async def insert(
self,
graphql_type: str,
objects: List[dict],
on_conflict: dict = None,
alias: str = None,
selection_set: GQLObjectTypes = "affected_rows",
run_mutation: bool = True,
) -> Box:
"""
Runs an `insert` mutation against the provided Hasura type, evaluating the provided
`selection_set` and returning the full result.
The `selection_set` is inserted directly into the graphql query, and should not
be surrounded by curly braces. Valid top-level keys are `affected_rows` and `returning`.
"""
if not isinstance(objects, (list, set, tuple)):
raise TypeError(
f"`objects` should be a collection; received {type(objects).__name__}"
)
alias = alias or "insert"
# -----------------------------------------------------------
# create variables
arguments = {}
variables = []
# --- variable: objects
arguments["objects"] = Variable(
name=f"{alias}_objects",
type=f"[{graphql_type}_insert_input!]!",
value=objects,
)
variables.append(arguments["objects"])
# --- variable: on conflict
if isinstance(on_conflict, str):
arguments["on_conflict"] = EnumValue(on_conflict)
elif on_conflict:
arguments["on_conflict"] = Variable(
name=f"{alias}_on_conflict",
type=f"{graphql_type}_on_conflict",
value=on_conflict,
)
variables.append(arguments["on_conflict"])
# -------------------------------------------------------------
# build mutation
mutation_name = f"{alias}: insert_{graphql_type}"
selection_set = selection_set or "affected_rows"
graphql = dict(
query={with_args(mutation_name, arguments): selection_set},
variables=variables,
)
if run_mutation:
result = await self.execute_mutations_in_transaction(
mutations=[graphql])
return result.data[alias]
else:
return graphql
def logs(name, info):
"""
Query logs for a flow run.
\b
Options:
--name, -n TEXT A flow run name to query [required]
--info, -i Retrieve detailed logging info
"""
log_query = {
with_args("logs", {
"order_by": {
EnumValue("timestamp"): EnumValue("asc")
}
}): {
"timestamp": True,
"message": True,
"level": True,
},
"start_time": True,
}
if info:
log_query = {
with_args("logs", {
"order_by": {
EnumValue("timestamp"): EnumValue("asc")
}
}): {
"timestamp": True,
"info": True
},
"start_time": True,
}
query = {
"query": {
with_args(
"flow_run",
{
"where": {
"name": {
"_eq": name
}
},
"order_by": {
EnumValue("start_time"): EnumValue("desc")
},
},
):
log_query
}
}
result = Client().graphql(query)
flow_run = result.data.flow_run
if not flow_run:
click.secho("{} not found".format(name), fg="red")
return
run = flow_run[0]
logs = run.logs
output = []
if not info:
for log in logs:
output.append([log.timestamp, log.level, log.message])
click.echo(
tabulate(
output,
headers=["TIMESTAMP", "LEVEL", "MESSAGE"],
tablefmt="plain",
numalign="left",
stralign="left",
))
return
for log in logs:
click.echo(log.info)
def register(
self,
flow: "Flow",
project_name: str,
build: bool = True,
set_schedule_active: bool = True,
version_group_id: str = None,
compressed: bool = True,
) -> str:
"""
Push a new flow to Prefect Cloud
Args:
- flow (Flow): a flow to register
- project_name (str): the project that should contain this flow.
- build (bool, optional): if `True`, the flow's environment is built
prior to serialization; defaults to `True`
- set_schedule_active (bool, optional): if `False`, will set the
schedule to inactive in the database to prevent auto-scheduling runs (if the Flow has a schedule).
Defaults to `True`. This can be changed later.
- version_group_id (str, optional): the UUID version group ID to use for versioning this Flow
in Cloud; if not provided, the version group ID associated with this Flow's project and name
will be used.
- compressed (bool, optional): if `True`, the serialized flow will be; defaults to `True`
compressed
Returns:
- str: the ID of the newly-registered flow
Raises:
- ClientError: if the register failed
"""
required_parameters = {p for p in flow.parameters() if p.required}
if flow.schedule is not None and required_parameters:
raise ClientError(
"Flows with required parameters can not be scheduled automatically."
)
if any(e.key for e in flow.edges) and flow.result_handler is None:
raise ClientError(
"Flows are required to have a result handler for storing inputs and outputs."
)
if compressed:
create_mutation = {
"mutation($input: createFlowFromCompressedStringInput!)": {
"createFlowFromCompressedString(input: $input)": {"id"}
}
}
else:
create_mutation = {
"mutation($input: createFlowInput!)": {
"createFlow(input: $input)": {"id"}
}
}
query_project = {
"query": {
with_args("project", {
"where": {
"name": {
"_eq": project_name
}
}
}): {
"id": True
}
}
}
project = self.graphql(query_project).data.project # type: ignore
if not project:
raise ValueError(
'Project {} not found. Run `client.create_project("{}")` to create it.'
.format(project_name, project_name))
serialized_flow = flow.serialize(build=build) # type: Any
# verify that the serialized flow can be deserialized
try:
prefect.serialization.flow.FlowSchema().load(serialized_flow)
except Exception as exc:
raise ValueError(
"Flow could not be deserialized successfully. Error was: {}".
format(repr(exc)))
if compressed:
serialized_flow = compress(serialized_flow)
res = self.graphql(
create_mutation,
variables=dict(input=dict(
projectId=project[0].id,
serializedFlow=serialized_flow,
setScheduleActive=set_schedule_active,
versionGroupId=version_group_id,
)),
) # type: Any
flow_id = (res.data.createFlowFromCompressedString.id
if compressed else res.data.createFlow.id)
return flow_id
def _get_flow_run_metadata(
self,
flow_run_ids: Iterable[str],
) -> List["GraphQLResult"]:
"""
Get metadata about a collection of flow run ids that the agent is preparing
to submit
This function will filter the flow runs to a collection where:
- The flow run is in a 'Scheduled' state. This prevents flow runs that have
been submitted by another agent from being submitted again.
- The flow run is in another state, but has task runs in a 'Running' state
scheduled to start now. This is for retries in which the flow run is placed
back into the ready queue but is not in a Scheduled state.
Args:
flow_run_ids: Flow run ids to query (order will not be respected)
start_time: Only
Returns:
List: Metadata per flow run sorted by scheduled start time (ascending)
"""
if not flow_run_ids:
return []
flow_run_ids = list(flow_run_ids)
self.logger.debug(
f"Retrieving metadata for {len(flow_run_ids)} flow run(s)...")
# This buffer allows flow runs to retry immediately in their own deployment
# without the agent creating a second deployment
retry_start_time_buffer = pendulum.now("UTC").subtract(
seconds=3).isoformat()
where = {
# Only get flow runs in the requested set
"id": {
"_in": flow_run_ids
},
# and filter by the additional criteria...
"_or": [
# This flow run has not been taken by another agent
{
"state": {
"_eq": "Scheduled"
}
},
# Or, this flow run has been set to retry and has not been immediately
# retried in its own process
{
"state": {
"_eq": "Running"
},
"task_runs": {
"state_start_time": {
"_lte": retry_start_time_buffer
}
},
},
],
}
query = {
"query": {
with_args("flow_run", {"where": where}): {
"id": True,
"version": True,
"state": True,
"serialized_state": True,
"parameters": True,
"scheduled_start_time": True,
"run_config": True,
"name": True,
"flow": {
"id",
"name",
"environment",
"storage",
"version",
"core_version",
},
# Collect and return task run metadata as well so the state can be
# updated in `_mark_flow_as_submitted`
with_args(
"task_runs",
{
"where": {
"state_start_time": {
"_lte": retry_start_time_buffer
}
}
},
): {"id", "version", "task_id", "serialized_state"},
}
}
}
result = self.client.graphql(query)
return sorted(
result.data.flow_run,
key=lambda flow_run: flow_run.serialized_state.get(
"start_time",
pendulum.now("utc").isoformat()),
)
def flow_runs(limit, flow, project, started):
"""
Query information regarding Prefect flow runs.
