semvec/pypi-packages huggingface dataset:
asanak-web-call-client 0.0.0
Asanak Web Call client for making and managing calls via REST API
Requires Python: >=3.7

# 📦 Asanak Web Call Client (Python)

یک کلاینت پایتونی برای مدیریت تماس ها از طریق API Asanak

## 📌 ویژگی‌ها

- آپلود فایل صوتی به لیست فایل ها
- ایجاد تماس از طریق فایل صوتی (تک یا چند مقصده)
- ایجاد تماس برای کد های احراز هویت (OTP)
- دریافت گزارش وضعیت تماس ها
- دریافت اعتبار باقی مانده

## 📄 منابع و مستندات

- 🌐 [صفحه اصلی سرویس تماس آسا‌نک](https://callapi.asanak.com/)
- 🧾 [مستندات آنلاین کامل](https://callapi.asanak.com/docs/v1)
- 🚀 [مستندات آنلاین Postman](https://documenter.getpostman.com/view/45759202/2sB34Zq3mN)
- ⬇️ [دانلود فایل کالکشن Postman](https://callapi.asanak.com/docs/v1/Asanak_Call_API_Service.postman_collection.json)

## 🚀 نصب پکیج

### از PyPI:
```bash
pip install asanak-web-call-client
```

### از GitHub:
```bash
pip install git+https://github.com/Asanak-Team/python-web-call-client.git
```

## 📚 استفاده از کلاینت

```python
from web_call_client import AsanakWebCallClient

client = AsanakWebCallClient("username", "password")

```

1- افزودن فایل صوتی جدید
```python

try:
    data = client.upload_new_voice("/path/file/voice.mp3")
    print(data)
except Exception as e:
    print(e)
```

2- تماس از طریق فایل صوتی
```python

try:
    data = client.call_by_voice("VOICE_ID", "0912000000")
    print(data)
except Exception as e:
    print(e)
```

3-  تماس OTP
```python

try:
    data = client.call_by_otp(1234, "0912000000")
    print(data)
except Exception as e:
    print(e)
```

4-  استعلام وضعیت تماس ها
```python

try:
    data = client.call_status(['CALL_ID_1', 'CALL_ID_2'])
    print(data)
except Exception as e:
    print(e)
```

5-  استعلام اعتبار باقی مانده
```python

try:
    data = client.credit()
    print(data)
except Exception as e:
    print(e)
```


## 📝 پارامتر‌های ورودی

- `username`: نام کاربری از API Asanak
- `password`: رمز عبور از API Asanak
- `base_url`: آدرس سرور API Asanak (پیش‌فرض: `https://callapi.asanak.com`)

## 📝 پارامتر‌های خروجی
```json
{
    "success": boolean,
    "error": null|str,
}
```
pdfcrop-cli 0.3.0
An experimental alternative of TeX/pdfcrop tool
Requires Python: >=3.10

# pdfcrop

An experimental alternative of TeX/pdfcrop tool

## Install from source

```shell
pip install git+https://github.com/Jordan-Haidee/pdfcrop.git
```

## Install from PyPI
```shell
pip install pdfcrop-cli
```

## Usage

```shell
$ pdfcrop.exe --help
usage: pdfcrop [-h] [OPTIONS]

╭─ options ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮  
│ -h, --help              show this help message and exit                                                                                        │  
│ --input PATH, -i PATH   The input pdf file. (required)                                                                                         │  
│ --output {None}|PATH, -o {None}|PATH                                                                                                           │  
│                         The output path. (default: None)                                                                                       │  
│ --pages {None}|{[INT [INT ...]]}                                                                                                               │  
│                         The page numbers to crop. None denotes all pages. (default: None)                                                      │  
│ --margins {None}|{[INT [INT ...]]}                                                                                                             │  
│                         The margins to reserve. None denotes all 0. If one number is given, it will be applied to four borders. (default:      │  
│                         None)                                                                                                                  │  
╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ 
```

You can use `examples/example.pdf` to test whether pdfcrop works.
regspline 25.7.2
Regression spline
Requires Python: >=3.9
Keywords: statistics, regression, splines

# Regression splines

This module includes two spline implementations splines suitable for regression: linear splines using a hinge function basis, and natural cubic splines.

```python
import numpy as np
import matplotlib.pyplot as plt
from regspline import LinearSpline
plt.close('all')

knots = [0,1,2]
coeffs = [1,2,3]
s = LinearSpline(knots, coeffs)
y=s(np.linspace(0,1))

x=np.linspace(0,np.pi)
y=np.sin(x)
xobs = np.repeat(x,50)
yobs = np.repeat(y,50) + 0.01*np.random.randn(*xobs.shape)

s, res = LinearSpline.from_data(xobs, yobs,
                                knots=np.linspace(0,np.pi,30),
                                method='OLS',
                                return_estim_result=True,
                                prune=True)

plt.plot(x,y)
plt.plot(x,s(x))
```

Several regression types are supported to extract the splines from data, including OLS, LASSO, and quantile regression. See the example files.

## Installation

You can install this library directly from github:

```bash
pip install regspline.git
```

There are two optional dependencies: `scikit-learn`, and `cvxopt`. They are only required to estimate splines on data with, respectively, support vector regressions, and LASSO.

