Meta
Meta Examples
Examples of using the Meta class are listed at the bottom of this page Examples.
Meta: A class that provides high level information and summaries of SageWorks/AWS Artifacts. The Meta class provides 'meta' information, what account are we in, what is the current configuration, etc. It also provides metadata for AWS Artifacts, such as Data Sources, Feature Sets, Models, and Endpoints.
Meta
Meta: A class that provides Metadata for a broad set of AWS Artifacts
Common Usage
Source code in src/sageworks/api/meta.py
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|
__init__()
Meta Initialization
Source code in src/sageworks/api/meta.py
account()
Print out the AWS Account Info
Returns:
Name | Type | Description |
---|---|---|
dict |
dict
|
The AWS Account Info |
config()
Return the current SageWorks Configuration
Returns:
Name | Type | Description |
---|---|---|
dict |
dict
|
The current SageWorks Configuration |
data_source_details(data_source_name, database='sageworks', refresh=False)
Get detailed information about a specific data source in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
data_source_name
|
str
|
The name of the data source |
required |
database
|
str
|
Glue database. Defaults to 'sageworks'. |
'sageworks'
|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Name | Type | Description |
---|---|---|
dict |
Union[dict, None]
|
Detailed information about the data source (or None if not found) |
Source code in src/sageworks/api/meta.py
data_sources(refresh=False)
Get a summary of the Data Sources in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Type | Description |
---|---|
DataFrame
|
pd.DataFrame: A summary of the Data Sources in AWS |
Source code in src/sageworks/api/meta.py
data_sources_deep(database='sageworks', refresh=False)
Get a deeper set of data for the Data Sources in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
database
|
str
|
Glue database. Defaults to 'sageworks'. |
'sageworks'
|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Name | Type | Description |
---|---|---|
dict |
dict
|
Detailed information about all the Data Sources in AWS |
Source code in src/sageworks/api/meta.py
endpoints(refresh=False)
Get a summary of the Endpoints in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Type | Description |
---|---|
DataFrame
|
pd.DataFrame: A summary of the Endpoints in AWS |
Source code in src/sageworks/api/meta.py
endpoints_deep(refresh=False)
Get a deeper set of data for Endpoints in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Name | Type | Description |
---|---|---|
dict |
dict
|
A summary of the Endpoints in AWS |
Source code in src/sageworks/api/meta.py
feature_set_details(feature_set_name)
Get detailed information about a specific feature set in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
feature_set_name
|
str
|
The name of the feature set |
required |
Returns:
Name | Type | Description |
---|---|---|
dict |
dict
|
Detailed information about the feature set |
Source code in src/sageworks/api/meta.py
feature_sets(refresh=False)
Get a summary of the Feature Sets in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Type | Description |
---|---|
DataFrame
|
pd.DataFrame: A summary of the Feature Sets in AWS |
Source code in src/sageworks/api/meta.py
feature_sets_deep(refresh=False)
Get a deeper set of data for the Feature Sets in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Name | Type | Description |
---|---|---|
dict |
dict
|
A summary of the Feature Sets in AWS |
Source code in src/sageworks/api/meta.py
glue_jobs(refresh=False)
Get summary data about AWS Glue Jobs
Parameters:
Name | Type | Description | Default |
---|---|---|---|
refresh
|
bool
|
Force a refresh of the Glue Job metadata. Defaults to False. |
False
|
Returns:
Type | Description |
---|---|
DataFrame
|
pd.DataFrame: A summary of the Glue Jobs in AWS |
Source code in src/sageworks/api/meta.py
glue_jobs_deep(refresh=False)
Get a deeper set of data for the Glue Jobs in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Name | Type | Description |
---|---|---|
dict |
dict
|
A summary of the Glue Jobs in AWS |
Source code in src/sageworks/api/meta.py
incoming_data(refresh=False)
Get summary data about data in the incoming-data S3 Bucket
Parameters:
Name | Type | Description | Default |
---|---|---|---|
refresh
|
bool
|
Force a refresh of the incoming data metadata. Defaults to False. |
False
|
Returns:
Type | Description |
---|---|
DataFrame
|
pd.DataFrame: A summary of the data in the incoming-data S3 Bucket |
Source code in src/sageworks/api/meta.py
incoming_data_deep(refresh=False)
Get a deeper set of data for the Incoming Data in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Name | Type | Description |
---|---|---|
dict |
dict
|
A summary of the Incoming Data in AWS |
Source code in src/sageworks/api/meta.py
model_details(model_group_name)
Get detailed information about a specific model group in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
model_group_name
|
str
|
The name of the model group |
required |
Returns:
Name | Type | Description |
---|---|---|
dict |
dict
|
Detailed information about the model group |
Source code in src/sageworks/api/meta.py
models(refresh=False)
Get a summary of the Models in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Type | Description |
---|---|
DataFrame
|
pd.DataFrame: A summary of the Models in AWS |
Source code in src/sageworks/api/meta.py
models_deep(refresh=False)
Get a deeper set of data for Models in AWS
Args: refresh (bool, optional): Force a refresh of the metadata. Defaults to False.
