id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
4,275 | from promptflow._sdk._configuration import Configuration
PRIVACY_STATEMENT = """
Welcome to prompt flow!
---------------------
Use `pf -h` to see available commands or go to https://aka.ms/pf-cli.
Telemetry
---------
The prompt flow CLI collects usage data in order to improve your experience.
The data is anonymous and does not include commandline argument values.
The data is collected by Microsoft.
You can change your telemetry settings with `pf config`.
"""
def show_privacy_statement():
config = Configuration.get_instance()
ran_before = config.get_config("first_run")
if not ran_before:
print(PRIVACY_STATEMENT)
config.set_config("first_run", True) | null |
4,276 | from promptflow._sdk._configuration import Configuration
WELCOME_MESSAGE = r"""
____ _ __ _
| _ \ _ __ ___ _ __ ___ _ __ | |_ / _| | _____ __
| |_) | '__/ _ \| '_ ` _ \| '_ \| __| | |_| |/ _ \ \ /\ / /
| __/| | | (_) | | | | | | |_) | |_ | _| | (_) \ V V /
|_| |_| \___/|_| |_| |_| .__/ \__| |_| |_|\___/ \_/\_/
|_|
Welcome to the cool prompt flow CLI!
Use `pf --version` to display the current version.
Here are the base commands:
"""
def show_welcome_message():
print(WELCOME_MESSAGE) | null |
4,277 | import json
import time
from promptflow._cli._pf._experiment import add_experiment_parser, dispatch_experiment_commands
from promptflow._cli._utils import _get_cli_activity_name, cli_exception_and_telemetry_handler
from promptflow._sdk._configuration import Configuration
from promptflow._sdk._telemetry.activity import update_activity_name
import argparse
import logging
import sys
from promptflow._cli._pf._config import add_config_parser, dispatch_config_commands
from promptflow._cli._pf._connection import add_connection_parser, dispatch_connection_commands
from promptflow._cli._pf._flow import add_flow_parser, dispatch_flow_commands
from promptflow._cli._pf._run import add_run_parser, dispatch_run_commands
from promptflow._cli._pf._tool import add_tool_parser, dispatch_tool_commands
from promptflow._cli._pf.help import show_privacy_statement, show_welcome_message
from promptflow._cli._pf._upgrade import add_upgrade_parser, upgrade_version
from promptflow._cli._user_agent import USER_AGENT
from promptflow._sdk._utils import ( # noqa: E402
get_promptflow_sdk_version,
print_pf_version,
setup_user_agent_to_operation_context,
)
from promptflow._utils.logger_utils import get_cli_sdk_logger
def run_command(args):
# Log the init finish time
init_finish_time = time.perf_counter()
try:
# --verbose, enable info logging
if hasattr(args, "verbose") and args.verbose:
for handler in logger.handlers:
handler.setLevel(logging.INFO)
# --debug, enable debug logging
if hasattr(args, "debug") and args.debug:
for handler in logger.handlers:
handler.setLevel(logging.DEBUG)
if args.version:
print_pf_version()
elif args.action == "flow":
dispatch_flow_commands(args)
elif args.action == "connection":
dispatch_connection_commands(args)
elif args.action == "run":
dispatch_run_commands(args)
elif args.action == "config":
dispatch_config_commands(args)
elif args.action == "tool":
dispatch_tool_commands(args)
elif args.action == "upgrade":
upgrade_version(args)
elif args.action == "experiment":
dispatch_experiment_commands(args)
except KeyboardInterrupt as ex:
logger.debug("Keyboard interrupt is captured.")
raise ex
except SystemExit as ex: # some code directly call sys.exit, this is to make sure command metadata is logged
exit_code = ex.code if ex.code is not None else 1
logger.debug(f"Code directly call sys.exit with code {exit_code}")
raise ex
except Exception as ex:
logger.debug(f"Command {args} execute failed. {str(ex)}")
raise ex
finally:
# Log the invoke finish time
invoke_finish_time = time.perf_counter()
logger.info(
"Command ran in %.3f seconds (init: %.3f, invoke: %.3f)",
invoke_finish_time - start_time,
init_finish_time - start_time,
invoke_finish_time - init_finish_time,
)
def get_parser_args(argv):
parser = argparse.ArgumentParser(
prog="pf",
formatter_class=argparse.RawDescriptionHelpFormatter,
description="pf: manage prompt flow assets. Learn more: https://microsoft.github.io/promptflow.",
)
parser.add_argument(
"-v", "--version", dest="version", action="store_true", help="show current CLI version and exit"
)
subparsers = parser.add_subparsers()
add_upgrade_parser(subparsers)
add_flow_parser(subparsers)
add_connection_parser(subparsers)
add_run_parser(subparsers)
add_config_parser(subparsers)
add_tool_parser(subparsers)
if Configuration.get_instance().is_internal_features_enabled():
add_experiment_parser(subparsers)
return parser.prog, parser.parse_args(argv)
The provided code snippet includes necessary dependencies for implementing the `entry` function. Write a Python function `def entry(argv)` to solve the following problem:
Control plane CLI tools for promptflow.
Here is the function:
def entry(argv):
"""
Control plane CLI tools for promptflow.
"""
prog, args = get_parser_args(argv)
if hasattr(args, "user_agent"):
setup_user_agent_to_operation_context(args.user_agent)
activity_name = _get_cli_activity_name(cli=prog, args=args)
activity_name = update_activity_name(activity_name, args=args)
cli_exception_and_telemetry_handler(run_command, activity_name)(args) | Control plane CLI tools for promptflow. |
4,278 | import os
from promptflow._cli._params import add_param_yes, base_params
from promptflow._cli._utils import activate_action, get_cli_sdk_logger
from promptflow._utils.utils import prompt_y_n
from promptflow.exceptions import UserErrorException
The provided code snippet includes necessary dependencies for implementing the `add_upgrade_parser` function. Write a Python function `def add_upgrade_parser(subparsers)` to solve the following problem:
Add upgrade parser to the pf subparsers.
Here is the function:
def add_upgrade_parser(subparsers):
"""Add upgrade parser to the pf subparsers."""
epilog = """
Examples:
# Upgrade prompt flow without prompt and run non-interactively:
pf upgrade --yes
""" # noqa: E501
add_params = [
add_param_yes,
] + base_params
activate_action(
name="upgrade",
description="Upgrade prompt flow CLI.",
epilog=epilog,
add_params=add_params,
subparsers=subparsers,
help_message="pf upgrade",
action_param_name="action",
) | Add upgrade parser to the pf subparsers. |
4,279 | import os
from promptflow._cli._params import add_param_yes, base_params
from promptflow._cli._utils import activate_action, get_cli_sdk_logger
from promptflow._utils.utils import prompt_y_n
from promptflow.exceptions import UserErrorException
logger = get_cli_sdk_logger()
UPGRADE_MSG = "Not able to upgrade automatically"
def _upgrade_on_windows(yes):
"""Download MSI to a temp folder and install it with msiexec.exe.
Directly installing from URL may be blocked by policy: https://github.com/Azure/azure-cli/issues/19171
This also gives the user a chance to manually install the MSI in case of msiexec.exe failure.
"""
import subprocess
import sys
import tempfile
msi_url = "https://aka.ms/installpromptflowwindowsx64"
logger.warning("Updating prompt flow CLI with MSI from %s", msi_url)
# Save MSI to ~\AppData\Local\Temp\promptflow-msi, clean up the folder first
msi_dir = os.path.join(tempfile.gettempdir(), "promptflow-msi")
try:
import shutil
shutil.rmtree(msi_dir)
except FileNotFoundError:
# The folder has already been deleted. No further retry is needed.
# errno: 2, winerror: 3, strerror: 'The system cannot find the path specified'
pass
except OSError as err:
logger.warning("Failed to delete '%s': %s. You may try to delete it manually.", msi_dir, err)
os.makedirs(msi_dir, exist_ok=True)
msi_path = _download_from_url(msi_url, msi_dir)
if yes:
subprocess.Popen(["msiexec.exe", "/i", msi_path, "/qn"])
else:
subprocess.call(["msiexec.exe", "/i", msi_path])
logger.warning("Installation started. Please complete the upgrade in the opened window.")
sys.exit(0)
def upgrade_version(args):
import platform
import subprocess
import sys
from packaging.version import parse
from promptflow._constants import _ENV_PF_INSTALLER, CLI_PACKAGE_NAME
from promptflow._utils.version_hint_utils import get_latest_version
from promptflow._version import VERSION as local_version
installer = os.getenv(_ENV_PF_INSTALLER) or ""
installer = installer.upper()
print(f"installer: {installer}")
latest_version = get_latest_version(CLI_PACKAGE_NAME, installer=installer)
if not latest_version:
logger.warning("Failed to get the latest prompt flow version.")
return
elif parse(latest_version) <= parse(local_version):
logger.warning("You already have the latest prompt flow version: %s", local_version)
return
yes = args.yes
exit_code = 0
latest_version_msg = (
"Upgrading prompt flow CLI version to {}.".format(latest_version)
if yes
else "Latest version available is {}.".format(latest_version)
)
logger.warning("Your current prompt flow CLI version is %s. %s", local_version, latest_version_msg)
if not yes:
logger.warning("Please check the release notes first")
if not sys.stdin.isatty():
logger.debug("No tty available.")
raise UserErrorException("No tty available. Please run command with --yes.")
