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PDF to JSON Converter – Convert PDF Data to JSON Free Online
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PDF to JSON Converter
Extract PDF Data to JSON Free

Convert any PDF document into clean, structured JSON data. Extract full text, paragraphs, lines, words, or document metadata. Perfect for developers, data analysts, and automation workflows — runs entirely in your browser.

PDF
PDF Document
➔
JSON
Structured Data
100%
Free Forever
4
Extraction Modes
0s
Server Upload Time
API
Ready Output

PDF to JSON — Convert Now

Upload your PDF, choose an extraction mode, configure output options, then copy or download your clean JSON data instantly.

Extraction Settings
Extraction Mode
Select Output Structure Choose how the PDF content is structured in the JSON output. Each mode is suited for different use cases.
📄
Full Document
Pages, paragraphs, lines & metadata
☰
Line by Line
Every text line as a JSON array item
🔤
Word by Word
Every individual word in an array
🗂️
Metadata Only
Title, author, page count, info fields
Output Format
Pretty Print (Indented) Format JSON with indentation and line breaks for human readability. Disable for compact minified output.
Include Page Numbers Add a page field to each content block indicating the source page number.
Include Document Metadata Prepend a metadata object with title, author, page count, and PDF version.
Filter Empty Lines Skip blank or whitespace-only lines from the output to produce cleaner, more compact JSON data.
Page Range
Start Page First page to extract. Default is 1.
End Page Last page to extract. Enter 0 for all pages.
JSON Indent Size Number of spaces for indentation when pretty print is on.
Output Filename
JSON Filename The downloaded file will be saved as output.json
Upload PDF File
🔒
100% Private: Your PDF is parsed entirely in your browser using PDF.js. No data is sent to any server — your document stays on your device throughout the entire extraction process.
📄

Drag & Drop your PDF here

or click to browse — text-based PDFs work best

✅ PDF Supported
Output Schema

What the JSON Output Looks Like

In Full Document mode, the extracted JSON follows a clean, predictable schema with document metadata and per-page content blocks.

"document": { "metadata": { "title": "Annual Report 2025", "author": "Jane Smith", "totalPages": 12, "pdfVersion": "1.7" }, "pages": [ { "page": 1, "paragraphs": [ { "index": 0, "text": "Executive Summary", "lines": ["Executive Summary"] } ], "lineCount": 42, "wordCount": 318 } ] }
Why It Works

Four Pillars of a Great
PDF to JSON Converter

The design principles behind this tool — and what to look for in any PDF data extractor you use.

01

Structured Output

Clean, predictable JSON schemas — not a flat text dump. Pages, paragraphs, lines, and words are nested logically.

02

Local Processing

Your PDF is parsed entirely in your browser with PDF.js. Sensitive documents never touch a remote server.

03

Developer Friendly

Pretty-print, minify, copy to clipboard, set indent size — built to drop straight into code, APIs, and pipelines.

04

Flexible Modes

Four extraction modes cover document structure, line processing, tokenisation, and metadata cataloguing.

Why Use This Tool

The Best Free PDF to JSON Converter

Browser-based, private, and built for developers and data professionals who need reliable structured JSON from PDF files.

