# deep-code
[](https://github.com/deepesdl/deep-code/actions/workflows/unittest-workflow.yaml)
[](https://codecov.io/gh/deepesdl/deep-code)
[](https://github.com/psf/black)
[](https://github.com/deepesdl/deep-code/blob/main/LICENSE)
`deep-code` is a lightweight python tool that comprises a command line interface(CLI)
and Python API providing utilities that aid integration of DeepESDL datasets,
experiments with EarthCODE.
The first release will focus on implementing the publish feature of DeepESDL
experiments/workflow as OGC API record and Datasets as an OSC stac collection.
## Setup
## Install
`deep-code` will be available in PyPI for now and will be available in conda-forge
in the near future. Till the stable release,
developers/contributors can follow the below steps to install deep-code.
## Installing from the repository for Developers/Contributors
To install deep-code directly from the git repository, clone the repository, and execute the steps below:
```commandline
conda env create
conda activate deep-code
pip install -e .
```
This installs all the dependencies of `deep-code` into a fresh conda environment,
and installs deep-code from the repository into the same environment.
## Testing
To run the unit test suite:
```commandline
pytest
```
To analyze test coverage
```shell
pytest --cov=deep-code
```
To produce an HTML coverage report
```commandline
pytest --cov-report html --cov=deep-code
```
## deep_code usage
`deep_code` provides a command-line tool called deep-code, which has several subcommands
providing different utility functions.
Use the --help option with these subcommands to get more details on usage.
The CLI retrieves the Git username and personal access token from a hidden file named
.gitaccess. Ensure this file is located in the same directory where you execute the CLI
command.
#### .gitaccess example
```
github-username: your-git-user
github-token: personal access token
```
### deep-code generate-config
Generates starter configuration templates for publishing to EarthCODE openscience
catalog.
#### Usage
```
deep-code generate-config [OPTIONS]
```
#### Options
--output-dir, -o : Output directory (default: current)
#### Examples:
```
deep-code generate-config
deep-code generate-config -o ./configs
```
### deep-code publish
Publishes metadata of experiment, workflow and dataset to the EarthCODE open-science
catalog
### Usage
```
deep-code publish DATASET_CONFIG WORKFLOW_CONFIG [--environment ENVIRONMENT]
```
#### Arguments
DATASET_CONFIG - Path to the dataset configuration YAML file
(e.g., dataset-config.yaml)
WORKFLOW_CONFIG - Path to the workflow configuration YAML file
(e.g., workflow-config.yaml)
#### Options
--environment, -e - Target catalog environment:
production (default) | staging | testing
#### Examples:
1. Publish to staging catalog
```
deep-code publish dataset-config.yaml workflow-config.yaml --environment=staging
```
2. Publish to testing catalog
```
deep-code publish dataset-config.yaml workflow-config.yaml -e testing
```
3. Publish to production catalog
```
deep-code publish dataset-config.yaml workflow-config.yaml
```
#### dataset-config.yaml example
```
dataset_id: esa-cci-permafrost-1x1151x1641-1.0.0.zarr
collection_id: esa-cci-permafrost
osc_themes:
- cryosphere
osc_region: global
# non-mandatory
documentation_link: https://deepesdl.readthedocs.io/en/latest/datasets/esa-cci-permafrost-1x1151x1641-0-0-2-zarr
access_link: s3://deep-esdl-public/esa-cci-permafrost-1x1151x1641-1.0.0.zarr
dataset_status: completed
```
dataset-id has to be a valid dataset-id from `deep-esdl-public` s3 bucket or your team
bucket.
