semvec/pypi-packages huggingface dataset:
open-aoi 0.0.17
Support python package for Open AOI system project.
Requires Python: >=3.7
Keywords: automated optical inspection, pcb, computer vision

# Welcome to Open AOI!
This is a support package for [Open AOI project](https://github.com/ChrnyaevEK/open-aoi-system).

Open AOI is ROS2 powered Automated Optical Inspection framework, developed as part of my master thesis at **BUT Brno** university. Project aims to provide development environment for PCB optical inspection tasks in production. Project targets **Raspberry Pi** platform yet it is possible to use any other general purpose computer. Project use **docker** and **Nice GUI** for frontend.


*Please refer main project repository for details.*

## Run web service
Start web server with the following command.
```
python -m open_aoi_web_interface.main
```

## Run GPIO service
```
python -m open_aoi_gpio_interface.main
```
app-lib-py 0.0.14
Example library for scientific software.
Requires Python: >=3.6

# app-lib-py

This template is a suggestion of good practice for a scientific python library that includes continuous integration and conntinuous development and continuous documentation.
The application is demonstrated though streamlist which is deployed with continuous deployment, and also made a available via pypi as a python library with `pip install`

The single github repo contains 2 seperate software artefacts, a python library that can be installed and used by others, and a streamlit web application that demonstreates the library and provides a simple usage. Additionally there is a docker file which allows the upload of a docker image to dockerhub for a middle use of locally hosted web application.

To use this library yourself, use the "Template" button as described below.

## 1. Create a template for yourself

## 2. Change the name (search on app-lib-py or app_lib_py)
- in the yml files in pydoctor line 24
- docker yml line 26
- pypi yml line 43

## 2. Setup development environments
See [dev environments](dev.md)

## 3. Setup precommit hooks
https://pre-commit.com/
Run it to check
`pre-commit run --all-files`
`ruff --target-version=py311 --line-length 88 . --fix`
`black ./ --check --line-length 88 --diff`

## 4. Change the tokens, get all workflows in github actions working

pydoctor --make-html --html-output=./docs/api lib/src/app_lib_py --theme readthedocs

## 5. Test driven development, design the functionality

## 6. Implement

## 7. Distribute and deploy

### 7a. Pypi
Tokens are needed from pypi and from github. Follow these instructions: [pypi gha](https://www.seanh.cc/2022/05/21/publishing-python-packages-from-github-actions/)

To release to pypi you need to either:
- Create a release in github, the tag will be the version number of the library
- Or if it is only a minor incremebt, you can run the workflow in Actions [Create a new patch release](https://github.com/RachelAlcraft/app-lib-py/actions/workflows/release.yml). This will increment the minor version and release.


### 7b. Streamlit
Streamlit will be automatically deployed when the main branch is updated after the link with streamlit is made.
1. Create an account with [streamlit io](https://streamlit.io/)
2. Go to the [deploy](https://share.streamlit.io/deploy)
3. Choose your repo: RachelAlcraft/app-lib-py
4. Choose Branch: Main
5. Choose entry file: app/home.py
6. Amend the domain to your liking [app-lib-py](https://app-lib-py.streamlit.app/)
7. Press deploy

### 7c. Docker
steelas 0.2.0
steelas is a Python package for the design of steel structures to relevant Australian Standards
Requires Python: >=3.11
Keywords: AS4100, steel structures, structural engineering

# About
*steelas* is a Python package with tools to support research and design of Australian steel structures. It can be used to determine the material properties, section properties, and design capacities for structural members as per Australian Standard AS4100:2020 (Steel Structures). 

# Documentation
Detailed information on *steelas* is available in package documentation at [steelas.readthedocs.io](https://steel-as.readthedocs.io/). This includes project background, examples, and an API reference guide.

# Installation
*steelas* can be installed from the Python Package index:
```
pip install steelas
```

For more detailed instructions, please refer to the [documentation]([https://steel-as.readthedocs.io]).

# Current Features
- **Section and component library**: define sections and calculate section properties from typical Australian steel products and components, or from custom user input. 
- **Material library**: create steel materials from typical Australian grade classifications.
- **Design capacity calculations**: solve the design capacities of structural steel members following AS4100 design methods.

# Questions, Feedback, and Contributions 
If you have questions, feedback, or suggestions for further development, please email [Joe Gattas](https://researchers.uq.edu.au/researcher/9443) or create an issue on the *steelas* github repository.

Similarly, if you find any bugs, or are interested to contribute to the project, please create an issue or email Joe.


# License 
*steelas* is an open source engineering tool provided under an MIT License. Please refer to the [LICENSE](./LICENSE.md) file for more information. 

Please note that this software has been developed by student and academic engineering researchers, NOT by chartered or registered engineers. 

# Acknowledgements
This package has been developed from research projects supported by the [University of Queensland](https://civil.uq.edu.au/).

If you use *steelas* for projects or scientific publications, please consider citing our work.
pdfconversorcall 0.0.2
Convert WebElement into pdf
Keywords: python, rpa, robocorp, pdf, html, conversor


# HTMLConversor

HTMLConversor is a Python class that automates the process of converting sales data from an intranet website to a PDF file. It utilizes the Robot Framework's RPA library for web automation.

## Features

- Log in to the intranet website.
- Download sales data stored in an Excel file.
- Fill in a sales form with data from the Excel file.
- Collect sales results and export them as a PDF file.
- Log out from the intranet website.

## Installation

1. Make sure you have Python installed on your system.
2. Install the required dependencies using pip


## Usage

```python
from HTMLConversor import HTMLConversor

# Initialize HTMLConversor
converter = HTMLConversor()

# Convert sales data to PDF
converter.to_pdf()
pdf-conversor-test-123 0.0.1
Convert WebElement into pdf
Keywords: python, rpa, robocorp, pdf, html, conversor


# HTMLConversor

HTMLConversor is a Python class that automates the process of converting sales data from an intranet website to a PDF file. It utilizes the Robot Framework's RPA library for web automation.

## Features

- Log in to the intranet website.
- Download sales data stored in an Excel file.
- Fill in a sales form with data from the Excel file.
- Collect sales results and export them as a PDF file.
- Log out from the intranet website.

## Installation

1. Make sure you have Python installed on your system.
2. Install the required dependencies using pip


## Usage

```python
from HTMLConversor import HTMLConversor

# Initialize HTMLConversor
converter = HTMLConversor()

# Convert sales data to PDF
converter.to_pdf()