Merge pull request #374 from mindsdb/staging

Release 0.14.0

.github/workflows/pypi.yml

@@ -10,8 +10,8 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [ubuntu-latest, windows-latest, macos-latest]
-        python-version: [3.7, 3.8]
+        os: [ubuntu-latest, windows-latest]
+        python-version: [3.8, 3.9]
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}
@@ -38,7 +38,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v2
         with:
-          python-version: 3.7
+          python-version: 3.8
       - name: build wheel
         run: |
           pip install wheel

.github/workflows/test.yml

@@ -10,8 +10,8 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [ubuntu-latest, windows-latest, macos-latest]
-        python-version: [3.7,3.8,3.9]
+        os: [ubuntu-latest, windows-latest]
+        python-version: [3.8,3.9,'3.10']
     steps:
     - uses: actions/checkout@v2
     - name: Set up Python ${{ matrix.python-version }}

mindsdb_sql/__about__.py

@@ -1,6 +1,6 @@
 __title__ = 'mindsdb_sql'
 __package_name__ = 'mindsdb_sql'
-__version__ = '0.13.0'
+__version__ = '0.14.0'
 __description__ = "Pure python SQL parser"
 __email__ = "[email protected]"
 __author__ = 'MindsDB Inc'

mindsdb_sql/parser/dialects/mindsdb/create_predictor.py

@@ -11,7 +11,6 @@ def __init__(self,
                  targets=None,
                  integration_name=None,
                  query_str=None,
-                 datasource_name=None,
                  order_by=None,
                  group_by=None,
                  window=None,
@@ -26,7 +25,6 @@ def __init__(self,
         self.integration_name = integration_name
         self.query_str = query_str
         self.targets = targets
-        self.datasource_name = datasource_name
         self.order_by = order_by
         self.group_by = group_by
         self.window = window
@@ -50,10 +48,6 @@ def to_tree(self, *args, level=0, **kwargs):
 
         query_str = f'\n{ind1}query={self.query_str},'
 
-        datasource_name_str = ''
-        if self.datasource_name:
-            datasource_name_str = f'\n{ind1}datasource_name={self.datasource_name.to_tree()},'
-
         if self.targets is not None:
             target_trees = ',\n'.join([t.to_tree(level=level+2) for t in self.targets])
             targets_str = f'\n{ind1}targets=[\n{target_trees}\n{ind1}],'
@@ -83,7 +77,6 @@ def to_tree(self, *args, level=0, **kwargs):
                   f'{name_str}' \
                   f'{integration_name_str}' \
                   f'{query_str}' \
-                  f'{datasource_name_str}' \
                   f'{targets_str}' \
                   f'{order_by_str}' \
                   f'{group_by_str}' \
@@ -119,22 +112,20 @@ def get_string(self, *args, **kwargs):
                 using_ar.append(f'{Identifier(key).to_string()}={value}')
 
             using_str = f'USING ' + ', '.join(using_ar)
-        datasource_name_str = f'AS {self.datasource_name.to_string()} ' if self.datasource_name is not None else ''
 
         query_str = ''
         if self.query_str is not None:
-            query_str = f'({self.query_str}) '
+            integration_name_str = ''
+            if self.integration_name is not None:
+                integration_name_str = f' {self.integration_name.to_string()}'
 
-        integration_name_str = ''
-        if self.integration_name is not None:
-            integration_name_str = f'FROM {self.integration_name.to_string()} '
+            query_str = f'FROM{integration_name_str} ({self.query_str}) '
 
         or_replace_str = ' OR REPLACE' if self.is_replace else ''
         if_not_exists_str = 'IF NOT EXISTS ' if self.if_not_exists else ''
         object_str = self._object + ' ' if self._object else ''
 
-        out_str = f'{self._action}{or_replace_str} {object_str}{if_not_exists_str}{self.name.to_string()} {integration_name_str}{query_str}' \
-                  f'{datasource_name_str}' \
+        out_str = f'{self._action}{or_replace_str} {object_str}{if_not_exists_str}{self.name.to_string()} {query_str}' \
                   f'{targets_str} ' \
                   f'{order_by_str}' \
                   f'{group_by_str}' \
@@ -148,7 +139,7 @@ def get_string(self, *args, **kwargs):
 class CreatePredictor(CreatePredictorBase):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
-        self._object = 'PREDICTOR'
+        self._object = 'MODEL'
 
 
 # Models by task type

mindsdb_sql/parser/dialects/mindsdb/parser.py

@@ -365,22 +365,25 @@ def set_item_list(self, p):
     # set names
     @_('id id',
        'id constant',
+       'id identifier',
        'id id COLLATE constant',
        'id id COLLATE id',
        'id constant COLLATE constant',
        'id constant COLLATE id')
     def set_item(self, p):
         category = p[0]
-        if category.lower() != 'names':
-            raise ParsingException(f'Expected "SET names", got "SET {category}"')
-        if isinstance(p[1], Constant):
+
+        if isinstance(p[1], (Constant, Identifier)):
             value = p[1]
         else:
             # is id
             value = Constant(p[1], with_quotes=False)
 
         params = {}
         if hasattr(p, 'COLLATE'):
+            if category.lower() != 'names':
+                raise ParsingException(f'Expected "SET names", got "SET {category}"')
+
             if isinstance(p[3], Constant):
                 val = p[3]
             else:
@@ -776,6 +779,7 @@ def create_predictor(self, p):
     @_('CREATE replace_or_empty PREDICTOR if_not_exists_or_empty identifier FROM identifier LPAREN raw_query RPAREN PREDICT result_columns',
        'CREATE replace_or_empty PREDICTOR if_not_exists_or_empty identifier PREDICT result_columns',
        'CREATE replace_or_empty MODEL if_not_exists_or_empty identifier FROM identifier LPAREN raw_query RPAREN PREDICT result_columns',
+       'CREATE replace_or_empty MODEL if_not_exists_or_empty identifier FROM LPAREN raw_query RPAREN PREDICT result_columns',
        'CREATE replace_or_empty MODEL if_not_exists_or_empty identifier PREDICT result_columns'
        )
     def create_predictor(self, p):
@@ -837,11 +841,15 @@ def create_anomaly_detection_model(self, p):
 
