def test_mem_generate_excel():
alive = kick_maxrss()
# Note: this has been tested with 1M row, and it works but it's slow.
# 100krow makes the point.
N_ROWS = 80000
table = make_table(N_ROWS, 4)
mem_before = getmaxrss_mb()
# outputter = ExcelOutput
outputter = ExceleratorOutput
# outputter = XlsxWriterOutput
with outputter("test/test_mem_generate_excel.xlsx") as xls:
n = 0
write_row = xls.add_sheet("hi")
for row in find_trs(BytesIO(table)):
write_row([e.text for e in row])
used = getmaxrss_mb() - mem_before
print "Used MB for 65krow:", used
# measured at <42 MB
assert used < 50, "Excessive memory usage"
def test_mem_parse_giant_table():
# Note: this test really wants to be run by itself in a process since it
# measures the *max* rss of the whole program. If python allocates
# a large object which goes away, the test will lie to us. Hence,
# kick_maxrss().
alive = kick_maxrss()
# Note: this has been tested with 1M row, and it works but it's slow.
# 100krow makes the point.
N_ROWS = 100000
table = make_table(N_ROWS, 4)
mem_before = getmaxrss_mb()
n = 0
for row in find_trs(BytesIO(table)):
n += 1
used = getmaxrss_mb() - mem_before
assert_equal(N_ROWS, n)
# Check that we didn't use more than 1MB to parse the table.
assert_less_equal(used, 1)
