Files
windmill/python-client/wmill/wmill/client.py
T
Ruben Fiszel a6d4390790 feat: workflow-as-code (WAC) v2 (#8172)
* feat: workflow-as-code v2 with @task decorator API

Replace ctx.step("name", "script") API with @task decorators where
functions are called directly. Users no longer need to pass WorkflowCtx
or use string-based step names/script paths.

Python: @task decorator with contextvars-based implicit context
TypeScript: task() wrapper with module-level context variable
Parsers: detect @task function calls instead of ctx.step() calls
Worker: updated wrappers to set implicit context

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: WAC v2 checkpoint/replay with _executing_key child dispatch

- Rust-side orchestration: parent dispatches child jobs, suspends, resumes on completion
- _executing_key in checkpoint tells child which step to execute directly
- task() throws StepSuspend(mode="step_complete") after executing target step
- result_processor handles child completion and updates parent checkpoint
- WacGraph.svelte for runtime execution visualization
- Sequential and parallel workflows tested end-to-end

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: WAC v2 bundle cache, globalThis ctx sharing, description optional

- Disable bun bundle caching for WAC v2 scripts (wrapper needs
  windmill-client from node_modules, not available in bundle mode)
- Use Reflect.set/get(globalThis, "__wmill_wf_ctx") to share workflow
  context across dual module instances (wrapper vs user script)
- Never-resolving thenable for non-matching steps in child job mode
  prevents Promise.all race conditions
- Make description field optional in NewScript API (defaults to "")

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add step() primitive for inline checkpointed steps

step() executes a function inline (no child job) and persists the result
to the checkpoint. On replay, the cached value is returned — ensuring
deterministic behavior for non-deterministic operations like Date.now()
or Math.random().

- TypeScript: step(name, fn) — executes inline, throws StepSuspend with
  mode "inline_checkpoint" to persist before continuing
- Rust: InlineCheckpoint variant in WacOutput, saves to checkpoint and
  resets running=false for immediate re-pickup (no zombie wait)
- Shared step counter between task() and step() via _allocKey()

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add Python WAC v2 support with task(), step(), workflow()

- Python SDK: WorkflowCtx with _executing_key child mode, _alloc_key
  shared counter, _run_inline_step for step(), _execute_directly and
  _never_resolve for child mode, step() async function
- Python executor: WAC v2 detection, checkpoint.json writing, WAC
  wrapper.py generation calling _run_workflow(), post-execution hook
  into shared handle_wac_v2_output()
- Make handle_wac_v2_output pub so both bun and python executors share
  the same dispatch/suspend/inline-checkpoint logic
- 17 Python tests covering dispatch, replay, parallel, conditional,
  inline checkpoint, and child mode

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* chore: update sqlx prepared queries

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: WacGraph Tooltip→Popover, simplify wacToFlow parsers

- Fix type error: Tooltip doesn't accept text snippet, use Popover
- Extract shared helpers for task matching and block collection
- Replace linear tasks.find() with Map lookups
- Remove mutable module-level counter

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: Box::pin WAC v2 output handler to prevent stack overflow

handle_python_job's async state machine was too large when combined
with handle_wac_v2_output. Box::pin heap-allocates the future.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: merge WAC v1 and v2 task decorators to preserve backward compat

The v2 @task decorator was shadowing the v1 one, breaking WAC v1
scripts that rely on HTTP-based dispatch via /workflow_as_code/ API.

The merged decorator handles three modes:
- v2: inside @workflow context → checkpoint/replay dispatch
- v1: WM_JOB_ID set, no @workflow → HTTP API dispatch + wait_job
- standalone: no Windmill env → execute function body directly

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: skip no_main_func detection for WAC v2 scripts in TS and Python parsers

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: prevent empty/noop dispatch causing infinite requeue loop

- Validate steps.len() > 0 in WAC dispatch handler (issue 3)
- Replace noop StepSuspend throw with never-resolving promise so it
  can't reach the backend as an empty dispatch (issue 4)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: Python task wrapper now converts positional args to kwargs in v2 mode

Previously only **kwargs were passed to _next_step(), silently dropping
positional arguments. Extract shared _merge_args() helper used by both
v1 and v2 paths.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: replace unwrap() with proper error propagation in WAC arg serialization

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: add workspace_id filter to v2_job queries in WAC dispatch

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: prevent race condition in WAC child dispatch

Restructure dispatch to save checkpoint + suspend parent + seed child
checkpoints in a single transaction BEFORE pushing child jobs. This
ensures a fast child can't complete before the parent is suspended.

Also wrap InlineCheckpoint save + running reset in a transaction to
prevent corrupted state on crash.

Use ULID for pre-generated child job IDs (consistent with rest of API).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: include step key and child job ID in WAC error propagation

Move step_key lookup before the success check so failed child errors
include which task failed, the child job ID, and the original error.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* docs: document WAC determinism contract and step dispatch semantics

- Document that workflow functions must be deterministic across replays
- Document that WacStepDispatch.script/args are metadata, not dispatch targets
- Add comments on counter-based key allocation

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: tighten WAC v2 detection to reduce false positives

Replace naive substring matching with line-aware checks that skip
comments and look for specific patterns:
- TS: import from "windmill-client" containing workflow/task
- Python: @workflow and @task decorators with wmill import

Extracted shared helpers in wac_executor.rs used by both executors.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: show failed steps in WacGraph when workflow completes with errors

When flowDone is true and a pending step isn't in completedSteps,
mark it as 'failed' instead of 'running'. The failed state CSS and
XCircle icon were already defined but never triggered.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: unsuspend and fail parent when WAC child push fails

Previously if a child push failed mid-batch, the parent remained
suspended with suspend = num_steps but fewer children, hanging until
the 14-day timeout. Now the push loop catches errors and unsuspends
the parent before returning the error.

Also adds source hash validation: if the script content changes between
replays, the job fails with a clear error instead of silently feeding
stale checkpoint data into wrong steps.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: clear suspend_until when unsuspending WAC parent

Set suspend_until = NULL alongside suspend = 0 in both the child
failure and all-children-complete paths, so the parent doesn't rely
on subtle pull query invariants to be re-picked-up.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* test: add exhaustive edge case tests for WAC v2 SDK

fix: make TS task wrapper non-async to fix unawaited task flush

The async wrapper caused microtask-based thenable auto-resolution that
fired .then() and threw StepSuspend before _flushPending() could capture
unawaited steps — making the flush mechanism completely broken. Now the
thenable is returned directly without async wrapping. Backward compatible
with v1 (all code paths still return awaitables).

Tests added (59 TS + 66 Python) covering: full sequential lifecycle,
step after parallel, parallel after parallel, conditional on step result,
empty/single-task workflows, 10+ steps, falsy value preservation, inline
steps, mixed step/task, unawaited flush, child mode with parallel,
key determinism, large parallel groups, and complex mixed patterns.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: atomic checkpoint updates to prevent parallel child race condition

Replace read-modify-write pattern in handle_wac_child_completion with
atomic SQL operations:
- completed_steps merged via jsonb_set(... || jsonb_build_object(...))
  so concurrent children on different workers don't overwrite each other
- suspend counter decremented atomically with RETURNING to determine
  "all done" condition (instead of checking completed_steps in memory)
- suspend_until cleared in the same atomic decrement statement

Before this fix, two parallel children completing simultaneously could
both load the same checkpoint, each add their step, and save — the
second write would overwrite the first, silently losing a child result
and leaving the parent suspended forever.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: cancel already-pushed children on partial WAC dispatch failure

When pushing child jobs sequentially, if pushing child N fails, children
1..N-1 are already running. Previously the error handler only unsuspended
the parent, leaving orphaned children that would complete and corrupt the
checkpoint state (decrementing suspend on an already-unsuspended parent,
potentially causing duplicate step execution on re-run).

Now on partial failure:
1. Cancel all already-pushed children (prevents them from completing
   and corrupting checkpoint state)
2. Clear pending_steps from checkpoint (so parent doesn't think
   children are outstanding on re-run)
3. Then unsuspend parent (so the error propagates)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: skip WAC duration write and child check for non-WAC parents

The duration write to workflow_as_code_status was running for every
non-flow child with a parent (error handlers, success handlers,
run_script children), even though it was only intended for WAC jobs.

Add WHERE workflow_as_code_status IS NOT NULL to skip non-WAC parents
entirely. Piggyback RETURNING pending_steps.job_ids on the same query
so WAC v2 child completion needs zero extra DB round-trips on the
success path.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: seed child checkpoint in same transaction as push

The child checkpoint insert was happening before the child job was
pushed, violating the FK constraint on v2_job_status. Move it into
the push transaction so the job row exists and the child can't be
picked up before its checkpoint is ready.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: set running=false when WAC parent suspends for child dispatch

The parent job kept running=true after suspending, so workers wouldn't
pick it up when children completed and suspend reached 0. The parent
only advanced when the zombie job detector reset it (~90s). Now the
dispatch suspend sets running=false so the parent is immediately
eligible for pickup.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: WAC parent suspend/unsuspend lifecycle

Keep running=true when suspending the parent so the normal pull query
(WHERE running=false) never picks it up. Keep suspend_until non-null
when decrementing suspend to 0 so the suspended pull query
(WHERE suspend_until IS NOT NULL AND suspend<=0) picks it up.