🔒
100% Private & Secure
Your PDF is parsed entirely in your browser using PDF.js. It is never uploaded to any server. Your documents and their contents remain on your device at all times — no exceptions.
📄
Full Document Mode
Extract the complete document structure: metadata, pages, paragraphs, and individual lines — all nested into a clean hierarchical JSON object ready for programmatic processing or API ingestion.
☰
Line-by-Line Extraction
Convert every text line in the PDF into a flat JSON array with page numbers attached. Ideal for processing logs, reports, or structured plain-text documents line by line.
🔤
Word-by-Word Extraction
Output every individual word as a JSON array item with its source page. Useful for NLP pipelines, word frequency analysis, text tokenisation, and custom search index building.
🗂️
Metadata Extraction
Extract only document metadata — title, author, creator, producer, PDF version, page count, and creation date — without processing content. Perfect for document cataloguing workflows.
{ }
Pretty Print & Minify
Toggle between indented, human-readable JSON and compact minified output with a single click. Choose indent size (2 or 4 spaces) to match your team's code style preferences.
📐
Page Range Control
Extract only the pages you need using the Start Page and End Page controls. Process a single page, a chapter, or the full document — without converting unnecessary content.
⎘
Copy & Download
Copy the entire JSON output to your clipboard with one click, or download it as a clean .json file. Use it directly in your code editor, API client, or data pipeline.
🔄
Re-extract Without Reloading
Change extraction mode, toggle options, or adjust page range and click "Re-extract" — your PDF stays loaded and re-processes instantly without requiring another file upload.
📊
Live Extraction Stats
A live stats bar shows pages extracted, lines found, words found, and the resulting JSON file size — updated every time you extract or re-extract.
🖥️
Built-in JSON Viewer
Preview the output in a dark, monospaced editor pane with a clear size badge before you copy or download. No need to open the file in a separate tool.
🌗
Auto Dark Mode
The interface adapts to your system theme via prefers-color-scheme, with no manual toggling required.
♾️
Unlimited Use
Convert as many PDFs as you want, as often as you want. No daily quotas, no waiting timers, no paywalls — ever.
Simple Process

Convert PDF to JSON in 3 Steps

From PDF upload to downloadable JSON in seconds. No account, no installation required.

1
Upload Your PDF
Drag and drop your PDF or click to browse. The tool reads the file locally — nothing leaves your device. Text-based PDFs are supported and work best.
2
Choose Extraction Settings
Select your extraction mode (Full Document, Lines, Words, or Metadata), configure output toggles, set a page range, and choose pretty-print or minified format.
3
Copy or Download JSON
Click "Convert to JSON". Preview the output in the built-in editor, copy it to clipboard, or download it as a .json file ready for your pipeline.
Extraction Modes

Which Mode Should
You Choose?

Four extraction modes, each producing a different JSON shape for a different job. Here's a guide to picking the right one.

📄

Full Document

Nested structure: metadata → pages → paragraphs → lines, with per-page line and word counts. Best when you want to preserve document hierarchy for rich downstream processing or rendering.

☰

Line by Line

A flat array where every line is one object with its page number and text. Best for log-style documents, line-oriented reports, or feeding a line-based parser.

🔤

Word by Word

A flat array of every word with its source page. Best for NLP tokenisation, word-frequency analysis, building search indexes, or training simple text models.

🗂️

Metadata Only

Just the document info object — title, author, creator, producer, PDF version, page count, creation date. Best for cataloguing or indexing large PDF collections fast.

Behind the Scenes

What Happens Inside Your
Browser, Step by Step

For the curious: a look at exactly what the tool does between the moment you drop your PDF and the moment your JSON appears.

📥

1. File arrives as a Blob CLIENT-SIDE

When you drop or select a PDF, the browser hands it to JavaScript as a Blob, then an ArrayBuffer. The bytes never touch the network — they exist only in your tab's memory.

🔍

2. PDF.js parses the document PARSE

Mozilla's PDF.js opens the byte array, decodes its internal object tree, and exposes the page count plus a metadata info dictionary (title, author, producer, etc.).

🗂️

3. Metadata is read META

We call getMetadata() to collect the document's title, author, subject, creator, producer, PDF version, page count, and creation date into a clean object.

📃

4. Each page's text is extracted EXTRACT

For each page in your chosen range, PDF.js's getTextContent() returns every text item. We join the item strings into the raw page text.

✂️

5. Text is split into lines & paragraphs STRUCTURE

Raw text is split on line breaks into lines, and on double line breaks into paragraphs. Each is trimmed, and (optionally) empty entries are filtered out.

🔢

6. Words & counts computed COUNT

We tokenise on whitespace to get words and counts. Per-page line and word counts feed the live stats bar and (in Full mode) the JSON output.

🏗️

7. JSON object assembled BUILD

Depending on mode, we build the nested document object, a flat lines array, a flat words array, or just the metadata object — honouring your page-number and metadata toggles.

