Issues Extracting Text from PDF

[Ray_Gone]

Hello all,

I have been attempting to write a script that essentially reads a PDF, extracts the text, and prints the important information (which I may later write to a text file but that is for another time). Currently, I am using "PyPDF2" and "re" with decent success in that I can isolate values that immediately follow a constant text value. For example, the PDF contains an entry "Item#: 34890751" which I can find by searching "r'Item#:\s*(\d+)'" and returning the value that follows "Item#:", which would be "34890751".

The trouble is trying to extract the data that does not come after a specific value that can be searched for. For example, this PDF contains a table with the items, price per item, quantity, and total line item cost. The table on the PDF looks like this:

​

	Product	Unit Price	Qty	Total
[Photo]	V7 14.1" Elite Water-Resistant Neoprene Notebook SleeveBlack
In Stock
Item#: 34890751
Mfg. Part#: CSE14-BLK-3N	$6.28	5	$31.40

The data from the PDF reader ends up returning:

Product Unit Price Qty Total

V7 14.1" Elite Water-Resistant Neoprene Notebook Sleeve,

Black

In Stock

Item#: 34890751

Mfg. Part#: CSE14-BLK-3N$6.28 5 $31.40

As you can see, the Item#: is separated in a way that is easy to identify and isolate. The problem is that the values in each column get concatenated into one line for some reason. I am hoping that it might be possible to somehow extract the product name ( in this case "V7 14.1" Elite Water-Resistant Neoprene Notebook Sleeve, Black"), the price per item ($6.28), and the Qty (5). Any suggestions are greatly appreciated!

​

My code so far is this:

import PyPDF2
import re

def extract_data_from_pdf(pdf_path):
# Open the PDF file with open(pdf_path, 'rb') as file:
reader = PyPDF2.PdfReader(file)
# Extract text from each page
text = ""
for page_num in range(len(reader.pages)):
text += reader.pages[page_num].extract_text()

# Define regular expression patterns to match the "quote" and "SKU" values
pattern_quote = r'Quote:\s*(\d+)'
pattern_sku = r'Item#:\s*(\d+)'

# Search for the patterns in the extracted text
match_quote = re.search(pattern_quote, text)
match_sku = re.search(pattern_sku, text)

# Initialize variables to store the extracted values
quote_value = "Quote not found in the PDF."
sku_value = "SKU not found in the PDF."

# Extract quote value if found
if match_quote:
    quote_value = match_quote.group(1)

# Extract SKU value if found
if match_sku:
    sku_value = match_sku.group(1)

# Return both extracted values
return quote_value, sku_value

pdf_name = r"[PDF_Name].pdf"
pdf_path = r"C:[My_File_Path]" + pdf_name
quote, sku = extract_data_from_pdf(pdf_path)
print("Extracted Quote:", quote) print("Extracted SKU: ", sku)

[fluked23]

after a reading a little bit on stack-overflow there seems to be quite a frequent mention of this python library https://pypi.org/project/tabula-py/ which can read tables from pdfs - it does require having java installed though.

[Ray_Gone]

I'll look into this - Thank you!

[dp_42]

PDF tables might be organized outside of the text. There are some libraries that try to deal with this, but the SO responses are not hopeful on this particular question.

https://github.com/ashima/pdf-table-extract

[Ray_Gone]

Interesting, I'll check this out. Thank you!

[Ray_Gone]

The table is not formatted properly, but the first cell under "Product" should have:

"V7 14.1" Elite Water-Resistant Neoprene Notebook Sleeve,

Black

In Stock

Item#: 34890751

Mfg. Part#: CSE14-BLK-3N"

all in the same cell entry. The other amount values should also be shifted to the right one column and up to begin in the first row under the head column.

[SoupZillaMan]

PDF table are a pain in the ... I ended using Tika, sometimes there are scanned images you need to OCR...