\b
Options:
--limit, l INTEGER A limit amount of flow runs to query, defaults to 10
--flow, -f TEXT Name of a flow to query for runs
--project, -p TEXT Name of a project to query
--started, -s Only retrieve started flow runs, default shows `Scheduled` runs
"""
if started:
order = {"start_time": EnumValue("desc")}
where = {
"_and": {
"flow": {
"_and": {
"name": {
"_eq": flow
},
}
},
"start_time": {
"_is_null": False
},
}
}
if project:
where["_and"]["flow"]["_and"]["project"] = {
"name": {
"_eq": project
}
}
else:
order = {"created": EnumValue("desc")}
where = {
"flow": {
"_and": {
"name": {
"_eq": flow
},
}
}
}
if project:
where["flow"]["_and"]["project"] = {"name": {"_eq": project}}
query = {
"query": {
with_args("flow_run", {
"where": where,
"limit": limit,
"order_by": order
}): {
"flow": {
"name": True
},
"created": True,
"state": True,
"name": True,
"duration": True,
"start_time": True,
}
}
}
result = Client().graphql(query)
flow_run_data = result.data.flow_run
output = []
for item in flow_run_data:
start_time = (pendulum.parse(item.start_time).to_datetime_string()
if item.start_time else None)
output.append([
item.name,
item.flow.name,
item.state,
pendulum.parse(item.created).diff_for_humans(),
start_time,
item.duration,
])
click.echo(
tabulate(
output,
headers=[
"NAME", "FLOW NAME", "STATE", "AGE", "START TIME", "DURATION"
],
tablefmt="plain",
numalign="left",
stralign="left",
))
async def schedule_flow_runs(flow_id: str, max_runs: int = 10) -> List[str]:
"""
Schedule the next `max_runs` runs for this flow. Runs will not be scheduled
if they are earlier than latest currently-scheduled run that has auto_scheduled = True.
Runs are created with an idempotency key to avoid rescheduling.
Args:
- flow_id (str): the flow ID
- max_runs (int): the maximum number of runs to schedule (defaults to 10)
Returns:
- List[str]: the ids of the new runs
"""
if flow_id is None:
raise ValueError("Invalid flow id.")
run_ids = []
flow = await models.Flow.where({
# match the provided ID
"id": {
"_eq": flow_id
},
# schedule is not none or flow group schedule is not none
"_or": [
{
"schedule": {
"_is_null": False
}
},
{
"flow_group": {
"schedule": {
"_is_null": False
}
}
},
],
# schedule is active
"is_schedule_active": {
"_eq": True
},
# flow is not archived
"archived": {
"_eq": False
},
}).first(
{
"schedule": True,
"flow_group": {
"schedule": True
},
with_args("flow_runs_aggregate", {
"where": {
"auto_scheduled": {
"_eq": True
}
}
}): {
"aggregate": {
"max": "scheduled_start_time"
}
},
},
apply_schema=False,
)
if not flow:
logger.debug(f"Flow {flow_id} can not be scheduled.")
return run_ids
else:
# attempt to pull the schedule from the flow group if possible
# if not possible, pull the schedule from the flow
flow_schedule = flow.flow_group.schedule or flow.schedule
try:
flow_schedule = schedule_schema.load(flow_schedule)
except Exception as exc:
logger.error(exc, exc_info=True)
logger.critical(
f"Failed to deserialize schedule for flow {flow_id}: {flow_schedule}"
)
return run_ids
if flow.flow_runs_aggregate.aggregate.max.scheduled_start_time is not None:
last_scheduled_run = pendulum.parse(
flow.flow_runs_aggregate.aggregate.max.scheduled_start_time)
else:
last_scheduled_run = pendulum.now("UTC")
schedule_coros = []
# schedule every event with an idempotent flow run
for event in flow_schedule.next(n=max_runs, return_events=True):
# if the event has parameter defaults or labels, we do allow for
# same-time scheduling
if event.parameter_defaults or event.labels is not None:
md5 = hashlib.md5()
param_string = str(sorted(json.dumps(event.parameter_defaults)))
label_string = str(sorted(json.dumps(event.labels)))
md5.update((param_string + label_string).encode("utf-8"))
idempotency_key = (
f"auto-scheduled:{event.start_time.in_tz('UTC')}:{md5.hexdigest()}"
)
# if this run was already scheduled, continue
elif last_scheduled_run and event.start_time <= last_scheduled_run:
continue
else:
idempotency_key = f"auto-scheduled:{event.start_time.in_tz('UTC')}"
schedule_coros.append(
api.runs.create_flow_run(
flow_id=flow_id,
scheduled_start_time=event.start_time,
parameters=event.parameter_defaults,
labels=event.labels,
idempotency_key=idempotency_key,
))
# schedule runs concurrently
run_ids.extend(await asyncio.gather(*schedule_coros))
await models.FlowRun.where({
"id": {
"_in": run_ids
}
}).update(set={"auto_scheduled": True})
return run_ids
async def run_scheduled(self, flow_id=None):
"""
Queries for any flow runs that are SCHEDULED, OR any flow runs that have SCHEDULED
task runs [if the flow run itself is RUNNING]. Sets all Scheduled runs to Submitted
and runs the flow.
If a flow_id is provided, only flow runs of that flow are matched.
"""
now = pendulum.now()
flow_runs = await models.FlowRun.where({
"_or": [
{
"state_start_time": {
"_lte": str(now)
}
},
{
"state": {
"_eq": "Running"
},
"task_runs": {
"state_start_time": {
"_lte": str(now)
}
},
},
],
"flow_id": {
"_eq": flow_id
},
}).get(
selection_set={
"id": True,
"version": True,
"tenant_id": True,
"state": True,
"serialized_state": True,
"parameters": True,
"flow": {"id", "environment", "name", "storage"},
with_args("task_runs", {
"where": {
"state_start_time": {
"_lte": str(now)
}
}
}): {"id", "version", "task_id", "serialized_state"},
},
limit=100,
order_by={"state_start_time": EnumValue("asc")},
)
for fr in flow_runs:
skip_counter = 0
fr_serialized_state = state_schema.load(fr.serialized_state)
# set the flow run state to submitted, if it's scheduled
if fr_serialized_state.is_scheduled():
try:
await api.states.set_flow_run_state(
flow_run_id=fr.id,
state=Submitted(
message="Submitted for execution",
state=fr_serialized_state,
),
)
except ValueError as exc:
skip_counter += 1
if "Update failed" not in str(exc):
raise
# set each task run state to submitted, if it's scheduled
for tr in fr.task_runs:
tr_serialized_state = state_schema.load(tr.serialized_state)
try:
await api.states.set_task_run_state(
task_run_id=tr.id,
state=Submitted(
message="Submitted for execution",
state=tr_serialized_state,
),
)
except ValueError as exc:
skip_counter += 1
if "Update failed" not in str(exc):
raise
# none of the states were set, so we shouldn't bother running
if skip_counter == 1 + len(fr.task_runs):
continue
self.logger.info(f'Submitting flow run "{fr.id}" for execution.')
# run the flow
self.run_flow(
flow_name=fr.flow.name,
storage=storage_schema.load(fr.flow.storage),
environment=environment_schema.load(fr.flow.environment),
config={
"cloud.api":
f"http://localhost:4200",
"cloud.graphql":
"http://localhost:4200",
"engine.flow_runner.default_class":
"prefect.engine.cloud.CloudFlowRunner",
"engine.task_runner.default_class":
"prefect.engine.cloud.CloudTaskRunner",
"engine.executor.default_class":
"prefect.engine.executors.LocalExecutor",
},
context={"flow_run_id": fr.id},
)
def register_serialized_flow(
client: "prefect.Client",
serialized_flow: dict,
project_id: str,
force: bool = False,
) -> Tuple[str, int, bool]:
"""Register a pre-serialized flow.
