Extract text areas Leave feedback
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GroupDocs.Parser provides functionality to extract text areas with position information (coordinates) and formatting details from documents.
- GroupDocs.Parser for Python via .NET installed
- Sample documents for testing
- Understanding of coordinate systems in documents
Text areas represent rectangular regions on a page containing text. Each text area includes:
- Page index: The page where the text appears
- Rectangle: Position and size (x, y, width, height)
- Text: The actual text content
- Baseline: The baseline position of the text
- Text style: Formatting information (font, size, etc.)
- Child areas: For composite text areas
To extract all text areas from a document:
from groupdocs.parser import Parser
# Create an instance of Parser class
with Parser("./sample.pdf") as parser:
# Extract text areas
text_areas = parser.get_text_areas()
# Check if text areas extraction is supported
if text_areas is None:
print("Text areas extraction isn't supported")
else:
# Iterate over text areas
for area in text_areas:
# Print page index, rectangle, and text
print(f"Page: {area.page.index}, Rectangle: {area.rectangle}, Text: {area.text}")
The following sample file is used in this example: sample.pdf
Page: 0, Rectangle: (56; 803.10098896) (213.13599999999997; 8.799999999999955), Text: Harbor Lane Provisions | 18 Quayside Road, Port Ellery |
Page: 0, Rectangle: (269.14500426999996; 803.10098896) (70.69599999999974; 8.799999999999955), Text: harborlane.example
Page: 0, Rectangle: (339.85700426999995; 803.10098896) (10.975999999999942; 8.799999999999955), Text: |
Page: 0, Rectangle: (350.82400513; 803.10098896) (30.239999999999895; 8.799999999999955), Text: LinkedIn
Page: 0, Rectangle:
[TRUNCATED]
Expected behavior: Returns a collection of PageTextArea objects with position and text information for each text area in the document.
To extract text areas from a specific page:
from groupdocs.parser import Parser
# Create an instance of Parser class
with Parser("./sample.pdf") as parser:
# Check if text areas extraction is supported
if not parser.features.text_areas:
print("Document doesn't support text areas extraction")
else:
# Get document info
info = parser.get_document_info()
# Check if document has pages
if info.page_count == 0:
print("Document has no pages")
else:
# Iterate over pages
for page_index in range(info.page_count):
print(f"\nPage {page_index + 1}/{info.page_count}")
# Extract text areas from the page
text_areas = parser.get_text_areas(page_index)
# Iterate over text areas
if text_areas:
for area in text_areas:
# Print rectangle and text
rect = area.rectangle
print(f"Position: ({rect.left}, {rect.top}), Size: ({rect.size.width}x{rect.size.height})")
print(f"Text: {area.text}")
The following sample file is used in this example: sample.pdf
Page 1/4
Position: (56, 803.10098896), Size: (213.13599999999997x8.799999999999955)
Text: Harbor Lane Provisions | 18 Quayside Road, Port Ellery |
Position: (269.14500426999996, 803.10098896), Size: (70.69599999999974x8.799999999999955)
Text: harborlane.example
Position: (339.85700426999995, 803.10098896), Size: (10.975999999999942x8.799999999999955)
Text: |
Position: (350.82400513, 803.10098896), Size: (30.239999999999895x8.799999999999955)
Text: LinkedIn
Position: (381.07200513, 803.1
[TRUNCATED]
Expected behavior: Returns text areas only for the specified page, allowing page-by-page processing.
To extract text areas from a specific region with filtering:
from groupdocs.parser import Parser
from groupdocs.parser.options import PageTextAreaOptions
from groupdocs.parser.data import Rectangle, Point, Size
# Create an instance of Parser class
with Parser("./sample.pdf") as parser:
# Define the region (upper-left corner, 300x200 points)
region = Rectangle(Point(0, 0), Size(300, 200))
# Create options to extract only text areas with digits in the specified region
options = PageTextAreaOptions(r"\d+", region)
# Extract text areas
text_areas = parser.get_text_areas(options)
if text_areas is None:
print("Text areas extraction isn't supported")
else:
# Iterate over filtered text areas
for area in text_areas:
print(f"Page: {area.page.index}, Rectangle: {area.rectangle}, Text: {area.text}")
The following sample file is used in this example: sample.pdf
Page: 0, Rectangle: (109.368; 92.40000019000013) (17.792; 8.799999999999955), Text: 2025
Page: 0, Rectangle: (242.31599999999995; 114.49799948999998) (57.849999999999994; 28.600000000000023), Text: 2025
Page: 1, Rectangle: (203.936; 28.400000190000128) (17.79200000000003; 8.799999999999955), Text: 2025
Page: 1, Rectangle: (56; 98.74999968999998) (8.340000000000003; 16.5), Text: 2
Page: 1, Rectangle: (149.38; 121.74900065999998) (11.120000000000005; 11), Text: 13
Page: 1, Rectangle: (163.28000000
[TRUNCATED]
Expected behavior: Returns only text areas that match the regular expression pattern and fall within the specified rectangular region.