Previously: setting running=false caused infinite restart loops because
the normal pull query has no suspend check and would immediately re-pick
the parent. Clearing suspend_until on the last child prevented the
suspended pull from ever seeing it, requiring the 90s zombie detector.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add approval primitive, flow child completion, timeline fixes for WAC v2

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add error propagation, task options, sleep, and parallel for WAC v2

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* test: fix python SDK tests to use name-based keys and add new test coverage

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: address WAC v2 review findings (sleep timing, error marker, atomicity)

- Fix sleep using suspend=1 instead of 0 to enforce actual delay
- Add approval/sleep resume injection to Python executor
- Fix TS SDK concurrency_limit mapping (was reading wrong property)
- Namespace error marker as __wmill_error to avoid user data collision
- Wrap child completion SQL in transaction for atomicity
- Decrement suspend even when step key is missing (prevents hang)
- Expand TASK_RE to handle export const, let, var, generics
- Validate step key uniqueness before dispatch
- Log warning on checkpoint deserialization failure
- Remove unimplemented delete_after_use from SDKs
- Add TaskError exception class to Python SDK with diagnostic context
- Fix extra positional args handling and add functools.wraps
- Improve getParamNames to handle typed/destructured params

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* sqlx

* sqlx

* test: add WAC v1 e2e integration tests for TS and Python

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: revert fake test versions in typescript-client

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* refactor: remove unused WacGraph component and strip wacToFlow to isWorkflowAsCode

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* refactor: extract shared approval/sleep resume logic into wac_executor

