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Merge pull request #107 from Avaiga/hotfix2.3/update-deepdiff-numpy-r…
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…equirements

Hotfix 2.3 - Update deepdiff and numpy requirements
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trgiangdo authored Jul 8, 2024
2 parents f884c33 + f688a30 commit 3ce3d65
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Showing 3 changed files with 5 additions and 84 deletions.
3 changes: 2 additions & 1 deletion Pipfile
Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,8 @@ name = "pypi"

[packages]
toml = "==0.10"
deepdiff = "==6.2.2"
deepdiff = "==6.7.1"
numpy = "<2.0.0"

[dev-packages]
black = "*"
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2 changes: 1 addition & 1 deletion setup.py
Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,7 @@
if vext := version.get("ext"):
version_string = f"{version_string}.{vext}"

requirements = ["toml>=0.10,<0.11", "deepdiff>=6.2,<6.3"]
requirements = ["toml>=0.10,<0.11", "deepdiff>=6.7,<7.0", "numpy < 2.0"]

test_requirements = ["pytest>=3.8"]

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84 changes: 2 additions & 82 deletions src/taipy/config/config.pyi
Original file line number Diff line number Diff line change
Expand Up @@ -256,30 +256,6 @@ class Config:
comparators: Optional[Dict[str, Union[List[Callable], Callable]]] = None,
**properties,
) -> "ScenarioConfig":
"""Configure the default values for scenario configurations.
This function creates the *default scenario configuration* object,
where all scenario configuration objects will find their default
values when needed.
Parameters:
pipeline_configs (List[PipelineConfig^]): The list of pipeline configurations used
by this scenario configuration.
frequency (Optional[Frequency^]): The scenario frequency.
It corresponds to the recurrence of the scenarios instantiated from this
configuration. Based on this frequency each scenario will be attached to
the relevant cycle.
comparators (Optional[Dict[str, Union[List[Callable], Callable]]]): The list of
functions used to compare scenarios. A comparator function is attached to a
scenario's data node configuration. The key of the dictionary parameter
corresponds to the data node configuration id. During the scenarios'
comparison, each comparator is applied to all the data nodes instantiated from
the data node configuration attached to the comparator. See
`taipy.compare_scenarios()^` more more details.
**properties (dict[str, any]): A keyworded variable length list of additional arguments.
Returns:
The new default scenario configuration.
"""
@staticmethod
Expand All @@ -299,47 +275,12 @@ class Config:
@staticmethod
def configure_default_pipeline(task_configs: Union[TaskConfig, List[TaskConfig]], **properties) -> "PipelineConfig":
"""Configure the default values for pipeline configurations.
This function creates the *default pipeline configuration* object,
where all pipeline configuration objects will find their default
values when needed.
Parameters:
task_configs (Union[TaskConfig^, List[TaskConfig^]]): The list of the task
configurations that make the default pipeline configuration. This can be
a single task configuration object is this pipeline holds a single task.
**properties (dict[str, any]): A keyworded variable length list of additional arguments.
Returns:
The default pipeline configuration.
"""

@staticmethod
def configure_default_data_node(
storage_type: str, scope: Optional[Scope] = None, validity_period: Optional[timedelta] = None, **properties
) -> "DataNodeConfig":
"""Configure the default values for data node configurations.
This function creates the _default data node configuration_ object,
where all data node configuration objects will find their default
values when needed.
Parameters:
storage_type (str): The default storage type for all data node configurations.
The possible values are *"pickle"* (the default value), *"csv"*, *"excel"*,
*"sql"*, *"mongo_collection"*, *"in_memory"*, *"json"*, *"parquet"* or
*"generic"*.
scope (Optional[Scope^]): The default scope for all data node configurations.<br/>
The default value is `Scope.SCENARIO`.
validity_period (Optional[timedelta]): The duration since the last edit date for which the data node can be
considered up-to-date. Once the validity period has passed, the data node is considered stale and
relevant tasks will run even if they are skippable (see the
[Task configs page](../core/config/task-config.md) for more details).
If *validity_period* is set to None, the data node is always up-to-date.
**properties (dict[str, any]): A keyworded variable length list of additional arguments.
Returns:
The default data node configuration.
"""
@classmethod
Expand All @@ -358,12 +299,12 @@ class Config:
storage_type (Optional[str]): The data node configuration storage type. The possible values
are None (which is the default value of *"pickle"*, unless it has been overloaded by the
*storage_type* value set in the default data node configuration
(see `(Config.)configure_default_data_node()^`)), *"pickle"*, *"csv"*, *"excel"*,
(see `(Config.)set_default_data_node_configuration()^`)), *"pickle"*, *"csv"*, *"excel"*,
*"sql_table"*, *"sql"*, *"json"*, *"parquet"*, *"mongo_collection"*, *"in_memory"*, or
*"generic"*.
scope (Optional[Scope^]): The scope of the data node configuration.<br/>
The default value is `Scope.SCENARIO` (or the one specified in
`(Config.)configure_default_data_node()^`).
`(Config.)set_default_data_node_configuration()^`).
validity_period (Optional[timedelta]): The duration since the last edit date for which the data node can be
considered up-to-date. Once the validity period has passed, the data node is considered stale and
relevant tasks will run even if they are skippable (see the
Expand Down Expand Up @@ -813,27 +754,6 @@ class Config:
skippable: Optional[bool] = False,
**properties,
) -> "TaskConfig":
"""Configure the default values for task configurations.
This function creates the *default task configuration* object,
where all task configuration objects will find their default
values when needed.
Parameters:
function (Callable): The python function called by Taipy to run the task.
input (Optional[Union[DataNodeConfig^, List[DataNodeConfig^]]]): The list of the
input data node configurations. This can be a unique data node
configuration if there is a single input data node, or None if there are none.
output (Optional[Union[DataNodeConfig^, List[DataNodeConfig^]]]): The list of the
output data node configurations. This can be a unique data node
configuration if there is a single output data node, or None if there are none.
skippable (bool): If True, indicates that the task can be skipped if no change has
been made on inputs.<br/>
The default value is False.
**properties (dict[str, any]): A keyworded variable length list of additional
arguments.
Returns:
The default task configuration.
"""

@staticmethod
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