ByteScout Cloud API Server – Delete Text From PDF – Python – Delete PDF Text From URL Asynchronously

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DeletePdfTextFromUrlAsynchronously.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.

# The authentication key (API Key).
# Get your own by registering at https://app.pdf.co/documentation/api
API_KEY = "******************************************"

# 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-split/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):
    deleteTextFromPdf(SourceFileURL, DestinationFile)


def deleteTextFromPdf(uploadedFileUrl, destinationFile):
    """Delete Text from 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["url"] = uploadedFileUrl
    parameters["searchString"] = "conspicuous"

    # Prepare URL for 'Delete Text from PDF' API request
    url = "{}/pdf/edit/delete-text".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()
    

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