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SIENTIAPDE-1081

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Enhance documentation across multiple modules with detailed parameter descriptions and usage examples
This commit is contained in:
vitor-aignosi
2025-05-26 16:45:50 -03:00
parent 5326051714
commit 10081b71d2
12 changed files with 294 additions and 92 deletions
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58
laborious/activities/gates.py
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@@ -55,13 +55,13 @@ class Gates(BaseActivity):
Filters the data based on the filters. The return value is a tuple with the first element
being the policy and the second element being the confidence status.
Args:
input_data (dict): The input data. Contains:
filters (dict): The filters to apply.
- input_data (dict): The input data. Contains:
- filters (dict): The filters to apply.
The key is the filter name and the value is the filter configuration.
data (dict[str, Any]): The data to filter.
path_priority (list[str]): The path priority.
- data (dict[str, Any]): The data to filter.
- path_priority (list[str]): The path priority.
Returns:
tuple[str | None, int, str]: (policy, confidence) based in priority
tuple[str | None, int, str]: (policy, confidence, comments) based in priority
list and filter configuration and functions.
"""
@@ -111,13 +111,13 @@ class Gates(BaseActivity):
The return value is a tuple with the first element
being the policy and the second element being the confidence status.
Args:
input_data (dict): The input data. Contains:
filters (dict): The filter configuration to apply.
data (dict[str, Any]): The data to filter.
path_priority (list[str]): The path priority list.
type (str): The type of the gate.
- input_data (dict): The input data. Contains:
- filters (dict): The filter configuration to apply.
- data (dict[str, Any]): The data to filter.
- path_priority (list[str]): The path priority list.
- type (str): The type of the gate.
Returns:
tuple[str | None, int, str]: (policy, confidence) based in priority list
tuple[str | None, int, str]: (policy, confidence, comments) based in priority list
and filter configuration and functions.
"""
@@ -174,13 +174,13 @@ class Gates(BaseActivity):
The return value is a tuple with the first element
being the policy and the second element being the confidence status.
Args:
input_data (dict): The input data. Contains:
filters (dict): The filter configuration to apply.
data (dict[str, Any]): The data to filter.
path_priority (list[str]): The path priority list.
type (str): The type of the gate.
- input_data (dict): The input data. Contains:
- filters (dict): The filter configuration to apply.
- data (dict[str, Any]): The data to filter.
- path_priority (list[str]): The path priority list.
- type (str): The type of the gate.
Returns:
tuple[str | None, int, str]: (policy, confidence) based in priority
tuple[str | None, int, str]: (policy, confidence, comments) based in priority
list and filter configuration and functions.
"""
@@ -233,11 +233,11 @@ class Gates(BaseActivity):
"""
Formats the prediction data.
Args:
input_data (dict): The input data. Contains:
data (dict[str, Any]): The data to format.
timestamp (str): The timestamp of the data.
model_id (str): The id of the model.
prediction_confidence (float): The confidence of the prediction.
- input_data (dict): The input data. Contains:
- data (dict[str, Any]): The data to format.
- timestamp (str): The timestamp of the data.
- model_id (str): The id of the model.
- prediction_confidence (float): The confidence of the prediction.
Returns:
dict: The formatted data.
"""
@@ -260,11 +260,11 @@ class Gates(BaseActivity):
and usefull information in the other fields.
Args:
input_data (dict): The input data. Contains:
timestamp (str): The timestamp of the data.
model_id (str): The id of the model.
prediction_confidence (float): The confidence of the prediction.
comment (str): The comment of the prediction.
- input_data (dict): The input data. Contains:
- timestamp (str): The timestamp of the data.
- model_id (str): The id of the model.
- prediction_confidence (float): The confidence of the prediction.
- comment (str): The comment of the prediction.
Returns:
dict: The formatted data.
"""
@@ -286,8 +286,8 @@ class Gates(BaseActivity):
"""
Gets the last timestamp of the data.
Args:
input_data (dict): The input data. Contains:
data (dict[str, Any]): The data to get the last timestamp from.
- input_data (dict): The input data. Contains:
- data (dict[str, Any]): The data to get the last timestamp from.
Returns:
str: The last timestamp of the data.
"""

16
laborious/activities/mlflow.py
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@@ -29,10 +29,10 @@ class MLFlow(BaseActivity):
"""
Access MLFlow model to get the transformed data.
Args:
input_data (dict): The input data. Contains:
data (dict[str, Any]): The data to transform.
model_name (str): The name of the model.
model_retention (int): The retention of the model in minutes.
- input_data (dict): The input data. Contains:
- data (dict[str, Any]): The data to transform.
- model_name (str): The name of the model.
- model_retention (int): The retention time of the model, in minutes.
Returns:
dict[str, Any]: The transformed data.
"""
@@ -67,10 +67,10 @@ class MLFlow(BaseActivity):
"""
Access MLFlow model to get the predicted data.
Args:
input_data (dict): The input data. Contains:
data (dict[str, Any]): The data to predict.
model_name (str): The name of the model.
model_retention (int): The retention of the model.
- input_data (dict): The input data. Contains:
- data (dict[str, Any]): The data to predict.
- model_name (str): The name of the model.
- model_retention (int): The retention time of the model, in minutes.
Returns:
dict[str, Any]: The predicted data.
"""

22
laborious/activities/opc.py
View File

@@ -39,6 +39,17 @@ class OPC(BaseActivity):
def write_data(self, server: str, tag: str, data: Any,
data_type: str, tag_type: str):
"""
Write data to OPC server.
Args:
- server (str): The name of the OPC server.
- tag (str): The tag to write to.
- data (Any): The data to write.
- data_type (str): The data type.
- tag_type (str): The tag type.
"""
try:
self.opc_repository[server].write_data(
tag, data, data_type)
@@ -61,15 +72,14 @@ class OPC(BaseActivity):
operations are optional and independent of each other.
Args:
input_data (dict[str, Any]): The input data. Contains the following keys:
- data (dict[str, Any]): The dataframe that contains the data to write
- input_data(dict[str, Any]): The input data. Contains the following keys:
- data(dict[str, Any]): The dataframe that contains the data to write
to the OPC servers.
- opc_output_config (dict[str, Any]): The OPC writing configuration.
- opc_output_config(dict[str, Any]): The OPC writing configuration.
The keys are the OPC server names and the values contain:
prediction_tags (dict[str, Any]): The tags to write to the OPC servers.
confidence_tags (dict[str, Any]): The tags to write to the OPC servers.
- prediction_tags(dict[str, Any]): The tags to write to the OPC servers.
- confidence_tags(dict[str, Any]): The tags to write to the OPC servers.
Returns:
"""
self.logger.debug("Writing data to OPC servers...")
data = DataFrame(input_data['data'])