Up and running in ten lines

#include <task_graph/task_graph.hpp>

using namespace task_graph;

int main() {
    DAG dag;

    auto fetch = std::make_shared<Task>("fetch", [](TaskContext& ctx) {
        return TaskResult{.status = TaskStatus::COMPLETED, .value = std::string("user_123")};
    });
    auto process = std::make_shared<Task>("process", [](TaskContext& ctx) {
        auto data = ctx.input<std::string>("in");
        return TaskResult{.status = TaskStatus::COMPLETED,
                          .value = std::string(*data + "_processed")};
    });

    dag.add_task(fetch);
    dag.add_task(process);
    dag.connect("fetch", "process");               // out -> in

    DAGExecutor executor;
    executor.execute(dag).wait();
}

Graphs as data

The same graph can be expressed as JSON, loaded by DAGSerializer::from_string and executed by DAGExecutor — exactly the format GraphStudio saves and loads:

{
  "version": "2.0",
  "tasks": [
    { "id": "src", "type": "opencv_image_read", "params": { "file_path": "test.png" } },
    { "id": "gaussian", "type": "opencv_gaussian_blur_filter" },
    { "id": "sobel", "type": "opencv_sobel_filter" }
  ],
  "edges": [
    { "from": "src", "from_port": "out", "to": "gaussian", "to_port": "in" },
    { "from": "gaussian", "from_port": "out", "to": "sobel", "to_port": "in" }
  ]
}

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