🎨

8. Serialized with your format SERIALIZE

JSON.stringify serializes the object — pretty-printed with your chosen indent, or minified to a single line for the smallest payload.

🖥️

9. Rendered in the viewer PREVIEW

The JSON string fills the in-page editor with a live size badge, so you can review the output before copying or downloading.

💾

10. Copy or download OUTPUT

Copy to clipboard via the Clipboard API, or download a Blob as a .json file. Nothing uploaded — it moves straight from tab memory to your disk.

Format Deep Dive

Why JSON, and Why
It Pairs Well with PDF Data

Understanding JSON's strengths explains why it's the default interchange format for extracted document data.

{ } JSON Is the Lingua Franca of Data

JSON (JavaScript Object Notation) is a lightweight, text-based data interchange format. Despite the name, it's language-independent — virtually every programming language can parse and generate it. That universality is exactly why it's the natural target when you extract structured data out of a PDF: whatever you build next — a Python script, a Node service, a spreadsheet importer — will read JSON natively.

📐 Just Six Data Types

JSON's simplicity is its strength. It has only six value types: string, number, boolean, null, object, and array. The extracted output here uses all of them — strings for text, numbers for counts and page indices, objects for structure, and arrays for repeated items like pages, lines, and words.

🌲 Why Nesting Matters

A PDF has a natural hierarchy: a document contains pages, pages contain paragraphs, paragraphs contain lines. JSON's nested objects and arrays map onto that hierarchy perfectly. That's why Full Document mode produces a tree rather than a flat list — it preserves the relationships your downstream code may need.

📜 A Brief Standards Note

JSON was specified by Douglas Crockford in the early 2000s and later standardized as ECMA-404 and RFC 8259. The output of this tool is valid against both — meaning any compliant JSON parser, in any language, will read it without trouble.

🆚 JSON vs CSV vs XML for PDF Data

You could extract PDF data to CSV (great for flat tables, poor for nested structure) or XML (verbose, but supports hierarchy). JSON sits in the sweet spot: it handles nesting like XML but with far less ceremony, and it's the native format for web APIs and JavaScript tooling. For most modern data pipelines, JSON is the path of least resistance.

⚠️ The One Big Caveat: Text-Based PDFs

JSON extraction is only as good as the text inside the PDF. A PDF created from a word processor or export tool contains real, selectable text — extraction is clean. A PDF created by scanning paper contains only images of text, with no actual characters to extract. For those, you need OCR first to convert the images into real text before any JSON tool can do its job.

A Brief History

PDF & JSON Through the Years

How two very different formats — one for fixed layout, one for flexible data — came to be paired in modern extraction workflows.

1993
PDF 1.0 launches
Adobe ships the Portable Document Format. Its strength — pixel-perfect fixed layout — is also what makes data extraction tricky decades later: PDF stores positioned text, not structured data.
2001
JSON is born
Douglas Crockford specifies JSON as a lightweight alternative to XML for data interchange. Its simplicity makes it an instant favourite for web developers.
2006
JSON standardized (RFC 4627)
JSON gets its first formal specification. Adoption accelerates as AJAX-driven web apps need a clean way to pass structured data between server and browser.
2008
PDF becomes ISO 32000-1
PDF is published as an open ISO standard, formally documenting its object model — the foundation that text-extraction libraries rely on.
2011
PDF.js released
Mozilla launches PDF.js, a pure-JavaScript PDF parser and renderer. For the first time, browsers can extract PDF text without a plugin or server.
2013
JSON gets a syntax standard (ECMA-404)
ECMA-404 nails down JSON's grammar precisely. JSON is now the default data format for REST APIs across the entire web.
2017
RFC 8259 — current JSON standard
The latest JSON standard requires UTF-8 and clarifies edge cases. JSON is everywhere: config files, APIs, databases, and document-extraction output.
Today
Browser-native PDF→JSON
Modern browsers run PDF.js to extract text and JavaScript to build JSON entirely client-side. No server, no upload. This tool is built for that reality.
Use Cases

When You'll Want to
Convert PDF to JSON

Turning fixed-layout PDF content into structured JSON unlocks automation everywhere. Here's where it shines.

