Amibroker Data Plugin Source Code Top May 2026

The Developer’s Guide to AmiBroker Data Plugin Source Code: Top Resources & Examples

For algorithmic traders and quantitative developers, AmiBroker remains one of the most powerful technical analysis platforms available. However, its true potential is unlocked not just by its formula language (AFL), but by its ability to connect to virtually any data source.

While many data vendors provide ready-made plugins, there are countless scenarios where a trader needs to build their own data connector—perhaps to integrate a proprietary database, a crypto exchange, or a niche broker API that lacks official support.

This article explores the top resources for AmiBroker data plugin source code, breaking down the essential SDKs, community repositories, and the structural logic you need to know to build a robust data feed.

Conclusion: Mastering the Source Code

The search for "Amibroker data plugin source code top" is not about finding a single file to copy-paste. It is about understanding the contract between your data source and Amibroker’s high-performance database engine.

Top takeaways for your own source code:

Always compile with _UNICODE and WIN64.
Never block inside GetQuotesEx longer than 10ms.
Use a free, open-source reference like the "AmiDevKit" (available on GitHub) as your foundation.
Respect the QUOTETYPE flags (HISTORY, REALTIME, SNAPSHOT) – mixing them up is the #1 reason for "Data not refreshing" errors.

By building or auditing a plugin with these principles, you will join an elite group of traders who control their data pipeline end-to-end. Happy coding, and may your backtests be accurate.

Disclaimer: Amibroker is a trademark of Amibroker.com. This article is for educational purposes. Always refer to the official SDK license.

Introduction

Amibroker is a popular technical analysis and trading platform that allows users to create custom indicators, backtest trading strategies, and analyze financial data. One of the key features of Amibroker is its ability to connect to various data sources using plugins. In this guide, we will walk you through the process of creating an Amibroker data plugin source code.

Prerequisites

Before you start, make sure you have:

Amibroker installed on your system (version 5.20 or later)
A basic understanding of C++ programming language
A data source (e.g., a database, API, or file) that you want to connect to Amibroker

Step 1: Choose a Data Source

Select a data source that you want to connect to Amibroker. This could be a:

Database (e.g., MySQL, PostgreSQL, SQLite)
API (e.g., Quandl, Alpha Vantage, Intrinio)
File (e.g., CSV, JSON, XML)

Step 2: Create a New Plugin Project

Create a new C++ project in your preferred IDE (e.g., Visual Studio, Xcode, Eclipse). Name your project (e.g., "MyDataPlugin").

Step 3: Include Amibroker SDK

Include the Amibroker SDK (Software Development Kit) in your project. You can download the SDK from the Amibroker website. The SDK provides the necessary header files, libraries, and documentation to create Amibroker plugins.

Step 4: Implement the Plugin Interface

Create a new C++ class that implements the Amibroker plugin interface. The interface consists of several pure virtual functions that you must implement:

GetDataParamCount(): Returns the number of data parameters required by the plugin.
GetDataParamName(): Returns the name of a data parameter.
GetDataParamType(): Returns the type of a data parameter (e.g., string, integer, float).
OpenConnection(): Opens a connection to the data source.
CloseConnection(): Closes the connection to the data source.
GetSymbol(): Returns a list of symbols (e.g., stocks, futures, forex) available from the data source.
GetBarCount(): Returns the number of bars available for a symbol.
GetBar(): Returns a single bar for a symbol.
GetQuote(): Returns a quote for a symbol.

Here's an example implementation:

class MyDataPlugin : public IDataPlugin
public:
    int GetDataParamCount()  return 2; 
    const char* GetDataParamName(int index)  return index == 0 ? "username" : "password"; 
    int GetDataParamType(int index)  return index == 0 ? PARAM_STRING : PARAM_STRING;
int OpenConnection()  /* open connection to data source */ return 1; 
    int CloseConnection()  /* close connection to data source */ return 1;
void GetSymbol(int index, char* symbol)  /* return symbol */ 
    int GetBarCount(const char* symbol)  /* return bar count */ return 100; 
    void GetBar(const char* symbol, int barIndex, float* open, float* high, float* low, float* close, float* volume)  /* return bar data */ 
    void GetQuote(const char* symbol, float* bid, float* ask)  /* return quote */ 
;

Step 5: Implement Data Loading

Implement the data loading functions to retrieve data from your data source. This may involve:

Reading data from a file
Querying a database
Calling an API

Here's an example implementation:

int MyDataPlugin::GetBar(const char* symbol, int barIndex, float* open, float* high, float* low, float* close, float* volume)
// Read data from a file
    FILE* file = fopen("data.csv", "r");
    if (file == NULL) return 0;
char line[1024];
    int index = 0;
    while (fgets(line, 1024, file) != NULL)
if (index == barIndex)
sscanf(line, "%f,%f,%f,%f,%f", open, high, low, close, volume);
            fclose(file);
            return 1;
index++;
fclose(file);
    return 0;

Step 6: Compile and Build the Plugin

Compile and build your plugin using your preferred IDE. Make sure to link against the Amibroker SDK libraries.

