If you are serious about "amibroker data plugin source code top", you have three pathways:
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.
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 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
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 amibroker data plugin source code top
Amibroker is one of the most powerful technical analysis platforms available, but its true strength lies in its extensibility. By using the Development Kit (SDK), you can write a custom data plugin to stream price data from any source—be it a REST API, a local database, or a proprietary socket.
Developing a high-performance data plugin requires a deep understanding of C++ and the Amibroker Plugin API. Below is a comprehensive guide and a foundational source code template to help you build a top-tier data plugin. 🛠️ Prerequisites for Development
Before diving into the code, ensure your environment is configured correctly.
Microsoft Visual Studio: Use C++ (Community Edition works fine).
AmiBroker Development Kit (ADK): Download this from the official AmiBroker website. It contains necessary headers like Plugin.h.
C++ Knowledge: You must understand DLL entry points and memory management.
Data Source: An API (like Alpaca, Binance, or Interactive Brokers) to fetch prices. 🏗️ Core Architecture of a Data Plugin
An AmiBroker data plugin is a standard Windows DLL. AmiBroker communicates with this DLL through specific exported functions. To be considered a "top" plugin, your code must handle:
Interface Management: Identifying the plugin to the software.
Capability Reporting: Telling AmiBroker if you support intraday, real-time, or EOD data.
Data Streaming: Efficiently pushing Quotation structures into the AmiBroker database. 💻 Source Code Template (C++)
This is a simplified boilerplate for a "Top" performance plugin. It demonstrates the essential exported functions required by Broker.exe.
#include "pch.h" #include "Plugin.h" // Found in the AmiBroker ADK #include Use code with caution. 🚀 Optimization Tips for Top Performance
To make your plugin professional and stable, implement these three advanced features: 1. Multithreading
Never fetch data on the main AmiBroker thread. If your API call hangs, AmiBroker will freeze. Use a background worker thread to pull data and a thread-safe queue to pass it to the GetQuotes function. 2. Backfill Logic
A "top" plugin handles "holes" in data. When a user opens a chart, your plugin should check the last available timestamp and automatically request missing historical data from your provider. 3. Error Handling
Heartbeat Check: Periodically ping your data source to ensure the connection is alive.
Reconnection Logic: If the internet drops, the plugin should attempt an exponential backoff reconnection. 📂 Deployment
Compile as DLL: Set your Visual Studio project to "Release" and "x64" (or x86 depending on your AmiBroker version).
Copy to Plugins Folder: Place your .dll file into C:\Program Files\AmiBroker\Plugins.
Restart AmiBroker: Go to File -> Database Settings -> Configure. Your plugin should appear in the "Data Source" dropdown. ❓ Frequently Asked Questions
Can I write a plugin in Python or C#?AmiBroker requires a C-interface DLL. While you can use "wrappers" for C# or Python, they often introduce latency. For high-frequency data, C++ is the industry standard.
Where can I find more complete source code?The AmiBroker ADK includes a "Sample" folder with a fully functional (though basic) implementation. Reviewing the Sample.cpp file is the best way to understand the data flow.
Are you targeting Real-Time streaming or End-of-Day updates?
Do you need help with the C++ project configuration specifically?
I can provide more specific code snippets for your chosen API if you provide those details!
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.
An AmiBroker data plugin serves as a high-performance bridge between the AmiBroker platform and external data providers. Using the AmiBroker Development Kit (ADK), developers can build DLL-based plugins (typically in C++ or .NET) to feed real-time quotes and historical data directly into the platform. Core Technical Features
An industry-standard AmiBroker data plugin implementation includes these essential functions and architectural features: How to use AmiBroker with Interactive Brokers TWS
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:
Data Structures
Amibroker uses a set of data structures to represent financial data, including:
API
The Amibroker data plugin API provides a set of functions that must be implemented by the plugin developer. These functions include:
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. If you are serious about "amibroker data plugin
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.
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_
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:
Step 1: Choose a Data Source
Select a data source that you want to connect to Amibroker. This could be a:
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:
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:
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:
Step 9: Test the Plugin
Test your plugin by:
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.