🤖

Automation Pipelines

Feed PDF content into automation tools (Zapier, Make, custom scripts) that expect structured JSON input rather than raw documents.

🧠

NLP & Machine Learning

Word-by-word mode produces clean tokenised arrays ready for NLP preprocessing, embeddings, or training datasets.

🔌

API Ingestion

Many APIs accept JSON payloads. Convert PDF content to JSON to push document data into a CRM, CMS, or analytics endpoint.

🔎

Search Indexing

Build a search index from a PDF library by extracting line- or word-level JSON and feeding it to Elasticsearch, Algolia, or a custom index.

🧾

Invoice & Receipt Parsing

Extract invoice text to JSON, then run pattern matching on the structured output to pull totals, dates, and line items.

📊

Data Analysis

Load extracted JSON into pandas, R, or a spreadsheet importer to analyse document content programmatically.

🗃️

Document Cataloguing

Metadata-only mode rapidly extracts title, author, and page count from a whole PDF library for a searchable catalogue.

🔄

Format Migration

Move legacy PDF content into a modern database or CMS by first converting it to JSON, then mapping fields to your schema.

🧪

QA & Testing

Extract expected text to JSON to build automated test fixtures that verify a PDF generator's output stays correct over time.

📚

Research Corpora

Researchers convert PDF papers into JSON for text mining, citation analysis, and building structured research datasets.

💬

Chatbot Knowledge Bases

Convert manuals and docs into JSON chunks to feed retrieval-augmented generation (RAG) systems and chatbot knowledge bases.

📈

Reporting Dashboards

Extract figures and text from report PDFs into JSON, then drive a live dashboard or BI tool from the structured data.

🗂️

Content Audits

Convert a batch of PDFs to JSON to audit word counts, detect duplicate content, or compare versions programmatically.

🌐

Localization

Extract text to JSON so translators and localization tools can work with structured strings instead of fixed PDF layouts.

⚙️

ETL Workflows

Use JSON as the "transform" stage in an Extract-Transform-Load pipeline that moves PDF content into a data warehouse.

🧰

Developer Prototyping

Quickly get realistic JSON test data out of a sample PDF when prototyping a document-processing feature.

Format Comparison

JSON vs CSV vs XML vs Plain Text

Four ways to export extracted PDF data. Here's how they compare so you can pick the right target format.

Property { } JSON CSV XML Plain Text
Nested structureExcellentFlat onlyYesNone
Human readableYes (pretty)YesVerboseYes
Web API nativeYesNoLegacyNo
Parse in any languageUniversalUniversalUniversalTrivial
File size overheadLowLowestHighestLowest
Holds metadata cleanlyYesAwkwardYesNo
Good for tablesYesBestOKPoor
Comments supportedNoNoYesN/A
Best forAPIs & nested dataTabular dataLegacy/enterpriseQuick text dumps
Rule of thumb: If your downstream consumer is a web API, JavaScript app, or anything that needs document hierarchy — use JSON. If you're loading a flat table into a spreadsheet, CSV is leaner. XML only makes sense when an existing enterprise system requires it.
Pro Tips

12 Tips for Better PDF→JSON Output

Small choices that make a noticeable difference in how clean and useful your extracted JSON turns out.

Match mode to your consumer

If a script reads line-by-line, use Lines mode. If you need document hierarchy, use Full. Picking the right mode upfront saves transformation code later.

Minify for production payloads

Pretty-print is great for reading, but turn it off (or hit Minify) before sending JSON over the wire — minified payloads are smaller and faster.

Keep Filter Empty Lines on

Blank lines add noise and bloat. Leaving the empty-line filter enabled gives you cleaner arrays with fewer junk entries to handle downstream.

Use page range to test fast

Before processing a 500-page PDF, set End Page to 5 and verify the output shape looks right. Then set it to 0 to process everything.

