Hướng dẫn dynamic regex python

If alternative methods are options, you could compare list with list:

list_less_than_or_equal = ['less than or equal', 'lesser than or equal', 'lower than or equal', 'smaller than or equal','less than or equals', 'lesser than or equals', 'lower than or equals', 'smaller than or equals', 'less than equal', 'lesser than equal', 'higher than equal','less than equals', 'lesser than equals', 'higher than equals']

if any(word in 'When the loan amount is smaller than or equal to 50000' for word in list_less_than_or_equal):
  print("yep");
else:
  print("nope");

Or regex:

import re

list_less_than_or_equal = ['less than or equal', 'lesser than or equal', 'lower than or equal', 'smaller than or equal','less than or equals', 'lesser than or equals', 'lower than or equals', 'smaller than or equals', 'less than equal', 'lesser than equal', 'higher than equal','less than equals', 'lesser than equals', 'higher than equals']

if any(re.findall(r'|'.join(list_less_than_or_equal), 'When the loan amount is smaller than or equal to 50000', re.IGNORECASE)):
    print ('yep')
else:
    print ('nope')

In this lesson, you’ll learn about type systems, comparing dynamic typing and static typing. All programming languages include some kind of type system that formalizes which categories of objects it can work with and how those categories are treated.

Nội dung chính

• Dynamic Typing
• Static Typing
• What is the difference between static typing and dynamic typing?
• What is static typing in Python?
• What is dynamic typing feature in Python?
• What is the difference between dynamic and static programming?

Dynamic Typing

Python is a dynamically typed language. This means that the Python interpreter does type checking only as code runs, and the type of a variable is allowed to change over its lifetime. Here are a couple of examples that demonstrate those ideas:

>>>

>>> if False:
...     1 + "two"  # This line never runs, so no TypeError is raised
... else:
...     1 + 2
...
3
>>> 1 + "two"  # Now this is type checked
TypeError: unsupported operand type(s) for +: 'int' and 'str'

In the first example, the branch 1 + "two" never runs, so it’s never type checked. The second example shows that when 1 + "two" is evaluated, it raises a TypeError since you can’t add an integer and a string in Python.

In this next example, you see if variables can change type:

>>>

>>> thing = "Hello"
>>> type(thing)
<class 'str'>

>>> thing = 28.1
>>> type(thing)
<class 'float'>

type() returns the type of an object.

Static Typing

The opposite of dynamic typing is static typing. Static type checks are performed without running the program. In most statically typed languages, for instance C and Java, this is done as your program is compiled. The type of a variable is not allowed to change over its lifetime.

In this Hello World example in Java, look at the middle section, where String thing; is statically defined as a type of String and then assigned the value thing = "Hello World";:

public class HelloTypes {

    public static void main(String[] args) {

        String thing;
        thing = "Hello World";

        System.out.println(thing);
    }
}

This is not a course on Java, so don’t worry about the specifics of how to create Java code. The purpose of this example is to show you that there are extra steps in most statically typed languages.

In this next example, you would use the command javac to compile the program. This creates a new file with the same name, but a different extension .class instead of .java. That is the file that can be run using the java filename.class command:

$ javac HelloTypes.java
$ java HelloTypes.class
Hello World

If you were to try to reassign thing to a value that is of a different type, you will not get an error initially. Only when the code is compiled would you see the error:

public class HelloTypes {

    public static void main(String[] args) {

        String thing;
        thing = "Hello World";

        thing = 42;

        System.out.println(thing);
    }
}

The line thing = 42; is attempting to change the type of thing from a string to an int. If you compile this code, you will see the error:

$ javac Hellotypes.java
HelloTypes.java:8: error: incompatible types: int cannot be converted to String
    thing = 42;
1 error

Python will always remain a dynamically typed language. However, PEP 484 introduced type hints, which make it possible to also do static type checking of Python code.

Here are a few resources on bpython, the REPL(Read–Eval–Print Loop) tool used in these videos:

• A better Python REPL: bpython vs python
• bpython Homepage
• bpython Docs

What is the difference between static typing and dynamic typing?

There are two main differences between dynamic typing and static typing that you should be aware of when writing transformation scripts. First, dynamically-typed languages perform type checking at runtime, while statically typed languages perform type checking at compile time.

What is static typing in Python?

Static type checks are performed without running the program. In most statically typed languages, for instance C and Java, this is done as your program is compiled. With static typing, variables generally are not allowed to change types, although mechanisms for casting a variable to a different type may exist.

What is dynamic typing feature in Python?

Python is a dynamically typed language. This means that the Python interpreter does type checking only as code runs, and the type of a variable is allowed to change over its lifetime.

What is the difference between dynamic and static programming?

A dynamic language (Lisp, Perl, Python, Ruby) is designed to optimize programmer efficiency, so you can implement functionality with less code. A static language (C, C++, etc) is designed to optimize hardware efficiency, so that the code you write executes as quickly as possible.