## Background

The module contains two splines:

- A linear spline represented by Hinge functions: $h_i(x) = \max(x-k_i,0)$, where $k_i$ are the knots.
- A natural cubic spline.

The splines chosen:

- have coefficents that have a one-to-one correspondence with the knots.
- have the ability that knots can be removed, e.g., when the corresponding coefficient is small or insignificant, without changing the basis functions corresponding to other knots.
- have the ability to represent functions with sparse basis.

One way to interpret, e.g., the linear spline in the hings basis is as follows. $h_1(x)$ sets an initial slope from the first knot onwards. Then next basis function $h_2(x)$ can adjust the slope at the knot $k_2$, if no adjustment is required, its coefficient is insignificant and the knot can be removed from the spline without any impact on the other basis functions.

## Related projects

Some projects with related methods:

- [basis-expansions](https://github.com/madrury/basis-expansions)
- [py-earth](https://github.com/scikit-learn-contrib/py-earth)
- Quantile regression using decision trees [scikit-garden](https://scikit-garden.github.io/)

The module differs from these implementations as it implements the splines as functions, and they are not integrated within an estimation framework.

## Development

For development purposes, clone the repo:

```bash
git clone https://github.com/mvds314/regspline.git
```

Then navigate to the folder containing `setup.py` and run

```bash
pip install -e .
```

to install the package in edit mode.

Run unittests with `pytest`.

Install the optional dependencies to test all functionality.
graphdict 3.4.14
Python package for creating and manipulating graphs and networks
Requires Python: >=3.7
Keywords: Networks, Graph Theory, Mathematics, network, graph, discrete mathematics, math

Graphdict
=========

.. image:: https://codecov.io/gh/taylortech75/graphdict/branch/main/graph/badge.svg
   :target: https://app.codecov.io/gh/taylortech75/graphdict/branch/main

.. image:: https://img.shields.io/github/labels/taylortech75/graphdict/Good%20First%20Issue?color=green&label=Contribute%20&style=flat-square
   :target: https://github.com/taylortech75/graphdict/issues?q=is%3Aopen+is%3Aissue+label%3A%22Good+First+Issue%22

Graphdict is a Python package for the creation, manipulation,
and study of the structure, dynamics, and functions of complex networks.

- **Website (including documentation):** https://networkx.org
- **Mailing list:** https://groups.google.com/forum/#!forum/networkx-discuss
- **Source:** https://github.com/taylortech75/graphdict
- **Bug reports:** https://github.com/taylortech75/graphdict/issues
- **Tutorial:** https://networkx.org/documentation/latest/tutorial.html
- **GitHub Discussions:** https://github.com/taylortech75/graphdict/discussions

Simple example
--------------

Find the shortest path between two nodes in an undirected graph:

.. code:: python

   >>> import graphdict as nx
   >>> G = nx.Graph()
   >>> G.add_edge('A', 'B', weight=4)
   >>> G.add_edge('B', 'D', weight=2)
   >>> G.add_edge('A', 'C', weight=3)
   >>> G.add_edge('C', 'D', weight=4)
   >>> nx.shortest_path(G, 'A', 'D', weight='weight')
   ['A', 'B', 'D']

Install
-------

Install the latest version of Graphdict::

   $ pip install graphdict

Install with all optional dependencies::

   $ pip install graphdict[all]

For additional details, please see `INSTALL.rst`.

Bugs
----

Please report any bugs that you find `here <https://github.com/taylortech75/graphdict/issues>`_.
Or, even better, fork the repository on `GitHub <https://github.com/taylortech75/graphdict>`_
and create a pull request (PR). We welcome all changes, big or small, and we
will help you make the PR if you are new to `git` (just ask on the issue and/or
see `CONTRIBUTING.rst`).

License
-------

Released under the 3-Clause BSD license (see `LICENSE.txt`)::

   Copyright (C) 2004-2021 Graphdict Developers
   John Smith <johnsmithdev92@gmail.com>
detect-qt-binding 0.1.0a0
A lightweight utility to automatically detect which Qt Python binding is available in your environment.
Requires Python: >=2

# `detect-qt-binding`

A lightweight utility to automatically detect which Qt Python binding is available in your environment.

## Features

- Detects installed Qt bindings (PyQt6, PySide6, PyQt5, PySide2, PyQt4, PySide)
- Checks both already imported modules and attempts to import available bindings
- Returns a typed `QtBindings` enum value or `None` if no binding is found

## Installation

```bash
pip install detect-qt-binding
```

## Usage

```python
from detect_qt_binding import detect_qt_binding, QtBindings

binding = detect_qt_binding()

if binding is None:
    print("No Qt binding found")
elif binding == QtBindings.PyQt6:
    print("PyQt6 detected")
# ... handle other cases
```

## API Reference

### `detect_qt_binding() -> Optional[QtBindings]`

Attempts to detect which Qt binding is available by:
1. Checking already imported modules
2. Attempting to import each known Qt binding

Returns:

- A `QtBindings` enum member if a binding is found
- `None` if no Qt binding is available

### `QtBindings` Enum

Available values:

- `PyQt6`
- `PySide6`
- `PyQt5`
- `PySide2`
- `PyQt4`
- `PySide`

## License

MIT License - Based on code from [pyqtgraph](https://github.com/pyqtgraph/pyqtgraph) (also MIT licensed)