𝗛𝗼𝘄 𝗜 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗜𝗻𝘃𝗼𝗶𝗰𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴

𝗛𝗼𝘄 𝗜 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗜𝗻𝘃𝗼𝗶𝗰𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴

I used to process dozens of invoices from different vendors every month.

The problem was the formats.

Some files arrived as PDFs. Some arrived as Excel sheets. Others arrived as HTML tables.

I had to put all this data into one CSV file. Doing this manually caused mistakes. It took too much time.

My first method was simple. I opened each file and copied the data. This worked for a few files. It failed when the work grew.

I decided to use automation instead. I built a workflow to handle the files.

The process looked like this:

• Scan the invoice folder.
• Read the file content.
• Extract the data.
• Combine everything into one list.
• Save the final result to a CSV.

I used a Python script to do the heavy lifting. Here is the logic:

from pathlib import Path import pandas as pd

invoice_dir = Path("invoices") all_data = []

for file in invoice_dir.glob("*"): # Logic to read files goes here df = pd.read_csv(file) all_data.append(df)

combined = pd.concat(all_data, ignore_index=True) print("Done!")

This task used to frustrate me. Now, it saves me hours every month.

The lesson is clear. Stop doing repetitive data entry. Use code to do it for you.

How do you handle document extraction? Do you use OCR, scripts, or other tools?

Source: https://dev.to/dylan_parker123/how-i-automated-invoice-processing-instead-of-copy-pasting-data-2002