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pydap

An implementation of the Opendap/DODS protocol, written from scratch in pure Python, that allows researchers to access NASA Earth science data from a variety of programs.
https://github.com/pydap/pydap

Category: Sustainable Development
Sub Category: Data Catalogs and Interfaces

Keywords

dap data dods opendap science

Keywords from Contributors

climate weather oceanography compression pangeo data-access geospatial-data data-catalog climate-model climate-science

Last synced: about 21 hours ago
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Repository metadata

A Python library implementing the Data Access Protocol (DAP, aka OPeNDAP).

README.md

pydap

CI
Python
PyPI
PyPI - Downloads
conda-forge
conda-forge Downloads
black
license
pre-commit.ci status
DOI

What is pydap?

pydap is an open-source implementation of the OPeNDAP protocol, written from scratch in pure Python. You can use pydap to access scientific data available on the many OPeNDAP servers publicly-available through the internet. Because pydap supports remote and lazy evaluation, you can access the data without having to download it; Instead, you work with special array and iterable objects that download data on-the-fly as necessary, saving bandwidth and time. The module also comes with a robust-but-lightweight OPeNDAP server, implemented as a WSGI application.

Why pydap?

Originally developed in the 2000s, pydap is one of the oldest open-source Python projects available and is routinely developed and maintained by the OPeNDAP community at large. In addition, pydap is a long-recognized backend engine (and dependency) for xarray and chances are you have used pydap in the past without knowing it.

Quickstart

pydap is a lightweight python package that you can use in either of the two modalities: a client and as a server. You can install the latest version using pip. After installing pip you can install pydap with this command:

    $ pip install pydap

This will install pydap together with all the required dependencies.

pydap is also available through Anaconda. Below we install pydap and its required dependencies, along with common additional packages in a fresh conda environment named "pydap":

    $ conda create -n pydap -c conda-forge python=3.12 pydap numpy jupyterlab ipython netCDF4 scipy matplotlib

Now you simply activate the pydap environment:

    $ conda activate pydap

[!NOTE]
If you have mamba installed, you can replace conda in the commands with mamba.

You can now use pydap as a client and open any remotely served dataset, and pydap will download the accessed data on-the-fly as needed. For example consider this dataset currently hosted on OPeNDAP's Hyrax data server

    from pydap.client import open_url
    pyds = open_url('http://test.opendap.org:8080/opendap/catalog/ghrsst/20210102090000-JPL-L4_GHRSST-SSTfnd-MUR-GLOB-v02.0-fv04.1.nc', protocol='dap4')
    pyds.tree()

    .20210102090000-JPL-L4_GHRSST-SSTfnd-MUR-GLOB-v02.0-fv04.1.nc
    ├──time
    ├──lat
    ├──lon
    ├──analysed_sst
    ├──analysis_error
    ├──mask
    ├──sea_ice_fraction
    ├──dt_1km_data
    └──sst_anomaly

    pyds['sst_anomaly'].shape

    (1, 17999, 36000)

[!NOTE]
In the example above, no data was downloaded, it was all lazily evaluated using OPeNDAP's DMR (DAP4) metadata representation. For more information, please check the documentation on using pydap as a client.

pydap also comes with a simple server, implemented as a WSGI application. To use it, you first need to install the server and optionally a data handler:

Running pydap as a Server

    $ pip install "pydap[server,netcdf]"

This will install the necessary dependencies for running pydap as a server, along with extra dependencies for handling netCDF4 dataset. Now create a directory for your server data.

To run the server just issue the command:

    $ pydap --data ./myserver/data/ --port 8001 --workers 4 --threads 4

This will start a standalone server running on the default http://localhost:8001/, serving netCDF files from ./myserver/data/ Since the server uses the WSGI standard, pydap uses by default one (1) worker and one (1) thread, but these can be defined by the user like in the case above (four (4) workers and four (4) threads). pydap can also easily be run behind Apache.

The server documentation has more information on how to better deploy pydap.

Documentation

For more information, see the pydap documentation.

Help and Community

If you need any help with pydap, open an issue in this repository. You can also email the mailing list.

