Format output string, right alignment

I am processing a text file containing coordinates x, y, z

     1      128  1298039
123388        0        2
....

every line is delimited into 3 items using

words = line.split()

After processing data I need to write coordinates back in another txt file so as items in each column are aligned right (as well as the input file). Every line is composed of the coordinates

line_new = words[0]  + '  ' + words[1]  + '  ' words[2].

Is there any manipulator like std::setw() etc. in C++ allowing to set the width and alignment?

Answers:

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Method 1

Try this approach using the newer str.format syntax:

line_new = '{:>12}  {:>12}  {:>12}'.format(word[0], word[1], word[2])

And here’s how to do it using the old % syntax (useful for older versions of Python that don’t support str.format):

line_new = '%12s  %12s  %12s' % (word[0], word[1], word[2])

Method 2

You can align it like that:

print('{:>8} {:>8} {:>8}'.format(*words))

where > means “align to right” and 8 is the width for specific value.

And here is a proof:

>>> for line in [[1, 128, 1298039], [123388, 0, 2]]:
    print('{:>8} {:>8} {:>8}'.format(*line))


       1      128  1298039
  123388        0        2

Ps. *line means the line list will be unpacked, so .format(*line) works similarly to .format(line[0], line[1], line[2]) (assuming line is a list with only three elements).

Method 3

It can be achieved by using rjust:

line_new = word[0].rjust(10) + word[1].rjust(10) + word[2].rjust(10)

Method 4

Here is another way how you can format using ‘f-string’ format:

print(
    f"{'Trades:':<15}{cnt:>10}",
    f"n{'Wins:':<15}{wins:>10}",
    f"n{'Losses:':<15}{losses:>10}",
    f"n{'Breakeven:':<15}{evens:>10}",
    f"n{'Win/Loss Ratio:':<15}{win_r:>10}",
    f"n{'Mean Win:':<15}{mean_w:>10}",
    f"n{'Mean Loss:':<15}{mean_l:>10}",
    f"n{'Mean:':<15}{mean_trd:>10}",
    f"n{'Std Dev:':<15}{sd:>10}",
    f"n{'Max Loss:':<15}{max_l:>10}",
    f"n{'Max Win:':<15}{max_w:>10}",
    f"n{'Sharpe Ratio:':<15}{sharpe_r:>10}",
)

This will provide the following output:

Trades:              2304
Wins:                1232
Losses:              1035
Breakeven:             37
Win/Loss Ratio:      1.19
Mean Win:           0.381
Mean Loss:         -0.395
Mean:               0.026
Std Dev:             0.56
Max Loss:          -3.406
Max Win:             4.09
Sharpe Ratio:      0.7395

What you are doing here is you are saying that the first column is 15 chars long and it’s left-justified and the second column (values) is 10 chars long and it’s right-justified.

If you joining items from the list and you want to format space between items you can use “ and regular formatting techniques.

This example separates each number by 3 spaces. The key here is f”{”:>3}”

print(f"{'':>3}".join(str(i) for i in range(1, 11)))

output:

1   2   3   4   5   6   7   8   9   10

Method 5

I really enjoy a new literal string interpolation in Python 3.6+:

line_new = f'{word[0]:>12}  {word[1]:>12}  {word[2]:>12}'

Reference: PEP 498 — Literal String Interpolation

Method 6

Simple tabulation of the output:

a = 0.3333333
b = 200/3
print("variable a    variable b")
print("%10.2f    %10.2f" % (a, b))

output:

variable a    variable b
      0.33         66.67

%10.2f: 10 is the minimum length and 2 is the number of decimal places.

Method 7

To do it by using f-string and with control of the number of trailing digits:

print(f'A number -> {my_number:>20.5f}')

Method 8

Mixing Vlad’s fine content with others, the code can also be written for readabily and ease-of-use like …

>>> cnt = wins = losses      = str(   2)
>>> evens = win_r = mean_w   = str(  14)
>>> mean_l = mean_trd = sd   = str( 336)
>>> max_l = max_w = sharpe_r = str(4278)
>>>
>>> rpad = 10
>>>
>>> print(
...     'n Trades         ' +      cnt.rjust(rpad),
...     'n Wins           ' +     wins.rjust(rpad),
...     'n Losses         ' +   losses.rjust(rpad),
...     'n Breakeven      ' +    evens.rjust(rpad),
...     'n Win/Loss Ratio ' +    win_r.rjust(rpad),
...     'n Mean Win       ' +   mean_w.rjust(rpad),
...     'n Mean Loss      ' +   mean_l.rjust(rpad),
...     'n Mean           ' + mean_trd.rjust(rpad),
...     'n Std Dev        ' +       sd.rjust(rpad),
...     'n Max Loss       ' +    max_l.rjust(rpad),
...     'n Max Win        ' +    max_w.rjust(rpad),
...     'n Sharpe Ratio   ' + sharpe_r.rjust(rpad),
... )

 Trades                  2
 Wins                    2
 Losses                  2
 Breakeven              14
 Win/Loss Ratio         14
 Mean Win               14
 Mean Loss             336
 Mean                  336
 Std Dev               336
 Max Loss             4278
 Max Win              4278
 Sharpe Ratio         4278

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