def test_filereader_book1xlsx():
path = Path(__file__).parent / "data" / 'book1.xlsx'
assert path.exists()
start = process_time_ns()
tables = list(file_reader(path))
end = process_time_ns()
fields = sum(len(t) * len(t.columns) for t in tables)
print("{:,} fields/seccond".format(
round(1e9 * fields / max(1, end - start), 0)))
sheet1 = Table(filename=path.name, sheet_name='Sheet1')
for column_name in list('abcdef'):
sheet1.add_column(column_name, int, False)
sheet2 = Table(
filename=path.name,
sheet_name='Sheet2 ') # there's a deliberate white space at the end!
sheet2.add_column('a', int, False)
for column_name in list('bcdef'):
sheet2.add_column(column_name, float, False)
books = [sheet1, sheet2]
for book, table in zip(books, tables):
table.show(slice(5))
assert table.compare(book)
assert len(table) == 45, len(table)
def test_filereader_gdocs1csv_no_header():
path = Path(__file__).parent / "data" / 'gdocs1.csv'
assert path.exists()
table = list(file_reader(path, has_headers=False))[0]
table.show(slice(0, 10))
book1_csv = Table(filename=path.name)
for idx, _ in enumerate(list('abcdef'), 1):
book1_csv.add_column(f"_{idx}", str)
assert table.compare(book1_csv), table.compare(book1_csv)
assert len(table) == 46
def test_filereader_gdocs1xlsx():
path = Path(__file__).parent / "data" / 'gdocs1.xlsx'
assert path.exists()
table = list(file_reader(path))[0]
table.show(slice(0, 10))
gdocs1xlsx = Table(filename=path.name, sheet_name='Sheet1')
for float_type in list('abcdef'):
gdocs1xlsx.add_column(float_type, int)
assert table.compare(gdocs1xlsx), table.compare(gdocs1xlsx)
assert len(table) == 45
def test_filereader_gdocs1xlsx_no_header():
path = Path(__file__).parent / "data" / 'gdocs1.xlsx'
assert path.exists()
table = list(file_reader(path, has_headers=False))[0]
table.show(slice(0, 10))
gdocs1xlsx = Table(filename=path.name, sheet_name='Sheet1')
for idx, _ in enumerate(list('abcdef'), 1):
gdocs1xlsx.add_column(f"_{idx}", str)
assert table.compare(gdocs1xlsx), table.compare(gdocs1xlsx)
assert len(table) == 46
def test_filereader_exceldatesxlsx():
path = Path(__file__).parent / "data" / 'excel_dates.xlsx'
assert path.exists()
table = list(file_reader(path))[0]
table.show()
sheet1 = Table(filename=path.name, sheet_name='Sheet1')
sheet1.add_column('Date', datetime, False)
sheet1.add_column('numeric value', int, False)
sheet1.add_column('string', date, False)
sheet1.add_column('bool', bool, False)
assert table.compare(sheet1)
assert len(table) == 2, len(table)
def test_filereader_gdocsc1ods():
path = Path(__file__).parent / "data" / 'gdocs1.ods'
assert path.exists()
tables = file_reader(path)
sheet1 = Table(filename=path.name, sheet_name='Sheet1')
for int_type in list('abcdef'):
sheet1.add_column(int_type, int)
sheet2 = Table(filename=path.name, sheet_name='Sheet2')
sheet2.add_column('a', int)
for float_type in list('bcdef'):
sheet2.add_column(float_type, float)
sheets = [sheet1, sheet2]
for sheet, table in zip(sheets, tables):
table.compare(sheet)
assert len(table) == 45, table.show(blanks="")
def test_groupby_02():
t = Table()
t.add_column('A', int, data=[1, 1, 2, 2, 3, 3] * 2)
t.add_column('B', int, data=[1, 2, 3, 4, 5, 6] * 2)
