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Understanding Python Regular Expressions is an example-driven guide that teaches regex from beginner concepts through advanced pattern techniques. It primarily covers Python’s standard re module while also introducing the third-party regex package. Early chapters explain anchors, alternation, grouping, escaping, character classes, and quantifiers. Later material explores backreferences, lookarounds, flags, Unicode, common tasks, debugging, and regex pitfalls.

Full documentation: Download pfactrisX.Y.html Tetris, but with arithmetic, each tile has an integer on it. Drop a tile onto a tile below so that the numbers divide and cancel out. Once a tile drops and cancels with the tile below, it will attempt to cancel the next tile below that and so on. If no more below-cancellations happen it will also try to cancel with the tile to the left and then the tile to the right of it. For complete description go to Files tab and see readme.txt

Learn Python 3 is a sample-code repository that accompanies Liao Xuefeng's Python 3 tutorial. It provides runnable examples that reinforce concepts introduced throughout the course. The collection starts with basic syntax and progresses through functions, modules, object-oriented programming, and functional programming. More advanced examples cover asynchronous programming, multitasking, databases, regular expressions, sockets, and web development. It also includes material for I/O,...

100 Days of Code YouTube is a day-by-day source-code collection for a comprehensive Python programming course. The repository organizes lessons into numbered folders that progress from basic concepts to advanced language features. Early material covers variables, data types, input, strings, conditions, loops, functions, and common collections. Intermediate lessons explore exceptions, modules, file I/O, functional programming, and extensive object-oriented programming concepts. Later days...

ety is a Python library and command-line tool designed to explore and retrieve the etymological origins of words by analyzing linguistic data and relationships between languages. It allows users to query a word and obtain its historical roots, including intermediate forms across different languages and time periods. The tool can generate recursive etymology chains as well as tree structures that visually represent how a word evolved over time.

This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested...

...The goal of this collection is to offer a quick reference for both old and new users but also to provide a set of exercises for those who teach. For extended exercises, make sure to read From Python to NumPy. Markdown and ipython notebook are created programmatically from the source data in source/exercises.ktx. To modify the content of these files, please change the text in the source and run the generators.py module with a python interpreter with the libraries under requirements.txt installed. The keyed text format (ktx) is a minimal human readable key-values to store text (markdown or others) indexed by keys.

The Python scripts for the conversion from the Chinese Pinyin transcription(ISO 7098) to International Phonetic Alphabet(IPA), comprised of a core module for developers and a flexible GUI application for the common end-users on Modern Chinese phonetics.

Python module for reading and writing MARC records in both transport (z39.2) and plain-text mnemonic formats. Also includes simple command-line tools for translation between these formats.