Step 7: Install the Plugin

Copy the compiled plugin (e.g., "MyDataPlugin.dll") to the Amibroker plugins directory (usually "C:\Program Files\Amibroker\Plugins").

Step 8: Configure Amibroker

Configure Amibroker to use your plugin:

Open Amibroker and go to "Tools" > "Preferences" > "Plugins"
Select your plugin from the list and click "Configure"
Enter any required parameters (e.g., username, password)

Step 9: Test the Plugin

Test your plugin by:

Creating a new analysis in Amibroker
Selecting your plugin as the data source
Verifying that data is loaded correctly

That's it! You now have a working Amibroker data plugin source code. Note that this is a basic guide, and you may need to modify the code to suit your specific requirements. Additionally, you may want to consider adding error handling, caching, and other features to improve performance and reliability.

The official resource for AmiBroker data plugin source code is the AmiBroker Development Kit (ADK). While the source code for proprietary plugins like Interactive Brokers is not publicly available, the ADK provides full example codes for various data plugins to help you build your own. Top Official & Community Resources

AmiBroker Development Kit (ADK): The definitive starting point for writing your own plugins. It includes C++ source code examples for plugins like QuoteTracker and QP2.

Access the ADK on GitLab for the base source files and documentation.

AmiBroker .NET SDK: If you prefer working with C# or .NET rather than native C++, this open-source SDK allows you to create data plugins more easily.

Explore the kriasoft AmiBroker .NET SDK on GitHub for full implementation details, including the DataSource.cs template.

WsRtd WebSocket Data Plugin: A modern, high-performance plugin that uses WebSocket-JSON communication for real-time data streaming.

Find the Rtd_Ws_AB_plugin source code on GitHub, which is broker-agnostic and supports historical backfilling.

Q2Ami Plugin: An open-source project on GitHub that provides headers like Plugin.h detailing the AmiBroker plugin interface structure. Quick Implementation Steps

Download the SDK: Start with either the official C++ ADK or the community .NET SDK.

Define Plugin Info: Update the GetPluginInfo() method with your plugin's metadata.

Implement Data Logic: Add your quote-fetching logic inside methods like GetQuotesEx() or the equivalent in your chosen language.

Install: Compile your code into a .dll and place it in the C:\Program Files\AmiBroker\Plugins directory.

Do you need help debugging a specific error in your plugin's C++ or .NET implementation?

Download the Ib.dll (data plugin) source code - Plug-ins - AmiBroker Community Forum amibroker data plugin source code top

The primary resource for developers is the AmiBroker Development Kit (ADK). It contains the essential header files and C++ sample code needed to interface with AmiBroker's internal architecture.

Core Functions: Every plugin requires three standard functions: GetPluginInfo(), Init(), and Release().

Sample Projects: The ADK typically includes a Data_Template folder containing Plugin.cpp and Plugin.h, which you can use as a skeleton for your own project.

Compatibility: While originally built with Visual C++ 6.0, these samples are compatible with modern IDEs like Visual Studio and free packages like DevC++. 2. .NET SDK and Community Plugins

For developers who prefer C# or VB.NET, the AmiBroker .NET SDK simplifies the process by providing a wrapper around the complex C++ interface.

GitHub Repository: High-quality source code for a .NET-based data source can be found on the KriaSoft AmiBroker GitHub.

Key File: Look at DataSource.cs in the repository for an example of how to implement GetQuotes() to return price data to AmiBroker.

Ease of Use: This SDK handles multithreading and memory management, which are notoriously difficult in native C++ plugin development. 3. Specialty & Open-Source Projects

There are several niche repositories that provide source code for specific types of data connections:

Websocket-JSON Plugin: The Rtd_Ws_AB_plugin repository provides code for connecting to modern web-based data streams using Python and WebSockets.

