Make Searchable PDF From URL Asynchronously - Python
PDF Make Text Searchable or Unsearchable sample in Python demonstrating ‘Make Searchable PDF From URL Asynchronously’
MakeSearchablePdfFromUrlAsynchronously.py
""" Cloud API asynchronous "PDF To Text" job example.
Allows to avoid timeout errors when processing huge or scanned PDF documents.
"""
import os
import requests # pip install requests
import time
import datetime
# The authentication key (API Key).
# Get your own by registering at https://app.pdf.co
API_KEY = "******************************************"
# Base URL for PDF.co Web API requests
BASE_URL = "https://api.pdf.co/v1"
# Direct URL of source PDF file.
# You can also upload your own file into PDF.co and use it as url. Check "Upload File" samples for code snippets: https://github.com/bytescout/pdf-co-api-samples/tree/master/File%20Upload/
SourceFileURL = "https://bytescout-com.s3.amazonaws.com/files/demo-files/cloud-api/pdf-make-searchable/sample.pdf"
# Comma-separated list of page indices (or ranges) to process. Leave empty for all pages. Example: '0,2-5,7-'.
Pages = ""
# PDF document password. Leave empty for unprotected documents.
Password = ""
# Destination PDF file name
DestinationFile = ".\\result.pdf"
# OCR language. "eng", "fra", "deu", "spa" supported currently. Let us know if you need more.
Language = "eng"
# (!) Make asynchronous job
Async = True
def main(args = None):
makeSearchablePDF(SourceFileURL, DestinationFile)
def makeSearchablePDF(uploadedFileUrl, destinationFile):
"""Make Searchable PDF using PDF.co Web API"""
# Prepare requests params as JSON
# See documentation: https://apidocs.pdf.co
parameters = {}
parameters["async"] = Async
parameters["name"] = os.path.basename(destinationFile)
parameters["password"] = Password
parameters["pages"] = Pages
parameters["lang"] = Language
parameters["url"] = uploadedFileUrl
# Prepare URL for 'Make Searchable PDF' API request
url = "{}/pdf/makesearchable".format(BASE_URL)
# Execute request and get response as JSON
response = requests.post(url, data=parameters, headers={ "x-api-key": API_KEY })
if (response.status_code == 200):
json = response.json()
if json["error"] == False:
# Asynchronous job ID
jobId = json["jobId"]
# URL of the result file
resultFileUrl = json["url"]
# Check the job status in a loop.
# If you don't want to pause the main thread you can rework the code
# to use a separate thread for the status checking and completion.
while True:
status = checkJobStatus(jobId) # Possible statuses: "working", "failed", "aborted", "success".
# Display timestamp and status (for demo purposes)
print(datetime.datetime.now().strftime("%H:%M.%S") + ": " + status)
if status == "success":
# Download result file
r = requests.get(resultFileUrl, stream=True)
if (r.status_code == 200):
with open(destinationFile, 'wb') as file:
for chunk in r:
file.write(chunk)
print(f"Result file saved as \"{destinationFile}\" file.")
else:
print(f"Request error: {response.status_code} {response.reason}")
break
elif status == "working":
# Pause for a few seconds
time.sleep(3)
else:
print(status)
break
else:
# Show service reported error
print(json["message"])
else:
print(f"Request error: {response.status_code} {response.reason}")
def checkJobStatus(jobId):
"""Checks server job status"""
url = f"{BASE_URL}/job/check?jobid={jobId}"
response = requests.get(url, headers={ "x-api-key": API_KEY })
if (response.status_code == 200):
json = response.json()
return json["status"]
else:
print(f"Request error: {response.status_code} {response.reason}")
return None
if __name__ == '__main__':
main()
PDF.co Web API: the Web API with a set of tools for documents manipulation, data conversion, data extraction, splitting and merging of documents. Includes image recognition, built-in OCR, barcode generation and barcode decoders to decode bar codes from scans, pictures and pdf.
Download Source Code (.zip)
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