semvec/pypi-packages huggingface dataset:
pyweb-database 1.0
This is a simple JSON-based database library
Requires Python: >=3.7
Keywords: example python

It is a simple JSON-based database library. It can be used both synchronously and asynchronously

Example of synchronous use:
conn = pyweb_database.connection(database_name) # Creating a database connection
conn.create_table(table_name)  # Create a table
conn.insert_datas_into_table(table_name, [9234, 3895345, 4358, 340858340], unique=True)  # Insert multiple unique data into table
conn.delete_from_table(table_name, 9234)  # Delete the data '9234' from table
conn.update_data(table_name, 3895345, 50505)  # Update the data '3895345' to '50505' in table
conn.get_data(table_name) # Getting content from table
conn.insert_into_table(table_name, 8023)  # Insert a single data '8023' into table
conn.delete_table(table_name)  # Delete table

Example of asynchronous use:
conn = pyweb_database.connection(database_name) # Creating a database connection
await conn.create_table(table_name)  # Create a table
await conn.insert_datas_into_table(table_name, [9234, 3895345, 4358, 340858340], unique=True)  # Insert multiple unique data into table
await conn.delete_from_table(table_name, 9234)  # Delete the data '9234' from table
await conn.update_data(table_name, 3895345, 50505)  # Update the data '3895345' to '50505' in table
await conn.get_data(table_name) # Getting content from table
await conn.insert_into_table(table_name, 8023)  # Insert a single data '8023' into table
await conn.delete_table(table_name)  # Delete table
SPyOD 0.1.7
Spectral Proper Orthogonal Decomposition
Requires Python: >=3.7

# Spectral Proper Orthogonal Decomposition


## Table of contents

  * [Description](#description)
  * [Installation](#installation)
  * [License](#license)
  * [Contact us](#contact-us)
  * [Contributors](#contributors)


## Description

__SPyOD__ is the python implementation of the Spectral Proper Orthogonal Decomposition published by [Sieber et al. in 2016](https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/spectral-proper-orthogonal-decomposition/DCD8A6EDEFD56F5A9715DBAD38BD461A).

It includes two __.py-files__:

- `spod.py` - Includes the function `spod` which calculates the SPOD and

- `findpairs.py` - Includes the post-processing of the SPOD in the function `findpairs` which finds linked modes as described in [Sieber et al. in 2016](https://www.cambridge.org/core/journals/journal-of-fluid-mechanics/article/spectral-proper-orthogonal-decomposition/DCD8A6EDEFD56F5A9715DBAD38BD461A)


and one __jupyter notebook__ example `example_SPOD_free_jet.ipynb` of the SPOD of experimental PIV data from a free jet flow. The data are stored in `PIV_jext_example.mat`.

The paper describing the SPOD method is made publicly available by the TU Berlin at the following link: [https://doi.org/10.14279/depositonce-6377](https://doi.org/10.14279/depositonce-6377).

## Installation 

The __SPyOD__ package can be installed using the following command:
```bash
$ pip install SPyOD
```
The package can be imported by
```bash
$ from spyod.spod import spod
$ from spyod.findpairs import findpairs
```

## License

__SPyOD__ is released under the MIT License. Please have a look at [LICENSE.md](LICENSE.md) for more details.

## Contact us
The best way to contribute is to report any issues you mention for improvement and extension of the code or documentation as well as fixing bugs etc. Feel free to contact us. 


## Contributors

<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
<!-- prettier-ignore-start -->
<!-- markdownlint-disable -->
<table>
  <tbody>
    <tr>
      <td align="center"><a href="https://github.com/grigorishat"><img src="https://avatars.githubusercontent.com/u/114856563?s=400&u=9eea6aaba80fe841c18c8a621111e2d9f3da63ed&v=4" width="100px;" alt="Grigorios Hatzissawidis"/><br /><sub><b>Grigorios Hatzissawidis</b></sub></td>
      <td align="center"><a href="https://github.com/morsieber"><img src="https://avatars.githubusercontent.com/u/116639701?v=4" width="100px;" alt="Moritz Sieber"/><br /><sub><b>Moritz Sieber</b></sub></td>

  </tbody>
</table>

<!-- markdownlint-restore -->
<!-- prettier-ignore-end -->

<!-- ALL-CONTRIBUTORS-LIST:END -->
pymecavideo 8.0rc11
pedagogic tool to analyze video records for mechanics
Requires Python: >=3.7

**Description :**

Pymecavideo est un logiciel écrit en PyQT (4 puis 5) pour permettre le
pointage d'une vidéo, le tracé des trajectoires du point pointé et
l'export des positions (temporelles et spatiales) des points choisis.


**Installation :**

Pymecavideo nécessite 4 dépendances :
        PyQT5 : python-qt5  (-devel si vous utilisez les sources)
        OpenCV : python-opencv-headless
        pyqtgraph : python-pyqtgraph
        python-odf (ou odfpy)
        matplotlib
	
avec une installation via pip : 
pip install opencv-python-headless
pip install pyqt5
pip install python-pyqtgraph


**Contribuer :**

Pymecavideo a été en premier lieu écrit en français : le code est
documenté en français, il est internationalisé et des fichiers de
localisation existent en anglais, espagnol et catalan.

Cependant, si vous voulez contribuer et formuler des patch, merci de
mettre vos variables avec des noms français ou francisés :
    exemple : "self.calcul_precis" sera préféré à "self.accurate_compute"

La version git se trouve ici :
https://gitlab.com/oppl/pymecavideo

Toute la gestion des bugs se fait pr gitlab
https://gitlab.com/oppl/pymecavideo/issues

pour l'installer : Voir le fichier INSTALL 

Enjoy :=)

JB BUTET <ashashiwa@gmail.com>