Magical Syntax

The Mystery of Curly Braces

You might be puzzled by the curly brace syntax in Python's f-Strings, for example, why f'{{{74}}}' and f'{{74}}' output the same result {74}? In fact, this demonstrates a magical feature of f-Strings.

In f-Strings, curly braces {} are used to represent an expression, not a literal. So in f'{{{74}}}', the two pairs of curly braces are interpreted as one pair of curly braces, with the expression 74 inside. When Python processes this string, it first evaluates the expression inside the curly braces, getting the result 74, and then inserts it into the string. This explains why two seemingly different strings ultimately produce the same output.

This feature is very convenient, allowing us to directly insert the results of any Python expression into a string without manual concatenation. Don't you think this trick is cool? You can make good use of it when formatting strings.

The Trail of Indices

I know you might also find it perplexing to use list indices as iteration variables in Python's for loops. Indeed, we usually use list elements as iteration variables, but indices can be used too!

The reason is that Python's for loop is essentially iterating over an iterable object. And the indices of a list happen to be an iterable object, which will generate 0, 1, 2... up to the last index in sequence. So we can absolutely use it as an iteration variable.

Although this usage is not common, it's quite useful in certain scenarios. For example, when you need to access both list elements and indices simultaneously, you can write:

my_list = ['apple', 'banana', 'orange']
for i, fruit in enumerate(my_list):
    print(f'Index {i}: {fruit}')

The output would be:

Index 0: apple
Index 1: banana 
Index 2: orange

This way, you can conveniently get both the elements and their corresponding indices. Don't you think this little trick is pretty neat? You can apply it in appropriate situations.

The Mystery of Infinity

Speaking of some special values in Python, I'm sure you're curious about the behavior of inf and nan. For instance, why does (inf + 0j)*1 result in inf + nanj?

The key here is that inf and nan are not ordinary values; they represent the special concepts of infinity and not-a-number. When adding them to the complex number 0j, the result is still inf, because infinity plus any finite value is still infinity.

However, when inf and nan are involved in operations, according to the IEEE 754 floating-point standard, the result becomes another special value nan. So (inf + 0j)*1 ultimately results in inf + nanj.

This seemingly strange behavior is actually the result of Python (and most programming languages) following the standard when performing operations on these special values. Although we don't often encounter this in daily programming, understanding the principles behind it is very helpful for a deeper understanding of floating-point arithmetic.

Another interesting detail is that the value of hash(inf) in Python actually contains the digits of π! This is not intentional, just an interesting coincidence. In Python's underlying C language implementation, the hash value of inf happens to include the first few digits of π. This little detail reflects some interesting designs and accidental results in the implementation of programming languages, giving us a deeper understanding of the internal mechanisms of the language.

Elegant Judgments

Finally, let's look at a classic problem: how to elegantly express complex conditional judgments like ((x == a and y == b) or (x == b and y == a))?

Of course, we can write it directly like this, but the code readability is not very good. A more elegant way to write it is:

if (x, y) in [(a, b), (b, a)]:
    # Do something

This method utilizes the characteristics of tuples and lists, making the code more concise and readable. (x, y) is a tuple, and [(a, b), (b, a)] is a list containing all possible matching situations.

When the value of (x, y) is in the list, the condition will be considered true. So one line of code can express such a complex logical relationship!

Don't you think this approach is clever? I personally believe that being good at using language features to simplify code not only improves readability but also enhances code maintainability. Of course, this requires a deeper understanding of the language, but as long as you think more, you can definitely write beautiful Python code.

In conclusion, Python is full of magic and surprises everywhere. As long as you carefully experience it, you will gain a lot. I hope that through today's sharing, you can also understand and apply some of Python's features more deeply. The road of coding is long and arduous, let's work hard together and grow together!