Drop metadata for pure data

If your pipeline only cares about content, toggle off Include Document Metadata so the JSON root is just your pages/lines/words array.

Keep page numbers for traceability

Leaving Include Page Numbers on lets you trace any extracted line or word back to its source page — invaluable for debugging and audits.

Re-extract instead of re-uploading

Changed your mind about the mode or range? Adjust settings and hit Re-extract — the PDF stays in memory, so it's instant.

Match indent to your codebase

Set indent to 2 or 4 spaces to match your project's style so the downloaded file drops cleanly into version control without reformatting.

Validate before relying on it

Paste the output into a JSON validator (or JSON.parse in your console) to confirm it's well-formed before wiring it into production.

OCR scanned PDFs first

If you get empty output, your PDF is probably scanned images. Run OCR (e.g. OCRmyPDF) to embed real text, then re-upload here.

Words mode for frequency analysis

Word-by-word output drops straight into a counting routine — group by the word field to build a frequency map in a few lines of code.

Name your file meaningfully

Set the output filename to something descriptive like invoice-2025-q1 so your downloads stay organised in data folders.

Who Uses This

Who Converts PDF to JSON Most?

Turning documents into structured data is a daily task across many technical roles.

💻

Software Developers

Pull document content into apps and services that expect JSON, without writing a PDF parser from scratch.

📊

Data Analysts

Extract report and dataset PDFs into JSON for loading into pandas, notebooks, or BI tools for analysis.

🧠

ML & NLP Engineers

Build training corpora and tokenised datasets from PDF documents using word- and line-level extraction.

⚙️

Automation Engineers

Wire PDF content into no-code and low-code automation flows that pass structured JSON between steps.

🔌

Integration Specialists

Map legacy PDF outputs into JSON payloads to bridge old document systems with modern JSON APIs.

🧾

Finance & Accounting

Parse invoices, statements, and receipts into structured JSON for bookkeeping and reconciliation tooling.

🔬

Researchers

Convert academic PDFs to JSON for text mining, citation extraction, and structured research datasets.

📚

Librarians & Archivists

Use metadata-only mode to rapidly catalogue large PDF collections into a searchable JSON index.

🛡️

Compliance Teams

Extract document text to JSON for automated keyword scanning, redaction checks, and audit trails.

📰

Content & SEO Teams

Pull text from PDF assets into JSON to feed CMS imports, content audits, and search indexing.

🧰

QA Engineers

Build test fixtures by extracting known-good PDF text to JSON, then asserting against generator output.

🤝

Operations Teams

Turn recurring PDF reports into JSON to automate dashboards and status feeds without manual re-keying.

Privacy & Security

How Your PDF Is Handled

Transparency matters. Here's exactly what happens when you use this converter.

🔐 Files Are Processed In Your Browser

This tool uses PDF.js by Mozilla — a client-side JavaScript library — to parse your PDF and extract its text. Everything runs inside your browser tab. Your PDF is read from your device, parsed in memory, converted to JSON, and shown back to you without ever leaving your machine.

That means the tool never needs to upload your file to a server to convert it. Speed depends entirely on your device's CPU and available memory, not on a remote service.

🛡️ What You Can Still Watch Out For

Although the extraction logic is local, modern websites do receive normal browser metadata such as your IP address, user agent, and referrer. If you're working with sensitive material — contracts, financial statements, personal records — it's always smart to verify how a tool behaves. You can open your browser's developer tools and inspect the Network tab while extracting to confirm no PDF data is being sent externally.

For background reading on browser security and safe handling of personal files, see the Electronic Frontier Foundation's privacy resources.

🧹 Nothing Stored After You Leave

When you close the browser tab, the PDF bytes and the generated JSON are discarded automatically. There's no account, no cloud storage, no history. Save the JSON to your device before closing the tab if you want to keep it.

