peasy-document 0.1.1

Document conversion library — Markdown, HTML, CSV, and JSON transformations with zero heavyweight dependencies.

peasy-document

Pure Python document conversion library with 10 conversion functions across 6 formats — Markdown, HTML, CSV, JSON, YAML, and plain text. Convert between document formats with frozen dataclass results, full conversion metadata, and only one lightweight dependency (markdown). Handles strings, bytes, and file paths uniformly through a single TextInput type, so you never have to worry about I/O boilerplate.

Built from the document conversion engine behind PeasyDocument, which provides interactive browser-based tools for Markdown to HTML conversion, CSV to JSON transformation, and HTML to Markdown extraction. The library covers 10 conversion paths with sub-millisecond performance for typical documents.

Try the interactive tools at peasydocument.com — Markdown to HTML, CSV to JSON, HTML to Text, JSON to YAML, CSV to Markdown Table

Table of Contents

• Install
• Quick Start
• What You Can Do
  • Markdown to HTML Conversion
  • HTML Processing and Extraction
  • CSV and JSON Transformation
  • JSON to YAML Conversion
  • Table Formatting and Rendering
• Command-Line Interface
• API Reference
  • Conversion Functions
  • Types
• Learn More About Document Conversion
• Peasy Developer Tools
• License

Install

# Core library (only markdown dependency)
pip install peasy-document

# With CLI support
pip install "peasy-document[cli]"

# Everything
pip install "peasy-document[all]"

Quick Start

from peasy_document import markdown_to_html, csv_to_json, html_to_text

# Convert Markdown to HTML with tables, code highlighting, and TOC support
result = markdown_to_html("# Hello World\n\nThis is **bold** text.")
print(result.content)
# <h1>Hello World</h1>
# <p>This is <strong>bold</strong> text.</p>

# Convert CSV data to JSON array of objects
result = csv_to_json("name,age\nAlice,30\nBob,25")
print(result.content)
# [{"name": "Alice", "age": "30"}, {"name": "Bob", "age": "25"}]

# Strip HTML to plain text — removes all tags and decodes entities
result = html_to_text("<h1>Title</h1><p>Hello &amp; welcome.</p>")
print(result.content)
# Title
# Hello & welcome.

All functions return frozen dataclasses with conversion metadata — source format, target format, and byte sizes before and after conversion:

# Every ConversionResult carries metadata about the transformation
result = markdown_to_html("# Hello")
print(result.source_format)  # "markdown"
print(result.target_format)  # "html"
print(result.source_size)    # 7 (bytes of input)
print(result.target_size)    # 18 (bytes of output)

What You Can Do

Markdown to HTML Conversion

Markdown is the de facto standard for developer documentation, README files, and technical writing. Defined by the CommonMark specification, Markdown provides a lightweight syntax that maps cleanly to HTML. peasy-document uses the battle-tested Python-Markdown library under the hood, with sensible defaults that cover the most common use cases out of the box.

Feature	Extension	Enabled by Default
Pipe tables	tables	Yes
Fenced code blocks	fenced_code	Yes
Syntax highlighting	codehilite	Yes
Table of contents	toc	Yes
Custom extensions	Pass any Python-Markdown extension	Via extensions= kwarg

from peasy_document import markdown_to_html

# Convert Markdown with default extensions: tables, fenced_code, codehilite, toc
result = markdown_to_html("""
# API Documentation

