Get More Than 1 Record in CSV File from Knack

The steps are below. Basically, I am pulling all PDF documents from Docparser that get processed and then exporting them to Google Drive as a txt file. Each single PDF gets exported as a separate text file because Docparser processes every file as a separate document. I am trying to combine all the CSV records into one file which seems very difficult. I have a batch file on the system combining them right now but would like to find a way to do it Zapier if possible. 

All the records get saved into Knack so I would think it would be easy to tell Zapier to download all records with a specific variable in the database but I can’t seem to do that either. Why is it so difficult to download records to a combined CSV?

See below: 

Step 1: 

Step 2:

Step 3: 

I can to this. I hope in the future that there is a way to download multiple records from the DB without having to use an API. Thank you. 

FYI - this is a good script for anyone to use to pull records from your Knack DB. All you need to do is change the following:

BASE_URL = "https://api.knack.com/v1/objects/object_1/records"

Change this line and put in your proper object ID (IE.object_1). The object ID can be found in the address bar: 

The just make sure you put in your APPLICATION ID and API KEY in those two lines and you are good. Those can be found in your SETTINGS in Knack. You can replace the XXX in this script with both. 

This script is designed to pull all records from the object you specify and then download them into a CSV file. I am excluding the RAW fields and only pulling the regular fields. This script will work with any table as long as you specify the object ID. 

I hope this helps people with little coding knowledge to be able to download records from your Knack table to a CSV file. You can also add specific values to download only specific records (IE. Field 2 = NO). 

Thanks. I figured out how to download the headers. This script is pulling all the records I need, downloading the headers and limiting the records downloaded to CSV Created = N. So I am assuming I want to use the KNACK API REQUEST to run this as that sounds like it’s the most logical choice. 

So if I use the KNACK API REQUEST I am assuming the Knack records will be available in other processes correct? I have to assume since the API is calling the records you want I can then use those records in future process steps. Is this a correct assumption? 

Thank you very much for your help. It was very informative and I learned a lot building the API and reading the feedback on the forum. This solves my major issue of getting all the records into one properly formatted CSV file. This solves my problem after 2 months of trying!! 

If you can let me know if the records will be available in the ZAP process after the API call, I will greatly appreciated it. I have to assume so but I want to confirm. 

The script is below for anyone who is trying to figure out how to pull records out of Knack and writing them to a CSV file. I have figured out all the logic of how to pull the proper header files, writing it to the CSV matching the database field order, excluding fields and pulling records based on a specific criteria.

This API script should cover 95% of everything anyone wants to do with pulling Knack records: 

import requests
import csv
import json

# Knack API endpoint and headers - Change the Object ID to your Knack Object ID
BASE_URL = "https://api.knack.com/v1/objects/object_1/records"
HEADERS = {
    "Content-Type": "application/json",
    "X-Knack-Application-Id": "put your app id here", 
    "X-Knack-REST-API-Key": "put your API key here"
}

# List of fields to exclude from downloading
EXCLUDED_FIELDS = ["id", "field_50", "field_46", "field_1", "field_30", "field_49","field_26"]

def fetch_field_metadata():
    response = requests.get(f"https://api.knack.com/v1/objects/object_1", headers=HEADERS)
    metadata = response.json().get("object", {}).get("fields", [])
    print("Field Metadata:", json.dumps(metadata, indent=4))  # Print the field metadata for debugging
    return metadata

def get_header_mappings():
    field_metadata = fetch_field_metadata()
    return {field["key"]: field.get("name", field["key"]) for field in field_metadata}

def get_all_records():
    all_records = []
    page_number = 1
    filter_param = {
        "match": "and",
        "rules": [{
            "field": "field_49",
            "operator": "is",
            "value": "N"
        }]
    }

    while True:
        response = requests.get(
            BASE_URL, 
            headers=HEADERS, 
            params={'page': page_number, 'filters': json.dumps(filter_param)}
        )
        if response.status_code != 200:
            print(f"Failed to fetch data on page {page_number}. Status code: {response.status_code}, Response text: {response.text}")
            break
        records = response.json().get("records", [])
        if not records:
            break
        all_records.extend(records)
        page_number += 1

    return all_records

def save_records_to_csv(records, headers_mapping, filename="knack_data.csv"):
    if not records:
        print("No records to save.")
        return
    # Filter out excluded fields
    header_labels = [headers_mapping.get(key, key) for key in records[0].keys() if key not in EXCLUDED_FIELDS and not key.endswith("_raw")]
    with open(filename, 'w', newline='', encoding='utf-8') as csv_file:
        writer = csv.DictWriter(csv_file, fieldnames=header_labels)
        writer.writeheader()
        for record in records:
            # Exclude fields in EXCLUDED_FIELDS
            writer.writerow({headers_mapping.get(key, key): record[key] for key in record.keys() if key not in EXCLUDED_FIELDS and not key.endswith("_raw")})
    print(f"Data saved to {filename}")

if __name__ == "__main__":
    records = get_all_records()
    headers_mapping = get_header_mappings()
    save_records_to_csv(records, headers_mapping)