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Python: Strong (or Strict) Typing

Python is one of the languages that is strict about data types. So it will respond to any type incompatibility with an error. It is all about strong typing.

We know about two different types of data: numbers and strings. For example, we could add numbers, because the addition operation is an operation for the "numbers" type. But what if we applied this operation not to two numbers, but to a number and a string?

print(1 + '7')  # TypeError: unsupported operand type(s)...

Python will not allow adding the number 1 and the string '7', because they are of different types. You have to first either make the string a number or the number a string. We'll talk about how to do that later.

This pedantic attitude towards type compatibility is called strict typing or strong typing. Python is a language with strict typing.

Not all languages do this. For example, PHP is a language with weak typing. It is aware of the existence of different types, but is not very strict about their use. PHP tries to convert information when it makes sense. The same goes for JavaScript:

// What do you think of that, Elon Musk?
// Number 1 + Line 7 = Line 17
1 + '7'; // '17'

On the one hand, automatic implicit type conversion does seem convenient. But in practice this language's property creates a lot of errors and problems that are hard to find. The code may sometimes work and sometimes not work, depending on whether you have "luck" with automatic conversion or not. The programmer will not notice this immediately and will spend a lot of time on debugging.


Print the result of the expression: 7 - (-8 - -2). Try to make the number 7 a string instead of a number. Experiment with other numbers too.

The exercise doesn't pass checking. What to do? 😶

If you've reached a deadlock it's time to ask your question in the «Discussions». How ask a question correctly:

  • Be sure to attach the test output, without it it's almost impossible to figure out what went wrong, even if you show your code. It's complicated for developers to execute code in their heads, but having a mistake before their eyes most probably will be helpful.
In my environment the code works, but not here 🤨

Tests are designed so that they test the solution in different ways and against different data. Often the solution works with one kind of input data but doesn't work with others. Check the «Tests» tab to figure this out, you can find hints at the error output.

My code is different from the teacher's one 🤔

It's fine. 🙆 One task in programming can be solved in many different ways. If your code passed all tests, it complies with the task conditions.

In some rare cases, the solution may be adjusted to the tests, but this can be seen immediately.

I've read the lessons but nothing is clear 🙄

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