PDF to JSON API in Python with PDF.co Web API

PDF.co Web API is the Rest API that provides set of data extraction functions, tools for documents manipulation, splitting and merging of pdf files. Includes built-in OCR, images recognition, can generate and read barcodes from images, scans and pdf.

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ConvertPdfToJSONFromUploadedFile.py

      
import os
import requests # pip install requests

# 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://api.pdf.co/v1"

# Source PDF file
SourceFile = ".\\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 JSON file name
DestinationFile = ".\\result.json"


def main(args = None):
    uploadedFileUrl = uploadFile(SourceFile)
    if (uploadedFileUrl != None):
        convertPdfToJson(uploadedFileUrl, DestinationFile)


def convertPdfToJson(uploadedFileUrl, destinationFile):
    """Converts PDF To Json using PDF.co Web API"""

    # Some of advanced options available through profiles:
    # (it can be single/double-quoted and contain comments.)
    # {
    #     "profiles": [
    #         {
    #             "profile1": {
    #                 "SaveImages": "None", // Whether to extract images. Values: "None", "Embed".
    #                 "ImageFormat": "PNG", // Image format for extracted images. Values: "PNG", "JPEG", "GIF", "BMP".
    #                 "SaveVectors": false, // Whether to extract vector objects (vertical and horizontal lines). Values: true / false
    #                 "ExtractInvisibleText": true, // Invisible text extraction. Values: true / false
    #                 "ExtractShadowLikeText": true, // Shadow-like text extraction. Values: true / false
    #                 "LineGroupingMode": "None", // Values: "None", "GroupByRows", "GroupByColumns", "JoinOrphanedRows"
    #                 "ColumnDetectionMode": "ContentGroupsAndBorders", // Values: "ContentGroupsAndBorders", "ContentGroups", "Borders", "BorderedTables"
    #                 "Unwrap": false, // Unwrap grouped text in table cells. Values: true / false
    #                 "ShrinkMultipleSpaces": false, // Shrink multiple spaces in table cells that affect column detection. Values: true / false
    #                 "DetectNewColumnBySpacesRatio": 1, // Spacing ratio that affects column detection.
    #                 "CustomExtractionColumns": [ 0, 50, 150, 200, 250, 300 ], // Explicitly specify columns coordinates for table extraction.
    #                 "CheckPermissions": true, // Ignore document permissions. Values: true / false
    #             }
    #         }
    #     ]
    # }

    # Sample profile that sets advanced conversion options
    # Advanced options are properties of JSONExtractor class from ByteScout JSON Extractor SDK used in the back-end:
    # https://cdn.bytescout.com/help/BytescoutPDFExtractorSDK/html/84356d44-6249-3251-2da8-83c1f34a2f39.htm
    profiles = '{ "profiles": [ { "profile1": { "TrimSpaces": "False", "PreserveFormattingOnTextExtraction": "True" } } ] }'

    # Prepare requests params as JSON
    # See documentation: https://apidocs.pdf.co
    parameters = {}
    parameters["name"] = os.path.basename(destinationFile)
    parameters["password"] = Password
    parameters["pages"] = Pages
    parameters["url"] = uploadedFileUrl
    parameters["profiles"] = profiles

    # Prepare URL for 'PDF To Json' API request
    url = "{}/pdf/convert/to/json".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:
            #  Get URL of result file
            resultFileUrl = json["url"]            
            # 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}")
        else:
            # Show service reported error
            print(json["message"])
    else:
        print(f"Request error: {response.status_code} {response.reason}")


def uploadFile(fileName):
    """Uploads file to the cloud"""
    
    # 1. RETRIEVE PRESIGNED URL TO UPLOAD FILE.

    # Prepare URL for 'Get Presigned URL' API request
    url = "{}/file/upload/get-presigned-url?contenttype=application/octet-stream&name={}".format(
        BASE_URL, os.path.basename(fileName))
    
    # Execute request and get response as JSON
    response = requests.get(url, headers={ "x-api-key": API_KEY })
    if (response.status_code == 200):
        json = response.json()
        
        if json["error"] == False:
            # URL to use for file upload
            uploadUrl = json["presignedUrl"]
            # URL for future reference
            uploadedFileUrl = json["url"]

            # 2. UPLOAD FILE TO CLOUD.
            with open(fileName, 'rb') as file:
                requests.put(uploadUrl, data=file, headers={ "x-api-key": API_KEY, "content-type": "application/octet-stream" })

            return uploadedFileUrl
        else:
            # Show service reported error
            print(json["message"])    
    else:
        print(f"Request error: {response.status_code} {response.reason}")

    return None


if __name__ == '__main__':
    main()

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