t.add_column('C', int, data=[6, 5, 4, 3, 2, 1] * 2)
t.show()
# +=====+=====+=====+
# | A | B | C |
# | int | int | int |
# |False|False|False|
# +-----+-----+-----+
# | 1| 1| 6|
# | 1| 2| 5|
# | 2| 3| 4|
# | 2| 4| 3|
# | 3| 5| 2|
# | 3| 6| 1|
# | 1| 1| 6|
# | 1| 2| 5|
# | 2| 3| 4|
# | 2| 4| 3|
# | 3| 5| 2|
# | 3| 6| 1|
# +=====+=====+=====+
g = t.groupby(keys=['A', 'C'], functions=[('B', gb.sum)])
g.table.show()
t2 = g.pivot('A')
t2.show()
# +=====+==========+==========+==========+
# | C |Sum(B,A=1)|Sum(B,A=2)|Sum(B,A=3)|
# | int | int | int | int |
# |False| True | True | True |
# +-----+----------+----------+----------+
# | 5| 4| None| None|
# | 6| 2| None| None|
# | 3| None| 8| None|
# | 4| None| 6| None|
# | 1| None| None| 12|
# | 2| None| None| 10|
# +=====+==========+==========+==========+
assert len(t2) == 6 and len(t2.columns) == 4
def test_lookup_functions(): # doing lookups is supported by indexing:
table6 = Table()
table6.add_column(
'A',
str,
data=['Alice', 'Bob', 'Bob', 'Ben', 'Charlie', 'Ben', 'Albert'])
table6.add_column('B',
str,
data=[
'Alison', 'Marley', 'Dylan', 'Affleck', 'Hepburn',
'Barnes', 'Einstein'
])
index = table6.index('A') # single key.
assert index[('Bob', )] == {1, 2}
index2 = table6.index('A', 'B') # multiple keys.
assert index2[('Bob', 'Dylan')] == {2}
def test_filereader_utf8sig_encoding_csv():
path = Path(__file__).parent / "data" / 'utf8sig.csv'
assert path.exists()
table = list(file_reader(path, sep=','))[0]
table.show(slice(0, 10))
table.show(slice(-15))
book1_csv = Table(filename=path.name)
book1_csv.add_column('432', int)
book1_csv.add_column('1', int)
assert table.compare(book1_csv), table.compare(book1_csv)
assert len(table) == 2, len(table)
def test_filereader_gdocsc1ods_no_header():
path = Path(__file__).parent / "data" / 'gdocs1.ods'
assert path.exists()
tables = file_reader(path, has_headers=False)
sheet1 = Table(filename=path.name, sheet_name='Sheet1')
for idx, _ in enumerate(list('abcdef'), 1):
sheet1.add_column(f"_{idx}", str)
sheet2 = Table(filename=path.name, sheet_name='Sheet2')
for idx, _ in enumerate(list('abcdef'), 1):
sheet2.add_column(f"_{idx}", str)
sheets = [sheet1, sheet2]
for sheet, table in zip(sheets, tables):
table.show(slice(0, 10))
table.compare(sheet)
assert len(table) == 46, table.show(blanks="")
def test_filereader_book1tsv():
path = Path(__file__).parent / "data" / 'book1.tsv'
assert path.exists()
table = list(file_reader(path))[0]
table.show(slice(0, 10))
book1 = Table(filename=path.name)
book1.add_column('a', int)
for float_type in list('bcdef'):
book1.add_column(float_type, float)
assert table.compare(book1), table.compare(book1)
assert len(table) == 45
def test_ttopi():
""" example code from the readme as "reversing a pivot tablite". """
from random import seed, choice
seed(11)
records = 9
t = Table()
t.add_column('record id',
int,
allow_empty=False,
data=[i for i in range(records)])
for column in [f"4.{i}.a" for i in range(5)]:
t.add_column(
column,
str,
allow_empty=True,
data=[choice(['a', 'h', 'e', None]) for i in range(records)])
print("\nshowing raw data:")
t.show()