confirmation = prompt_y_n("Do you want to continue?", default="y")
if not confirmation:
logger.debug("Upgrade stopped by user")
return
if installer == "MSI":
_upgrade_on_windows(yes)
elif installer == "PIP":
pip_args = [
sys.executable,
"-m",
"pip",
"install",
"--upgrade",
"promptflow[azure,executable,azureml-serving,executor-service]",
"-vv",
"--disable-pip-version-check",
"--no-cache-dir",
]
logger.debug("Update prompt flow with '%s'", " ".join(pip_args))
exit_code = subprocess.call(pip_args, shell=platform.system() == "Windows")
elif installer == "SCRIPT":
command = "curl https://promptflowartifact.blob.core.windows.net/linux-install-scripts/install | bash"
logger.warning(f"{UPGRADE_MSG}, you can try to run {command} in your terminal directly to upgrade package.")
return
else:
logger.warning(UPGRADE_MSG)
return
if exit_code:
err_msg = "CLI upgrade failed."
logger.warning(err_msg)
sys.exit(exit_code)
import importlib
import json
importlib.reload(subprocess)
importlib.reload(json)
version_result = subprocess.check_output(["pf", "version"], shell=platform.system() == "Windows")
version_json = json.loads(version_result)
new_version = version_json["promptflow"]
if new_version == local_version:
err_msg = f"CLI upgrade to version {latest_version} failed or aborted."
logger.warning(err_msg)
sys.exit(1)
logger.warning("Upgrade finished.") | null |
4,280 | import jwt
from promptflow.exceptions import ValidationException
def is_arm_id(obj) -> bool:
return isinstance(obj, str) and obj.startswith("azureml://") | null |
4,281 | import jwt
from promptflow.exceptions import ValidationException
def get_token(credential, resource) -> str:
from azure.ai.ml._azure_environments import _resource_to_scopes
azure_ml_scopes = _resource_to_scopes(resource)
token = credential.get_token(*azure_ml_scopes).token
# validate token has aml audience
decoded_token = jwt.decode(
token,
options={"verify_signature": False, "verify_aud": False},
)
if decoded_token.get("aud") != resource:
msg = """AAD token with aml scope could not be fetched using the credentials being used.
Please validate if token with {0} scope can be fetched using credentials provided to PFClient.
Token with {0} scope can be fetched using credentials.get_token({0})
"""
raise ValidationException(
message=msg.format(*azure_ml_scopes),
)
return token
def get_aml_token(credential) -> str:
from azure.ai.ml._azure_environments import _get_aml_resource_id_from_metadata
resource = _get_aml_resource_id_from_metadata()
return get_token(credential, resource) | null |
4,282 | import jwt
from promptflow.exceptions import ValidationException
def get_arm_token(credential) -> str:
from azure.ai.ml._azure_environments import _get_base_url_from_metadata
resource = _get_base_url_from_metadata()
return get_token(credential, resource)
def get_authorization(credential=None) -> str:
token = get_arm_token(credential=credential)
return "Bearer " + token | null |
4,283 | import jwt
from promptflow.exceptions import ValidationException
def get_arm_token(credential) -> str:
from azure.ai.ml._azure_environments import _get_base_url_from_metadata
resource = _get_base_url_from_metadata()
return get_token(credential, resource)
def get_user_alias_from_credential(credential):
token = get_arm_token(credential=credential)
decode_json = jwt.decode(token, options={"verify_signature": False, "verify_aud": False})
try:
email = decode_json.get("upn", decode_json.get("email", None))
return email.split("@")[0]
except Exception:
# use oid when failed to get upn, e.g. service principal
return decode_json["oid"] | null |
4,284 | import asyncio
import contextvars
import functools
import json
from pathlib import Path
from typing import Optional, Union
import httpx
from azure.core.exceptions import HttpResponseError
from azure.storage.blob.aio import BlobServiceClient
from promptflow._sdk._constants import DEFAULT_ENCODING, DownloadedRun
from promptflow._sdk._errors import DownloadInternalError, RunNotFoundError, RunOperationError
from promptflow._sdk.entities import Run
from promptflow._utils.logger_utils import get_cli_sdk_logger
from promptflow.exceptions import UserErrorException
async def to_thread(func, /, *args, **kwargs):
# this is copied from asyncio.to_thread() in Python 3.9
# as it is not available in Python 3.8, which is the minimum supported version of promptflow
loop = asyncio.get_running_loop()
ctx = contextvars.copy_context()
func_call = functools.partial(ctx.run, func, *args, **kwargs)
return await loop.run_in_executor(None, func_call) | null |
4,285 | from typing import Any, Dict, Union
import requests
from azure.ai.ml._scope_dependent_operations import (
OperationConfig,
OperationsContainer,
OperationScope,
_ScopeDependentOperations,
)
from azure.core.exceptions import ClientAuthenticationError
from promptflow._constants import ConnectionAuthMode
from promptflow._sdk.entities._connection import CustomConnection, _Connection
from promptflow._utils.retry_utils import http_retry_wrapper
from promptflow.azure._models._models import WorkspaceConnectionPropertiesV2BasicResource
from promptflow.azure._restclient.flow_service_caller import FlowServiceCaller
from promptflow.azure._utils.general import get_arm_token
from promptflow.exceptions import ErrorTarget, SystemErrorException, UserErrorException
def get_case_insensitive_key(d, key, default=None):
for k, v in d.items():
if k.lower() == key.lower():
return v
return default | null |
4,286 | import os
import uuid
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, Optional, TypeVar, Union
from azure.ai.ml._artifacts._blob_storage_helper import BlobStorageClient
from azure.ai.ml._artifacts._gen2_storage_helper import Gen2StorageClient
from azure.ai.ml._azure_environments import _get_storage_endpoint_from_metadata
from azure.ai.ml._restclient.v2022_10_01.models import DatastoreType
from azure.ai.ml._scope_dependent_operations import OperationScope
from azure.ai.ml._utils._arm_id_utils import (
AMLNamedArmId,
get_resource_name_from_arm_id,
is_ARM_id_for_resource,
remove_aml_prefix,
)
from azure.ai.ml._utils._asset_utils import (
IgnoreFile,
_build_metadata_dict,
_validate_path,
get_ignore_file,
get_object_hash,
)
from azure.ai.ml._utils._storage_utils import (
AzureMLDatastorePathUri,
get_artifact_path_from_storage_url,
get_storage_client,
)
from azure.ai.ml.constants._common import SHORT_URI_FORMAT, STORAGE_ACCOUNT_URLS
from azure.ai.ml.entities import Environment
from azure.ai.ml.entities._assets._artifacts.artifact import Artifact, ArtifactStorageInfo
from azure.ai.ml.entities._credentials import AccountKeyConfiguration
from azure.ai.ml.entities._datastore._constants import WORKSPACE_BLOB_STORE
from azure.ai.ml.exceptions import ErrorTarget, ValidationException
from azure.ai.ml.operations._datastore_operations import DatastoreOperations
from azure.storage.blob import BlobSasPermissions, generate_blob_sas
from azure.storage.filedatalake import FileSasPermissions, generate_file_sas
from ..._utils.logger_utils import LoggerFactory
from ._fileshare_storeage_helper import FlowFileStorageClient
The provided code snippet includes necessary dependencies for implementing the `list_logs_in_datastore` function. Write a Python function `def list_logs_in_datastore(ds_info: Dict[str, str], prefix: str, legacy_log_folder_name: str) -> Dict[str, str]` to solve the following problem:
Returns a dictionary of file name to blob or data lake uri with SAS token, matching the structure of RunDetails.logFiles. legacy_log_folder_name: the name of the folder in the datastore that contains the logs /azureml-logs/*.txt is the legacy log structure for commandJob and sweepJob /logs/azureml/*.txt is the legacy log structure for pipeline parent Job
Here is the function:
def list_logs_in_datastore(ds_info: Dict[str, str], prefix: str, legacy_log_folder_name: str) -> Dict[str, str]:
"""Returns a dictionary of file name to blob or data lake uri with SAS token, matching the structure of
RunDetails.logFiles.
legacy_log_folder_name: the name of the folder in the datastore that contains the logs
/azureml-logs/*.txt is the legacy log structure for commandJob and sweepJob
/logs/azureml/*.txt is the legacy log structure for pipeline parent Job
"""
if ds_info["storage_type"] not in [
DatastoreType.AZURE_BLOB,
DatastoreType.AZURE_DATA_LAKE_GEN2,
]:
raise Exception("Only Blob and Azure DataLake Storage Gen2 datastores are supported.")