Args:
- client (prefect.Client): the prefect client
- serialized_flow (dict): the serialized flow
- project_id (str): the project id
- force (bool, optional): If `False` (default), an idempotency key will
be generated to avoid unnecessary re-registration. Set to `True` to
force re-registration.
Returns:
- flow_id (str): the flow id
- flow_version (int): the flow version
- is_new (bool): True if this is a new flow version, false if
re-registration was skipped.
"""
# Get most recent flow id for this flow. This can be removed once
# the registration graphql routes return more information
flow_name = serialized_flow["name"]
resp = client.graphql(
{
"query": {
with_args(
"flow",
{
"where": {
"_and": {
"name": {"_eq": flow_name},
"project": {"id": {"_eq": project_id}},
}
},
"order_by": {"version": EnumValue("desc")},
"limit": 1,
},
): {"id", "version"}
}
}
)
if resp.data.flow:
prev_id = resp.data.flow[0].id
prev_version = resp.data.flow[0].version
else:
prev_id = None
prev_version = 0
inputs = dict(
project_id=project_id,
serialized_flow=compress(serialized_flow),
)
if not force:
inputs["idempotency_key"] = hashlib.sha256(
json.dumps(serialized_flow, sort_keys=True).encode()
).hexdigest()
res = client.graphql(
{
"mutation($input: create_flow_from_compressed_string_input!)": {
"create_flow_from_compressed_string(input: $input)": {"id"}
}
},
variables=dict(input=inputs),
retry_on_api_error=False,
)
new_id = res.data.create_flow_from_compressed_string.id
if new_id == prev_id:
return new_id, prev_version, False
else:
return new_id, prev_version + 1, True
self.heartbeat_cmd = [
sys.executable,
"-m",
"prefect",
"heartbeat",
"flow-run",
"-i",
flow_run_id,
]
=======
self.heartbeat_cmd = ["prefect", "heartbeat", "flow-run", "-i", flow_run_id]
>>>>>>> prefect clone
query = {
"query": {
with_args("flow_run_by_pk", {"id": flow_run_id}): {
"flow": {"settings": True},
}
}
}
flow_run = self.client.graphql(query).data.flow_run_by_pk
if not flow_run.flow.settings.get("heartbeat_enabled", True):
return False
return True
except Exception:
self.logger.exception(
"Heartbeat failed for Flow '{}'".format(self.flow.name)
)
return False
def call_runner_target_handlers(self, old_state: State, new_state: State) -> State:
def run_flow(self) -> None:
"""
Run the flow using the default executor
Raises:
- ValueError: if no `flow_run_id` is found in context
"""
# Call on_start callback if specified
if self.on_start:
self.on_start()
try:
from prefect.engine import (
get_default_flow_runner_class,
get_default_executor_class,
)
flow_run_id = prefect.context.get("flow_run_id")
if not flow_run_id:
raise ValueError("No flow run ID found in context.")
query = {
"query": {
with_args("flow_run", {"where": {"id": {"_eq": flow_run_id}}}): {
"flow": {"name": True, "storage": True,},
}
}
}
client = Client()
result = client.graphql(query)
flow_run = result.data.flow_run[0]
flow_data = flow_run.flow
storage_schema = prefect.serialization.storage.StorageSchema()
storage = storage_schema.load(flow_data.storage)
## populate global secrets
secrets = prefect.context.get("secrets", {})
for secret in storage.secrets:
secrets[secret] = prefect.tasks.secrets.PrefectSecret(name=secret).run()
with prefect.context(secrets=secrets):
flow = storage.get_flow(storage.flows[flow_data.name])
runner_cls = get_default_flow_runner_class()
if getattr(self, "executor", None) is not None:
executor = self.executor # type: ignore
else:
executor_cls = get_default_executor_class()
# Deprecated, to be removed
if hasattr(self, "executor_kwargs"):
executor = executor_cls(**self.executor_kwargs) # type: ignore
else:
executor = executor_cls
runner_cls(flow=flow).run(executor=executor)
except Exception as exc:
self.logger.exception(
"Unexpected error raised during flow run: {}".format(exc)
)
raise exc
finally:
# Call on_exit callback if specified
if self.on_exit:
self.on_exit()
def logs(name, id, info):
"""
Query logs for a flow run.
Note: at least one of `name` or `id` must be specified. If only `name` is set then
the most recent flow run with that name will be queried.
\b
Options:
--name, -n TEXT A flow run name to query
--id TEXT A flow run ID to query
--info, -i Retrieve detailed logging info
"""
if not name and not id:
click.secho("Either --name or --id must be provided", fg="red")
return
log_query = {
with_args("logs", {"order_by": {EnumValue("timestamp"): EnumValue("asc")}}): {
"timestamp": True,
"message": True,
"level": True,
},
"start_time": True,
}
if info:
log_query = {
with_args(
"logs", {"order_by": {EnumValue("timestamp"): EnumValue("asc")}}
): {"timestamp": True, "info": True},
"start_time": True,
}
query = {
"query": {
with_args(
"flow_run",
{
"where": {"name": {"_eq": name}, "id": {"_eq": id}},
"order_by": {EnumValue("start_time"): EnumValue("desc")},
},
): log_query
}
}
result = Client().graphql(query)
flow_run = result.data.flow_run
if not flow_run:
click.secho("{} not found".format(name), fg="red")
return
run = flow_run[0]
logs = run.logs
output = []
if not info:
for log in logs:
output.append([log.timestamp, log.level, log.message])
click.echo(
tabulate(
output,
headers=["TIMESTAMP", "LEVEL", "MESSAGE"],
tablefmt="plain",
numalign="left",
stralign="left",
)
)
return
for log in logs:
click.echo(log.info)
from prefect import Client
from prefect.utilities.graphql import with_args
c = Client()
name = "my_flow"
c.graphql({"query": {with_args("flow", {"where": {"name": {"_eq": name}}}): "id"}})
# c.graphql({"query": "'query' {'flow'('where': { 'name': { '_eq': 'ltest' } }) {'id'}}"})
def run(
self,
flow_name: str = None,
project_name: str = None,
parameters: dict = None,
run_config: RunConfig = None,
new_flow_context: dict = None,
run_name: str = None,
idempotency_key: str = None,
scheduled_start_time: datetime.datetime = None,
) -> str:
"""
Run method for the task; responsible for scheduling the specified flow run.
Args:
- flow_name (str, optional): the name of the flow to schedule; if not provided,
this method will use the flow name provided at initialization
- project_name (str, optional): the Cloud project in which the flow is located; if
not provided, this method will use the project provided at initialization. If
running with Prefect Core's server as the backend, this should not be provided.
- parameters (dict, optional): the parameters to pass to the flow run being
scheduled; if not provided, this method will use the parameters provided at
initialization
- run_config (RunConfig, optional): a run-config to use for this flow
run, overriding any existing flow settings.
- new_flow_context (dict, optional): the optional run context for the new flow run
- run_name (str, optional): name to be set for the flow run
- idempotency_key (str, optional): a unique idempotency key for scheduling the
flow run. Duplicate flow runs with the same idempotency key will only create
a single flow run. This is useful for ensuring that only one run is created
if this task is retried. If not provided, defaults to the active `task_run_id`.
