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Explore idiomatic Python coding practices to write more elegant and efficient code, regardless of skill level. Learn forgotten vanilla features and refactor a function using Pythonic idioms.
Explore advantages and challenges of static typing in Python, including type hints, tools, and future implications for the language and its programmers.
Learn to build efficient GraphQL APIs in Django using Graphene. Explore ObjectTypes, Queries, Mutations, and pagination while understanding the advantages over REST APIs.
Strategies for transitioning large Python projects to version 3, focusing on process management, team coordination, and overcoming common challenges in legacy codebases.
Explore Python's grammar, parser, and design decisions. Learn how language features are implemented, limitations overcome, and new rules added, gaining deeper insight into Python's simplicity and power.
Explore real-world AsyncIO experiences in Python, including successes, challenges, and best use cases. Learn when to embrace or avoid this powerful concurrency approach.
Explore combining Go and Python: learn to create Python extension modules using Go, covering data sharing, callbacks, and garbage collection. Discover the advantages of this powerful combination.
Explore modern deployment techniques for Python, focusing on avoiding vendor lock-in and creating flexible, future-proof setups for seamless transitions between cloud platforms.
Explore Python programming on the International Space Station with Astro Pi, a collaboration between Raspberry Pi Foundation and ESA, offering exciting opportunities for students to conduct space experiments.
Explore Python's parallel computing landscape, from low-level interfaces to high-level libraries, and learn about recent advances in shared memory management and object serialization.
Explore the transition from HTTP to Kafka-based microservices, discussing challenges, solutions, and benefits of asynchronous communication in Python-based systems.
Explore modern Python dependency management using pyproject.toml, comparing tools like Poetry, Hatch, and Pipenv. Learn to simplify project setup and ensure reliable, repeatable installations.
Discover techniques to optimize Docker builds for Python apps, focusing on speeding up the process and reducing image size for both development and production environments.
Discover lesser-known Python Standard Library modules and functions, exploring practical examples and recipes to enhance your coding skills and leverage built-in solutions for common tasks.
Discover the workflow and tools for building, deploying, and operating GraphQL APIs on Kubernetes. Learn from Numberly's transition experience and gain insights into cluster design and developer processes.
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