Example Of Task Config With Different Parameters

from truefoundry.workflow import (
    PythonTaskConfig,
    TaskPythonBuild,
    task,
    workflow,
)
from truefoundry.deploy import Resources, SecretMount, VolumeMount, StringDataMount, NvidiaGPU

task_config = PythonTaskConfig(
    image=TaskPythonBuild(
        python_version="3.9",
        pip_packages=["truefoundry[workflow]==0.4.7rc0"],
        #To install pip packages from a requirements file uncomment this and provide the path to the requirements file
        # requirements_path="requirements.txt", 
        apt_packages=[
            "git",
            "ffmpeg",
        ]
    ),
    resources=Resources(
        cpu_request=0.45,
        cpu_limit=0.5,
        memory_request=100,
        memory_limit=150,
        ephemeral_storage_request=100,
        ephemeral_storage_limit=150,
        devices=[NvidiaGPU(name="T4", count=1)],
        capacity_type="spot_fallback_on_demand"
    ),
    service_account="default",
    mounts=[
        # To use volume mount or secret mount uncomment the following lines and provide the correct values
        # VolumeMount(mount_path="/tmp/data", volume_fqn="tfy-volume://tfy-usea1-devtest:nikp-wf-test:wf-test"),
        # SecretMount(mount_path="/tmp/secret", secret_fqn="tfy-secret://truefoundry:test-secret-1730850194619:abctestkey3"),
        StringDataMount(mount_path="/tmp/stringdata", data="Enter your data here"),
    ]
)

# Task 1: Extract data (simulates loading data from an external source)
@task(task_config=task_config, retries=3)
def print_string_mount_data() -> str:
    with open("/tmp/stringdata", "r") as f:
        data = f.read()
        print(f"Data: {data}")
    return data


@workflow
def simple_workflow() -> str:
    data = print_string_mount_data()
    return data

if __name__ == "__main__":
    print(f"data_pipeline(): {simple_workflow()}")