How do I download data using Python?

Note that each data feed on Nasdaq Data Link is delivered through one of the following Nasdaq Data Link APIs:

  • Streaming API for real-time data
  • REST API for real-time or delayed data
  • REST API for time-series
  • REST API for tables

You can learn more about these APIs, data formats and authentication here.

The streaming API is available through a Java SDK and Python SDK.

Data that is delivered through the REST API for time-series or REST API for tables can be used with the Nasdaq Data Link Python package.

To download data from Nasdaq Data Link, you first have to identify which data feed you'd like to get data from and identify which API to use for that data feed.

You can go to to see our data feeds. Once you find a data feed you're interested in, click on that data feed and look for its API type and see the "Usage" tab for API examples.

For example, if you go to go to and click on the Sharadar Equity Prices data feed, you'll be led to At the right-hand panel, you'll see some basic information about the data feed, including the API type for that feed - in this case, it's Tables API:

From, you can also click on the "Usage" tab, then "Python". That will lead you to where you will see Python command examples for that particular feed. You would have to be logged in to your account to see these examples. If you do not have a Nasdaq Data Link account, please create an account in order to see the examples. 

As previously mentioned,  the time-series and tables API can be used with the Nasdaq Data Link Python package. You can download and install the Python package as per the instructions here.


To use the Python package with data in time-series format, please see the documentation here

Note that you must use nasdaqdatalink.get with data in time-series format. 


To use the Python package with data in tables format, please see the documentation here.

Note that you must use nasdaqdatalink.get_table or nasdaqdatalink.export_table with data in tables format.

If you are interested in using the Python SDK for real-time data, please see the instructions here.

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