How to Build an ETL App for NASA Data in Python with CData

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python and the petl framework, you can build NASA-connected applications and pipelines for extracting, transforming, and loading NASA data. This article shows how to connect to NASA with the CData Python Connector and use petl and pandas to extract, transform, and load NASA data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live NASA data in Python. When you issue complex SQL queries from NASA, the driver pushes supported SQL operations, like filters and aggregations, directly to NASA and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to NASA Data

Connecting to NASA data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Using API Key Authentication

Most NASA API endpoints (APOD, NeoWS, DONKI, TechTransfer) require a NASA API key. Register for a free key at https://api.nasa.gov. The default DEMO_KEY provides limited access (30 requests/hour, 50 requests/day); a registered key allows 1,000 requests/hour.

The following endpoints do not require an API key and work without authentication: EONET (Earth Observatory Natural Event Tracker), EPIC (Earth Polychromatic Imaging Camera), NASA Image and Video Library, and TechPort.

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your NASA API key. Use DEMO_KEY for limited testing.

Example Connection String

Profile=C:\profiles\NASA.apip;AuthScheme=APIKey;APIKey=YOUR_NASA_API_KEY

Connecting to NASA

Once the authentication is configured, you can connect to NASA and query data from any of the available tables such as AstronomyPictureOfDay, NearEarthObjectFeed, EonetEvents, and NasaImageLibrary.

After installing the CData NASA Connector, follow the procedure below to install the other required modules and start accessing NASA through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install petl
pip install pandas

Build an ETL App for NASA Data in Python

Once the required modules and frameworks are installed, we are ready to build our ETL app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import petl as etl
import pandas as pd
import cdata.api as mod

You can now connect with a connection string. Use the connect function for the CData NASA Connector to create a connection for working with NASA data.

cnxn = mod.connect("Profile=C:\profiles\NASA.apip;AuthScheme=APIKey;APIKey=YOUR_NASA_API_KEY")

Create a SQL Statement to Query NASA

Use SQL to create a statement for querying NASA. In this article, we read data from the AstronomyPictureOfDay entity.

sql = "SELECT ,  FROM AstronomyPictureOfDay WHERE StartDate = '2024-01-01'"

Extract, Transform, and Load the NASA Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the NASA data. In this example, we extract NASA data, sort the data by the column, and load the data into a CSV file.

Loading NASA Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

etl.tocsv(table2,'astronomypictureofday_data.csv')

With the CData API Driver for Python, you can work with NASA data just like you would with any database, including direct access to data in ETL packages like petl.

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to NASA data. Reach out to our Support Team if you have any questions.

Full Source Code

import petl as etl
import pandas as pd
import cdata.api as mod

cnxn = mod.connect("Profile=C:\profiles\NASA.apip;AuthScheme=APIKey;APIKey=YOUR_NASA_API_KEY")

sql = "SELECT ,  FROM AstronomyPictureOfDay WHERE StartDate = '2024-01-01'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

etl.tocsv(table2,'astronomypictureofday_data.csv')