If you are a Python Developer check out the official pip library ExtractTable-py - takes only 3 lines of code for the output
ExtractTable API allows extracting structured tabular data from images or PDF files. The motivation is to make it easier for developers to not worry about the table area, column or row coordinates, rotation et al in the input.
\n\n\nIf you are a Python Developer check out the official pip library ExtractTable-py - takes only 3 lines of code for the output
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![\"image\"](\"https://img.shields.io/badge/python-3.5%20%7C%203.6%20%7C%203.7-blue\"){kind=icon}
from ExtractTable import *\net_sess = ExtractTable(api_key=YOUR_API_KEY) # Replace your VALID API Key here\nprint(et_sess.check_usage()) # Validates API Key & show credits usage \ntable_data = et_sess.process_file(filepath=Location_of_Image_with_Tables, output_format=\"df\")\nThe service is authenticated with an API key, grab some FREE credits here for trial or most welcome to BUY credits here. ExtractTable.com offers the best accuracy, lowest $/credit with longest validity and credit refund on bad outputs(literally, no one does this). For any information needed/assistance/troubleshooting feel free to email me at saradhi@extracttable.com. A detailed competitive comparison here.
\nHow/Where to use the API Key?
\nFirstly, note that there are 3 different API endpoints - all endpoints must need a valid API Key passed in header as “x-api-key”
\nWhat are the common error codes & How to resolve?
\nWhat are all the possible responses?
\nEvery triggered job can have one of the below 4 status
\nWhat is the output of the process?
\nThe output response will be in the below format, based on the API Key Plan type.
\n{\n \"JobStatus\": <string>, # Status of the triggered Process @ JOB-LEVEL\n \"Pages\": <integer>, # Number of pages processed in this request @ PAGE-LEVEL\n \"Tables\": [<list of key-value objects of table> # List of all tables found @ TABLE-LEVEL\n {\n \"Page\": <integer>, ## Page number in which this table is found\n \"CharacterConfidence\": <float>, ## Accuracy of Characters recognized from the input-page\n \"LayoutConfidence\": <float>, ## Accuracy of table layout's design decision\n \"TableJson\": <dict>, ## Table Cell Text in key-value format with index orientation - {row#: {col#: <str>}}\n \"TableCoordinates\": <dict>, ## Top-left & Bottom-right Cell Coordinates - {row#: {col#: <list(x1,y1,x2,y2)>}}\n \"TableConfidence\": <dict> ## Cell level accuracy of detected characters - {row#: {col#: <float>}}\n },\n {...} ## ... more \"Tables\" objects\n ],\n \"Lines\": [<list of key-value objects> # Pagewise Line details @ PAGE-LEVEL\n {\n \"Page\": <integer>, # Page number in which the lines are found\n \"CharacterConfidence\": <float>, # Average Accuracy of all Characters recognized from the input-page\n \"LinesArray\": [\n <list of key-value objects of line> # Ordered list of lines in this page @ LINE-LEVEL\n {\n \"Line\": <str>, ## Detected text of the complete line\n \"WordsArray\": [\n <list of key-value objects> ## Word level datails in this line @ WORD-LEVEL\n {\n \"Conf\": <float>, ### Accuracy of recognized characters of the word\n \"Word\": <str>, ### Detected text of the word\n \"Loc\": [x1, y1, x2, y2] ### Top-left & Bottom-right coordinates, w.r.t the input-page width-height dimensions\n },\n {...} ### More \"WordsArray\" objects\n ]\n },\n {...} ## More \"LinesArray\" objects\n ]\n },\n {...} # More Pagewise \"Lines\" details\n ]\n}\nOutput objects are based on the API Key Plan type. Available plan types are
\nPurchased Plans
\nPromotional Plans: Any plan other than Purchased plans are promotional
\nHow to transform the \"TableJson\" to csv?
\nResponseJSON[\"Tables\"], an array, contain tabular json data of all tables extracted from the file.
ResponseJSON[\"Tables\"][0].TableJson is a dictionary with row number as key and column data as values.