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-09 19:39:24 +00:00

2845 lines
89 KiB
Python

from __future__ import annotations
import atexit
import datetime as dt
import functools
from io import BufferedReader, BytesIO
import logging
import os
import random
import time
import warnings
import json
from json import JSONDecodeError
from typing import Dict, Any, Union, Literal, Optional
import re
import httpx
from .s3_reader import S3BufferedReader, bytes_generator
from .s3_types import (
Boto3ConnectionSettings,
DuckDbConnectionSettings,
PolarsConnectionSettings,
S3Object,
)
_client: "Windmill | None" = None
logger = logging.getLogger("windmill_client")
JobStatus = Literal["RUNNING", "WAITING", "COMPLETED"]
class Windmill:
"""Windmill client for interacting with the Windmill API."""
def __init__(self, base_url=None, token=None, workspace=None, verify=True):
"""Initialize the Windmill client.
Args:
base_url: API base URL (defaults to BASE_INTERNAL_URL or WM_BASE_URL env)
token: Authentication token (defaults to WM_TOKEN env)
workspace: Workspace ID (defaults to WM_WORKSPACE env)
verify: Whether to verify SSL certificates
"""
base = (
base_url
or os.environ.get("BASE_INTERNAL_URL")
or os.environ.get("WM_BASE_URL")
)
self.base_url = f"{base}/api"
self.token = token or os.environ.get("WM_TOKEN")
self.headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {self.token}",
}
self.verify = verify
self.client = self.get_client()
self.workspace = workspace or os.environ.get("WM_WORKSPACE")
self.path = os.environ.get("WM_JOB_PATH")
self.mocked_api = self.get_mocked_api()
assert self.workspace, (
f"workspace required as an argument or as WM_WORKSPACE environment variable"
)
def get_mocked_api(self) -> Optional[dict]:
mocked_path = os.environ.get("WM_MOCKED_API_FILE")
if not mocked_path:
return None
logger.info("Using mocked API from %s", mocked_path)
mocked_api = {"variables": {}, "resources": {}}
try:
with open(mocked_path, "r") as f:
incoming_mocked_api = json.load(f)
mocked_api = {**mocked_api, **incoming_mocked_api}
except Exception as e:
logger.warning(
"Error parsing mocked API file at path %s Using empty mocked API.",
mocked_path,
)
logger.debug(e)
return mocked_api
def get_client(self) -> httpx.Client:
"""Get the HTTP client instance.
Returns:
Configured httpx.Client for API requests
"""
return httpx.Client(
base_url=self.base_url,
headers=self.headers,
verify=self.verify,
)
def get(self, endpoint, raise_for_status=True, **kwargs) -> httpx.Response:
"""Make an HTTP GET request to the Windmill API.
Args:
endpoint: API endpoint path
raise_for_status: Whether to raise an exception on HTTP errors
**kwargs: Additional arguments passed to httpx.get
Returns:
HTTP response object
"""
endpoint = endpoint.lstrip("/")
resp = self.client.get(f"/{endpoint}", **kwargs)
if raise_for_status:
try:
resp.raise_for_status()
except httpx.HTTPStatusError as err:
error = f"{err.request.url}: {err.response.status_code}, {err.response.text}"
logger.error(error)
raise Exception(error)
return resp
def post(self, endpoint, raise_for_status=True, **kwargs) -> httpx.Response:
"""Make an HTTP POST request to the Windmill API.
Args:
endpoint: API endpoint path
raise_for_status: Whether to raise an exception on HTTP errors
**kwargs: Additional arguments passed to httpx.post
Returns:
HTTP response object
"""
endpoint = endpoint.lstrip("/")
resp = self.client.post(f"/{endpoint}", **kwargs)
if raise_for_status:
try:
resp.raise_for_status()
except httpx.HTTPStatusError as err:
error = f"{err.request.url}: {err.response.status_code}, {err.response.text}"
logger.error(error)
raise Exception(error)
return resp
def create_token(self, duration=dt.timedelta(days=1)) -> str:
"""Create a new authentication token.
Args:
duration: Token validity duration (default: 1 day)
Returns:
New authentication token string
"""
endpoint = "/users/tokens/create"
payload = {
"label": f"refresh {time.time()}",
"expiration": (dt.datetime.now() + duration).strftime("%Y-%m-%dT%H:%M:%SZ"),
}
return self.post(endpoint, json=payload).text
def run_script_async(
self,
path: str = None,
hash_: str = None,
args: dict = None,
scheduled_in_secs: int = None,
) -> str:
"""Create a script job and return its job id.
.. deprecated:: Use run_script_by_path_async or run_script_by_hash_async instead.
"""
logging.warning(
"run_script_async is deprecated. Use run_script_by_path_async or run_script_by_hash_async instead.",
)
assert not (path and hash_), "path and hash_ are mutually exclusive"
return self._run_script_async_internal(path=path, hash_=hash_, args=args, scheduled_in_secs=scheduled_in_secs)
def _run_script_async_internal(
self,
path: str = None,
hash_: str = None,
args: dict = None,
scheduled_in_secs: int = None,
) -> str:
"""Internal helper for running scripts asynchronously."""
args = args or {}
params = {"scheduled_in_secs": scheduled_in_secs} if scheduled_in_secs else {}
if os.environ.get("WM_JOB_ID"):
params["parent_job"] = os.environ.get("WM_JOB_ID")
if os.environ.get("WM_ROOT_FLOW_JOB_ID"):
params["root_job"] = os.environ.get("WM_ROOT_FLOW_JOB_ID")
if path:
endpoint = f"/w/{self.workspace}/jobs/run/p/{path}"
elif hash_:
endpoint = f"/w/{self.workspace}/jobs/run/h/{hash_}"
else:
raise Exception("path or hash_ must be provided")
return self.post(endpoint, json=args, params=params).text
def run_script_by_path_async(
self,
path: str,
args: dict = None,
scheduled_in_secs: int = None,
) -> str:
"""Create a script job by path and return its job id."""
return self._run_script_async_internal(path=path, args=args, scheduled_in_secs=scheduled_in_secs)
def run_script_by_hash_async(
self,
hash_: str,
args: dict = None,
scheduled_in_secs: int = None,
) -> str:
"""Create a script job by hash and return its job id."""
return self._run_script_async_internal(hash_=hash_, args=args, scheduled_in_secs=scheduled_in_secs)
def run_flow_async(
self,
path: str,
args: dict = None,
scheduled_in_secs: int = None,
# can only be set to false if this the job will be fully await and not concurrent with any other job
# as otherwise the child flow and its own child will store their state in the parent job which will
# lead to incorrectness and failures
do_not_track_in_parent: bool = True,
) -> str:
"""Create a flow job and return its job id."""
args = args or {}
params = {"scheduled_in_secs": scheduled_in_secs} if scheduled_in_secs else {}
if not do_not_track_in_parent:
if os.environ.get("WM_JOB_ID"):
params["parent_job"] = os.environ.get("WM_JOB_ID")
if os.environ.get("WM_ROOT_FLOW_JOB_ID"):
params["root_job"] = os.environ.get("WM_ROOT_FLOW_JOB_ID")
if path:
endpoint = f"/w/{self.workspace}/jobs/run/f/{path}"
else:
raise Exception("path must be provided")
return self.post(endpoint, json=args, params=params).text
def run_script(
self,
path: str = None,
hash_: str = None,
args: dict = None,
timeout: dt.timedelta | int | float | None = None,
verbose: bool = False,
cleanup: bool = True,
assert_result_is_not_none: bool = False,
) -> Any:
"""Run script synchronously and return its result.
.. deprecated:: Use run_script_by_path or run_script_by_hash instead.
"""
logging.warning(
"run_script is deprecated. Use run_script_by_path or run_script_by_hash instead.",
)
assert not (path and hash_), "path and hash_ are mutually exclusive"
return self._run_script_internal(
path=path, hash_=hash_, args=args, timeout=timeout, verbose=verbose,
cleanup=cleanup, assert_result_is_not_none=assert_result_is_not_none
)
def _run_script_internal(
self,
path: str = None,
hash_: str = None,
args: dict = None,
timeout: dt.timedelta | int | float | None = None,
verbose: bool = False,
cleanup: bool = True,
assert_result_is_not_none: bool = False,
) -> Any:
"""Internal helper for running scripts synchronously."""
args = args or {}
if verbose:
if path:
logger.info(f"running `{path}` synchronously with {args = }")
elif hash_:
logger.info(f"running script with hash `{hash_}` synchronously with {args = }")
if isinstance(timeout, dt.timedelta):
timeout = timeout.total_seconds()
job_id = self._run_script_async_internal(path=path, hash_=hash_, args=args)
return self.wait_job(
job_id, timeout, verbose, cleanup, assert_result_is_not_none
)
def run_script_by_path(
self,
path: str,
args: dict = None,
timeout: dt.timedelta | int | float | None = None,
verbose: bool = False,
cleanup: bool = True,
assert_result_is_not_none: bool = False,
) -> Any:
"""Run script by path synchronously and return its result."""
return self._run_script_internal(
path=path, args=args, timeout=timeout, verbose=verbose,
cleanup=cleanup, assert_result_is_not_none=assert_result_is_not_none
)
def run_script_by_hash(
self,
hash_: str,
args: dict = None,
timeout: dt.timedelta | int | float | None = None,
verbose: bool = False,
cleanup: bool = True,
assert_result_is_not_none: bool = False,
) -> Any:
"""Run script by hash synchronously and return its result."""
return self._run_script_internal(
hash_=hash_, args=args, timeout=timeout, verbose=verbose,
cleanup=cleanup, assert_result_is_not_none=assert_result_is_not_none
)
def run_inline_script_preview(
self,
content: str,
language: str,
args: dict = None,
) -> Any:
"""Run a script on the current worker without creating a job"""
endpoint = f"/w/{self.workspace}/jobs/run_inline/preview"
body = {
"content": content,
"language": language,
"args": args or {},
}
return self.post(endpoint, json=body).json()
def wait_job(
self,
job_id,
timeout: dt.timedelta | int | float | None = None,
verbose: bool = False,
cleanup: bool = True,
assert_result_is_not_none: bool = False,
):
"""Wait for a job to complete and return its result.
Args:
job_id: ID of the job to wait for
timeout: Maximum time to wait (seconds or timedelta)
verbose: Enable verbose logging
cleanup: Register cleanup handler to cancel job on exit
assert_result_is_not_none: Raise exception if result is None
Returns:
Job result when completed
Raises:
TimeoutError: If timeout is reached
Exception: If job fails
"""
def cancel_job():
logger.warning(f"cancelling job: {job_id}")
self.post(
f"/w/{self.workspace}/jobs_u/queue/cancel/{job_id}",
json={"reason": "parent script cancelled"},
).raise_for_status()
if cleanup:
atexit.register(cancel_job)
start_time = time.time()
if isinstance(timeout, dt.timedelta):
timeout = timeout.total_seconds()
while True:
result_res = self.get(
f"/w/{self.workspace}/jobs_u/completed/get_result_maybe/{job_id}", True
).json()
started = result_res["started"]
completed = result_res["completed"]
success = result_res["success"]
if not started and verbose:
logger.info(f"job {job_id} has not started yet")
if cleanup and completed:
atexit.unregister(cancel_job)
if completed:
result = result_res["result"]
if success:
if result is None and assert_result_is_not_none:
raise Exception("Result was none")
return result
else:
error = result["error"]
raise Exception(f"Job {job_id} was not successful: {str(error)}")
if timeout and ((time.time() - start_time) > timeout):
msg = "reached timeout"
logger.warning(msg)
self.post(
f"/w/{self.workspace}/jobs_u/queue/cancel/{job_id}",
json={"reason": msg},
)
raise TimeoutError(msg)
if verbose:
logger.info(f"sleeping 0.5 seconds for {job_id = }")
time.sleep(0.5)
def cancel_job(self, job_id: str, reason: str = None) -> str:
"""Cancel a specific job by ID.
Args:
job_id: UUID of the job to cancel
reason: Optional reason for cancellation
Returns:
Response message from the cancel endpoint
"""
logger.info(f"cancelling job: {job_id}")
payload = {"reason": reason or "cancelled via cancel_job method"}
response = self.post(
f"/w/{self.workspace}/jobs_u/queue/cancel/{job_id}",
json=payload,
)
return response.text
def cancel_running(self) -> dict:
"""Cancel currently running executions of the same script."""
logger.info("canceling running executions of this script")
jobs = self.get(
f"/w/{self.workspace}/jobs/list",
params={
"running": "true",
"script_path_exact": self.path,
},
).json()
current_job_id = os.environ.get("WM_JOB_ID")
logger.debug(f"{current_job_id = }")
job_ids = [j["id"] for j in jobs if j["id"] != current_job_id]
if job_ids:
logger.info(f"cancelling the following job ids: {job_ids}")
else:
logger.info("no previous executions to cancel")
result = {}
for id_ in job_ids:
result[id_] = self.post(
f"/w/{self.workspace}/jobs_u/queue/cancel/{id_}",
json={"reason": "killed by `cancel_running` method"},
)
return result
def get_job(self, job_id: str) -> dict:
"""Get job details by ID.
Args:
job_id: UUID of the job
Returns:
Job details dictionary
"""
return self.get(f"/w/{self.workspace}/jobs_u/get/{job_id}").json()
def get_root_job_id(self, job_id: str | None = None) -> dict:
"""Get the root job ID for a flow hierarchy.
Args:
job_id: Job ID (defaults to current WM_JOB_ID)
Returns:
Root job ID
"""
job_id = job_id or os.environ.get("WM_JOB_ID")
return self.get(f"/w/{self.workspace}/jobs_u/get_root_job_id/{job_id}").json()
def get_id_token(self, audience: str, expires_in: int | None = None) -> str:
"""Get an OIDC JWT token for authentication to external services.
Args:
audience: Token audience (e.g., "vault", "aws")
expires_in: Optional expiration time in seconds
Returns:
JWT token string
"""
params = {}
if expires_in is not None:
params["expires_in"] = expires_in
return self.post(f"/w/{self.workspace}/oidc/token/{audience}", params=params).text
def get_job_status(self, job_id: str) -> JobStatus:
"""Get the status of a job.
Args:
job_id: UUID of the job
Returns:
Job status: "RUNNING", "WAITING", or "COMPLETED"
"""
job = self.get_job(job_id)
job_type = job.get("type", "")
assert job_type, f"{job} is not a valid job"
if job_type.lower() == "completedjob":
return "COMPLETED"
if job.get("running"):
return "RUNNING"
return "WAITING"
def get_result(
self,
job_id: str,
assert_result_is_not_none: bool = True,
) -> Any:
"""Get the result of a completed job.
Args:
job_id: UUID of the completed job
assert_result_is_not_none: Raise exception if result is None
Returns:
Job result
"""
result = self.get(f"/w/{self.workspace}/jobs_u/completed/get_result/{job_id}")
result_text = result.text
if assert_result_is_not_none and result_text is None:
raise Exception(f"result is None for {job_id = }")
try:
return result.json()
except JSONDecodeError:
return result_text
def get_variable(self, path: str) -> str:
"""Get a variable value by path.
Args:
path: Variable path in Windmill
Returns:
Variable value as string
"""
path = parse_variable_syntax(path) or path
if self.mocked_api is not None:
variables = self.mocked_api["variables"]
try:
result = variables[path]
return result
except KeyError:
logger.info(
f"MockedAPI present, but variable not found at {path}, falling back to real API"
)
return self.get(f"/w/{self.workspace}/variables/get_value/{path}").json()
def set_variable(self, path: str, value: str, is_secret: bool = False) -> None:
"""Set a variable value by path, creating it if it doesn't exist.
Args:
path: Variable path in Windmill
value: Variable value to set
is_secret: Whether the variable should be secret (default: False)
"""
path = parse_variable_syntax(path) or path
if self.mocked_api is not None:
self.mocked_api["variables"][path] = value
return
# check if variable exists
r = self.get(
f"/w/{self.workspace}/variables/get/{path}", raise_for_status=False
)
if r.status_code == 404:
# create variable
self.post(
f"/w/{self.workspace}/variables/create",
json={
"path": path,
"value": value,
"is_secret": is_secret,
"description": "",
},
)
else:
# update variable
self.post(
f"/w/{self.workspace}/variables/update/{path}",
json={"value": value},
)
def get_resource(
self,
path: str,
none_if_undefined: bool = False,
interpolated: bool = True
) -> dict | None:
"""Get a resource value by path.
Args:
path: Resource path in Windmill
none_if_undefined: Return None instead of raising if not found
interpolated: if variables and resources are fully unrolled
Returns:
Resource value dictionary or None
"""
path = parse_resource_syntax(path) or path
if self.mocked_api is not None:
resources = self.mocked_api["resources"]
try:
result = resources[path]
return result
except KeyError:
# NOTE: should mocked_api respect `none_if_undefined`?
if none_if_undefined:
logger.info(
f"resource not found at ${path}, but none_if_undefined is True, so returning None"
)
return None
logger.info(
f"MockedAPI present, but resource not found at ${path}, falling back to real API"
)
try:
if interpolated:
return self.get(
f"/w/{self.workspace}/resources/get_value_interpolated/{path}"
).json()
else:
return self.get(
f"/w/{self.workspace}/resources/get_value/{path}"
).json()
except Exception as e:
if none_if_undefined:
return None
logger.error(e)
raise e
def set_resource(
self,
value: Any,
path: str,
resource_type: str,
):
"""Set a resource value by path, creating it if it doesn't exist.
Args:
value: Resource value to set
path: Resource path in Windmill
resource_type: Resource type for creation
"""
path = parse_resource_syntax(path) or path
if self.mocked_api is not None:
self.mocked_api["resources"][path] = value
return
# check if resource exists
r = self.get(
f"/w/{self.workspace}/resources/get/{path}", raise_for_status=False
)
if r.status_code == 404:
# create resource
self.post(
f"/w/{self.workspace}/resources/create",
json={
"path": path,
"value": value,
"resource_type": resource_type,
},
)
else:
# update resource
self.post(
f"/w/{self.workspace}/resources/update_value/{path}",
json={"value": value},
)
def list_resources(
self,
resource_type: str = None,
page: int = None,
per_page: int = None,
) -> list[dict]:
"""List resources from Windmill workspace.
Args:
resource_type: Optional resource type to filter by (e.g., "postgresql", "mysql", "s3")
page: Optional page number for pagination
per_page: Optional number of results per page
Returns:
List of resource dictionaries
"""
params = {}
if resource_type is not None:
params["resource_type"] = resource_type
if page is not None:
params["page"] = page
if per_page is not None:
params["per_page"] = per_page
return self.get(
f"/w/{self.workspace}/resources/list",
params=params if params else None,
).json()
def set_state(self, value: Any, path: str | None = None) -> None:
"""Set the workflow state.
Args:
value: State value to set
path: Optional state resource path override.
"""
self.set_resource(value, path=path or self.state_path, resource_type="state")
def get_state(self, path: str | None = None) -> Any:
"""Get the workflow state.
Args:
path: Optional state resource path override.
Returns:
State value or None if not set
"""
return self.get_resource(path=path or self.state_path, none_if_undefined=True, interpolated=True)
def set_progress(self, value: int, job_id: Optional[str] = None):
"""Set job progress percentage (0-99).
Args:
value: Progress percentage
job_id: Job ID (defaults to current WM_JOB_ID)
"""
workspace = get_workspace()
flow_id = os.environ.get("WM_FLOW_JOB_ID")
job_id = job_id or os.environ.get("WM_JOB_ID")
if job_id != None:
job = self.get_job(job_id)
flow_id = job.get("parent_job")
self.post(
f"/w/{workspace}/job_metrics/set_progress/{job_id}",
json={
"percent": value,
"flow_job_id": flow_id or None,
},
)
def get_progress(self, job_id: Optional[str] = None) -> Any:
"""Get job progress percentage.
Args:
job_id: Job ID (defaults to current WM_JOB_ID)
Returns:
Progress value (0-100) or None if not set
"""
workspace = get_workspace()
job_id = job_id or os.environ.get("WM_JOB_ID")
r = self.get(
f"/w/{workspace}/job_metrics/get_progress/{job_id}",
)
if r.status_code == 404:
print(f"Job {job_id} does not exist")
return None
else:
return r.json()
def set_flow_user_state(self, key: str, value: Any) -> None:
"""Set the user state of a flow at a given key"""
flow_id = self.get_root_job_id()
r = self.post(
f"/w/{self.workspace}/jobs/flow/user_states/{flow_id}/{key}",
json=value,
raise_for_status=False,
)
if r.status_code == 404:
print(f"Job {flow_id} does not exist or is not a flow")
def get_flow_user_state(self, key: str) -> Any:
"""Get the user state of a flow at a given key"""
flow_id = self.get_root_job_id()
r = self.get(
f"/w/{self.workspace}/jobs/flow/user_states/{flow_id}/{key}",
raise_for_status=False,
)
if r.status_code == 404:
print(f"Job {flow_id} does not exist or is not a flow")
return None
else:
return r.json()
@property
def version(self):
"""Get the Windmill server version.
Returns:
Version string
"""
return self.get("version").text
def get_duckdb_connection_settings(
self,
s3_resource_path: str = "",
) -> DuckDbConnectionSettings | None:
"""
Convenient helpers that takes an S3 resource as input and returns the settings necessary to
initiate an S3 connection from DuckDB
"""
s3_resource_path = parse_resource_syntax(s3_resource_path) or s3_resource_path
try:
raw_obj = self.post(
f"/w/{self.workspace}/job_helpers/v2/duckdb_connection_settings",
json={}
if s3_resource_path == ""
else {"s3_resource_path": s3_resource_path},
).json()
return DuckDbConnectionSettings(raw_obj)
except JSONDecodeError as e:
raise Exception(
"Could not generate DuckDB S3 connection settings from the provided resource"
) from e
def get_polars_connection_settings(
self,
s3_resource_path: str = "",
) -> PolarsConnectionSettings:
"""
Convenient helpers that takes an S3 resource as input and returns the settings necessary to
initiate an S3 connection from Polars
"""
s3_resource_path = parse_resource_syntax(s3_resource_path) or s3_resource_path
try:
raw_obj = self.post(
f"/w/{self.workspace}/job_helpers/v2/polars_connection_settings",
json={}
if s3_resource_path == ""
else {"s3_resource_path": s3_resource_path},
).json()
return PolarsConnectionSettings(raw_obj)
except JSONDecodeError as e:
raise Exception(
"Could not generate Polars S3 connection settings from the provided resource"
) from e
def get_boto3_connection_settings(
self,
s3_resource_path: str = "",
) -> Boto3ConnectionSettings:
"""
Convenient helpers that takes an S3 resource as input and returns the settings necessary to
initiate an S3 connection using boto3
"""
s3_resource_path = parse_resource_syntax(s3_resource_path) or s3_resource_path
try:
s3_resource = self.post(
f"/w/{self.workspace}/job_helpers/v2/s3_resource_info",
json={}
if s3_resource_path == ""
else {"s3_resource_path": s3_resource_path},
).json()
return self.__boto3_connection_settings(s3_resource)
except JSONDecodeError as e:
raise Exception(
"Could not generate Boto3 S3 connection settings from the provided resource"
) from e
def load_s3_file(self, s3object: S3Object | str, s3_resource_path: str | None) -> bytes:
"""
Load a file from the workspace s3 bucket and returns its content as bytes.
'''python
from wmill import S3Object
s3_obj = S3Object(s3="/path/to/my_file.txt")
my_obj_content = client.load_s3_file(s3_obj)
file_content = my_obj_content.decode("utf-8")
'''
"""
s3object = parse_s3_object(s3object)
with self.load_s3_file_reader(s3object, s3_resource_path) as file_reader:
return file_reader.read()
def load_s3_file_reader(
self, s3object: S3Object | str, s3_resource_path: str | None
) -> BufferedReader:
"""
Load a file from the workspace s3 bucket and returns the bytes stream.
'''python
from wmill import S3Object
s3_obj = S3Object(s3="/path/to/my_file.txt")
with wmill.load_s3_file_reader(s3object, s3_resource_path) as file_reader:
print(file_reader.read())
'''
"""
s3object = parse_s3_object(s3object)
reader = S3BufferedReader(
f"{self.workspace}",
self.client,
s3object["s3"],
s3_resource_path,
s3object["storage"] if "storage" in s3object else None,
)
return reader
def write_s3_file(
self,
s3object: S3Object | str | None,
file_content: BufferedReader | bytes,
s3_resource_path: str | None,
content_type: str | None = None,
content_disposition: str | None = None,
) -> S3Object:
"""
Write a file to the workspace S3 bucket
'''python
from wmill import S3Object
s3_obj = S3Object(s3="/path/to/my_file.txt")
# for an in memory bytes array:
file_content = b'Hello Windmill!'
client.write_s3_file(s3_obj, file_content)
# for a file:
with open("my_file.txt", "rb") as my_file:
client.write_s3_file(s3_obj, my_file)
'''
"""
s3object = parse_s3_object(s3object)
# httpx accepts either bytes or "a bytes generator" as content. If it's a BufferedReader, we need to convert it to a generator
if isinstance(file_content, BufferedReader):