# +=====+=====+
# | A | B |
# | str | str |
# |False|False|
# +-----+-----+
# |4.2.a|e |
# |4.3.a|h |
# |4.2.a|h |
# |4.2.a|e |
# |4.3.a|e |
# |4.3.a|e |
# |4.1.a|e |
# |4.1.a|a |
# |4.3.a|e |
# |4.2.a|a |
# |4.3.a|e |
# |4.3.a|a |
# |4.1.a|a |
# |4.1.a|a |
# |4.2.a|a |
# |4.2.a|a |
# |4.1.a|e |
# |4.1.a|a |
# |4.3.a|h |
# |4.3.a|h |
# |4.3.a|h |
# |4.1.a|e |
# +=====+=====+
# wanted output:
# +=====+=====
# | A | Count(A,B=a) | Count(A,B=h) | Count(A,B=e) |
# | str | int | int | int |
# |False| False | False | False |
# +-----+--------------+--------------+--------------+
# |4.1.a| 3 | 0 | 3 |
# |4.2.a| 3 | 1 | 2 |
# |4.3.a| 1 | 4 | 4 |
# +=====+==============+==============+==============+
reverse_pivot = Table()
records = t['record id']
reverse_pivot.add_column('record id', records.datatype, allow_empty=False)
reverse_pivot.add_column('4.x', str, allow_empty=False)
reverse_pivot.add_column('ahe', str, allow_empty=True)
for name in t.columns:
if not name.startswith('4.'):
continue
column = t[name]
for index, entry in enumerate(column):
new_row = records[index], name, entry # record id, 4.x, ahe
reverse_pivot.add_row(new_row)
print("\nshowing reversed pivot of the raw data:")
reverse_pivot.show()
g = reverse_pivot.groupby(['4.x', 'ahe'],
functions=[('ahe', GroupBy.count)])
print("\nshowing basic groupby of the reversed pivot")
g.table.show()
t2 = g.pivot('ahe')
print("\nshowing the wanted output:")
t2.show()
def test_lookup():
friends = Table()
friends.add_column(
"name",
str,
data=['Alice', 'Betty', 'Charlie', 'Dorethy', 'Edward', 'Fred'])
friends.add_column("stop",
str,
data=[
'Downtown-1', 'Downtown-2', 'Hillside View',
'Hillside Crescent', 'Downtown-2', 'Chicago'
])
friends.show()
random.seed(11)
table_size = 40
times = [
DataTypes.time(random.randint(21, 23), random.randint(0, 59))
for i in range(table_size)
]
stops = [
'Stadium', 'Hillside', 'Hillside View', 'Hillside Crescent',
'Downtown-1', 'Downtown-2', 'Central station'
] * 2 + [f'Random Road-{i}' for i in range(table_size)]
route = [random.choice([1, 2, 3]) for i in stops]
bustable = Table()
bustable.add_column("time", DataTypes.time, data=times)
bustable.add_column("stop", str, data=stops[:table_size])
bustable.add_column("route", int, data=route[:table_size])
bustable.sort(**{'time': False})
print("Departures from Concert Hall towards ...")
bustable[:10].show()
lookup_1 = friends.lookup(bustable, ('time', ">=", DataTypes.time(21, 10)),
('stop', "==", 'stop'))
lookup_1.sort(**{'time': False})
lookup_1.show()
expected = [
('Fred', 'Chicago', None, None, None),
('Dorethy', 'Hillside Crescent', time(21, 5), 'Hillside Crescent', 2),
('Betty', 'Downtown-2', time(21, 51), 'Downtown-2', 1),
('Edward', 'Downtown-2', time(21, 51), 'Downtown-2', 1),
('Charlie', 'Hillside View', time(22, 19), 'Hillside View', 2),
('Alice', 'Downtown-1', time(23, 12), 'Downtown-1', 3),
]
for row in lookup_1.rows:
expected.remove(row)
assert expected == []
def test_clipboard():
t = Table()
t.add_column('dog', int, data=[1, 4])
t.add_column('cat', int, data=[2, 5])
t.add_column('hat', int, data=[3, 6])
t.show()
try:
t.copy_to_clipboard()
t2 = t.copy_from_clipboard()
assert t == t2
except pyperclip.PyperclipException:
pass # travis VMs can't handle this.