storage_client = get_storage_client(
credential=ds_info["credential"],
container_name=ds_info["container_name"],
storage_account=ds_info["storage_account"],
storage_type=ds_info["storage_type"],
)
items = storage_client.list(starts_with=prefix + "/user_logs/")
# Append legacy log files if present
items.extend(storage_client.list(starts_with=prefix + legacy_log_folder_name))
log_dict = {}
for item_name in items:
sub_name = item_name.split(prefix + "/")[1]
if isinstance(storage_client, BlobStorageClient):
token = generate_blob_sas(
account_name=ds_info["storage_account"],
container_name=ds_info["container_name"],
blob_name=item_name,
account_key=ds_info["credential"],
permission=BlobSasPermissions(read=True),
expiry=datetime.utcnow() + timedelta(minutes=30),
)
elif isinstance(storage_client, Gen2StorageClient):
token = generate_file_sas( # pylint: disable=no-value-for-parameter
account_name=ds_info["storage_account"],
file_system_name=ds_info["container_name"],
file_name=item_name,
credential=ds_info["credential"],
permission=FileSasPermissions(read=True),
expiry=datetime.utcnow() + timedelta(minutes=30),
)
log_dict[sub_name] = "{}/{}/{}?{}".format(ds_info["account_url"], ds_info["container_name"], item_name, token)
return log_dict | Returns a dictionary of file name to blob or data lake uri with SAS token, matching the structure of RunDetails.logFiles. legacy_log_folder_name: the name of the folder in the datastore that contains the logs /azureml-logs/*.txt is the legacy log structure for commandJob and sweepJob /logs/azureml/*.txt is the legacy log structure for pipeline parent Job |
4,287 | import os
import uuid
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, Optional, TypeVar, Union
from azure.ai.ml._artifacts._blob_storage_helper import BlobStorageClient
from azure.ai.ml._artifacts._gen2_storage_helper import Gen2StorageClient
from azure.ai.ml._azure_environments import _get_storage_endpoint_from_metadata
from azure.ai.ml._restclient.v2022_10_01.models import DatastoreType
from azure.ai.ml._scope_dependent_operations import OperationScope
from azure.ai.ml._utils._arm_id_utils import (
AMLNamedArmId,
get_resource_name_from_arm_id,
is_ARM_id_for_resource,
remove_aml_prefix,
)
from azure.ai.ml._utils._asset_utils import (
IgnoreFile,
_build_metadata_dict,
_validate_path,
get_ignore_file,
get_object_hash,
)
from azure.ai.ml._utils._storage_utils import (
AzureMLDatastorePathUri,
get_artifact_path_from_storage_url,
get_storage_client,
)
from azure.ai.ml.constants._common import SHORT_URI_FORMAT, STORAGE_ACCOUNT_URLS
from azure.ai.ml.entities import Environment
from azure.ai.ml.entities._assets._artifacts.artifact import Artifact, ArtifactStorageInfo
from azure.ai.ml.entities._credentials import AccountKeyConfiguration
from azure.ai.ml.entities._datastore._constants import WORKSPACE_BLOB_STORE
from azure.ai.ml.exceptions import ErrorTarget, ValidationException
from azure.ai.ml.operations._datastore_operations import DatastoreOperations
from azure.storage.blob import BlobSasPermissions, generate_blob_sas
from azure.storage.filedatalake import FileSasPermissions, generate_file_sas
from ..._utils.logger_utils import LoggerFactory
from ._fileshare_storeage_helper import FlowFileStorageClient
def get_datastore_info(operations: DatastoreOperations, name: str) -> Dict[str, str]:
"""Get datastore account, type, and auth information."""
datastore_info = {}
if name:
datastore = operations.get(name, include_secrets=True)
else:
datastore = operations.get_default(include_secrets=True)
storage_endpoint = _get_storage_endpoint_from_metadata()
credentials = datastore.credentials
datastore_info["storage_type"] = datastore.type
datastore_info["storage_account"] = datastore.account_name
datastore_info["account_url"] = STORAGE_ACCOUNT_URLS[datastore.type].format(
datastore.account_name, storage_endpoint
)
if isinstance(credentials, AccountKeyConfiguration):
datastore_info["credential"] = credentials.account_key
else:
try:
datastore_info["credential"] = credentials.sas_token
except Exception as e: # pylint: disable=broad-except
if not hasattr(credentials, "sas_token"):
datastore_info["credential"] = operations._credential
else:
raise e
if datastore.type == DatastoreType.AZURE_BLOB:
datastore_info["container_name"] = str(datastore.container_name)
elif datastore.type == DatastoreType.AZURE_DATA_LAKE_GEN2:
datastore_info["container_name"] = str(datastore.filesystem)
elif datastore.type == DatastoreType.AZURE_FILE:
datastore_info["container_name"] = str(datastore.file_share_name)
else:
raise Exception(
f"Datastore type {datastore.type} is not supported for uploads. "
f"Supported types are {DatastoreType.AZURE_BLOB} and {DatastoreType.AZURE_DATA_LAKE_GEN2}."
)
return datastore_info
def _get_default_datastore_info(datastore_operation):
return get_datastore_info(datastore_operation, None) | null |
4,288 | import os
import uuid
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, Optional, TypeVar, Union
from azure.ai.ml._artifacts._blob_storage_helper import BlobStorageClient
from azure.ai.ml._artifacts._gen2_storage_helper import Gen2StorageClient
from azure.ai.ml._azure_environments import _get_storage_endpoint_from_metadata
from azure.ai.ml._restclient.v2022_10_01.models import DatastoreType
from azure.ai.ml._scope_dependent_operations import OperationScope
from azure.ai.ml._utils._arm_id_utils import (
AMLNamedArmId,
get_resource_name_from_arm_id,
is_ARM_id_for_resource,
remove_aml_prefix,
)
from azure.ai.ml._utils._asset_utils import (
IgnoreFile,
_build_metadata_dict,
_validate_path,
get_ignore_file,
get_object_hash,
)
from azure.ai.ml._utils._storage_utils import (
AzureMLDatastorePathUri,
get_artifact_path_from_storage_url,
get_storage_client,
)
from azure.ai.ml.constants._common import SHORT_URI_FORMAT, STORAGE_ACCOUNT_URLS
from azure.ai.ml.entities import Environment
from azure.ai.ml.entities._assets._artifacts.artifact import Artifact, ArtifactStorageInfo
from azure.ai.ml.entities._credentials import AccountKeyConfiguration
from azure.ai.ml.entities._datastore._constants import WORKSPACE_BLOB_STORE
from azure.ai.ml.exceptions import ErrorTarget, ValidationException
from azure.ai.ml.operations._datastore_operations import DatastoreOperations
from azure.storage.blob import BlobSasPermissions, generate_blob_sas
from azure.storage.filedatalake import FileSasPermissions, generate_file_sas
from ..._utils.logger_utils import LoggerFactory
from ._fileshare_storeage_helper import FlowFileStorageClient
def _get_datastore_name(*, datastore_name: Optional[str] = WORKSPACE_BLOB_STORE) -> str:
datastore_name = WORKSPACE_BLOB_STORE if not datastore_name else datastore_name
try:
datastore_name = get_resource_name_from_arm_id(datastore_name)
except (ValueError, AttributeError, ValidationException):
module_logger.debug("datastore_name %s is not a full arm id. Proceed with a shortened name.\n", datastore_name)
datastore_name = remove_aml_prefix(datastore_name)
if is_ARM_id_for_resource(datastore_name):
datastore_name = get_resource_name_from_arm_id(datastore_name)
return datastore_name
def get_datastore_info(operations: DatastoreOperations, name: str) -> Dict[str, str]:
"""Get datastore account, type, and auth information."""
datastore_info = {}
if name:
datastore = operations.get(name, include_secrets=True)
else:
datastore = operations.get_default(include_secrets=True)
storage_endpoint = _get_storage_endpoint_from_metadata()
credentials = datastore.credentials
datastore_info["storage_type"] = datastore.type
datastore_info["storage_account"] = datastore.account_name
datastore_info["account_url"] = STORAGE_ACCOUNT_URLS[datastore.type].format(
datastore.account_name, storage_endpoint
)
if isinstance(credentials, AccountKeyConfiguration):
datastore_info["credential"] = credentials.account_key
else:
try:
datastore_info["credential"] = credentials.sas_token
except Exception as e: # pylint: disable=broad-except
if not hasattr(credentials, "sas_token"):
datastore_info["credential"] = operations._credential
else:
raise e
if datastore.type == DatastoreType.AZURE_BLOB:
datastore_info["container_name"] = str(datastore.container_name)
elif datastore.type == DatastoreType.AZURE_DATA_LAKE_GEN2:
datastore_info["container_name"] = str(datastore.filesystem)
elif datastore.type == DatastoreType.AZURE_FILE:
datastore_info["container_name"] = str(datastore.file_share_name)
else:
raise Exception(
f"Datastore type {datastore.type} is not supported for uploads. "
f"Supported types are {DatastoreType.AZURE_BLOB} and {DatastoreType.AZURE_DATA_LAKE_GEN2}."
)
return datastore_info
def download_artifact(
starts_with: Union[str, os.PathLike],
destination: str,
datastore_operation: DatastoreOperations,
datastore_name: Optional[str],
datastore_info: Optional[Dict] = None,
) -> str:
"""Download datastore path to local file or directory.
:param Union[str, os.PathLike] starts_with: Prefix of blobs to download
:param str destination: Path that files will be written to
:param DatastoreOperations datastore_operation: Datastore operations
:param Optional[str] datastore_name: name of datastore
:param Dict datastore_info: the return value of invoking get_datastore_info
:return str: Path that files were written to
"""
starts_with = starts_with.as_posix() if isinstance(starts_with, Path) else starts_with
datastore_name = _get_datastore_name(datastore_name=datastore_name)
if datastore_info is None:
datastore_info = get_datastore_info(datastore_operation, datastore_name)
storage_client = get_storage_client(**datastore_info)
storage_client.download(starts_with=starts_with, destination=destination)
return destination
The provided code snippet includes necessary dependencies for implementing the `download_artifact_from_storage_url` function. Write a Python function `def download_artifact_from_storage_url( blob_url: str, destination: str, datastore_operation: DatastoreOperations, datastore_name: Optional[str], ) -> str` to solve the following problem:
Download datastore blob URL to local file or directory.
