Merge pull request #256 from thelittlebug/dsl-find-feature

add find operators

dataset/table.py

@@ -293,6 +293,24 @@ class Table(object):
                 clauses.append(false())
             elif isinstance(value, (list, tuple)):
                 clauses.append(self.table.c[column].in_(value))
+            elif isinstance(value, dict):
+                key = list(value.keys())[0]
+                if key in ('like',):
+                    clauses.append(self.table.c[column].like(value[key]))
+                elif key in ('>', 'gt'):
+                    clauses.append(self.table.c[column] > value[key])
+                elif key in ('<', 'lt'):
+                    clauses.append(self.table.c[column] < value[key])
+                elif key in ('>=', 'gte'):
+                    clauses.append(self.table.c[column] >= value[key])
+                elif key in ('<=', 'lte'):
+                    clauses.append(self.table.c[column] <= value[key])
+                elif key in ('!=', '<>', 'not'):
+                    clauses.append(self.table.c[column] != value[key])
+                elif key in ('between', '..'):
+                    clauses.append(self.table.c[column].between(value[key][0], value[key][1]))
+                else:
+                    clauses.append(false())
             else:
                 clauses.append(self.table.c[column] == value)
         return and_(*clauses)

docs/quickstart.rst

@@ -138,9 +138,25 @@ We can search for specific entries using :py:meth:`find() <dataset.Table.find>`
    # Get a specific user
    john = table.find_one(name='John Doe')
 
-   # Find by comparison
+   # Find multiple at once
+   winners = table.find(id=[1, 3, 7])
+
+   # Find by comparison operator
+   elderly_users = table.find(age={'>=': 70})
+   possible_customers = table.find(age={'between': [21, 80]})
+
+   # Use the underlying SQLAlchemy directly
    elderly_users = table.find(table.table.columns.age >= 70)
 
+Possible comparison operators::
+
+  gt, >
+  lt, <
+  gte, >=
+  lte, <=
+  !=, <>, not
+  between, ..
+
 Using  :py:meth:`distinct() <dataset.Table.distinct>` we can grab a set of rows
 with unique values in one or more columns::
 

test/test_dataset.py

@@ -321,6 +321,22 @@ class TableTestCase(unittest.TestCase):
         ds = list(self.tbl.find(self.tbl.table.columns.temperature > 4))
         assert len(ds) == 3, ds
 
+    def test_find_dsl(self):
+        ds = list(self.tbl.find(place={'like': '%lw%'}))
+        assert len(ds) == 3, ds
+        ds = list(self.tbl.find(temperature={'>': 5}))
+        assert len(ds) == 2, ds
+        ds = list(self.tbl.find(temperature={'>=': 5}))
+        assert len(ds) == 3, ds
+        ds = list(self.tbl.find(temperature={'<': 0}))
+        assert len(ds) == 1, ds
+        ds = list(self.tbl.find(temperature={'<=': 0}))
+        assert len(ds) == 2, ds
+        ds = list(self.tbl.find(temperature={'!=': -1}))
+        assert len(ds) == 5, ds
+        ds = list(self.tbl.find(temperature={'between': [5, 8]}))
+        assert len(ds) == 3, ds
+
     def test_offset(self):
         ds = list(self.tbl.find(place=TEST_CITY_1, _offset=1))
         assert len(ds) == 2, ds