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This guide provides a quick overview of how to set up and start using GroupDocs.Parser for Python via .NET. The library opens a document and extracts its text, tables, images, metadata and more, whatever the format.
To proceed, make sure you have:
- Configured environment as described in the System Requirements topic.
- Optionally you may Get a Temporary License to test all the product features.
For best practices, use a virtual environment to manage dependencies in Python applications. Learn more about virtual environments at the Create and Use Virtual Environments documentation topic.
Create a virtual environment:
py -m venv .venv
python3 -m venv .venv
python3 -m venv .venv
Activate a virtual environment:
.venv\Scripts\activate
source .venv/bin/activate
source .venv/bin/activate
After activating the virtual environment, run the following command in your terminal to install the latest version of the package:
py -m pip install groupdocs-parser-net
python3 -m pip install groupdocs-parser-net
python3 -m pip install groupdocs-parser-net
Ensure the package is installed successfully. You should see the message
Successfully installed groupdocs-parser-net-*
NoteVersion 26.10 is not on PyPI yet: until it is,pip install groupdocs-parser-netinstalls 25.12. Install the 26.10 wheel for your platform from the GroupDocs Releases website instead, as described in Install from a Pre-Downloaded Wheel.
To quickly test the library, let’s extract the text of a PDF report.
import os
from groupdocs.parser import Parser, License
def extract_text():
# Optionally set a license
license_path = os.path.abspath("./GroupDocs.Parser.lic")
if os.path.exists(license_path):
License().set_license(license_path)
# Open the document and extract its text
with Parser("./sample.pdf") as parser:
text = parser.get_text()
if text is None:
print("Text extraction isn't supported for this format")
else:
print(text)
if __name__ == "__main__":
extract_text()
sample.pdf is the sample file used in this example. Click here to download it.
Investor relations
Annual Report 2025 | Port Ellery
Annual Report 2025
1. Overview
Harbor Lane Provisions supplies specialty food to 1,265 independent grocers, cafes and restaurants from its
Quayside warehouse in Port Ellery. In 2025 net revenue grew 15.1% to $21.4 million, driven by the Autumn
[TRUNCATED]
Your folder tree should look similar to the following directory structure:
📂 demo-app
├──extract_text.py
├──sample.pdf
└──GroupDocs.Parser.lic (Optionally)
py extract_text.py
python3 extract_text.py
python3 extract_text.py
After running the app you can deactivate the virtual environment by executing deactivate or closing your shell.
Parser("./sample.pdf"): Opens the document. Used as a context manager so the native document handle is released.parser.get_text(): Extracts the text of the whole document as astr, or returnsNonefor a format that has no text extraction. Pass a page index, as inget_text(0), to extract one page.
In this example we read the document properties of the same report: its title, subject, author and dates.
import os
from groupdocs.parser import Parser, License
def extract_metadata():
# Optionally set a license
license_path = os.path.abspath("./GroupDocs.Parser.lic")
if os.path.exists(license_path):
License().set_license(license_path)
# Open the document and print each metadata item
with Parser("./sample.pdf") as parser:
metadata = parser.get_metadata()
if metadata is None:
print("Metadata extraction isn't supported for this format")
else:
for item in metadata:
print(item.name, "=", item.value)
if __name__ == "__main__":
extract_metadata()
sample.pdf is the sample file used in this example. Click here to download it.
title = Harbor Lane Provisions - Annual Report 2025
subject = Annual report and financial summary
keywords = annual report, wholesale, Autumn Harvest, revenue, logistics
author = Amara Osei
application = Aspose Pty Ltd.
last-saved-time = 2/16/2026 12:00:00 PM
py extract_metadata.py
python3 extract_metadata.py
python3 extract_metadata.py
parser.get_metadata(): Returns the document’s metadata items, orNonefor a format without metadata extraction.item.name/item.value: The name and the value of each property, such astitleorauthor.
Sometimes you need the data of a document rather than its text. get_tables() returns each table with its rows and cells.
import os
from groupdocs.parser import Parser, License
def extract_tables():
# Optionally set a license
license_path = os.path.abspath("./GroupDocs.Parser.lic")
if os.path.exists(license_path):
License().set_license(license_path)
# Open the document and print each table row by row
with Parser("./sample.pdf") as parser:
tables = parser.get_tables()
if tables is None:
print("Table extraction isn't supported for this format")
return
for table in tables:
print("Table on page", table.page.index + 1)
for row in range(table.row_count):
cells = [table[row, column].text for column in range(table.column_count)]
print(" | ".join(cells))
if __name__ == "__main__":
extract_tables()
sample.pdf is the sample file used in this example. Click here to download it.
Table on page 1
Metric | 2024 | 2025 | Change
Net revenue | $18.6 m | $21.4 m | +15.1%
Gross margin | 31.2% | 32.8% | +1.6 pts
Orders shipped | 48,900 | 55,300 | +13.1%
Wholesale customers | 1,140 | 1,265 | +11.0%
On-time delivery | 96.1% | 97.4% | +1.3 pts
Table on page 3
Category | Revenue | Share | Growth
Coffee & Tea | $5.9 m | 27.6% | +18.4%
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py extract_tables.py
python3 extract_tables.py
python3 extract_tables.py
parser.get_tables(): Returns the tables of the document, orNonefor a format without table extraction.table.page.index: The zero-based index of the page the table is on.table[row, column].text: The text of one cell;row_countandcolumn_countgive the table’s size.
After completing the basics, explore additional resources to enhance your usage:
- Get document info: Read the file type, page count and size of a document.
- Extract images: Extract the images of a document and save them to files.
- Extract text from documents: Extract the text of one page, and choose between the accurate and the raw mode.
- Supported Document Formats: Review the full list of supported file types, or list them in code.
- Licensing and Evaluation: Check details on licensing and evaluation.
- Developer Guide: Dive into tables, images, annotations, templates and containers across every supported format.
- Technical Support: Contact support for assistance if you encounter issues.
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