To extract text areas with their position on the page, and their formatting where the document reports it:
from groupdocs.parser import Parser
# Create an instance of Parser class
with Parser("./sample.docx") as parser:
# Extract text areas
text_areas = parser.get_text_areas()
if text_areas is None:
print("Text areas extraction isn't supported")
else:
# Iterate over the first text areas
for area in list(text_areas)[:8]:
rect = area.rectangle
print(f"Text: {area.text}")
print(f"Page: {area.page.index + 1}, position: ({rect.left:.0f}, {rect.top:.0f}), "
f"size: {rect.right - rect.left:.0f} x {rect.bottom - rect.top:.0f}, "
f"base line: {area.base_line:.1f}")
# The text style is None where the format doesn't report one
if area.text_style is not None:
print(f"Font: {area.text_style.font_name}, {area.text_style.font_size} pt, "
f"bold: {area.text_style.is_bold}, italic: {area.text_style.is_italic}")
print("---")
The following sample file is used in this example: sample.docx
Text: Supply Agreement
Page: 1, position: (56, 121), size: 230 x 30, base line: 150.9
---
Text: Harbor Lane Provisions and Northwind Coffee Roasters
Page: 1, position: (56, 154), size: 247 x 11, base line: 165.4
---
Text: 1. Parties
Page: 1, position: (56, 175), size: 67 x 17, base line: 192.6
---
Text: Buyer: Harbor Lane Provisions, 18 Quayside Road, Port Ellery, represented by Lena Park, Procurement
[TRUNCATED]
Expected behavior: Prints each text area with its page, position, size and base line, and its font where the document reports one, useful for document analysis.
Extract text from multiple predefined regions:
from groupdocs.parser import Parser
from groupdocs.parser.options import PageTextAreaOptions
from groupdocs.parser.data import Rectangle, Point, Size
def extract_from_regions(file_path, regions):
"""
Extract text from specific regions of a document.
Args:
file_path: Path to the document
regions: List of tuples (x, y, width, height)
"""
with Parser(file_path) as parser:
if not parser.features.text_areas:
print("Text areas extraction not supported")
return {}
results = {}
for idx, (x, y, w, h) in enumerate(regions):
# Create rectangle for this region
rect = Rectangle(Point(x, y), Size(w, h))
options = PageTextAreaOptions(None, rect)
# Extract text areas from this region
areas = parser.get_text_areas(options)
# Collect text from all areas in this region
text_list = [area.text for area in areas] if areas else []
results[f"region_{idx}"] = " ".join(text_list)
return results
# Define regions (e.g., header, body, footer)
regions = [
(0, 0, 600, 100), # Header region
(0, 100, 600, 700), # Body region
(0, 800, 600, 100) # Footer region
]
# Extract text from regions
extracted = extract_from_regions("sample.pdf", regions)
for region_name, text in extracted.items():
print(f"{region_name}: {text[:100]}...")
The following sample file is used in this example: sample.pdf
region_0: Annual Report 2025 | Port Ellery Investor relations Harbor Lane Provisions | Annual Report 2025 ...
region_1: Annual Report 2025 | Port Ellery Annual Report 2025 1. Overview Harbor Lane Provisions supplies sp...
region_2: Harbor Lane Provisions | 18 Quayside Road, Port Ellery | harborlane.example | LinkedIn | ...
- Text area extraction is more detailed than simple text extraction
- Not all document formats support text area extraction - check
parser.features.text_areasfirst - Coordinates are in document-specific units (usually points or pixels)
- Composite text areas contain child text areas in the
areasproperty - Use regular expressions in
PageTextAreaOptionsto filter text areas by content - Rectangle coordinates start from the top-left corner (0, 0)
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