datamule 0.16

Making it easier to use SEC filings

datamule

A python package to make using SEC filings easier. Currently makes downloads easier and faster.

Links: Download Indices (900mb)

Installation

pip install datamule

Quickstart:

Using the API

Limited to 10,000 results per query.

from datamule import Downloader
downloader = Downloader()
downloader.download_using_api(form='10-K',ticker='AAPL')

Without the API

Either download the pre-built indices from the links in the readme and set the indices_path to the folder

from datamule import Downloader
downloader = Downloader()
downloader.set_indices_path(indices_path)

Or run the indexer

from datamule import Indexer
indexer = Indexer()
indexer.run()

Example Downloads

# Example 1: Download all 10-K filings for Tesla using CIK
downloader.download(form='10-K', cik='1318605', output_dir='filings')

# Example 2: Download 10-K filings for Tesla and META using CIK
downloader.download(form='10-K', cik=['1318605','1326801'], output_dir='filings')

# Example 3: Download 10-K filings for Tesla using ticker
downloader.download(form='10-K', ticker='TSLA', output_dir='filings')

# Example 4: Download 10-K filings for Tesla and META using ticker
downloader.download(form='10-K', ticker=['TSLA','META'], output_dir='filings')

# Example 5: Download every form 3 for a specific date
downloader.download(form ='3', date='2024-05-21', output_dir='filings')

# Example 6: Download every 10K for a year
downloader.download(form='10-K', date=('2024-01-01', '2024-12-31'), output_dir='filings')

# Example 7: Download every form 4 for a list of dates
downloader.download(form = '4',date=['2024-01-01', '2024-12-31'], output_dir='filings')

TODO

• Integration with datamule's SEC Router bulk data endpoint to remove need for indexing.
• integration with datamules Parser endpoint
• download indices instead of re-running using python

Update Log: 9/9/24

• added download_using_api(self, output_dir, **kwargs). No indices required. 9/8/24
• Added integration with datamule's SEC Router API 9/7/24
• Simplified indices approach
• Switched from pandas to polar. Loading indices now takes under 500 milliseconds.