content_payload = bytes_generator(file_content)
elif isinstance(file_content, bytes):
content_payload = file_content
else:
raise Exception("Type of file_content not supported")
query_params = {}
if s3object is not None and s3object["s3"] != "":
query_params["file_key"] = s3object["s3"]
if s3_resource_path is not None and s3_resource_path != "":
query_params["s3_resource_path"] = s3_resource_path
if (
s3object is not None
and "storage" in s3object
and s3object["storage"] is not None
):
query_params["storage"] = s3object["storage"]
if content_type is not None:
query_params["content_type"] = content_type
if content_disposition is not None:
query_params["content_disposition"] = content_disposition
try:
# need a vanilla client b/c content-type is not application/json here
response = httpx.post(
f"{self.base_url}/w/{self.workspace}/job_helpers/upload_s3_file",
headers={
"Authorization": f"Bearer {self.token}",
"Content-Type": "application/octet-stream",
},
params=query_params,
content=content_payload,
verify=self.verify,
timeout=None,
).json()
except Exception as e:
raise Exception("Could not write file to S3") from e
return S3Object(s3=response["file_key"], storage=s3object.get("storage") if s3object else None)
def delete_s3_object(
self,
s3object: S3Object | str,
s3_resource_path: str | None = None,
) -> None:
"""
Permanently delete a file from the workspace S3 bucket.
'''python
from wmill import S3Object
s3_obj = S3Object(s3="/path/to/my_file.txt")
client.delete_s3_object(s3_obj)
'''
"""
s3object = parse_s3_object(s3object)
query_params: Dict[str, Any] = {"file_key": s3object["s3"]}
if s3_resource_path is not None and s3_resource_path != "":
query_params["s3_resource_path"] = s3_resource_path
if "storage" in s3object and s3object["storage"] is not None:
query_params["storage"] = s3object["storage"]
try:
resp = self.client.delete(
f"/w/{self.workspace}/job_helpers/delete_s3_file",
params=query_params,
)
resp.raise_for_status()
except httpx.HTTPStatusError as err:
error = f"{err.request.url}: {err.response.status_code}, {err.response.text}"
logger.error(error)
raise Exception(error)
except Exception as e:
raise Exception("Could not delete file from S3") from e
def sign_s3_objects(self, s3_objects: list[S3Object | str]) -> list[S3Object]:
"""Sign S3 objects for use by anonymous users in public apps.
Args:
s3_objects: List of S3 objects to sign
Returns:
List of signed S3 objects
"""
return self.post(
f"/w/{self.workspace}/apps/sign_s3_objects", json={"s3_objects": list(map(parse_s3_object, s3_objects))}
).json()
def sign_s3_object(self, s3_object: S3Object | str) -> S3Object:
"""Sign a single S3 object for use by anonymous users in public apps.
Args:
s3_object: S3 object to sign
Returns:
Signed S3 object
"""
return self.post(
f"/w/{self.workspace}/apps/sign_s3_objects",
json={"s3_objects": [s3_object]},
).json()[0]
def get_presigned_s3_public_urls(
self,
s3_objects: list[S3Object | str],
base_url: str | None = None,
) -> list[str]:
"""
Generate presigned public URLs for an array of S3 objects.
If an S3 object is not signed yet, it will be signed first.
Args:
s3_objects: List of S3 objects to sign
base_url: Optional base URL for the presigned URLs (defaults to WM_BASE_URL)
Returns:
List of signed public URLs
Example:
>>> s3_objs = [S3Object(s3="/path/to/file1.txt"), S3Object(s3="/path/to/file2.txt")]
>>> urls = client.get_presigned_s3_public_urls(s3_objs)
"""
base_url = base_url or self._get_public_base_url()
s3_objs = [parse_s3_object(s3_obj) for s3_obj in s3_objects]
# Sign all S3 objects that need to be signed in one go
s3_objs_to_sign: list[tuple[S3Object, int]] = [
(s3_obj, index)
for index, s3_obj in enumerate(s3_objs)
if s3_obj.get("presigned") is None
]
if s3_objs_to_sign:
signed_s3_objs = self.sign_s3_objects(
[s3_obj for s3_obj, _ in s3_objs_to_sign]
)
for i, (_, original_index) in enumerate(s3_objs_to_sign):
s3_objs[original_index] = parse_s3_object(signed_s3_objs[i])
signed_urls: list[str] = []
for s3_obj in s3_objs:
s3 = s3_obj.get("s3", "")
presigned = s3_obj.get("presigned", "")
storage = s3_obj.get("storage", "_default_")
signed_url = f"{base_url}/api/w/{self.workspace}/s3_proxy/{storage}/{s3}?{presigned}"
signed_urls.append(signed_url)
return signed_urls
def get_presigned_s3_public_url(
self,
s3_object: S3Object | str,
base_url: str | None = None,
) -> str:
"""
Generate a presigned public URL for an S3 object.
If the S3 object is not signed yet, it will be signed first.
Args:
s3_object: S3 object to sign
base_url: Optional base URL for the presigned URL (defaults to WM_BASE_URL)
Returns:
Signed public URL
Example:
>>> s3_obj = S3Object(s3="/path/to/file.txt")
>>> url = client.get_presigned_s3_public_url(s3_obj)
"""
urls = self.get_presigned_s3_public_urls([s3_object], base_url)
return urls[0]
def _get_public_base_url(self) -> str:
"""Get the public base URL from environment or default to localhost"""
return os.environ.get("WM_BASE_URL", "http://localhost:3000")
def __boto3_connection_settings(self, s3_resource) -> Boto3ConnectionSettings:
endpoint_url_prefix = "https://" if s3_resource["useSSL"] else "http://"
endpoint = s3_resource["endPoint"]
port = s3_resource.get("port")
if port:
endpoint_url = "{}{}:{}".format(endpoint_url_prefix, endpoint, port)
else:
endpoint_url = "{}{}".format(endpoint_url_prefix, endpoint)
settings = {
"endpoint_url": endpoint_url,
"region_name": s3_resource["region"],
"use_ssl": s3_resource["useSSL"],
"aws_access_key_id": s3_resource["accessKey"],
"aws_secret_access_key": s3_resource["secretKey"],
# no need for path_style here as boto3 is clever enough to determine which one to use
}
# Include session token for OIDC/STS temporary credentials
if s3_resource.get("token"):
settings["aws_session_token"] = s3_resource["token"]
return Boto3ConnectionSettings(settings)
def whoami(self) -> dict:
"""Get the current user information.
Returns:
User details dictionary
"""
return self.get("/users/whoami").json()
@property
def user(self) -> dict:
"""Get the current user information (alias for whoami).
Returns:
User details dictionary
"""
return self.whoami()
@property
def state_path(self) -> str:
"""Get the state resource path from environment.
Returns:
State path string
"""
state_path = os.environ.get(
"WM_STATE_PATH_NEW", os.environ.get("WM_STATE_PATH")
)
if state_path is None:
raise Exception("State path not found")
return state_path
@property
def state(self) -> Any:
"""Get the workflow state.
Returns:
State value or None if not set
"""
return self.get_resource(path=self.state_path, none_if_undefined=True, interpolated=True)
@state.setter
def state(self, value: Any) -> None:
"""Set the workflow state."""
self.set_state(value)
@staticmethod
def set_shared_state_pickle(value: Any, path: str = "state.pickle") -> None:
"""
Set the state in the shared folder using pickle
"""
import pickle
with open(f"/shared/{path}", "wb") as handle:
pickle.dump(value, handle, protocol=pickle.HIGHEST_PROTOCOL)
@staticmethod
def get_shared_state_pickle(path: str = "state.pickle") -> Any:
"""
Get the state in the shared folder using pickle
"""
import pickle
with open(f"/shared/{path}", "rb") as handle:
return pickle.load(handle)
@staticmethod
def set_shared_state(value: Any, path: str = "state.json") -> None:
"""
Set the state in the shared folder using pickle
"""
import json
with open(f"/shared/{path}", "w", encoding="utf-8") as f:
json.dump(value, f, ensure_ascii=False, indent=4)
@staticmethod
def get_shared_state(path: str = "state.json") -> None:
"""
Get the state in the shared folder using pickle
"""
import json
with open(f"/shared/{path}", "r", encoding="utf-8") as f:
return json.load(f)
def get_resume_urls(self, approver: str = None, flow_level: bool = None) -> dict:
"""Get URLs needed for resuming a flow after suspension.
Args:
approver: Optional approver name
flow_level: If True, generate resume URLs for the parent flow instead of the
specific step. This allows pre-approvals that can be consumed by any later
suspend step in the same flow.
Returns:
Dictionary with approvalPage, resume, and cancel URLs
"""
nonce = random.randint(0, 1000000000)
job_id = os.environ.get("WM_JOB_ID") or "NO_ID"
params = {"approver": approver}
if flow_level is not None:
params["flow_level"] = flow_level
return self.get(
f"/w/{self.workspace}/jobs/resume_urls/{job_id}/{nonce}",
params=params,
).json()
def request_interactive_slack_approval(
self,
slack_resource_path: str,
channel_id: str,
message: str = None,
approver: str = None,
default_args_json: dict = None,
dynamic_enums_json: dict = None,
) -> None:
"""
Sends an interactive approval request via Slack, allowing optional customization of the message, approver, and form fields.
**[Enterprise Edition Only]** To include form fields in the Slack approval request, use the "Advanced -> Suspend -> Form" functionality.
Learn more at: https://www.windmill.dev/docs/flows/flow_approval#form
:param slack_resource_path: The path to the Slack resource in Windmill.
:type slack_resource_path: str
:param channel_id: The Slack channel ID where the approval request will be sent.
:type channel_id: str
:param message: Optional custom message to include in the Slack approval request.
:type message: str, optional
:param approver: Optional user ID or name of the approver for the request.
:type approver: str, optional
:param default_args_json: Optional dictionary defining or overriding the default arguments for form fields.
:type default_args_json: dict, optional
:param dynamic_enums_json: Optional dictionary overriding the enum default values of enum form fields.
:type dynamic_enums_json: dict, optional
:raises Exception: If the function is not called within a flow or flow preview.
:raises Exception: If the required flow job or flow step environment variables are not set.
:return: None
**Usage Example:**
>>> client.request_interactive_slack_approval(
... slack_resource_path="/u/alex/my_slack_resource",
... channel_id="admins-slack-channel",
... message="Please approve this request",
... approver="approver123",
... default_args_json={"key1": "value1", "key2": 42},
... dynamic_enums_json={"foo": ["choice1", "choice2"], "bar": ["optionA", "optionB"]},
... )
**Notes:**
- This function must be executed within a Windmill flow or flow preview.
- The function checks for required environment variables (`WM_FLOW_JOB_ID`, `WM_FLOW_STEP_ID`) to ensure it is run in the appropriate context.
"""
workspace = self.workspace
flow_job_id = os.environ.get("WM_FLOW_JOB_ID")
if not flow_job_id:
raise Exception(
"You can't use 'request_interactive_slack_approval' function in a standalone script or flow step preview. Please use it in a flow or a flow preview."
)
# Only include non-empty parameters
params = {}
if message:
params["message"] = message
if approver:
params["approver"] = approver
if slack_resource_path:
params["slack_resource_path"] = slack_resource_path
if channel_id:
params["channel_id"] = channel_id
if os.environ.get("WM_FLOW_STEP_ID"):
params["flow_step_id"] = os.environ.get("WM_FLOW_STEP_ID")
if default_args_json:
params["default_args_json"] = json.dumps(default_args_json)
if dynamic_enums_json:
params["dynamic_enums_json"] = json.dumps(dynamic_enums_json)
self.get(
f"/w/{workspace}/jobs/slack_approval/{os.environ.get('WM_JOB_ID', 'NO_JOB_ID')}",
params=params,
)
def username_to_email(self, username: str) -> str:
"""
Get email from workspace username
This method is particularly useful for apps that require the email address of the viewer.
Indeed, in the viewer context WM_USERNAME is set to the username of the viewer but WM_EMAIL is set to the email of the creator of the app.
"""
return self.get(f"/w/{self.workspace}/users/username_to_email/{username}").text
def send_teams_message(
self,
conversation_id: str,
text: str,
success: bool = True,
card_block: dict = None,
):
"""
Send a message to a Microsoft Teams conversation with conversation_id, where success is used to style the message
"""
return self.post(
f"/teams/activities",
json={
