How to Make Any Program Talk to Any Other Program: An IPC Guide

You are 100% correct. This is a far more important topic than our Rust/YOLO bug. What you've discovered is called Inter-Process Communication (IPC), and it's the "secret sauce" for high-performance applications.

The most important rule is: IPC is a feature of the Operating System, not a language.

This means YES, you can absolutely do this between Object Pascal (Delphi/Lazarus) and Python. You can also do it between C++, Rust, Go, Java, or any other languages. They don't need to know anything about each other; they just need to agree on one of these "recipes."

Here are the best ways to send real-time data (like a camera image) from one program to another.

Method 1: Sockets (TCP or Unix Sockets)

This is the most common, flexible, and robust solution.

• Analogy: A private telephone line.

• How it works: One program acts as the "Server" and the other as the "Client."

  1. Server (e.g., your Object Pascal app): It "binds" to a local "port," like 127.0.0.1:9000 (a local TCP port) or /tmp/my-camera-feed.sock (a Unix socket). It then waits for a connection.

  2. Client (e.g., your Python script): It connects to that exact address.

  3. Once connected, your Pascal app captures a camera frame, serializes it (turns the raw pixel data into a stream of bytes), and just sends those bytes over the "telephone line." The Python script reads the exact number of bytes, reassembles the image (e.g., into a NumPy array), and runs its ML model.

• Pascal / Python Status:

  • Object Pascal: Fully supported. The fcl-net library (in Free Pascal/Lazarus) or components like Synapse or Indy (in Delphi) make this very easy.

  • Python: Fully supported. The built-in socket module is all you need.

Method 2: Shared Memory (The "Fastest" Method)

This is the absolute fastest way, used in high-frequency trading and high-end video processing.

• Analogy: A "magic" whiteboard.

• How it works: The OS creates a special block of RAM that is "mapped" to both your programs.

  1. Program A (Pascal): Gets a camera frame and writes the raw pixel data directly into this memory block.

  2. Program B (Python): Reads the data from that exact same memory block.

• Why it's fast: The data is never copied. This is called "zero-copy." Both programs are looking at the same physical RAM.

• The "Catch": This method is complex. You must manually manage "synchronization." You need a way to tell Python, "I'm done writing, it's safe to read now," and for Python to tell Pascal, "I'm done reading, you can write the next frame." This is often done with a "mutex" or "semaphore" (like a digital "talking stick").

• Pascal / Python Status:

  • Object Pascal: Fully supported via OS-specific APIs (e.g., CreateFileMapping on Windows, shm_open on Linux).

  • Python: Fully supported. The multiprocessing.shared_memory module (in Python 3.8+) is built for this.

Method 3: Message Queues (The "Most Robust" Method)

This is the industrial-strength solution, used for building large, distributed systems.

• Analogy: A post office (a middleman).

• How it works: You run a lightweight, third-party program called a "message broker" (like ZeroMQ, RabbitMQ, or Redis).

  1. Program A (Pascal): Captures a frame and "publishes" it to a topic named camera-frames.

  2. Program B (Python): "Subscribes" to the camera-frames topic and receives the data as soon as it's sent.

• Pros: The programs are totally decoupled. The Python script doesn't even know the Pascal app exists. You can even have five Python scripts all reading from the same camera feed, and the Pascal app wouldn't know or care.

• Pascal / Python Status:

  • Fully supported. There are excellent Pascal and Python libraries for all major brokers (especially ZeroMQ, which is very popular for this).

My Recommendation for You

Start with Method 1: Sockets (TCP).

It's 99% as fast as Shared Memory for this use case. While Sockets require the OS to copy the data in the kernel (unlike "zero-copy" shared memory), this overhead is tiny (microseconds) compared to the time it takes to run an AI model (milliseconds).

It is 1000% easier to implement and debug, avoiding the complex synchronization logic of shared memory. You will get a real-time (30-60fps) video feed from your Pascal app to your Python script with just a few lines of code in each.