How I Automated Invoice Processing Instead of Copy-Pasting Data

A few months ago, I had to process dozens of invoices from different vendors.

The problem wasn't the volume—it was the formats.

Some invoices arrived as PDFs, others as Excel spreadsheets, and a few were exported as HTML tables. Getting everything into a single CSV file for analysis became a repetitive and error-prone task.

My first approach was manual:

Open invoice
Copy values
Paste into spreadsheet
Repeat

It worked, but it didn't scale.

So I started experimenting with automation. The workflow I ended up using looked something like this:

from pathlib import Path
import pandas as pd

invoice_dir = Path("invoices")

all_data = []

for file in invoice_dir.iterdir():
if file.suffix == ".csv":
df = pd.read_csv(file)
all_data.append(df)

combined = pd.concat(all_data, ignore_index=True)
combined.to_csv("combined_invoices.csv", index=False)

print("Done!")

The code above is intentionally simple, but the lesson was valuable:

Eliminate repetitive data entry whenever possible.
Standardize input formats early.
Build small automation tools before buying large software solutions.

What started as a frustrating administrative task turned into a workflow that now saves hours every month.

How are you handling invoice processing or document extraction in your projects? Do you use OCR, custom scripts, or third-party tools?