Welcome to CB_IPO’s documentation!

This is a library designed for quick webscraping in finding information on SEC filings with a focus on new IPOs and annual reports.

Quick Start:

• Installation
• Usage
• Methods
• Example Uses

Overview

Researching information on trends for companies can be incredibly tedious, this library will automate part of the proccess making DCF building and IPO research easier. CB_IPO is a library that will fetch information on recent and historical IPOs by scraping the SEC EDGAR database for S-1 filings. With these links, the library also has a function for using a 10-k link and returning a dictionary or dataframe of info such as assets, liabilities, and income.

Example

Suppose I want to find companies that have filed either an S-1, 10-K or 10-Q between January 2021 and March 2023

sc = scrape()
sc.set_search_date("2021-01-01", "2023-03-31")
sc.add_forms(['S-1','10-K', '10-Q'])
dataframe = sc.generate_df(10, 1)

Then this pandas.DataFrame is returned

                                                names filing date
0               Inhibikase Therapeutics, Inc.  (IKT)   2023-03-31
1                       AMERINST INSURANCE GROUP LTD   2023-03-31
2                      SLM Student Loan Trust 2013-5   2023-03-31
3   Games & Esports Experience Acquisition Corp.  ...  2023-03-31
4   Bilander Acquisition Corp.  (TWCB, TWCBU, TWCBW)   2023-03-31
5                                VirTra, Inc  (VTSI)   2023-03-31
6             Actinium Pharmaceuticals, Inc.  (ATNM)   2023-03-31
7                              Genprex, Inc.  (GNPX)   2023-03-31
8                           Mega Matrix Corp.  (MPU)   2023-03-31
9       Digital Media Solutions, Inc.  (DMS, DMS-WT)   2023-03-31

Details

This project is a pure python project using modern tooling. It uses a Makefile as a command registry, with the following commands:

• make: list available commands.

• make develop: install and build this library and its dependencies using pip.

• make build: build the library using setuptools

• make lint: perform static analysis of this library with flake8 and black

• make format: autoformat this library using black

• make annotate: run type checking using mypy

• make test: run automated tests with pytest

• make coverage: run automated tests with pytest and collect coverage information

• make dist: package library for distribution