     @_('RETRAIN identifier',
        'RETRAIN identifier PREDICT result_columns',
+       'RETRAIN identifier FROM LPAREN raw_query RPAREN',
+       'RETRAIN identifier FROM LPAREN raw_query RPAREN PREDICT result_columns',
        'RETRAIN identifier FROM identifier LPAREN raw_query RPAREN',
        'RETRAIN identifier FROM identifier LPAREN raw_query RPAREN PREDICT result_columns',
        'RETRAIN MODEL identifier',
        'RETRAIN MODEL identifier PREDICT result_columns',
+       'RETRAIN MODEL identifier FROM LPAREN raw_query RPAREN',
        'RETRAIN MODEL identifier FROM identifier LPAREN raw_query RPAREN',
+       'RETRAIN MODEL identifier FROM LPAREN raw_query RPAREN PREDICT result_columns',
        'RETRAIN MODEL identifier FROM identifier LPAREN raw_query RPAREN PREDICT result_columns')
     def create_predictor(self, p):
         query_str = None
@@ -862,7 +870,9 @@ def create_predictor(self, p):
         )
 
     @_('FINETUNE identifier FROM identifier LPAREN raw_query RPAREN',
-       'FINETUNE MODEL identifier FROM identifier LPAREN raw_query RPAREN')
+       'FINETUNE identifier FROM LPAREN raw_query RPAREN',
+       'FINETUNE MODEL identifier FROM identifier LPAREN raw_query RPAREN',
+       'FINETUNE MODEL identifier FROM LPAREN raw_query RPAREN')
     def create_predictor(self, p):
         query_str = None
         if hasattr(p, 'raw_query'):

setup.py

@@ -24,6 +24,7 @@
         "Programming Language :: Python :: 3.7",
         "Programming Language :: Python :: 3.8",
         "Programming Language :: Python :: 3.9",
+        "Programming Language :: Python :: 3.10",
     ],
     python_requires=">=3.6"
 )

tests/test_parser/test_base_sql/test_misc_sql_queries.py

@@ -221,6 +221,15 @@ def test_charset(self):
         assert ast.to_tree() == expected_ast.to_tree()
         assert str(ast) == str(expected_ast)
 
+    def test_set_version(self):
+        sql = "SET active model_name.1"
+
+        ast = parse_sql(sql)
+        expected_ast = Set(category='active', value=Identifier(parts=['model_name', '1']))
+
+        assert ast.to_tree() == expected_ast.to_tree()
+        assert str(ast) == str(expected_ast)
+
     def test_interval(self):
         sql = """
            select interval '1 day'+1 from aaa

tests/test_parser/test_mindsdb/test_create_predictor.py

@@ -60,7 +60,7 @@ def test_create_predictor_full(self):
         assert ast.to_tree() == ast2.to_tree()
 
     def test_create_predictor_minimal(self):
-        sql = """CREATE PREDICTOR IF NOT EXISTS pred
+        sql = """CREATE MODEL IF NOT EXISTS pred
                 FROM integration_name 
                 (select * FROM table_name)
                 PREDICT f1 as f1_alias, f2
@@ -196,3 +196,45 @@ def test_create_anomaly_detection_model(self):
 
             assert to_single_line(str(ast)) == to_single_line(str(expected_ast))
             assert ast.to_tree() == expected_ast.to_tree()
+
+    def test_optional_db(self):
+        sql = "CREATE MODEL xxx from (select 1) PREDICT sss"
+        ast = parse_sql(sql, dialect='mindsdb')
+        expected_ast = CreatePredictor(
+            name=Identifier('xxx'),
+            query_str='select 1',
+            targets=[Identifier('sss')],
+        )
+        assert to_single_line(str(ast)) == to_single_line(str(expected_ast))
+        assert ast.to_tree() == expected_ast.to_tree()
+
+        # retrain
+        sql = "RETRAIN MODEL xxx from (select 1)"
+        ast = parse_sql(sql, dialect='mindsdb')
+        expected_ast = RetrainPredictor(
+            name=Identifier('xxx'),
+            query_str='select 1',
+        )
+        assert to_single_line(str(ast)) == to_single_line(str(expected_ast))
+        assert ast.to_tree() == expected_ast.to_tree()
+
+        sql = "RETRAIN xxx from (select 1)"
+        ast = parse_sql(sql, dialect='mindsdb')
+        assert to_single_line(str(ast)) == to_single_line(str(expected_ast))
+        assert ast.to_tree() == expected_ast.to_tree()
+
+        # finetune
+        sql = "FINETUNE MODEL xxx from (select 1)"
+        ast = parse_sql(sql, dialect='mindsdb')
+        expected_ast = FinetunePredictor(
+            name=Identifier('xxx'),
+            query_str='select 1',
+        )
+        assert to_single_line(str(ast)) == to_single_line(str(expected_ast))
+        assert ast.to_tree() == expected_ast.to_tree()
+
+        sql = "FINETUNE xxx from (select 1)"
+        ast = parse_sql(sql, dialect='mindsdb')
+        assert to_single_line(str(ast)) == to_single_line(str(expected_ast))
+        assert ast.to_tree() == expected_ast.to_tree()
+