datadock 1.1.0

DataDock python library to access SEC edgar fillings.

DataDockPy Library

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Introduction

DataDockPy is a powerful and user-friendly Python package designed to enhance data analysis. It simplifies the extraction and presentation of information from the SEC Edgar database, offering enriched data display for SEC form types, form controls, and financial analysis, making it an essential tool for professionals working with regulatory filings.

This library uses Poetry as a dependency manager.

Features

• 📁 Access any SEC filing: You can access any filings on SEC forms of Form 8-K and Form 10-K
• 📅 List filings for any date range: List filings by date e.g. or date range 2024-02-29:2024-03-15
• 🌟 User Friendly library: Uses rich & tabulate library to display SEC Edgar data in a beautiful way.
• 🔄 Page through filings: Use filings.next() and filings.previous() to page through filings
• 🏗️ Filter filings data: Build data filtering by cik, accession number, form type, filing date
• ✅ Select a filing: You can select a filing from the list of filings.
• 🔍 Preview the text data for a filing: You can preview the filing (sections) in the terminal or a notebook.
• 📊 Parse to Dataframe: You can parse filings to a dataframe.
• 📈 Financial Statement: Get financial statements of Form 8-K and Form 10-K of various companies.

Get Started on Windows/MacOS/Linux Terminal

1. Open your terminal and install poetry using pip.

   pip install poetry
   

   or

   Install poetry using pipx.

   pipx install poetry
   

2. Create a project and clone DataDockPy github repository.

   git clone https://github.com/DataDock-AI/DataDockPy.git
   

3. Change directory to DataDockPy

   cd DataDockPy
   

4. Run the poetry command to install dependencies:

   poetry install
   

5. Activate virtual environment using poetry:

   poetry shell
   

6. Set up your SEC_IDENTITY in an .env file

    SEC_IDENTITY=<your email or usernmae for SEC IDENTITY>
   

7. See the following scripts on how to use the package: run_checks.py and run_checks2.py

Use DataDockPy with Jupyter

1. Open terminal and install poetry using pip.

   pip install poetry
   

   or

   Install poetry using pipx.

   pipx install poetry
   

2. Create a project and clone DataDockPy github repository

    git clone https://github.com/DataDock-AI/DataDockPy.git
   

3. Change directory to DataDockPy

   cd DataDockPy
   

4. Open your project directory on Anaconda or Visual Studio Code.

5. Choose a python environment (recommended python environment), where poetry was installed. Ctrl+Shift+P

6. If asked to install ipykernel, see here on installation: ipykernel installation

7. Check to see if poetry is installed:

   !poetry --version   
   

8. Run the poetry command to install dependencies:

   poetry install
   

Download DataDockPy Source Code

You can download any of the source codes: zip or tar.gz here: DataDockPy Source Code.

If you have any issue or contribution, please write an issue with this link: https://github.com/DataDock-AI/DataDockPy/issues