Open Source Python Libraries - Page 25

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https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README.md https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README_EN.txt https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README_EN.deps.txt https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/README_EN.linux_x86_64.txt https://sourceforge.net/p/tacklelib/tacklelib/ci/master/tree/changelog.txt

A simple font chooser for Tkinter that allow the user to select the font family among the fonts available on his/her system. The size and style (bold, italic, underline, strikethrough) of the text can be set too. This module contains a `FontChooser` class which implements the font chooser and an `askfont` function that displays the font chooser and returns the chosen font when the user closes the font chooser. The font is returned as a dictionary like the one returned by the function `tkFont.Font.actual`.

TimerMiddleware Call Count allows you to create CountCase's for your Pylons application using your applications custom TimerMiddleware.

Transformer is a TensorFlow implementation of the architecture introduced in the Attention Is All You Need paper. It was created as a readable and relatively modular reference for understanding and experimenting with Transformer-based machine translation. The updated implementation corrects issues involving masking, positional encoding, and other parts of the original code. It adds components such as byte-pair encoding and shared weight matrices. Training and evaluation are demonstrated with the IWSLT 2016 German-to-English translation dataset. The repository includes preprocessing, training, inference, evaluation, configurable hyperparameters, pretrained checkpoints, and BLEU-based translation results.

The troposphere library allows for easier creation of the AWS CloudFormation JSON by writing Python code to describe the AWS resources. troposphere also includes some basic support for OpenStack resources via Heat. To facilitate catching CloudFormation or JSON errors early the library has property and type checking built into the classes.

vae is a collection of Keras experiments implementing variational autoencoders and related generative models. It includes simple VAE and conditional VAE examples along with several alternative architectures. Separate scripts explore CelebA image generation, convolutional VAEs, clustering-oriented variants, hyperspherical latent spaces, and vector-quantized autoencoders. The repository includes sample output from a CelebA training run as a visual reference. Its documented environment uses Python 2.7 with TensorFlow 1.8 or 1.13 and Keras 2.2.4. The code is organized as standalone experiments rather than a unified library API. It is best suited for studying older Keras implementations of latent-variable generative modeling techniques.

The Validating Stub Resolver (vsResolver) is a DNS stub resolver that implements the Domain Name System Security Extensions (DNSSEC) specified in RFC 4033, RFC 4034 and RFC 4035. These add data origin authentication and data integrity to the Domain Name System. vsResolver extends the dnspython toolkit (http://www.dnspython.org/) and uses the pycrypto library for its underlying crypto implementation(https://www.dlitz.net/software/pycrypto/). Click on this link for a ridiculously simple python page demonstrating vsResolver working - http://superawesum.novas.us/py/hello.py. Try entering some domains and click submit. Then, enable details, click submit to get the details,and compare with what you get for that domain at http://dnssec-debugger.verisignlabs.com.

Wordvectors is a collection of pretrained word embeddings for more than 30 languages. It was created to make multilingual vector representations easier to obtain, especially for languages with fewer readily available resources than English. The repository provides models trained using both Word2Vec and fastText. Training corpora are constructed from Wikipedia database dumps using language-specific preprocessing when necessary. Scripts are included for corpus creation and for training new embeddings with either supported algorithm. Available languages include Chinese, Japanese, Korean, Spanish, French, German, Hindi, Russian, Vietnamese, Thai, and many others, with model metadata covering vector, corpus, and vocabulary sizes.

xbar-plugins is the community plugin repository for xbar, the macOS menu bar utility inspired by BitBar. It contains scripts, programs, and command-line tools that add quick status displays or interactive menu bar actions. The repository works as a centralized collection where users can find plugins for monitoring systems, services, development tools, productivity, and everyday utilities. Plugin authors can contribute their own scripts so others can install and use them through xbar. The project is practical because xbar can turn almost any script output into a menu bar item. It is best suited for macOS users who want lightweight, customizable, script-driven information in their menu bar.

UniCurses is a wrapper for Python 2.x/3.x that provides a unified set of Curses functions on all platforms (MS Windows, Linux, and Mac OS X) with syntax close to that of the original NCurses. To provide functionality on MS Windows it wraps PDCurses.

Pyside QtRPT Python Binding for QtRPT (PySide Shiboken) QtRPT Report Engine Python Report License LGPL3 compatible with QtRPT (see license) """QtRPT is the easy-to-use print report engine written in C++ QtToolkit. It allows combining several reports in one XML file. For separately taken field, you can specify some condition depending on which this field will display in different font and background color, etc. The project consists of two parts: report library QtRPT and report designer application QtRptDesigner. Report file is a file in XML format. The report designer makes easy to create report XML file. QtRPT (http://www.qtrpt.tk/index.php) Recommendations: please read "readme.txt" file use QtRptDesigner -> to edit xml files. view examples. Important: from Qt5.12, the package must have the same version and subversion de PySide2 and shiboken2. for example the PyQtRPT_5.12.3 package has a requirement of PySide2_5.12.3 and shiboken2_5.12.3.

This is a Python package with extensions for Tkinter. It supports both Python 2.7 and Python 3.3. Currently, the project is in version 1.0 of the Production stage. Feel free to fork off the main project or send me possible additions to the package.