dataretrieval-python
A Python alternative to USGS-R's dataRetrieval package for obtaining USGS or EPA water quality data, streamflow data, and metadata directly from web services.
https://github.com/DOI-USGS/dataretrieval-python
Category: Natural Resources
Sub Category: Water Supply and Quality
Keywords from Contributors
hydrology usgs water ow modflow prms
Last synced: about 2 hours ago
JSON representation
Repository metadata
Python package for retrieving water data from USGS or the multi-agency Water Quality Portal
- Host: GitHub
- URL: https://github.com/DOI-USGS/dataretrieval-python
- Owner: DOI-USGS
- License: other
- Created: 2018-09-27T14:05:26.000Z (over 6 years ago)
- Default Branch: main
- Last Pushed: 2024-10-25T17:37:02.000Z (6 months ago)
- Last Synced: 2025-04-11T23:57:07.799Z (16 days ago)
- Language: Python
- Homepage: https://doi-usgs.github.io/dataretrieval-python/
- Size: 14.9 MB
- Stars: 180
- Watchers: 10
- Forks: 44
- Open Issues: 31
- Releases: 15
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
README.md
dataretrieval: Download hydrologic data
⚠️ USGS data availability and format are changing on Water Quality Portal (WQP). Since March 2024, data obtained from WQP legacy profiles will not include new USGS data or recent updates to existing data.
To view the status of changes in data availability and code functionality, visit: https://doi-usgs.github.io/dataRetrieval/articles/Status.html
📣 09/03/2024: The groundwater levels service has switched endpoints, and dataretrieval
was updated accordingly in v1.0.10
. Older versions using the discontinued endpoint will return 503 errors for nwis.get_gwlevels
or the service='gwlevels'
argument. Visit Water Data For the Nation for more information.
What is dataretrieval?
dataretrieval
was created to simplify the process of loading hydrologic data into the Python environment.
Like the original R version dataRetrieval
,
it is designed to retrieve the major data types of U.S. Geological Survey (USGS) hydrology
data that are available on the Web, as well as data from the Water
Quality Portal (WQP), which currently houses water quality data from the
Environmental Protection Agency (EPA), U.S. Department of Agriculture
(USDA), and USGS. Direct USGS data is obtained from a service called the
National Water Information System (NWIS).
Note that the python version is not a direct port of the original: it attempts to reproduce the functionality of the R package,
though its organization and interface often differ.
If there's a hydrologic or environmental data portal that you'd like dataretrieval to
work with, raise it as an issue.
Here's an example using dataretrieval
to retrieve data from the National Water Information System (NWIS).
# first import the functions for downloading data from NWIS
import dataretrieval.nwis as nwis
# specify the USGS site code for which we want data.
site = '03339000'
# get instantaneous values (iv)
df = nwis.get_record(sites=site, service='iv', start='2017-12-31', end='2018-01-01')
# get water quality samples (qwdata)
df2 = nwis.get_record(sites=site, service='qwdata', start='2017-12-31', end='2018-01-01')
# get basic info about the site
df3 = nwis.get_record(sites=site, service='site')
Services available from NWIS include:
- instantaneous values (iv)
- daily values (dv)
- statistics (stat)
- site info (site)
- discharge peaks (peaks)
- discharge measurements (measurements)
- water quality samples (qwdata)
To access the full functionality available from NWIS web services, nwis.get record appends any additional kwargs into the REST request. For example
nwis.get_record(sites='03339000', service='dv', start='2017-12-31', parameterCd='00060')
will download daily data with the parameter code 00060 (discharge).
Accessing the "Internal" NWIS
If you're connected to the USGS network, dataretrieval call pull from the internal (non-public) NWIS interface.
Most dataretrieval functions pass kwargs directly to NWIS's REST API, which provides simple access to internal data; simply specify "access='3'".
For example
nwis.get_record(sites='05404147',service='iv', start='2021-01-01', end='2021-3-01', access='3')
More services and documentation to come!
Quick start
dataretrieval can be installed using pip:
$ python3 -m pip install -U dataretrieval
or conda:
$ conda install -c conda-forge dataretrieval
More examples of use are include in demos
.
Issue tracker
Please report any bugs and enhancement ideas using the dataretrieval issue
tracker:
https://github.com/USGS-python/dataretrieval/issues
Feel free to also ask questions on the tracker.
Contributing
Any help in testing, development, documentation and other tasks is welcome.
For more details, see the file CONTRIBUTING.md.
Package Support
The Water Mission Area of the USGS supports the development and maintenance of dataretrieval
and most likely further into the future.
Resources are available primarily for maintenance and responding to user questions.
Priorities on the development of new features are determined by the dataretrieval
development team.
Acknowledgments
This material is partially based upon work supported by the National Science Foundation (NSF) under award 1931297.
Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.
Disclaimer
This software is preliminary or provisional and is subject to revision.
It is being provided to meet the need for timely best science.
The software has not received final approval by the U.S. Geological Survey (USGS).
No warranty, expressed or implied, is made by the USGS or the U.S. Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty.
The software is provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the software.
Citation
Hodson, T.O., Hariharan, J.A., Black, S., and Horsburgh, J.S., 2023, dataretrieval (Python): a Python package for discovering
and retrieving water data available from U.S. federal hydrologic web services:
U.S. Geological Survey software release,
https://doi.org/10.5066/P94I5TX3.
Owner metadata
- Name: U.S. Geological Survey
- Login: DOI-USGS
- Email: [email protected]
- Kind: organization
- Description: By integrating our diverse scientific expertise, we understand complex natural science phenomena and provide scientific products that lead to solutions.
