updated pycaret-nightly==0.19

.gitignore

@@ -17,3 +17,4 @@ catboost_info
 /pycaret.egg-info
 /dist
 .vscode/settings.json
+/logs.log
\ No newline at end of file

pycaret/anomaly.py

@@ -35,8 +35,8 @@ def setup(data,
           n_jobs = -1, #added in pycaret==2.0.0
           html = True, #added in pycaret==2.0.0
           session_id = None,
+          log_experiment = False, #added in pycaret==2.0.0
           experiment_name = None, #added in pycaret==2.0.0
-          logging = False, #added in pycaret==2.0.0
           log_plots = False, #added in pycaret==2.0.0
           log_profile = False, #added in pycaret==2.0.0
           log_data = False, #added in pycaret==2.0.0
@@ -252,12 +252,12 @@ def setup(data,
     unique number is then distributed as a seed in all functions used during the 
     experiment. This can be used for later reproducibility of the entire experiment.
     
+    log_experiment: bool, default = True
+    When set to True, all metrics and parameters are logged on MLFlow server.
+
     experiment_name: str, default = None
     Name of experiment for logging. When set to None, 'clf' is by default used as 
-    alias for the experiment name.
-
-    logging: bool, default = True
-    When set to True, all metrics and parameters are logged on MLFlow server.
+    alias for the experiment name.    
 
     log_plots: bool, default = False
     When set to True, specific plots are logged in MLflow as a png file. By default,
@@ -491,9 +491,9 @@ def setup(data,
     if type(html) is not bool:
         sys.exit('(Type Error): html parameter only accepts True or False.')
 
-    #logging
-    if type(logging) is not bool:
-        sys.exit('(Type Error): logging parameter only accepts True or False.')
+    #log_experiment
+    if type(log_experiment) is not bool:
+        sys.exit('(Type Error): log_experiment parameter only accepts True or False.')
 
     #log_plots
     if type(log_plots) is not bool:
@@ -897,7 +897,7 @@ def setup(data,
     n_jobs_param = n_jobs
 
     #create logging parameter
-    logging_param = logging
+    logging_param = log_experiment
 
     #create exp_name_log param incase logging is False
     exp_name_log = 'no_logging'

pycaret/clustering.py

@@ -35,8 +35,8 @@ def setup(data,
         n_jobs = -1, #added in pycaret==2.0.0
         html = True, #added in pycaret==2.0.0
         session_id = None,
+        log_experiment = False, #added in pycaret==2.0.0
         experiment_name = None, #added in pycaret==2.0.0
-        logging = False, #added in pycaret==2.0.0
         log_plots = False, #added in pycaret==2.0.0
         log_profile = False, #added in pycaret==2.0.0
         log_data = False, #added in pycaret==2.0.0
@@ -256,7 +256,7 @@ def setup(data,
     Name of experiment for logging. When set to None, 'clf' is by default used as 
     alias for the experiment name.
 
-    logging: bool, default = True
+    log_experiment: bool, default = True
     When set to True, all metrics and parameters are logged on MLFlow server.
 
     log_plots: bool, default = False
@@ -491,9 +491,9 @@ def setup(data,
     if type(html) is not bool:
         sys.exit('(Type Error): html parameter only accepts True or False.')
 
-    #logging
-    if type(logging) is not bool:
-        sys.exit('(Type Error): logging parameter only accepts True or False.')
+    #log_experiment
+    if type(log_experiment) is not bool:
+        sys.exit('(Type Error): log_experiment parameter only accepts True or False.')
 
     #log_plots
     if type(log_plots) is not bool:
@@ -892,7 +892,7 @@ def setup(data,
     n_jobs_param = n_jobs
 
     #create logging parameter
-    logging_param = logging
+    logging_param = log_experiment
 
     #create exp_name_log param incase logging is False
     exp_name_log = 'no_logging'

pycaret/nlp.py

@@ -9,8 +9,8 @@ def setup(data,
           custom_stopwords=None,
           html = True, #added in pycaret==2.0.0
           session_id = None,
+          log_experiment = False, #added in pycaret==2.0.0
           experiment_name = None, #added in pycaret==2.0.0
-          logging = False, #added in pycaret==2.0.0
           log_plots = False, #added in pycaret==2.0.0
           log_data = False, #added in pycaret==2.0.0)
           verbose = True): #added in pycaret==2.0.0)
@@ -56,13 +56,13 @@ def setup(data,
     unique number is then distributed as a seed in all functions used during the 
     experiment. This can be used for later reproducibility of the entire experiment.
 
