Data Biosphere Data Store Command Line Interface
This repository is a pip-installable command line interface (CLI) and Python library (API) for interacting with the Data Biosphere Data Storage System (DSS), also called the data store.
Currently the dbio package supports interaction with the data store for uploading, downloading, and fetching information about data in the data store.
The Data Biosphere CLI is compatible with Python versions 3.5+.
pip install dbio.
Documentation on readthedocs.io:
To see the list of commands you can use, type
The Data Biosphere CLI supports ingesting configuration from a configurable array of sources. Each source is a JSON file. Configuration sources that follow the first source update the configuration using recursive dictionary merging. Sources are enumerated in the following order (i.e., in order of increasing priority):
- Site-wide configuration source, /etc/dbio/config.json
- User configuration source, ~/.config/dbio/config.json
- Any sources listed in the colon-delimited variable DBIO_CONFIG_FILE
- Command line options
Array merge operators: When loading a chain of configuration sources, the Data Biosphere CLI uses recursive dictionary merging to combine the sources. Additionally, when the original config value is a list, the package supports array manipulation operators, which let you extend and modify arrays defined in underlying configurations. See https://github.com/kislyuk/tweak#array-merge-operators for a list of these operators.
To develop on the CLI, first run pip install -r requirements-dev.txt. You can install your locally modified copy of the dbio package by running make install in the repository root directory.
To use the command line interface with a local or test DSS, first run dbio (or scripts/dbio if you want to use the package in-place from the repository root directory). This will create the file ~/.config/dbio/config.json, which you can modify to update the value of DSSClient.swagger_url to point to the URL of the Swagger definition served by your DSS deployment. Lastly, the CLI enforces HTTPS connection to the DSS API. If you are connecting to a local DSS, make this change in dbio/util/__init__.py in the SwaggerClient object:
scheme = "http"
To use the Python interface with a local or test DSS, pass the URL of the Swagger definition to the DSSClient constructor via the swagger_url parameter:
client = DSSClient(swagger_url="https://dss.example.com/v1/swagger.json")
You can also layer a minimal config file on top of the default config.json using the DBIO_CONFIG_FILE environment variable, for example:
export SWAGGER_URL="https://dss.dev.ucsc-cgp-redwood.org/v1/swagger.json" jq -n .DSSClient.swagger_url=env.SWAGGER_URL > ~/.config/dbio/config.staging.json export DBIO_CONFIG_FILE=~/.config/dbio/config.staging.json
Before you run tests, first run dbio dss login. This will open a browser where you can log in to authenticate with Google. Use an email address from one of the whitelisted domains (in DSS_SUBSCRIPTION_AUTHORIZED_DOMAINS_ARRAY from here).
Primary CI testing is through Travis CI on the Gitlab toilspark instance.
Please report bugs, issues, feature requests, etc. in the HumanCellAtlas/dcp-cli repository on GitHub.
Please email reports about any security related issues you find to email@example.com. Use a descriptive subject line for your report email. In addition, please include the following information along with your report:
- Your name and affiliation (if any).
- A description of the technical details of the vulnerabilities, to help us reproduce your findings.
- An explanation of who can exploit this vulnerability, and what they gain when doing so (an attack scenario).
- Whether this vulnerability is public or known to third parties. If so, please provide details.
Licensed under the terms of the MIT License.
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