Parse Data from Documents Leave feedback
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Use template-based parsing to pull structured values (like invoice numbers, dates, tables) from documents.
from groupdocs.parser import Parser
from groupdocs.parser.templates import Template, TemplateField, TemplateFixedPosition
from groupdocs.parser.data import Rectangle, Point, Size
template = Template([
TemplateField(
TemplateFixedPosition(Rectangle(Point(35.0, 135.0), Size(100.0, 10.0))),
"CompanyName",
),
TemplateField(
TemplateFixedPosition(Rectangle(Point(440.0, 115.0), Size(110.0, 15.0))),
"InvoiceNumber",
),
])
with Parser("./invoice.pdf") as parser:
data = parser.parse_by_template(template)
if data is None:
print("Parsing by template isn't supported for this format.")
else:
# DocumentData exposes extracted fields as an indexed collection.
for i in range(data.count):
field = data[i]
print(f"{field.name}: {field.text}")
The following sample file is used in this example: invoice.pdf
COMPANYNAME: Northwind Coffee
INVOICENUMBER: HLP-2025-0412
- Build a
Templatewith fields or tables (fixed positions, regex, linked positions, etc.). - Call
parser.parse_by_template(template)to receiveDocumentData. - Iterate through extracted fields by index (
data.countanddata[i]) and process each extracted value based on its type (text, table, etc.).
For complex templates (tables, linked fields, regex fields), see the advanced templates guide.
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