🔎 Verify It Yourself

Don't take our word for it. Press F12 (or Cmd+Option+I on Mac) to open developer tools, switch to the Network tab, then drop a PDF and run extraction. You'll see the page's own assets loading, but no outbound request carrying your PDF bytes. That's the difference between a server-side and a client-side tool — and it's auditable in seconds.

What to Expect

Typical PDFs & JSON Output

Rough expectations for common document sizes. Numbers vary with extraction mode, PDF complexity, and device speed.

Source PDF Pages Approx. Words JSON (Full) JSON (Words) Extraction Time*
Invoice / form1 – 2~300~8 KB~12 KB< 1 second
Article5 – 10~3,000~40 KB~70 KB1 – 2 seconds
Whitepaper15 – 30~8,000~110 KB~190 KB2 – 4 seconds
Report40 – 80~20,000~280 KB~480 KB4 – 8 seconds
Book / manual200 – 350~80,000~1.1 MB~1.9 MB15 – 30 seconds
Large technical doc600 – 1,000~200,000~2.8 MB~4.8 MB40 – 90 seconds

*Times measured on a typical 2024-class laptop with pretty-print on. Mobile devices and older hardware will take longer.

Pro tip: Word-by-word mode produces larger JSON than Full mode because each word becomes its own object with a page field. If size matters, minify the output and turn off page numbers.
Heads-up: Very large PDFs (1,000+ pages) build large JSON strings in memory. On low-end devices this can be slow or hit memory limits. Use the page-range controls to process in chunks.
Common Misconceptions

8 PDF-to-JSON Myths — Debunked

A lot of confusion swirls around extracting data from PDFs. Here are the most common myths and the actual truth.

Myth

"Any PDF can be perfectly extracted to JSON."

Truth

Only text-based PDFs extract cleanly. Scanned PDFs are images of text and need OCR first — there are no characters to extract otherwise.

Myth

"Online converters always upload your file."

Truth

Some do — but this one runs entirely in your browser with PDF.js. You can verify it in the DevTools Network tab in seconds.

Myth

"JSON preserves the PDF's visual layout."

Truth

JSON captures text and structure, not pixel positions. If you need exact layout, that's what the PDF itself is for.

Myth

"Tables come out as clean JSON arrays."

Truth

PDF tables are visually-positioned text with no grid metadata. Text extracts, but reconstructing exact rows and columns needs extra processing.

Myth

"Minified JSON is a different format."

Truth

Minified and pretty-printed JSON are identical data — just different whitespace. Any parser reads both the same way.

Myth

"You need a server or API for PDF parsing."

Truth

Modern browsers run PDF.js to parse PDFs entirely client-side. No backend is required for text extraction.

Myth

"Bigger indent means bigger data."

Truth

Indentation only affects file size and readability, never the actual data. Parsed back in, 2-space and 4-space JSON are equal.

Myth

"Password-protected PDFs can be extracted."

Truth

Encrypted PDFs can't be parsed without the password. Remove protection in a PDF editor first, then extract.

Troubleshooting

Common PDF-to-JSON Issues

If your output doesn't look the way you expected, one of these is usually the cause.

📭 "JSON output is empty / no text"

Your PDF was likely created by scanning paper, so it contains images of text rather than real characters. Fix: run the PDF through OCR first (Adobe Acrobat, ABBYY FineReader, or OCRmyPDF) to embed real text, then re-upload here.

🔒 "Failed to load PDF" error

The PDF is probably password-encrypted. Fix: open it in your usual reader, save an unprotected copy, then upload that. Corrupt PDFs also fail — confirm the file opens elsewhere first.

🧩 "Text is jumbled or out of order"

Multi-column layouts, sidebars, and complex page designs can cause text to extract in an unexpected reading order. Fix: the order comes from how the PDF stores text items — for heavy layouts, expect to post-process, or try a single-column source PDF.

📊 "My table lost its structure"

PDF tables are just positioned text with no row/column metadata. The text extracts, but the grid does not. Fix: for table-heavy PDFs, consider a dedicated table-extraction tool, or reconstruct columns from the line text in your own code.

