def test_no_strings(self):
conn = dbapi.connect(self._simple_fixture())
curs = conn.cursor()
assert_raises_message(
dbapi.Error,
"Only Pandas callable functions accepted for execute()",
curs.execute, "select * from table")
def test_description(self):
def stmt(trace, namespace, params):
return namespace["df1"][["col1", "col2", "col3"]]
conn = dbapi.connect(self._simple_fixture())
curs = conn.cursor()
curs.execute(stmt)
eq_(curs.description, [('col1', None, None, None, None, None, None),
('col2', None, None, None, None, None, None),
('col3', None, None, None, None, None, None)])
def test_dataframe(self):
def stmt(trace, namespace, params):
return namespace["df1"][["col1", "col2", "col3"]]
conn = dbapi.connect(self._simple_fixture())
curs = conn.cursor()
curs.execute(stmt)
eq_(list(curs.dataframe.itertuples(index=False)),
[(0, 'string: 0', 0.0), (1, 'string: 1', 0.0054729999999999996),
(2, 'string: 2', 0.010945999999999999),
(3, 'string: 3', 0.016419),
(4, 'string: 4', 0.021891999999999998)])
def test_simple_statement(self):
def stmt(trace, namespace, params):
return namespace["df1"][["col1", "col2", "col3"]]
conn = dbapi.connect(self._simple_fixture())
curs = conn.cursor()
curs.execute(stmt)
eq_(curs.fetchall(), [(0, 'string: 0', 0.0),
(1, 'string: 1', 0.005473),
(2, 'string: 2', 0.010946),
(3, 'string: 3', 0.016419),
(4, 'string: 4', 0.021892)])
def _numbers_fixture(self):
numbers = pd.DataFrame(np.array(
((0.01, 0.01, 0.02, 0.04, 0.03), (0.00, 0.02, 0.02, 0.03, 0.02),
(0.01, 0.02, 0.02, 0.03, 0.02), (0.01, 0.00, 0.01, 0.05, 0.03))),
columns=['a', 'b', 'c', 'd', 'e'])
m = MetaData()
n_t = Table('numbers', m, Column('a', Float), Column('b', Float),
Column('c', Float), Column('d', Float), Column('e', Float))
conn = dbapi.connect({"numbers": numbers})
return n_t, conn
def _emp_d_fixture(self):
emp_df = pd.DataFrame([
{
"emp_id": 1,
"name": "ed",
"fullname": "Ed Jones",
"dep_id": 1
},
{
"emp_id": 2,
"name": "wendy",
"fullname": "Wendy Wharton",
"dep_id": 1
},
{
"emp_id": 3,
"name": "jack",
"fullname": "Jack Smith",
"dep_id": 2
},
])
dept_df = pd.DataFrame([
{
"dep_id": 1,
"name": "Engineering"
},
{
"dep_id": 2,
"name": "Accounting"
},
{
"dep_id": 3,
"name": "Sales"
},
])
m = MetaData()
emp = Table('employee', m, Column('emp_id', Integer, primary_key=True),
Column('name', String), Column('fullname', String),
Column('dep_id', Integer, ForeignKey('department.dep_id')))
dep = Table(
'department',
m,
Column('dep_id', Integer, primary_key=True),
Column('name', String),
)
conn = dbapi.connect({"employee": emp_df, "department": dept_df})
return emp, dep, conn
def _autoinc_fixture(self):
dept_df = pd.DataFrame([
{
"name": "Engineering"
},
{
"name": "Accounting"
},
{
"name": "Sales"
},
])
m = MetaData()
dep = Table('department',
m,
Column('dep_id', Integer, primary_key=True),
Column('name', String),
pandas_index_pk=True)
conn = dbapi.connect({"department": dept_df})
return dep, conn
def _emp_d_fixture(self, pandas_index_pk=False):
if pandas_index_pk:
emp_df = pd.DataFrame(columns=["name", "fullname", "dep_id"])
dept_df = pd.DataFrame(columns=["name"])
else:
emp_df = pd.DataFrame(
columns=["emp_id", "name", "fullname", "dep_id"])
dept_df = pd.DataFrame(columns=["dep_id", "name"])
m = MetaData()
emp = Table('employee',
m,
Column('emp_id', Integer, primary_key=True),
Column('name', String),
Column('fullname', String),
Column('dep_id', Integer, ForeignKey('department.dep_id')),
pandas_index_pk=pandas_index_pk)
dep = Table('department',
m,
Column('dep_id', Integer, primary_key=True),
Column('name', String),
pandas_index_pk=pandas_index_pk)
conn = dbapi.connect({"employee": emp_df, "department": dept_df})
return emp, dep, conn
def _conn_fixture(self):
conn = dbapi.connect(None)
return conn