Search Results for "python accounting source code"
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Showing 82 open source projects for "python accounting source code"
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Hello Python
Comprehensive tutorial repository aimed at teaching the Python program
Hello-Python is a comprehensive tutorial repository aimed at teaching the Python programming language from scratch for beginners. It includes over 100 classes and about 44 hours of video instruction, combined with code samples, projects, and a chat community for support. The material covers the fundamentals—variables, data types, loops, functions—as well as intermediate topics like date handling, list comprehensions, file IO, regular expressions, modules, and packages. ... -
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Google Open Source Project Style Guide
Chinese version of Google open source project style guide
Each larger open source project has its own style guide, a series of conventions on how to write code for the project (sometimes more arbitrary). When all the code maintains a consistent style, it is more important when understanding large code bases. easy. The meaning of "style" covers a wide range, from "variables use camelCase" to "never use global variables" to "never use exceptions". The English version of the project maintains the programming style guidelines used in Google. If the... -
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AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. -
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Claude How-To
A visual, example-driven guide to Claude Code
Claude How-To is a visual, example-driven guide for learning Claude Code. It covers basic concepts, memory, slash commands, hooks, skills, subagents, MCP configuration, plugins, and advanced agent workflows. The project is designed as a practical learning path rather than a simple list of notes. It includes copy-paste templates that users can apply directly to their own projects. The guide also uses diagrams and structured examples to explain not only how features work, but why they matter... -
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Open Science
Open Science is an open-source, local-first, model-agnostic research
Open Science is an open-source, local-first AI research workbench built for scientific discovery on macOS, Windows, and Linux. Researchers can describe a task in plain language and let an agent inspect files, execute Python or R, search the web, and call scientific data connectors. The system is model-agnostic, allowing users to connect supported providers, compatible gateways, or subscription-based backends. -
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ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
ThinkStats2 is the code and text companion for the second edition of Think Stats, an introduction to statistics and data science for Python programmers. It teaches probability and statistical reasoning through short programs, experiments, and analysis of real datasets. The material emphasizes exploratory methods that help readers ask and answer practical questions with data. Case studies draw from public sources, including health-related datasets, to connect abstract concepts with realistic... -
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PocketFlow Tutorial Codebase Knowledge
Codebase to Tutorial
PocketFlow Tutorial Codebase Knowledge is a project that demonstrates how to build an AI agent capable of analyzing arbitrary codebases and generating beginner-friendly tutorials that explain how they work, turning complex source code into clear educational content. The repository builds on a lightweight 100-line LLM framework and uses natural language models to inspect repository structures, identify core abstractions, map dependencies, and articulate the reasoning behind code design and... -
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ML for Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
ML-For-Beginners is a structured, project-driven curriculum that teaches foundational machine learning concepts with approachable math and lots of code. Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. The... -
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PythonPark
Python open source project "The Road to Self-Study Programming"
PythonPark is a large, curated “learning playground” for Python — essentially a comprehensive self-study meta-repository aimed at helping learners progress in Python programming, data science, machine learning, web scraping, and software engineering practices. It aggregates tutorials, learning guides, project examples, and resources across topics: from Python basics and data structures to machine learning, web scraping, and even interview preparation and “programmer life” guidance. Because... -
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Ansible-lint
Best practices checker for Ansible
Ansible Lint is a command-line tool for linting playbooks, roles and collections aimed towards any Ansible users. Its main goal is to promote proven practices, patterns and behaviors while avoiding common pitfalls that can easily lead to bugs or make code harder to maintain. Ansible lint is also supposed to help users upgrade their code to work with newer versions of Ansible. Due to this reason we recommend using it with the newest version of Ansible, even if the version used in production... -
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LeetCode Book
Comprehensive study guide for coding interviews
LeetCode-Book is a comprehensive study guide for coding interviews that consolidates algorithm patterns, data-structure templates, and worked LeetCode solutions. It organizes problems by topic—arrays, linked lists, stacks/queues, trees/graphs, dynamic programming, greedy, backtracking, and math—so you can study systematically. Explanations are concise but intentional, highlighting why a pattern fits, how to reason about boundary cases, and the time/space trade-offs. Many entries include... -
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Web Dev for Beginners
About 24 Lessons, 12 Weeks, Get Started as a Web Developer
Web-Dev-For-Beginners is Microsoft’s open source, project-based curriculum for learning web development from scratch. Designed as a 12-week, 24-lesson course, it covers HTML, CSS, and JavaScript fundamentals through hands-on projects like terrariums, browser extensions, and space games. Each lesson includes a mix of pre-lecture quizzes, written content, assignments, challenges, and post-lecture quizzes to reinforce learning. The course also offers global accessibility with translations in... -
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Scientific Visualization
An open access book on scientific visualization using python
The Scientific Visualization book is a freely available open-access textbook that introduces how to produce effective scientific visualizations using Python, focusing especially on leveraging the popular plotting library Matplotlib (and related tools). It goes beyond simple plotting tutorials and emphasizes design principles: how to choose colors, layout subplots, annotate graphs, and present data in a way that is both accurate and visually compelling. As such, it serves as a guide for... -
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Build your own X
Master programming by recreating your favorite technologies
build-your-own-x is a massive, community-curated roadmap of hands-on tutorials that teach you to re-implement complex systems from scratch—things like databases, compilers, operating systems, interpreters, web servers, neural networks, regex engines, and more. Rather than offering abstract theory, it organizes step-by-step guides by topic and by programming language, so you can pick a project that fits your stack and skill level. The focus is on demystifying internals: you don’t just use a... -
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AI Researcher
An autonomous AI researcher
AI Researcher is an experimental open-source project that demonstrates how multiple AI agents can collaborate to conduct complex research tasks from start to finish with minimal human intervention. It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they... -
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Recommenders
Best practices on recommendation systems
The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several... -
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Simulation of Urban MObility
SUMO is a microscopic, multi-modal traffic simulation.
SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians and comes with a large set of tools for scenario creation. The code and the issue tracker can be found at https://github.com/eclipse-sumo/sumo/ The documentation can be found at https://sumo.dlr.de/docs/ -
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ktrain
ktrain is a Python library that makes deep learning AI more accessible
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines... -
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Think Python 2
LaTeX source and supporting code for Think Python, 2nd edition
ThinkPython2 is the repository for the second edition of Allen Downey’s Think Python textbook, which teaches programming fundamentals in Python to beginners. The code includes all of the example programs, exercises, and supplementary files referenced in the book, allowing learners to run the examples, experiment, and extend them. 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,... -
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Popppy
Population Propogation in Python. Simulate births, marriages, deaths
...Beyond that the input parameters fertility rate, marriage age and mortality rates could change in an unpredictable manner. The tool could also be useful and fun for a student, for anyone curious about near-future demographics or CO2 emissions, or curious amateurs. Since it's Open Source (<2000 lines of Python code) you can make your own changes. It runs from the command line and should run on any (MS WIndows, Linux/Unix/Mac OSX) platform running Python 3. A non-Python MS Windows pre-compiled Popppy executable/binary is included for those who just want to run it without having the bother of installing Python 3.x or not wanting to change the source code. -
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Prime number ( primenumbers )
Benchmark for 50 000 000 prime numbers as single and multicore
...Surprise, same code in JavaScript for M2 chip in Safari: 12,5 sec single core and 3,3 sec multi core. Python version with numba and numpy on MacOS with M2: 3,78 sec, Intel Ultra 5 225F Linux Fedora 43 GNOME(*Intel): 3,64 sec., W11Intel: 3,73; Faster style in python, MacOS M2: 1,81 sec, *Intel & W11Intel: 2,02 sec.; Ultra faster style in python, MacOS M2: 1,24 s - 1,26 s - 1,34 s, *Intel: 1,48 s - 1,50 s, W11Intel: 1,53 - 1,63. -
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clavirio
Learn touch typing without leaving the terminal
A free, open-source typing tutor for the terminal. Progressive lessons, practice modes, real-time stats, and a virtual keyboard with finger hints — for QWERTY, Dvorak, and Colemak. Methodology Research on typing skill suggests that skilled typing relies more on implicit procedural control than on explicit knowledge of key locations. The paper also suggests that the keyboard is represented in terms of its row-and-column structure, not as a memorized list of individual... -
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Gemi
PCR primers / probes design from multiple & degenerate sequences
...Gemi can be used for quantitative, real-time and conventional PCR (qPCR, rt-PCR, etc.), and Sanger sequencing. Gemi can parse large dataset of sequences efficiently. Python source code is available upon request. Milestone: The tool reached about 3000 downloads sine 2012. Article Gemi: PCR primers prediction from multiple alignments. Comparative and functional genomics 2012 PMID: https://www.ncbi.nlm.nih.gov/pubmed/23316117 A great review on designing primer, Gemi, and other tools: Designing degenerate primers: Overview, challenges, and computational methods. ... -
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Mastering Bitcoin
Mastering Bitcoin 3rd Edition - Programming the Open Blockchain
The bitcoinbook repository contains the source code for Mastering Bitcoin, the authoritative open-source book by Andreas M. Antonopoulos on Bitcoin and cryptocurrency technologies. Written in a collaborative and continuously updated format using Markdown and AsciiDoc, the book serves as a comprehensive technical guide for developers, engineers, and system architects who want to understand how Bitcoin works. It covers the protocol, cryptography, peer-to-peer architecture, wallets, mining, and... -
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D2L.ai
Interactive deep learning book with multi-framework code
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge. This open-source book represents our attempt to make deep learning approachable, teaching you the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and interactive examples with self-contained code. Offers sufficient technical depth to...