- scheduled_start_time (datetime, optional): the time to schedule the execution
for; if not provided, defaults to now
Returns:
- str: the ID of the newly-scheduled flow run
Raises:
- ValueError: if flow was not provided, cannot be found, or if a project name was
not provided while using Cloud as a backend
Example:
```python
from prefect.tasks.prefect.flow_run import StartFlowRun
kickoff_task = StartFlowRun(project_name="Hello, World!", flow_name="My Cloud Flow")
```
"""
# verify that flow and project names were passed where necessary
if flow_name is None:
raise ValueError("Must provide a flow name.")
if project_name is None:
raise ValueError("Must provide a project name.")
where_clause = {
"name": {"_eq": flow_name},
"archived": {"_eq": False},
"project": {"name": {"_eq": project_name}},
}
# find the flow ID to schedule
query = {
"query": {
with_args(
"flow",
{
"where": where_clause,
"order_by": {"version": EnumValue("desc")},
"limit": 1,
},
): {"id"}
}
}
client = Client()
flow = client.graphql(query).data.flow
# verify that a flow has been returned
if not flow:
raise ValueError("Flow '{}' not found.".format(flow_name))
# grab the ID for the most recent version
flow_id = flow[0].id
if idempotency_key is None:
idempotency_key = context.get("task_run_id", None)
# providing an idempotency key ensures that retries for this task
# will not create additional flow runs
flow_run_id = client.create_flow_run(
flow_id=flow_id,
parameters=parameters,
run_config=run_config,
idempotency_key=idempotency_key,
context=new_flow_context,
run_name=run_name,
scheduled_start_time=scheduled_start_time,
)
self.logger.debug(f"Flow Run {flow_run_id} created.")
self.logger.debug(f"Creating link artifact for Flow Run {flow_run_id}.")
run_link = client.get_cloud_url("flow-run", flow_run_id, as_user=False)
create_link(urlparse(run_link).path)
if not self.wait:
return flow_run_id
while True:
time.sleep(10)
flow_run_state = client.get_flow_run_info(flow_run_id).state
if flow_run_state.is_finished():
exc = signal_from_state(flow_run_state)(
f"{flow_run_id} finished in state {flow_run_state}"
)
raise exc
async def update(
self,
graphql_type: str,
where: GQLObjectTypes = None,
id: str = None,
set: GQLObjectTypes = None,
increment: GQLObjectTypes = None,
alias: str = None,
selection_set: GQLObjectTypes = "affected_rows",
run_mutation: bool = True,
) -> Box:
"""
Runs an `update` mutation against the provided Hasura type and `where` clause, applying
the operations (either `set` or `increment`)
evaluating the provided `selection_set` and returning the full result.
The `selection_set` is inserted directly into the graphql query, and should not
be surrounded by curly braces. Valid top-level keys are `affected_rows` and `returning`.
"""
if id is None and not isinstance(where, dict):
raise TypeError(
"`where` must be provided as a dict if `id` is None; "
f"received {type(where).__name__}")
elif all(op is None for op in [set, increment]):
raise ValueError("At least one update operation must be provided")
where = where or {}
if id is not None:
where["id"] = {"_eq": id}
alias = alias or "update"
# -------------------------------------------------------------
# create variables
arguments = {}
variables = []
# --- variable: where
arguments["where"] = Variable(name=f"{alias}_where",
type=f"{graphql_type}_bool_exp!",
value=where)
variables.append(arguments["where"])
# --- variable: _set
if set:
arguments["_set"] = Variable(name=f"{alias}_set",
type=f"{graphql_type}_set_input",
value=set)
variables.append(arguments["_set"])
# --- variable: _inc
if increment:
arguments["_inc"] = Variable(name=f"{alias}_inc",
type=f"{graphql_type}_inc_input",
value=increment)
variables.append(arguments["_inc"])
# -------------------------------------------------------------
# build mutation
mutation_name = f"{alias}: update_{graphql_type}"
selection_set = selection_set or "affected_rows"
graphql = dict(
query={with_args(mutation_name, arguments): selection_set},
variables=variables,
)
if run_mutation:
result = await self.execute_mutations_in_transaction(
mutations=[graphql])
return result.data[alias]
else:
return graphql
def run(
self,
flow_name: str = None,
project_name: str = None,
parameters: dict = None,
idempotency_key: str = None,
new_flow_context: dict = None,
run_name: str = None,
) -> str:
"""
Run method for the task; responsible for scheduling the specified flow run.
Args:
- flow_name (str, optional): the name of the flow to schedule; if not provided,
this method will use the flow name provided at initialization
- project_name (str, optional): the Cloud project in which the flow is located; if
not provided, this method will use the project provided at initialization. If
running with Prefect Core's server as the backend, this should not be provided.
- parameters (dict, optional): the parameters to pass to the flow run being
scheduled; if not provided, this method will use the parameters provided at
initialization
- idempotency_key (str, optional): an optional idempotency key for scheduling the
flow run; if provided, ensures that only one run is created if this task is retried
or rerun with the same inputs. If not provided, the current flow run ID will be used.
- new_flow_context (dict, optional): the optional run context for the new flow run
- run_name (str, optional): name to be set for the flow run
Returns:
- str: the ID of the newly-scheduled flow run
Raises:
- ValueError: if flow was not provided, cannot be found, or if a project name was
not provided while using Cloud as a backend
Example:
```python
from prefect.tasks.prefect.flow_run import FlowRunTask
kickoff_task = FlowRunTask(project_name="Hello, World!", flow_name="My Cloud Flow")
```
"""
# verify that flow and project names were passed where necessary
if flow_name is None:
raise ValueError("Must provide a flow name.")
if project_name is None:
raise ValueError("Must provide a project name.")
where_clause = {
"name": {"_eq": flow_name},
"archived": {"_eq": False},
"project": {"name": {"_eq": project_name}},
}
# find the flow ID to schedule
query = {
"query": {
with_args(
"flow",
{
"where": where_clause,
"order_by": {"version": EnumValue("desc")},
"limit": 1,
},
): {"id"}
}
}
client = Client()
flow = client.graphql(query).data.flow
# verify that a flow has been returned
if not flow:
raise ValueError("Flow '{}' not found.".format(flow_name))
# grab the ID for the most recent version
flow_id = flow[0].id
idem_key = None
if context.get("flow_run_id"):
map_index = context.get("map_index")
default = context.get("flow_run_id") + (
f"-{map_index}" if map_index else ""
)
idem_key = idempotency_key or default
# providing an idempotency key ensures that retries for this task
# will not create additional flow runs
flow_run_id = client.create_flow_run(
flow_id=flow_id,
parameters=parameters,
idempotency_key=idem_key or idempotency_key,
context=new_flow_context,
run_name=run_name,
)
self.logger.debug(f"Flow Run {flow_run_id} created.")
if not self.wait:
return flow_run_id
while True:
time.sleep(10)
flow_run_state = client.get_flow_run_info(flow_run_id).state
if flow_run_state.is_finished():
exc = signal_from_state(flow_run_state)(
f"{flow_run_id} finished in state {flow_run_state}"
)
raise exc
def get_logs(
self,
start_time: pendulum.DateTime = None,
end_time: pendulum.DateTime = None,
) -> List["FlowRunLog"]:
"""
Get logs for this flow run from `start_time` to `end_time`.
Args:
- start_time (optional): A time to start the log query at, useful for
limiting the scope. If not provided, all logs up to `updated_at` are
retrieved.
- end_time (optional): A time to end the log query at. By default, this is
set to `self.updated_at` which is the last time that the flow run was
updated in the backend before this object was created.