Here is the function:
def download_artifact_from_storage_url(
blob_url: str,
destination: str,
datastore_operation: DatastoreOperations,
datastore_name: Optional[str],
) -> str:
"""Download datastore blob URL to local file or directory."""
datastore_name = _get_datastore_name(datastore_name=datastore_name)
datastore_info = get_datastore_info(datastore_operation, datastore_name)
starts_with = get_artifact_path_from_storage_url(
blob_url=str(blob_url), container_name=datastore_info.get("container_name")
)
return download_artifact(
starts_with=starts_with,
destination=destination,
datastore_operation=datastore_operation,
datastore_name=datastore_name,
datastore_info=datastore_info,
) | Download datastore blob URL to local file or directory. |
4,289 | import os
import uuid
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, Optional, TypeVar, Union
from azure.ai.ml._artifacts._blob_storage_helper import BlobStorageClient
from azure.ai.ml._artifacts._gen2_storage_helper import Gen2StorageClient
from azure.ai.ml._azure_environments import _get_storage_endpoint_from_metadata
from azure.ai.ml._restclient.v2022_10_01.models import DatastoreType
from azure.ai.ml._scope_dependent_operations import OperationScope
from azure.ai.ml._utils._arm_id_utils import (
AMLNamedArmId,
get_resource_name_from_arm_id,
is_ARM_id_for_resource,
remove_aml_prefix,
)
from azure.ai.ml._utils._asset_utils import (
IgnoreFile,
_build_metadata_dict,
_validate_path,
get_ignore_file,
get_object_hash,
)
from azure.ai.ml._utils._storage_utils import (
AzureMLDatastorePathUri,
get_artifact_path_from_storage_url,
get_storage_client,
)
from azure.ai.ml.constants._common import SHORT_URI_FORMAT, STORAGE_ACCOUNT_URLS
from azure.ai.ml.entities import Environment
from azure.ai.ml.entities._assets._artifacts.artifact import Artifact, ArtifactStorageInfo
from azure.ai.ml.entities._credentials import AccountKeyConfiguration
from azure.ai.ml.entities._datastore._constants import WORKSPACE_BLOB_STORE
from azure.ai.ml.exceptions import ErrorTarget, ValidationException
from azure.ai.ml.operations._datastore_operations import DatastoreOperations
from azure.storage.blob import BlobSasPermissions, generate_blob_sas
from azure.storage.filedatalake import FileSasPermissions, generate_file_sas
from ..._utils.logger_utils import LoggerFactory
from ._fileshare_storeage_helper import FlowFileStorageClient
def download_artifact(
starts_with: Union[str, os.PathLike],
destination: str,
datastore_operation: DatastoreOperations,
datastore_name: Optional[str],
datastore_info: Optional[Dict] = None,
) -> str:
"""Download datastore path to local file or directory.
:param Union[str, os.PathLike] starts_with: Prefix of blobs to download
:param str destination: Path that files will be written to
:param DatastoreOperations datastore_operation: Datastore operations
:param Optional[str] datastore_name: name of datastore
:param Dict datastore_info: the return value of invoking get_datastore_info
:return str: Path that files were written to
"""
starts_with = starts_with.as_posix() if isinstance(starts_with, Path) else starts_with
datastore_name = _get_datastore_name(datastore_name=datastore_name)
if datastore_info is None:
datastore_info = get_datastore_info(datastore_operation, datastore_name)
storage_client = get_storage_client(**datastore_info)
storage_client.download(starts_with=starts_with, destination=destination)
return destination
The provided code snippet includes necessary dependencies for implementing the `download_artifact_from_aml_uri` function. Write a Python function `def download_artifact_from_aml_uri(uri: str, destination: str, datastore_operation: DatastoreOperations)` to solve the following problem:
Downloads artifact pointed to by URI of the form `azureml://...` to destination. :param str uri: AzureML uri of artifact to download :param str destination: Path to download artifact to :param DatastoreOperations datastore_operation: datastore operations :return str: Path that files were downloaded to
Here is the function:
def download_artifact_from_aml_uri(uri: str, destination: str, datastore_operation: DatastoreOperations):
"""Downloads artifact pointed to by URI of the form `azureml://...` to destination.
:param str uri: AzureML uri of artifact to download
:param str destination: Path to download artifact to
:param DatastoreOperations datastore_operation: datastore operations
:return str: Path that files were downloaded to
"""
parsed_uri = AzureMLDatastorePathUri(uri)
return download_artifact(
starts_with=parsed_uri.path,
destination=destination,
datastore_operation=datastore_operation,
datastore_name=parsed_uri.datastore,
) | Downloads artifact pointed to by URI of the form `azureml://...` to destination. :param str uri: AzureML uri of artifact to download :param str destination: Path to download artifact to :param DatastoreOperations datastore_operation: datastore operations :return str: Path that files were downloaded to |
4,290 | import os
import uuid
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, Optional, TypeVar, Union
from azure.ai.ml._artifacts._blob_storage_helper import BlobStorageClient
from azure.ai.ml._artifacts._gen2_storage_helper import Gen2StorageClient
from azure.ai.ml._azure_environments import _get_storage_endpoint_from_metadata
from azure.ai.ml._restclient.v2022_10_01.models import DatastoreType
from azure.ai.ml._scope_dependent_operations import OperationScope
from azure.ai.ml._utils._arm_id_utils import (
AMLNamedArmId,
get_resource_name_from_arm_id,
is_ARM_id_for_resource,
remove_aml_prefix,
)
from azure.ai.ml._utils._asset_utils import (
IgnoreFile,
_build_metadata_dict,
_validate_path,
get_ignore_file,
get_object_hash,
)
from azure.ai.ml._utils._storage_utils import (
AzureMLDatastorePathUri,
get_artifact_path_from_storage_url,
get_storage_client,
)
from azure.ai.ml.constants._common import SHORT_URI_FORMAT, STORAGE_ACCOUNT_URLS
from azure.ai.ml.entities import Environment
from azure.ai.ml.entities._assets._artifacts.artifact import Artifact, ArtifactStorageInfo
from azure.ai.ml.entities._credentials import AccountKeyConfiguration
from azure.ai.ml.entities._datastore._constants import WORKSPACE_BLOB_STORE
from azure.ai.ml.exceptions import ErrorTarget, ValidationException
from azure.ai.ml.operations._datastore_operations import DatastoreOperations
from azure.storage.blob import BlobSasPermissions, generate_blob_sas
from azure.storage.filedatalake import FileSasPermissions, generate_file_sas
from ..._utils.logger_utils import LoggerFactory
from ._fileshare_storeage_helper import FlowFileStorageClient
def get_datastore_info(operations: DatastoreOperations, name: str) -> Dict[str, str]:
"""Get datastore account, type, and auth information."""
datastore_info = {}
if name:
datastore = operations.get(name, include_secrets=True)
else:
datastore = operations.get_default(include_secrets=True)
storage_endpoint = _get_storage_endpoint_from_metadata()
credentials = datastore.credentials
datastore_info["storage_type"] = datastore.type
datastore_info["storage_account"] = datastore.account_name
datastore_info["account_url"] = STORAGE_ACCOUNT_URLS[datastore.type].format(
datastore.account_name, storage_endpoint
)
if isinstance(credentials, AccountKeyConfiguration):
datastore_info["credential"] = credentials.account_key
else:
try:
datastore_info["credential"] = credentials.sas_token
except Exception as e: # pylint: disable=broad-except
if not hasattr(credentials, "sas_token"):
datastore_info["credential"] = operations._credential
else:
raise e
if datastore.type == DatastoreType.AZURE_BLOB:
datastore_info["container_name"] = str(datastore.container_name)
elif datastore.type == DatastoreType.AZURE_DATA_LAKE_GEN2:
datastore_info["container_name"] = str(datastore.filesystem)
elif datastore.type == DatastoreType.AZURE_FILE:
datastore_info["container_name"] = str(datastore.file_share_name)
else:
raise Exception(
f"Datastore type {datastore.type} is not supported for uploads. "
f"Supported types are {DatastoreType.AZURE_BLOB} and {DatastoreType.AZURE_DATA_LAKE_GEN2}."
)
return datastore_info
The provided code snippet includes necessary dependencies for implementing the `aml_datastore_path_exists` function. Write a Python function `def aml_datastore_path_exists( uri: str, datastore_operation: DatastoreOperations, datastore_info: Optional[dict] = None )` to solve the following problem:
Checks whether `uri` of the form "azureml://" points to either a directory or a file. :param str uri: azure ml datastore uri :param DatastoreOperations datastore_operation: Datastore operation :param dict datastore_info: return value of get_datastore_info
Here is the function:
def aml_datastore_path_exists(
uri: str, datastore_operation: DatastoreOperations, datastore_info: Optional[dict] = None
):
"""Checks whether `uri` of the form "azureml://" points to either a directory or a file.