def test_sortation(): # Sortation
table7 = Table()
table7.add_column('A',
int,
data=[1, None, 8, 3, 4, 6, 5, 7, 9],
allow_empty=True)
table7.add_column('B', int, data=[10, 100, 1, 1, 1, 1, 10, 10, 10])
table7.add_column('C', int, data=[0, 1, 0, 1, 0, 1, 0, 1, 0])
assert not table7.is_sorted()
sort_order = {'B': False, 'C': False, 'A': False}
table7.sort(**sort_order)
assert list(table7.rows) == [(4, 1, 0), (8, 1, 0), (3, 1, 1), (6, 1, 1),
(1, 10, 0), (5, 10, 0), (9, 10, 0),
(7, 10, 1), (None, 100, 1)]
assert list(table7.filter('A', 'B', slice(4, 8))) == [(1, 10), (5, 10),
(9, 10), (7, 10)]
assert table7.is_sorted(**sort_order)
def test_sql_joins(): # a couple of examples with SQL join:
numbers = Table()
numbers.add_column('number',
int,
allow_empty=True,
data=[1, 2, 3, 4, None])
numbers.add_column('colour',
str,
data=['black', 'blue', 'white', 'white', 'blue'])
letters = Table()
letters.add_column('letter',
str,
allow_empty=True,
data=['a', 'b', 'c', 'd', None])
letters.add_column('color',
str,
data=['blue', 'white', 'orange', 'white', 'blue'])
# left join
# SELECT number, letter FROM numbers LEFT JOIN letters ON numbers.colour == letters.color
left_join = numbers.left_join(letters,
left_keys=['colour'],
right_keys=['color'],
columns=['number', 'letter'])
left_join.show()
# +======+======+
# |number|letter|
# | int | str |
# | True | True |
# +------+------+
# | 1|None |
# | 2|a |
# | 2|None |
# | 3|b |
# | 3|d |
# | 4|b |
# | 4|d |
# |None |a |
# |None |None |
# +======+======+
assert [i
for i in left_join['number']] == [1, 2, 2, 3, 3, 4, 4, None, None]
assert [i for i in left_join['letter']
] == [None, 'a', None, 'b', 'd', 'b', 'd', 'a', None]
# inner join
# SELECT number, letter FROM numbers JOIN letters ON numbers.colour == letters.color
inner_join = numbers.inner_join(letters,
left_keys=['colour'],
right_keys=['color'],
columns=['number', 'letter'])
inner_join.show()
# +======+======+
# |number|letter|
# | int | str |
# | True | True |
# +------+------+
# | 2|a |
# | 2|None |
# |None |a |
# |None |None |
# | 3|b |
# | 3|d |
# | 4|b |
# | 4|d |
# +======+======+
assert [i for i in inner_join['number']] == [2, 2, None, None, 3, 3, 4, 4]
assert [i for i in inner_join['letter']
] == ['a', None, 'a', None, 'b', 'd', 'b', 'd']
# outer join
# SELECT number, letter FROM numbers OUTER JOIN letters ON numbers.colour == letters.color
outer_join = numbers.outer_join(letters,
left_keys=['colour'],
right_keys=['color'],
columns=['number', 'letter'])
outer_join.show()
# +======+======+
# |number|letter|
# | int | str |
# | True | True |
# +------+------+
# | 1|None |
# | 2|a |
# | 2|None |
# | 3|b |
# | 3|d |
# | 4|b |
# | 4|d |
# |None |a |
# |None |None |
# |None |c |
# +======+======+
assert [i for i in outer_join['number']
] == [1, 2, 2, 3, 3, 4, 4, None, None, None]
assert [i for i in outer_join['letter']
] == [None, 'a', None, 'b', 'd', 'b', 'd', 'a', None, 'c']
assert left_join != inner_join
assert inner_join != outer_join
assert left_join != outer_join
def test_basic_table():
# creating a tablite incrementally is straight forward:
table = Table()
table.add_column('A', int, False)
assert 'A' in table
table.add_column('B', str, allow_empty=False)
assert 'B' in table
# appending rows is easy:
table.add_row((1, 'hello'))
table.add_row((2, 'world'))
# converting to and from json is easy:
table_as_json = table.to_json()
table2 = Table.from_json(table_as_json)
zipped = zlib.compress(table_as_json.encode())
a, b = len(zipped), len(table_as_json)
print("zipping reduces to", a, "from", b, "bytes, e.g.",
round(100 * a / b, 0), "% of original")
# copying is easy:
table3 = table.copy()
table.rename_column('A', 'aa')
assert list(table.columns) == ['aa', 'B']
table.rename_column('aa', 'A')
assert list(table.columns) == ['A', 'B']
# and checking for headers is simple:
assert 'A' in table
assert 'Z' not in table
# comparisons are straight forward:
assert table == table2 == table3
# even if you only want to check metadata:
table.compare(table3) # will raise exception if they're different.