Returns:
A list of `FlowRunLog` objects sorted by timestamp
"""
client = prefect.Client()
end_time = end_time or self.updated_at
logs_query = {
with_args(
"logs",
{
"order_by": {
EnumValue("timestamp"): EnumValue("asc")
},
"where": {
"_and": [
{
"timestamp": {
"_lte": end_time.isoformat()
}
},
({
"timestamp": {
"_gt": start_time.isoformat()
}
} if start_time else {}),
]
},
},
): {
"timestamp": True,
"message": True,
"level": True
}
}
result = client.graphql({
"query": {
with_args(
"flow_run",
{
"where": {
"id": {
"_eq": self.flow_run_id
}
},
},
):
logs_query
}
})
# Unpack the result
logs = result.get("data", {}).get("flow_run", [{}])[0].get("logs", [])
return [FlowRunLog.from_dict(log) for log in logs]
def deploy(
self,
flow: "Flow",
project_name: str,
build: bool = True,
set_schedule_active: bool = True,
compressed: bool = True,
) -> str:
"""
Push a new flow to Prefect Cloud
Args:
- flow (Flow): a flow to deploy
- project_name (str): the project that should contain this flow.
- build (bool, optional): if `True`, the flow's environment is built
prior to serialization; defaults to `True`
- set_schedule_active (bool, optional): if `False`, will set the
schedule to inactive in the database to prevent auto-scheduling runs (if the Flow has a schedule).
Defaults to `True`. This can be changed later.
- compressed (bool, optional): if `True`, the serialized flow will be; defaults to `True`
compressed
Returns:
- str: the ID of the newly-deployed flow
Raises:
- ClientError: if the deploy failed
"""
required_parameters = {p for p in flow.parameters() if p.required}
if flow.schedule is not None and required_parameters:
raise ClientError(
"Flows with required parameters can not be scheduled automatically."
)
if compressed:
create_mutation = {
"mutation($input: createFlowFromCompressedStringInput!)": {
"createFlowFromCompressedString(input: $input)": {"id"}
}
}
else:
create_mutation = {
"mutation($input: createFlowInput!)": {
"createFlow(input: $input)": {"id"}
}
}
query_project = {
"query": {
with_args("project", {"where": {"name": {"_eq": project_name}}}): {
"id": True
}
}
}
project = self.graphql(query_project).data.project # type: ignore
if not project:
raise ValueError(
"Project {} not found. Run `client.create_project({})` to create it.".format(
project_name, project_name
)
)
serialized_flow = flow.serialize(build=build) # type: Any
if compressed:
serialized_flow = compress(serialized_flow)
res = self.graphql(
create_mutation,
input=dict(
projectId=project[0].id,
serializedFlow=serialized_flow,
setScheduleActive=set_schedule_active,
),
) # type: Any
flow_id = (
res.data.createFlowFromCompressedString.id
if compressed
else res.data.createFlow.id
)
return flow_id
def flow_run():
"""
Execute a flow run in the context of a backend API.
"""
flow_run_id = prefect.context.get("flow_run_id")
if not flow_run_id:
click.echo("Not currently executing a flow within a Cloud context.")
raise Exception(
"Not currently executing a flow within a Cloud context.")
query = {
"query": {
with_args("flow_run", {"where": {
"id": {
"_eq": flow_run_id
}
}}): {
"flow": {
"name": True,
"storage": True
},
"version": True,
}
}
}
client = Client()
result = client.graphql(query)
flow_run = result.data.flow_run
if not flow_run:
click.echo("Flow run {} not found".format(flow_run_id))
raise ValueError("Flow run {} not found".format(flow_run_id))
try:
flow_data = flow_run[0].flow
storage_schema = prefect.serialization.storage.StorageSchema()
storage = storage_schema.load(flow_data.storage)
# populate global secrets
secrets = prefect.context.get("secrets", {})
for secret in storage.secrets:
secrets[secret] = PrefectSecret(name=secret).run()
with prefect.context(secrets=secrets, loading_flow=True):
flow = storage.get_flow(storage.flows[flow_data.name])
with prefect.context(secrets=secrets):
if getattr(flow, "run_config", None) is not None:
runner_cls = get_default_flow_runner_class()
runner_cls(flow=flow).run()
else:
environment = flow.environment
environment.setup(flow)
environment.execute(flow)
except Exception as exc:
msg = "Failed to load and execute Flow's environment: {}".format(
repr(exc))
state = prefect.engine.state.Failed(message=msg)
client.set_flow_run_state(flow_run_id=flow_run_id, state=state)
click.echo(str(exc))
raise exc
def run(self,
flow_name: str = None,
project_name: str = None,
parameters: dict = None) -> str:
"""
Run method for the task; responsible for scheduling the specified flow run.
Args:
- flow_name (str, optional): the name of the flow to schedule; if not provided, this method will
use the flow name provided at initialization
- project_name (str, optional): the Cloud project in which the flow is located; if not provided, this method
will use the project provided at initialization. If running with Prefect Core's server as the backend,
this should not be provided.
- parameters (dict, optional): the parameters to pass to the flow run being scheduled; if not provided,
this method will use the parameters provided at initialization
Returns:
- str: the ID of the newly-scheduled flow run
Raises:
- ValueError: if flow was not provided, cannot be found, or if a project name was not provided while using
Cloud as a backend
Example:
```python
from prefect.tasks.prefect.flow_run import FlowRunTask
kickoff_task = FlowRunTask(project_name="Hello, World!", flow_name="My Cloud Flow")
```
"""
# verify that flow and project names were passed where necessary
if flow_name is None:
raise ValueError("Must provide a flow name.")
if project_name is None and config.backend == "cloud":
raise ValueError("Must provide a project name.")
where_clause = {
"name": {
"_eq": flow_name
},
"archived": {
"_eq": False
},
}
if project_name:
where_clause["project"] = {"name": {"_eq": project_name}}
# find the flow ID to schedule
query = {
"query": {
with_args(
"flow",
{
"where": where_clause,
"order_by": {
"version": EnumValue("desc")
},
"limit": 1,
},
): {"id"}
}
}
client = Client()
flow = client.graphql(query).data.flow
# verify that a flow has been returned
if not flow:
raise ValueError("Flow '{}' not found.".format(flow_name))
# grab the ID for the most recent version
flow_id = flow[0].id
return client.create_flow_run(flow_id=flow_id, parameters=parameters)
def _run_flow(
name,
version,
parameters_file,
parameters_string,
run_name,
watch,
logs,
no_url,
project=None,
):
if watch and logs:
click.secho(
"Streaming state and logs not currently supported together.",
fg="red")
return
where_clause = {
"_and": {
"name": {
"_eq": name
},
"version": {
"_eq": version
},
"project": {
"name": {
"_eq": project
}
},
}
}
query = {
"query": {
with_args(
"flow",
{
"where": where_clause,
"order_by": {
"name": EnumValue("asc"),
"version": EnumValue("desc"),
},
"distinct_on": EnumValue("name"),
},
): {
"id": True
}
}
}
client = Client()
result = client.graphql(query)
flow_data = result.data.flow
if flow_data:
flow_id = flow_data[0].id
else:
click.secho("{} not found".format(name), fg="red")
return
# Load parameters from file if provided
file_params = {}
if parameters_file:
with open(parameters_file) as params_file:
file_params = json.load(params_file)
# Load parameters from string if provided
string_params = {}
if parameters_string:
string_params = json.loads(parameters_string)
flow_run_id = client.create_flow_run(flow_id=flow_id,
parameters={
**file_params,
**string_params
},
run_name=run_name)
if no_url:
click.echo("Flow Run ID: {}".format(flow_run_id))
else:
flow_run_url = client.get_cloud_url("flow-run", flow_run_id)
click.echo("Flow Run: {}".format(flow_run_url))
if watch:
current_states = []
while True:
query = {
"query": {
with_args("flow_run_by_pk", {"id": flow_run_id}): {
with_args(
"states",
{
"order_by": {
EnumValue("timestamp"): EnumValue("asc")
}
},
): {
"state": True,
"timestamp": True
}
}
}
}
result = client.graphql(query)
# Filter through retrieved states and output in order
for state_index in result.data.flow_run_by_pk.states:
state = state_index.state
if state not in current_states:
if state != "Success" and state != "Failed":
click.echo("{} -> ".format(state), nl=False)
else:
click.echo(state)
return flow_run_id
current_states.append(state)
time.sleep(3)
if logs:
all_logs = []
log_query = {
with_args("logs", {
"order_by": {
EnumValue("timestamp"): EnumValue("asc")
}
}): {
"timestamp": True,
"message": True,
"level": True
},
"start_time": True,
"state": True,
}
query = {
"query": {
with_args(
"flow_run",
{
"where": {
"id": {
"_eq": flow_run_id
}
},
"order_by": {
EnumValue("start_time"): EnumValue("desc")
},
},
):
log_query
}
}
while True:
result = client.graphql(query)
flow_run = result.data.flow_run
if not flow_run:
click.secho("{} not found".format(flow_run_id), fg="red")
return
new_run = flow_run[0]
logs = new_run.logs
output = []
for i in logs:
if [i.timestamp, i.level, i.message] not in all_logs:
if not len(all_logs):
click.echo(
tabulate(
[[i.timestamp, i.level, i.message]],
headers=["TIMESTAMP", "LEVEL", "MESSAGE"],
tablefmt="plain",
numalign="left",
stralign="left",
))
all_logs.append([i.timestamp, i.level, i.message])
continue
output.append([i.timestamp, i.level, i.message])
all_logs.append([i.timestamp, i.level, i.message])
if output:
click.echo(
tabulate(output,
tablefmt="plain",
numalign="left",
stralign="left"))
if new_run.state == "Success" or new_run.state == "Failed":
return flow_run_id
time.sleep(3)
return flow_run_id
def cloud(
name,
project,
version,
parameters_file,
parameters_string,
run_name,
watch,
logs,
no_url,
):
"""
Run a registered flow in Prefect Cloud.