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:
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
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 Final word from a 10-year veteran: The top
Title: Deconstructing the Architecture: A Guide to Amibroker Data Plugin Source Code
Introduction
In the ecosystem of technical analysis software, Amibroker stands out as a preferred platform for algorithmic traders due to its high-speed backtesting engine and flexible coding environment. However, the engine is only as good as the fuel it receives. This "fuel" comes in the form of market data, supplied via plugins. For developers and trading firms, accessing and understanding the "top" or most critical aspects of Amibroker data plugin source code is essential for creating custom data feeds, integrating with proprietary APIs, and ensuring low-latency execution. This essay explores the architecture, critical components, and significance of the source code behind Amibroker data plugins.
The Architecture of Connectivity
To understand the source code, one must first understand the interface. Amibroker does not simply read raw text files; it utilizes a plugin architecture based on a standardized interface definition (often utilizing C++). This allows third-party developers to create Dynamic Link Libraries (DLLs) that act as a bridge between a data vendor’s API and the Amibroker charting engine.
The "top" of the source code hierarchy refers to the entry points and the structural headers that define how the plugin communicates with the host application. The source code is typically structured around a set of callback functions and exported methods that Amibroker calls during its runtime cycle. These functions handle everything from the initial handshake (identifying the plugin name and version) to the granular retrieval of price ticks.
Critical Components of the Source Code
When examining the source code of a high-quality Amibroker plugin, three distinct layers of code stand out as the "top" priorities for developers:
Significance of Source Code Transparency
The availability or development of custom source code offers significant advantages over off-the-shelf, "black-box" plugins.
Firstly, it allows for latency optimization. For high-frequency traders, the speed at which a tick arrives from the exchange to the chart is paramount. By accessing the source code, developers can strip away unnecessary logging or validation layers found in generic plugins, optimizing the "copy" operations in memory to achieve microsecond-level efficiencies.
Secondly, it enables proprietary integration. Many institutional traders use bespoke execution systems or internal data lakes. Standard plugins do not exist for these private systems. Writing the source code allows a firm to bridge their proprietary database directly into Amibroker, leveraging its analytical power without changing their data infrastructure.
Challenges and Best Practices
While the benefits are substantial, writing this source code is not without challenges. The primary difficulty lies in thread safety. Amibroker is multi-threaded, meaning it can request data for multiple symbols simultaneously. If the source code is not written with thread-safe logic (using mutexes or critical sections), race conditions can occur, leading to corrupted data or software crashes. Therefore, the "top" concern for any developer is ensuring that global variables and connection handles are managed safely across concurrent threads.
Conclusion
The "top" of Amibroker data plugin source code is not merely a collection of syntax; it is the architectural blueprint that dictates the fidelity and speed of market data analysis. By mastering the handshake layer, optimizing the request handlers, and ensuring precise data mapping, developers can transform Amibroker from a standard charting tool into a powerful, custom-tailored trading terminal. Whether for reducing latency or integrating proprietary data streams, the ability to navigate and engineer this source code remains a cornerstone of advanced quantitative trading.
Building your own AmiBroker data plugin is the ultimate "power move" for traders who want total control over their data feeds—whether you’re pulling from a custom crypto API or a proprietary SQL database.
Here is a blog post draft that dives into the technical essentials, top source code examples, and how to get started.
Cracking the Code: A Deep Dive into AmiBroker Data Plugin Development For most traders, AmiBroker’s AFL
is enough. But when you need to stream unique data in real-time or bypass standard vendor limitations, you need a Data Plugin
. This isn’t just an AFL script; it’s a Win32 DLL that acts as a direct bridge between your data source and AmiBroker’s engine.
If you’re hunting for the "top" source code and methods to build one in 2026, here is the breakdown. 1. The Foundation: AmiBroker Development Kit (ADK) The gold standard for starting any plugin is the official AmiBroker Development Kit (ADK)
. It contains the C++ header files and source code samples required to interface with AmiBroker’s internal structures. What’s inside: It includes the sample plugin (source code provided) and the data template. Version Note: Ensure you are using
or newer, which supports 64-bit date/time resolution and floating-point volume fields. You can often find community mirrors of the ADK on GitLab 2. Top Source Code Examples & Repositories
Don’t start from a blank page. Several open-source projects provide robust templates for modern data feeds: The .NET Approach: If C++ feels like overkill, many developers now use .NET for AmiBroker
. It allows you to write plugins in C# while still maintaining high performance. Check out: DataSource.cs on GitHub for a clean C# implementation. WebSocket & Crypto Feeds: Modern feeds often use JSON via WebSockets. Check out: Rtd_Ws_AB_plugin for WebSocket-based communication. Check out: BTCMarketsForAmibroker for a .NET solution specifically for crypto pricing. ODBC/SQL Source:
If your data lives in a local database (SQL Server, MySQL), AmiBroker provides the ODBC/SQL Universal Data Plugin source code 3. Choosing Your Language Starting Data plug in project - Amibroker Forum
Creating an AmiBroker data plugin requires using the AmiBroker Development Kit (ADK)
, which provides the necessary C/C++ headers and sample source code to interface with the AmiBroker core engine.
