils.launch_app("com.example.app")
utils.hide_keyboard()
utils.click_by_text("*.Continue.*", regex=True)
utils.click_by_id("com.example:id/login")
utils.click_by_content_desc("Settings")
utils.click_by_xpath("//android.widget.Button[@text='OK']")
utils.swipe_up()
utils.swipe_down()
utils.swipe_until_text_visible("*.Continue.*", direction="SWIPE_UP", regex=True)
```
digiflot 1.1.0.post1.dev0
A digital and modular platform to assist on laboratory flotation experiments and collect relevant information.
Requires Python: >=3.8

# DigiFlot

A digital and modular platform to assist on laboratory flotation experiments and collect relevant information from different sensors in a structured manner.

<image src="https://github.com/pereirageomet/digiflot/blob/main/docs/run.png" width="450"/> <image src="https://github.com/pereirageomet/digiflot/blob/main/docs/demo.gif" width="300"/>

# Wiki

![Here you will learn more about DigiFlot](docs/welcome.md), including its structure, how to install it, and how to use it in the lab.

* Very important, once installed, you call digiflot with:

```python
python -m digiflot.DigiFlot
```

# Necessary parts
[Here you find a list with the pieces you need or might want to have for your system.](docs/DigiFlot-pieces.csv)

Please keep in mind that **we have no affiliation with the vendors suggested in there, and we do not receive any financial support from them**. Our objective with this list is to only simplify the system installation in your laboratory. 
All pieces indicated there are alredy integrated in the DigiFlot system.

# Acknowldgements
This laboratory assistant has, so far, been programmed at the [Helmholtz Institute Freiberg for Resource Technology](https://hzdr.de/hif), by Lucas Pereira & Christian Schmidt. 

The developers are extremely grateful to all test users who battled through the bugs of the preliminary versions, also providing much valuable feedback. To name a few: Borhane Ben Said, Ali Hassan, Gülce Öktem, Aliza Salces, and Klaus Sygusch.

Also many thanks to Rocco Naumann, responsible to assure the safety of all of our sensors, always engineering the best connectors for the laboratory assistant.

This project has been partially financed by the Federal Ministry of Research, Technology and Space through the WIR! Recomine funding scheme, project "WIR!-rECOmine – Digitalisierung und modellprädiktive Regelung komplexer Aufbreitungsprozesse mittels Sensorfusion und KI-gestützter Auswertung (03WIR1919B)". 

# Reference
If you use this open source project, please cite it in your work as:

```
Pereira, L., Schmidt, C., Rudolph, M., 2025. DigiFlot: a modular laboratory assistant tailored for froth flotation experiments. https://doi.org/10.14278/rodare.3841
```