SECEdgar-Python

A simple library to interact with and retrieve information from the SEC Edgar Data.

Dependencies:

• OS
• pandas
• requests
• bs4

Installation

To install the required dependencies, run:

pip install -r requirements.txt

Functions

CIKExtractor() -> list

Extracts the CIK for S&P 500 companies from Wikipedia.

Usage:

from SECedgarpyExtractor import CIKExtractor
cik_list = CIKExtractor()
print(cik_list)

Concepts Used:

• Web scraping using requests and BeautifulSoup
• Error handling for HTTP requests

GetAllSP500CSV()

Gets all the S&P 500 info in the form of a CSV.

Usage:

from SECedgarpyExtractor import GetAllSP500CSV
GetAllSP500CSV()

Concepts Used:

• Web scraping using pandas
• Saving data to CSV

getCSVfile(URLlist: list[str], nameOfFile: str) -> None

Downloads the XLSX file from the list of URLs and converts them to CSV.

Usage:

from SECedgarpyDownloading import getCSVfile
getCSVfile(["url1", "url2"], "output_file")

Concepts Used:

• HTTP requests
• File handling
• Data conversion using pandas

getXLSXfile(URLlist: list[str], nameOfFile: str) -> None

Downloads the XLSX file from the list of URLs.

Usage:

from SECedgarpyDownloading import getXLSXfile
getXLSXfile(["url1", "url2"], "output_file")

Concepts Used:

• HTTP requests
• File handling

GenerateCSVreport(nameOfFile)

Generates a CSV report by filtering and keeping the necessary sheets only.

Usage:

from SECedgarpyDownloading import GenerateCSVreport
GenerateCSVreport("input_file")

Concepts Used:

• Data filtering
• Data merging using pandas

download_and_convert_filtered_xlsx(URLlist: list[str], nameOfFile: str, target_sheets: list[str]) -> None

Downloads and converts filtered XLSX files to CSV.

Usage:

from SECedgarpyDownloading import download_and_convert_filtered_xlsx
download_and_convert_filtered_xlsx(["url1", "url2"], "output_file", ["sheet1", "sheet2"])

Concepts Used:

• HTTP requests
• Data filtering
• Data conversion using pandas

filter_and_convert_to_csv(xlsx_file_path: str, csv_file_path: str, target_sheets: list[str]) -> None

Filters relevant sheets and converts them to CSV.

Usage:

from SECedgarpyDownloading import filter_and_convert_to_csv
filter_and_convert_to_csv("input.xlsx", "output.csv", ["sheet1", "sheet2"])

Concepts Used:

• Data filtering
• Data conversion using pandas

filterfunc(a: list) -> bool

Filters out and gets only the 10-K reports.

Usage:

from SECedgarpyProcessing import filterfunc
filtered_list = filter(filterfunc, data_list)

Concepts Used:

• Data filtering using custom functions

extract10Kurl(cikval: str) -> list

Extracts the URL using the CIK which is passed into the function.

Usage:

from SECedgarpyProcessing import extract10Kurl
urls = extract10Kurl("0000320193")
print(urls)

Concepts Used:

• API requests
• Data extraction and transformation

URLtoXLSX(URLlist: list[str]) -> list

Converts the URL to direct XLSX files.

Usage:

from SECedgarpyProcessing import URLtoXLSX
xlsx_urls = URLtoXLSX(["url1", "url2"])
print(xlsx_urls)

Concepts Used:

• URL manipulation