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Codecov
ByCodecovCodecov

Codecov

#1in Code Coverage
Discussions14
Followers324
OverviewDiscussions14

What is Codecov?

Our patrons rave about our elegant coverage reports, integrated pull request comments, interactive commit graphs, our Chrome plugin and security.

Codecov is a tool in the Code Coverage category of a tech stack.

Key Features

Beautiful ReportsPull Request CommentsInteractive Commit GraphsChrome ExtensionGithub Commit StatusEasy to IntegrateHipchat Integration

Codecov Pros & Cons

Pros of Codecov

  • ✓Easy setup
  • ✓More stable than coveralls
  • ✓GitHub integration
  • ✓They reply their users
  • ✓Easy setup,great ui
  • ✓Easily see per-commit coverage in GitHub
  • ✓Steve is the man
  • ✓Golang support
  • ✓Merges coverage from multiple CI jobs
  • ✓Code coverage

Cons of Codecov

  • ✗GitHub org / team integration is a little too tight
  • ✗Delayed results by hours since recent outage
  • ✗Support does not respond to email

Codecov Alternatives & Comparisons

What are some alternatives to Codecov?

Coveralls

Coveralls

Coveralls works with your CI server and sifts through your coverage data to find issues you didn't even know you had before they become a problem. Free for open source, pro accounts for private repos, instant sign up with GitHub OAuth.

Istanbul

Istanbul

It is a JS code coverage tool that computes statement, line, function and branch coverage with module loader hooks to transparently add coverage when running tests. Supports all JS coverage use cases including unit tests, server side functional tests and browser tests. Built for scale.

uberalls

uberalls

Code coverage metric storage service. Provide coverage metrics on differentials with Phabricator and Jenkins, just like Coveralls does for GitHub and TravisCI.

Codecov Integrations

HipChat, Jenkins, Bitbucket, GitLab, GitHub and 7 more are some of the popular tools that integrate with Codecov. Here's a list of all 12 tools that integrate with Codecov.

HipChat
HipChat
Jenkins
Jenkins
Bitbucket
Bitbucket
GitLab
GitLab
GitHub
GitHub
CircleCI
CircleCI
Heroku
Heroku
GNU Bash
GNU Bash
Bitrise
Bitrise
Sourcegraph
Sourcegraph
Codemagic
Codemagic
OpsLevel
OpsLevel

Codecov Discussions

Discover why developers choose Codecov. Read real-world technical decisions and stack choices from the StackShare community.Showing 4 of 5 discussions.

Tim Abbott
Tim Abbott

Founder at Zulip

May 16, 2019

Needs adviceonCodecovCodecovCoverallsCoveralls

We use Codecov because it's a lot better than Coveralls. Both of them provide the useful feature of having nice web-accessible reports of which files have what level of test coverage (though every coverage tool produces reasonably nice HTML in a directory on the local filesystem), and can report on PRs cases where significant new code was added without test coverage.

That said, I'm pretty unhappy with both of them for our use case. The fundamental problem with both of them is that they don't handle the ~1% probability situations with missing data due to networking flakiness well. The reason I think our use case is relevant is that we submit coverage data from multiple jobs (one that runs our frontend test suite and another that runs our backend test suite), and the coverage provider is responsible for combining that data together.

I think the problem is if a test suite runs successfully but due to some operational/networking error between Travis/CircleCI and Codecov the coverage data for part of the codebase doesn't get submitted, Codecov will report a huge coverage drop in a way that is very confusing for our contributors (because they experience it as "why did the coverage drop 12%, all I did was added a test").

We migrated from Coveralls to Codecov because empirically this sort of breakage happened 10x less on Codecov, but it still happens way more often than I'd like.

I wish they put more effort in their retry mechanism and/or providing clearer debugging information (E.g. a big "Missing data" banner) so that one didn't need to be specifically told to ignore Codecov/Coveralls when it reports a giant coverage drop.

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David Antonini
David Antonini

May 6, 2019

Needs adviceonCodecovCodecovCoverallsCoveralls

Codecov Although I actually use both codecov and Coveralls, I very much like the graphs I get from codecov, and some of their diagnostic tools.

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Stef Heyenrath
Stef Heyenrath

Mar 16, 2019

Needs adviceonCodecovCodecov

I use Codecov because it's easy to integrate in Github PullRequests which enables a grpahical view from the code coverage.

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Eli Hooten
Eli Hooten

CTO at Codecov

Nov 30, 2018

Needs adviceonVue.jsVue.jsPythonPythonvuexvuex

We chose Vue.js at Codecov to replace a front end that was based mostly on server side rendered Python templates, and was getting fairly long in the tooth. The move to Vue.js allowed us to take a more component driven approach to our front end, providing greater flexibility and reuse when creating new pages and refactoring old ones. Another bonus was how easily we could integrate Axios with VueJS for making AJAX calls within Vue.js components and their associated vuex stores. We were also able to easily integrate Vue.js with the Jest testing framework, which allowed to provide test coverage for a front end where none previously existed.

The move to Vue.js has allowed us to be more agile in our front end development by further decoupling our front end from our back end. Additionally, by fully embracing a component-driven approach, we're able to more easily isolate and test functionality, leading to a more readible, maintainable, and extensible front end codebase.

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