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https://github.com/iterative/example-repos-dev
Source code and generator scripts for example DVC projects
https://github.com/iterative/example-repos-dev
bash dvc example machine-learning open-source
Last synced: about 1 month ago
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Source code and generator scripts for example DVC projects
- Host: GitHub
- URL: https://github.com/iterative/example-repos-dev
- Owner: iterative
- Created: 2018-11-29T17:59:53.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2024-05-10T20:21:36.000Z (8 months ago)
- Last Synced: 2024-08-14T07:08:55.685Z (5 months ago)
- Topics: bash, dvc, example, machine-learning, open-source
- Language: Python
- Homepage: https://dvc.org/doc
- Size: 264 KB
- Stars: 21
- Watchers: 14
- Forks: 13
- Open Issues: 9
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- jimsghstars - iterative/example-repos-dev - Source code and generator scripts for example DVC projects (Python)
README
# Get Started Tutorial (sources)
Contains source code and [Shell](https://www.shellscript.sh/) scripts to
generate and deploy example DVC repositories used in the [Get
Started](https://dvc.org/doc/get-started) and other sections of the DVC docs.
## Requirements
Please make sure you have these available on the environment where these scripts
will run:
- [Git](https://git-scm.com/)
- [Python](https://www.python.org/) 3 (with `python3` and [pip](https://pypi.org/project/pip/) commands)
- [Virtualenv](https://virtualenv.pypa.io/en/stable/)
## Naming Convention for Example Repositories
In order to have a consistent naming scheme across all example repositories, the
new repositories should be named as:
```
example-PROD-FEATURE
```
where `PROD` is one of the products like `dvc`, `cml`, `studio`, or `dvclive`, and `FEATURE` is
the feature that the repository focused on, like `experiments`, or `pipelines`.
You can also use additional keywords as suffix to differentiate from the others.
⚠️ Please create all new repositories with the prefix `example-`.
## Scripts
Each example DVC project is in each of the root directories (below). `cd` into
the directory first before running the desired script, for example:
```console
$ cd example-get-started
$ ./deploy.sh
```
### example-get-started
There are 2 GitHub Actions set up to test and deploy the project:
- [test](.github/workflows/example-get-started-test.yaml)
- [deploy](.github/workflows/example-get-started-deploy.yaml)
These will automatically test and deploy the project. If you need to run the project
locally/manually, you only directly need `generate.sh`. `deploy.sh` is a helper script
run within `generate.sh`.
- `generate.sh`: Generates the `example-get-started` DVC project from
scratch.
By default, the source code archive is derived from the local workspace for
development purposes.
For deployment, use `generate.sh prod` to upload/download a source code
archive from S3 the same way as in [Connect Code and
Data](https://dvc.org/doc/get-started/connect-code-and-data).
- `deploy.sh`: Makes and deploys code archive from
[example-get-started/code](example-get-started/code) to use for `generate.sh`.
By default, makes local code archive in example-get-started/code.zip.
For deployment, use `deploy.sh prod` to upload to S3.
> Requires AWS CLI and write access to `s3://dvc-public/code/get-started/`.
### example-get-started-experiments
There are 2 GitHub Actions set up to test and deploy the project:
- [test](.github/workflows/example-get-started-experiments-test.yaml)
- [deploy](.github/workflows/example-get-started-experiments-deploy.yaml)
These will automatically test and deploy the project. If you need to run the project locally/manually, run `generate.sh`.
Even after automatic deployment, you still need to follow the
[instructions](example-get-started-experiments/README.md) to:
- Update Studio to create a PR from the best generated experiment.
- Push to GitLab if you want to update the repo there.