Racer
Racer is a simple Python task runner framework that supports sequential and parallel task execution. It also allows the result of one task to be passed to the next, making it flexible for various workflows.
Features
- Task Execution: Run tasks sequentially or in parallel.
- Task Result Propagation: Optionally pass the result of a task to the next task in the queue.
- Multithreading Support: Execute tasks in parallel using multiple threads.
- Customizable Tasks: Easily define custom tasks by extending the
BaseTaskclass.
Getting Started
Basic Usage
Define your tasks using either the Task or ParallelTask class, then use the Racer class to run them sequentially.
from racer import Task, ParallelTask, Racer
def add(x: int, y: int):
return x + y
def mul(x: int, y: int):
return x * y
task1 = Task(name="task1", target=add, kwargs={"x": 1, "y": 5})
task2 = Task(name="task2", target=mul, args=(3, 4))
racer = Racer([task1, task2])
result = racer.run(1)
print(result)
Output:
{0: {'task1': 6, 'task2': 12}}
Running Parallel Task
To run a task in parallel, use the ParallelTask class. You can specify the number of workers (threads) to run the task concurrently.
from racer import ParallelTask
def mul(x: int, y: int):
return x * y
parallel_task = ParallelTask(name="task3", target=mul, num_workers=3, args=(5, 6))
racer = Racer([parallel_task])
result = racer.run(1)
print(result)
Output:
{0: {'task3': [30, 30, 30]}}
Passing the Previous Task’s Result to the Next Task
To pass the result of one task to the next, set the use_prev_result flag to True when defining the task. The framework will automatically pass the previous task’s result as an argument to the next task.
def sub(x: int, y: int, prev_result=None):
return prev_result - x - y
task1 = Task(name="task1", target=add, kwargs={"x": 1, "y": 5})
task2 = Task(name="task2", target=sub, args=(3, 4), use_prev_result=True)
racer = Racer([task1, task2])
result = racer.run(1)
print(result)
In this example, the result of task1 is passed as an additional argument to task2.
Output:
{0: {'task1': 6, 'task2': -1}}
Running with Clones
You can run the same set of tasks multiple times by passing the number of clones to the run method.
racer = Racer([task1, task2])
result = racer.run(3)
print(result)
Output:
{0: {'task1': 6, 'task2': -1}, 1: {'task1': 6, 'task2': -1}, 2: {'task1': 6, 'task2': -1}}
More Examples
from racer import ParallelTask, Racer, Task
def add(x: int, y: int):
return x + y
def sub(x: int, y: int, z: int):
return x - y - z
def mul(x: int, y: int, z: int):
return x * y * z
if __name__ == "__main__":
task1 = Task(name="task1", target=add, kwargs={"x": 1, "y": 5})
task2 = Task(name="task2", target=sub, args=(3, 4), use_prev_result=True)
task3 = ParallelTask(
name="task3", target=mul, num_workers=3, args=(5, 6), use_prev_result=True
)
# tasks will be run sequentially
racer = Racer([task1, task2, task3])
results = racer.run(1)
print(results)
Output:
{0: {'task1': 6, 'task2': -7, 'task3': [30, 30, 30]}}
Release files for task-racer 0.0.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| task-racer-0.0.5.tar.gz | 4.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| task_racer-0.0.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:8.3 kB
Release files / task-racer-0.0.5.tar.gz
| Download URL | task-racer-0.0.5.tar.gz |
|---|---|
| Size | 4.0 kB |
| Tags | Source |
|
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Release files / task_racer-0.0.5-py3-none-any.whl
| Download URL | task_racer-0.0.5-py3-none-any.whl |
|---|---|
| Size | 4.3 kB |
| Tags | Python 3 |
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| Uploaded via |
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