- Website: https://www.usgs.gov/
- Location: United States of America
- Twitter: USGS
- Company:
- Icon url: https://avatars.githubusercontent.com/u/65027635?v=4
- Repositories: 59
- Last ynced at: 2023-06-11T08:40:17.441Z
- Profile URL: https://github.com/DOI-USGS
GitHub Events
Total
- Create event: 1
- Issues event: 3
- Release event: 1
- Watch event: 20
- Issue comment event: 19
- Push event: 4
- Pull request review comment event: 5
- Pull request review event: 9
- Pull request event: 5
- Fork event: 9
Last Year
- Create event: 1
- Issues event: 3
- Release event: 1
- Watch event: 20
- Issue comment event: 19
- Push event: 4
- Pull request review comment event: 5
- Pull request review event: 9
- Pull request event: 5
- Fork event: 9
Committers metadata
Last synced: 7 days ago
Total Commits: 131
Total Committers: 21
Avg Commits per committer: 6.238
Development Distribution Score (DDS): 0.489
Commits in past year: 31
Committers in past year: 11
Avg Commits per committer in past year: 2.818
Development Distribution Score (DDS) in past year: 0.677
Name | Commits | |
---|---|---|
Timothy Hodson | 3****s | 67 |
J. Hariharan | j****n@u****v | 22 |
Scott Black | s****k@u****u | 8 |
Elise Hinman | 1****n | 6 |
Pabitra Dash | p****a@h****m | 5 |
Joseph Stachelek | j****a | 4 |
Elise Hinman | e****n@u****v | 2 |
Ibrahim El Merehbi | e****i | 2 |
Doug Dennis | d****r@g****m | 2 |
Joshua Larsen | j****n@u****v | 2 |
Camilo J. Bastidas Pacheco | c****s@g****m | 1 |
Dave Tapley | d****e@t****m | 1 |
David Blodgett | d****t@u****v | 1 |
Edwin | 3****c | 1 |
Justin Bousquin | j****n@y****m | 1 |
Keith Doore | 5****e | 1 |
Lee Stanish | 8****s | 1 |
mnfienen | m****n@u****v | 1 |
Austin Raney | a****y@n****v | 1 |
Joe Zemmels (he/him) | j****s@g****m | 1 |
MLR | m****1@g****m | 1 |
Committer domains:
- usgs.gov: 5
- noaa.gov: 1
- tapley.com: 1
- usu.edu: 1
Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 96
Total pull requests: 86
Average time to close issues: 3 months
Average time to close pull requests: 12 days
Total issue authors: 48
Total pull request authors: 20
Average comments per issue: 2.13
Average comments per pull request: 1.72
Merged pull request: 74
Bot issues: 0
Bot pull requests: 0
Past year issues: 18
Past year pull requests: 27
Past year average time to close issues: 17 days
Past year average time to close pull requests: 5 days
Past year issue authors: 10
Past year pull request authors: 8
Past year average comments per issue: 1.5
Past year average comments per pull request: 2.44
Past year merged pull request: 22
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- thodson-usgs (15)
- ehinman (8)
- lstanish-usgs (7)
- davetapley (6)
- SorooshMani-NOAA (5)
- elbeejay (5)
- putmanannie (4)
- jnmitchell-USGS (2)
- pkdash (2)
- jpouliot10 (2)
- andrewrfrench (2)
- jsta (2)
- jreniel (1)
- oconnelljon (1)
- hwreeves-USGS (1)
Top Pull Request Authors
- elbeejay (21)
- thodson-usgs (20)
- ehinman (9)
- jsta (5)
- pkdash (5)
- sblack-usu (4)
- elmerehbi (3)
- jlarsen-usgs (3)
- cjbas22 (3)
- dblodgett-usgs (2)
- edsaac (2)
- lstanish-usgs (1)
- jbousquin (1)
- aaraney (1)
- kjdoore (1)
Top Issue Labels
- enhancement (7)
- bug (6)
- question (4)
- documentation (4)
Top Pull Request Labels
- bug (6)
- enhancement (2)
- documentation (2)
Package metadata
- Total packages: 1
-
Total downloads:
- pypi: 5,990 last-month
- Total dependent packages: 8
- Total dependent repositories: 11
- Total versions: 18
- Total maintainers: 2
pypi.org: dataretrieval
Discover and retrieve water data from U.S. federal hydrologic web services.
- Homepage:
- Documentation: https://dataretrieval.readthedocs.io/
- Licenses: License ======= Unless otherwise noted, this project is in the public domain in the United States because it contains materials that originally came from the United States Geological Survey, an agency of the United States Department of Interior. For more information, see the official USGS copyright policy at https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits Additionally, we waive copyright and related rights in the work worldwide through the CC0 1.0 Universal public domain dedication. CC0 1.0 Universal Summary ------------------------- This is a human-readable summary of the [Legal Code (read the full text)][1]. ### No Copyright The person who associated a work with this deed has dedicated the work to the public domain by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. ### Other Information In no way are the patent or trademark rights of any person affected by CC0, nor are the rights that other persons may have in the work or in how the work is used, such as publicity or privacy rights. Unless expressly stated otherwise, the person who associated a work with this deed makes no warranties about the work, and disclaims liability for all uses of the work, to the fullest extent permitted by applicable law. When using or citing the work, you should not imply endorsement by the author or the affirmer. [1]: https://creativecommons.org/publicdomain/zero/1.0/legalcode
- Latest release: 1.0.11 (published 6 months ago)
- Last Synced: 2025-04-26T14:35:50.329Z (1 day ago)
- Versions: 18
- Dependent Packages: 8
- Dependent Repositories: 11
- Downloads: 5,990 Last month
-
Rankings:
- Dependent packages count: 1.865%
- Average: 3.454%
- Downloads: 4.125%
- Dependent repos count: 4.373%
- Maintainers (2)
Dependencies
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Score: 17.09772697423865