taipy.config.Config

Configuration singleton.

backup(filename) classmethod

Backup a configuration.

The backup is done in a toml file.

The backed up configuration is a compilation from the three possible methods to configure the application: the python code configuration, the file configuration and the environment configuration.

Parameters:

Name	Type	Description	Default
filename	Union[str, Path]	The path of the file to export.	required

Note

If filename already exists, it is overwritten.

block_update() classmethod

Block update on the configuration signgleton.

check() classmethod

Check configuration.

This method logs issue messages and returns an issue collector.

Returns:

Type	Description
IssueCollector	Collector containing the info, warning and error issues.

configure_authentication(protocol, secret_key=None, auth_session_duration=3600, **properties) staticmethod

Configure authentication.

Parameters:

Name	Type	Description	Default
protocol	str	The name of the protocol to configure ("ldap", "taipy" or "none").	required
secret_key	str	A secret string used to internally encrypt the credentials' information. If no value is provided, the first run-time authentication sets the default value to a random text string.	None
auth_session_duration	int	How long, in seconds, are credentials valid after their creation. The default value is 3600, corresponding to an hour.	3600
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments. Depending on the protocol, these arguments are: "LDAP" protocol: the following arguments are accepted: server: the URL of the LDAP server this authenticator connects to. base_dn: the LDAP distinguished name that is used. "Taipy" protocol: the following arguments are accepted: roles: a dictionary that configures the association of usernames to roles. passwords: if required, a dictionary that configures the association of usernames to hashed passwords. A user can be authenticated if it appears at least in one of the roles or the password dictionaries. If it only appears in roles, then the user is authenticated if provided a password exactly identical to its username. If it only appears in passwords, then the user is assigned no roles. "None": No additional arguments are required.	{}

Returns:

Type	Description
	AuthenticationConfig: The authentication configuration.

configure_csv_data_node(id, default_path=None, has_header=True, exposed_type='pandas', scope=Scope.SCENARIO, **properties) staticmethod

Configure a new CSV data node configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new CSV data node configuration.	required
default_path	str	The default path of the CSV file.	None
has_header	bool	If True, indicates that the CSV file has a header.	True
exposed_type		The exposed type of the data read from CSV file. The default value is pandas.	'pandas'
scope	Scope	The scope of the CSV data node configuration. The default value is Scope.SCENARIO.	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The new CSV data node configuration.

configure_data_node(id, storage_type=None, scope=Scope.SCENARIO, **properties) staticmethod

Configure a new data node configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new data node configuration.	required
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 configure_default_data_node())), "pickle", "csv", "excel", "sql_table", "sql", "json", "parquet", "mongo_collection", "in_memory", or "generic".	None
scope	Scope	The scope of the data node configuration. The default value is Scope.SCENARIO (or the one specified in configure_default_data_node()).	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The new data node configuration.

configure_default_data_node(storage_type, scope=Scope.SCENARIO, **properties) staticmethod

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:

Name	Type	Description	Default
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".	required
scope	Scope	The default scope for all data node configurations. The default value is Scope.SCENARIO.	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The default data node configuration.

configure_default_pipeline(task_configs, **properties) staticmethod

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:

Name	Type	Description	Default
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.	required
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
PipelineConfig	PipelineConfig: The default pipeline configuration.

configure_default_scenario(pipeline_configs, frequency=None, comparators=None, **properties) staticmethod

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:

Name	Type	Description	Default
pipeline_configs	List[PipelineConfig]	The list of pipeline configurations used by this scenario configuration.	required
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.	None
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 compare_scenarios() more more details.	None
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
ScenarioConfig	ScenarioConfig: The default scenario configuration.

configure_default_task(function, input=None, output=None, skippable=False, **properties) staticmethod

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:

Name	Type	Description	Default
function	Callable	The python function called by Taipy to run the task.	required
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.	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.	None
skippable	bool	If True, indicates that the task can be skipped if no change has been made on inputs. The default value is False.	False
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
TaskConfig	TaskConfig: The default task configuration.

configure_excel_data_node(id, default_path=None, has_header=True, sheet_name=None, exposed_type='pandas', scope=Scope.SCENARIO, **properties) staticmethod

