semvec/pypi-packages huggingface dataset:
rblx 0.1.0
A Python library for Roblox utilities
Requires Python: >=3.8

# RBLX

RBLX is a Python library providing utilities for Roblox.

## Installation

```bash
pip install .
```

## Usage

```python
from rblx import get_username, greet

print(get_username(123))
print(greet("TuFueguito"))
```
sqlramen 0.9.3
SQLRamen provides a convenient way to map Python objects to relational database tables, with no declarative code of any kind.  It's built on top of the SQLAlchemy ORM and provides a super-minimalistic interface to an existing database.


SQLSoup is no longer supported and does not work with modern versions of SQLAlchemy. For modern support of ad-hoc models based on database reflection, please refer to the automap feature at: https://docs.sqlalchemy.org/en/stable/orm/extensions/automap.html

SQLRamen intends to be a replacement to SQLSoup with a different API

# SQLRamen


SQLRamen provides a convenient way to map Python objects to relational database tables, with no declarative code of any kind. It's built on top of the SQLAlchemy ORM and provides a super-minimalistic interface to an existing database.

Usage is as simple as:

```python

from sqlramen import *
db = SQLRamen("sqlite:///../pdca/aide")
user = db.query(db.table.user).filter_by(email="j@j.com").one()
[ l.message for l in user.comment_collection ]
# ['SCAM Manual\r\n\r\nA complete guide to create a guide with scam',
# ...
#  'future plan',
#  'further down']
db.query(db.table.comment.message).join(db.table.comment.user
    ).filter(db.table.user.email=="j@j.com").all()
# same
print([l for l in db.table.user.__table__.c])
# [Column('id', INTEGER(), table=<user>, primary_key=True, nullable=False),
# Column('pic_file', TEXT(), table=<user>),
# Column('name', TEXT(), table=<user>, nullable=False),
# Column('email', TEXT(), table=<user>, nullable=False),
# Column('secret_token', TEXT(), table=<user>),
# Column('secret_password', TEXT(), table=<user>, nullable=False)]
db.raw("select * from comment limit 5").all()
#[('2025-01-12 12:52:09', 1, 1, None, 'SCAM Manual\r\n\r\nA complete guide to create a guide with scam', None, 'story'),
# ('2025-01-12 13:28:14', 2, 1, 1, 'Synopsis\r\n\r\nA frontend to a pandoc toolchain to build a book in a supposedly new way.', None, 'story_item'),
# ('2025-01-12 13:28:47', 3, 1, 1, 'How to install and start it\r\n', None, 'story_item'),
# ('2025-01-12 13:29:48', 4, 1, 1, 'walkthrough to create this manual with the tool\r\n\r\nFirst post//landing page', None, 'story_item'),
# ('2025-01-12 13:30:23', 5, 1, 3, 'Quickstart', None, 'comment')]
```

## db\_introspect

Usage:
```bash

db_introspect sqlite:///../pdca/aide && xdot out.dot
# introspecting sqlite:///../pdca/aide
# nb col = 23
# nb fk = 7
# output available in out.dot
```

output:

![entity relation diagram](https://github.com/jul/sqlramen/blob/main/out.png?raw=true)

# Changelog

## 0.9.2//0.9.3

* improved README

## 0.9.1

* initial release
pycommence 0.2.4
wrapper for Commence Rm via pywin32
Requires Python: >=3.13

.. |.modindex| replace:: Module Index
.. _.modindex: https://pawrequest.github.io/pycommence/py-modindex.html
.. |.pycommence.wrapper._icommence| replace:: ``pycommence.wrapper._icommence``
.. _.pycommence.wrapper._icommence: https://github.com/pawrequest/pycommence/blob/main/src/pycommence/wrapper.py


PyCommence - Python vs Commence RM
====================================================

`Commence RM <https://commence.com/information-for-customers-81/>`_ is a powerful and flexible database application for customer relationship management, but it is decidedly dated, and its API is not very user-friendly.

Commence Designer Edition is a particuarly cranky beast that demands super-brittle VBS and DDE approaches to integration and offers little support for modern tooling.

This package wraps the Commence API in a python interface for convenience; a complete installation of Commence is required.

PyCommence is built atop |.pycommence.wrapper._icommence|_ - a makepy generated Com-Object wrapper - via the `win32com` package.


* `PyCommence Api <https://pawrequest.github.io/pycommence/pycommence_api.html>`_

  * `PyCommence Object <https://pawrequest.github.io/pycommence/pycommence_api.html#module-pycommence.__init__>`_


  * `Cursor <https://pawrequest.github.io/pycommence/pycommence_api.html#module-pycommence.cursor>`_


  * `Types <https://pawrequest.github.io/pycommence/pycommence_api.html#module-pycommence.pycmc_types>`_



* `Commence Wrapper <https://pawrequest.github.io/pycommence/pycommence_wrapper.html>`_

  * `DB Wrapper <https://pawrequest.github.io/pycommence/pycommence_wrapper.html#module-pycommence.wrapper.cmc_db>`_


  * `Cursor Wrapper <https://pawrequest.github.io/pycommence/pycommence_wrapper.html#module-pycommence.wrapper.cmc_csr>`_