:param str uri: azure ml datastore uri
:param DatastoreOperations datastore_operation: Datastore operation
:param dict datastore_info: return value of get_datastore_info
"""
parsed_uri = AzureMLDatastorePathUri(uri)
datastore_info = datastore_info or get_datastore_info(datastore_operation, parsed_uri.datastore)
return get_storage_client(**datastore_info).exists(parsed_uri.path) | Checks whether `uri` of the form "azureml://" points to either a directory or a file. :param str uri: azure ml datastore uri :param DatastoreOperations datastore_operation: Datastore operation :param dict datastore_info: return value of get_datastore_info |
4,291 | import os
import uuid
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, Optional, TypeVar, Union
from azure.ai.ml._artifacts._blob_storage_helper import BlobStorageClient
from azure.ai.ml._artifacts._gen2_storage_helper import Gen2StorageClient
from azure.ai.ml._azure_environments import _get_storage_endpoint_from_metadata
from azure.ai.ml._restclient.v2022_10_01.models import DatastoreType
from azure.ai.ml._scope_dependent_operations import OperationScope
from azure.ai.ml._utils._arm_id_utils import (
AMLNamedArmId,
get_resource_name_from_arm_id,
is_ARM_id_for_resource,
remove_aml_prefix,
)
from azure.ai.ml._utils._asset_utils import (
IgnoreFile,
_build_metadata_dict,
_validate_path,
get_ignore_file,
get_object_hash,
)
from azure.ai.ml._utils._storage_utils import (
AzureMLDatastorePathUri,
get_artifact_path_from_storage_url,
get_storage_client,
)
from azure.ai.ml.constants._common import SHORT_URI_FORMAT, STORAGE_ACCOUNT_URLS
from azure.ai.ml.entities import Environment
from azure.ai.ml.entities._assets._artifacts.artifact import Artifact, ArtifactStorageInfo
from azure.ai.ml.entities._credentials import AccountKeyConfiguration
from azure.ai.ml.entities._datastore._constants import WORKSPACE_BLOB_STORE
from azure.ai.ml.exceptions import ErrorTarget, ValidationException
from azure.ai.ml.operations._datastore_operations import DatastoreOperations
from azure.storage.blob import BlobSasPermissions, generate_blob_sas
from azure.storage.filedatalake import FileSasPermissions, generate_file_sas
from ..._utils.logger_utils import LoggerFactory
from ._fileshare_storeage_helper import FlowFileStorageClient
def _upload_to_datastore(
operation_scope: OperationScope,
datastore_operation: DatastoreOperations,
path: Union[str, Path, os.PathLike],
artifact_type: str,
datastore_name: Optional[str] = None,
show_progress: bool = True,
asset_name: Optional[str] = None,
asset_version: Optional[str] = None,
asset_hash: Optional[str] = None,
ignore_file: Optional[IgnoreFile] = None,
sas_uri: Optional[str] = None, # contains registry sas url
) -> ArtifactStorageInfo:
_validate_path(path, _type=artifact_type)
if not ignore_file:
ignore_file = get_ignore_file(path)
if not asset_hash:
asset_hash = get_object_hash(path, ignore_file)
artifact = upload_artifact(
str(path),
datastore_operation,
operation_scope,
datastore_name,
show_progress=show_progress,
asset_hash=asset_hash,
asset_name=asset_name,
asset_version=asset_version,
ignore_file=ignore_file,
sas_uri=sas_uri,
)
return artifact
def _upload_and_generate_remote_uri(
operation_scope: OperationScope,
datastore_operation: DatastoreOperations,
path: Union[str, Path, os.PathLike],
artifact_type: str = ErrorTarget.ARTIFACT,
datastore_name: str = WORKSPACE_BLOB_STORE,
show_progress: bool = True,
) -> str:
# Asset name is required for uploading to a datastore
asset_name = str(uuid.uuid4())
artifact_info = _upload_to_datastore(
operation_scope=operation_scope,
datastore_operation=datastore_operation,
path=path,
datastore_name=datastore_name,
asset_name=asset_name,
artifact_type=artifact_type,
show_progress=show_progress,
)
path = artifact_info.relative_path
datastore = AMLNamedArmId(artifact_info.datastore_arm_id).asset_name
return SHORT_URI_FORMAT.format(datastore, path) | null |
4,292 | import os
import uuid
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, Optional, TypeVar, Union
from azure.ai.ml._artifacts._blob_storage_helper import BlobStorageClient
from azure.ai.ml._artifacts._gen2_storage_helper import Gen2StorageClient
from azure.ai.ml._azure_environments import _get_storage_endpoint_from_metadata
from azure.ai.ml._restclient.v2022_10_01.models import DatastoreType
from azure.ai.ml._scope_dependent_operations import OperationScope
from azure.ai.ml._utils._arm_id_utils import (
AMLNamedArmId,
get_resource_name_from_arm_id,
is_ARM_id_for_resource,
remove_aml_prefix,
)
from azure.ai.ml._utils._asset_utils import (
IgnoreFile,
_build_metadata_dict,
_validate_path,
get_ignore_file,
get_object_hash,
)
from azure.ai.ml._utils._storage_utils import (
AzureMLDatastorePathUri,
get_artifact_path_from_storage_url,
get_storage_client,
)
from azure.ai.ml.constants._common import SHORT_URI_FORMAT, STORAGE_ACCOUNT_URLS
from azure.ai.ml.entities import Environment
from azure.ai.ml.entities._assets._artifacts.artifact import Artifact, ArtifactStorageInfo
from azure.ai.ml.entities._credentials import AccountKeyConfiguration
from azure.ai.ml.entities._datastore._constants import WORKSPACE_BLOB_STORE
from azure.ai.ml.exceptions import ErrorTarget, ValidationException
from azure.ai.ml.operations._datastore_operations import DatastoreOperations
from azure.storage.blob import BlobSasPermissions, generate_blob_sas
from azure.storage.filedatalake import FileSasPermissions, generate_file_sas
from ..._utils.logger_utils import LoggerFactory
from ._fileshare_storeage_helper import FlowFileStorageClient
def _update_blob_metadata(name, version, indicator_file, storage_client) -> None:
container_client = storage_client.container_client
if indicator_file.startswith(storage_client.container):
indicator_file = indicator_file.split(storage_client.container)[1]
blob = container_client.get_blob_client(blob=indicator_file)
blob.set_blob_metadata(_build_metadata_dict(name=name, version=version))
def _update_gen2_metadata(name, version, indicator_file, storage_client) -> None:
artifact_directory_client = storage_client.file_system_client.get_directory_client(indicator_file)
artifact_directory_client.set_metadata(_build_metadata_dict(name=name, version=version))
def _update_metadata(name, version, indicator_file, datastore_info) -> None:
storage_client = get_storage_client(**datastore_info)
if isinstance(storage_client, BlobStorageClient):
_update_blob_metadata(name, version, indicator_file, storage_client)
elif isinstance(storage_client, Gen2StorageClient):
_update_gen2_metadata(name, version, indicator_file, storage_client) | null |
4,293 | import os
import uuid
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, Optional, TypeVar, Union
from azure.ai.ml._artifacts._blob_storage_helper import BlobStorageClient
from azure.ai.ml._artifacts._gen2_storage_helper import Gen2StorageClient
from azure.ai.ml._azure_environments import _get_storage_endpoint_from_metadata
from azure.ai.ml._restclient.v2022_10_01.models import DatastoreType
from azure.ai.ml._scope_dependent_operations import OperationScope
from azure.ai.ml._utils._arm_id_utils import (
AMLNamedArmId,
get_resource_name_from_arm_id,
is_ARM_id_for_resource,
remove_aml_prefix,
)
from azure.ai.ml._utils._asset_utils import (
IgnoreFile,
_build_metadata_dict,
_validate_path,
get_ignore_file,
get_object_hash,
)
from azure.ai.ml._utils._storage_utils import (
AzureMLDatastorePathUri,
get_artifact_path_from_storage_url,
get_storage_client,
)
from azure.ai.ml.constants._common import SHORT_URI_FORMAT, STORAGE_ACCOUNT_URLS
from azure.ai.ml.entities import Environment
from azure.ai.ml.entities._assets._artifacts.artifact import Artifact, ArtifactStorageInfo
from azure.ai.ml.entities._credentials import AccountKeyConfiguration
from azure.ai.ml.entities._datastore._constants import WORKSPACE_BLOB_STORE
from azure.ai.ml.exceptions import ErrorTarget, ValidationException
from azure.ai.ml.operations._datastore_operations import DatastoreOperations
from azure.storage.blob import BlobSasPermissions, generate_blob_sas
from azure.storage.filedatalake import FileSasPermissions, generate_file_sas
from ..._utils.logger_utils import LoggerFactory
from ._fileshare_storeage_helper import FlowFileStorageClient
def _upload_to_datastore(
operation_scope: OperationScope,
datastore_operation: DatastoreOperations,
path: Union[str, Path, os.PathLike],
artifact_type: str,
datastore_name: Optional[str] = None,
show_progress: bool = True,
asset_name: Optional[str] = None,
asset_version: Optional[str] = None,
asset_hash: Optional[str] = None,
ignore_file: Optional[IgnoreFile] = None,
sas_uri: Optional[str] = None, # contains registry sas url
) -> ArtifactStorageInfo:
_validate_path(path, _type=artifact_type)
if not ignore_file:
ignore_file = get_ignore_file(path)
if not asset_hash:
asset_hash = get_object_hash(path, ignore_file)
artifact = upload_artifact(
str(path),
datastore_operation,
operation_scope,
datastore_name,
show_progress=show_progress,
asset_hash=asset_hash,
asset_name=asset_name,
asset_version=asset_version,
ignore_file=ignore_file,
sas_uri=sas_uri,
)
return artifact
T = TypeVar("T", bound=Artifact)
The provided code snippet includes necessary dependencies for implementing the `_check_and_upload_path` function. Write a Python function `def _check_and_upload_path( artifact: T, asset_operations: Union["DataOperations", "ModelOperations", "CodeOperations", "FeatureSetOperations"], artifact_type: str, datastore_name: Optional[str] = None, sas_uri: Optional[str] = None, show_progress: bool = True, )` to solve the following problem:
Checks whether `artifact` is a path or a uri and uploads it to the datastore if necessary. param T artifact: artifact to check and upload param Union["DataOperations", "ModelOperations", "CodeOperations"] asset_operations: the asset operations to use for uploading param str datastore_name: the name of the datastore to upload to param str sas_uri: the sas uri to use for uploading
Here is the function:
def _check_and_upload_path(
artifact: T,
asset_operations: Union["DataOperations", "ModelOperations", "CodeOperations", "FeatureSetOperations"],
artifact_type: str,
datastore_name: Optional[str] = None,
sas_uri: Optional[str] = None,
show_progress: bool = True,
):
"""Checks whether `artifact` is a path or a uri and uploads it to the datastore if necessary.
