How to convert DOC to PDF from URL asynchronously for DOC to PDF API in Python using Web API

How to convert DOC to PDF from URL asynchronously for DOC to PDF API in Python: Step By Step Instructions

These source code samples are listed and grouped by their programming language and functions they use. Web API helps with DOC to PDF API in Python. Web API is 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.

Python code snippet like this for Web API works best when you need to quickly implement DOC to PDF API in your Python application. This Python sample code can be used by copying and pasting into your project. Once done,just compile your project and click Run. Further improvement of the code will make it more robust.

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""" 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 API_KEY = "******************************************" # Base URL for Web API requests BASE_URL = "" # Direct URL of source DOC file. SourceFileURL = "" # Destination PDF file name DestinationFile = ".\\result.pdf" # (!) Make asynchronous job Async = True def main(args = None): convertDocToPDF(SourceFileURL, DestinationFile) def convertDocToPDF(uploadedFileUrl, destinationFile): """Converts DOC To PDF using Web API""" # Prepare URL for 'DOC To PDF' API request url = "{}/pdf/convert/from/doc?async={}&name={}&url={}".format( BASE_URL, Async, os.path.basename(destinationFile), uploadedFileUrl ) # Execute request and get response as JSON response = requests.get(url, headers={ "x-api-key": API_KEY, "content-type": "application/octet-stream" }) 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("%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()



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