ByteScout Cloud API Server – PDF Optimization API – Python – Optimize PDF From URL Asynchronously

Home
/
Articles
/
ByteScout Cloud API Server – PDF Optimization API – Python – Optimize PDF From URL Asynchronously

printable version:
ByteScout-Cloud-API-Server-Python-Optimize-PDF-From-URL-Asynchronously.pdf

How to optimize PDF from URL asynchronously for PDF optimization API in Python with ByteScout Cloud API Server

Step-by-step tutorial:How to optimize PDF from URL asynchronously to have PDF optimization API in Python

Every ByteScout tool includes sample Python source codes that you can find here or in the folder with installed ByteScout product. ByteScout Cloud API Server was designed to assist PDF optimization API in Python. ByteScout Cloud API Server is API server that is ready to use and can be installed and deployed in less than 30 minutes on your own Windows server or server in a cloud. It can save data and files on your local server-based file storage or in Amazon AWS S3 storage. Data is processed solely on the API server and is powered by ByteScout engine, no cloud services or Internet connection is required for data processing..

This simple and easy to understand sample source code in Python for ByteScout Cloud API Server contains different functions and options you should do calling the API to implement PDF optimization API. Follow the tutorial and copy – paste code for Python into your project’s code editor. Enjoy writing a code with ready-to-use sample Python codes to implement PDF optimization API using ByteScout Cloud API Server.

Free! Free! Free! ByteScout free trial version is available for FREE download from our website. Programming tutorials along with source code samples are assembled.

On-demand (REST Web API) version:
Web API (on-demand version)

On-premise offline SDK for Windows:
60 Day Free Trial (on-premise)

OptimizePdfFromUrlAsynchronously.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

# Please NOTE: In this sample we're assuming Cloud Api Server is hosted at "https://localhost". 
# If it's not then please replace this with with your hosting url.

# Base URL for PDF.co Web API requests
BASE_URL = "https://localhost"

# Direct URL of source PDF file.
SourceFileURL = "https://bytescout-com.s3.amazonaws.com/files/demo-files/cloud-api/pdf-optimize/sample.pdf"
# PDF document password. Leave empty for unprotected documents.
Password = ""
# Destination PDF file name
DestinationFile = ".\\result.pdf"
# (!) Make asynchronous job
Async = True


def main(args = None):
    optimizePDF(SourceFileURL, DestinationFile)


def optimizePDF(uploadedFileUrl, destinationFile):
    """Optimize PDF using PDF.co Web API"""

    # Prepare URL for 'Optimize PDF' API request
    url = "{}/pdf/optimize?async={}&name={}&password={}&url={}".format(
        BASE_URL,
        Async,
        os.path.basename(destinationFile),
        Password,
        uploadedFileUrl
    )

    # Execute request and get response as JSON
    response = requests.get(url, headers={  "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(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)
    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()