Python wrapper for the NASA API
Python wrapper for the nasa.gov API.
nasapy is most easily installed using
pip install nasapy
The library can also be cloned or downloaded into a location of your choosing and then installed using the
file per the following:
git clone firstname.lastname@example.org:aschleg/nasapy.git cd nasapy python setup.py install
- Python 3.4+
- Although not strictly required to use
nasapy, the pandas library is needed for returning results as a DataFrame.
- Although not strictly required to use
Tutorials and In-Depth Examples
The following are articles that explore a facet of the
nasapy library in more depth.
- Plot Earth Fireball Impacts with nasapy, pandas and folium
- Analyzing the Next Decade of Earth Close-Approaching Objects with nasapy
- Get All NASA Astronomy Pictures of the Day from 2019
Examples and Usage
Although not strictly required to begin interacting with the NASA API, it is recommended to sign up to receive an API access key that has a significantly higher usage limit available compared to the demo key option. Many methods do not require an API key, but for those that do, it is typically a good option to use a provided API key rather than the demo key. Using a received API key allows for 1,000 requests per hour, while the demo key has 30 requests limit per hour and 50 requests per day.
Assuming an API key was received after signing up, authentication to the NASA API happens when initializing the
nasa = Nasa(key=key)
If using a demo key, the initialization does not require any parameters to be passed.
nasa = Nasa()
Remaining Requests Available
limit_remaining attribute of the initialized
Nasa class allows one to see the number of available requests
The following are some quick examples to get started.
Astronomy Picture of the Day
# Return today's picture of the day nasa.picture_of_the_day() # Return a previous date's picture of the day with the high-definition URL included. nasa.picture_of_the_day('2019-01-01', hd=True)
# Return the most recent data for the previous seven Sols (Martian Days) nasa.mars_weather()
# Get asteroids approaching Earth at the beginning of 2019. nasa.asteroid_feed(start_date='2019-01-01')
Get Asteroid Data
# Get entire asteroid data set. nasa.get_asteroids() # Get asteroid with ID 3542519 nasa.get_asteroids(asteroid_id=3542519)
DONKI (Space Weather Database of Notifications, Knowledge and Information)
# Coronal Mass Ejection Event Data # View data from coronal mass ejection events from the last thirty days nasa.coronal_mass_ejection() # View all CME events from the beginning of 2019. nasa.coronal_mass_ejection(start_date='2019-01-01', end_date=datetime.datetime.today()) # Geomagnetic Storm Event Data # Get geomagnetic storm events from the last thirty days. nasa.geomagnetic_storm() # Solar Flare Event Data # Get solar flare events from May of 2019 nasa.solar_flare(start_date='2019-05-01', end_date='2019-05-31') # Solar Energetic Particle Data # Get data from April 2017 nasa.solar_energetic_particle(start_date='2017-04-01', end_date='2017-04-30') # Magnetopause Crossing Data # Get data on magnetopause crossing events from 2018 to the current date. nasa.magnetopause_crossing(start_date='2018-01-01') # Radiation Belt Enhancement Data # Get data on radiation belt enhancement events from the last 30 days. nasa.radiation_belt_enhancement() # Hight Speed Stream Data # Get data on hight speed stream events from the beginning of September 2019. nasa.hight_speed_stream() # WSA Enlil-Simulation Data # Get data from the first simulation performed in 2019. wsa = n.wsa_enlil_simulation(start_date='2019-01-01') wsa
EPIC (DSCOVR's Earth Polychromatic Imaging Camera)
# Get EPIC data from the beginning of 2019. e = nasa.epic(date='2019-01-01') # Print the first result e
# Get all exoplanets data as a pandas DataFrame. exoplanets(return_df=True) # Get all confirmed planets in the Kepler field. exoplanets(where='pl_kepflag=1') # Stars known to host exoplanets as a pandas DataFrame. exoplanets(select='distinct pl_hostname', order='pl_hostname', return_df=True)
Landsat Images for a given Latitude-Longitude
# Get imagery at latitude 1.5, longitude 100.75 and include the computed cloud score calculation. nasa.earth_imagery(lon=100.75, lat=1.5, cloud_score=True) # Get assets available beginning from 2014-02-01 at lat-lon 100.75, 1.5 nasa.earth_assets(lat=100.75, lon=1.5, begin_date='2014-02-01')
Available Image data collected by the Mars rovers Curiosity, Discovery and Spirit.