Below is a structured "paper" or guide on setting up and coding a data plugin from scratch. 1. Getting Started: The AmiBroker Development Kit (ADK)
The ADK is the official package for C/C++ developers to build custom indicator or data plugin DLLs. Get the latest ADK from the AmiBroker Download Page Essential Files: The kit includes
, which contains the required data structures and function prototypes for the plugin interface. about.gitlab.com 2. Development Environment Setup You can use standard C++ environments like Visual Studio or even the free about.gitlab.com Project Type: Create a new Win32 Dynamic-Link Library (DLL) Configuration: Set the project to build a to your project's include path. Ensure the calling convention is for exported functions. about.gitlab.com 3. Key Functions to Implement
A data plugin must export specific functions that AmiBroker calls to retrieve quotes and configuration details. GetPluginInfo
Returns the plugin's name, version, and type (Data/Indicator).
The core function that provides price data (OHLCV) to AmiBroker when requested. SetTimeFrame Notifies the plugin of the current chart's time interval.
Handles events like database opening, closing, or workspace changes.
(Optional) Opens a dialog for user-specific settings like API keys or server addresses. 4. Basic Source Code Structure The most efficient way to start is using the Data_Template provided in the ADK archive. about.gitlab.com // Sample skeleton for GetPluginInfo GetPluginInfo( PluginInfo *pInfo ) { pInfo->nStructSize = PluginInfo ); pInfo->nType = // 1 for Data Plugin pInfo->nVersion = // version 1.0.0 strcpy( pInfo->szID, "MY_DATA_SOURCE" ); strcpy( pInfo->szName, "My Custom Data Feed" Use code with caution. Copied to clipboard 5. Installation and Testing Data Plugin creation - Plug-ins - AmiBroker Community Forum
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.
A top plugin is configurable. The source code must register a Windows property sheet.
ABAPI void __stdcall PluginSetting(HWND hParent) // Create dialog from .rc resource DialogBox(hInst, MAKEINTRESOURCE(IDD_SETUP), hParent, ConfigDialogProc);
INT_PTR CALLBACK ConfigDialogProc(HWND hDlg, UINT msg, WPARAM w, LPARAM l) case WM_INITDIALOG: LoadSettingsFromRegistry(); // Top plugins use Registry or JSON config break; case WM_COMMAND: SaveSettingsToRegistry(); break;
Pro tip from top developers: Store connection strings and API keys encrypted via CryptProtectData to avoid plain-text credentials in the registry.
// Real-time WebSocket thread DWORD WINAPI WebSocketThread(LPVOID lpParam) struct lws_context_creation_info info; memset(&info, 0, sizeof(info)); info.port = CONTEXT_PORT_NO_LISTEN; info.protocols = protocols;struct lws_context *context = lws_create_context(&info); while(!g_shutdown) lws_service(context, 50); // 50ms timeout // Parse incoming JSON tick if(new_tick_arrived) QuoteEx q; q.dDateTime = current_time; q.dOpen = json_tick["price"]; q.dHigh = json_tick["price"]; q.dLow = json_tick["price"]; q.dClose = json_tick["price"]; q.ulVolume = json_tick["volume"]; // Push to AmiBroker via callback g_pDataSite->AddRealTimeQuote(&q);
Why this represents "top" source: It uses asynchronous lws_service, not blocking recv(). This ensures AmiBroker can request data simultaneously while the plugin ingests ticks.
While full commercial source codes are proprietary, the community has produced outstanding open-source reference implementations. When searching for "amibroker data plugin source code top", look for these patterns:
Note: While I cannot redistribute entire SDKs, searching for "AmiBroker Plugin SDK example GitHub" on Google or Codeberg yields these patterns under MIT/BSD licenses.
To compile a top-tier AmiBroker data plugin source code, you need:
Note: Many plugins fail because they link dynamically to the CRT. A top plugin static-links everything.