#### workflow-config.yaml example
```
workflow_id: "esa-cci-permafrost"
properties:
title: "ESA CCI permafrost"
description: "cube generation workflow for esa-cci-permafrost"
keywords:
- Earth Science
themes:
- cryosphere
license: proprietary
jupyter_kernel_info:
name: deepesdl-xcube-1.8.3
python_version: 3.11
env_file: "https://github.com/deepesdl/cube-gen/blob/main/Permafrost/environment.yml"
jupyter_notebook_url: "https://github.com/deepesdl/cube-gen/blob/main/Permafrost/Create-CCI-Permafrost-cube-EarthCODE.ipynb"
contact:
- name: Tejas Morbagal Harish
organization: Brockmann Consult GmbH
links:
- rel: "about"
type: "text/html"
href: "https://www.brockmann-consult.de/"
```
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"description": "# deep-code\n\n[](https://github.com/deepesdl/deep-code/actions/workflows/unittest-workflow.yaml)\n[](https://codecov.io/gh/deepesdl/deep-code)\n[](https://github.com/psf/black)\n[](https://github.com/deepesdl/deep-code/blob/main/LICENSE)\n\n`deep-code` is a lightweight python tool that comprises a command line interface(CLI) \nand Python API providing utilities that aid integration of DeepESDL datasets, \nexperiments with EarthCODE.\n\nThe first release will focus on implementing the publish feature of DeepESDL \nexperiments/workflow as OGC API record and Datasets as an OSC stac collection.\n\n## Setup\n\n## Install\n`deep-code` will be available in PyPI for now and will be available in conda-forge \nin the near future. Till the stable release,\ndevelopers/contributors can follow the below steps to install deep-code.\n\n## Installing from the repository for Developers/Contributors\n\nTo install deep-code directly from the git repository, clone the repository, and execute the steps below:\n\n```commandline\nconda env create\nconda activate deep-code\npip install -e .\n```\n\nThis installs all the dependencies of `deep-code` into a fresh conda environment, \nand installs deep-code from the repository into the same environment.\n\n## Testing\n\nTo run the unit test suite:\n\n```commandline\npytest\n```\n\nTo analyze test coverage\n```shell\npytest --cov=deep-code\n```\n\nTo produce an HTML coverage report\n\n```commandline\npytest --cov-report html --cov=deep-code\n```\n\n## deep_code usage\n\n`deep_code` provides a command-line tool called deep-code, which has several subcommands \nproviding different utility functions.\nUse the --help option with these subcommands to get more details on usage.\n\nThe CLI retrieves the Git username and personal access token from a hidden file named \n.gitaccess. Ensure this file is located in the same directory where you execute the CLI\ncommand.\n\n#### .gitaccess example\n\n```\ngithub-username: your-git-user\ngithub-token: personal access token\n```\n### deep-code generate-config\n\nGenerates starter configuration templates for publishing to EarthCODE openscience \ncatalog.\n\n#### Usage\n```\ndeep-code generate-config [OPTIONS]\n```\n\n#### Options\n --output-dir, -o : Output directory (default: current)\n\n#### Examples:\n```\ndeep-code generate-config\ndeep-code generate-config -o ./configs\n```\n\n### deep-code publish\n\nPublishes metadata of experiment, workflow and dataset to the EarthCODE open-science \ncatalog\n\n### Usage\n```\ndeep-code publish DATASET_CONFIG WORKFLOW_CONFIG [--environment ENVIRONMENT]\n ```\n\n#### Arguments\n DATASET_CONFIG - Path to the dataset configuration YAML file\n (e.g., dataset-config.yaml)\n\n WORKFLOW_CONFIG - Path to the workflow configuration YAML file\n (e.g., workflow-config.yaml)\n\n#### Options\n --environment, -e - Target catalog environment:\n production (default) | staging | testing\n\n#### Examples:\n1. Publish to staging catalog\n```\ndeep-code publish dataset-config.yaml workflow-config.yaml --environment=staging\n```\n2. Publish to testing catalog\n```\ndeep-code publish dataset-config.yaml workflow-config.yaml -e testing\n```\n3. Publish to production catalog\n```\ndeep-code publish dataset-config.yaml workflow-config.yaml\n```\n#### dataset-config.yaml example\n\n```\ndataset_id: esa-cci-permafrost-1x1151x1641-1.0.0.zarr\ncollection_id: esa-cci-permafrost\nosc_themes:\n - cryosphere\nosc_region: global\n# non-mandatory\ndocumentation_link: https://deepesdl.readthedocs.io/en/latest/datasets/esa-cci-permafrost-1x1151x1641-0-0-2-zarr\naccess_link: s3://deep-esdl-public/esa-cci-permafrost-1x1151x1641-1.0.0.zarr\ndataset_status: completed\n```\n\ndataset-id has to be a valid dataset-id from `deep-esdl-public` s3 bucket or your team \nbucket.\n\n#### workflow-config.yaml example\n\n```\nworkflow_id: \"esa-cci-permafrost\"\nproperties:\n title: \"ESA CCI permafrost\"\n description: \"cube generation workflow for esa-cci-permafrost\"\n keywords:\n - Earth Science\n themes:\n - cryosphere\n license: proprietary\n jupyter_kernel_info:\n name: deepesdl-xcube-1.8.3\n python_version: 3.11\n env_file: \"https://github.com/deepesdl/cube-gen/blob/main/Permafrost/environment.yml\"\njupyter_notebook_url: \"https://github.com/deepesdl/cube-gen/blob/main/Permafrost/Create-CCI-Permafrost-cube-EarthCODE.ipynb\"\ncontact:\n - name: Tejas Morbagal Harish\n organization: Brockmann Consult GmbH\n links:\n - rel: \"about\"\n type: \"text/html\"\n href: \"https://www.brockmann-consult.de/\"\n```\n",
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