ODBC/SQL Universal Plugin: If your data is in a database, AmiBroker provides a built-in ODBC plugin. While the source code for the plugin itself may be closed, the AFL scripts to interact with it are widely documented.

Python Integration: Some community members use Python scripts to download data and save it as ASCII files that AmiBroker then "watches," effectively acting as a lightweight data bridge. 4. Implementation Checklist

When reviewing source code for your plugin, ensure it addresses these critical performance areas:

Optimizing Real-Time Data Plugin for Multiple Tickers - Plug-ins

Part 3: Top Open-Source Code Repositories (Where to Find Gold)

While Amibroker is closed-source, several top-tier developers have published reference implementations. Searching for "Amibroker data plugin source code top" typically leads to these archetypes:

Conclusion: Where to Find the "Top" Source Code

If you are serious about "amibroker data plugin source code top", you have three pathways:

Open Source Audit (Free): Search GitHub for "AmiBroker Plugin" with language filter "C++". Look for repositories updated within 2 years (showing active maintenance). Study IDataPlugin.cpp patterns.
Commercial SDK Purchase ($199–$499): Companies like Norgate Data provide full source with their premium subscription. This is the highest quality, production-tested code.
Contract Developer ($2k–$5k): Hire a freelancer who has previously compiled the AmiBroker SDK. Ask for their prior DataPlugin implementation as a code sample.

Final word from a 10-year veteran: The top source code isn't the one with the most features; it's the one that handles disconnections gracefully, uses zero polling, and survives a 10,000-tick-per-second stress test. Reverse-engineer the open-source examples, master the CRITICAL_SECTION, and you will build a plugin that rivals commercial offerings.

Disclaimer: AmiBroker is a registered trademark of AmiBroker.com. This article is for educational purposes. Always respect software licensing agreements when modifying or distributing plugin code.

To understand how AmiBroker data plugin source code works, it helps to view it through the lens of a developer building a bridge between raw financial data and a high-speed charting engine The Quest for "Total Control": A Developer’s Story

In the world of quantitative trading, data is everything. For many developers using

, the standard data feeds aren't enough—they need to connect to custom APIs, proprietary databases, or specialized brokers. This is where the AmiBroker Development Kit (ADK)

becomes the "holy grail" for those seeking "Total Control" over their data arrays. 1. Building the Foundation (The DLL) Our story begins in Microsoft Visual C++ (or even the free ). An AmiBroker data plugin is essentially a Win32 Dynamic Link Library (DLL)

. To make it talk to the main program, every plugin must expose three core functions: GetPluginInfo : Tells AmiBroker who you are (your plugin's name and ID).

: The handshake where the plugin wakes up and prepares its connections. : The graceful exit when the user closes the database. 2. The Bridge to Data A developer starts with a simple project template from the . They copy Plugin.cpp

into their workspace. In these files, they define how to handle "Quotes." The plugin acts as a translator: it takes incoming data (like a JSON stream from a WebSocket) and converts it into a format AmiBroker understands—specifically, an array of structures containing Date, Time, Open, High, Low, Close, and Volume. 3. Real-Time vs. Backfill Starting Data plug in project - Amibroker Forum

Developing a high-performance data plugin for AmiBroker requires a deep understanding of its C++ SDK and the mechanics of real-time data streaming. AmiBroker’s architecture is designed for speed, and its plugin system allows developers to feed external market data—whether from a REST API, WebSocket, or local database—directly into the software’s database engine. The Foundation of an AmiBroker Plugin

The core of any AmiBroker data plugin is a dynamic link library (DLL) written in C++. AmiBroker provides a specialized Software Development Kit (SDK) that defines the required entry points and structures. The most critical component is the PluginInfo structure, which tells AmiBroker the name of the plugin, its version, and what capabilities it supports, such as intraday data, tick-by-tick updates, or backfill functionality.

To initiate communication, the plugin must export several mandatory functions. The GetPluginInfo function is the first point of contact, providing metadata to the host application. Once the user selects the data source in AmiBroker's settings, the Init function is called to set up resources, while Release handles the cleanup when the application closes or the data source is changed. Managing Data Streams and Backfills

The true complexity of a data plugin lies in how it handles the GetQuotes and GetExtraData functions. AmiBroker operates on a "pull" or "notification" basis. When the software needs to update a chart, it calls the plugin to see if new data is available. A robust plugin must implement an efficient buffering system. Since market data often arrives in bursts, the plugin should store incoming ticks in a thread-safe queue and then flush them to AmiBroker's memory structures during the update cycle.

