Software Alternatives, Accelerators & Startups

PyFlakes VS Azkaban

Compare PyFlakes VS Azkaban and see what are their differences

PyFlakes logo PyFlakes

A simple program which checks Python source files for errors.

Azkaban logo Azkaban

Azkaban is a batch workflow job scheduler created at LinkedIn to run Hadoop jobs.
  • PyFlakes Landing page
    Landing page //
    2023-10-11
  • Azkaban Landing page
    Landing page //
    2019-08-01

PyFlakes videos

replay - pyflakes string format linting - 2019-04-03

Azkaban videos

Harry Potter and the Prisoner of Azkaban - Movie Review

More videos:

  • Review - Harry Potter and the Prisoner of Azkaban - Movie Review
  • Review - Harry Potter and The Prisoner of Azkaban

Category Popularity

0-100% (relative to PyFlakes and Azkaban)
Code Coverage
100 100%
0% 0
Workflow Automation
0 0%
100% 100
Code Analysis
100 100%
0% 0
DevOps Tools
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Azkaban seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

PyFlakes mentions (0)

We have not tracked any mentions of PyFlakes yet. Tracking of PyFlakes recommendations started around Mar 2021.

Azkaban mentions (3)

What are some alternatives?

When comparing PyFlakes and Azkaban, you can also consider the following products

PyLint - Pylint is a Python source code analyzer which looks for programming errors.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

flake8 - A wrapper around Python tools to check the style and quality of Python code.

Luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs.

PEP8 - pep8 is a tool to check your Python code against some of the style conventions in PEP 8.

Metaflow - Framework for real-life data science; build, improve, and operate end-to-end workflows.