def register_flow(f: prefect.Flow, project_name: str) -> None:
"""Registers f to "Monitorfich" project.
Args:
f (prefect.Flow): Prefect flow
"""
f.register(project_name)
from prefect import task, Flow
from prefect.environments.storage import Docker
from datetime import timedelta
import time
@task(tags=["test"])
def fail_me():
print("I am starting")
time.sleep(600)
print("I am done sleeping")
f = Flow("Tag1-Flow",
tasks=[fail_me],
storage=Docker(prefect_version="q-schedule"))
f.register(project_name="Demo")
def welcome_logger():
logger = prefect.context["logger"]
with open("/ascii-welcome.txt", "r") as f:
lines = "\n\n" + "".join(f.readlines()) + "\n\n"
logger.info(lines)
f = Flow("Welcome Flow", tasks=[welcome_logger])
## if we don't provide our own storage, Prefect will default to storing
## your flow in ~/.prefect/flows, and only agents running on this machine
## will be able to submit this flow for execution.
## At this time, your environment will be automatically labeled with
## the labels ["local", "welcome-flow"]
f.register("Jenny")
# f.run()
## now, we can run an appropriately configured agent for this flow
## immediately in-process; this agent will listen for scheduled work
## from Prefect Cloud:
# f.run_agent() # spawns a local agent
## we can also run an agent via CLI in the same way as before:
## (local agents will always label themselves "local")
# prefect agent start local -t TOKEN -l welcome-flow
## if we exit the process in which we created this Flow, we can always
## restore the Flow object via the Flow.load interface;
## if we were to recreate the Flow, we must call flow.deploy() again
## to re-register the Flow with its new Task IDs
import prefect
from prefect import task, Flow
@task(log_stdout=True)
def check():
print(prefect.context.get("flow_id"))
print(prefect.context.get("TEST"))
print(prefect.context.get("logging", {}).get("level"))
f = Flow(
"ctx-check",
tasks=[check],
storage=prefect.environments.storage.Local(
stored_as_script=True, path="/Users/josh/Desktop/code/Dummy-Flows/ctx_check.py"
),
)
f.register("Demo")
from prefect import task, Flow
from musedashboard.mongo_job_flow import MongoJobFlow
@task
def update_history_muse_dashboard():
MongoJobFlow.save_history_in_mongo_db()
flow = Flow("muse_dashboard", tasks=[update_history_muse_dashboard])
flow.register(project_name="muse_dashboard")
def register_update_flow():
flow = Flow("update_task", tasks=[update_task])
flow.register(project_name=prefect_project_name)
from datetime import timedelta
from prefect import Flow
from prefect.schedules import Schedule
from prefect.schedules.clocks import IntervalClock
schedule = Schedule(clocks=[IntervalClock(timedelta(seconds=65))])
my_flow = Flow("Interval Test", schedule=schedule)
my_flow.register(project_name="experimental")
container = CreateContainer(
docker_server_url="tcp://localhost:2375",
image_name="prefecthq/prefect:latest",
command=
'''python -c "from prefect import Flow; f = Flow('empty'); f.run()"''',
)
start = StartContainer(docker_server_url="tcp://localhost:2375", )
logs = GetContainerLogs(docker_server_url="tcp://localhost:2375",
trigger=always_run)
status_code = WaitOnContainer(docker_server_url="tcp://localhost:2375", )
flow = Flow(
"Run a Prefect Flow in Docker",
environment=KubernetesJobEnvironment(job_spec_file="job_spec.yaml"),
storage=Docker(
registry_url="joshmeek18",
image_name="flows",
),
)
# set task dependencies using imperative API
container.set_upstream(image, flow=flow)
start.set_upstream(container, flow=flow, key="container_id")
logs.set_upstream(container, flow=flow, key="container_id")
status_code.set_upstream(container, flow=flow, key="container_id")
status_code.set_upstream(start, flow=flow)
logs.set_upstream(status_code, flow=flow)
flow.register("Demo")
#!/usr/bin/env python
import prefect
from prefect import task, Flow
from prefect.environments.storage import Docker
@task
def hello_task():
logger = prefect.context.get("logger")
logger.info("test message")
flow = Flow("prefect-base-logs", tasks=[hello_task])
base_image = "prefect-base-logs:latest"
flow.storage = Docker(base_image=base_image, local_image=True)
flow.register(project_name="test")
import prefect
from prefect import task, Flow
@task
def hello_task():
logger = prefect.context.get("logger")
logger.info("Hello World!")
flow = Flow("Hi World", tasks=[hello_task])
# to run locally use flow.run()
#flow.run()
# to register to the prefect server use flow.register
# this assumes you have a project named ExtractLoad
flow.register(project_name="ExtractLoad")
def register_init_flow():
flow = Flow("init_task", tasks=[init_task])
flow.register(project_name=prefect_project_name)
import prefect
from prefect import task, Flow
from prefect.environments.storage import Docker
@task
def hello_task():
logger = prefect.context.get("logger")
logger.info("Hello, Cloud!")
flow = Flow("hello-flow", tasks=[hello_task])
flow.storage = Docker(registry_url="docker.io/joshmeek18")
flow.register(project_name="Hello, World!")
MAX_WIDTH = 11
PROB_EDGE = 0.1
VERSION = 6
random.seed(SEED)
flow = Flow(f"{SEED} Seed Flow {VERSION}")
LEVELS = dict()
for level in range(N_LEVELS):
width = random.randint(MIN_WIDTH, MAX_WIDTH)
LEVELS[level] = [
Task(name=f"Task {level}-{i}") for i, _ in enumerate(range(width))
]
for task in LEVELS[level]:
flow.add_task(task)
if level:
for a, b in itertools.product(LEVELS[level - 1], LEVELS[level]):
if random.random() > PROB_EDGE:
flow.add_edge(a, b)
# flow.storage = Docker(
# base_image="python:3.8",
# python_dependencies=[],
# registry_url="znicholasbrown",
# image_name=f"random_seed-{VERSION}",
# image_tag=f"random-seed-flow-{VERSION}",
# )
flow.register(project_name="Community Support Flows")
