update everything to use python 3.11

data/any_env.py

@@ -12,7 +12,7 @@ def create_data(X=None):
     @staticmethod
     def create_data_popen(X=None):
         # Specify the python package dependencies.  Will be installed in order of list
-        pyversion = "3.8"
+        pyversion = "3.11"
         _install_h2oaicore = False
         _install_datatable = True
         _modules_needed_by_name = ["pandas==1.5.3"]

data/any_env2.py

@@ -4,7 +4,7 @@
 import functools
 
 
-def wrap_create(pyversion="3.8", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=[],
+def wrap_create(pyversion="3.11", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=[],
                 cache_env=False, file=None, id=None,
                 **kwargs_wrapper):
     """ Decorate a function to create_data in popen in isolated env
@@ -23,7 +23,7 @@ def wrapper(*args, **kwargs):
     return actual_decorator
 
 
-def create_data_popen(func, *args, pyversion="3.8", install_h2oaicore=False, install_datatable=True,
+def create_data_popen(func, *args, pyversion="3.11", install_h2oaicore=False, install_datatable=True,
                       modules_needed_by_name=[], cache_env=False, file=None, id=None,
                       X=None, **kwargs):
     """ Run recipe in popen in isolated env
@@ -119,9 +119,9 @@ class FreshEnvData(CustomData):
     # NOTE: Keep @wrap_create on a single line
     # NOTE: If want to share cache across recipes, can set cache_env=True and set id=<some unique identifier, like myrecipe12345>
     # Below caches the env into "id" folder
-    # @wrap_create(pyversion="3.8", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=["pandas==1.5.3"], cache_env=True, file=__file__, id="myrecipe12345")
+    # @wrap_create(pyversion="3.11", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=["pandas==1.5.3"], cache_env=True, file=__file__, id="myrecipe12345")
     # Below does not cache the env
-    @wrap_create(pyversion="3.8", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=["pandas==1.5.3"], file=__file__)
+    @wrap_create(pyversion="3.11", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=["pandas==1.5.3"], file=__file__)
     def create_data(X=None):
         import os
         import datatable as dt

data/any_env3.py

@@ -10,9 +10,9 @@ class FreshEnvData(CustomData):
     # NOTE: Keep @wrap_create on a single line
     # NOTE: If want to share cache across recipes, can set cache_env=True and set id=<some unique identifier, like myrecipe12345>
     # Below caches the env into "id" folder
-    # @wrap_create(pyversion="3.6", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=["pandas==1.5.3"], cache_env=True, file=__file__, id="myrecipe12345")
+    # @wrap_create(pyversion="3.11", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=["pandas==1.5.3"], cache_env=True, file=__file__, id="myrecipe12345")
     # Below does not cache the env
-    @wrap_create(pyversion="3.8", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=["pandas==1.5.3"], file=__file__)
+    @wrap_create(pyversion="3.11", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=["pandas==1.5.3"], file=__file__)
     def create_data(X=None):
         import os
         import datatable as dt

data/any_env4.py

@@ -6,9 +6,9 @@
 class FreshEnvData(CustomData):
     # Specify the python package dependencies.  Will be installed in order of list
     # Below caches the env into "id" folder
-    # isolate_env = dict(pyversion="3.6", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=["pandas==1.5.3"], cache_env=True, id="myrecipe12345")
+    # isolate_env = dict(pyversion="3.11", install_h2oaicore=False, install_datatable=True, modules_needed_by_name=["pandas==1.5.3"], cache_env=True, id="myrecipe12345")
     # Below does not cache the env
-    isolate_env = dict(pyversion="3.8", install_h2oaicore=False, install_datatable=True,
+    isolate_env = dict(pyversion="3.11", install_h2oaicore=False, install_datatable=True,
                        modules_needed_by_name=["pandas==1.5.3"])
 
     @staticmethod

models/algorithms/autogluon.py

@@ -27,7 +27,7 @@ class AutoGluonModel(CustomModel):
 
     # autogluon depends upon slightly different package versions than DAI has, or could work with xgboost but needs official xgboost <1.5
     # so use isolated env
-    isolate_env = dict(pyversion="3.8", install_h2oaicore=False, install_datatable=True, cache_env=True,
+    isolate_env = dict(pyversion="3.11", install_h2oaicore=False, install_datatable=True, cache_env=True,
                        cache_by_full_module_name=False, install_pip="latest",
                        modules_needed_by_name=['autogluon==0.3.1'])