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Imitation of Perl double quoted strings in Python

Python String Formatting Best Practices – Real Python

Python 3.6 added a new string formatting approach called formatted string literals or “f-strings”. This new way of formatting strings lets you use embedded Python expressions inside string constants. Here’s a simple example to give you a feel for the feature:

>>>
>>> f'Hello, {name}!'
'Hello, Bob!'

As you can see, this prefixes the string constant with the letter “f“—hence the name “f-strings.” This new formatting syntax is powerful. Because you can embed arbitrary Python expressions, you can even do inline arithmetic with it. Check out this example:

>>>
>>> a = 5
>>> b = 10
>>> f'Five plus ten is {a + b} and not {2 * (a + b)}.'
'Five plus ten is 15 and not 30.'

Formatted string literals are a Python parser feature that converts f-strings into a series of string constants and expressions. They then get joined up to build the final string.

Imagine you had the following greet() function that contains an f-string:

>>>
>>> def greet(name, question):
...     return f"Hello, {name}! How's it {question}?"
...
>>> greet('Bob', 'going')
"Hello, Bob! How's it going?"

When you disassemble the function and inspect what’s going on behind the scenes, you’ll see that the f-string in the function gets transformed into something similar to the following:

>>>
>>> def greet(name, question):
...    return "Hello, " + name + "! How's it " + question + "?"

The real implementation is slightly faster than that because it uses the BUILD_STRING opcode as an optimization. But functionally they’re the same:

>>>
>>> import dis
>>> dis.dis(greet)
  2           0 LOAD_CONST               1 ('Hello, ')
              2 LOAD_FAST                0 (name)
              4 FORMAT_VALUE             0
              6 LOAD_CONST               2 ("! How's it ")
              8 LOAD_FAST                1 (question)
             10 FORMAT_VALUE             0
             12 LOAD_CONST               3 ('?')
             14 BUILD_STRING             5
             16 RETURN_VALUE

String literals also support the existing format string syntax of the str.format() method. That allows you to solve the same formatting problems we’ve discussed in the previous two sections:

>>>
>>> f"Hey {name}, there's a {errno:#x} error!"
"Hey Bob, there's a 0xbadc0ffee error!"

Python’s new formatted string literals are similar to JavaScript’s Template Literals added in ES2015. I think they’re quite a nice addition to Python, and I’ve already started using them in my day to day (Python 3) work. You can learn more about formatted string literals in our in-depth Python f-strings tutorial.

#4 Template Strings (Standard Library)

Here's one more tool for string formatting in Python: template strings. It's a simpler and less powerful mechanism, but in some cases this might be exactly what you're looking for.

Let's take a look at a simple greeting example:

>>>
>>> from string import Template
>>> t = Template('Hey, $name!')
>>> t.substitute(name=name)
'Hey, Bob!'

You see here that we need to import the Template class from Python's built-in string module. Template strings are not a core language feature but they're supplied by the string module in the standard library.

Another difference is that template strings don't allow format specifiers. So in order to get the previous error string example to work, you'll need to manually transform the int error number into a hex-string:

>>>
>>> templ_string = 'Hey $name, there is a $error error!'
>>> Template(templ_string).substitute(
...     name=name, error=hex(errno))
'Hey Bob, there is a 0xbadc0ffee error!'

That worked great.

So when should you use template strings in your Python programs? In my opinion, the best time to use template strings is when you're handling formatted strings generated by users of your program. Due to their reduced complexity, template strings are a safer choice.

The more complex formatting mini-languages of the other string formatting techniques might introduce security vulnerabilities to your programs. For example, it's possible for format strings to access arbitrary variables in your program.

That means, if a malicious user can supply a format string, they can potentially leak secret keys and other sensitive information! Here's a simple proof of concept of how this attack might be used against your code:

>>>
>>> # This is our super secret key:
>>> SECRET = 'this-is-a-secret'

>>> class Error:
...      def __init__(self):
...          pass

>>> # A malicious user can craft a format string that
>>> # can read data from the global namespace:
>>> user_input = '{error.__init__.__globals__[SECRET]}'

>>> # This allows them to exfiltrate sensitive information,
>>> # like the secret key:
>>> err = Error()
>>> user_input.format(error=err)
'this-is-a-secret'

See how a hypothetical attacker was able to extract our secret string by accessing the __globals__ dictionary from a malicious format string? Scary, huh? Template strings close this attack vector. This makes them a safer choice if you're handling format strings generated from user input:

>>>
>>> user_input = '${error.__init__.__globals__[SECRET]}'
>>> Template(user_input).substitute(error=err)
ValueError:
"Invalid placeholder in string: line 1, col 1"

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Which String Formatting Method Should You Use?

I totally get that having so much choice for how to format your strings in Python can feel very confusing. This is an excellent cue to bust out this handy flowchart infographic I've put together for you:

Python String Formatting Rule of Thumb (Image: Click to Tweet)

This flowchart is based on the rule of thumb that I apply when I'm writing Python:

Python String Formatting Rule of Thumb: If your format strings are user-supplied, use Template Strings (#4) to avoid security issues. Otherwise, use Literal String Interpolation/f-Strings (#3) if you're on Python 3.6+, and "New Style" str.format (#2) if you're not.

Key Takeaways

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Python String Formatting Tips & Best Practices

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Last modified: November 13, 2019