pyDataverse
pyDataverse is a Python module for Dataverse. It helps to access the Dataverse API's and manipulate, validate, import and export all Dataverse data-types (Dataverse, Dataset, Datafile).
Find out more: Read the Docs
Running tests
In order to run the tests, you need to have a Dataverse instance running. We have prepared a shell script that will start a Dataverse instance using Docker that runs all tests in a clean environment. To run the tests, execute the following command:
# Defaults to Python 3.11
./run_tests.sh
# To run the tests with a specific Python version
./run_tests.sh -p 3.8
Once finished, you can find the test results in the dv/unit-tests.log file and in the terminal.
Manual setup
If you want to run single tests you need to manually set up the environment and set up the necessary environment variables. Please follow the instructions below.
1. Start the Dataverse instance
docker compose \
-f ./docker/docker-compose-base.yml \
--env-file local-test.env \
up -d
2. Set up the environment variables
export BASE_URL=http://localhost:8080
export DV_VERSION=6.2 # or any other version
export $(grep "API_TOKEN" "dv/bootstrap.exposed.env")
export API_TOKEN_SUPERUSER=$API_TOKEN
3. Run the test(s) with pytest
python -m pytest -v
Chat with us!
If you are interested in the development of pyDataverse, we invite you to join us for a chat on our Zulip Channel. This is the perfect place to discuss and exchange ideas about the development of pyDataverse. Whether you need help or have ideas to share, feel free to join us!
PyDataverse Working Group
We have formed a pyDataverse working group to exchange ideas and collaborate on pyDataverse. There is a bi-weekly meeting planned for this purpose, and you are welcome to join us by clicking the following WebEx meeting link. For a list of all the scheduled dates, please refer to the Dataverse Community calendar.
Metadata
Release files for pyDataverse 0.3.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| pydataverse-0.3.5.tar.gz | 86.6 kB | Without provenance | Details for pydataverse-0.3.5.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| pydataverse-0.3.5-py3-none-any.whl | Python 3 | none | any | Details for pydataverse-0.3.5-py3-none-any.whl |
Total release size: 182.2 kB
Release files / pydataverse-0.3.5.tar.gz
| Download URL | pydataverse-0.3.5.tar.gz |
|---|---|
| Size | 86.6 kB |
| Tags | Source |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.1.4 CPython/3.11.0 Linux/6.11.0-1018-azure
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Release files / pydataverse-0.3.5-py3-none-any.whl
| Download URL | pydataverse-0.3.5-py3-none-any.whl |
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| Size | 95.6 kB |
| Tags | Python 3 |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/2.1.4 CPython/3.11.0 Linux/6.11.0-1018-azure
|
Security for pyDataverse 0.3.5
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
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To learn more about protecting yourself from malicious actors, visit our package security documentation.