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  • Book Overview & Buying Modern Python Standard Library Cookbook
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Modern Python Standard Library Cookbook

Modern Python Standard Library Cookbook

By : Molina
4.4 (7)
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Modern Python Standard Library Cookbook

Modern Python Standard Library Cookbook

4.4 (7)
By: Molina

Overview of this book

The Python 3 Standard Library is a vast array of modules that you can use for developing various kinds of applications. It contains an exhaustive list of libraries, and this book will help you choose the best one to address specific programming problems in Python. The Modern Python Standard Library Cookbook begins with recipes on containers and data structures and guides you in performing effective text management in Python. You will find Python recipes for command-line operations, networking, filesystems and directories, and concurrent execution. You will learn about Python security essentials in Python and get to grips with various development tools for debugging, benchmarking, inspection, error reporting, and tracing. The book includes recipes to help you create graphical user interfaces for your application. You will learn to work with multimedia components and perform mathematical operations on date and time. The recipes will also show you how to deploy different searching and sorting algorithms on your data. By the end of the book, you will have acquired the skills needed to write clean code in Python and develop applications that meet your needs.
Table of Contents (16 chapters)
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Unpacking multiple keyword arguments

Frequently, you ended up in a situation where you had to provide arguments to a function from a dictionary. If you've ever faced that need, you probably also ended up in a case where you had to take the arguments from multiple dictionaries.

Generally, Python functions accept arguments from a dictionary through unpacking (the ** syntax), but so far, it hasn't been possible to use unpacking twice in the same call, nor was there an easy way to merge two dictionaries.

How to do it...

The steps for this recipe are:

  1. Given a function, f, we want to pass the arguments from two dictionaries, d1 and d2 as follows:
>>> def f(a, b, c, d):
... print (a, b, c, d)
...
>>> d1 = dict(a=5, b=6)
>>> d2 = dict(b=7, c=8, d=9)
  1. collections.ChainMap can help us achieve what we want; it can cope with duplicated entries and works with any Python version:
>>> f(**ChainMap(d1, d2))
5 6 8 9
  1. In Python 3.5 and newer versions, you can also create a new dictionary by combining multiple dictionaries through the literal syntax, and then pass the resulting dictionary as the argument of the function:
>>> f(**{**d1, **d2})
5 7 8 9
  1. In this case, the duplicated entries are accepted too, but are handled in reverse order of priority to ChainMap (so right to left). Notice how b has a value of 7, instead of the 6 it had with ChainMap, due to the reversed order of priorities.

This syntax might be harder to read due to the amount of unpacking operators involved, and with ChainMap it is probably more explicit what's happening for a reader.

How it works...

As we already know from the previous recipe, ChainMap looks up keys in all the provided dictionaries, so it's like the sum of all the dictionaries. The unpacking operator (**) works by inviting all keys to the container and then providing an argument for each key.

As ChainMap has keys resulting from the sum of all the provided dictionaries keys, it will provide the keys contained in all the dictionaries to the unpacking operator, thus allowing us to provide keyword arguments from multiple dictionaries.

There's more...

Since Python 3.5 through PEP 448, it's now possible to unpack multiple mappings to provide keyword arguments:

>>> def f(a, b, c, d):
...     print (a, b, c, d)
...
>>> d1 = dict(a=5, b=6)
>>> d2 = dict(c=7, d=8)
>>> f(**d1, **d2)
5 6 7 8

This solution is very convenient, but has two limits:

  • It's only available in Python 3.5+
  • It chokes on duplicated arguments

If you don't know where the mappings/dictionaries you are unpacking come from, it's easy to end up with the issue of duplicated arguments:

>>> d1 = dict(a=5, b=6)
>>> d2 = dict(b=7, c=8, d=9)
>>> f(**d1, **d2)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: f() got multiple values for keyword argument 'b'

In the previous example, the b key is declared in both d1 and d2, and that causes the function to complain that it received duplicate arguments.

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