Retrieving Buddhist Text Commentaries Using Pecha.org api: A Step-by-Step Guide

🚀 WG སྡེ་ཚན། 💁‍♂️ Pecha API WG
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Retrieving Buddhist Text Commentaries Using Pecha.org Api: A Step-by-Step Guide

In this tutorial, we’ll explore how to use Python to fetch Buddhist text commentaries and their related content using a simple API on Pecha.org. This code is particularly useful for researchers, scholars, and developers working with Buddhist texts and their commentaries that are available on Pecha.org.

Prerequisites

Before we begin, make sure you have:

Understanding the Code Structure

The code is organized into three main functions:

  1. fetch_commentary_content(): Retrieves specific commentary content
  2. call_root_text_related_content(): Makes API calls to get related content
  3. extract_commentary_refs(): Extracts commentary references from the API response

How to Use the Code

1. Basic Setup

First, import the required libraries and set your base URL:

import requests
import json

BASE_URL = "http://127.0.0.1:8000"  # Use local server
# BASE_URL = "https://pecha.org"     # Or use online server

2. Specifying Your Text

To retrieve commentaries, you need to specify:

  • The root text name
  • The segment you’re interested in
root_text_name = "The Way of the Boddhisattva"
root_text_segments = "2.1"  # Format: chapter.verse
root_text_segment_path = f'{root_text_name}.{root_text_segments}'

3. Retrieving Commentaries

The code follows this process:

  1. Fetches related content for the specified text segment
  2. Extracts commentary references
  3. Retrieves the actual commentary content
  4. Organizes everything in a dictionary
commentaries_list = []
root_commentary_dict = {}

# Get related content
api_url = f'{BASE_URL}/api/related/{root_text_segment_path}'
root_text_response = call_root_text_related_content(api_url)

# Process the response
if root_text_response:
    commentary_refs = extract_commentary_refs(root_text_response)
    for ref in commentary_refs:
        content = fetch_commentary_content(ref)
        commentaries_list.append(content)

# Store results
root_commentary_dict[root_text_segment_path] = commentaries_list

Example Output

The code returns a dictionary with the following structure:

{
    "Root_Text.2.1": [
        "commentary.2.1.2": {
            "text": "English commentary text...",
            "he": "Tibetan commentary text..."
        },
        # Additional commentaries...
    ]
}

Customization Options

  1. Change the Text Source:

    • Modify root_text_name and root_text_segments to fetch different texts
    • Example: root_text_name = "Different Text", root_text_segments = "1.1"

  2. Switch Between Servers:

    • Local development: BASE_URL = "http://127.0.0.1:8000"
    • Production: BASE_URL = "https://pecha.org"

  3. Error Handling:

    • The code includes built-in error handling for API calls and JSON parsing
    • Failed requests return None and print error messages
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