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Last synced: 2 days ago

Total Commits: 796
Total Committers: 43
Avg Commits per committer: 18.512
Development Distribution Score (DDS): 0.715

Commits in past year: 84
Committers in past year: 7
Avg Commits per committer in past year: 12.0
Development Distribution Score (DDS) in past year: 0.214

Name Email Commits
Roberto De Almeida r****o@d****t 227
Miguel Jimenez m****z@o****g 198
Frederic Laliberte l****c@g****m 185
James Hiebert j****s@h****e 56
Edward Hartnett E****t@n****v 24
pre-commit-ci[bot] 6****] 19
dependabot[bot] 4****] 11
Tom Kralidis t****s@g****m 11
ocefpaf o****f@g****m 9
Ghislain Antony Vaillant g****l 8
Owen Littlejohns o****s@n****v 7
James Gallagher j****r@o****g 3
Juan Luis Cano Rodríguez j****1@g****m 3
Ray Bell r****0@g****m 2
Michael Bunsen n****t@g****m 2
Lewis John McGibbney l****y@g****m 2
Christian Skarby c****y@m****o 2
Daniel Gray d****n@t****m 2
Aaron Kaplan a****n 1
Aleksandar Jelenak a****k@h****g 1
Amanda Yoshiizumi m****i@g****m 1
nathanlcarlson 2****n 1
kikocorreoso k****o 1
epifanio e****a@m****m 1
anthonybaxter a****r@g****m 1
Will Holmgren w****n@g****m 1
Trevor James Smith 1****e 1
Tobias Kölling t****i@d****e 1
Stephan Hoyer s****r@g****m 1
SiggyF f****t@g****m 1
and 13 more...

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Issue and Pull Request metadata

Last synced: 2 days ago

Total issues: 220
Total pull requests: 327
Average time to close issues: 4 months
Average time to close pull requests: 2 months
Total issue authors: 47
Total pull request authors: 26
Average comments per issue: 1.39
Average comments per pull request: 0.83
Merged pull request: 259
Bot issues: 0
Bot pull requests: 31

Past year issues: 15
Past year pull requests: 32
Past year average time to close issues: 18 days
Past year average time to close pull requests: 1 day
Past year issue authors: 1
Past year pull request authors: 6
Past year average comments per issue: 0.6
Past year average comments per pull request: 0.19
Past year merged pull request: 27
Past year bot issues: 0
Past year bot pull requests: 7

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/pydap/pydap

Top Issue Authors

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Package metadata

pypi.org: pydap

A pure python implementation of the Data Access Protocol.

  • Homepage:
  • Documentation: https://pydap.readthedocs.io/
  • Licenses: MIT License
  • Latest release: 3.5.11 (published about 2 months ago)
  • Last Synced: 2026-11-06T08:07:00.284Z (2 days ago)
  • Versions: 56
  • Dependent Packages: 18
  • Dependent Repositories: 57
  • Downloads: 185,877 Last month
  • Docker Downloads: 970
  • Rankings:
    • Dependent packages count: 0.752%
    • Downloads: 1.746%
    • Average: 1.76%
    • Dependent repos count: 1.965%
    • Docker downloads count: 2.577%
  • Maintainers (5)
proxy.golang.org: github.com/pydap/pydap

  • Homepage:
  • Status: removed
  • Documentation: https://pkg.go.dev/github.com/pydap/pydap#section-documentation
  • Licenses: mit
  • Latest release: v0.0.0-20260819001352-81f431d0a6c0 (published 3 months ago)
  • Last Synced: 2026-11-05T16:41:12.581Z (3 days ago)
  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Rankings:
    • Dependent packages count: 4.262%
    • Average: 4.408%
    • Dependent repos count: 4.553%
conda-forge.org: pydap

  • Homepage: https://pydap.github.io/pydap/intro.html
  • Licenses: MIT
  • Latest release: 3.3.0 (published almost 5 years ago)
  • Last Synced: 2026-04-01T03:22:24.433Z (7 months ago)
  • Versions: 5
  • Dependent Packages: 9
  • Dependent Repositories: 54
  • Rankings:
    • Dependent repos count: 4.831%
    • Average: 5.639%
    • Dependent packages count: 6.447%
guix: python-pydap

Data Access Protocol implementation in Python

Dependencies

setup.py pypi
  • Jinja2 *
  • Webob *
  • beautifulsoup4 *
  • docopt *
  • numpy *
  • requests *
  • six *
.github/workflows/publish_to_pypi.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • pypa/gh-action-pypi-publish release/v1 composite
pyproject.toml pypi
  • Jinja2 *
  • Webob *
  • beautifulsoup4 *
  • docopt-ng *
  • numpy *
  • requests *
ci/environment.yml conda
  • docopt-ng
  • netcdf4
  • pip
docs/environment.yml conda
  • cartopy
  • dask
  • earthaccess
  • jupyter-book <2.0
  • jupyterlab
  • matplotlib
  • netcdf4
  • pip
  • python 3.12
  • virtualizarr
  • xarray
.github/workflows/ci.yml actions
  • actions/checkout v7 composite
  • mamba-org/setup-micromamba v3 composite

Score: 21.320577620199465