pycaret-nightly==0.27 update part 1

pycaret/anomaly.py

@@ -3501,9 +3501,6 @@ def models():
     
     """
 
-    import logging
-    logger.info("Initializing models()")
-
     import pandas as pd
 
     model_id = ['abod', 'iforest', 'cluster', 'cof', 'histogram', 'knn', 'lof', 'svm', 'pca', 'mcd', 'sod', 'sos']
@@ -3540,8 +3537,6 @@ def models():
 
     df.set_index('ID', inplace=True)
 
-    logger.info("models() succesfully completed")
-
     return df
 
 def get_logs(experiment_name = None, save = False):
@@ -3570,9 +3565,6 @@ def get_logs(experiment_name = None, save = False):
     
     """
 
-    import logging
-    logger.info("Initializing get_logs()")
-
     import sys
 
     if experiment_name is None:
@@ -3586,20 +3578,15 @@ def get_logs(experiment_name = None, save = False):
     client = MlflowClient()
 
     if client.get_experiment_by_name(exp_name_log_) is None:
-        logger.info("No active run found.")
         sys.exit('No active run found. Check logging parameter in setup or to get logs for inactive run pass experiment_name.')
     
     exp_id = client.get_experiment_by_name(exp_name_log_).experiment_id    
-    logger.info("Searching runs")
     runs = mlflow.search_runs(exp_id)
 
     if save:
-        logger.info("Saving logs as csv")
         file_name = str(exp_name_log_) + '_logs.csv'
         runs.to_csv(file_name, index=False)
 
-    logger.info("get_logs() succesfully completed")
-
     return runs
 
 def get_config(variable):

pycaret/clustering.py

@@ -3757,9 +3757,6 @@ def models():
         models and their metadata.     
     
     """
-    
-    import logging
-    logger.info("Initializing models()")
 
     import pandas as pd
 
@@ -3791,8 +3788,6 @@ def models():
 
     df.set_index('ID', inplace=True)
 
-    logger.info("models() succesfully completed")
-
     return df
 
 def get_logs(experiment_name = None, save = False):
@@ -3821,9 +3816,6 @@ def get_logs(experiment_name = None, save = False):
     
     """
 
-    import logging
-    logger.info("Initializing get_logs()")
-
     import sys
 
     if experiment_name is None:
@@ -3837,20 +3829,15 @@ def get_logs(experiment_name = None, save = False):
     client = MlflowClient()
 
     if client.get_experiment_by_name(exp_name_log_) is None:
-        logger.info("No active run found.")
         sys.exit('No active run found. Check logging parameter in setup or to get logs for inactive run pass experiment_name.')
     
     exp_id = client.get_experiment_by_name(exp_name_log_).experiment_id    
-    logger.info("Searching runs")
     runs = mlflow.search_runs(exp_id)
 
     if save:
-        logger.info("Saving logs as csv")
         file_name = str(exp_name_log_) + '_logs.csv'
         runs.to_csv(file_name, index=False)
 
-    logger.info("get_logs() succesfully completed")
-
     return runs
 
 def get_config(variable):

pycaret/regression.py

@@ -9577,9 +9577,6 @@ def models(type=None):
     
     """
 
-    import logging
-    logger.info("Initializing models()")
-
     import pandas as pd
 
     model_id = ['lr', 'lasso', 'ridge', 'en', 'lar', 'llar', 'omp', 'br', 'ard', 'par', 
@@ -9660,8 +9657,6 @@ def models(type=None):
     if type == 'ensemble':
         df = df[df.index.isin(ensemble_models)]
 
-    logger.info("models() succesfully completed")
-
     return df
 
 def get_logs(experiment_name = None, save = False):
@@ -9690,9 +9685,6 @@ def get_logs(experiment_name = None, save = False):
     
     """
     
-    import logging
-    logger.info("Initializing get_logs()")
-
     import sys
 
     if experiment_name is None:
@@ -9703,24 +9695,18 @@ def get_logs(experiment_name = None, save = False):
     import mlflow
     from mlflow.tracking import MlflowClient
     
-    logger.info("Importing MLFlow Client")
     client = MlflowClient()
 
     if client.get_experiment_by_name(exp_name_log_) is None:
-        logger.info("No active run found.")
         sys.exit('No active run found. Check logging parameter in setup or to get logs for inactive run pass experiment_name.')
     
     exp_id = client.get_experiment_by_name(exp_name_log_).experiment_id    
-    logger.info("Searching runs")
     runs = mlflow.search_runs(exp_id)
 
     if save:
-        logger.info("Saving logs as csv")
         file_name = str(exp_name_log_) + '_logs.csv'
         runs.to_csv(file_name, index=False)
 
-    logger.info("get_logs() succesfully completed")
-
     return runs
 
 def get_config(variable):

pycaret/utils.py

@@ -2,7 +2,7 @@
 # Author: Moez Ali <moez.ali@queensu.ca>
 # License: MIT
 
-version_ = "pycaret-nightly-0.26"
+version_ = "pycaret-nightly-0.27"
 
 def version():
     print(version_)

setup.py

@@ -13,7 +13,7 @@ with open('requirements.txt') as f:
 
 setup(
     name="pycaret-nightly",
-    version="0.26",
+    version="0.27",
     description="Nightly build of PyCaret - An open source, low-code machine learning library in Python.",
     long_description=readme(),
     long_description_content_type="text/markdown",