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Description

The Code Climate CLI is distributed and run as a Docker image. The engines that perform the actual analyses are also Docker images. To support this, you must have Docker installed and running locally. We also require that the Docker daemon supports connections on the default Unix socket /var/run/docker.sock.

On OS X, we recommend using Docker Machine.

Code Quality Rank: L5
Monthly Downloads: 1,218
Programming language: Ruby
License: AGPL
Tags: Code Analysis    
Latest version: v0.85.9

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README

Code Climate CLI

Code Climate CircleCI

Overview

codeclimate is a command line interface for the Code Climate analysis platform. It allows you to run Code Climate engines on your local machine inside of Docker containers.

Prerequisites

The Code Climate CLI is distributed and run as a Docker image. The engines that perform the actual analyses are also Docker images. To support this, you must have Docker installed and running locally. We also require that the Docker daemon supports connections on the default Unix socket /var/run/docker.sock.

On macOS, we recommend using Docker for Mac.

Installation

macOS

brew tap codeclimate/formulae
brew install codeclimate

To update the brew package, use brew update first:

brew update
brew upgrade codeclimate

Anywhere

curl -L https://github.com/codeclimate/codeclimate/archive/master.tar.gz | tar xvz
cd codeclimate-* && sudo make install

To upgrade to a newer version, just run those steps again.

Manual Docker invocation

The above packages pull the docker image and install a shell script wrapper. In some cases you may want to run the docker image directly.

To pull the docker image:

docker pull codeclimate/codeclimate

To invoke the CLI via Docker:

docker run \
  --interactive --tty --rm \
  --env CODECLIMATE_CODE="$PWD" \
  --volume "$PWD":/code \
  --volume /var/run/docker.sock:/var/run/docker.sock \
  --volume /tmp/cc:/tmp/cc \
  codeclimate/codeclimate help

Project setup

Configuration

No explicit configuration is needed: by default codeclimate analyze will evaluate supported source files in your repository using our maintainability checks. To change default configuration to customize how the maintainability checks are evaluated, or to turn on open source plugins, see our documentation on advanced configuration.

Plugin installation

Plugins, or "engines", are the docker images that run analysis tools. We support many different plugins, and will only install the ones necessary to run analysis. As part of setting up your project, we recommend running codeclimate engines:install from within your repository before running codeclimate analyze, and after adding any new plugins to your configuration file.

Running analysis

Once you've installed plugins and made any necessary changes to your configuration, run codeclimate analyze to run analysis and see a report on any issues in your repository.

Commands

A list of available commands is accessible by running codeclimate or codeclimate help.

$ codeclimate help

Available commands:
    analyze [-f format] [-e engine[:channel]] [--dev] [path]
    console
    engines:install
    engines:list
    help [command]
    prepare [--allow-internal-ips]
    validate-config
    version

The following is a brief explanation of each available command.

  • analyze Analyze all relevant files in the current working directory. All engines that are enabled in your .codeclimate.yml file will run, one after another. The -f (or format) argument allows you to set the output format of the analysis (using json, text, or html). The --dev flag lets you run engines not known to the CLI, for example if you're an engine author developing your own, unreleased image.

You can optionally provide a specific path to analyze. If not provided, the CLI will analyze your entire repository, except for your configured exclude_paths. When you do provide an explicit path to analyze, your configured exclude_paths are ignored, and normally excluded files will be analyzed.

You can also pipe in source in combination with a path to analyze code that is not yet written to disk. This is useful when you want to check if your source code style matches the project's. This is also a good way to implement integration with an editor to check style on the fly.

  • console start an interactive session providing access to the classes within the CLI. Useful for engine developers and maintainers.
  • engines:install Compares the list of engines in your .codeclimate.yml file to those that are currently installed, then installs any missing engines.
  • engines:list Lists all available engines in the Code Climate Docker Hub .
  • help Displays a list of commands that can be passed to the Code Climate CLI.
  • validate-config Validates the .codeclimate.yml file in the current working directory.
  • version Displays the current version of the Code Climate CLI.

Environment Variables

  • To run codeclimate in debug mode:
  CODECLIMATE_DEBUG=1 codeclimate analyze

Prints additional information about the analysis steps, including any stderr produced by engines.

  • To increase the amount of time each engine container may run (default 15 min):
  # 30 minutes
  CONTAINER_TIMEOUT_SECONDS=1800 codeclimate analyze
  • You can also configure the default alotted memory with which each engine runs (default is 1,024,000,000 bytes):
  # 2,000,000,000 bytes
  ENGINE_MEMORY_LIMIT_BYTES=2000000000 codeclimate analyze

See [LICENSE](LICENSE)


*Note that all licence references and agreements mentioned in the Code Climate README section above are relevant to that project's source code only.