# append is easy as + also work:
table3x2 = table3 + table3
assert len(table3x2) == len(table3) * 2
# and so does +=
table3x2 += table3
assert len(table3x2) == len(table3) * 3
# type verification is included:
try:
table.columns['A'][0] = 'Hallo'
assert False, "A TypeError should have been raised."
except TypeError:
assert True
# updating values is familiar to any user who likes a list:
assert 'A' in table.columns
assert isinstance(table.columns['A'], (StoredList, list))
last_row = -1
table['A'][last_row] = 44
table['B'][last_row] = "Hallo"
assert table != table2
# if you try to loop and forget the direction, Table will tell you
try:
for row in table: # wont pass
assert False, "not possible. Use for row in tablite.rows or for column in tablite.columns"
except AttributeError:
assert True
_ = [table2.add_row(row) for row in table.rows]
before = [r for r in table2.rows]
assert before == [(1, 'hello'), (2, 'world'), (1, 'hello'), (44, 'Hallo')]
# as is filtering for ALL that match:
filter_1 = lambda x: 'llo' in x
filter_2 = lambda x: x > 3
after = table2.all(**{'B': filter_1, 'A': filter_2})
assert list(after.rows) == [(44, 'Hallo')]
# as is filtering or for ANY that match:
after = table2.any(**{'B': filter_1, 'A': filter_2})
assert list(after.rows) == [(1, 'hello'), (1, 'hello'), (44, 'Hallo')]
# Imagine a tablite with columns a,b,c,d,e (all integers) like this:
t = Table()
for c in 'abcde':
t.add_column(header=c,
datatype=int,
allow_empty=False,
data=[i for i in range(5)])
# we want to add two new columns using the functions:
def f1(a, b, c):
return a + b + c + 1
def f2(b, c, d):
return b * c * d
# and we want to compute two new columns 'f' and 'g':
t.add_column(header='f', datatype=int, allow_empty=False)
t.add_column(header='g', datatype=int, allow_empty=True)
# we can now use the filter, to iterate over the tablite:
for row in t.filter('a', 'b', 'c', 'd'):
a, b, c, d = row
# ... and add the values to the two new columns
t['f'].append(f1(a, b, c))
t['g'].append(f2(b, c, d))
assert len(t) == 5
assert list(t.columns) == list('abcdefg')
t.show()
# slicing is easy:
table_chunk = table2[2:4]
assert isinstance(table_chunk, Table)
# we will handle duplicate names gracefully.
table2.add_column('B', int, allow_empty=True)
assert set(table2.columns) == {'A', 'B', 'B_1'}
# you can delete a column as key...
del table2['B_1']
assert set(table2.columns) == {'A', 'B'}
# adding a computed column is easy:
table.add_column('new column',
str,
allow_empty=False,
data=[f"{r}" for r in table.rows])
# part of or the whole tablite is easy:
table.show()
table.show('A', slice(0, 1))
# updating a column with a function is easy:
f = lambda x: x * 10
table['A'] = [f(r) for r in table['A']]