Configure a new Excel data node configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new Excel data node configuration.	required
default_path	str	The path of the Excel file.	None
has_header	bool	If True, indicates that the Excel file has a header.	True
sheet_name	Union[List[str], str]	The list of sheet names to be used. This can be a unique name.	None
exposed_type		The exposed type of the data read from Excel file. The default value is pandas.	'pandas'
scope	Scope	The scope of the Excel data node configuration. The default value is Scope.SCENARIO.	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The new CSV data node configuration.

configure_generic_data_node(id, read_fct=None, write_fct=None, read_fct_params=None, write_fct_params=None, scope=Scope.SCENARIO, **properties) staticmethod

Configure a new generic data node configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new generic data node configuration.	required
read_fct	Optional[Callable]	The Python function called to read the data.	None
write_fct	Optional[Callable]	The Python function called to write the data. The provided function must have at least one parameter that receives the data to be written.	None
read_fct_params	Optional[List]	The parameters that are passed to read_fct to read the data.	None
write_fct_params	Optional[List]	The parameters that are passed to write_fct to write the data.	None
scope	Optional[Scope]	The scope of the Generic data node configuration. The default value is Scope.SCENARIO.	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The new Generic data node configuration.

configure_global_app(root_folder=None, storage_folder=None, clean_entities_enabled=None, **properties) classmethod

Configure the global application.

Parameters:

Name	Type	Description	Default
root_folder	Optional[str]	The path of the base folder for the Taipy application.	None
storage_folder	Optional[str]	The folder name used to store Taipy data. It is used in conjunction with the root_folder field: the storage path is "".	None
clean_entities_enabled	Optional[str]	The field to activate or deactivate the 'clean entities' feature. The default value is False.	None

Returns:

Type	Description
GlobalAppConfig	The global application configuration.

configure_gui(**properties) staticmethod

Configure the Graphical User Interface.

Parameters:

Name	Type	Description	Default
**properties	Dict[str, Any]	Keyword arguments that configure the behavior of the Gui instances. Please refer to the Configuration section of the User Manual for more information on the accepted arguments.	{}

Returns:

Type	Description
	_GuiSection^: The gui configuration.

configure_in_memory_data_node(id, default_data=None, scope=Scope.SCENARIO, **properties) staticmethod

Configure a new in_memory data node configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new in_memory data node configuration.	required
default_data	Optional[Any]	The default data of the data nodes instantiated from this in_memory data node configuration.	None
scope	Scope	The scope of the in_memory data node configuration. The default value is Scope.SCENARIO.	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The new in_memory data node configuration.

configure_job_executions(mode=None, nb_of_workers=None, max_nb_of_workers=None, **properties) staticmethod

Configure job execution.

Parameters:

Name	Type	Description	Default
mode	Optional[str]	The job execution mode. Possible values are: "standalone" (the default value) or "development".	None
max_nb_of_workers	Optional[int, str]	Parameter used only in default "standalone" mode. The maximum number of jobs able to run in parallel. The default value is 1. A string can be provided to dynamically set the value using an environment variable. The string must follow the pattern: ENV[<env_var>] where <env_var> is the name of environment variable.	None
nb_of_workers	Optional[int, str]	Deprecated. Use max_nb_of_workers instead.	None

Returns:

Type	Description
JobConfig	JobConfig: The job execution configuration.

configure_json_data_node(id, default_path=None, encoder=None, decoder=None, scope=Scope.SCENARIO, **properties) staticmethod

Configure a new JSON data node configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new JSON data node configuration.	required
default_path	str	The default path of the JSON file.	None
encoder	json.JSONEncoder	The JSON encoder used to write data into the JSON file.	None
decoder	json.JSONDecoder	The JSON decoder used to read data from the JSON file.	None
scope	Scope	The scope of the JSON data node configuration. The default value is Scope.SCENARIO.	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The new JSON data node configuration.

configure_mongo_collection_data_node(id, db_name, collection_name, custom_document=DefaultCustomDocument, db_username='', db_password='', db_host='localhost', db_port=27017, db_extra_args={}, scope=Scope.SCENARIO, **properties) staticmethod

