scikit-dataaccess

Scikit Data Access

Import scientific data from various sources through one easy Python API.
Use iterator patterns for each data source (configurable data generators + functions to get next data chunk).
Skip parser programming and file format handling.
Enjoy a common namespace for all data and unleash the power of data fusion.
Handle data distribution in different modes: (1) local download, (2) caching of accessed data, or (3) online stream access
Easily pull data on cloud servers through Python scripts and facilitate large-scale parallel processing.
Build on an extensible plattform: Adding access to a new data source only requires addition of its "DataFetcher.py".
Open source (MIT License)

Scikit Data Access Overview

Supported data sets:

	Namespace	Preview ^(link)	Description & Data Source
^Astronomy
	^astro.kepler		^{Light curves for stars imaged by the NASA Kepler Space Telescope Source: https://keplerscience.arc.nasa.gov}
	^{astro.spectra}		^{Spectra from the Sloan Digital Sky Survey Source: https://www.sdss.org/dr14/spectro/}
	^{astro.tess.data}		^{Light curves from TESS Data Alerts Source: https://archive.stsci.edu/prepds/tess-data-alerts/}
	^{astro.tess.simulated}		^{Simulated light curves from TESS End-to-End 6 Source: https://archive.stsci.edu/prepds/tess-data-alerts/}
	^{astro.voyager}		^{Data from the Voyager mission. Source: https://spdf.gsfc.nasa.gov/}
^Engineering
	^{engineering.la.traffic_counts}		^{Traffic Count data in Los Angeles. Source: https://data.lacity.org/A-Livable-and-Sustainable-City/LADOT-Traffic-Counts-Summary/94wu-3ps3}
	^{engineering.webcam.mit_sailing}		^{Images from webcams located at the MIT Sailing Pavilion Source: http://sailing.mit.edu/webcam.php}
^Finance
	^{finance.timeseries}		^{Financial time series data retrieved using Alpha Vantage API. Source: https://www.alphavantage.co/}
^Geoscience
	^{geo.era_interim}		^{Era-Interim data at different pressure values from the European Centre for Medium-Range Weather Forecasts accessed through the University Corporation for Atmospheric Research. Source: https://rda.ucar.edu/datasets/ds627.0/}
	^geo.gldas		^{Land hydrology model produced by NASA. This version of the data is generated to match the GRACE temporal and spatial characteristics and is available as a complementary data product. Source: https://grace.jpl.nasa.gov/data/get-data/land-water-content}
	^geo.grace		^{NASA GRACE Tellus Monthly Mass Grids. 30-day measurements of changes in Earth’s gravity field to quantify equivalent water thickness. Source: https://grace.jpl.nasa.gov/data/get-data/monthly-mass-grids-land}
	^{geo.grace.mascon}		^{NASA GRACE Tellus Monthly Mass Grids - Global Mascons. 30-day measurements of changes in Earth’s gravity field to quantify equivalent water thickness. Source: https://grace.jpl.nasa.gov/data/get-data/jpl_global_mascons}
	^{geo.groundwater}		^{United States groundwater monitoring wells measuring the depth to water level. Source: https://waterservices.usgs.gov}
	^{geo.magnetometer}		^{Data collected at magnetic observatories operated by the U.S. Geological Survey. Source: https://geomag.usgs.gov}
	^{geo.mahali.rinex}		^{Rinex files from the MIT led NSF project studying the Earth’s ionosphere with GPS. Web: http://mahali.mit.edu}
	^{geo.mahali.tec}		^{Total Electron Content from the MIT led NSF project studying the Earth’s ionosphere with GPS. Web:http://mahali.mit.edu}
	^{geo.mahali.temperature}		^{Temperature data from the MIT led NSF project studying the Earth’s ionosphere with GPS. Web: http://mahali.mit.edu}
	^geo.modis		^{Spectroradiometer aboard the NASA Terra and Aqua image satellites. Generates approximately daily images of the Earth’s surface. Source:https://modis.gsfc.nasa.gov}
	^geo.pbo		^{EarthScope - Plate Boundary Observatory (PBO): Daily GPS displacement time series measurements throughout the United States. Source: http://www.unavco.org/projects/major-projects/pbo/pbo.html}
	^{geo.sentinel_1}		^{Sentinel-1 TOPSAR data from the European Space Agency retrieved from the Alaska Satellite Facility. Source:https://www.asf.alaska.edu/}
	^geo.srtm		^{Elevation data at a one arc second resolution from the Shuttle Radar Topography Mission (SRTMGL1). Source: https://lpdaac.usgs.gov/dataset_discovery/measures/measures_products_table/srtmgl1_v003}
	^geo.uavsar		^{UAVSAR SLC data from JPL. Source: https://uavsar.jpl.nasa.gov/}
	^{geo.wyoming_sounding}		^{Sounding data from the University of Wyoming. Source: http://weather.uwyo.edu/upperair/sounding.html}
^{Planetary Science}
	^{planetary.ode}		^{Mars planetary data from PDS Geosciences Node's Orbital Data Explorer. Source: http://pds-geosciences.wustl.edu/default.htm}
^{Solar Science}
	^solar.sdo		^{Images from the Solar Dynamics Observatory. Source: https://sdo.gsfc.nasa.gov/}

Install

pip install scikit-dataaccess

Documentation

User Manual: /docs/skdaccess_manual.pdf
Code documentation (Doxygen): /docs/skdaccess_doxygen.pdf
Code visualization (treemap): /docs/skdaccess_treemap.png
Code class diagrams: /docs/class_diagrams

Contributors

Project lead: Victor Pankratius (MIT)
Contributors: Cody M. Rude, Justin D. Li, David M. Blair, Michael G. Gowanlock, Guillaume Rongier, Victor Pankratius

New contributors welcome! Contact to contribute and add interface code for your own datasets 😄

Acknowledgements

We acknowledge support from NASA AIST14-NNX15AG84G, NASA AIST16-80NSSC17K0125, NSF ACI-1442997, and NSF AGS-1343967.

Examples

Code examples (Jupyter notebooks) for all datasets listed above are available at: /skdaccess/examples

Metadata

Release files for scikit-dataaccess 1.9.17.post2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for scikit-dataaccess 1.9.17.post2
File	Size	Uploaded
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Release files / scikit-dataaccess-1.9.17.post2.tar.gz

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