# using regular indexing will also work.
for ix, r in enumerate(table['A']):
table['A'][ix] = r * 10
# and it will tell you if you're not allowed:
try:
f = lambda x: f"'{x} as text'"
table['A'] = [f(r) for r in table['A']]
assert False, "The line above must raise a TypeError"
except TypeError as error:
print("The error is:", str(error))
# works with all datatypes:
now = datetime.now()
table4 = Table()
table4.add_column('A', int, allow_empty=False, data=[-1, 1])
table4.add_column('A', int, allow_empty=True, data=[None, 1]) # None!
table4.add_column('A', float, False, data=[-1.1, 1.1])
table4.add_column(
'A', str, False,
data=["", "1"]) # Empty string is not a None, when dtype is str!
table4.add_column(
'A', str, True,
data=[None, "1"]) # Empty string is not a None, when dtype is str!
table4.add_column('A', bool, False, data=[False, True])
table4.add_column('A', datetime, False, data=[now, now])
table4.add_column('A', date, False, data=[now.date(), now.date()])
table4.add_column('A', time, False, data=[now.time(), now.time()])
table4_json = table4.to_json()
table5 = Table.from_json(table4_json)
# .. to json and back.
assert table4 == table5
# And finally: I can add metadata:
table5.metadata['db_mapping'] = {
'A': 'customers.customer_name',
'A_2': 'product.sku',
'A_4': 'locations.sender'
}
# which also jsonifies without fuzz.
table5_json = table5.to_json()
table5_from_json = Table.from_json(table5_json)
assert table5 == table5_from_json
def test_filereader_win1251_encoding_csv():
path = Path(__file__).parent / "data" / 'win1250_test.csv'
assert path.exists()
table = list(file_reader(path, sep=';'))[0]
table.show(slice(0, 10))
table.show(slice(-15))
book1_csv = Table(filename=path.name)
book1_csv.add_column('Item', int)
book1_csv.add_column('Materiál', str)
book1_csv.add_column('Objem', float)
book1_csv.add_column('Jednotka objemu', str)
book1_csv.add_column('Free Inv Pcs', int)
assert table.compare(book1_csv), table.compare(book1_csv)
assert len(table) == 99, len(table)
def test_add_rows():
""" Example from docstring. """
t = Table()
t.add_column('test', int)
t.add_column('A', int)
t.add_column('B', int)
t.add_column('C', int)
test_number = count(1)
# The following examples are all valid and append the row (1,2,3) to the tablite.
t.add_row(next(test_number), 1, 2, 3)
t.add_row([next(test_number), 1, 2, 3])
t.add_row((next(test_number), 1, 2, 3))
t.add_row(*(next(test_number), 1, 2, 3))
t.add_row(test=next(test_number), A=1, B=2, C=3)
t.add_row(**{'test': next(test_number), 'A': 1, 'B': 2, 'C': 3})
# The following examples add two rows to the tablite
t.add_row((next(test_number), 1, 2, 3), (next(test_number), 4, 5, 6))
t.add_row([next(test_number), 1, 2, 3], [next(test_number), 4, 5, 6])
t.add_row({
'test': next(test_number),
'A': 1,
'B': 2,
'C': 3
}, {
'test': next(test_number),
'A': 4,
'B': 5,
'C': 6
}) # two (or more) dicts as args.
t.add_row(*[{
'test': next(test_number),
'A': 1,
'B': 2,
'C': 3
}, {
'test': next(test_number),
'A': 1,
'B': 2,
'C': 3
}]) # list of dicts.