Backfilling is another essential feature. When a user opens a new symbol, the plugin must recognize that historical data is missing and trigger a request to the data provider's server. This is typically handled through a background thread to ensure that the AmiBroker user interface remains responsive while the historical bars are being downloaded and processed. Performance and Stability Considerations

Because AmiBroker is a 32-bit or 64-bit multi-threaded application, thread safety is paramount. Developers must use mutexes or critical sections when accessing shared data structures to prevent crashes. Furthermore, memory management must be impeccable; leaking memory in a data plugin will eventually lead to system instability, especially during long trading sessions where millions of ticks may be processed.

Optimization is also key. Using efficient data structures for symbol lookups, such as hash maps, and minimizing the overhead of string manipulations can significantly improve the speed at which the plugin feeds data to the UI. A well-coded plugin not only delivers data accurately but does so with minimal CPU footprint, allowing the user to run complex AFL (AmiBroker Formula Language) scripts without lag. Conclusion

Creating a top-tier AmiBroker data plugin is a bridge between raw financial data and sophisticated technical analysis. By mastering the C++ SDK, implementing reliable threading models, and ensuring efficient data throughput, a developer can create a seamless experience for traders. While the initial development curve is steep, the resulting ability to integrate any data source into AmiBroker provides a powerful competitive edge in the world of automated trading and market analysis.

Developing an AmiBroker data plugin requires using the AmiBroker Development Kit (ADK)

, which provides the necessary C/C++ headers and sample source code to link external data feeds into the AmiBroker engine. Core Architecture

AmiBroker data plugins are standard Win32 DLLs (32-bit or 64-bit) that implement a specific set of exported functions. The engine communicates with these DLLs to request price data for specific tickers and timeframes. about.gitlab.com 1. Required Standard Exports

Every AmiBroker plugin must export these three core functions: GetPluginInfo

: Returns basic metadata like the plugin name, vendor, and a unique 4-character ID (PIDCODE). : Called when the plugin is loaded to initialize resources. : Called when the plugin is unloaded to free memory. 2. Primary Data Functions

To act as a data source, the plugin must implement functions to provide quotes: GetQuotesEx

: The modern function for fetching historical and real-time data. It receives a ticker name and periodicity and must fill a buffer with price arrays (Open, High, Low, Close, Volume, etc.). GetPluginConfig

: (Optional) Provides a custom configuration dialog for users to enter API keys or server settings.

: Used to inform AmiBroker of status changes (e.g., connection lost or new data available). AmiBroker Community Forum Key Development Resources

Optimizing Real-Time Data Plugin for Multiple Tickers - Plug-ins

To develop an AmiBroker data plugin, you primarily need the AmiBroker Development Kit (ADK), which provides the necessary C++ headers and sample source code. For modern developers, there are also community-supported .NET alternatives that simplify the process. 1. Official AmiBroker Development Kit (ADK)

The official way to build a plugin is using the ADK, which includes the C++ API definitions and working examples for both indicator and data DLLs. The Developer’s Guide to AmiBroker Data Plugin Source

Latest Version: ADK 2.10a (supports 64-bit date/time and floating-point volume).

Core Files: Look for Plugin.cpp and Plugin.h within the Data_Template folder of the kit.

Documentation: The included ADK.html contains the full API specification for functions like GetQuotesEx.

Download: Available as a self-extracting ADK.exe or ADK.zip from the AmiBroker Download Page. 2. Open Source Examples & SDKs

If you prefer not to work directly in C++, several GitHub repositories provide modern wrappers and full plugin implementations: A AmiBroker Development Kit - GitLab

It sounds like you are looking for top-tier features to include in an Amibroker data plugin (real-time or historical feed), specifically if you are writing or evaluating source code for one.

Below is a ranked list of must-have, advanced, and competitive features to implement in high-quality Amibroker data plugin source code.

Final Recommendation for Your "Top" Feature Set

If you can only implement 5 features to claim "top tier":

64-bit + 32-bit support
Asynchronous real-time with tick aggregation
Intraday backfill on-demand
External config file + logging
Auto-reconnection with gap detection

Would you like a code skeleton (C++ example) for an Amibroker plugin with these features?

Building a High-Performance AmiBroker Data Plugin: A Deep Dive into Source Code and Architecture

AmiBroker is renowned among quantitative traders for its blistering backtesting speed and flexibility. However, the software is only as good as the data feeding it. While many commercial vendors offer ready-made connectors, developing your own AmiBroker data plugin using the source code SDK allows for unparalleled customization—whether you’re plugging into a proprietary API, a crypto exchange, or a niche local database.

