Тестирование на pytest
pytest — ближе по духу к языку Python нежели unittest, которая накладывает определенные обязательства при разработке тестов. Например, создание классов-наследников от TestCase или выполнение определенной процедуры запуска тестов.
Но при разработке на pytest ничего этого делать не нужно. Вы просто пишете функции, которые должны начинаться с "test_" и используете assert, встроенные в Python.
Также он поддерживает запуск тестов на unittest и nose, то есть полная обратная совместимость с ними.
#python#pytest#assert
#python#algorithms
🐍
Algorithmic Thinking with Python: Foundations
Learn how to develop your algorithmic thinking skills to become a better problem solver.
🗣Robin Andrews
📆2022-04-26
⌚️1h 11m
🔗Link
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Main channel:@repo_science
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🔥 20 Step-by-Step Data Analysis Projects with Python Code
Below are popular data analysis projects from Kaggle, Github, and Medium users. They will:
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☕Coffee Shop Sales Analysis
⚽ FIFA World Cup Data Analysis
⚡️ADIDAS Sales Analysis
📱Netflix Data Analysis (1)
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🚕 Uber Rides Data Analysis
👀Smartwatch Data Analysis
🤑Financial Budget Analysis
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🎮 Video Game Sales Analysis
🤓 Is There a Trend of Increasing Geek Girls?
🏆 Let's Discover More About the Olympic Games!
📉Marketing Analysis
🐶Animal Shelter Data Analysis
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💲Billionaire Data Analysis
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😏Pokemon Data Analysis
📱Spotify Data Analysis. What Does It Take to Hit the Charts
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#python#beancount
Beancount is free, open-source double-entry accounting software that uses simple text files to track finances, create reports, and view data via a web interface. Download the current stable Version 3 from GitHub, check docs at beancount.github.io/docs, and ask questions on the mailing list. This helps you manage money flexibly with version control, automation, privacy, and no vendor lock-in, saving time on tracking expenses, assets, and budgets accurately.
https://github.com/beancount/beancount
#python#ai_researcher
AI-Researcher is a powerful tool that fully automates scientific research from start to finish. It can review literature, generate new research ideas, design and implement algorithms, validate results, and even write complete academic papers. You just provide research ideas or reference papers, and it handles the rest using advanced AI agents. This saves you time and effort by streamlining complex research tasks, helping you innovate faster without needing deep technical expertise. It supports multiple AI models, offers a user-friendly web interface, and includes a benchmark to evaluate research quality, making it an efficient assistant for accelerating scientific discovery.
https://github.com/HKUDS/AI-Researcher
https://github.com/google/python-fire
#Python#Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
Python Fire is a simple way to create a CLI in Python.
Python Fire is a helpful tool for developing and debugging Python code.
Python Fire helps with exploring existing code or turning other people's code into a CLI.
Python Fire makes transitioning between Bash and Python easier.
Python Fire makes using a Python REPL easier by setting up the REPL with the modules and variables you'll need already imported and created.
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Inside PythonistaCafe, you'll interact with professional developers and hobbyists from all over the world who will share their experiences in a safe setting—so you can learn from them and avoid the same mistakes they've made.
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