\b
Options:
--name, -n TEXT The name of a flow to run [required]
--project, -p TEXT The name of a project that contains the flow [required]
--version, -v INTEGER A flow version to run
--parameters-file, -pf FILE PATH A filepath of a JSON file containing parameters
--parameters-string, -ps TEXT A string of JSON parameters
--run-name, -rn TEXT A name to assign for this run
--watch, -w Watch current state of the flow run, stream output to stdout
--logs, -l Get logs of the flow run, stream output to stdout
--no-url Only output the flow run id instead of a link
\b
If both `--parameters-file` and `--parameters-string` are provided then the values passed
in through the string will override the values provided from the file.
\b
e.g.
File contains: {"a": 1, "b": 2}
String: '{"a": 3}'
Parameters passed to the flow run: {"a": 3, "b": 2}
"""
if watch and logs:
click.secho(
"Streaming state and logs not currently supported together.",
fg="red")
return
query = {
"query": {
with_args(
"flow",
{
"where": {
"_and": {
"name": {
"_eq": name
},
"version": {
"_eq": version
},
"project": {
"name": {
"_eq": project
}
},
}
},
"order_by": {
"name": EnumValue("asc"),
"version": EnumValue("desc"),
},
"distinct_on": EnumValue("name"),
},
): {
"id": True
}
}
}
client = Client()
result = client.graphql(query)
flow_data = result.data.flow
if flow_data:
flow_id = flow_data[0].id
else:
click.secho("{} not found".format(name), fg="red")
return
# Load parameters from file if provided
file_params = {}
if parameters_file:
with open(parameters_file) as params_file:
file_params = json.load(params_file)
# Load parameters from string if provided
string_params = {}
if parameters_string:
string_params = json.loads(parameters_string)
flow_run_id = client.create_flow_run(flow_id=flow_id,
parameters={
**file_params,
**string_params
},
run_name=run_name)
if no_url:
click.echo("Flow Run ID: {}".format(flow_run_id))
else:
# Generate direct link to Cloud run
tenant_slug = client.get_default_tenant_slug()
url = (re.sub("api-", "", config.cloud.api)
if re.search("api-", config.cloud.api) else re.sub(
"api", "cloud", config.cloud.api))
flow_run_url = "/".join(
[url.rstrip("/"), tenant_slug, "flow-run", flow_run_id])
click.echo("Flow Run: {}".format(flow_run_url))
if watch:
current_states = []
while True:
query = {
"query": {
with_args("flow_run_by_pk", {"id": flow_run_id}): {
with_args(
"states",
{
"order_by": {
EnumValue("timestamp"): EnumValue("asc")
}
},
): {
"state": True,
"timestamp": True
}
}
}
}
result = client.graphql(query)
# Filter through retrieved states and output in order
for state_index in result.data.flow_run_by_pk.states:
state = state_index.state
if state not in current_states:
if state != "Success" and state != "Failed":
click.echo("{} -> ".format(state), nl=False)
else:
click.echo(state)
return
current_states.append(state)
time.sleep(3)
if logs:
all_logs = []
log_query = {
with_args("logs", {
"order_by": {
EnumValue("timestamp"): EnumValue("asc")
}
}): {
"timestamp": True,
"message": True,
"level": True
},
"start_time": True,
}
query = {
"query": {
with_args(
"flow_run",
{
"where": {
"id": {
"_eq": flow_run_id
}
},
"order_by": {
EnumValue("start_time"): EnumValue("desc")
},
},
):
log_query
}
}
while True:
result = client.graphql(query)
flow_run = result.data.flow_run
if not flow_run:
click.secho("{} not found".format(flow_run_id), fg="red")
return
new_run = flow_run[0]
logs = new_run.logs
output = []
for i in logs:
if [i.timestamp, i.level, i.message] not in all_logs:
if not len(all_logs):
click.echo(
tabulate(
[[i.timestamp, i.level, i.message]],
headers=["TIMESTAMP", "LEVEL", "MESSAGE"],
tablefmt="plain",
numalign="left",
stralign="left",
))
all_logs.append([i.timestamp, i.level, i.message])
continue
output.append([i.timestamp, i.level, i.message])
all_logs.append([i.timestamp, i.level, i.message])
if output:
click.echo(
tabulate(output,
tablefmt="plain",
numalign="left",
stralign="left"))
# Check if state is either Success or Failed, exit if it is
pk_query = {
"query": {
with_args("flow_run_by_pk", {"id": flow_run_id}): {
"state": True
}
}
}
result = client.graphql(pk_query)
if (result.data.flow_run_by_pk.state == "Success"
or result.data.flow_run_by_pk.state == "Failed"):
return
time.sleep(3)
def run_flow(self) -> None:
"""
Run the flow using a Dask executor
"""
# Call on_start callback if specified
if self.on_start:
self.on_start()
try:
from prefect.engine import get_default_flow_runner_class
from prefect.engine.executors import DaskExecutor
from dask_kubernetes import KubeCluster
if self._worker_spec:
worker_pod = self._worker_spec
worker_pod = self._populate_worker_spec_yaml(
yaml_obj=worker_pod)
else:
with open(path.join(path.dirname(__file__),
"worker_pod.yaml")) as pod_file:
worker_pod = yaml.safe_load(pod_file)
worker_pod = self._populate_worker_pod_yaml(
yaml_obj=worker_pod)
cluster = KubeCluster.from_dict(
worker_pod, namespace=prefect.context.get("namespace"))
cluster.adapt(minimum=self.min_workers, maximum=self.max_workers)
flow_run_id = prefect.context.get("flow_run_id")
if not flow_run_id:
raise ValueError("No flow run ID found in context.")