In this guide, we will explore the structural "top" tier of AmiBroker data plugin development, breaking down the C++ SDK essentials and how to optimize your source code for real-time performance. 1. The AmiBroker Development Kit (ADK)

To start, you need the AmiBroker Development Kit (ADK). This is a collection of C-style headers and sample C++ projects provided by AmiBroker's creator, Tomasz Janeczko. The ADK defines the standard interface that allows the Broker.exe process to communicate with external DLLs. Key Files in the Source:

Plugin.h: The core header file containing structure definitions like Quotations, StockInfo, and PluginInfo.

AmiRoot.cpp/h: Often used as the entry point for managing the connection lifecycle. 2. Core Functions Every Plugin Needs

When you look at the top-performing data plugin source codes, they all implement a specific set of exported functions. Without these, AmiBroker won't recognize your DLL. GetPluginInfo

This identifies your plugin to the system. It returns the name, vendor, and type of plugin (Data, Indicator, or Tools).

__declspec(dllexport) int GetPluginInfo(struct PluginInfo *pInfo) pInfo->Name = "Custom SQL Connector"; pInfo->Vendor = "YourName Quant Lab"; pInfo->Type = 1; // 1 for Data Plugin return 1; Use code with caution. GetQuotes

This is the "engine room." When AmiBroker needs data for a chart, it calls GetQuotes. A high-performance plugin source code should implement intelligent caching here. Instead of hitting your API every time a user scrolls, the plugin should store data in a local buffer. 3. Real-Time Streaming vs. Backfill

The "top" tier of plugins are those that handle both historical backfill and real-time "tick" data seamlessly.

Historical Backfill: Uses a loop to populate the Quotations array. Efficiency here depends on how you handle memory allocation—pre-allocating the array size based on the expected date range is a common optimization.

Real-Time Streaming: Requires a multi-threaded approach. Your source code should have a background thread listening to a WebSocket or Socket connection, pushing new ticks into a thread-safe queue that GetQuotesEx can then drain. 4. Best Practices for Professional Source Code

If you are searching for "top" source code examples, look for these architectural patterns:

Thread Safety: Since AmiBroker may request data for multiple charts simultaneously, your internal data structures (like a std::map of symbols) must be protected by Mutexes or Critical Sections.

Error Logging: Implement a robust logging system that writes to the AmiBroker "Log" window using SiteContext->LogMessage(). This makes debugging connection drops much easier.

Adaptive Polling: Top-tier plugins adjust their request frequency based on whether a symbol is currently being viewed or if it's just being updated in the background. 5. Where to Find Source Code Examples?

While the official ADK includes a "Universal Data Plug-in" sample, it is quite basic. For more advanced implementations, developers often look toward:

GitHub Repositories: Search for "AmiBroker Plugin C++" to find wrappers for modern APIs like Interactive Brokers (IBKR) or IQFeed.

AmiBroker Custom Dev Forum: A hub for veteran coders sharing snippets for specific data formats like JSON or Protocol Buffers. Conclusion

Writing an AmiBroker data plugin is a rite of passage for serious systems traders. By mastering the ADK and focusing on thread-safe, cached data delivery, you can build a connector that matches the speed of the software it feeds.

The most authoritative "paper" and resource for AmiBroker data plugin source code is the AmiBroker Development Kit (ADK). It provides the official C/C++ header files, source code samples, and documentation necessary to interface with AmiBroker's internal structures. Official AmiBroker Development Kit (ADK)

The ADK is the primary reference for creating data plugins. It includes updated documentation and samples for 64-bit date/time resolution and floating-point volume fields.

Documentation & Headers: Contains the PluginInfo and Quotation structures required for data handling.

Key Functions: Focuses on functions like GetQuotesEx() for handling real-time and historical data streams. Download Links: Official EXE: ADK.exe Official ZIP: ADK.zip Git Mirror: AmiBroker Development Kit on GitLab Modern SDK Alternatives

If you prefer higher-level languages like C#, several open-source wrappers provide pre-built templates: Amibroker Data Plugin Source Code Top _hot_

Developing a custom data plugin for AmiBroker allows you to stream real-time or historical market data from any source directly into the software's high-speed database. This is typically achieved using the AmiBroker Development Kit (ADK), which provides the necessary C/C++ headers and architectural guidelines. 1. Core Architecture and ADK

AmiBroker data plugins are regular Win32 Dynamic Link Libraries (.dll). To build one, you must implement specific exported functions that AmiBroker calls to communicate with your data source. Essential Exported Functions: Every plugin must include:

GetPluginInfo: Returns metadata like the plugin name, vendor, and a unique ID code to prevent conflicts.