Configure a new Mongo collection data node configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new Mongo collection data node configuration.	required
db_name	str	The database name.	required
collection_name	str	The collection in the database to read from and to write the data to.	required
custom_document	Any	The custom document class to store, encode, and decode data when reading and writing to a Mongo collection. The custom_document can have optional decode method to decode data in the Mongo collection to a custom object, and encode method to encode the object's properties to the Mongo collection when writing.	DefaultCustomDocument
db_username	str	The database username.	''
db_password	str	The database password.	''
db_host	str	The database host. The default value is "localhost".	'localhost'
db_port	int	The database port. The default value is 27017.	27017
db_extra_args	Dict[str, Any]	A dictionary of additional arguments to be passed into database connection string.	{}
scope	Scope	The scope of the Mongo collection data node configuration. The default value is Scope.SCENARIO.	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The new Mongo collection data node configuration.

configure_parquet_data_node(id, default_path=None, exposed_type='pandas', engine='pyarrow', compression='snappy', read_kwargs={}, write_kwargs={}, scope=Scope.SCENARIO, **properties) staticmethod

Configure a new Parquet data node configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new Parquet data node configuration.	required
default_path	str	The default path of the Parquet file.	None
exposed_type		The exposed type of the data read from Parquet file. The default value is pandas.	'pandas'
engine	Optional[str]	Parquet library to use. Possible values are "fastparquet" or "pyarrow". The default value is "pyarrow".	'pyarrow'
compression	Optional[str]	Name of the compression to use. Use None for no compression. {'snappy', 'gzip', 'brotli', None}, default 'snappy'.	'snappy'
read_kwargs	Optional[Dict]	Additional parameters passed to the pandas.read_parquet method.	{}
write_kwargs	Optional[Dict]	Additional parameters passed to the pandas.DataFrame.write_parquet method. The parameters in "read_kwargs" and "write_kwargs" have a higher precedence than the top-level parameters which are also passed to Pandas.	{}
scope	Scope	The scope of the Parquet data node configuration. The default value is Scope.SCENARIO.	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The new Parquet data node configuration.

configure_pickle_data_node(id, default_data=None, scope=Scope.SCENARIO, **properties) staticmethod

Configure a new pickle data node configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new pickle data node configuration.	required
default_data	Optional[Any]	The default data of the data nodes instantiated from this pickle data node configuration.	None
scope	Scope	The scope of the pickle data node configuration. The default value is Scope.SCENARIO.	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The new pickle data node configuration.

configure_pipeline(id, task_configs, **properties) staticmethod

Configure a new pipeline configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new pipeline configuration.	required
task_configs	Union[TaskConfig, List[TaskConfig]]	The list of the task configurations that make this new pipeline. This can be a single task configuration object is this pipeline holds a single task.	required
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
PipelineConfig	PipelineConfig: The new pipeline configuration.

configure_scenario(id, pipeline_configs, frequency=None, comparators=None, **properties) staticmethod

Configure a new scenario configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new scenario configuration.	required
pipeline_configs	List[PipelineConfig]	The list of pipeline configurations used by this new scenario configuration.	required
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.	None
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 compare_scenarios() more more details.	None
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
ScenarioConfig	ScenarioConfig: The new scenario configuration.

configure_scenario_from_tasks(id, task_configs, frequency=None, comparators=None, pipeline_id=None, **properties) staticmethod

Configure a new scenario configuration made of a single new pipeline configuration.

A new pipeline configuration is created as well. If pipeline_id is not provided, the new pipeline configuration identifier is set to the scenario configuration identifier post-fixed by '_pipeline'.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the scenario configuration.	required
task_configs	List[TaskConfig]	The list of task configurations used by the new pipeline configuration that is created.	required
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.	None
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.	None
pipeline_id	str	The identifier of the new pipeline configuration to be configured.	None
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
ScenarioConfig	ScenarioConfig: The new scenario configuration.

configure_sql_data_node(id, db_username, db_password, db_name, db_engine, db_port=1433, db_host='localhost', db_driver='ODBC Driver 17 for SQL Server', db_extra_args=None, read_query=None, write_query_builder=None, exposed_type='pandas', scope=Scope.SCENARIO, **properties) staticmethod

