Alternative to locals() in printing a table with a

问题:

[Python 3.1]

Edit: mistake in the original code.

I need to print a table. The first row should be a header, which consists of column names separated by tabs. The following rows should contain the data (also tab-separated).

To clarify, let's say I have columns "speed", "power", "weight". I originally wrote the following code, with the help from a related question I asked earlier:

column_names = ['speed', 'power', 'weight']

def f(row_number):
  # some calculations here to populate variables speed, power, weight
  # e.g., power = retrieve_avg_power(row_number) * 2.5
  # e.g., speed = math.sqrt(power) / 2
  # etc.
  locals_ = locals()
  return {x : locals_[x] for x in column_names}

def print_table(rows):
  print(*column_names, sep = '\t')
  for row_number in range(rows):
    row = f(row_number)
    print(*[row[x] for x in component_names], sep = '\t')

But then I learned that I should avoid using locals() if possible.

Now I'm stuck. I don't want to type the list of all the column names more than once. I don't want to rely on the fact that every dictionary I create inside f() is likely to iterate through its keys in the same order. And I don't want to use locals().

Note that the functions print_table() and f() do a lot of other stuff; so I have to keep them separate.

How should I write the code?

回答1:

class Columns:
    pass

def f(row_number):
    c = Columns()
    c.power = retrieve_avg_power(row_number) * 2.5
    c.speed = math.sqrt(power) / 2
    return c.__dict__

This also lets you specify which of the variables are meant as columns, instead of rather being temporary in the function.

回答2:

You could use an OrderedDict to fix the order of the dictionaries. But as I see it that isn't even necessary. You are always taking the keys from the column_names list (except in the last line, I assume that is a typo), so the order of the values will always be the same.

回答3:

an alternative to locals() will be to use the inspect module

import inspect

def f(row_number):
    # some calculations here to populate variables speed, power, weight
    # e.g., power = retrieve_avg_power(row_number) * 2.5
    # e.g., speed = math.sqrt(power) / 2
    # etc.
    locals_ = inspect.currentframe().f_locals
    return {x : locals_[x] for x in column_names }