Init() and Release(): Handle the setup and teardown of the plugin.

GetQuotesEx: The primary function for retrieving data. It handles 64-bit date/time stamps and floating-point values for volume and open interest.

Notify: Receives notifications from AmiBroker regarding database loads, unloads, or settings changes. 2. Available Source Code Templates

Developers can find starting points in several languages, depending on their expertise:

Native C/C++ (Official): The AmiBroker ADK is the standard tool. It includes a "Data_Template" project that can be compiled with Visual C++ 6.0 or newer versions like Visual Studio 2022.

C# / .NET SDK: For those preferring managed code, the AmiBroker .NET SDK on GitHub provides a wrapper that allows you to write plugins in C#.

Python Integration: While Python is often used for data scraping or "feeder" scripts (e.g., ami2py), a true data plugin typically requires a DLL bridge. 3. Implementation Patterns Modern plugins often use a two-part architecture: Conclusion: Mastering the Source Code The search for

A Connector: A script (often Python or Node.js) that fetches data via WebSockets or REST APIs from a broker or data provider.

The DLL Plugin: A compiled C++ or C# library that sits inside the AmiBroker/Plugins folder and feeds that data into the GetQuotesEx buffer. Starting Data plug in project - Amibroker Forum

Overview

The Amibroker data plugin source code provides a set of APIs and interfaces for developers to create custom data plugins that can feed data into Amibroker. The plugins can be written in C++ or C# and use Amibroker's proprietary API.

Plugin Architecture

The Amibroker data plugin architecture consists of the following components:

Data Plugin DLL: A dynamic-link library (DLL) that contains the plugin's code and implements the Amibroker data plugin interface.
Amibroker API: A set of COM (Component Object Model) interfaces that provide access to Amibroker's data and functionality.

Key Functions

The Amibroker data plugin source code provides several key functions that developers can use to create custom data plugins:

GetQuote: Retrieves a single quote (e.g., bid, ask, or last price) for a specific symbol.
GetBar: Retrieves a single bar (e.g., OHLCV data) for a specific symbol and time interval.
GetBars: Retrieves multiple bars for a specific symbol and time interval.
GetSymbolInfo: Retrieves information about a specific symbol, such as its name, exchange, and currency.

Plugin Types

Amibroker supports several types of data plugins:

Real-time plugin: Provides real-time data to Amibroker.
Historical plugin: Provides historical data to Amibroker.
Both: Provides both real-time and historical data to Amibroker.

Code Structure

The Amibroker data plugin source code typically consists of:

Plugin class: Implements the Amibroker data plugin interface and provides the necessary functions (e.g., GetQuote, GetBar, etc.).
API wrapper class: Wraps the Amibroker API and provides a simpler interface for the plugin class.

Example Code

Here's an example of a simple Amibroker data plugin written in C++:

#include <Amibroker/ABDataPlugin.h>
class MyDataPlugin : public CAbDataPlugin
public:
    virtual HRESULT STDMETHODCALLTYPE GetQuote(BSTR symbol, VARIANT* quote) override
// Implement GetQuote function
virtual HRESULT STDMETHODCALLTYPE GetBar(BSTR symbol, int interval, VARIANT* bar) override
// Implement GetBar function
;
extern "C" __declspec(dllexport) HRESULT STDMETHODCALLTYPE AbPluginGetInstance(IAbDataPlugin** plugin)
*plugin = new MyDataPlugin();
    return S_OK;

This example demonstrates a basic data plugin that implements the GetQuote and GetBar functions.

Top-level Source Code Files

The top-level source code files for Amibroker data plugins typically include:

AbDataPlugin.h: The header file for the Amibroker data plugin interface.
AbAPI.h: The header file for the Amibroker API.
Plugin.cpp: The implementation file for the data plugin.

Challenges and Best Practices

When developing Amibroker data plugins, developers should be aware of the following challenges and best practices:

Thread-safety: Data plugins must be thread-safe to ensure that Amibroker can access the data concurrently.
Error handling: Data plugins must handle errors properly to prevent crashes or data corruption.
Performance optimization: Data plugins should be optimized for performance to ensure fast data retrieval and processing.

