# How to Implement Custom Data Connectors for Fincept’s 100+ Data Sources > Learn to implement custom data connectors for Fincept s 100 data sources using the plug-in style connector registry and DataHub for seamless data integration. - Repository: [Fincept Corporation/FinceptTerminal](https://github.com/Fincept-Corporation/FinceptTerminal) - Tags: how-to-guide - Published: 2026-04-20 --- **Fincept Terminal exposes a plug-in style connector registry that lets you add new data sources by declaring a `ConnectorConfig`, registering it statically, and implementing a lightweight service that publishes data via the `DataHub`.** Fincept Terminal manages its extensive ecosystem of data providers through a **data-driven connector architecture**. Whether you are integrating a proprietary market feed, a cloud time-series database, or an internal REST API, the process follows the same three-layer pattern used by the 100+ built-in sources. This guide walks you through implementing custom data connectors for Fincept using the exact structures found in the repository. ## Understanding the Connector Architecture ### The Three-Layer Pattern Every connector in `FinceptTerminal` is composed of three distinct layers: 1. **Connector Definition** – A declarative `ConnectorConfig` object (ID, UI label, category, input fields, and defaults). 2. **Registration** – A static initialization block that pushes the configuration into the global `ConnectorRegistry` at program startup. 3. **Data Retrieval** – A service (C++ or Python) that communicates with the external system and publishes results via `DataHub` for streaming or returns batch payloads. This architecture decouples the UI from the implementation. The `DataSourcesScreen` automatically generates configuration dialogs from the field list, allowing you to swap service implementations without touching interface code. ### Key Components **`ConnectorRegistry`** ([`fincept-qt/src/screens/data_sources/ConnectorRegistry.h`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/fincept-qt/src/screens/data_sources/ConnectorRegistry.h)) A singleton that stores all `ConnectorConfig` objects. Access it via `ConnectorRegistry::instance()` and call `add()` to register new connectors. **`ConnectorConfig`** ([`fincept-qt/src/screens/data_sources/DataSourceTypes.h`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/fincept-qt/src/screens/data_sources/DataSourceTypes.h)) Defines the schema for a connector, including `id`, `name`, `category`, `color`, and a `QVector` describing UI inputs (URLs, passwords, dropdowns). **`DataHub`** ([`fincept-qt/src/datahub/DataHub.h`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/fincept-qt/src/datahub/DataHub.h)) The internal pub/sub bus. Services publish data using `DataHub::instance().publish(topic, QVariant::fromValue(payload))`, and consumers (charts, watchlists) subscribe to topics like `market:quote:AAPL`. **`PythonRunner`** ([`fincept-qt/src/python/PythonRunner.cpp`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/fincept-qt/src/python/PythonRunner.cpp)) Executes custom Python scripts for data extraction, returning JSON that the C++ side wraps as `QVariant`. This provides an alternative to writing C++ services. ## Step-by-Step Implementation Guide ### Step 1 – Define the Connector Configuration Create a new file in [`fincept-qt/src/screens/data_sources/connectors/YourConnector.cpp`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/fincept-qt/src/screens/data_sources/connectors/YourConnector.cpp). Define a function that returns a `QVector` containing your data source metadata and field definitions. ```cpp // IOOPlusConnector.cpp #include "screens/data_sources/ConnectorRegistry.h" #include "screens/data_sources/DataSourceTypes.h" namespace fincept::screens::datasources { static QVector ioo_plus_configs() { return { { "ioo-plus", "IOO+ Data Feed", "ioo-plus", Category::MarketData, "I", "#009688", "Custom IOO+ endpoint supporting realtime quotes and historic bars", true, false, { {"baseUrl", "Base URL", FieldType::Url, "https://api.iooplus.com", true, "", {}}, {"apiKey", "API Key", FieldType::Password, "", true, "", {}}, {"symbols", "Symbols", FieldType::Text, "AAPL,MSFT,GOOGL", false, "", {}}, {"interval", "Interval", FieldType::Select, "", false, "1d", { {"1 minute","1m"}, {"5 minutes","5m"}, {"1 hour","1h"}, {"1 day","1d"} } } } } }; } } // namespace ``` ### Step 2 – Register with ConnectorRegistry Use a static initialization lambda to push your configurations into the registry. This pattern ensures the linker includes your translation unit and the connector appears at startup. ```cpp // Add to the same IOOPlusConnector.cpp file static bool registered = []{ for (auto &c : ioo_plus_configs()) ConnectorRegistry::instance().add(std::move(c)); return true; }(); ``` This self-registration pattern is identical to the implementation in [`TimeSeriesDatabases.cpp`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/TimeSeriesDatabases.cpp) and [`MarketData.cpp`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/MarketData.cpp). ### Step 3 – Implement the Data Retrieval Service Create a service class that handles HTTP requests or WebSocket connections. In [`fincept-qt/src/services/iooplus/IOOPlusService.cpp`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/fincept-qt/src/services/iooplus/IOOPlusService.cpp): ```cpp #include "services/iooplus/IOOPlusService.h" #include "core/network/http/HttpClient.h" #include "datahub/DataHub.h" using namespace fincept::core::network; namespace fincept::services::iooplus { void IOOPlusService::fetchQuotes(const QString &baseUrl, const QString &apiKey, const QStringList &symbols, std::function cb) { QUrl url(baseUrl + "/quotes"); QUrlQuery query; query.addQueryItem("symbols", symbols.join(',')); url.setQuery(query); HttpClient client; client.setHeader(QByteArrayLiteral("Authorization"), QByteArrayLiteral("Bearer ") + apiKey.toUtf8()); client.get(url, [cb](Result res){ if (!res) { cb(false, {}); return; } QJsonDocument doc = QJsonDocument::fromJson(*res); cb(true, doc.array()); }); } void IOOPlusService::publishQuotes(const QJsonArray "es) { for (const QJsonValue &v : quotes) { QString symbol = v.toObject()["symbol"].toString(); QString topic = QStringLiteral("market:quote:%1").arg(symbol); DataHub::instance().publish(topic, QVariant::fromValue(v.toObject())); } } } // namespace ``` Alternatively, use the `PythonRunner` for rapid prototyping by placing a script in [`fincept-qt/python/ioo_plus_fetcher.py`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/fincept-qt/python/ioo_plus_fetcher.py) and invoking it via `PythonRunner::runScript()`. ### Step 4 – Build and Verify Add your new files to [`fincept-qt/CMakeLists.txt`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/fincept-qt/CMakeLists.txt): ```cmake target_sources(fincept-qt PRIVATE src/screens/data_sources/connectors/IOOPlusConnector.cpp src/services/iooplus/IOOPlusService.cpp ) ``` Build the project, launch Fincept Terminal, and navigate to **Settings → Data Sources**. Your **IOO+ Data Feed** connector will appear automatically. Configure the endpoint, save, and trigger a fetch to verify data flows through `DataHub` to your subscribed screens. ## Summary - **Custom data connectors for Fincept** are implemented via a declarative `ConnectorConfig` object that defines UI fields and metadata. - **Static registration** via `ConnectorRegistry::instance().add()` ensures connectors self-register at program startup without modifying central lists. - **Data retrieval** is handled by services (C++ or Python) that communicate with external APIs and publish results through the `DataHub` pub/sub system. - **Zero UI changes** are required; the `DataSourcesScreen` dynamically generates configuration dialogs from the `FieldConfig` vector. - **Reference implementations** in [`MarketData.cpp`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/MarketData.cpp) and [`TimeSeriesDatabases.cpp`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/TimeSeriesDatabases.cpp) provide proven templates for new connectors. ## Frequently Asked Questions ### What is the ConnectorRegistry in Fincept Terminal? The `ConnectorRegistry` is a singleton class defined in [`fincept-qt/src/screens/data_sources/ConnectorRegistry.h`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/fincept-qt/src/screens/data_sources/ConnectorRegistry.h) that stores all available `ConnectorConfig` objects. It provides static initialization hooks that allow new connectors to self-register at startup by calling `ConnectorRegistry::instance().add()`, eliminating the need to edit central configuration files when adding new data sources. ### Do I need to modify the UI code to add a new data connector? No. The `DataSourcesScreen` automatically reads all entries from `ConnectorRegistry::instance().all()` and constructs the configuration table and dialogs dynamically based on the `FieldConfig` vector inside each `ConnectorConfig`. As long as you properly define your fields (URL, password, text, select dropdowns), the UI will render the appropriate input controls without any manual QML or Qt Widgets modifications. ### Can I use Python instead of C++ for the data retrieval service? Yes. Fincept Terminal includes a `PythonRunner` component in [`fincept-qt/src/python/PythonRunner.cpp`](https://github.com/Fincept-Corporation/FinceptTerminal/blob/main/fincept-qt/src/python/PythonRunner.cpp) that can execute Python scripts for data extraction and analytics. You can place your integration script in `fincept-qt/python/` and invoke it via `PythonRunner::runScript()`, which returns JSON that the C++ side wraps as `QVariant` and publishes through `DataHub`. This is ideal for rapid prototyping or when integrating with Python-native APIs.