mypy VS Apache Airflow

mypy Reviews

Apache Airflow Reviews

mypy mentions (49)

• Moving your bugs forward in time

  ‍I’m not here to tell people which languages they should love. But if you do find yourself writing production code in a dynamically typed language like Python, Ruby, or JavaScript, I would give serious consideration to opting into the type-checking tools that have become available in those ecosystems. In Python, consider requiring type hints and adding mypy checks to your CI to move your type safety bugs forward... - Source: dev.to / 8 days ago

• Embracing Modern Python for Web Development

  Mypy is "an optional static type checker for Python that aims to combine the benefits of dynamic (or "duck") typing and static typing". As Python is dynamically typed, Mypy adds an extra layer of safety by checking types at compile time (based on type annotations conforming to PEP 484), catching potential errors before runtime. - Source: dev.to / 6 months ago

• A Tale of Two Kitchens - Hypermodernizing Your Python Code Base

  Mypy stands as an essential static type-checking tool. Its primary function is to verify the correctness of types in your codebase. However, manually annotating types in legacy code can be laborious and time-consuming. - Source: dev.to / 7 months ago

• Lua: The Little Language That Could

  Lua is a great language for embedding, but one thing I wish it had was some form of optional type annotations that could be checked by a linter. Something like mypy for Lua would be super-useful. Source: 12 months ago

• Please critique my Collatz conjecture code

  Python is a dynamically typed language (unlike C or java which are statically typed) meaning that there's no enforcement on the type. This var ; type syntax is called Type Hints, and they are just that, merely hints. So they serve as a reminder to developers of what types of variables a function should receive and output, but they implement no real restrictions. So if you try to pass a string to collatz for... Source: about 1 year ago

Apache Airflow mentions (66)

• AI Strategy Guide: How to Scale AI Across Your Business

  Level 1 of MLOps is when you've put each lifecycle stage and their intefaces in an automated pipeline. The pipeline could be a python or bash script, or it could be a directed acyclic graph run by some orchestration framework like Airflow, dagster or one of the cloud-provider offerings. AI- or data-specific platforms like MLflow, ClearML and dvc also feature pipeline capabilities. - Source: dev.to / 5 days ago

• The 2024 Web Hosting Report

  For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules. - Source: dev.to / 3 months ago

• Best ETL Tools And Why To Choose

  Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows. Source: 6 months ago

• Simplifying Data Transformation in Redshift: An Approach with DBT and Airflow

  Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring. - Source: dev.to / 6 months ago

• Share Your favorite python related software!

  AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic! Source: 8 months ago