Building a "Search Inside PDF" Feature for Your Web App
Ever uploaded a 200-page PDF and needed to find where it mentions "Total" or "Error"? Scrolling through pages manually is painful. Building full-text search from scratch means parsing PDFs, indexing content, and handling edge cases.
There is a much simpler approach: use an API that does the heavy lifting. In this tutorial, we will build a Python function that searches inside any PDF and returns the exact page numbers and context lines where your search term appears.
Quick Start: Search a PDF in 10 Lines
import requests
response = requests.post(
'https://apdf.io/api/pdf/content/search',
headers={
'Authorization': 'Bearer YOUR_API_TOKEN',
'Accept': 'application/json',
'Content-Type': 'application/json'
},
json={
'file': 'https://example.com/document.pdf',
'text': 'invoice'
}
)
print(response.json())Real-World Use Case: Support Ticket Search
Imagine you are building a support dashboard. Customers upload PDF documents (contracts, invoices, error logs), and your team needs to quickly find specific information without opening each file.
Let us build a reusable function that:
- Takes a PDF URL and search term
- Calls the Apdf Search API
- Returns a clean summary of matches
Step 1: Get Your API Token
- Go to Apdf and sign up (free).
- Copy your API Token from the dashboard.
Install the requests library if you have not already:
pip install requestsStep 2: The Search Function
import requests
API_TOKEN = "YOUR_API_TOKEN"
API_URL = "https://apdf.io/api/pdf/content/search"
def search_pdf(pdf_url, search_term, case_sensitive=False, use_regex=False):
"""
Search for a term inside a PDF and return matches with context.
Args:
pdf_url: URL of the PDF file to search
search_term: Text to search for
case_sensitive: Set True for case-sensitive matching
use_regex: Set True to interpret search_term as a regex pattern
Returns:
dict with search results or error message
"""
payload = {
'file': pdf_url,
'text': search_term
}
if case_sensitive:
payload['case'] = '1'
if use_regex:
payload['regex'] = '1'
try:
response = requests.post(
API_URL,
headers={
'Authorization': f'Bearer {API_TOKEN}',
'Accept': 'application/json',
'Content-Type': 'application/json'
},
json=payload
)
if response.status_code == 200:
return response.json()
else:
return {'error': f'API returned {response.status_code}: {response.text}'}
except Exception as e:
return {'error': str(e)}
def print_results(results):
"""Pretty-print search results."""
if 'error' in results:
print(f"Error: {results['error']}")
return
print(f"\nSearch term: '{results['search_text']}'")
print(f"Total matches: {results['results_total']}")
print(f"Pages with matches: {results['results_pages']}\n")
if results['results']:
for match in results['results']:
print(f" Page {match['page']}: ...{match['matched_line']}...")
print(f" Matched: '{match['exact_word']}'\n")
else:
print(" No matches found.")
# Example usage
if __name__ == "__main__":
pdf_url = "https://pdfobject.com/pdf/sample.pdf"
# Basic search
print("=== Basic Search ===")
results = search_pdf(pdf_url, "PDF")
print_results(results)
# Regex search: find words starting with capital letter
print("\n=== Regex Search ===")
results = search_pdf(pdf_url, "[A-Z][a-z]+", use_regex=True)
print_results(results)Run the Script
python pdf_search.pyOutput
=== Basic Search ===
Search term: 'PDF'
Total matches: 2
Pages with matches: 1
Page 1: ...Sample PDF...
Matched: 'PDF'
Page 1: ...This is a simple PDF file. Fun fun fun....
Matched: 'PDF'
=== Regex Search ===
Search term: '[A-Z][a-z]+'
Total matches: 36
Pages with matches: 1
Page 1: ...Sample PDF...
Matched: 'Sample'
Page 1: ...This is a simple PDF file. Fun fun fun....
Matched: 'This'
... (more matches)Step 3: Add a Simple Web Interface (Optional)
Want to let users search PDFs from a web form? Here is a minimal Flask app:
from flask import Flask, request, jsonify, render_template_string
import requests
app = Flask(__name__)
API_TOKEN = "YOUR_API_TOKEN"
TEMPLATE = """
<!DOCTYPE html>
<html>
<head><title>PDF Search</title></head>
<body style="font-family: sans-serif; max-width: 600px; margin: 50px auto;">
<h1>Search Inside PDF</h1>
<form method="POST">
<input name="pdf_url" placeholder="PDF URL" style="width: 100%; padding: 10px; margin: 5px 0;" required>
<input name="search_term" placeholder="Search term" style="width: 100%; padding: 10px; margin: 5px 0;" required>
<button type="submit" style="padding: 10px 20px;">Search</button>
</form>
{% if results %}
<div style="margin-top: 20px; padding: 15px; background: #f5f5f5;">
<strong>Found {{ results.results_total }} matches on {{ results.results_pages }} page(s)</strong>
<ul>
{% for match in results.results %}
<li>Page {{ match.page }}: "{{ match.matched_line }}"</li>
{% endfor %}
</ul>
</div>
{% endif %}
</body>
</html>
"""
@app.route('/', methods=['GET', 'POST'])
def search():
results = None
if request.method == 'POST':
response = requests.post(
'https://apdf.io/api/pdf/content/search',
headers={
'Authorization': f'Bearer {API_TOKEN}',
'Accept': 'application/json',
'Content-Type': 'application/json'
},
json={
'file': request.form['pdf_url'],
'text': request.form['search_term']
}
)
results = response.json()
return render_template_string(TEMPLATE, results=results)
if __name__ == '__main__':
app.run(debug=True)Run it with python app.py and open http://localhost:5000.
API Response Explained
The Search API returns a JSON object with these fields:
{
"search_text": "invoice",
"results_total": 5,
"results_pages": 2,
"results": [
{
"page": "1",
"matched_line": "Invoice #12345 dated November 2025",
"exact_word": "Invoice"
},
{
"page": "3",
"matched_line": "Please pay this invoice within 30 days",
"exact_word": "invoice"
}
]
}- search_text: The term you searched for
- results_total: Total number of matches found
- results_pages: Number of pages containing at least one match
- results: Array of match objects with page number, the full line of text, and the exact matched word
Next Steps
- Extract Full Text: Use the Read Content endpoint to extract all text from specific pages for further processing.
- Jump to Specific Pages: Once you know which pages contain matches, use the Extract Pages endpoint to create a new PDF with only the relevant pages.
Related tutorials
Search a PDF From Your Editor
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Add Page Numbers and Headers to PDFs with Python
Add consistent page numbers, headers, or footers to existing PDF documents using Python and the Apdf Overlay API. Perfect for preparing reports for distribution without regenerating the original documents.
Convert Scanned PDFs to Searchable Documents with Python
Transform image-based scanned PDFs into fully searchable documents using Python and the Apdf OCR API. Perfect for digitizing paper archives, enabling text selection, and making legacy documents ready for modern search systems.
Your code made the PDF.
Then it went dark.
Opened, read, re-read, dropped on page 4 — you never see any of it. Share the PDFs you generate through Apdf recipient links, and every signal becomes something you can act on: ping Slack, update the CRM, let an agent follow up. Same account, same API token, one more call.
API · Webhook · MCP