  * `RowSet Wrappers <https://pawrequest.github.io/pycommence/pycommence_wrapper.html#module-pycommence.wrapper.rowset>`_


  * `Commence Enums <https://pawrequest.github.io/pycommence/pycommence_wrapper.html#module-pycommence.wrapper.enums_cmc>`_


  * `Commence Conversation Wrapper <https://pawrequest.github.io/pycommence/pycommence_wrapper.html#module-pycommence.wrapper.conversation>`_


  * `ICommence Interface Wrapper <https://pawrequest.github.io/pycommence/pycommence_wrapper.html#module-pycommence.wrapper._icommence>`_



* `Commence RM API <https://pawrequest.github.io/pycommence/cmc_api.html>`_

  |




Index
-----------

* |.modindex|_
zbl 0.7.1
real-time window capture library based on D3D11 and Windows.Graphics.Capture
Requires Python: >=3.9
Keywords: windows, d3d11, window-capture, graphics-capture, cv

# zbl

[![PyPI version](https://badge.fury.io/py/zbl.svg)](https://badge.fury.io/py/zbl)

`zbl` is a Rust and Python library for screen/window capturing on Windows. It provides an interface
to `Windows.Graphics.Capture` API with a focus on simplifying integrating computer vision applications for Windows Desktop apps.

**This library is in early development stage**. This means that it's only verified to work for a 'happy path'
scenarios - beware of bugs!

## Python

### Installation

`pip install zbl`

Alternatively, you can install suitable wheel from [releases page](https://github.com/modelflat/zbl/releases).

### Usage

```python
from zbl import Capture

with Capture(window_name='visual studio code') as cap:
    # grab a single frame (numpy.ndarray) and print its shape
    print(cap.grab().shape)
```

The snippet above will capture a window which title contains the string `visual studio code`,
grab one frame and print its shape.

See [Capture](https://github.com/modelflat/zbl/blob/master/zbl_py/zbl/__init__.py) for other API methods.

To run an example using OpenCV's `highgui`:

1. Install `opencv-python`
2. Run `python -m zbl --display-id 0`

## Rust

See [examples](https://github.com/modelflat/zbl/tree/master/zbl/examples).
Note: if you are getting OpenCV build errors when building the example, check out [how to build OpenCV rust bindings](https://github.com/twistedfall/opencv-rust#rust-opencv-bindings).

## Comparison to `mss` / `pyautogui`

Both are very slow at the time of writing. `mss` tops at 30-50 fps in a tight loop, `pyautogui` is
even slower than that. `zbl` is able to capture an order of magnitude faster (at 500-700 fps). This allows a lot more time for the actual processing.

## Credits

`zbl` is heavily inspired by [screenshot-rs](https://github.com/robmikh/screenshot-rs).
mfthree 11.7.2
Matter and Form - THREE - Library
Requires Python: >=3.10

# Matter and Form THREE Library

## Overview
The Matter and Form THREE library provides a comprehensive API for controlling and interacting with the Matter and Form THREE scanner. This library allows developers to build custom integrations, automate tasks, and create new front-end systems for 3D scanning.

## Project Home
[Github Project HERE](https://github.com/Matter-and-Form/three-python-library).

## Examples 

### Using Premade Examples
To connect to the scanner, you can use the provided examples. For instance, to run the connection example, execute:

```sh
python examples/connect.py
```

### Simple Example
Here is an example of how to use the library to connect to the scanner and control the projector:

```python
from matter_and_form_three import Scanner

# Create and connect to the scanner
scanner = Scanner(OnTask=None, OnMessage=None, OnBuffer=None)
# Use the Zeroconf address or replace with the ip
scanner.Connect("ws://matterandform.local:8081")

# Simple request to list all projects
projectTask = scanner.list_projects()

# Check the output from the task for errors
if projectTask.Error:
    print('Error:', projectTask.Error)
    return
# Do something with the output
for project_obj in projectTask.Output:
    project = Project.Brief(**project_obj)
    print('Project index:', project.index, ' - Name:', project.name)
```

### More Examples
The library comes with several pre-made examples. You can find them in the [examples directory](https://github.com/Matter-and-Form/three-python-library/tree/develop/three/examples).

To run a specific example, use:

```sh
python three/examples/<example_name>.py
```

## Documentation
For detailed documentation, visit the TODO -> [official documentation](https://github.com/Matter-and-Form/three-python-library/wiki).


## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
mq-image-processing 0.0.1
Processamento de imagens usando combinação e transformação
Requires Python: >=3.8

# image_processing

Description,
The package image_processing is used to:
    Processing:
    - Histogram matching
    - Structural similarity
    - REsize image

    Utils:
        - Read image
        - Save image
        - Plot image
        - Plot result
        - Plot histogram

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name

```bash
pip install package_name
```

## Author
Mariana Simões Queiroz

## License
[MIT](https://choosealicense.com/licenses/mit/)
frigg 0.1.2
Convert common crawl to multimodal datasets.
Requires Python: >=3.10

# Frigg

Installation
```
uv pip install frigg
```

Citation
```
@misc{beaumont-2022-cc2dataset,
  author = {Romain Beaumont},
  title = {cc2dataset: Easily convert common crawl to a dataset of caption and document.},
  year = {2022},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/rom1504/cc2dataset}}
}
```