t.show() # expects:
# +=====+=====+=====+=====+
# | test| A | B | C |
# | int | int | int | int |
# |False|False|False|False|
# +-----+-----+-----+-----+
# | 1| 1| 2| 3|
# | 2| 1| 2| 3|
# | 3| 1| 2| 3|
# | 4| 1| 2| 3|
# | 5| 1| 2| 3|
# | 6| 1| 2| 3|
# | 7| 1| 2| 3|
# | 8| 4| 5| 6|
# | 9| 1| 2| 3|
# | 10| 4| 5| 6|
# | 11| 1| 2| 3|
# | 12| 4| 5| 6|
# | 13| 1| 2| 3|
# | 14| 1| 2| 3|
# +=====+=====+=====+=====+
assert next(test_number) == 14 + 1
def test_filereader_saptxt():
path = Path(__file__).parent / "data" / 'sap.txt'
assert path.exists()
# test part 1: split using user defined sequence.
header = " | Delivery | Item|Pl.GI date|Route |SC|Ship-to |SOrg.|Delivery quantity|SU| TO Number|Material |Dest.act.qty.|BUn|Typ|Source Bin|Cty"
split_sequence = ["|"] * header.count('|')
table = list(file_reader(path, split_sequence=split_sequence))[0]
table.show(slice(5))
sap_sample = Table(filename=path.name)
sap_sample.add_column('None', str, True)
sap_sample.add_column('Delivery', int, False)
sap_sample.add_column('Item', int, False)
sap_sample.add_column('Pl.GI date', date, False)
sap_sample.add_column('Route', str, False)
sap_sample.add_column('SC', str, False)
sap_sample.add_column('Ship-to', str, False)
sap_sample.add_column('SOrg.', str, False)
sap_sample.add_column('Delivery quantity', int, False)
sap_sample.add_column('SU', str, False)
sap_sample.add_column('TO Number', int, False)
sap_sample.add_column('Material', str, False)
sap_sample.add_column('Dest.act.qty.', int, False)
sap_sample.add_column('BUn', str, False)
sap_sample.add_column('Typ', str, False)
sap_sample.add_column('Source Bin', str, False)
sap_sample.add_column('Cty|', str, False)
assert table.compare(sap_sample)
assert len(table) == 20, len(table)
def test_groupby():
t = Table()
for c in 'abcde':
t.add_column(header=c,
datatype=int,
allow_empty=False,
data=[i for i in range(5)])
# we want to add two new columns using the functions:
def f1(a, b, c):
return a + b + c + 1
def f2(b, c, d):
return b * c * d
# and we want to compute two new columns 'f' and 'g':
t.add_column(header='f', datatype=int, allow_empty=False)
t.add_column(header='g', datatype=int, allow_empty=True)
# we can now use the filter, to iterate over the tablite:
for row in t.filter('a', 'b', 'c', 'd'):
a, b, c, d = row
# ... and add the values to the two new columns
t['f'].append(f1(a, b, c))
t['g'].append(f2(b, c, d))
assert len(t) == 5
assert list(t.columns) == list('abcdefg')
t.show()
g = GroupBy(keys=['a', 'b'],
functions=[('f', gb.max), ('f', gb.min), ('f', gb.sum),
('f', gb.first), ('f', gb.last), ('f', gb.count),
('f', gb.count_unique), ('f', gb.avg),
('f', gb.stdev), ('a', gb.stdev), ('f', gb.median),
('f', gb.mode), ('g', gb.median)])
t2 = t + t
assert len(t2) == 2 * len(t)
t2.show()
g += t2
assert list(g.rows) == [
(0, 0, 1, 1, 2, 1, 1, 2, 1, 1.0, 0.0, 0.0, 1, 1, 0),
(1, 1, 4, 4, 8, 4, 4, 2, 1, 4.0, 0.0, 0.0, 4, 4, 1),
(2, 2, 7, 7, 14, 7, 7, 2, 1, 7.0, 0.0, 0.0, 7, 7, 8),
(3, 3, 10, 10, 20, 10, 10, 2, 1, 10.0, 0.0, 0.0, 10, 10, 27),
(4, 4, 13, 13, 26, 13, 13, 2, 1, 13.0, 0.0, 0.0, 13, 13, 64)
]
g.table.show()
g2 = GroupBy(keys=['a', 'b'], functions=[('f', gb.max), ('f', g.sum)])
g2 += t + t + t
g2.table.show()
pivot_table = g2.pivot('b')
pivot_table.show()
def test_filereader_123csv():
csv_file = Path(__file__).parent / "data" / "123.csv"
table7 = Table(filename=csv_file.name)
table7.metadata['filename'] = '123.csv'
table7.add_column('A',
