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Delete PDF Text From URL Asynchronously - Python

PDF Search and Delete Text from PDF sample in Python demonstrating ‘Delete PDF Text From URL Asynchronously’

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

# 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-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()

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.

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