Skip to main content

High-level PDF structure extraction library for developers.

Project description

sv-smartpdf

The best high-level PDF structure extraction library in Python that solves the painful manual work developers currently face.

Existing tools are powerful but low-level. sv-smartpdf provides a beautiful, high-level interface for extracting hierarchical sections, tables, figures, and metadata from complex PDFs.

Installation

pip install sv-smartpdf

For OCR support:

pip install sv-smartpdf[ocr]

Quick Start

from sv_smartpdf import parse

# Parse a document
doc = parse("paper.pdf")

# Beautiful high-level interface
print(doc.title)
print(doc.metadata)

# Hierarchical sections
for section in doc.sections:
    print(f"{'  ' * section.level}- {section.title}")
    
# Rich table objects
for table in doc.tables:
    print(table.df) # pandas DataFrame

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sv_smartpdf-0.1.2.tar.gz (540.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sv_smartpdf-0.1.2-py3-none-any.whl (8.7 kB view details)

Uploaded Python 3

File details

Details for the file sv_smartpdf-0.1.2.tar.gz.

File metadata

  • Download URL: sv_smartpdf-0.1.2.tar.gz
  • Upload date:
  • Size: 540.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.3

File hashes

Hashes for sv_smartpdf-0.1.2.tar.gz
Algorithm Hash digest
SHA256 b85fbdf2424619d537c029a34cf6c05f440a57a001040dcad80361be290be704
MD5 ecb3e87343d76d8ef3548be53bcf04a3
BLAKE2b-256 d6b09961c494a8dc9363a2c195db823945532801144986db9df5f77ba0d375fd

See more details on using hashes here.

File details

Details for the file sv_smartpdf-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: sv_smartpdf-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 8.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.3

File hashes

Hashes for sv_smartpdf-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 9aca33ce4d15130b93b37f289d7b090161bc4cae022f8250d57f109e56a3ce01
MD5 c69d9cad66ba329768c16a42063dad42
BLAKE2b-256 41e3e03bf8044e127f1f80bbb7b9a3860f36a5a8407ebe170604088c9f3d4958

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page