| Method | Endpoint | Description |
|--------|----------|-------------|
| GET    | /users   | List users  |
| POST   | /users   | Create user |

```python
import requests
response = requests.get("/users")
\```
""")

# Override extensions for minimal output (tables + toc only)
result = markdown_to_html("content", extensions=["tables", "toc"])

Accepts str, bytes, or Path objects — read from files or process raw data without boilerplate:

from pathlib import Path

# Read Markdown from a file and convert to HTML
result = markdown_to_html(Path("README.md"))

# Process binary content from an HTTP response or database blob
result = markdown_to_html(b"# Binary input works too")

Learn more: Markdown to HTML Tool · Markdown Syntax Guide · CommonMark Specification

HTML Processing and Extraction

HTML is the backbone of the web, but extracting useful content from HTML documents often requires stripping tags, decoding entities (& to &, < to <), and ignoring non-content elements like <script> and <style> blocks. peasy-document provides two extraction paths: HTML to plain text for content indexing, and HTML to Markdown for content migration or CMS workflows.

Both functions use Python's stdlib html.parser — no external dependencies like BeautifulSoup or lxml required.

Conversion	Use Case	Tags Handled
HTML to Text	Search indexing, content extraction, text analysis	Strips all tags, decodes entities, ignores <script>/<style>
HTML to Markdown	CMS migration, content republishing, documentation conversion	p, h1-h6, a, strong/b, em/i, ul/ol/li, code, pre, br, img
Text to HTML	Plain text formatting, email body generation	Wraps paragraphs in <p>, converts single newlines to <br>

from peasy_document import html_to_text, html_to_markdown, text_to_html

# Strip HTML to plain text — useful for search indexing and content analysis
result = html_to_text("""
<html>
<head><title>Page</title></head>
<body>
  <h1>Welcome</h1>
  <p>This is a <strong>formatted</strong> document with &amp; entities.</p>
  <script>alert('ignored')</script>
</body>
</html>
""")
print(result.content)
# Welcome
# This is a formatted document with & entities.

# Convert HTML to Markdown — preserves links, emphasis, headings, and lists
result = html_to_markdown("""
<h1>Document Title</h1>
<p>Visit <a href="https://example.com">our site</a> for <strong>more info</strong>.</p>
<ul>
  <li>First item</li>
  <li>Second item</li>
</ul>
""")
print(result.content)
# # Document Title
# Visit [our site](https://example.com) for **more info**.
# - First item
# - Second item

# Convert plain text to HTML paragraphs — double newlines become <p> tags
result = text_to_html("First paragraph.\n\nSecond paragraph.\nWith a line break.")
print(result.content)
# <p>First paragraph.</p>
# <p>Second paragraph.<br>With a line break.</p>

Learn more: HTML to Text Tool · HTML to Markdown Tool · HTML Entity Reference

CSV and JSON Transformation

CSV (Comma-Separated Values) and JSON (JavaScript Object Notation) are the two most common data interchange formats. CSV, defined in RFC 4180, represents tabular data with rows and columns. JSON, specified in RFC 8259, represents structured data as nested objects and arrays. Converting between these two formats is one of the most frequent tasks in data processing pipelines, API integrations, and ETL workflows.

peasy-document handles both directions using Python's stdlib csv and json modules — no pandas or external data libraries required.

Direction	Input Format	Output Format	Key Features
CSV to JSON	RFC 4180 CSV with header row	JSON array of objects	Custom delimiters, header-keyed objects
JSON to CSV	JSON array of objects	CSV with auto-detected headers	Handles inconsistent keys across objects

from peasy_document import csv_to_json, json_to_csv

# CSV to JSON — each row becomes a JSON object keyed by header values
result = csv_to_json("name,role,team\nAlice,Engineer,Backend\nBob,Designer,Frontend")
print(result.content)
# [
#   {"name": "Alice", "role": "Engineer", "team": "Backend"},
#   {"name": "Bob", "role": "Designer", "team": "Frontend"}
# ]

# Roundtrip: JSON back to CSV preserves column order
result = json_to_csv(result.content)
print(result.content)
# name,role,team
# Alice,Engineer,Backend
# Bob,Designer,Frontend

# Tab-separated values (TSV) — pass any single-character delimiter
result = csv_to_json("name\tage\nAlice\t30", delimiter="\t")

# Handles inconsistent keys gracefully — union of all keys becomes the header
result = json_to_csv('[{"a": 1, "b": 2}, {"b": 3, "c": 4}]')
# → a,b,c header with empty cells where keys are missing

Learn more: CSV to JSON Tool · JSON to CSV Tool · RFC 4180 CSV Standard

JSON to YAML Conversion

YAML (YAML Ain't Markup Language) is widely used for configuration files — Kubernetes manifests, Docker Compose files, CI/CD pipelines, and infrastructure-as-code tools all rely on YAML's human-readable format. Converting JSON to YAML is a common need when moving between API responses (JSON) and configuration files (YAML).

peasy-document implements JSON-to-YAML conversion with a recursive pure-Python renderer. No PyYAML dependency is required. The converter handles nested objects, arrays, strings, numbers, booleans, and null values. Special characters in strings are automatically quoted per the YAML 1.2 specification.

YAML Feature	Supported	Notes
Nested objects	Yes	Indented with 2 spaces
Arrays	Yes	Block sequence style (- item)
Strings with special chars	Yes	Auto-quoted (":", "#", brackets, etc.)
Reserved words	Yes	true, false, null, yes, no are quoted when used as strings
Numbers and booleans	Yes	Rendered without quotes

from peasy_document import json_to_yaml