query = {
"query": {
with_args("flow_run", {
"where": {
"id": {
"_eq": flow_run_id
}
}
}): {
"flow": {
"name": True,
"storage": True,
},
}
}
}
client = Client()
result = client.graphql(query)
flow_run = result.data.flow_run[0]
flow_data = flow_run.flow
storage_schema = prefect.serialization.storage.StorageSchema()
storage = storage_schema.load(flow_data.storage)
## populate global secrets
secrets = prefect.context.get("secrets", {})
for secret in storage.secrets:
secrets[secret] = prefect.tasks.secrets.PrefectSecret(
name=secret).run()
with prefect.context(secrets=secrets):
flow = storage.get_flow(storage.flows[flow_data.name])
executor = DaskExecutor(address=cluster.scheduler_address)
runner_cls = get_default_flow_runner_class()
runner_cls(flow=flow).run(executor=executor)
except Exception as exc:
self.logger.exception(
"Unexpected error raised during flow run: {}".format(exc))
raise exc
finally:
# Call on_exit callback if specified
if self.on_exit:
self.on_exit()
def query_flow_runs(self) -> list:
"""
Query Prefect Cloud for flow runs which need to be deployed and executed
Returns:
- list: A list of GraphQLResult flow run objects
"""
self.logger.debug("Querying for flow runs")
# keep a copy of what was curringly running before the query (future callbacks may be
# updating this set)
currently_submitting_flow_runs = self.submitting_flow_runs.copy()
# Get scheduled flow runs from queue
mutation = {
"mutation($input: get_runs_in_queue_input!)": {
"get_runs_in_queue(input: $input)": {"flow_run_ids"}
}
}
now = pendulum.now("UTC")
result = self.client.graphql(
mutation,
variables={
"input": {
"before": now.isoformat(),
"labels": list(self.labels),
"tenant_id": self.client._active_tenant_id,
}
},
)
# we queried all of the available flow runs, however, some may have already been pulled
# by this agent and are in the process of being submitted in the background. We do not
# want to act on these "duplicate" flow runs until we've been assured that the background
# thread has attempted to submit the work (successful or otherwise).
flow_run_ids = set(
result.data.get_runs_in_queue.flow_run_ids) # type: ignore
if flow_run_ids:
msg = "Found flow runs {}".format(
result.data.get_runs_in_queue.flow_run_ids)
else:
msg = "No flow runs found"
already_submitting = flow_run_ids & currently_submitting_flow_runs
target_flow_run_ids = flow_run_ids - already_submitting
if already_submitting:
msg += " ({} already submitting: {})".format(
len(already_submitting), list(already_submitting))
self.logger.debug(msg)
# Query metadata for flow runs found in queue
query = {
"query": {
with_args(
"flow_run",
{
# match flow runs in the flow_run_ids list
"where": {
"id": {
"_in": list(target_flow_run_ids)
},
"_or": [
# who are EITHER scheduled...
{
"state": {
"_eq": "Scheduled"
}
},
# OR running with task runs scheduled to start more than 3
# seconds ago
{
"state": {
"_eq": "Running"
},
"task_runs": {
"state_start_time": {
"_lte": str(
now.subtract(seconds=3)) # type: ignore
}
},
},
],
},
},
): {
"id": True,
"version": True,
"state": True,
"serialized_state": True,
"parameters": True,
"scheduled_start_time": True,
"flow": {
"id",
"name",
"environment",
"run_config",
"storage",
"version",
"core_version",
},
with_args(
"task_runs",
{
"where": {
"state_start_time": {
"_lte": str(now.subtract(seconds=3)) # type: ignore
}
}
},
): {"id", "version", "task_id", "serialized_state"},
}
}
}
if target_flow_run_ids:
self.logger.debug("Querying flow run metadata")
result = self.client.graphql(query)
# Return flow runs sorted by scheduled start time
return sorted(result.data.flow_run,
key=lambda flow_run: flow_run.scheduled_start_time)
else:
return []
async def reap_zombie_task_runs(self,
heartbeat_cutoff: datetime.datetime = None
) -> int:
"""
Zombie tasks are tasks that claim to be Running, but haven't updated their heartbeat.
This method either retries them or marks them as failed.
Returns:
- int: the number of zombie task runs that were handled
"""
zombies = 0
heartbeat_cutoff = heartbeat_cutoff or pendulum.now("utc").subtract(
minutes=10)
where_clause = await self.get_task_runs_where_clause(
heartbeat_cutoff=heartbeat_cutoff)
task_runs = await models.TaskRun.where(where_clause).get(
selection_set={
"id": True,
"flow_run_id": True,
"tenant_id": True,
# Information about the current flow run state
"flow_run": {"state"},
# get information about retries from task
"task": {"max_retries", "retry_delay"},
# count the number of retrying states for this task run
with_args(
"retry_count: states_aggregate",
{"where": {
"state": {
"_eq": "Retrying"
}
}},
): {
"aggregate": {"count"}
},
},
limit=5000,
order_by={"updated": EnumValue("desc")},
apply_schema=False,
)
if task_runs:
self.logger.info(
f"Zombie killer found {len(task_runs)} task runs.")
# Set task run states to failed
for tr in task_runs:
try:
# if the flow run is running and retries are available, mark as retrying
if (tr.flow_run.state == "Running"
and tr.retry_count.aggregate.count <
(tr.task.max_retries or 0)):
message = (
"No heartbeat detected from the remote task; retrying the run."
f"This will be retry {tr.retry_count.aggregate.count + 1} of {tr.task.max_retries}."
)
retry_delay = orm._as_timedelta(tr.task.retry_delay or "0")
await prefect.api.states.set_task_run_state(
task_run_id=tr.id,
state=Retrying(
message=message,
run_count=tr.retry_count.aggregate.count + 1,
start_time=pendulum.now("UTC") + retry_delay,
),
)
# mark failed
else:
message = "No heartbeat detected from the remote task; marking the run as failed."
await prefect.api.states.set_task_run_state(
task_run_id=tr.id,
state=Failed(message=message),
)
# log the state change to the task run
await prefect.api.logs.create_logs(
[
dict(
tenant_id=tr.tenant_id,
flow_run_id=tr.flow_run_id,
task_run_id=tr.id,
name=f"{self.logger.name}.TaskRun",
message=message,
level="ERROR",
)
],
defer_db_write=False,
)
zombies += 1
except ValueError as exc:
self.logger.error(exc)
if zombies:
self.logger.info(f"Addressed {zombies} zombie task runs.")
return zombies
def tasks(name, flow_name, flow_version, project, limit):
"""
Query information regarding your Prefect tasks.
\b
Options:
--name, -n TEXT A task name to query
--flow-name, -fn TEXT A flow name to query
--flow-version, -fv INTEGER A flow version to query
--project, -p TEXT The name of a project to query
--limit, -l INTEGER A limit amount of tasks to query, defaults to 10
"""
where_clause = {
"_and": {
"name": {
"_eq": name
},
"flow": {
"name": {
"_eq": flow_name
},
"version": {
"_eq": flow_version
},
},
}
}
if project:
where_clause["_and"]["flow"]["project"] = {"name": {"_eq": project}}
query = {
"query": {
with_args(
"task",
{
"where": where_clause,
"limit": limit,
"order_by": {
"created": EnumValue("desc")
},
},
): {
"name": True,
"created": True,
"flow": {
"name": True,
"version": True
},
"mapped": True,
"type": True,
}
}
}
result = Client().graphql(query)
task_data = result.data.task
output = []
for item in task_data:
output.append([
item.name,
item.flow.name,
item.flow.version,
pendulum.parse(item.created).diff_for_humans(),
item.mapped,
item.type,
])
click.echo(
tabulate(
output,
headers=[
"NAME", "FLOW NAME", "FLOW VERSION", "AGE", "MAPPED", "TYPE"
],
tablefmt="plain",
numalign="left",
stralign="left",
))
def cloud(name, project, version, watch):
"""
Run a deployed flow in Prefect Cloud.