Returns:
Name | Type | Description |
---|---|---|
dict |
dict
|
A summary of the Models in AWS |
Source code in src/sageworks/api/meta.py
pipelines(refresh=False)
Get a summary of the SageWorks Pipelines
Parameters:
Name | Type | Description | Default |
---|---|---|---|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Type | Description |
---|---|
DataFrame
|
pd.DataFrame: A summary of the SageWorks Pipelines |
Source code in src/sageworks/api/meta.py
refresh_all_aws_meta()
view_details(view_name, database='sageworks', refresh=False)
Get detailed information about a specific View in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
view_name
|
str
|
The name of the View |
required |
database
|
str
|
Glue database. Defaults to 'sageworks'. |
'sageworks'
|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Name | Type | Description |
---|---|---|
dict |
Union[dict, None]
|
Detailed information about the view (or None if not found) |
Source code in src/sageworks/api/meta.py
views(database='sageworks')
Get a summary of the all the Views, for the given database, in AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
database
|
str
|
Glue database. Defaults to 'sageworks'. |
'sageworks'
|
Returns:
Type | Description |
---|---|
DataFrame
|
pd.DataFrame: A summary of all the Views, for the given database, in AWS |
Source code in src/sageworks/api/meta.py
views_deep(database='sageworks', refresh=False)
Get a deeper set of data for the Views in Athena/AWS
Parameters:
Name | Type | Description | Default |
---|---|---|---|
database
|
str
|
Glue database. Defaults to 'sageworks'. |
'sageworks'
|
refresh
|
bool
|
Force a refresh of the metadata. Defaults to False. |
False
|
Returns:
Name | Type | Description |
---|---|---|
dict |
dict
|
Detailed information about all the Views in AWS |
Source code in src/sageworks/api/meta.py
Refresh
Setting refresh
to True
will lead to substantial performance issues, so don't do it :).
Examples
These example show how to use the Meta()
class to pull lists of artifacts from AWS. DataSources, FeatureSets, Models, Endpoints and more. If you're building a web interface plugin, the Meta class is a great place to start.
