A python-tabulate wrapper for producing tables from generators.
Motivation
lazy_table is useful when (i) each row of your table is generated by a possibly expensive computation and (ii) you want to print rows to the screen as soon as they are available.
For example, the rows in the table below correspond to numerically solving an ordinary differential equation with progressively more steps. See examples/euler_vdp.py for the code to generate this table.
Here is the same example with a progress bar.
Installation and usage
Install lazy_table via pip:
$ pip install lazy_table
In your Python code, add
import lazy_table as lt
Now, generating your own lazy table is as simple as calling lt.stream on a generator that yields one or more lists, where each list is a row of your table (see the example below).
Example
As a toy example, consider printing the first 10 Fibonacci numbers in a table. Since this is a relatively cheap operation, we will pretend it is expensive by adding an artificial sleep(1) call beteween Fibonacci numbers.
import time
import lazy_table as lt
def fib_table(n):
x0, x1 = 0, 1
yield [0, x0]
yield [1, x1]
for i in range(2, n + 1):
time.sleep(1) # Simulate work
x0, x1 = x1, x0 + x1
yield [i, x1]
lt.stream(fib_table(10), headers=['N', 'F_N'])
Your final table should look like this:
N F_N
--- -----
0 0
1 1
2 1
3 2
4 3
5 5
6 8
7 13
8 21
9 34
10 55
You can also specify an "artist" that determines how the table is rendered. For example, the ConsoleWithProgress artist displays a progress bar alongside the table indicating the percentage of rows completed:
n_rows = 10
artist = lt.artists.ConsoleWithProgress()
lt.stream(fib_table(n_rows), headers=['N', 'F_N'], n_rows=n_rows, artist=artist)
2 Jul 15, 2022
22 Dec 5, 2022
6.7k Dec 31, 2022
18.6k Dec 30, 2022
659 Dec 28, 2022
56 Nov 10, 2022
31 Dec 3, 2022
41.4k Jan 3, 2023
5.8k Jan 3, 2023
79 Dec 02, 2022
7 Aug 13, 2022
40 Jan 03, 2023
1 Dec 30, 2021
77 Dec 01, 2022
2 Apr 04, 2022
14.5k Jan 03, 2023
17 Dec 11, 2022
1.7k Jan 02, 2023
96 Jan 02, 2023
3.4k Dec 30, 2022
4 Aug 04, 2022
1 Nov 29, 2021
25 Dec 22, 2022
2 Apr 01, 2022
6 Jan 14, 2022
0 Oct 07, 2021
1.3k Jan 08, 2023
51 Nov 29, 2022
9 Dec 02, 2022