🐌 "Extraction is slow or the tab freezes"

Very large PDFs build big JSON strings in memory. Fix: use the Start/End Page controls to process in smaller chunks, close other tabs, or switch off pretty-print to reduce string size.

❓ "Output isn't valid JSON when I paste it"

The tool always produces valid JSON, but copy/paste through some apps can mangle quotes or whitespace. Fix: use the Download button to get an untouched .json file, or the Copy button which uses the clipboard API directly.

🔢 "Word and line counts look off"

Counts depend on how PDF.js joins text items. Hyphenation, ligatures, and unusual spacing can shift counts slightly. Fix: these are approximate by nature; for exact tokenisation, post-process the extracted text with your own rules.

🌐 "Non-Latin characters look wrong"

Most modern PDFs embed Unicode text that extracts cleanly. Some older PDFs use custom encodings that don't map to real characters. Fix: if a PDF was made with a non-standard font encoding, re-export it from the source with a Unicode-friendly font first.

Also Try

More Free PDF Tools

Explore more free browser-based PDF conversion and manipulation tools.

PDF to JPG PDF to PNG PDF to GIF Rotate PDF Protect PDF PNG to PDF PDF to CSV PDF to EPUB Organize PDF Pages Merge PDFs
External Resources

Trusted JSON & PDF Resources

Curated links to authoritative documentation if you want to go deeper into JSON, PDF, and web technology.

{ }
JSON.orgDouglas Crockford's canonical reference describing the JSON grammar and data types.
📜
RFC 8259The current IETF standard defining the JSON data interchange format.
📐
ECMA-404The ECMA standard formally specifying JSON's syntax.
🧪
PDF.js by MozillaThe open-source library that powers PDF parsing and text extraction in this tool.
📄
ISO 32000-2 (PDF 2.0)The current PDF specification maintained by ISO.
📘
MDN: JSONMozilla's developer guide to JSON.parse, JSON.stringify, and working with JSON in JavaScript.
📂
MDN File APIHow browsers read local files like your PDF entirely on-device.
⎘
MDN Clipboard APIThe browser API used by the Copy button to put JSON on your clipboard.
✅
JSONLintA free online validator to confirm your extracted JSON is well-formed.
🔠
OCRmyPDFOpen-source OCR tool to add a real text layer to scanned PDFs before extraction.
📖
Wikipedia: JSONA comprehensive overview of JSON's history, structure, and ecosystem.
🛡️
EFF Privacy CenterResources on personal data, file security, and online privacy.
Glossary

JSON & PDF Terms Explained

Short, friendly definitions for the technical terms you'll see when working with extracted PDF data.

JSON
JavaScript Object Notation. A lightweight, text-based, language-independent data interchange format.
Object
A JSON value made of key/value pairs in curly braces — used here for document, metadata, and page structures.
Array
An ordered list of JSON values in square brackets — used here for pages, paragraphs, lines, and words.
Key
The name part of a key/value pair in a JSON object, like "page" or "text".
Pretty Print
JSON formatted with indentation and line breaks for human readability.
Minify
Stripping all whitespace from JSON to produce the smallest possible file — ideal for API payloads.
Serialize
Converting an in-memory object into a JSON string, done here with JSON.stringify.
Parse
Converting a JSON string back into a usable object, done with JSON.parse.
Tokenise
Splitting text into individual units (words). Word-by-word mode produces a tokenised array.
Metadata
Data about the document — title, author, producer, page count — rather than its content.
PDF.js
Mozilla's open-source, pure-JavaScript PDF parser and renderer used to extract text here.
getTextContent()
The PDF.js method that returns every text item on a page, used to build the extracted text.
Text Item
A single run of positioned text returned by PDF.js — joined together to form lines and paragraphs.
OCR
Optical Character Recognition. Converts images of text (scans) into real, extractable characters.
Blob
A browser-native object representing immutable binary data. Your PDF and the output JSON both live as Blobs.
ArrayBuffer
A raw binary buffer in JavaScript. Your PDF's bytes are read into one before PDF.js parses them.
Clipboard API
The browser API the Copy button uses to place your JSON onto the system clipboard.
UTF-8
The Unicode text encoding required by modern JSON, supporting virtually every language and symbol.
Schema
The expected shape of a JSON document — which keys exist and what types their values are.
ETL
Extract, Transform, Load — a data pipeline pattern where PDF→JSON often serves as the extract/transform stage.
FAQ

PDF to JSON — Common Questions

Everything you need to know about converting PDF data to structured JSON format online.

