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Explore testing doubles in Python: mocks, fakes, dummies, stubs, and spies. Learn their differences, use cases, and implementation techniques for effective unit testing and dependency isolation.
Learn to implement Command Query Responsibility Segregation (CQRS) in Python using Nameko framework to enhance database performance and scalability in high-traffic applications.
Learn to build scalable, distributed machine learning data pipelines using Airflow with Celery backend. Gain insights on industry challenges, comparisons with other technologies, and practical knowledge for implementation.
Learn modern JavaScript from a Python developer's perspective, covering language basics, development tools, popular frameworks, and new features like TypeScript. Gain confidence in using JavaScript and its ecosystem.
Learn techniques for creating environment-agnostic Python applications that are easier to test, deploy, handle, and scale. Discover tools and best practices for structuring and configuring apps independent of their runtime environment.
Explore how LSTM neural networks and Python can generate AI-driven test inputs for software testing and network security, improving upon traditional fuzzing techniques.
Discover tox: an open-source tool for standardizing Python testing, simplifying CI processes, and ensuring high-quality, maintainable packages across various environments.
Explore 8 Python web frameworks in a whirlwind tour, comparing microframeworks, "batteries included" options, and async frameworks. Broaden your horizons with practical examples and Jules Verne-inspired fun.
Learn effective Django testing strategies to improve development speed and maintain project quality. Covers unit testing, mocking, project structure, and other testing methods.
Exploración profunda del módulo dataclasses de Python 3.7, comparándolo con alternativas existentes y analizando su diseño, propósito y beneficios para los desarrolladores.
A journey through a decade of EuroPython conferences, exploring the evolution of Python, its community, and the event itself, with insights and aspirations for the future.
Explore Python's iteration protocol, from basic loops to creating custom iterables and iterators, enhancing your understanding of this fundamental concept for more efficient coding.
Practical strategies for implementing type annotations in large Python codebases, addressing challenges, best practices, and solutions for common roadblocks encountered during the process.
Optimize complex Django queries by moving selection logic, calculations, and aggregations to the database, improving performance and maintainability of your web applications.
Learn how to introduce type checking in Python projects using mypy, with insights from Dropbox's experience in annotating large codebases. Discover step-by-step approaches to improve code clarity and catch bugs early.
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