Overall, the Amibroker data plugin source code provides a powerful and flexible way to extend Amibroker's capabilities and connect to custom data feeds. By understanding the plugin architecture, key functions, and best practices, developers can create high-quality data plugins that meet their specific needs.

A very specific request!

Amibroker is a popular technical analysis and trading platform, and its data plugin architecture allows developers to create custom plugins to fetch and manage data from various sources.

Here's a useful paper covering the Amibroker data plugin source code:

Amibroker Data Plugin Development Guide

Introduction

Amibroker provides a powerful data plugin architecture that allows developers to create custom plugins to fetch and manage data from various sources. This guide provides an overview of the Amibroker data plugin development process, including the plugin architecture, data structures, and API.

Plugin Architecture

An Amibroker data plugin consists of a DLL (Dynamic Link Library) file that exports a set of functions. These functions are used by Amibroker to interact with the plugin and retrieve data. The plugin architecture is based on the following components:

Plugin Interface: The plugin interface is the entry point for Amibroker to interact with the plugin. It consists of a set of exported functions that provide data and metadata to Amibroker.
Data Source: The data source is the actual data provider, which can be a database, a file, or a network connection.

Data Structures

Amibroker uses a set of data structures to represent financial data, including:

Bar: A bar represents a single data point, consisting of a timestamp, open, high, low, close, and volume.
Quote: A quote represents a single data point, consisting of a timestamp, bid, ask, and volume.

API

The Amibroker data plugin API provides a set of functions that must be implemented by the plugin developer. These functions include:

GetBar: Retrieves a single bar from the data source.
GetQuote: Retrieves a single quote from the data source.
GetSymbolInfo: Retrieves metadata about a symbol, such as its name, exchange, and currency.
GetTicker: Retrieves a list of tickers (symbols) supported by the plugin.

Example Plugin Source Code

Here's an example plugin source code in C++ that demonstrates a simple data plugin that reads data from a CSV file:

#include <Amibroker/Plugin.h>
// Define the plugin interface
extern "C" 
    __declspec(dllexport) int GetBar( const char *symbol, int period, int index, Bar *bar )
// Read data from CSV file
        FILE *file = fopen("data.csv", "r");
        if (file == NULL) return 0;
// Find the symbol and period
        char line[1024];
        while (fgets(line, 1024, file)) 
            if (strstr(line, symbol) != NULL && strstr(line, period) != NULL) 
                // Parse the bar data
                sscanf(line, "%d,%f,%f,%f,%f,%f", &bar->time, &bar->open, &bar->high, &bar->low, &bar->close, &bar->volume);
                fclose(file);
                return 1;
fclose(file);
        return 0;
__declspec(dllexport) int GetQuote( const char *symbol, Quote *quote )
// Not implemented
        return 0;
__declspec(dllexport) int GetSymbolInfo( const char *symbol, SymbolInfo *info )
// Not implemented
        return 0;
__declspec(dllexport) int GetTicker( int index, char *ticker )
// Not implemented
        return 0;

This example plugin provides a basic implementation of the GetBar function, which reads data from a CSV file.

Conclusion

Developing an Amibroker data plugin requires a good understanding of the plugin architecture, data structures, and API. This guide provides a useful overview of the development process, and the example plugin source code demonstrates a simple data plugin that reads data from a CSV file. With this information, you can create your own custom data plugins to fetch and manage data from various sources.

AmiBroker data plugins are specialized Dynamic Link Libraries (DLLs) that bridge the software with external data sources like real-time brokers, proprietary databases, or web services. Core Architecture of a Data Plugin

To create a functional data plugin, you must implement specific exported functions defined in the AmiBroker Development Kit (ADK).

GetPluginInfo(): The most critical entry point. AmiBroker scans the Plugins folder and ignores any DLL that does not export this function. It provides metadata like the plugin name, vendor, and version.

GetQuotesEx(): The primary function for data retrieval. It handles the actual request for price bars (OHLCV) and allows for 64-bit date/time stamps and floating-point volume.

Notify(): Used by AmiBroker to signal events to the plugin, such as when a database is loaded or unloaded.

