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https://github.com/codacy/codacy-metrics-example-tool
Docker engine example for a codacy metrics tool
https://github.com/codacy/codacy-metrics-example-tool
codacy codacy-tool docker engine example metrics tool
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Docker engine example for a codacy metrics tool
- Host: GitHub
- URL: https://github.com/codacy/codacy-metrics-example-tool
- Owner: codacy
- License: apache-2.0
- Created: 2019-12-04T16:55:24.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2022-02-11T10:47:56.000Z (almost 3 years ago)
- Last Synced: 2023-03-30T08:40:05.722Z (over 1 year ago)
- Topics: codacy, codacy-tool, docker, engine, example, metrics, tool
- Language: Shell
- Size: 34.2 KB
- Stars: 0
- Watchers: 13
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Codeowners: .github/CODEOWNERS
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README
# Codacy Metrics Example Tool
Docker engine example for a codacy metrics tool
## Documentation
### How to integrate an external metrics tool on Codacy
By creating a docker and writing code to handle the tool invocation and output,
you can integrate the tool of your choice on Codacy!
> To know more about dockers, and how to write a docker file please refer to
> [https://docs.docker.com/reference/builder/](https://docs.docker.com/reference/builder/)
In this tutorial, we explain how you can integrate a metrics tool of your choice
in Codacy. You can check the code of an already implemented tool and if you wish
fork it to start your own. You are free to modify and use it for your own tools.
### Structure
* To run the tool we provide the configuration file, `/.codacyrc`, with the
language to run and optional parameters your tool might need.
* The source code to be analysed will be located in `/src`, meaning that when
provided in the configuration, the file paths are relative to `/src`.
#### Structure of `.codacyrc` file
* **files:** Files to be analysed (their path is relative to `/src`)
* **language:** Language to run the tool
Check the schema [here](schemas/codacyrc_schema.json).
```json
{
"files" : [ "foo/bar/baz.scala", "foo2/bar/baz.scala" ],
"language": "Scala"
}
```
##### General tool behavior
**Exit codes**:
* The exit codes can be different, depending if the tool invocation is
successful or not:
* **0**: The tool executed successfully :tada:
* **1**: An unknown error occurred while running the tool :cold_sweat:
* **2**: Execution timeout :alarm_clock:
**Environment variables**:
* To run the tool in debug mode, so you can have more detailed logs, you need to
set the environment variable `DEBUG` to `true` when invoking the docker.
* To configure a different timeout for the tool, you have to set the environment
variable `TIMEOUT_SECONDS` when you run the docker image, setting it with values
like `10` or `1800` (30 minutes).
#### Output
You are free to write the code running inside the docker in the language you
prefer. After you have your results from the tool, you should print them to the
standard output in our **Result** format ([schema](schemas/output_schema.json)), one result per line. Example:
```json
{
"filename": "path/to/my/file1.scala",
"complexity": 1,
"loc": 300,
"cloc": 320,
"nrMethods": 20,
"nrClasses": 2,
"lineComplexities": [
{
"line": 2,
"value": 3
}
]
}
```
> The filename should not include the prefix `/src/`, the absolute path
> `/src/folder/file.js` should be returned as `folder/file.js`.
#### Submit the Docker
**Running the docker**:
```bash
docker run -t \
--net=none \
--privileged=false \
--cap-drop=ALL \
--user=docker \
--rm=true \
-v :/src:ro \
-v :/.codacyrc:ro \
:
```
**Docker restrictions**:
* Docker image size should not exceed 500MB
* Docker should contain a non-root user named docker with UID/GID 2004
* All the source code of the docker must be public
* The docker base must officially be supported on DockerHub
* Your docker must be provided in a repository through a public git host (ex:
GitHub, Bitbucket, ...)
**Docker submission**:
* To submit the docker you should send an email to [email protected] with the
link to the git repository with your docker definition.
* The docker will then be subjected to a review by our team and we will then
contact you with more details.
#### Test
Follow the instructions at
[codacy-plugins-test](https://github.com/codacy/codacy-plugins-test/blob/master/README.md#test-definition).
If you have any question or suggestion regarding this guide please contact us at
[email protected].
## What is Codacy
[Codacy](https://www.codacy.com/) is an Automated Code Review Tool that monitors
your technical debt, helps you improve your code quality, teaches best practices
to your developers, and helps you save time in Code Reviews.
### Among Codacy’s features
* Identify new Static Analysis issues
* Commit and Pull Request Analysis with GitHub, BitBucket/Stash, GitLab (and
also direct git repositories)
* Auto-comments on Commits and Pull Requests
* Integrations with Slack, HipChat, Jira, YouTrack
* Track issues in Code Style, Security, Error Proneness, Performance, Unused
Code and other categories
Codacy also helps keep track of Code Coverage, Code Duplication, and Code
Complexity.
Codacy supports PHP, Python, Ruby, Java, JavaScript, and Scala, among others.
### Free for Open Source
Codacy is free for Open Source projects.