Use Codacy and Codecov instead of Coveralls

FRosner / drunken-data-quality

Spark package for checking data quality

Apache License 2.0

222 stars 69 forks source link

Use Codacy and Codecov instead of Coveralls #60

Closed FRosner closed 8 years ago

FRosner commented 8 years ago

[x] setup codacy https://www.codacy.com/app/frank_7/drunken-data-quality
[x] setup codecov https://github.com/codecov/example-scala
[x] replace coveralls badge by codacy and codecov badge
[x] remove coveralls project
[x] check GitHub integration

JoshRosen commented 8 years ago

I'd also consider https://codecov.io/ for code coverage; I'm using it with Databricks' spark-redshift library.

FRosner commented 8 years ago

@JoshRosen thanks for the recommendation. It will look into it. How does it compare to the coverage from codacy? Which one would you recommend?

JoshRosen commented 8 years ago

@FRosner, for me the big differentiator is Codecov's browser plugin for displaying coverage metrics inline in the GitHub UI. For instance, this screenshot shows inline coverage / line hit numbers displayed on a PR:

Similarly, the browser plugin can display coverage metrics in the GitHub file browser:

And when browsing code:

Codacy has some nice features, but for pure code-coverage I think Codecov wins in my book.

FRosner commented 8 years ago

Cool! Thanks @JoshRosen. I will go for codecov then.