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Private Artifact Manager using Amazon S3

Project description

Private Artifact Manager using Amazon S3

PyPI version Build Status Coverage Status License 'Stories in Ready'

Features

  • Easy & lightweight artifact manager for Java/Scala

    • Especially optimized for all-in-one package (e.g. the result of sbt dist or sbt assembly)

  • No database or extra servers needed except Amazon S3

  • Quite simple command line interface (CLI)

  • Integrate your daily build & deploy tasks

Dependencies

  • Python >= 2.6

  • pytz

  • python-dateutil

  • GitPython >= 0.3.5

  • boto

  • moto (for testing)

Installation

Just install via pip! (may need sudo command):

pip install artifact-cli

Upgrading

pip install --upgrade artifact-cli
art --version

Quickstart Guide

1. Create your Amazon Web Services account (if need)

The responsibility of the AWS’s charge is your own.

2. Create IAM User to access Amazon S3 (if need)

Manage your own access key ID and secret access key to call the APIs.

3. Create Amazon S3 bucket

Set permissions to the IAM user.

4. Make configuration file

Create ~/.artifact-cli file and write credentials for AWS like this:

[default]
aws_access_key_id = XXXXXXXXXXXXXXXXXXXX
aws_secret_access_key = XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
bucket = your-bucket-name
region = your-region (e.g. ap-northeast-1, us-east-1)
Or you can use command line options instead of the configuration file.
(--access ACCESS_KEY --secret SECRET_KEY --bucket BUCKET_NAME --region REGION)

5. Check connection

Now, you are ready for using art command in the shell. Just list your artifacts:

$ art list GROUP_ID
[INFO] No artifacts.

Of course, there are no artifacts!

6. Build the artifact

Building is outside the reach of this tool. In other words, you can build as you like.

7. Upload the artifact

In the builder’s environment, you can upload the artifact to Amazon S3:

$ art upload GROUP_ID /path/to/your-artifact-0.0.1.jar

Specify group id and your local file path.

Artifact ID, version and packaging(=extension) are automatically parsed from the given file name.
In this case, artifact ID is your-artifact, version is 0.0.1 and packaging is jar.

8. View the artifact information

To view the index data, run art list or art info.

9. Download the artifact

Login to the deployer’s environment, then download the artifact from Amazon S3:

$ art download GROUP_ID /path/to/deployers/your-artifact-0.0.1.jar 1

To download the latest revision, use latest keyword. (case-sensitive):

$ art download GROUP_ID /path/to/deployers/your-artifact-0.0.1.jar latest

10. Deploy

Deploy the artifact any way you like!

11. And then …

For further information, type art -h.

Amazon S3 Paths

The structure of the paths is the following:

your-bucket-name
├── group.id.1                          // group ID
│   ├── .meta                           // meta data directory for each group
│   │   ├── index-awesome-project.json  // index data is written as JSON for each artifact ID
│   │   └── index-play-project.json
│   ├── awesome-project                 // artifact ID
│   │   ├── 0.0.1                       // version
│   │   │   ├── 1                       // revision (auto assigned, starting from 1)
|   │   │   │   └── awesome-project-0.0.1.jar
|   │   │   ├── 2
|   │   │   │   └── awesome-project-0.0.1.jar
|   │   │   ├── 3
|   │   │   │   └── awesome-project-0.0.1.jar
|   │   │   └── 4
|   │   │       └── awesome-project-0.0.1.jar
│   │   └── 0.0.2-SNAPSHOT
│   │       ├── 1
|   │       │   └── awesome-project-0.0.2-SNAPSHOT.jar
|   │       └── 2
|   │           └── awesome-project-0.0.2-SNAPSHOT.jar
│   └── play-project
│       └── 0.0.1
│           └── 1
|               └── play-project-0.0.1.zip
└── group.id.2
    ├── .meta
    │   └── index-awesome-project.json
    └── awesome-project                 // completely separated to the group.id.1's artifact
        └── 0.0.1
            └── 1
                └── awesome-project-0.0.1.zip

Notes

  • This tool supports only artifact-id-level concurrency.

    • Simultaneous uploading of the artifacts with same artifact id could let repository broken.

Uninstallation

pip uninstall artifact-cli

(may need sudo)

Project details


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artifact-cli-0.1.9.tar.gz (13.8 kB view hashes)

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