param T artifact: artifact to check and upload param
Union["DataOperations", "ModelOperations", "CodeOperations"]
asset_operations: the asset operations to use for uploading
param str datastore_name: the name of the datastore to upload to
param str sas_uri: the sas uri to use for uploading
"""
from azure.ai.ml._utils.utils import is_mlflow_uri, is_url
datastore_name = artifact.datastore
if (
hasattr(artifact, "local_path")
and artifact.local_path is not None
or (
hasattr(artifact, "path")
and artifact.path is not None
and not (is_url(artifact.path) or is_mlflow_uri(artifact.path))
)
):
path = (
Path(artifact.path)
if hasattr(artifact, "path") and artifact.path is not None
else Path(artifact.local_path)
)
if not path.is_absolute():
path = Path(artifact.base_path, path).resolve()
uploaded_artifact = _upload_to_datastore(
asset_operations._operation_scope,
asset_operations._datastore_operation,
path,
datastore_name=datastore_name,
asset_name=artifact.name,
asset_version=str(artifact.version),
asset_hash=artifact._upload_hash if hasattr(artifact, "_upload_hash") else None,
sas_uri=sas_uri,
artifact_type=artifact_type,
show_progress=show_progress,
ignore_file=getattr(artifact, "_ignore_file", None),
)
return uploaded_artifact | Checks whether `artifact` is a path or a uri and uploads it to the datastore if necessary. param T artifact: artifact to check and upload param Union["DataOperations", "ModelOperations", "CodeOperations"] asset_operations: the asset operations to use for uploading param str datastore_name: the name of the datastore to upload to param str sas_uri: the sas uri to use for uploading |
4,294 | import os
import uuid
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, Optional, TypeVar, Union
from azure.ai.ml._artifacts._blob_storage_helper import BlobStorageClient
from azure.ai.ml._artifacts._gen2_storage_helper import Gen2StorageClient
from azure.ai.ml._azure_environments import _get_storage_endpoint_from_metadata
from azure.ai.ml._restclient.v2022_10_01.models import DatastoreType
from azure.ai.ml._scope_dependent_operations import OperationScope
from azure.ai.ml._utils._arm_id_utils import (
AMLNamedArmId,
get_resource_name_from_arm_id,
is_ARM_id_for_resource,
remove_aml_prefix,
)
from azure.ai.ml._utils._asset_utils import (
IgnoreFile,
_build_metadata_dict,
_validate_path,
get_ignore_file,
get_object_hash,
)
from azure.ai.ml._utils._storage_utils import (
AzureMLDatastorePathUri,
get_artifact_path_from_storage_url,
get_storage_client,
)
from azure.ai.ml.constants._common import SHORT_URI_FORMAT, STORAGE_ACCOUNT_URLS
from azure.ai.ml.entities import Environment
from azure.ai.ml.entities._assets._artifacts.artifact import Artifact, ArtifactStorageInfo
from azure.ai.ml.entities._credentials import AccountKeyConfiguration
from azure.ai.ml.entities._datastore._constants import WORKSPACE_BLOB_STORE
from azure.ai.ml.exceptions import ErrorTarget, ValidationException
from azure.ai.ml.operations._datastore_operations import DatastoreOperations
from azure.storage.blob import BlobSasPermissions, generate_blob_sas
from azure.storage.filedatalake import FileSasPermissions, generate_file_sas
from ..._utils.logger_utils import LoggerFactory
from ._fileshare_storeage_helper import FlowFileStorageClient
def _upload_to_datastore(
operation_scope: OperationScope,
datastore_operation: DatastoreOperations,
path: Union[str, Path, os.PathLike],
artifact_type: str,
datastore_name: Optional[str] = None,
show_progress: bool = True,
asset_name: Optional[str] = None,
asset_version: Optional[str] = None,
asset_hash: Optional[str] = None,
ignore_file: Optional[IgnoreFile] = None,
sas_uri: Optional[str] = None, # contains registry sas url
) -> ArtifactStorageInfo:
_validate_path(path, _type=artifact_type)
if not ignore_file:
ignore_file = get_ignore_file(path)
if not asset_hash:
asset_hash = get_object_hash(path, ignore_file)
artifact = upload_artifact(
str(path),
datastore_operation,
operation_scope,
datastore_name,
show_progress=show_progress,
asset_hash=asset_hash,
asset_name=asset_name,
asset_version=asset_version,
ignore_file=ignore_file,
sas_uri=sas_uri,
)
return artifact
def _check_and_upload_env_build_context(
environment: Environment,
operations: "EnvironmentOperations",
sas_uri=None,
show_progress: bool = True,
) -> Environment:
if environment.path:
uploaded_artifact = _upload_to_datastore(
operations._operation_scope,
operations._datastore_operation,
environment.path,
asset_name=environment.name,
asset_version=str(environment.version),
asset_hash=environment._upload_hash,
sas_uri=sas_uri,
artifact_type=ErrorTarget.ENVIRONMENT,
datastore_name=environment.datastore,
show_progress=show_progress,
)
# TODO: Depending on decision trailing "/" needs to stay or not. EMS requires it to be present
environment.build.path = uploaded_artifact.full_storage_path + "/"
return environment | null |
4,295 | import json
import os
import sys
import time
import uuid
from functools import wraps, cached_property
import pydash
from azure.core.exceptions import HttpResponseError, ResourceExistsError
from azure.core.pipeline.policies import RetryPolicy
from promptflow._sdk._telemetry import request_id_context
from promptflow._sdk._telemetry import TelemetryMixin
from promptflow._utils.logger_utils import LoggerFactory
from promptflow.azure._constants._flow import AUTOMATIC_RUNTIME, SESSION_CREATION_TIMEOUT_ENV_VAR
from promptflow.azure._restclient.flow import AzureMachineLearningDesignerServiceClient
from promptflow.azure._utils.general import get_authorization, get_arm_token, get_aml_token
from promptflow.exceptions import UserErrorException, PromptflowException, SystemErrorException
class FlowRequestException(SystemErrorException):
"""FlowRequestException."""
def __init__(self, message, **kwargs):
super().__init__(message, **kwargs)
class RequestTelemetryMixin(TelemetryMixin):
def __init__(self):
super().__init__()
self._refresh_request_id_for_telemetry()
self._from_cli = False
def _get_telemetry_values(self, *args, **kwargs):
return {"request_id": self._request_id, "from_cli": self._from_cli}
def _set_from_cli_for_telemetry(self):
self._from_cli = True
def _refresh_request_id_for_telemetry(self):
# refresh request id from current request id context
self._request_id = request_id_context.get() or str(uuid.uuid4())
The provided code snippet includes necessary dependencies for implementing the `_request_wrapper` function. Write a Python function `def _request_wrapper()` to solve the following problem:
Wrapper for request. Will refresh request id and pretty print exception.
Here is the function:
def _request_wrapper():
"""Wrapper for request. Will refresh request id and pretty print exception."""
def exception_wrapper(func):
@wraps(func)
def wrapper(self, *args, **kwargs):
if not isinstance(self, RequestTelemetryMixin):
raise PromptflowException(f"Wrapped function is not RequestTelemetryMixin, got {type(self)}")
# refresh request before each request
self._refresh_request_id_for_telemetry()
try:
return func(self, *args, **kwargs)
except HttpResponseError as e:
raise FlowRequestException(
f"Calling {func.__name__} failed with request id: {self._request_id} \n"
f"Status code: {e.status_code} \n"
f"Reason: {e.reason} \n"
f"Error message: {e.message} \n"
)
return wrapper
return exception_wrapper | Wrapper for request. Will refresh request id and pretty print exception. |
4,296 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def build_get_runtime_latest_config_request(
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/runtimes/latestConfig')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,297 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_create_connection_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
connection_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connection/{connectionName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"connectionName": _SERIALIZER.url("connection_name", connection_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,298 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_update_connection_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
connection_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connection/{connectionName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"connectionName": _SERIALIZER.url("connection_name", connection_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="PUT",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,299 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
def build_get_connection_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
connection_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connection/{connectionName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"connectionName": _SERIALIZER.url("connection_name", connection_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,300 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_delete_connection_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
connection_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
connection_scope = kwargs.pop('connection_scope', None) # type: Optional[Union[str, "_models.ConnectionScope"]]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connection/{connectionName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"connectionName": _SERIALIZER.url("connection_name", connection_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if connection_scope is not None:
query_parameters['connectionScope'] = _SERIALIZER.query("connection_scope", connection_scope, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="DELETE",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,301 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_list_connections_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connection')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,302 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_list_connection_specs_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connection/specs')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,303 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_index_entity_by_id_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/v1.0/flows/getIndexEntities')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,304 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_updated_entity_ids_for_workspace_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/v1.0/flows/rebuildIndex')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,305 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import (
ClientAuthenticationError,
HttpResponseError,
ResourceExistsError,
ResourceNotFoundError,
map_error,
)
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_create_flow_session_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
session_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
waitfor_completion = kwargs.pop('waitfor_completion', False) # type: Optional[bool]
accept = "text/plain, application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowSessionsAdmin/{sessionId}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"sessionId": _SERIALIZER.url("session_id", session_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if waitfor_completion is not None:
query_parameters['waitforCompletion'] = _SERIALIZER.query("waitfor_completion", waitfor_completion, 'bool')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,306 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_create_runtime_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
runtime_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
async_call = kwargs.pop('async_call', False) # type: Optional[bool]
msi_token = kwargs.pop('msi_token', False) # type: Optional[bool]
skip_port_check = kwargs.pop('skip_port_check', False) # type: Optional[bool]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRuntimes/{runtimeName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"runtimeName": _SERIALIZER.url("runtime_name", runtime_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if async_call is not None:
query_parameters['asyncCall'] = _SERIALIZER.query("async_call", async_call, 'bool')
if msi_token is not None:
query_parameters['msiToken'] = _SERIALIZER.query("msi_token", msi_token, 'bool')
if skip_port_check is not None:
query_parameters['skipPortCheck'] = _SERIALIZER.query("skip_port_check", skip_port_check, 'bool')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,307 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_update_runtime_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
runtime_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
async_call = kwargs.pop('async_call', False) # type: Optional[bool]
msi_token = kwargs.pop('msi_token', False) # type: Optional[bool]
skip_port_check = kwargs.pop('skip_port_check', False) # type: Optional[bool]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRuntimes/{runtimeName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"runtimeName": _SERIALIZER.url("runtime_name", runtime_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if async_call is not None:
query_parameters['asyncCall'] = _SERIALIZER.query("async_call", async_call, 'bool')
if msi_token is not None:
query_parameters['msiToken'] = _SERIALIZER.query("msi_token", msi_token, 'bool')
if skip_port_check is not None:
query_parameters['skipPortCheck'] = _SERIALIZER.query("skip_port_check", skip_port_check, 'bool')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="PUT",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,308 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_runtime_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
runtime_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRuntimes/{runtimeName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"runtimeName": _SERIALIZER.url("runtime_name", runtime_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,309 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_delete_runtime_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
runtime_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
async_call = kwargs.pop('async_call', False) # type: Optional[bool]
msi_token = kwargs.pop('msi_token', False) # type: Optional[bool]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRuntimes/{runtimeName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"runtimeName": _SERIALIZER.url("runtime_name", runtime_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if async_call is not None:
query_parameters['asyncCall'] = _SERIALIZER.query("async_call", async_call, 'bool')
if msi_token is not None:
query_parameters['msiToken'] = _SERIALIZER.query("msi_token", msi_token, 'bool')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="DELETE",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,310 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_check_ci_availability_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
compute_instance_name = kwargs.pop('compute_instance_name') # type: str
custom_app_name = kwargs.pop('custom_app_name') # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRuntimes/checkCiAvailability')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['computeInstanceName'] = _SERIALIZER.query("compute_instance_name", compute_instance_name, 'str')
