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datacustodian-1.2.1


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توضیحات

Generalized data privacy and consent repository generator.
ویژگی مقدار
سیستم عامل -
نام فایل datacustodian-1.2.1
نام datacustodian
نسخه کتابخانه 1.2.1
نگهدارنده []
ایمیل نگهدارنده []
نویسنده ClearFoundation
ایمیل نویسنده developer@clearfoundation.com
آدرس صفحه اصلی https://gitlab.com/clearos/clearfoundation/datacustodian
آدرس اینترنتی https://pypi.org/project/datacustodian/
مجوز GPL-3.0
[![pipeline status](https://gitlab.com/clearos/clearfoundation/datacustodian/badges/master/pipeline.svg)](https://gitlab.com/clearos/clearfoundation/datacustodian/commits/master) [![coverage report](https://gitlab.com/clearos/clearfoundation/datacustodian/badges/master/coverage.svg)](https://gitlab.com/clearos/clearfoundation/datacustodian/commits/master) # `DataCustodian` Data Privacy Package Generator `DataCustodian` generates other repositories for generalized data privacy and consent systems. The generation follows YML specification files that define the endpoints, handlers, authentication, validation, etc. for each component of a data privacy solution. `DataCustodian` is built to work with decentralized and distributed systems to provide decentralized trust for storage and consent of data. Check out the [API Documentation](https://clearos.gitlab.io/clearfoundation/datacustodian) and a [real-world implementation](https://gitlab.com/clearos/clearfoundation/clearshare). ## Installation The package is available from the PyPI repository: ```bash pip install datacustodian ``` ## Generating a Package Look at the documentation in `docs/configs` for an example setup that we use for the unit tests. Customize that to your own application and then run: ```bash datacustodian_app.py path/to/your/app_spec.yml --generate ``` That will auto-generate the package *and* start the REST API server. ## Running Unit Tests Running unit tests can prove to be a massive pain because the gitlab CI runner runs on docker. For a project like this that uses `docker-compose`, we have to use `docker-in-docker` according to their instructions. However, the documentation is sparse and there are lots of dead-ends... Here are the steps to get the `docker-compose.yml` file to work: 1. Install a local `gitlab-runner` using `brew install gitlab-runner`. 2. `gitlab-runner exec docker --docker-privileged test`. Notice that there is a `--docker-privileged` argument. Without that, the `docker-in-docker` won't work. 3. Make sure all the `multiaddr` reference the `docker` service (which hosts all the other containers using `dind`). 4. `tox` should work, but for some reason: running the tests using `tox` produces connection refused errors, whereas running straight with `pytest` does not. Something about the tox environment screws things up. ## Problems with `coverage` For an yet-unknown reason, when the unit tests run in the CI server using: 1. Only `pytest`, they pass with no issues. 2. `coverage run` with `pytest`, we get problems with connection reset errors, and connection refused errors. Insead of trying to figure this out now, we just do the following: 1. Before pushing to the remote server, run `coverage` locally (which has no problems on MacOS). 2. Generate the `coverage report -m > codecov.out`. 3. Commit `codecov.out` and then push. The CI server *only* runs `pytest`, but it also `cat codecov.out` so that the output includes the regular code coverage matrix. That way, `gitlab` still has correct statistics about code coverage.


نیازمندی

مقدار نام
- argparse
- pyparsing
- termcolor
- tqdm
- jinja2
- flask
- flask-restful
- flask-restplus
- pyyaml
- attrdict
>=0.2.0 ipfscluster
- didauth
- aiohttp
- cloudant
- pynacl
- fido2


نحوه نصب


نصب پکیج whl datacustodian-1.2.1:

    pip install datacustodian-1.2.1.whl


نصب پکیج tar.gz datacustodian-1.2.1:

    pip install datacustodian-1.2.1.tar.gz