SageWorks REPL
If you'd like to see exactly what data/details you get back from the Meta()
class, you can spin up the SageWorks REPL, use the class and test out all the methods. Try it out! SageWorks REPL
[●●●]SageWorks:scp_sandbox> meta = Meta()
[●●●]SageWorks:scp_sandbox> model_info = meta.models()
[●●●]SageWorks:scp_sandbox> model_info
Model Group Health Owner ... Input Status Description
0 wine-classification healthy - ... wine_features Completed Wine Classification Model
1 abalone-regression-full healthy - ... abalone_features Completed Abalone Regression Model
2 abalone-regression healthy - ... abalone_features Completed Abalone Regression Model
[3 rows x 10 columns]
List the Models in AWS
from sageworks.api.meta import Meta
# Create our Meta Class and get a list of our Models
meta = Meta()
models = meta.models()
print(f"Number of Models: {len(models)}")
print(models)
# Get more details data on the Endpoints
models_groups = meta.models_deep()
for name, model_versions in models_groups.items():
print(name)
Output
Number of Models: 3
Model Group Health Owner ... Input Status Description
0 wine-classification healthy - ... wine_features Completed Wine Classification Model
1 abalone-regression-full healthy - ... abalone_features Completed Abalone Regression Model
2 abalone-regression healthy - ... abalone_features Completed Abalone Regression Model
[3 rows x 10 columns]
wine-classification
abalone-regression-full
abalone-regression
Getting Model Performance Metrics
from sageworks.api.meta import Meta
# Create our Meta Class to get metadata about our Models
meta = Meta()
model_info = meta.models_deep()
# Print out the summary of our Models
for name, info in model_info.items():
print(f"{name}")
latest = info[0] # We get a list of models, so we only want the latest
print(f"\tARN: {latest['ModelPackageGroupArn']}")
print(f"\tDescription: {latest['ModelPackageDescription']}")
print(f"\tTags: {latest['sageworks_meta']['sageworks_tags']}")
performance_metrics = latest["sageworks_meta"]["sageworks_inference_metrics"]
print(f"\tPerformance Metrics:")
print(f"\t\t{performance_metrics}")
Output
wine-classification
ARN: arn:aws:sagemaker:us-west-2:507740646243:model-package-group/wine-classification
Description: Wine Classification Model
Tags: wine::classification
Performance Metrics:
[{'wine_class': 'TypeA', 'precision': 1.0, 'recall': 1.0, 'fscore': 1.0, 'roc_auc': 1.0, 'support': 12}, {'wine_class': 'TypeB', 'precision': 1.0, 'recall': 1.0, 'fscore': 1.0, 'roc_auc': 1.0, 'support': 14}, {'wine_class': 'TypeC', 'precision': 1.0, 'recall': 1.0, 'fscore': 1.0, 'roc_auc': 1.0, 'support': 9}]
abalone-regression
ARN: arn:aws:sagemaker:us-west-2:507740646243:model-package-group/abalone-regression
Description: Abalone Regression Model
Tags: abalone::regression
Performance Metrics:
[{'MAE': 1.64, 'RMSE': 2.246, 'R2': 0.502, 'MAPE': 16.393, 'MedAE': 1.209, 'NumRows': 834}]
List the Endpoints in AWS
from sageworks.api.meta import Meta
# Create our Meta Class and get a list of our Endpoints
meta = Meta()
endpoints = meta.endpoints()
print(f"Number of Endpoints: {len(endpoints)}")
print(endpoints)
# Get more details data on the Endpoints
endpoints_deep = meta.endpoints_deep()
for name, info in endpoints_deep.items():
print(name)
print(info.keys())
Output
Number of Endpoints: 2
Name Health Instance Created ... Status Variant Capture Samp(%)
0 wine-classification-end healthy Serverless (2GB/5) 2024-03-23 23:09 ... InService AllTraffic False -
1 abalone-regression-end healthy Serverless (2GB/5) 2024-03-23 21:11 ... InService AllTraffic False -
[2 rows x 10 columns]
wine-classification-end
dict_keys(['EndpointName', 'EndpointArn', 'EndpointConfigName', 'ProductionVariants', 'EndpointStatus', 'CreationTime', 'LastModifiedTime', 'ResponseMetadata', 'InstanceType', 'sageworks_meta'])
abalone-regression-end
dict_keys(['EndpointName', 'EndpointArn', 'EndpointConfigName', 'ProductionVariants', 'EndpointStatus', 'CreationTime', 'LastModifiedTime', 'ResponseMetadata', 'InstanceType', 'sageworks_meta'])
Not Finding some particular AWS Data?
The SageWorks Meta API Class also has _details()
methods, so make sure to check those out.