Electoral bonds pdf to csv extraction

ebonds_extract.py

import re
from pypdf import PdfReader
import pandas as pd

# 34ca61ebc3ddbb71a1d16f8f43db38d031872126  encashment-details.pdf
encashment = PdfReader("encashment-details.pdf")

# 11e0aff1007065d9a4de49ac5499fbf4186dcda0  purchaser-details.pdf 
purchaser = PdfReader("purchaser-details.pdf")

def extractLines(file):
    data = []
    for epage in enumerate(file.pages):
        p = epage[0]
        page = epage[1]
        text = page.extract_text()
        lines = text.split("\n")
        data.extend(lines)
    return data
 
def fields(line):
    parts = re.match("^([0-9]+/[A-Za-z]+/[0-9]+) (.+) ([0-9,]+)$", line)
    assert parts != None, 'line = ' + line
    date = parts.group(1)
    entity = parts.group(2)
    amount = int(parts.group(3).replace(',', ''))
    return (date, entity, amount)
 
def extractEncashment(encashment):
    data = extractLines(encashment)
    if data[0] == 'Date of ' and data[1] == 'Encashment Name of the Political Party Denomination':
        data = data[2:]
    return [fields(line) for line in data]

def extractPurchaser(purchaser):
    data = extractLines(purchaser)
    if data[0] == 'Date of Purchase Purchaser Name Denomination':
        data = data[1:]
    return [fields(line) for line in data]

def todf(arr, headers):
    d = {}
    for c in range(len(headers)):
        h = headers[c]
        d[h] = [arr[i][c] for i in range(len(arr))]
    return pd.DataFrame(d)

encashmentHeaders = ['Date of Encashment', 'Name of the Political Party', 'Denomination']
todf(extractEncashment(encashment), encashmentHeaders).to_csv("encashment.csv", index=False)

purchaserHeaders = ['Date of Purchase', 'Purchaser Name', 'Denomination']
todf(extractPurchaser(purchaser), purchaserHeaders).to_csv("purchaser.csv", index=False)