Configure a new SQL data node configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new SQL data node configuration.	required
db_username	str	The database username.	required
db_password	str	The database password.	required
db_name	str	The database name.	required
db_engine	str	The database engine. Possible values are "sqlite", "mssql", "mysql", or "postgresql".	required
db_port	int	The database port. The default value is 1433.	1433
db_host	str	The database host. The default value is "localhost".	'localhost'
db_driver	str	The database driver. The default value is "ODBC Driver 17 for SQL Server".	'ODBC Driver 17 for SQL Server'
db_extra_args	Dict[str, Any]	A dictionary of additional arguments to be passed into database connection string.	None
read_query	str	The SQL query string used to read the data from the database.	None
write_query_builder	Callable	A callback function that takes the data as an input parameter and returns a list of SQL queries.	None
exposed_type		The exposed type of the data read from SQL query. The default value is pandas.	'pandas'
scope	Scope	The scope of the SQL data node configuration. The default value is Scope.SCENARIO.	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The new SQL data node configuration.

configure_sql_table_data_node(id, db_username, db_password, db_name, db_engine, table_name=None, db_port=1433, db_host='localhost', db_driver='ODBC Driver 17 for SQL Server', db_extra_args=None, exposed_type='pandas', scope=Scope.SCENARIO, **properties) staticmethod

Configure a new SQL table data node configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of the new SQL data node configuration.	required
db_username	str	The database username.	required
db_password	str	The database password.	required
db_name	str	The database name.	required
db_host	str	The database host. The default value is "localhost".	'localhost'
db_engine	str	The database engine. Possible values are "sqlite", "mssql", "mysql", or "postgresql".	required
db_driver	str	The database driver. The default value is "ODBC Driver 17 for SQL Server".	'ODBC Driver 17 for SQL Server'
db_port	int	The database port. The default value is 1433.	1433
db_extra_args	Dict[str, Any]	A dictionary of additional arguments to be passed into database connection string.	None
table_name	str	The name of the SQL table.	None
exposed_type		The exposed type of the data read from SQL query. The default value is pandas.	'pandas'
scope	Scope	The scope of the SQL data node configuration. The default value is Scope.SCENARIO.	Scope.SCENARIO
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
DataNodeConfig	DataNodeConfig: The new SQL data node configuration.

configure_task(id, function, input=None, output=None, skippable=False, **properties) staticmethod

Configure a new task configuration.

Parameters:

Name	Type	Description	Default
id	str	The unique identifier of this task configuration.	required
function	Callable	The python function called by Taipy to run the task.	required
input	Optional[Union[DataNodeConfig, List[DataNodeConfig]]]	The list of the function 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.	None
output	Optional[Union[DataNodeConfig, List[DataNodeConfig]]]	The list of the function 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.	None
skippable	bool	If True, indicates that the task can be skipped if no change has been made on inputs. The default value is False.	False
**properties	Dict[str, Any]	A keyworded variable length list of additional arguments.	{}

Returns:

Type	Description
TaskConfig	TaskConfig: The new task configuration.

data_nodes()

Return all data node configurations grouped by id in a dictionary.

Config.data_nodes() is an alias for Config.sections["DATA_NODE"]

export(filename) classmethod

Export a configuration.

The export is done in a toml file.

The exported configuration is taken from the python code configuration.

Parameters:

Name	Type	Description	Default
filename	Union[str, Path]	The path of the file to export.	required

Note

If filename already exists, it is overwritten.

global_config()

Return configuration values related to the global application as a GlobalAppConfig.

job_config()

Return the job execution configuration JobConfig.

load(filename) classmethod

Load a configuration file to replace the current python config and trigger the Config compilation.

Parameters:

Name	Type	Description	Default
filename	Union[str, Path]	The path of the toml configuration file to load.	required

override(filename) classmethod

Load a configuration from a file and overrides the current config.

Parameters:

Name	Type	Description	Default
filename	Union[str, Path]	The path of the toml configuration file to load.	required

pipelines()

Return all pipeline configurations grouped by id in a dictionary.

Config.pipelines() is an alias for Config.sections["PIPELINE"]

restore(filename) classmethod

Restore a configuration file and replace the current applied configuration.

Parameters:

Name	Type	Description	Default
filename	Union[str, Path]	The path of the toml configuration file to load.	required

scenarios()

Return all scenario configurations grouped by id in a dictionary.

Config.scenarios() is an alias for Config.sections["SCENARIO"]

sections()

Return all non unique sections.

tasks()

Return all task configurations grouped by id in a dictionary.

Config.tasks() is an alias for Config.sections["TASK"]

unblock_update() classmethod

Unblock update on the configuration signgleton.

unique_sections()

Return all unique sections.