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QuickBooks connector

Accounting platform for customers, invoices, expenses, bills, and financial records.

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Use this as an implementation starting point: adapt the worked example to the requested dataset and the source documentation. See Custom API for the shared SDK pattern and document-upload workflow.

What this connector is for

Accounting platform for customers, invoices, expenses, bills, and financial records.

A connector owns access to the source. Separate syncs shape selected resources into tables for analysis and downstream transformations using the Python SDK.

Data and tables you can pull

These are representative dataset families to consider, not a claim that the worked example implements every resource. Access, fields, and availability depend on the source account, product edition, and permissions. Use the vendor reference to select concrete resources.

Suggested tableOne row represents
customersa customer
vendorsa vendor
invoicesa invoice
billsa bill
paymentsa payment
accountsa account

Relationships and extraction considerations

Scope every table to its realm/company. Customers and vendors link to financial transactions; invoice and bill lines can become child tables. The example reads both active and inactive customers, using the query endpoint's STARTPOSITION and MAXRESULTS controls.

Connecting to QuickBooks

Uses a company-authorized QuickBooks OAuth token and realm/company ID. Includes active and inactive customers. Token rotation is managed by the platform.

Additional resources may require additional scopes. Connection settings belong to the connector; dataset filters and resource selection belong to each sync. See the CLI workflow for registration and configuration.

Connection settings used by the example

SettingRequirementPurpose
access_tokenRequired; secretPlatform-supplied access token. Refresh or rotate before expiry.
realm_idRequiredRealm Id
sandboxRequiredSandbox

requirements.in

Save these dependencies in requirements.in alongside connector.py; the example includes packages used by its sync. Install the published vortexify package for local development. Keep sync-specific dependencies in the sync's own requirements.in when splitting the implementation into separate resources.

vortexify==0.1.1
httpx>=0.27,<1
pandas>=2,<3

No separately installed database driver is needed by this HTTP example.

Worked example: sync customers

customers — Full read using the API's native pagination.

The complete files below implement only this example resource. They illustrate the current SDK signatures, a separate preview, bounded DataFrame output, and source-specific extraction. They do not establish complete source coverage. Live credentials and platform ingestion have not been used to validate this guide.

With default paths, place the connector files in connectors/quickbooks/ and sync files in connectors/quickbooks/syncs/customers/. Use your project configuration if it specifies different paths.

Connection schema: config.json

This file contains a JSON Schema, not actual credential values. Provide those through platform configuration.

{
  "type": "object",
  "properties": {
    "access_token": {
      "type": "string",
      "title": "Access Token",
      "description": "Platform-supplied access token. Refresh or rotate before expiry.",
      "minLength": 1,
      "x-vortexify-secret": true,
      "order": 0
    },
    "realm_id": {
      "type": "string",
      "minLength": 1,
      "title": "Realm Id",
      "order": 1
    },
    "sandbox": {
      "type": "boolean",
      "default": false,
      "title": "Sandbox",
      "order": 2
    }
  },
  "required": [
    "access_token",
    "realm_id",
    "sandbox"
  ]
}

Connector: connector.py

import httpx
from vortexify import Column, Connector, DiscoveredTable


class QuickbooksConnector(Connector):
    vendor_domain = "intuit.com"

    def client(self):
        if self._client is None or self._client.is_closed:
            self._client = httpx.Client(
                base_url=(
                    "https://sandbox-quickbooks.api.intuit.com/"
                    if self.config.get("sandbox", False)
                    else "https://quickbooks.api.intuit.com/"
                ),
                headers={
                    "Authorization": "Bearer " + self.config["access_token"],
                    "Accept": "application/json",
                },
                timeout=60,
                follow_redirects=False,
            )
        return self._client

    def check(self) -> bool:
        cfg = self.config
        page_size = 1
        path = "v3/company/" + cfg["realm_id"] + "/query"
        position = 1
        params = {
            "query": "SELECT * FROM Customer WHERE Active IN (true, false) STARTPOSITION 1 MAXRESULTS "
            + str(page_size)
        }
        response = self.client().get(path, params=params)
        response.raise_for_status()
        payload = response.json()
        return True

    def discover(self) -> list[DiscoveredTable]:
        return [
            DiscoveredTable(
                name="customers",
                schema=[
                    Column(name="id", type="string"),
                    Column(name="display_name", type="string"),
                    Column(name="active", type="boolean"),
                    Column(name="balance", type="number"),
                    Column(name="document", type="string"),
                ],
            )
        ]

    def close(self) -> None:
        if self._client is not None:
            try:
                self._client.close()
            finally:
                self._client = None