query_parameters['customAppName'] = _SERIALIZER.query("custom_app_name", custom_app_name, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,311 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
def build_check_mir_availability_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
endpoint_name = kwargs.pop('endpoint_name') # type: str
deployment_name = kwargs.pop('deployment_name') # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRuntimes/checkMirAvailability')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['endpointName'] = _SERIALIZER.query("endpoint_name", endpoint_name, 'str')
query_parameters['deploymentName'] = _SERIALIZER.query("deployment_name", deployment_name, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,312 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_check_runtime_upgrade_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
runtime_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRuntimes/{runtimeName}/needUpgrade')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"runtimeName": _SERIALIZER.url("runtime_name", runtime_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,313 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_runtime_capability_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
runtime_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRuntimes/{runtimeName}/capability')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"runtimeName": _SERIALIZER.url("runtime_name", runtime_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,314 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_runtime_latest_config_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRuntimes/latestConfig')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,315 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_list_runtimes_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRuntimes')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,316 | import datetime
import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_submit_bulk_run_async_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
bulk_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
error_handling_mode = kwargs.pop('error_handling_mode', None) # type: Optional[Union[str, "_models.ErrorHandlingMode"]]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRunsAdmin/{flowId}/bulkRuns/{bulkRunId}/submit')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"bulkRunId": _SERIALIZER.url("bulk_run_id", bulk_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if error_handling_mode is not None:
query_parameters['errorHandlingMode'] = _SERIALIZER.query("error_handling_mode", error_handling_mode, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,317 | import datetime
import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_send_policy_validation_async_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
bulk_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRunsAdmin/{flowId}/bulkRuns/{bulkRunId}/policy')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"bulkRunId": _SERIALIZER.url("bulk_run_id", bulk_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,318 | import datetime
import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_check_policy_validation_async_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
bulk_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRunsAdmin/{flowId}/bulkRuns/{bulkRunId}/policy')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"bulkRunId": _SERIALIZER.url("bulk_run_id", bulk_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,319 | import datetime
import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_log_result_for_bulk_run_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
bulk_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRunsAdmin/{flowId}/bulkRuns/{bulkRunId}/LogResult')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"bulkRunId": _SERIALIZER.url("bulk_run_id", bulk_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,320 | import datetime
import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
def build_get_storage_info_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRunsAdmin/storageInfo')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,321 | import datetime
import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_log_flow_run_event_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
flow_run_id, # type: str
runtime_version, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRunsAdmin/{flowId}/flowRuns/{flowRunId}/runtime/{runtimeVersion}/logEvent')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"flowRunId": _SERIALIZER.url("flow_run_id", flow_run_id, 'str'),
"runtimeVersion": _SERIALIZER.url("runtime_version", runtime_version, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,322 | import datetime
import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
def build_log_flow_run_event_v2_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
flow_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
runtime_version = kwargs.pop('runtime_version', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRunsAdmin/{flowId}/flowRuns/{flowRunId}/logEvent')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"flowRunId": _SERIALIZER.url("flow_run_id", flow_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if runtime_version is not None:
query_parameters['runtimeVersion'] = _SERIALIZER.query("runtime_version", runtime_version, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,323 | import datetime
import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_log_flow_run_terminated_event_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
flow_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
last_checked_time = kwargs.pop('last_checked_time', None) # type: Optional[datetime.datetime]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRunsAdmin/{flowId}/flowRuns/{flowRunId}/logTerminatedEvent')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"flowRunId": _SERIALIZER.url("flow_run_id", flow_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if last_checked_time is not None:
query_parameters['lastCheckedTime'] = _SERIALIZER.query("last_checked_time", last_checked_time, 'iso-8601')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,324 | import datetime
import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_update_service_logs_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
bulk_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRunsAdmin/{flowId}/bulkRuns/{bulkRunId}/serviceLogs')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"bulkRunId": _SERIALIZER.url("bulk_run_id", bulk_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,325 | import datetime
import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_batch_update_service_logs_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
bulk_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowRunsAdmin/{flowId}/bulkRuns/{bulkRunId}/serviceLogs/batch')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"bulkRunId": _SERIALIZER.url("bulk_run_id", bulk_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,326 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_init_trace_session_async_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
overwrite = kwargs.pop('overwrite', False) # type: Optional[bool]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/TraceSessions/initialize')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if overwrite is not None:
query_parameters['overwrite'] = _SERIALIZER.query("overwrite", overwrite, 'bool')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,327 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_cleanup_trace_session_async_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/TraceSessions/cleanup')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,328 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_poll_trace_session_status_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
operation_id, # type: str
operation_type, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/TraceSessions/operation/{operationType}/{operationId}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"operationId": _SERIALIZER.url("operation_id", operation_id, 'str'),
"operationType": _SERIALIZER.url("operation_type", operation_type, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,329 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
def build_attach_cosmos_account_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
overwrite = kwargs.pop('overwrite', False) # type: Optional[bool]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/TraceSessions/attachDb')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if overwrite is not None:
query_parameters['overwrite'] = _SERIALIZER.query("overwrite", overwrite, 'bool')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,330 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
def build_get_cosmos_resource_token_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
container_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
acquire_write = kwargs.pop('acquire_write', False) # type: Optional[bool]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/TraceSessions/container/{containerName}/resourceToken')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"containerName": _SERIALIZER.url("container_name", container_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if acquire_write is not None:
query_parameters['acquireWrite'] = _SERIALIZER.query("acquire_write", acquire_write, 'bool')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,331 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_create_flow_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
experiment_id = kwargs.pop('experiment_id', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if experiment_id is not None:
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,332 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_list_flows_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
experiment_id = kwargs.pop('experiment_id', None) # type: Optional[str]
owned_only = kwargs.pop('owned_only', None) # type: Optional[bool]
flow_type = kwargs.pop('flow_type', None) # type: Optional[Union[str, "_models.FlowType"]]
list_view_type = kwargs.pop('list_view_type', None) # type: Optional[Union[str, "_models.ListViewType"]]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if experiment_id is not None:
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
if owned_only is not None:
query_parameters['ownedOnly'] = _SERIALIZER.query("owned_only", owned_only, 'bool')
if flow_type is not None:
query_parameters['flowType'] = _SERIALIZER.query("flow_type", flow_type, 'str')
if list_view_type is not None:
query_parameters['listViewType'] = _SERIALIZER.query("list_view_type", list_view_type, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,333 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_update_flow_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
experiment_id = kwargs.pop('experiment_id') # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="PUT",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,334 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_patch_flow_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
experiment_id = kwargs.pop('experiment_id') # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="PATCH",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,335 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_flow_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
experiment_id = kwargs.pop('experiment_id') # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,336 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_submit_flow_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
experiment_id = kwargs.pop('experiment_id') # type: str
endpoint_name = kwargs.pop('endpoint_name', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/submit')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
if endpoint_name is not None:
query_parameters['endpointName'] = _SERIALIZER.query("endpoint_name", endpoint_name, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,337 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_flow_run_status_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
flow_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
experiment_id = kwargs.pop('experiment_id', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/{flowRunId}/status')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"flowRunId": _SERIALIZER.url("flow_run_id", flow_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if experiment_id is not None:
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,338 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
def build_get_flow_run_info_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
flow_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
experiment_id = kwargs.pop('experiment_id') # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/runs/{flowRunId}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"flowRunId": _SERIALIZER.url("flow_run_id", flow_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,339 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
def build_get_flow_child_runs_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
flow_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
index = kwargs.pop('index', None) # type: Optional[int]
start_index = kwargs.pop('start_index', None) # type: Optional[int]
end_index = kwargs.pop('end_index', None) # type: Optional[int]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/runs/{flowRunId}/childRuns')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"flowRunId": _SERIALIZER.url("flow_run_id", flow_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if index is not None:
query_parameters['index'] = _SERIALIZER.query("index", index, 'int')
if start_index is not None:
query_parameters['startIndex'] = _SERIALIZER.query("start_index", start_index, 'int')
if end_index is not None:
query_parameters['endIndex'] = _SERIALIZER.query("end_index", end_index, 'int')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,340 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
def build_get_flow_node_runs_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
flow_run_id, # type: str
node_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
index = kwargs.pop('index', None) # type: Optional[int]
start_index = kwargs.pop('start_index', None) # type: Optional[int]
end_index = kwargs.pop('end_index', None) # type: Optional[int]
aggregation = kwargs.pop('aggregation', False) # type: Optional[bool]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/runs/{flowRunId}/nodeRuns/{nodeName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"flowRunId": _SERIALIZER.url("flow_run_id", flow_run_id, 'str'),
"nodeName": _SERIALIZER.url("node_name", node_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if index is not None:
query_parameters['index'] = _SERIALIZER.query("index", index, 'int')
if start_index is not None:
query_parameters['startIndex'] = _SERIALIZER.query("start_index", start_index, 'int')
if end_index is not None:
query_parameters['endIndex'] = _SERIALIZER.query("end_index", end_index, 'int')
if aggregation is not None:
