Search Results for "data flow"
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Showing 17 open source projects for "data flow"
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Complete-Python-Bootcamp
The complete Python bootcamp guide
...The bootcamp also includes dedicated modules for data analysis with Python, working with databases, and logging, helping learners connect Python skills to data science and backend engineering tasks. -
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Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
The Complete-Python-3-Bootcamp repository is an educational resource created by Pierian Data as part of their popular Python for Data Science and Machine Learning Bootcamp course. It contains a comprehensive collection of Jupyter Notebooks designed to teach Python programming from the ground up. The repository covers a wide range of Python topics, including data types, control flow, functions, object-oriented programming, error handling, modules, and advanced concepts like decorators and generators. ... -
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Python Zero to Hero for DevOps Engineers
Learn Python from DevOps Engineer point of you
...The repository is organized into Day-01 through Day-19 folders plus a small sample app, which makes it very easy to follow in sequence like a bootcamp. The curriculum starts with Python installation, environment setup, and writing your first script, then quickly moves into data types, strings, regular expressions, variables, and functions. It places a strong emphasis on DevOps-specific use cases: environment variables, command-line arguments, configuration handling, and automating log analysis or user management tasks are all explicitly woven into the exercises. As you progress, you encounter increasingly rich Python features such as lists (with list comprehensions), dictionaries, sets, operators, and control flow, always tied back to practical automation or infrastructure examples. -
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Python Core 50 Courses
Structured learning path that organizes Python fundamentals
Python-Core-50-Courses is a structured learning path that organizes Python fundamentals into 50 digestible lessons designed for steady, incremental progress. The curriculum starts with the basics—syntax, variables, data types, and control flow—then advances to functions, modules, object-oriented programming, and common standard-library utilities. Each lesson favors hands-on examples and short exercises so learners can immediately apply new concepts in code. Later sections typically touch on practical topics such as file I/O, error handling, regular expressions, and simple networking, giving learners a toolbox for everyday scripts and utilities. ... -
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Think Python 2
LaTeX source and supporting code for Think Python, 2nd edition
...The repository contains clean, well-commented Python scripts that are easy to follow and map directly to chapters of the text, covering topics like variables, control flow, functions, recursion, data structures (lists, dictionaries), classes and objects, file I/O, and algorithmic thinking. It also contains solutions or hints for many exercises so learners can check their work or explore alternative implementations. Because it’s educational, the repository emphasizes readability, clarity, and progressive learning rather than performance tuning or advanced constructs. -
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ALEPH-w
Data structures and Algorithms library
...Dynamic linear hash tables are implemented too. The main algorithms on graphs are implemented in an easy way and with good performance features. Network Flow (maximum and min cost), cut points, topological sort, spanning trees, min paths. etc. The graphs are generic in the sense that they can contain data independent of the algorithm. Several containers of the C++ STL library are implemented with Aleph-w. Their performance is better than GNU implementation -
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ThinkJulia.jl
Port of the book Think Python to the Julia programming language
...It provides a comprehensive introduction to programming and computational thinking using Julia’s modern, high-performance features. The book is structured to gradually teach core concepts such as variables, control flow, functions, recursion, object-oriented programming, and data structures, while offering hands-on exercises to reinforce each topic. By combining clear explanations with practical examples, the project helps both beginners and experienced programmers transition to Julia. The material emphasizes not only writing code but also reasoning about algorithms and problem-solving. ... -
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How Web Works
What happens behind the scenes when we type google in a browser?
How Web Works is an educational project that explains how the web functions behind the scenes, walking developers through the sequence of events that occur from the moment a user enters a URL into a browser to when content is delivered on the screen. It breaks down networking basics like DNS resolution, HTTP requests and responses, TCP/IP fundamentals, browser rendering processes, and how servers handle and respond to client requests. By illuminating these core web infrastructure concepts,... -
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Lisp Koans
Common Lisp Koans is a language learning exercise
Lisp Koans is a self-guided learning path for Common Lisp that teaches the language’s idioms through a series of failing tests you progressively make pass. Each koan introduces a concept—symbols, lists, macros, multiple dispatch, reader syntax—then asks you to fill in the blanks and run the suite again. The feedback loop is intentionally tight: fail, reflect, fix, and rerun until the tests become a form of living documentation. Because koans are organized from fundamentals to... -
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PSKoans
A simple, fun, and interactive way to learn the PowerShell language
PSKoans is an interactive, educational PowerShell module that teaches core PowerShell concepts via Pester test-driven “koans” (small exercises that initially fail and must be fixed). Designed for beginners to learn PowerShell through hands‑on problem solving, it guides users through basic syntax, data structures, and automation tasks. -
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Learn Python the Hard Way
Concise study notes derived from “Learn Python the Hard Way”
This repository contains concise study notes derived from “Learn Python the Hard Way,” organized to reinforce core Python concepts through small, targeted examples. It emphasizes hands-on practice—short scripts, exercises, and explanations that help cement syntax, data structures, functions, and modules. The notes call out common gotchas, idioms, and style preferences so learners form good habits early. Because the content is intentionally compact, it’s easy to revisit a topic quickly when... -
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A Whirlwind Tour of Python
The Jupyter Notebooks behind my OReilly report
A Whirlwind Tour of Python is a concise but fast-paced introduction to core Python concepts, created by Jake VanderPlas as a companion to his work in scientific computing and data science. It consists of a series of Jupyter notebooks that walk through syntax, semantics, control flow, data structures, functions, errors, iterators, list comprehensions, generators, modules, strings, regular expressions, and a short preview of data science tools. The material is aimed at people who already know how to program in another language and want to transition efficiently into idiomatic Python, particularly for research and analytical work. ... -
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Wonder if your yacht design is ok? Will your wing fly or sink due turbulent flow? Download hydrosim and check, it's easy.
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This research project seeks to use compiler techniques to perform an attribute-based data-flow analysis on (MOF/UML)models allowing for a syntax-driven validation of a model's static semantics as well as an abstract interpretation of i dynamic behavior.
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Gnome Flow is program written to calculate and visualize simple, steady-state fluid flows around objects. The program calculates the stream, vorticity and pressure using the relaxation method.
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iFlow is an open source visualization software that transforms programs into interactive control flow graphs. It can be used for educational or presentational purposes. APIs are provided for potential control analysis or even compiler optimizations.
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PHP Interview System is a easy-to-use research system to build complex survey(s), interview(s) and poll(s). The interview can be dynamic (interactive) flow. Collect and react on input. Export data for analysis.
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