Sync schema: syncs/customers/config.json

{
  "type": "object",
  "properties": {},
  "required": []
}

Sync: syncs/customers/sync.py

from collections.abc import Iterator
from math import isfinite
import json
import pandas as pd
from vortexify import Sync


class QuickbooksCustomersSync(Sync):

    def preview(self) -> pd.DataFrame:
        cfg = self.connector.config
        page_size = 100
        path = "v3/company/" + cfg["realm_id"] + "/query"
        position = 1
        params = {
            "query": "SELECT * FROM Customer WHERE Active IN (true, false) STARTPOSITION 1 MAXRESULTS "
            + str(page_size)
        }
        response = self.client.get(path, params=params)
        response.raise_for_status()
        payload = response.json()
        records = payload.get("QueryResponse", {}).get("Customer", [])
        if not isinstance(records, list) or any(
            (not isinstance(record, dict) for record in records)
        ):
            raise ValueError(
                "Unexpected API record shape; refusing a partial successful sync"
            )
        records = records[:100]
        rows = []
        for record in records:
            row = {
                "id": record.get("Id"),
                "display_name": record.get("DisplayName"),
                "active": record.get("Active"),
                "balance": record.get("Balance"),
                "document": json.dumps(record, ensure_ascii=False, default=str),
            }
            rows.append(
                {
                    key: (
                        json.dumps(value, ensure_ascii=False, default=str)
                        if isinstance(value, (dict, list))
                        else value
                    )
                    for key, value in row.items()
                }
            )
        return pd.DataFrame(
            rows,
            columns=["id", "display_name", "active", "balance", "document"],
            dtype=object,
        )

    def extract(
        self, *, avg_row_size_bytes: float | None = None
    ) -> Iterator[pd.DataFrame]:
        memory_mib = self.compute.memory if self.compute else None
        memory_mib = memory_mib if memory_mib is not None and memory_mib > 0 else 1024
        target_bytes = min(16 * 1024 * 1024, max(1, memory_mib * 1024 * 1024 // 20))
        batch_size = 100
        if avg_row_size_bytes is not None:
            if not isfinite(avg_row_size_bytes) or avg_row_size_bytes <= 0:
                raise ValueError("avg_row_size_bytes must be finite and positive")
            batch_size = max(1, int(target_bytes / max(1.0, avg_row_size_bytes) / 4))
        batch_size = min(batch_size, 1000)
        cfg = self.connector.config
        page_size = batch_size
        path = "v3/company/" + cfg["realm_id"] + "/query"
        position = 1
        params = {
            "query": "SELECT * FROM Customer WHERE Active IN (true, false) STARTPOSITION 1 MAXRESULTS "
            + str(page_size)
        }
        seen_pages = set()
        while True:
            response = self.client.get(path, params=params)
            response.raise_for_status()
            payload = response.json()
            records = payload.get("QueryResponse", {}).get("Customer", [])
            if not isinstance(records, list) or any(
                (not isinstance(record, dict) for record in records)
            ):
                raise ValueError(
                    "Unexpected API record shape; refusing a partial successful sync"
                )
            rows = []
            for record in records:
                row = {
                    "id": record.get("Id"),
                    "display_name": record.get("DisplayName"),
                    "active": record.get("Active"),
                    "balance": record.get("Balance"),
                    "document": json.dumps(record, ensure_ascii=False, default=str),
                }
                rows.append(
                    {
                        key: (
                            json.dumps(value, ensure_ascii=False, default=str)
                            if isinstance(value, (dict, list))
                            else value
                        )
                        for key, value in row.items()
                    }
                )
            for start in range(0, len(rows), batch_size):
                yield pd.DataFrame(
                    rows[start : start + batch_size],
                    columns=["id", "display_name", "active", "balance", "document"],
                    dtype=object,
                )
            if len(records) < page_size:
                break
            position += len(records)
            params["query"] = (
                "SELECT * FROM Customer WHERE Active IN (true, false) STARTPOSITION "
                + str(position)
                + " MAXRESULTS "
                + str(page_size)
            )

Running and extending the example

Register the connector before the sync and commit each resource separately:

vortexify create connector quickbooks
vortexify create sync quickbooks/customers

Edit the files, inspect vortexify status, and use the CLI guide to commit and configure them. Registration alone does not run extraction or deploy the connector.

Preview must run with a fresh connector and disposable state. The extraction implementation determines full/incremental behavior; merely setting a mode does not implement change capture. API/driver failures propagate unless explicitly handled in the code. Check source limits and single-record/response sizes as well as output batch size.

Sources and further reading