def test_to_sqlite(self):
logger = logging.getLogger(__name__ + ":test_to_sqlite")
obj = [[1, "hello", datetime.date(2017, 5, 6)],
[2, "goodbye", datetime.date(1965, 7, 31)]
]
ft = Dataset.from_list_of_lists(obj, ["int", "str", "dt"])
now = datetime.datetime.now()
connection = ft.to_sqlite("list_of_lists")
logger.debug("elapsed %s " % (datetime.datetime.now() - now))
cursor = connection.cursor()
rows = cursor.execute("select count(*) from list_of_lists")
for row in rows:
logger.debug ("count %s " % row[0])
def dataset_list_of_lists():
a = datetime.datetime.now()
df = Dataset.from_list_of_lists(list_of_lists, None)
b = datetime.datetime.now()
print("type df %s" % type(df))
print("dataset_list_of_lists time %s" % (b - a))
for row in df.rows:
pass
c = datetime.datetime.now()
print("dataset_list_of_lists iter time %s" % (c - b))
for row in df.rows:
for col in row:
pass
d = datetime.datetime.now()
print("dataset_list_of_lists iter row col time %s" % (d - c))
return a, b
def test_from_list_of_lists(self):
obj = [[1,"hello",datetime.date(2017,5,6)],
[2,"goodbye",datetime.date(1965,7,31)]
]
ft = Dataset.from_list_of_lists(obj,["int","str","dt"])
logger.debug("row 0 %s" % ft.rows )
self.assertEqual(ft.rows[0][0],1)
self.assertEqual(ft.rows[0][1],"hello")
self.assertEqual(ft.rows[0][2],datetime.date(2017,5,6))
self.assertEqual(ft.rows[1][0],2)
self.assertEqual(ft.rows[1][1],"goodbye")
self.assertEqual(ft.rows[1][2],datetime.date(1965,7,31))
self.assertEqual(len(ft.rows),2)
self.assertEqual(len(ft.rows[0]),3)
self.assertEqual(len(ft.rows[1]),3)
self.assertEqual(ft.column_names[0],"int")
self.assertEqual(ft.column_names[1],"str")
self.assertEqual(ft.column_names[2],"dt")
self.assertEqual(len(ft.column_names),3)
def get_dataset_from_list_of_lists(matrix):
return Dataset.from_list_of_lists(matrix, None)
for col in row:
cell_sum += col
def to_html(dataset):
dataset.to_html()
def add_matrix(rows, columns):
matrix = get_list_of_lists(rows, columns)
name = "%s x %s" % (rows, columns)
matrices[name] = matrix
add_matrix(20000, 30)
add_matrix(10000, 2)
add_matrix(500, 12)
for k, v in matrices.items():
dataframes[k] = pandas.DataFrame(v)
datasets[k] = Dataset.from_list_of_lists(v, None)
for k in datasets:
df = dataframes[k]
ds = datasets[k]
benchmark_pair(k, iter_rows)
benchmark_pair(k, iter_rows_len)
benchmark_pair(k, iter_rows_and_columns)
benchmark_pair(k, sum_cells)
benchmark_pair(k, to_html)