GetStatus(): An optional function that reports the connection health (e.g., "Connected", "Trying to connect...") to the AmiBroker UI. Top Source Code Examples

Development typically uses C++ (via the ADK) or .NET (C#/VB.NET). ODBC/SQL Universal Data/AFL plugins - AmiBroker

The Developer’s Guide to AmiBroker Data Plugin Source Code: Top Resources & Examples

Conclusion: Mastering the Source Code

Top takeaways for your own source code:

Always compile with _UNICODE and WIN64.
Never block inside GetQuotesEx longer than 10ms.
Use a free, open-source reference like the "AmiDevKit" (available on GitHub) as your foundation.
Respect the QUOTETYPE flags (HISTORY, REALTIME, SNAPSHOT) – mixing them up is the #1 reason for "Data not refreshing" errors.

By building or auditing a plugin with these principles, you will join an elite group of traders who control their data pipeline end-to-end. Happy coding, and may your backtests be accurate.

Disclaimer: Amibroker is a trademark of Amibroker.com. This article is for educational purposes. Always refer to the official SDK license.

Introduction

Prerequisites

Before you start, make sure you have:

Amibroker installed on your system (version 5.20 or later)
A basic understanding of C++ programming language
A data source (e.g., a database, API, or file) that you want to connect to Amibroker

Step 1: Choose a Data Source

Select a data source that you want to connect to Amibroker. This could be a:

Database (e.g., MySQL, PostgreSQL, SQLite)
API (e.g., Quandl, Alpha Vantage, Intrinio)
File (e.g., CSV, JSON, XML)

Step 2: Create a New Plugin Project

Create a new C++ project in your preferred IDE (e.g., Visual Studio, Xcode, Eclipse). Name your project (e.g., "MyDataPlugin").

Step 3: Include Amibroker SDK

Step 4: Implement the Plugin Interface

Create a new C++ class that implements the Amibroker plugin interface. The interface consists of several pure virtual functions that you must implement:

GetDataParamCount(): Returns the number of data parameters required by the plugin.
GetDataParamName(): Returns the name of a data parameter.
GetDataParamType(): Returns the type of a data parameter (e.g., string, integer, float).
OpenConnection(): Opens a connection to the data source.
CloseConnection(): Closes the connection to the data source.
GetSymbol(): Returns a list of symbols (e.g., stocks, futures, forex) available from the data source.
GetBarCount(): Returns the number of bars available for a symbol.
GetBar(): Returns a single bar for a symbol.
GetQuote(): Returns a quote for a symbol.

Here's an example implementation:

class MyDataPlugin : public IDataPlugin
public:
    int GetDataParamCount()  return 2; 
    const char* GetDataParamName(int index)  return index == 0 ? "username" : "password"; 
    int GetDataParamType(int index)  return index == 0 ? PARAM_STRING : PARAM_STRING;
int OpenConnection()  /* open connection to data source */ return 1; 
    int CloseConnection()  /* close connection to data source */ return 1;
void GetSymbol(int index, char* symbol)  /* return symbol */ 
    int GetBarCount(const char* symbol)  /* return bar count */ return 100; 
    void GetBar(const char* symbol, int barIndex, float* open, float* high, float* low, float* close, float* volume)  /* return bar data */ 
    void GetQuote(const char* symbol, float* bid, float* ask)  /* return quote */ 
;

Step 5: Implement Data Loading

Implement the data loading functions to retrieve data from your data source. This may involve:

Reading data from a file
Querying a database
Calling an API

Here's an example implementation:

int MyDataPlugin::GetBar(const char* symbol, int barIndex, float* open, float* high, float* low, float* close, float* volume)
// Read data from a file
    FILE* file = fopen("data.csv", "r");
    if (file == NULL) return 0;
char line[1024];
    int index = 0;
    while (fgets(line, 1024, file) != NULL)
if (index == barIndex)
sscanf(line, "%f,%f,%f,%f,%f", open, high, low, close, volume);
            fclose(file);
            return 1;
index++;
fclose(file);
    return 0;

Step 6: Compile and Build the Plugin

Compile and build your plugin using your preferred IDE. Make sure to link against the Amibroker SDK libraries.

Step 7: Install the Plugin

Copy the compiled plugin (e.g., "MyDataPlugin.dll") to the Amibroker plugins directory (usually "C:\Program Files\Amibroker\Plugins").

Step 8: Configure Amibroker

Configure Amibroker to use your plugin:

Open Amibroker and go to "Tools" > "Preferences" > "Plugins"
Select your plugin from the list and click "Configure"
Enter any required parameters (e.g., username, password)

Step 9: Test the Plugin

Test your plugin by:

Creating a new analysis in Amibroker
Selecting your plugin as the data source
Verifying that data is loaded correctly