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papero-extract

PyPIInfrastructure

PulseGate's liveness check found it on 1 Oct 2026; it is registered on PyPI and has been in the index since 1 Oct 2026. How this is checked

papero-extract is an MIT-licensed Python package for converting PDFs into Markdown, JSON, and tables while preserving reading order and layout information. It supports extraction of formulas, images, bounding boxes, and OCR through library, CLI, REST API, and browser interfaces.

Inferred · not functionally tested

Open SourceMITCLISelf-hostedAPI
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Overview

6 features

Purpose: Extracting structured text, tables, formulas, images, and layout data from PDF documents.

Inferred · not functionally tested

Audience: developers building document-processing and PDF extraction workflows

Inferred · not functionally tested

Functions: data_extraction

Inferred · not functionally tested

Interfaces: API: indicated (inferred, not tested) · MCP: unknown · CLI: indicated (inferred, not tested) · Self-hosting: indicated (inferred, not tested)

Recorded constraints: pricing: open_source · license: MIT · platforms: CLI · deployment: cli, self_hosted, api_only

Constraint provenance is unknown; confirm requirements with the publisher.

Record sources: pypi.org. These links do not verify the individual claims.

papero-extract is a Computer vision, OCR & document AI project. Inferred · not functionally tested: It focuses on extracting structured text, tables, formulas, images, and layout data from PDF documents. Inferred · not functionally tested: papero-extract is an open-source project aimed at developers building document-processing and PDF extraction workflows. Basis unknown · not verified: papero-extract is open source under the MIT license. Basis unknown · not verified: It runs on the command line and API, and it can be self-hosted.

papero-extract first shipped in 2026. Inferred · not functionally tested: Among its 6 catalogued features are PDF parsing, markdown output, and JSON output.

Summary written by a language model from the project’s public pages.

Tasks: Inferred · not functionally tested

  • PDF parsing
  • Markdown output
  • JSON output
  • Table extraction
  • Formula extraction
  • Image extraction

Topics: Inferred · not functionally tested

Tags
pdf-extractiondocument-parsinglayout-analysistable-extractionocr

JSON profile · Text profile · Access guide

Built with & integrations

Runs on
CLISelf-hostedAPI-only

Trust & compliance

License
MIT
Public signals
HTTPSOpen SourceFree tier

Indexing history

3

What PulseGate has recorded for this listing

  1. Indexed2 Oct · 16:31 UTC
    papero-extract seen via PyPI Fresh Feed
    Source: PyPI Fresh Feed · Open
  2. Indexed1 Oct · 19:53 UTC
    papero-extract seen via PyPI Fresh Feed
    Source: PyPI Fresh Feed · Open
  3. Indexed1 Oct · 17:13 UTC
    papero-extract seen via PyPI Bulk Enumerator
    Source: PyPI Bulk Enumerator · Open

Frequently asked questions about papero-extract

What does papero-extract do?
Inferred · not functionally tested: Papero-extract focuses on extracting structured text, tables, formulas, images, and layout data from PDF documents. It is catalogued under Computer vision, OCR & document AI on PulseGate.
Who is papero-extract for?
Inferred · not functionally tested: papero-extract is an open-source project built for developers building document-processing and PDF extraction workflows.
Is papero-extract free?
Basis unknown · not verified: Yes — papero-extract is open source under the MIT license and free to use.
What platforms does papero-extract run on?
Basis unknown · not verified: papero-extract runs on the command line and API. It can also be self-hosted.
Is papero-extract still active?
PulseGate's liveness check found it on 1 Oct 2026.
What are alternatives to papero-extract?
Similar projects tracked by PulseGate include SpiderPet, PresbyFriend, and OpenDocRouter.SpiderPetPresbyFriendOpenDocRouter
How long has papero-extract been around?
papero-extract first shipped in 2026.
Is papero-extract open source?
Basis unknown · not verified: Yes — papero-extract is open source under the MIT license.

Also in Computer vision, OCR & document AI

Same category — not a similarity match