\b
Options:
--name, -n TEXT The name of a flow to run [required]
--project, -p TEXT The name of a project that contains the flow [required]
--version, -v INTEGER A flow version to run
--watch, -w Watch current state of the flow run, stream output to stdout
"""
query = {
"query": {
with_args(
"flow",
{
"where": {
"_and": {
"name": {
"_eq": name
},
"version": {
"_eq": version
},
"project": {
"name": {
"_eq": project
}
},
}
},
"order_by": {
"name": EnumValue("asc"),
"version": EnumValue("desc"),
},
"distinct_on": EnumValue("name"),
},
): {
"id": True
}
}
}
client = Client()
result = client.graphql(query)
flow_data = result.data.flow
if flow_data:
flow_id = flow_data[0].id
else:
click.secho("{} not found".format(name), fg="red")
return
flow_run_id = client.create_flow_run(flow_id=flow_id)
click.echo("Flow Run ID: {}".format(flow_run_id))
# TODO: Convert to using a subscription and make output prettier
if watch:
current_state = ""
while True:
query = {
"query": {
with_args("flow_run_by_pk", {"id": flow_run_id}): {
"state": True
}
}
}
result = client.graphql(query)
if result.data.flow_run_by_pk.state != current_state:
current_state = result.data.flow_run_by_pk.state
if current_state != "Success" and current_state != "Failed":
click.echo("{} -> ".format(current_state), nl=False)
else:
click.echo(current_state)
break
time.sleep(3)
def flows(name, version, project, limit, all_versions):
"""
Query information regarding your Prefect flows.
\b
Options:
--name, -n TEXT A flow name to query
--version, -v TEXT A flow version to query
--project, -p TEXT The name of a project to query
--limit, -l INTEGER A limit amount of flows to query, defaults to 10
--all-versions Output all versions of a flow, default shows most recent
"""
distinct_on = EnumValue("name")
if all_versions:
distinct_on = None
where_clause = {
"_and": {
"name": {
"_eq": name
},
"version": {
"_eq": version
},
}
}
query_results = {
"name": True,
"version": True,
"created": True,
}
headers = ["NAME", "VERSION", "AGE"]
if project:
where_clause["_and"]["project"] = {"name": {"_eq": project}}
query_results["project"] = {"name": True}
headers.append("PROJECT NAME")
query = {
"query": {
with_args(
"flow",
{
"where": where_clause,
"order_by": {
"name": EnumValue("asc"),
"version": EnumValue("desc"),
},
"distinct_on": distinct_on,
"limit": limit,
},
):
query_results
}
}
result = Client().graphql(query)
flow_data = result.data.flow
output = []
for item in flow_data:
result_output = [
item.name,
item.version,
pendulum.parse(item.created).diff_for_humans(),
]
if project:
result_output.append(item.project.name, )
output.append(result_output)
click.echo(
tabulate(
output,
headers=headers,
tablefmt="plain",
numalign="left",
stralign="left",
))
def query_flow_runs(self, tenant_id: str) -> list:
"""
Query Prefect Cloud for flow runs which need to be deployed and executed
Args:
- tenant_id (str): The tenant id to use in the query
Returns:
- list: A list of GraphQLResult flow run objects
"""
self.logger.debug("Querying for flow runs")
# Get scheduled flow runs from queue
mutation = {
"mutation($input: getRunsInQueueInput!)": {
"getRunsInQueue(input: $input)": {"flow_run_ids"}
}
}
now = pendulum.now("UTC")
result = self.client.graphql(
mutation,
variables={
"input": {
"tenantId": tenant_id,
"before": now.isoformat()
}
},
)
flow_run_ids = result.data.getRunsInQueue.flow_run_ids # type: ignore
self.logger.debug("Found flow runs {}".format(flow_run_ids))
# Query metadata fow flow runs found in queue
query = {
"query": {
with_args(
"flow_run",
{
# match flow runs in the flow_run_ids list
"where": {
"id": {
"_in": flow_run_ids
},
"_or": [
# who are EITHER scheduled...
{
"state": {
"_eq": "Scheduled"
}
},
# OR running with task runs scheduled to start more than 3 seconds ago
{
"state": {
"_eq": "Running"
},
"task_runs": {
"state_start_time": {
"_lte": str(now.subtract(seconds=3))
}
},
},
],
}
},
): {
"id": True,
"version": True,
"tenant_id": True,
"state": True,
"serialized_state": True,
"parameters": True,
"flow": {"id", "name", "environment", "storage"},
with_args(
"task_runs",
{
"where": {
"state_start_time": {
"_lte": str(now.subtract(seconds=3))
}
}
},
): {"id", "version", "task_id", "serialized_state"},
}
}
}
self.logger.debug("Querying flow run metadata")
result = self.client.graphql(query)
return result.data.flow_run # type: ignore
def get_flow_run_info(self, flow_run_id: str) -> FlowRunInfoResult:
"""
Retrieves version and current state information for the given flow run.
Args:
- flow_run_id (str): the id of the flow run to get information for
Returns:
- GraphQLResult: an object representing information about the flow run
Raises:
- ClientError: if the GraphQL mutation is bad for any reason
"""
query = {
"query": {
with_args("flow_run_by_pk", {"id": flow_run_id}): {
"id": True,
"name": True,
"flow_id": True,
"parameters": True,
"context": True,
"version": True,
"scheduled_start_time": True,
"serialized_state": True,
# load all task runs except dynamic task runs
with_args("task_runs", {
"where": {
"map_index": {
"_eq": -1
}
}
}): {
"id": True,
"task": {
"id": True,
"slug": True
},
"version": True,
"serialized_state": True,
},
}
}
}
result = self.graphql(query).data.flow_run_by_pk # type: ignore
if result is None:
raise ClientError(
'Flow run ID not found: "{}"'.format(flow_run_id))
# convert scheduled_start_time from string to datetime
result.scheduled_start_time = pendulum.parse(
result.scheduled_start_time)
# create "state" attribute from serialized_state
result.state = prefect.engine.state.State.deserialize(
result.pop("serialized_state"))
# reformat task_runs
task_runs = []
for tr in result.task_runs:
tr.state = prefect.engine.state.State.deserialize(
tr.pop("serialized_state"))
task_info = tr.pop("task")
tr.task_id = task_info["id"]
tr.task_slug = task_info["slug"]
task_runs.append(TaskRunInfoResult(**tr))
result.task_runs = task_runs
result.context = (result.context.to_dict()
if result.context is not None else None)
result.parameters = (result.parameters.to_dict()
if result.parameters is not None else None)
return FlowRunInfoResult(**result)
def flows(name, version, project, output):
"""
Describe a Prefect flow.
\b
Options:
--name, -n TEXT A flow name to query [required]
--version, -v INTEGER A flow version to query
--project, -p TEXT The name of a project to query
--output, -o TEXT Output style, currently supports `json`.
Defaults to Python dictionary format.
"""
where_clause = {
"_and": {
"name": {
"_eq": name
},
"version": {
"_eq": version
},
}
}
query_results = {
"name": True,
"version": True,
"created": True,
"description": True,
"parameters": True,
"archived": True,
"storage": True,
"environment": True,
}
if project:
where_clause["_and"]["project"] = {"name": {"_eq": project}}
query_results["project"] = {"name": True}
query = {
"query": {
with_args(
"flow",
{
"where": where_clause,
"order_by": {
"name": EnumValue("asc"),
"version": EnumValue("desc"),
},
"distinct_on": EnumValue("name"),
},
):
query_results
}
}
result = Client().graphql(query)
flow_data = result.data.flow
if flow_data:
if output == "json":
click.echo(json.dumps(flow_data[0]))
else:
click.echo(flow_data[0])
else:
click.secho("{} not found".format(name), fg="red")