# Convert a JSON config object to YAML — handles nested structures
result = json_to_yaml('{"server": {"host": "localhost", "port": 8080}, "debug": true}')
print(result.content)
# server:
#   host: localhost
#   port: 8080
# debug: true

# Arrays render as YAML block sequences
result = json_to_yaml('{"tags": ["python", "yaml", "json"], "count": 3}')
print(result.content)
# tags:
#   - python
#   - yaml
#   - json
# count: 3

# Special characters in values are auto-quoted for YAML safety
result = json_to_yaml('{"url": "https://example.com:8080/path#section"}')
print(result.content)
# url: "https://example.com:8080/path#section"

Learn more: JSON to YAML Tool · YAML vs JSON Guide · YAML 1.2 Specification

Table Formatting and Rendering

Tabular data can be rendered in multiple output formats depending on the target platform — Markdown tables for documentation, HTML tables for web pages, or structured TableData objects for programmatic access. peasy-document provides three rendering paths from CSV input, all using Python's stdlib csv module.

Function	Output	Use Case
csv_to_table()	TableData dataclass	Programmatic access to headers, rows, dimensions
csv_to_markdown()	Pipe-aligned Markdown table	GitHub README, documentation, Jupyter notebooks
csv_to_html()	<table> with <thead>/<tbody>	Web pages, email templates, reports

from peasy_document import csv_to_table, csv_to_markdown, csv_to_html

# Parse CSV into structured TableData — access headers, rows, and dimensions
table = csv_to_table("Name,Age,City\nAlice,30,NYC\nBob,25,LA")
print(table.headers)       # ['Name', 'Age', 'City']
print(table.row_count)     # 2
print(table.column_count)  # 3
print(table.rows[0])       # ['Alice', '30', 'NYC']

# Render as Markdown table with aligned columns
result = csv_to_markdown("Name,Age,City\nAlice,30,NYC\nBob,25,LA")
print(result.content)
# | Name  | Age | City |
# | ----- | --- | ---- |
# | Alice | 30  | NYC  |
# | Bob   | 25  | LA   |

# Render as HTML table with proper thead/tbody structure
result = csv_to_html("Name,Age\nAlice,30")
print(result.content)
# <table>
#   <thead>
#     <tr>
#       <th>Name</th>
#       <th>Age</th>
#     </tr>
#   </thead>
#   <tbody>
#     <tr>
#       <td>Alice</td>
#       <td>30</td>
#     </tr>
#   </tbody>
# </table>

Learn more: CSV to Markdown Tool · CSV to HTML Tool · Table Formatting Guide

Command-Line Interface

Install with CLI support: pip install "peasy-document[cli]"

The CLI exposes 6 conversion commands. All commands write to stdout by default — use -o / --output to write to a file.

# Convert Markdown to HTML
peasy-document md-to-html README.md -o output.html

# Strip HTML to plain text
peasy-document html-to-text page.html

# Convert CSV to JSON
peasy-document csv-to-json data.csv -o data.json

# Convert JSON array to CSV
peasy-document json-to-csv records.json -o records.csv

# CSV to Markdown table
peasy-document csv-to-markdown data.csv

# HTML to Markdown
peasy-document html-to-markdown page.html -o page.md

Command	Description	Options
md-to-html	Convert Markdown file to HTML	-o OUTPUT
html-to-text	Strip HTML tags, extract plain text	-o OUTPUT
csv-to-json	Convert CSV to JSON array of objects	-o OUTPUT, -d DELIMITER
json-to-csv	Convert JSON array to CSV	-o OUTPUT
csv-to-markdown	Render CSV as Markdown table	-o OUTPUT, -d DELIMITER
html-to-markdown	Convert HTML to Markdown	-o OUTPUT

API Reference

Conversion Functions

Function	Input	Output	Dependencies
markdown_to_html(source, *, extensions=None)	Markdown	HTML	markdown library
html_to_text(source)	HTML	Plain text	stdlib only
html_to_markdown(source)	HTML	Markdown	stdlib only
text_to_html(source)	Plain text	HTML	stdlib only
csv_to_json(source, *, delimiter=",")	CSV	JSON	stdlib only
json_to_csv(source)	JSON	CSV	stdlib only
csv_to_table(source, *, delimiter=",")	CSV	TableData	stdlib only
csv_to_markdown(source, *, delimiter=",")	CSV	Markdown table	stdlib only
csv_to_html(source, *, delimiter=",")	CSV	HTML table	stdlib only
json_to_yaml(source)	JSON	YAML	stdlib only

All functions accept TextInput (str | bytes | Path) and return ConversionResult or TableData.

Types

Type	Description	Fields
TextInput	Union type alias	str | bytes | Path
ConversionResult	Frozen dataclass — conversion output with metadata	content: str, source_format: str, target_format: str, source_size: int, target_size: int
TableData	Frozen dataclass — structured table representation	headers: list[str], rows: list[list[str]], row_count: int, column_count: int

Learn More About Document Conversion

• Tools: Markdown to HTML · CSV to JSON · HTML to Text · JSON to YAML · HTML to Markdown
• Tables: CSV to Markdown Table · CSV to HTML Table · JSON to CSV
• Guides: Markdown Syntax Guide · YAML vs JSON · Table Formatting
• Standards: CommonMark Spec · RFC 4180 (CSV) · RFC 8259 (JSON) · YAML 1.2
• npm: @aspect-build/peasy-document (TypeScript version)

Peasy Developer Tools

Part of the Peasy Tools developer tools ecosystem.

Package	PyPI	Description
peasy-document	PyPI	Document conversion — Markdown, HTML, CSV, JSON, YAML — peasydocument.com
peasy-pdf	PyPI	PDF manipulation and conversion — peasypdf.com
peasy-image	PyPI	Image format conversion and optimization — peasyimage.com
peasytext	PyPI	Text analysis and transformation — peasytext.com
peasy-css	PyPI	CSS minification and processing — peasycss.com
peasy-compress	PyPI	File compression utilities — peasytools.com
peasy-video	PyPI	Video processing and conversion — peasyvideo.com
peasy-audio	PyPI	Audio processing and conversion — peasyaudio.com
peasy-convert	PyPI	Unified CLI for all Peasy tools — peasytools.com
peasy-mcp	PyPI	Unified MCP hub for AI assistants — peasytools.com

License

MIT