# Return image data collected on Curiosity's 1000th sol. nasa.mars_rover(sol=1000)
Access GeneLab and Other Bioinformatics Databases
# Find Gene studies in the cgene database related to 'mouse liver' n.genelab_search(term='mouse liver')
The following functions do not require authentication with an API or demo key.
CelesTrak Two-Line Element Set Records
# Retrieve available data for a specific satellite ID. tle(satellite_number=43553)
Search for Available Imagery and Audio from the images.nasa.gov API
# Search for media related to 'apollo 11' with 'moon landing' in the description of the items. r = media_search(query='apollo 11', description='moon landing') # Print the first returned media item from the resulting collection. r['items']
Asteroid and Comet Close Approaches to planets in the past and future
# Get all close-approach object data in the year 2019 with a maximum approach distance of 0.01AU. close_approach(date_min='2019-01-01', date_max='2019-12-31', dist_max=0.01) # Get close-approach data for asteroid 433 Eros within 0.2AU from the years 1900 to 2100. close_approach(des='433', date_min='1900-01-01', date_max='2100-01-01', dist_max=0.2) # Return close-approach data from the beginning of 2000 to the beginning of 2020 as a pandas DataFrame. close_approach(date_min='2000-01-01', date_max='2020-01-01', return_df=True)
Fireball atmospheric impact data reported by US Government sensors
# Get all available data in reverse chronological order n = fireballs() # Return the earlieset record fireballs(limit=1) # Get data from the beginning of 2019 fireballs(date_min='2019-01-01') # Return fireball data from the beginning of the millennium to the beginning of 2020 as a pandas DataFrame. fireballs(date_min='2000-01-01', date_max='2020-01-01', return_df=True)
Jet Propulsion Laboratory/Solar System Dynamics small body mission design suite API
# Search for mission design data for SPK-ID 2000433 r = mission_design(spk=2000433) # Print the object data from the returned dictionary object. r['object']
Get Data on Near-Earth Object Human Space Flight Accessible Targets
# Get all available summary data for NHATS objects. n = nhats() # Get summary data as a pandas DataFrame n = nhats(return_df=True) # Get the results from a 'standard' search on the NHATS webpage. nhats(delta_v=6, duration=360, stay=8, magnitude=26, launch='2020-2045', orbit_condition_code=7) # Return data for a specific object by its designation nhats(des=99942)
Get Data from NASA's Center for Near-Earth Object Studies (CNEOS) Scout system
# Get all available summary data. scout() # Return all summary data as a pandas DataFrame. scout(return_df=True) # Return data and plot files for a specific object by its temporary designation. Note the object may no longer # exist in the current database scout(tdes='P20UvyK') # Get ephemeris data for a specific object at the current time with a Field of View diameter of 5 arc-minutes # with a limiting V-magnitude of 23.1. scout(tdes='P20UvyK', fov_diam=5, fov_vmag=23.1)
Get Data from the Center for Near Earth Object Studies (CNEOS) Sentry system
# Get summary data for available sentry objects. sentry() # Get summary data as a pandas DataFrame sentry(return_df=True) # Get data for a specific Sentry object by its designation. sentry(des=99942) # Get data for objects removed from the Sentry system. sentry(removed=1)
Other function examples
Getting the Julian and Modified Julian Date
# Return the modified Julian Date for the current time. julian_date() # Return the non-modified Julian Date for the current time. julian_date(modified=False) # Get the modified Julian Date for 2019-01-01 at midnight. julian_date(year=2019)
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