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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
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")
return
# Get document info
info = parser.get_document_info()
# Check if document has pages
if info.page_count == 0:
print("Document has no pages")
return
# Iterate over pages
for page_index in range(info.page_count):
print(f"
Page {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.width}x{rect.height})")
print(f"Text: {area.text}")
The following sample file is used in this example: sample.pdf
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, Rectangle, Point, Size
# Create an instance of Parser class
with Parser("./sample.pdf") as parser:
# Define the region (upper-left corner, 300x100 pixels)
region = Rectangle(Point(0, 0), Size(300, 100))
# 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
Expected behavior: Returns only text areas that match the regular expression pattern and fall within the specified rectangular region.
To extract text areas and access formatting information:
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 text areas
for area in text_areas:
# Get text style if available
if area.text_style:
print(f"Text: {area.text}")
print(f"Font: {area.text_style.name}")
print(f"Size: {area.text_style.font_size}")
print(f"Bold: {area.text_style.is_bold}")
print(f"Italic: {area.text_style.is_italic}")
print("---")
The following sample file is used in this example: sample.docx
Expected behavior: Extracts text areas with detailed formatting information, useful for document analysis.
Extract text from multiple predefined regions:
from groupdocs.parser import Parser
from groupdocs.parser.options import PageTextAreaOptions, 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
- 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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