Gathered helpful resources to make it easier for you to convert the JSON response into a CSV file.
\nDo you have website recommendations to VIEW the recieved JSON resonse as a CSV?
\n\nAPIKey received from https://extracttable.com
\n"}],"url":"https://validator.extracttable.com","description":"\n\n","urlObject":{"protocol":"https","host":["validator","extracttable","com"],"query":[],"variable":[]}},"response":[{"id":"c976208a-694a-4d94-aac4-3bd90b0a58e8","name":"Check APIKey usage","originalRequest":{"method":"GET","header":[{"key":"x-api-key","value":"Check the usage of APIKey
\n
APIKey received from https://extracttable.com
\n","type":"text"}],"url":"https://viewtransactions.extracttable.com","description":"View all your transactions that are processed in the last 24 hours.
\n","urlObject":{"protocol":"https","host":["viewtransactions","extracttable","com"],"query":[],"variable":[]}},"response":[{"id":"2ed30e68-2df8-47d2-a1b9-4843cf82e143","name":"View Transactions","originalRequest":{"method":"GET","header":[{"key":"x-api-key","value":"YOUR_APIKEY_HERE","description":"APIKey received from https://extracttable.com","type":"text"}],"url":"https://viewtransactions.extracttable.com"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[{"key":"Content-Type","value":"application/json"},{"key":"Content-Length","value":"250"},{"key":"Connection","value":"keep-alive"},{"key":"Date","value":"Wed, 18 Aug 2021 15:09:31 GMT"},{"key":"x-amzn-RequestId","value":"25a6f6ad-f843-4c05-bcc4-e459b659c5bc"},{"key":"Access-Control-Allow-Origin","value":"*"},{"key":"Content-Encoding","value":"gzip"},{"key":"x-amzn-Remapped-Content-Length","value":"263"},{"key":"x-amz-apigw-id","value":"ERJazEiuoAMFcXA="},{"key":"X-Amzn-Trace-Id","value":"Root=1-611d22ab-69c89dad5d9f297b36555ecf;Sampled=0"},{"key":"X-Cache","value":"Miss from cloudfront"},{"key":"Via","value":"1.1 0311e0b009120ac76c4a810bd0393910.cloudfront.net (CloudFront)"},{"key":"X-Amz-Cf-Pop","value":"ATL56-C4"},{"key":"X-Amz-Cf-Id","value":"yaMlucvCd3RCiT21RbZgxWwzjnfRNnXP4IEhldoIcDtYuz9-Bpcg1w=="}],"cookie":[],"responseTime":null,"body":"[\n {\n \"JobStatus\": \"Success\",\n \"Pages\": 1,\n \"createdon\": 1629235293,\n \"request_filename\": \"filename.png\",\n \"txn_id\": \"y4lB6VJsd9LwI2ElOiTJJg0kIah00yPWERhMA8nM1MNvhHncLzZ116292352911c\"\n }\n]"}],"_postman_id":"8da3cce8-4081-4d6a-af2b-25a105d34d7e"},{"name":"Trigger a Job","id":"db927c1b-f530-4173-8a22-581b47694c55","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"description":"APIKey received from https://extracttable.com
\n","key":"x-api-key","type":"text","value":"YOUR_APIKEY_HERE"}],"body":{"mode":"formdata","formdata":[{"description":"Image or PDF file from which tables to be extracted
\n","key":"input","type":"file","src":"foo-image.jpg"},{"key":"dup_check","value":"False","description":"True - to STOP Idempotent requests
\n","type":"text","disabled":true}]},"url":"https://trigger.extracttable.com","description":"\n\nTrigger a job to find tables from an image or PDF file content
\n
dup_check : False (default) provides synchronous results on Image files. Changing it to True - controls idempotent file processing, but the response will not contain tabular data, instead returns JobId which should be used to retrieve the result using \"Retrieve the result using JobId\".
\nWhenever the JobStatus is \"Processing\" make sure to track/save the \"JobId\" to retrieve the result, later.
\nNote that the idempotency is based on the filename, meaning, if 2 different requests with the same file name(even though different in file content) are triggered, the second request will not go through the table extraction process and responds to the user with the idempotent info.