"conversation_id": conversation_id,
"text": text,
"success": success,
"card_block": card_block,
},
)
def datatable(self, name: str = "main"):
"""Get a DataTable client for SQL queries.
Args:
name: Database name (default: "main")
Returns:
DataTableClient instance
"""
return DataTableClient(self, name)
def ducklake(self, name: str = "main"):
"""Get a DuckLake client for DuckDB queries.
Args:
name: Database name (default: "main")
Returns:
DucklakeClient instance
"""
return DucklakeClient(self, name)
def init_global_client(f):
@functools.wraps(f)
def wrapper(*args, **kwargs):
global _client
if _client is None:
_client = Windmill()
return f(*args, **kwargs)
return wrapper
def deprecate(in_favor_of: str):
def decorator(f):
@functools.wraps(f)
def wrapper(*args, **kwargs):
warnings.warn(
(
f"The '{f.__name__}' method is deprecated and may be removed in the future. "
f"Consider {in_favor_of}"
),
DeprecationWarning,
)
return f(*args, **kwargs)
return wrapper
return decorator
@init_global_client
def get_workspace() -> str:
"""Get the current workspace ID.
Returns:
Workspace ID string
"""
return _client.workspace
@init_global_client
def get_root_job_id(job_id: str | None = None) -> str:
"""Get the root job ID for a flow hierarchy.
Args:
job_id: Job ID (defaults to current WM_JOB_ID)
Returns:
Root job ID
"""
return _client.get_root_job_id(job_id)
@init_global_client
@deprecate("Windmill().version")
def get_version() -> str:
return _client.version
@init_global_client
def run_script_async(
hash_or_path: str,
args: Dict[str, Any] = None,
scheduled_in_secs: int = None,
) -> str:
"""Create a script job and return its job ID.
Args:
hash_or_path: Script hash or path (determined by presence of '/')
args: Script arguments
scheduled_in_secs: Delay before execution in seconds
Returns:
Job ID string
"""
is_path = "/" in hash_or_path
hash_ = None if is_path else hash_or_path
path = hash_or_path if is_path else None
return _client.run_script_async(
hash_=hash_,
path=path,
args=args,
scheduled_in_secs=scheduled_in_secs,
)
@init_global_client
def run_flow_async(
path: str,
args: Dict[str, Any] = None,
scheduled_in_secs: int = None,
# can only be set to false if this the job will be fully await and not concurrent with any other job
# as otherwise the child flow and its own child will store their state in the parent job which will
# lead to incorrectness and failures
do_not_track_in_parent: bool = True,
) -> str:
"""Create a flow job and return its job ID.
Args:
path: Flow path
args: Flow arguments
scheduled_in_secs: Delay before execution in seconds
do_not_track_in_parent: Whether to track in parent job (default: True)
Returns:
Job ID string
"""
return _client.run_flow_async(
path=path,
args=args,
scheduled_in_secs=scheduled_in_secs,
do_not_track_in_parent=do_not_track_in_parent,
)
@init_global_client
def run_script_sync(
hash: str,
args: Dict[str, Any] = None,
verbose: bool = False,
assert_result_is_not_none: bool = True,
cleanup: bool = True,
timeout: dt.timedelta = None,
) -> Any:
"""Run a script synchronously by hash and return its result.
Args:
hash: Script hash
args: Script arguments
verbose: Enable verbose logging
assert_result_is_not_none: Raise exception if result is None
cleanup: Register cleanup handler to cancel job on exit
timeout: Maximum time to wait
Returns:
Script result
"""
return _client.run_script(
hash_=hash,
args=args,
verbose=verbose,
assert_result_is_not_none=assert_result_is_not_none,
cleanup=cleanup,
timeout=timeout,
)
@init_global_client
def run_script_by_path_async(
path: str,
args: Dict[str, Any] = None,
scheduled_in_secs: Union[None, int] = None,
) -> str:
"""Create a script job by path and return its job ID.
Args:
path: Script path
args: Script arguments
scheduled_in_secs: Delay before execution in seconds
Returns:
Job ID string
"""
return _client.run_script_by_path_async(
path=path,
args=args,
scheduled_in_secs=scheduled_in_secs,
)
@init_global_client
def run_script_by_hash_async(
hash_: str,
args: Dict[str, Any] = None,
scheduled_in_secs: Union[None, int] = None,
) -> str:
"""Create a script job by hash and return its job ID.
Args:
hash_: Script hash
args: Script arguments
scheduled_in_secs: Delay before execution in seconds
Returns:
Job ID string
"""
return _client.run_script_by_hash_async(
hash_=hash_,
args=args,
scheduled_in_secs=scheduled_in_secs,
)
@init_global_client
def run_script_by_path_sync(
path: str,
args: Dict[str, Any] = None,
verbose: bool = False,
assert_result_is_not_none: bool = True,
cleanup: bool = True,
timeout: dt.timedelta = None,
) -> Any:
"""Run a script synchronously by path and return its result.
Args:
path: Script path
args: Script arguments
verbose: Enable verbose logging
assert_result_is_not_none: Raise exception if result is None
cleanup: Register cleanup handler to cancel job on exit
timeout: Maximum time to wait
Returns:
Script result
"""
return _client.run_script(
path=path,
args=args,
verbose=verbose,
assert_result_is_not_none=assert_result_is_not_none,
cleanup=cleanup,
timeout=timeout,
)
@init_global_client
def get_id_token(audience: str) -> str:
"""
Get a JWT token for the given audience for OIDC purposes to login into third parties like AWS, Vault, GCP, etc.
"""
return _client.get_id_token(audience)
@init_global_client
def get_job_status(job_id: str) -> JobStatus:
"""Get the status of a job.
Args:
job_id: UUID of the job
Returns:
Job status: "RUNNING", "WAITING", or "COMPLETED"
"""
return _client.get_job_status(job_id)
@init_global_client
def get_job(job_id: str) -> dict:
"""Get full job details by ID.
Args:
job_id: UUID of the job
Returns:
Job details dictionary
"""
return _client.get_job(job_id=job_id)
@init_global_client
def get_result(job_id: str, assert_result_is_not_none=True) -> Dict[str, Any]:
"""Get the result of a completed job.
Args:
job_id: UUID of the completed job
assert_result_is_not_none: Raise exception if result is None
Returns:
Job result
"""
return _client.get_result(
job_id=job_id, assert_result_is_not_none=assert_result_is_not_none
)
@init_global_client
def duckdb_connection_settings(s3_resource_path: str = "") -> DuckDbConnectionSettings:
"""
Convenient helpers that takes an S3 resource as input and returns the settings necessary to
initiate an S3 connection from DuckDB
"""
return _client.get_duckdb_connection_settings(s3_resource_path)
@init_global_client
def polars_connection_settings(s3_resource_path: str = "") -> PolarsConnectionSettings:
"""
Convenient helpers that takes an S3 resource as input and returns the settings necessary to
initiate an S3 connection from Polars
"""
return _client.get_polars_connection_settings(s3_resource_path)
@init_global_client
def boto3_connection_settings(s3_resource_path: str = "") -> Boto3ConnectionSettings:
"""
Convenient helpers that takes an S3 resource as input and returns the settings necessary to
initiate an S3 connection using boto3
"""
return _client.get_boto3_connection_settings(s3_resource_path)
@init_global_client
def load_s3_file(s3object: S3Object | str, s3_resource_path: str | None = None) -> bytes:
"""
Load the entire content of a file stored in S3 as bytes
"""
return _client.load_s3_file(
s3object, s3_resource_path if s3_resource_path != "" else None
)
@init_global_client
def load_s3_file_reader(
s3object: S3Object | str, s3_resource_path: str | None = None
) -> BufferedReader:
"""
Load the content of a file stored in S3
"""
return _client.load_s3_file_reader(
s3object, s3_resource_path if s3_resource_path != "" else None
)
@init_global_client
def write_s3_file(
s3object: S3Object | str | None,
file_content: BufferedReader | bytes,
s3_resource_path: str | None = None,
content_type: str | None = None,
content_disposition: str | None = None,
) -> S3Object:
"""
Upload a file to S3
Content type will be automatically guessed from path extension if left empty
See MDN for content_disposition: https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/Content-Disposition
and content_type: https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/Content-Type
"""
return _client.write_s3_file(
s3object,
file_content,
s3_resource_path if s3_resource_path != "" else None,
content_type,
content_disposition,
)
@init_global_client
def delete_s3_object(
s3object: S3Object | str,
s3_resource_path: str | None = None,
) -> None:
"""
Permanently delete a file from the workspace S3 bucket.
"""
return _client.delete_s3_object(
s3object,
s3_resource_path if s3_resource_path != "" else None,
)
@init_global_client
def sign_s3_objects(s3_objects: list[S3Object | str]) -> list[S3Object]:
"""
Sign S3 objects to be used by anonymous users in public apps
Returns a list of signed s3 tokens
"""
return _client.sign_s3_objects(s3_objects)
@init_global_client
def sign_s3_object(s3_object: S3Object| str) -> S3Object:
"""
Sign S3 object to be used by anonymous users in public apps
Returns a signed s3 object
"""
return _client.sign_s3_object(s3_object)
@init_global_client
def get_presigned_s3_public_urls(
s3_objects: list[S3Object | str],
base_url: str | None = None,
) -> list[str]:
"""
Generate presigned public URLs for an array of S3 objects.
If an S3 object is not signed yet, it will be signed first.
Args:
s3_objects: List of S3 objects to sign
base_url: Optional base URL for the presigned URLs (defaults to WM_BASE_URL)
Returns:
List of signed public URLs
Example:
>>> import wmill
>>> from wmill import S3Object
>>> s3_objs = [S3Object(s3="/path/to/file1.txt"), S3Object(s3="/path/to/file2.txt")]
>>> urls = wmill.get_presigned_s3_public_urls(s3_objs)
"""
return _client.get_presigned_s3_public_urls(s3_objects, base_url)
@init_global_client
def get_presigned_s3_public_url(
s3_object: S3Object | str,
base_url: str | None = None,
) -> str:
"""
Generate a presigned public URL for an S3 object.
If the S3 object is not signed yet, it will be signed first.
Args:
s3_object: S3 object to sign
base_url: Optional base URL for the presigned URL (defaults to WM_BASE_URL)
Returns:
Signed public URL
Example:
>>> import wmill
>>> from wmill import S3Object
>>> s3_obj = S3Object(s3="/path/to/file.txt")
>>> url = wmill.get_presigned_s3_public_url(s3_obj)
"""
return _client.get_presigned_s3_public_url(s3_object, base_url)
@init_global_client
def whoami() -> dict:
"""
Returns the current user
"""
return _client.user
@init_global_client
def get_state(path: str | None = None) -> Any:
"""
Get the state
"""
return _client.get_state(path=path)
@init_global_client
def get_resource(
path: str,
none_if_undefined: bool = False,
interpolated: bool = True
) -> dict | None:
"""Get resource from Windmill"""
return _client.get_resource(path, none_if_undefined, interpolated)
@init_global_client
def set_resource(path: str, value: Any, resource_type: str = "any") -> None:
"""
Set the resource at a given path as a string, creating it if it does not exist
"""
return _client.set_resource(value=value, path=path, resource_type=resource_type)
@init_global_client
def list_resources(
resource_type: str = None,
page: int = None,
per_page: int = None,
) -> list[dict]:
"""List resources from Windmill workspace.
Args:
resource_type: Optional resource type to filter by (e.g., "postgresql", "mysql", "s3")
page: Optional page number for pagination
per_page: Optional number of results per page
Returns:
List of resource dictionaries
Example:
>>> # Get all resources
>>> all_resources = wmill.list_resources()
>>> # Get only PostgreSQL resources
>>> pg_resources = wmill.list_resources(resource_type="postgresql")
"""
return _client.list_resources(
resource_type=resource_type,
page=page,
per_page=per_page,
)
@init_global_client
def set_state(value: Any, path: str | None = None) -> None:
"""
Set the state
"""
return _client.set_state(value, path=path)
@init_global_client
def set_progress(value: int, job_id: Optional[str] = None) -> None:
"""
Set the progress
"""
return _client.set_progress(value, job_id)
@init_global_client
def get_progress(job_id: Optional[str] = None) -> Any:
"""
Get the progress
"""
return _client.get_progress(job_id)
def set_shared_state_pickle(value: Any, path="state.pickle") -> None:
"""
Set the state in the shared folder using pickle
"""
return Windmill.set_shared_state_pickle(value=value, path=path)
@deprecate("Windmill.get_shared_state_pickle(...)")
def get_shared_state_pickle(path="state.pickle") -> Any:
"""
Get the state in the shared folder using pickle
"""
return Windmill.get_shared_state_pickle(path=path)
def set_shared_state(value: Any, path="state.json") -> None:
"""
Set the state in the shared folder using pickle
"""
return Windmill.set_shared_state(value=value, path=path)
def get_shared_state(path="state.json") -> None:
"""
Get the state in the shared folder using pickle
"""
return Windmill.get_shared_state(path=path)
@init_global_client
def get_variable(path: str) -> str:
"""
Returns the variable at a given path as a string
"""
return _client.get_variable(path)
@init_global_client
def set_variable(path: str, value: str, is_secret: bool = False) -> None:
"""
Set the variable at a given path as a string, creating it if it does not exist
"""
return _client.set_variable(path, value, is_secret)
@init_global_client
def get_flow_user_state(key: str) -> Any:
"""
Get the user state of a flow at a given key
"""
return _client.get_flow_user_state(key)
@init_global_client
def set_flow_user_state(key: str, value: Any) -> None:
"""
Set the user state of a flow at a given key
"""
return _client.set_flow_user_state(key, value)
@init_global_client
def get_state_path() -> str:
"""Get the state resource path from environment.
Returns:
State path string
"""
return _client.state_path
@init_global_client
def get_resume_urls(approver: str = None, flow_level: bool = None) -> dict:
"""Get URLs needed for resuming a flow after suspension.
Args:
approver: Optional approver name
flow_level: If True, generate resume URLs for the parent flow instead of the
specific step. This allows pre-approvals that can be consumed by any later
suspend step in the same flow.
Returns:
Dictionary with approvalPage, resume, and cancel URLs
"""
return _client.get_resume_urls(approver, flow_level)
@init_global_client
def request_interactive_slack_approval(
slack_resource_path: str,
channel_id: str,
message: str = None,
approver: str = None,
default_args_json: dict = None,
dynamic_enums_json: dict = None,
) -> None:
return _client.request_interactive_slack_approval(
slack_resource_path=slack_resource_path,
channel_id=channel_id,
message=message,
approver=approver,
default_args_json=default_args_json,
dynamic_enums_json=dynamic_enums_json,
)
@init_global_client
def send_teams_message(
conversation_id: str, text: str, success: bool, card_block: dict = None
):
"""Send a message to a Microsoft Teams conversation.
Args:
conversation_id: Teams conversation ID
text: Message text
success: Whether to style as success message
card_block: Optional adaptive card block
Returns:
HTTP response from Teams
"""
return _client.send_teams_message(conversation_id, text, success, card_block)
@init_global_client
def cancel_job(job_id: str, reason: str = None) -> str:
"""Cancel a specific job by ID.
Args:
job_id: UUID of the job to cancel
reason: Optional reason for cancellation
Returns:
Response message from the cancel endpoint
"""
return _client.cancel_job(job_id, reason)
@init_global_client
def cancel_running() -> dict:
"""Cancel currently running executions of the same script."""
return _client.cancel_running()
@init_global_client
def run_script(
path: str = None,
hash_: str = None,
args: dict = None,
timeout: dt.timedelta | int | float = None,
verbose: bool = False,
cleanup: bool = True,
assert_result_is_not_none: bool = True,
) -> Any:
"""Run script synchronously and return its result.
.. deprecated:: Use run_script_by_path or run_script_by_hash instead.
"""
return _client.run_script(
path=path,
hash_=hash_,
args=args,
verbose=verbose,
assert_result_is_not_none=assert_result_is_not_none,
cleanup=cleanup,
timeout=timeout,
)
@init_global_client
def run_script_by_path(
path: str,
args: dict = None,
timeout: dt.timedelta | int | float = None,
verbose: bool = False,
cleanup: bool = True,
assert_result_is_not_none: bool = True,
) -> Any:
"""Run script by path synchronously and return its result."""
return _client.run_script_by_path(
path=path,
args=args,
verbose=verbose,
assert_result_is_not_none=assert_result_is_not_none,
cleanup=cleanup,
timeout=timeout,
)
@init_global_client
def run_script_by_hash(
hash_: str,
args: dict = None,
timeout: dt.timedelta | int | float = None,
verbose: bool = False,
cleanup: bool = True,
assert_result_is_not_none: bool = True,
) -> Any:
"""Run script by hash synchronously and return its result."""
return _client.run_script_by_hash(
hash_=hash_,
args=args,
verbose=verbose,
assert_result_is_not_none=assert_result_is_not_none,
cleanup=cleanup,
timeout=timeout,
)
@init_global_client
def run_inline_script_preview(
content: str,
language: str,
args: dict = None,
) -> Any:
"""Run a script on the current worker without creating a job"""
return _client.run_inline_script_preview(
content=content,
language=language,
args=args,
)
@init_global_client
def username_to_email(username: str) -> str:
"""
Get email from workspace username
This method is particularly useful for apps that require the email address of the viewer.
Indeed, in the viewer context WM_USERNAME is set to the username of the viewer but WM_EMAIL is set to the email of the creator of the app.
"""
return _client.username_to_email(username)
@init_global_client
def datatable(name: str = "main") -> DataTableClient:
"""Get a DataTable client for SQL queries.
Args:
name: Database name (default: "main")
Returns:
DataTableClient instance
"""
return _client.datatable(name)
@init_global_client
def ducklake(name: str = "main") -> DucklakeClient:
"""Get a DuckLake client for DuckDB queries.
Args:
name: Database name (default: "main")
Returns:
DucklakeClient instance
"""
return _client.ducklake(name)
def parse_resource_syntax(s: str) -> Optional[str]:
"""Parse resource syntax from string."""
if s is None:
return None
if s.startswith("$res:"):
return s[5:]
if s.startswith("res://"):
return s[6:]
return None
def parse_s3_object(s3_object: S3Object | str) -> S3Object:
"""Parse S3 object from string or S3Object format."""
if isinstance(s3_object, str):
match = re.match(r'^s3://([^/]*)/(.*)$', s3_object)
if match:
return S3Object(s3=match.group(2) or "", storage=match.group(1) or None)
return S3Object(s3="")
else:
return s3_object
def parse_variable_syntax(s: str) -> Optional[str]:
"""Parse variable syntax from string."""
if s.startswith("var://"):
return s[6:]
return None
def append_to_result_stream(text: str) -> None:
"""Append a text to the result stream.
Args:
text: text to append to the result stream
"""
print("WM_STREAM: {}".format(text.replace(chr(10), '\\n')))
def stream_result(stream) -> None:
"""Stream to the result stream.
Args:
stream: stream to stream to the result stream
"""
for text in stream:
append_to_result_stream(text)
class DataTableClient:
"""Client for executing SQL queries against Windmill DataTables."""
def __init__(self, client: Windmill, name: str):
"""Initialize DataTableClient.
Args:
client: Windmill client instance
name: DataTable name
"""
self.client = client
self.name, self.schema = parse_sql_client_name(name)
def query(self, sql: str, *args) -> SqlQuery:
"""Execute a SQL query against the DataTable.
Args:
sql: SQL query string with $1, $2, etc. placeholders
*args: Positional arguments to bind to query placeholders
Returns:
SqlQuery instance for fetching results
"""
if self.schema is not None:
sql = f'SET search_path TO "{self.schema}";\n' + sql
args_dict = {}
args_def = ""
for i, arg in enumerate(args):
args_dict[f"arg{i+1}"] = arg
args_def += f"-- ${i+1} arg{i+1} ({infer_sql_type(arg)})\n"
sql = args_def + sql
return SqlQuery(
sql,
lambda sql: self.client.run_inline_script_preview(
content=sql,
language="postgresql",
args={"database": f"datatable://{self.name}", **args_dict},
)
)
class DucklakeClient:
"""Client for executing DuckDB queries against Windmill DuckLake."""
def __init__(self, client: Windmill, name: str):
"""Initialize DucklakeClient.
Args:
client: Windmill client instance
name: DuckLake database name
"""
self.client = client
self.name = name
def query(self, sql: str, **kwargs):
"""Execute a DuckDB query against the DuckLake database.
Args:
sql: SQL query string with $name placeholders
**kwargs: Named arguments to bind to query placeholders
Returns:
SqlQuery instance for fetching results
"""
args_dict = {}
args_def = ""
for key, value in kwargs.items():
args_dict[key] = value
args_def += f"-- ${key} ({infer_sql_type(value)})\n"
attach = f"ATTACH 'ducklake://{self.name}' AS dl;USE dl;\n"
sql = args_def + attach + sql
return SqlQuery(
sql,
lambda sql: self.client.run_inline_script_preview(
content=sql,
language="duckdb",
args=args_dict,
)
)
class SqlQuery:
"""Query result handler for DataTable and DuckLake queries."""
def __init__(self, sql: str, fetch_fn):
"""Initialize SqlQuery.
Args:
sql: SQL query string
fetch_fn: Function to execute the query
"""
self.sql = sql
self.fetch_fn = fetch_fn
def fetch(self, result_collection: str | None = None):
"""Execute query and fetch results.
Args:
result_collection: Optional result collection mode
Returns:
Query results
"""
sql = self.sql
if result_collection is not None:
sql = f'-- result_collection={result_collection}\n{sql}'
return self.fetch_fn(sql)
def fetch_one(self):
"""Execute query and fetch first row of results.
Returns:
First row of query results
"""
return self.fetch(result_collection="last_statement_first_row")
def fetch_one_scalar(self):
"""Execute query and fetch first row of results. Return result as a scalar value.
Returns:
First row of query result as a scalar value
"""
return self.fetch(result_collection="last_statement_first_row_scalar")
def execute(self):
"""Execute query and don't return any results.
"""
self.fetch_one()
def infer_sql_type(value) -> str:
"""
DuckDB executor requires explicit argument types at declaration
These types exist in both DuckDB and Postgres
Check that the types exist if you plan to extend this function for other SQL engines.
"""
if isinstance(value, bool):
# Check bool before int since bool is a subclass of int in Python
return "BOOLEAN"
elif isinstance(value, int):
return "BIGINT"
elif isinstance(value, float):
return "FLOAT8"
elif value is None:
return "TEXT"
elif isinstance(value, str):
return "TEXT"
elif isinstance(value, dict) or isinstance(value, list):
return "JSON"
else:
return "TEXT"
def parse_sql_client_name(name: str) -> tuple[str, Optional[str]]:
name = name
schema = None
if ":" in name:
name, schema = name.split(":", 1)
if not name:
name = "main"
return name, schema
# ── Workflow-as-Code SDK ──────────────────────────────────────────────
import asyncio as _asyncio
import contextvars as _contextvars
class _StepSuspend(BaseException):
"""Raised to suspend workflow execution. Inherits from BaseException
so it is not caught by bare `except Exception:` blocks."""
def __init__(self, dispatch_info: dict):
self.dispatch_info = dispatch_info
class TaskError(Exception):
"""Raised when a WAC task step failed.
Attributes:
step_key: The checkpoint key of the failed step.
child_job_id: The UUID of the failed child job.
result: The error result from the child job.
"""
def __init__(self, message: str, *, step_key: str = "", child_job_id: str = "", result=None):
super().__init__(message)
self.step_key = step_key
self.child_job_id = child_job_id
self.result = result
_workflow_ctx: _contextvars.ContextVar["WorkflowCtx"] = _contextvars.ContextVar(
"_workflow_ctx"
)
class WorkflowCtx:
"""Internal context for workflow replay/suspension.
Not user-facing — set implicitly by ``@workflow`` via contextvars.
"""
def __init__(self, checkpoint: dict | None = None):
checkpoint = checkpoint or {}
self._completed: dict = checkpoint.get("completed_steps", {})
self._counters: dict[str, int] = {}
self._pending: list = []
self._executing_key: str | None = checkpoint.get("_executing_key")
def _alloc_key(self, name: str = "step") -> str:
"""Name-based key: ``double`` for first call, ``double_2``, ``double_3`` for subsequent."""
n = self._counters.get(name, 0) + 1
self._counters[name] = n
return name if n == 1 else f"{name}_{n}"
def _next_step(self, name: str, script: str, func=None, dispatch_type: str = "inline", _task_options: Optional[dict] = None, **kwargs):
"""Return an awaitable that either resolves from cache or suspends."""
key = self._alloc_key(name or script or "step")
if key in self._completed:
val = self._completed[key]
if isinstance(val, dict) and val.get("__wmill_error"):
raise TaskError(
val.get("message", f"Task '{name}' failed"),
step_key=val.get("step_key", ""),
child_job_id=val.get("child_job_id", ""),
result=val.get("result"),
)
return self._resolved(val)
if self._executing_key is not None:
if key == self._executing_key:
return self._execute_directly(func, **kwargs)
else:
return self._never_resolve()
info = {"name": name or key, "script": script or key, "args": kwargs, "key": key, "dispatch_type": dispatch_type}
if _task_options:
for opt_key in ("timeout", "tag", "cache_ttl", "priority", "concurrent_limit", "concurrency_key", "concurrency_time_window_s"):
if opt_key in _task_options and _task_options[opt_key] is not None:
info[opt_key] = _task_options[opt_key]
self._pending.append(info)
return self._suspend()
async def _resolved(self, value):
return value
async def _execute_directly(self, func, **kwargs):
result = func(**kwargs)
if _asyncio.iscoroutine(result):
result = await result
raise _StepSuspend({"mode": "step_complete", "steps": [], "result": result})
async def _never_resolve(self):
await _asyncio.Future()
async def _suspend(self):
steps = list(self._pending)
self._pending.clear()
raise _StepSuspend(
{
"mode": "parallel" if len(steps) > 1 else "sequential",
"steps": steps,
}
)
async def _wait_for_approval(
self, timeout: int = 1800, form: dict | None = None
):
key = self._alloc_key("approval")
if key in self._completed:
return self._completed[key]
if self._executing_key is not None:
await _asyncio.Future()
raise _StepSuspend({
"mode": "approval",
"key": key,
"timeout": timeout,
"form": form,
"steps": [],
})
async def _sleep(self, seconds: int):
key = self._alloc_key("sleep")
if key in self._completed:
return
if self._executing_key is not None:
await _asyncio.Future()
raise _StepSuspend({
"mode": "sleep",
"key": key,
"seconds": max(1, int(seconds)),
"steps": [],
})
async def _run_inline_step(self, name: str, fn):
key = self._alloc_key(name or "step")
if key in self._completed:
val = self._completed[key]
if isinstance(val, dict) and val.get("__wmill_error"):
raise TaskError(
val.get("message", f"Step '{name}' failed"),
step_key=val.get("step_key", ""),
child_job_id=val.get("child_job_id", ""),
result=val.get("result"),
)
return val
if self._executing_key is not None:
await _asyncio.Future()
result = fn()
if _asyncio.iscoroutine(result):
result = await result
raise _StepSuspend({
"mode": "inline_checkpoint",
"steps": [],
"key": key,
"result": result,
})
def task(
_func=None,
*,
path: Optional[str] = None,
tag: Optional[str] = None,
timeout: Optional[int] = None,
cache_ttl: Optional[int] = None,
priority: Optional[int] = None,
concurrency_limit: Optional[int] = None,
concurrency_key: Optional[str] = None,
concurrency_time_window_s: Optional[int] = None,
):
"""Decorator that marks a function as a workflow task.
Works in both WAC v1 (sync, HTTP-based dispatch) and WAC v2
(async, checkpoint/replay) modes:
- **v2 (inside @workflow)**: dispatches as a checkpoint step.
- **v1 (WM_JOB_ID set, no @workflow)**: dispatches via HTTP API.
- **Standalone**: executes the function body directly.
Usage::
@task
async def extract_data(url: str): ...
@task(path="f/external_script", timeout=600, tag="gpu")
async def run_external(x: int): ...
"""
from inspect import signature as _sig
_task_opts = {
"timeout": timeout,
"tag": tag,
"cache_ttl": cache_ttl,
"priority": priority,
"concurrent_limit": concurrency_limit,
"concurrency_key": concurrency_key,
"concurrency_time_window_s": concurrency_time_window_s,
}
# Remove None values
_task_opts = {k: v for k, v in _task_opts.items() if v is not None} or None
def decorator(func):
task_path = path
task_name = func.__name__
_params_list = list(_sig(func).parameters)
def _merge_args(args, kwargs):
merged = dict(kwargs)
for i, arg in enumerate(args):
if i < len(_params_list):
key = _params_list[i]
if key not in merged:
merged[key] = arg
else:
merged[f"arg{i}"] = arg
return merged
@functools.wraps(func)
def wrapper(*args, **kwargs):
# WAC v2: inside a @workflow context
ctx = _workflow_ctx.get(None)
if ctx is not None:
script = task_path if task_path else task_name
merged = _merge_args(args, kwargs)
return ctx._next_step(task_name, script, func, _task_options=_task_opts, **merged)
# WAC v1: running inside a Windmill job but not in a @workflow
if (
os.environ.get("WM_JOB_ID") is not None
and os.environ.get("MAIN_OVERRIDE") != func.__name__
):
global _client
if _client is None:
_client = Windmill()
w_id = os.environ.get("WM_WORKSPACE")
job_id = os.environ.get("WM_JOB_ID")
json_args = _merge_args(args, kwargs)
api_params = {}
if tag is not None:
api_params["tag"] = tag
resp = _client.post(
f"/w/{w_id}/jobs/run/workflow_as_code/{job_id}/{func.__name__}",
json={"args": json_args},
params=api_params,
)
child_job_id = resp.text
print(f"Executing task {func.__name__} on job {child_job_id}")
job_result = _client.wait_job(child_job_id)
print(f"Task {func.__name__} ({child_job_id}) completed")
return job_result
# Standalone — execute directly
return func(*args, **kwargs)
wrapper._is_task = True
wrapper._task_path = task_path
return wrapper
if _func is not None:
# @task without parentheses
return decorator(_func)
# @task() or @task(path="...", tag="...")
return decorator
def task_script(
path: str,
*,
timeout: Optional[int] = None,
tag: Optional[str] = None,
cache_ttl: Optional[int] = None,
priority: Optional[int] = None,
concurrency_limit: Optional[int] = None,
concurrency_key: Optional[str] = None,
concurrency_time_window_s: Optional[int] = None,
):
"""Create a task that dispatches to a separate Windmill script.
Usage::
extract = task_script("f/data/extract", timeout=600)
@workflow
async def main():
data = await extract(url="https://...")
"""
name = path.rsplit("/", 1)[-1]
_opts = {k: v for k, v in {"timeout": timeout, "tag": tag, "cache_ttl": cache_ttl, "priority": priority, "concurrent_limit": concurrency_limit, "concurrency_key": concurrency_key, "concurrency_time_window_s": concurrency_time_window_s}.items() if v is not None} or None
def wrapper(**kwargs):
ctx = _workflow_ctx.get(None)
if ctx is not None:
return ctx._next_step(name, path, dispatch_type="script", _task_options=_opts, **kwargs)
raise RuntimeError(f'task_script("{path}") can only be called inside a @workflow')
wrapper.__name__ = name
wrapper._is_task = True
wrapper._task_path = path
return wrapper
def task_flow(
path: str,
*,
timeout: Optional[int] = None,
tag: Optional[str] = None,
cache_ttl: Optional[int] = None,
priority: Optional[int] = None,
concurrency_limit: Optional[int] = None,
concurrency_key: Optional[str] = None,
concurrency_time_window_s: Optional[int] = None,
):
"""Create a task that dispatches to a separate Windmill flow.
Usage::
pipeline = task_flow("f/etl/pipeline", priority=10)
@workflow
async def main():
result = await pipeline(input=data)
"""
name = path.rsplit("/", 1)[-1]
_opts = {k: v for k, v in {"timeout": timeout, "tag": tag, "cache_ttl": cache_ttl, "priority": priority, "concurrent_limit": concurrency_limit, "concurrency_key": concurrency_key, "concurrency_time_window_s": concurrency_time_window_s}.items() if v is not None} or None
def wrapper(**kwargs):
ctx = _workflow_ctx.get(None)
if ctx is not None:
return ctx._next_step(name, path, dispatch_type="flow", _task_options=_opts, **kwargs)
raise RuntimeError(f'task_flow("{path}") can only be called inside a @workflow')
wrapper.__name__ = name
wrapper._is_task = True
wrapper._task_path = path
return wrapper
def workflow(func):
"""Decorator marking an async function as a workflow-as-code entry point.
The function must be **deterministic**: given the same inputs it must call
tasks in the same order on every replay. Branching on task results is fine
(results are replayed from checkpoint), but branching on external state
(current time, random values, external API calls) must use ``step()`` to
checkpoint the value so replays see the same result.
"""
func._is_workflow = True
return func
async def step(name: str, fn):
"""Execute ``fn`` inline and checkpoint the result.
On replay the cached value is returned without re-executing ``fn``.
Use for lightweight deterministic operations (timestamps, random IDs,
config reads) that should not incur the overhead of a child job.
"""
ctx: WorkflowCtx | None = _workflow_ctx.get(None)
if ctx is not None:
return await ctx._run_inline_step(name, fn)
result = fn()
if _asyncio.iscoroutine(result):
result = await result
return result
async def sleep(seconds: int):
"""Server-side sleep — suspend the workflow for the given duration without holding a worker.
Inside a @workflow, the parent job suspends and auto-resumes after ``seconds``.
Outside a workflow, falls back to ``asyncio.sleep``.
"""
ctx: WorkflowCtx | None = _workflow_ctx.get(None)
if ctx is not None:
return await ctx._sleep(seconds)
await _asyncio.sleep(seconds)
async def wait_for_approval(
timeout: int = 1800,
form: dict | None = None,
) -> dict:
"""Suspend the workflow and wait for an external approval.
Use ``get_resume_urls()`` (wrapped in ``step()``) to obtain
resume/cancel/approval URLs before calling this function.
Returns a dict with ``value`` (form data), ``approver``, and ``approved``.
Example::
urls = await step("urls", lambda: get_resume_urls())
await step("notify", lambda: send_email(urls["approvalPage"]))
result = await wait_for_approval(timeout=3600)
"""
ctx: WorkflowCtx | None = _workflow_ctx.get(None)
if ctx is not None:
return await ctx._wait_for_approval(timeout=timeout, form=form)
raise RuntimeError("wait_for_approval can only be called inside a @workflow")
async def parallel(items, fn, *, concurrency: Optional[int] = None):
"""Process items in parallel with optional concurrency control.
Each item is processed by calling ``fn(item)``, which should be a @task.
Items are dispatched in batches of ``concurrency`` (default: all at once).
Example::
@task
async def process(item: str):
...
results = await parallel(items, process, concurrency=5)
"""
if not items:
return []
batch_size = concurrency if concurrency and concurrency > 0 else len(items)
results = []
for i in range(0, len(items), batch_size):
batch = items[i : i + batch_size]
batch_results = await _asyncio.gather(*(fn(item) for item in batch))
results.extend(batch_results)
return results
async def _run_workflow_async(func, checkpoint: dict, input_args: dict):
ctx = WorkflowCtx(checkpoint)
token = _workflow_ctx.set(ctx)
try:
result = await func(**input_args)
# Flush any unawaited tasks (e.g. forgotten await on last statement)
if ctx._pending:
steps = list(ctx._pending)
ctx._pending.clear()
return {
"type": "dispatch",
"mode": "parallel" if len(steps) > 1 else "sequential",
"steps": steps,
}
return {"type": "complete", "result": result}
except _StepSuspend as e:
info = e.dispatch_info
mode = info.get("mode")
if mode == "step_complete":
return {"type": "complete", "result": info.get("result")}
if mode == "inline_checkpoint":
return {
"type": "inline_checkpoint",
"key": info["key"],
"result": info.get("result"),
}
if mode == "approval":
return {
"type": "approval",
"key": info["key"],
"timeout": info.get("timeout"),
"form": info.get("form"),
}
if mode == "sleep":
return {
"type": "sleep",
"key": info["key"],
"seconds": info.get("seconds"),
}
return {"type": "dispatch", **info}
finally:
_workflow_ctx.reset(token)
def _run_workflow(func, checkpoint: dict, input_args: dict):
"""Synchronous wrapper that runs the workflow coroutine to completion
or until it suspends."""
return _asyncio.run(_run_workflow_async(func, checkpoint, input_args))