int,
data=[1, None, 8, 3, 4, 6, 5, 7, 9],
allow_empty=True)
table7.add_column('B', int, data=[10, 100, 1, 1, 1, 1, 10, 10, 10])
table7.add_column('C', int, data=[0, 1, 0, 1, 0, 1, 0, 1, 0])
sort_order = {'B': False, 'C': False, 'A': False}
table7.sort(**sort_order)
headers = ", ".join([c for c in table7.columns])
data = [headers]
for row in table7.rows:
data.append(", ".join(str(v) for v in row))
s = "\n".join(data)
print(s)
csv_file.write_text(s) # write
tr_table = list(file_reader(csv_file))[0] # read
csv_file.unlink() # cleanup
tr_table.show()
find_format(tr_table)
assert tr_table == table7
def test_recreate_readme_comparison():
try:
import os
import psutil
except ImportError:
return
process = psutil.Process(os.getpid())
baseline_memory = process.memory_info().rss
from time import process_time
from tablite import Table
digits = 1_000_000
records = Table()
records.add_column('method', str)
records.add_column('memory', int)
records.add_column('time', float)
records.add_row(('python', baseline_memory, 0.0))
# Let's now use the common and convenient "row" based format:
start = process_time()
L = []
for _ in range(digits):
L.append(tuple([11 for _ in range(10)]))
end = process_time()
# go and check taskmanagers memory usage.
# At this point we're using ~154.2 Mb to store 1 million lists with 10 items.
records.add_row(
('1e6 lists w. 10 integers',
process.memory_info().rss - baseline_memory, round(end - start, 4)))
L.clear()
# Let's now use a columnar format instead:
start = process_time()
L = [[11 for i in range(digits)] for _ in range(10)]
end = process_time()
# go and check taskmanagers memory usage.
# at this point we're using ~98.2 Mb to store 10 lists with 1 million items.
records.add_row(
('10 lists with 1e6 integers',
process.memory_info().rss - baseline_memory, round(end - start, 4)))
L.clear()
# We've thereby saved 50 Mb by avoiding the overhead from managing 1 million lists.
# Q: But why didn't I just use an array? It would have even lower memory footprint.
# A: First, array's don't handle None's and we get that frequently in dirty csv data.
# Second, Table needs even less memory.
# Let's start with an array:
import array
start = process_time()
L = [array.array('i', [11 for _ in range(digits)]) for _ in range(10)]
end = process_time()
# go and check taskmanagers memory usage.
# at this point we're using 60.0 Mb to store 10 lists with 1 million integers.
records.add_row(
('10 lists with 1e6 integers in arrays',
process.memory_info().rss - baseline_memory, round(end - start, 4)))
L.clear()
# Now let's use Table:
start = process_time()
t = Table()
for i in range(10):
t.add_column(str(i),
int,
allow_empty=False,
data=[11 for _ in range(digits)])
end = process_time()
records.add_row(
('Table with 10 columns with 1e6 integers',
process.memory_info().rss - baseline_memory, round(end - start, 4)))
# go and check taskmanagers memory usage.
# At this point we're using 97.5 Mb to store 10 columns with 1 million integers.
# Next we'll use the api `use_stored_lists` to drop to disk:
start = process_time()
t.use_disk = True
end = process_time()
records.add_row(
('Table on disk with 10 columns with 1e6 integers',
process.memory_info().rss - baseline_memory, round(end - start, 4)))
# go and check taskmanagers memory usage.
# At this point we're using 24.5 Mb to store 10 columns with 1 million integers.
# Only the metadata remains in pythons memory.
records.show()