\nAPIKey received from https://extracttable.com
\n","key":"x-api-key","type":"text","value":"YOUR_APIKEY_HERE"}],"url":"https://getresult.extracttable.com/?JobId=JOBID_Recieved_In_Trigger_Response","description":"\n\nRetrive the extracted table result using the
\nJobIdvalue received from Trigger-ed response
A Success in JobStatus tells the process is completed. The response contains the attributes mentioned below
{\n \"JobStatus\": \"Success\", # Success | Failed | Processing | Incomplete\n \"Pages\": 1, # Number of Input pages, equivalent to credits used\n \"Tables\": [ # List of all tables found in the file\n {\n \"CharacterConfidence\": 99.13, # Accuracy of Characters recognized from the image\n \"LayoutConfidence\": 75.12, # Accuracy of table layout's design decision\n \"Page\": 1, # The Page number of the below TableJson found\n \"TableJson\": { # TabularJson data\n \"1\": { # Row 1\n \"1\": \"Cycle\", # Col1\n \"2\": \"KI\", # Col2\n \"3\": \"Distance\", # Col3\n \"4\": \"\",\n \"5\": \"Percent Fuel\",\n \"6\": \"Savings\",\n \"7\": \"\"\n }\n }\n }\n ]\n}\nNote: The Tables attribute of the response will be an empty list/array if there are no tables found in any of the PDF pages or an image
APIKey received from https://extracttable.com
\n","key":"x-api-key","type":"text","value":"YOUR_APIKEY_HERE"}],"body":{"mode":"formdata","formdata":[{"description":"just the name of the file
\n","key":"filename","type":"text","value":"big_file.pdf"}]},"url":"https://bigfile.extracttable.com","description":"Extracting the data from the files up to 4 Mb is a straightforward one-step process. However, the files over 4 Mb have to go through an additional process that involves the below three steps.
\nStep 1: Generate a secured PRESIGNED URL that authenticates your request to upload the file.
\nMake a POST request to https://bigfile.extracttable.com, with the name of the file in form-data through filename
The value received in step 1 respons. Check step1_resp
\n"},{"key":"Content-Type","value":"step1_response[\"fields\"][\"Content-Type\"]","type":"text","description":"The value received in step 1 response
\n"},{"key":"acl","value":"step1_response[\"fields\"][\"acl\"]","type":"text","description":"The value received in step 1 response
\n"},{"key":"key","value":"step1_response[\"fields\"][\"key\"]","type":"text","description":"The value received in step 1 response
\n"},{"key":"policy","value":"step1_response[\"fields\"][\"policy\"]","type":"text","description":"The value received in step 1 response
\n"},{"key":"signature","value":"step1_response[\"fields\"][\"signature\"]","type":"text","description":"The value received in step 1 response
\n"},{"key":"x-amz-security-token","value":"step1_response[\"fields\"][\"x-amz-security-token\"]","type":"text","description":"The value received in step 1 response
\n"},{"key":"file","description":"The \"filename\" you SENT in step1
\n","type":"file","src":"big_file.pdf"}]},"url":"https://et-presign-target.s3.amazonaws.com/","description":"Step 2: Upload the file to the PRESIGNED URL
\nCapture the response of step1 (lets call this step1_resp), and POST the file to the below specifications
\nstep1_resp['url']step1_resp['fields'] objectAPIKey received from https://extracttable.com
\n","key":"x-api-key","type":"text","value":"YOUR_APIKEY_HERE"}],"body":{"mode":"formdata","formdata":[{"description":"Value of step1_resp[\"fields\"][\"key\"]
\n","key":"signed_filename","type":"text","value":"value of step1_resp[\"fields\"][\"key\"]"}]},"url":"https://trigger.extracttable.com","description":"Step 3:
\nOn successfully uploading the file in step 2, its time for triggering the process using step1_resp[\"fields\"][\"key\"] as signed_filename in the form-data
You will receive JobId in the response JSON. Follow Retrieve the result using JobId