+    log_experiment: bool, default = True
+    When set to True, all metrics and parameters are logged on MLFlow server.
+
     experiment_name: str, default = None
     Name of experiment for logging. When set to None, 'clf' is by default used as 
     alias for the experiment name.
 
-    logging: bool, default = True
-    When set to True, all metrics and parameters are logged on MLFlow server.
-
     log_plots: bool, default = False
     When set to True, specific plots are logged in MLflow as a png file. By default,
     it is set to False. 
@@ -149,9 +149,9 @@ def setup(data,
     if type(html) is not bool:
         sys.exit('(Type Error): html parameter only accepts True or False.')
 
-    #logging
-    if type(logging) is not bool:
-        sys.exit('(Type Error): logging parameter only accepts True or False.')
+    #log_experiment
+    if type(log_experiment) is not bool:
+        sys.exit('(Type Error): log_experiment parameter only accepts True or False.')
 
     #log_plots
     if type(log_plots) is not bool:
@@ -265,7 +265,7 @@ def setup(data,
         data_ = data.copy()
     
     #create logging parameter
-    logging_param = logging
+    logging_param = log_experiment
 
     #create exp_name_log param incase logging is False
     exp_name_log = 'no_logging'

pycaret/regression.py

@@ -56,8 +56,8 @@ def setup(data,
           n_jobs = -1, #added in pycaret==2.0.0
           html = True, #added in pycaret==2.0.0
           session_id = None,
+          log_experiment = False, #added in pycaret==2.0.0
           experiment_name = None, #added in pycaret==2.0.0
-          logging = False, #added in pycaret==2.0.0
           log_plots = False, #added in pycaret==2.0.0
           log_profile = False, #added in pycaret==2.0.0
           log_data = False, #added in pycaret==2.0.0
@@ -395,13 +395,13 @@ def setup(data,
     be performed assuming automatically inferred data types. Not recommended for direct use 
     except for established pipelines.
 
+    log_experiment: bool, default = False
+    When set to True, all metrics and parameters are logged on MLFlow server.
+
     experiment_name: str, default = None
     Name of experiment for logging. When set to None, 'clf' is by default used as 
     alias for the experiment name.
 
-    logging: bool, default = False
-    When set to True, all metrics and parameters are logged on MLFlow server.
-
     log_plots: bool, default = False
     When set to True, specific plots are logged in MLflow as a png file. By default,
     it is set to False. 
@@ -676,7 +676,6 @@ def setup(data,
     if type(interaction_threshold) is not float:
         sys.exit('(Type Error): interaction_threshold must be a float between 0 and 1. ')      
 
-
     #cannot drop target
     if ignore_features is not None:
         if target in ignore_features:
@@ -730,9 +729,9 @@ def setup(data,
     if type(data_split_shuffle) is not bool:
         sys.exit('(Type Error): data_split_shuffle parameter only accepts True or False.')
 
-    #logging
-    if type(logging) is not bool:
-        sys.exit('(Type Error): logging parameter only accepts True or False.')
+    #log_experiment
+    if type(log_experiment) is not bool:
+        sys.exit('(Type Error): log_experiment parameter only accepts True or False.')
 
     #log_plots
     if type(log_plots) is not bool:
@@ -1237,7 +1236,7 @@ def setup(data,
     display_container = []
 
     #create logging parameter
-    logging_param = logging
+    logging_param = log_experiment
 
     #create exp_name_log param incase logging is False
     exp_name_log = 'no_logging'

pycaret/utils.py

@@ -2,9 +2,13 @@
 # Author: Moez Ali <moez.ali@queensu.ca>
 # License: MIT
 
+version_ = "pycaret-nightly-0.19"
+
 def version():
-    print("pycaret-nightly-0.19")
+    print(version_)
 
+def __version__():
+    return version_
 
 def check_metric(actual, prediction, metric, round=4):