Is this PDF to JSON converter really free?
Yes, completely free with no signup, no subscription, and no usage limits. Convert as many PDFs as you need, as many times as you like, with no restrictions or hidden fees.
Is my PDF file uploaded to a server?
No. The entire extraction process runs locally in your browser using PDF.js. Your file never leaves your device — there is no server processing, no cloud upload, and no data retention of any kind.
Which extraction mode should I choose?
Use Full Document for rich structured output with metadata and page hierarchy. Use Line by Line for logs or reports. Use Word by Word for NLP or text analysis pipelines. Use Metadata Only for cataloguing or indexing document collections.
Will scanned PDFs work with this tool?
Scanned PDFs contain images rather than text, so no text can be extracted directly. This tool works best with text-based PDFs. For scanned documents, OCR software is required before converting to JSON.
What is the difference between pretty print and minified JSON?
Pretty print formats the JSON with indentation and line breaks for easy human reading. Minified JSON removes all whitespace to produce the smallest possible file size — ideal for API payloads and data pipelines.
Can I extract only specific pages to JSON?
Yes. Use the Start Page and End Page fields to extract any page range from your PDF. Set End Page to 0 to include all pages from the start page to the end of the document.
Is the output valid JSON?
Yes. The output is produced by JavaScript's built-in JSON.stringify, so it is always valid against the JSON standard (RFC 8259). You can confirm it in any JSON validator or by running JSON.parse on it.
Why is my Word-by-Word JSON so large?
Each word becomes its own object (with a page field if enabled), so the structural overhead adds up. Minify the output and turn off page numbers to shrink it considerably.
Can I edit the JSON before downloading?
The viewer is read-only to protect the extracted data, but you can copy it, paste it into your editor, and modify it there. The Format and Minify buttons let you reshape the whitespace in place.
Does it preserve tables and columns?
Table text is extracted, but the grid structure is not — PDF tables are just positioned text with no row/column metadata. Reconstructing exact tables requires extra processing in your own code.
What metadata fields are extracted?
Title, author, subject, creator, producer, PDF version, total page count, and creation date — whatever the PDF's info dictionary contains. Missing fields are returned as null.
Can I re-run with different settings without re-uploading?
Yes. Change the mode, toggles, or page range, then click "Re-extract with New Settings". Your PDF stays loaded in memory and re-processes instantly.
What indent sizes are available?
2 spaces (default), 4 spaces, 1 space, or a tab character. Indentation only affects readability and file size — never the underlying data.
Is there a maximum PDF size?
There's no hard cap — your device's memory is the practical limit. Laptops handle large documents fine; phones may struggle with very large technical manuals.
Why is the text order sometimes wrong?
Extraction order follows how text items are stored in the PDF. Multi-column layouts and complex designs can produce unexpected reading order — single-column source PDFs extract most predictably.
Can I convert password-protected PDFs?
No. Encrypted PDFs cannot be parsed without the password. Remove the protection using a PDF editor first, then upload the unprotected copy.
Does the Copy button work everywhere?
It uses the modern Clipboard API where available, with a fallback for older browsers. If copy ever fails, use the Download button to get the JSON file directly.
Will it work offline?
After the page loads once, PDF.js is cached, so extraction usually works on flaky connections. The first visit needs internet to load the library.
What browsers are supported?
All modern Chromium browsers (Chrome, Edge, Brave, Arc, Opera), Firefox, and Safari versions from the past 3 years work smoothly.
Can I use the JSON commercially?
Yes. The JSON is your data, extracted from your document. There are no restrictions on how you use the output from this tool.