def test_df_equivalent_after_sql(self):
# Parse the CSV
df_source = pandas_db.load_df_from_csvfile(
StringIO.StringIO(self.csv1), 0, 0)
# Store the DF in the DB
pandas_db.store_table(df_source, self.table_name)
# Load it from the DB
df_dst = pandas_db.load_table(self.table_name)
# Data frames mut be identical
assert df_source.equals(df_dst)
def df_equivalent_after_sql(self):
# Parse the CSV
df_source = pandas_db.load_df_from_csvfile(
StringIO.StringIO(self.csv1), 0, 0)
# Store the DF in the DB
pandas_db.store_table(df_source, self.table_name)
# Load it from the DB
df_dst = pandas_db.load_table(self.table_name)
# Columns have to have the same values (None and NaN are
# different)
for x in df_source.columns:
np.testing.assert_array_equal(
np.array(df_source[x], dtype=unicode),
np.array(df_dst[x], dtype=unicode))
def load_upload_from_db(pk):
return load_table(create_upload_table_name(pk))