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
7 Aug 19, 2022
781 Jan 01, 2023
305 Dec 17, 2022
164 Dec 14, 2022
4 Nov 17, 2022
1 Jan 05, 2022
10.5k Jan 08, 2023
3 Mar 23, 2022
20 Dec 21, 2022
1 Jul 24, 2022
12 Jan 29, 2022
1.1k Jan 04, 2023
3 Jan 23, 2022
68 Dec 30, 2022
32 Jun 23, 2022
1 Nov 17, 2021
641 Jan 03, 2023
2.8k Jan 05, 2023
12 Jan 25, 2021
2 Mar 11, 2022