query_parameters['aggregation'] = _SERIALIZER.query("aggregation", aggregation, 'bool')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,341 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_flow_node_run_base_path_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
flow_run_id, # type: str
node_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/runs/{flowRunId}/nodeRuns/{nodeName}/basePath')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"flowRunId": _SERIALIZER.url("flow_run_id", flow_run_id, 'str'),
"nodeName": _SERIALIZER.url("node_name", node_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,342 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_list_bulk_tests_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
experiment_id = kwargs.pop('experiment_id', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/bulkTests')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if experiment_id is not None:
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,343 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_bulk_test_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
bulk_test_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/bulkTests/{bulkTestId}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"bulkTestId": _SERIALIZER.url("bulk_test_id", bulk_test_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,344 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_flow_deploy_reserved_environment_variable_names_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/DeployReservedEnvironmentVariableNames')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,345 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_deploy_flow_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
async_call = kwargs.pop('async_call', False) # type: Optional[bool]
msi_token = kwargs.pop('msi_token', False) # type: Optional[bool]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/deploy')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if async_call is not None:
query_parameters['asyncCall'] = _SERIALIZER.query("async_call", async_call, 'bool')
if msi_token is not None:
query_parameters['msiToken'] = _SERIALIZER.query("msi_token", msi_token, 'bool')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,346 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_flow_run_log_content_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
flow_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/runs/{flowRunId}/logContent')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"flowRunId": _SERIALIZER.url("flow_run_id", flow_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,347 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_cancel_flow_run_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "text/plain, application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/runs/{flowRunId}/cancel')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowRunId": _SERIALIZER.url("flow_run_id", flow_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,348 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
def build_cancel_flow_test_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
flow_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "text/plain, application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/flowTests/{flowRunId}/cancel')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
"flowRunId": _SERIALIZER.url("flow_run_id", flow_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,349 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_cancel_bulk_test_run_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
bulk_test_run_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "text/plain, application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/bulkTests/{bulkTestRunId}/cancel')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"bulkTestRunId": _SERIALIZER.url("bulk_test_run_id", bulk_test_run_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,350 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_flow_snapshot_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/FlowSnapshot')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,351 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_connection_override_settings_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
runtime_name = kwargs.pop('runtime_name', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/connectionOverride')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if runtime_name is not None:
query_parameters['runtimeName'] = _SERIALIZER.query("runtime_name", runtime_name, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,352 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_flow_inputs_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/flowInputs')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,353 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_load_as_component_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/LoadAsComponent')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,354 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_flow_tools_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
experiment_id = kwargs.pop('experiment_id') # type: str
flow_runtime_name = kwargs.pop('flow_runtime_name', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/flowTools')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if flow_runtime_name is not None:
query_parameters['flowRuntimeName'] = _SERIALIZER.query("flow_runtime_name", flow_runtime_name, 'str')
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,355 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_setup_flow_session_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
experiment_id = kwargs.pop('experiment_id') # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/sessions')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,356 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_delete_flow_session_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
experiment_id = kwargs.pop('experiment_id') # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/sessions')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="DELETE",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,357 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_flow_session_status_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
experiment_id = kwargs.pop('experiment_id') # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/sessions/status')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,358 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
def build_list_flow_session_pip_packages_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
flow_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
experiment_id = kwargs.pop('experiment_id') # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Flows/{flowId}/sessions/pipPackages')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"flowId": _SERIALIZER.url("flow_id", flow_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['experimentId'] = _SERIALIZER.query("experiment_id", experiment_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,359 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_create_connection_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
connection_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connections/{connectionName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"connectionName": _SERIALIZER.url("connection_name", connection_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,360 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_update_connection_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
connection_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connections/{connectionName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"connectionName": _SERIALIZER.url("connection_name", connection_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="PUT",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,361 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_connection_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
connection_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connections/{connectionName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"connectionName": _SERIALIZER.url("connection_name", connection_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,362 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_delete_connection_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
connection_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connections/{connectionName}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"connectionName": _SERIALIZER.url("connection_name", connection_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="DELETE",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,363 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_connection_with_secrets_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
connection_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connections/{connectionName}/listsecrets')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"connectionName": _SERIALIZER.url("connection_name", connection_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,364 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_list_connections_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connections')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,365 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_list_connection_specs_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connections/specs')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,366 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_list_azure_open_ai_deployments_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
connection_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Connections/{connectionName}/AzureOpenAIDeployments')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"connectionName": _SERIALIZER.url("connection_name", connection_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,367 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_tool_setting_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Tools/setting')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,368 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_tool_meta_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
tool_name = kwargs.pop('tool_name') # type: str
tool_type = kwargs.pop('tool_type') # type: str
endpoint_name = kwargs.pop('endpoint_name', None) # type: Optional[str]
flow_runtime_name = kwargs.pop('flow_runtime_name', None) # type: Optional[str]
flow_id = kwargs.pop('flow_id', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Tools/meta')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['toolName'] = _SERIALIZER.query("tool_name", tool_name, 'str')
query_parameters['toolType'] = _SERIALIZER.query("tool_type", tool_type, 'str')
if endpoint_name is not None:
query_parameters['endpointName'] = _SERIALIZER.query("endpoint_name", endpoint_name, 'str')
if flow_runtime_name is not None:
query_parameters['flowRuntimeName'] = _SERIALIZER.query("flow_runtime_name", flow_runtime_name, 'str')
if flow_id is not None:
query_parameters['flowId'] = _SERIALIZER.query("flow_id", flow_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,369 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_tool_meta_v2_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
flow_runtime_name = kwargs.pop('flow_runtime_name', None) # type: Optional[str]
flow_id = kwargs.pop('flow_id', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Tools/meta-v2')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if flow_runtime_name is not None:
query_parameters['flowRuntimeName'] = _SERIALIZER.query("flow_runtime_name", flow_runtime_name, 'str')
if flow_id is not None:
query_parameters['flowId'] = _SERIALIZER.query("flow_id", flow_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,370 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_package_tools_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
flow_runtime_name = kwargs.pop('flow_runtime_name', None) # type: Optional[str]
flow_id = kwargs.pop('flow_id', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Tools/packageTools')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if flow_runtime_name is not None:
query_parameters['flowRuntimeName'] = _SERIALIZER.query("flow_runtime_name", flow_runtime_name, 'str')
if flow_id is not None:
query_parameters['flowId'] = _SERIALIZER.query("flow_id", flow_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,371 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_dynamic_list_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
flow_runtime_name = kwargs.pop('flow_runtime_name', None) # type: Optional[str]
flow_id = kwargs.pop('flow_id', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Tools/dynamicList')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if flow_runtime_name is not None:
query_parameters['flowRuntimeName'] = _SERIALIZER.query("flow_runtime_name", flow_runtime_name, 'str')
if flow_id is not None:
query_parameters['flowId'] = _SERIALIZER.query("flow_id", flow_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,372 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_retrieve_tool_func_result_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
flow_runtime_name = kwargs.pop('flow_runtime_name', None) # type: Optional[str]
flow_id = kwargs.pop('flow_id', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/Tools/RetrieveToolFuncResult')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
if flow_runtime_name is not None:
query_parameters['flowRuntimeName'] = _SERIALIZER.query("flow_runtime_name", flow_runtime_name, 'str')
if flow_id is not None:
query_parameters['flowId'] = _SERIALIZER.query("flow_id", flow_id, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
) | null |
4,373 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_create_flow_session_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
session_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowSessions/{sessionId}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"sessionId": _SERIALIZER.url("session_id", session_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
headers=header_parameters,
**kwargs
) | null |
4,374 | import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
def _format_url_section(template, **kwargs):
components = template.split("/")
while components:
try:
return template.format(**kwargs)
except KeyError as key:
formatted_components = template.split("/")
components = [
c for c in formatted_components if "{}".format(key.args[0]) not in c
]
template = "/".join(components)
def build_get_flow_session_request(
subscription_id, # type: str
resource_group_name, # type: str
workspace_name, # type: str
session_id, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/flow/api/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/FlowSessions/{sessionId}')
path_format_arguments = {
"subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str'),
"resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str'),
"workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str'),
"sessionId": _SERIALIZER.url("session_id", session_id, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
headers=header_parameters,
**kwargs
) | null |
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