1. Introduction
In Python programming, numeric types are extremely basic and critical data types, covering integers (ints), floats (floats), complexes, etc. These number types come with many practical built-in methods, and mastering these methods can significantly improve programming efficiency and code quality. This article will introduce in-depth methods for Python numeric types, supplemented by detailed code examples.
2. Built-in methods of integer type (int)
2.1 bit_length() method
This method is used to return the minimum number of digits required to represent the integer.
# Define an integernum = 10
# Use the bit_length() method to calculate the minimum number of bits required to represent the integerbit_length = num.bit_length()
print(f"Integer {num} The minimum number of digits required is: {bit_length}")
2.2 to_bytes() method
This method converts integers into byte objects of specified length and byte order.
# Define an integernum = 255
# Convert integers to byte objects with length 2 bytes and endianness as big endianbytes_obj = num.to_bytes(2, byteorder='big')
print(f"Integer {num} The converted byte object is: {bytes_obj}")
2.3 from_bytes() method
This method can convert byte objects into integers.
# Define a byte objectbytes_obj = b'\x01\x00'
# Convert byte objects to integers, with byte order to big endiannum = int.from_bytes(bytes_obj, byteorder='big')
print(f"Byte object {bytes_obj} The converted integer is: {num}")
3. Built-in methods of floating point number type (float)
3.1 as_integer_ratio() method
This method returns a tuple that contains two integers whose ratio is the floating point number.
# Define a floating point numbernum = 0.5
# Use the as_integer_ratio() method to return the integer ratio tuple representing the floating point numberratio = num.as_integer_ratio()
print(f"Floating point number {num} The integer ratio tuple is: {ratio}")
3.2 is_integer() method
This method is used to determine whether a floating point number is an integer.
# Define a floating point numbernum1 = 5.0
num2 = 5.5
# Determine whether num1 is an integeris_int1 = num1.is_integer()
# Determine whether num2 is an integeris_int2 = num2.is_integer()
print(f"Floating point number {num1} Is it an integer?: {is_int1}")
print(f"Floating point number {num2} Is it an integer?: {is_int2}")
3.3 hex() method
This method converts floating point numbers into hexadecimal strings.
# Define a floating point numbernum = 10.5
# Convert floating point numbers to hexadecimal stringshex_str = ()
print(f"Floating point number {num} The hexadecimal string representation is: {hex_str}")
3.4 fromhex() method
This method can convert hexadecimal strings into floating point numbers.
# Define a hexadecimal stringhex_str = '0x1.5p+3'
# Convert hexadecimal string to floating point numbernum = (hex_str)
print(f"Hexadecimal string {hex_str} The converted floating point number is: {num}")
4. Built-in methods of complex types
4.1 real attributes
This property is used to obtain the real part of the plural number.
# Define a plural numberc = 3 + 4j
# Get the real part of the plural numberreal_part =
print(f"plural {c} The real part is: {real_part}")
4.2 image attributes
This property is used to obtain the imaginary part of the plural number.
# Define a plural numberc = 3 + 4j
# Get the imaginary part of the plural numberimag_part =
print(f"plural {c} The imaginary part is: {imag_part}")
4.3 conjugate() method
This method is used to return the conjugated complex number of the complex number.
# Define a plural numberc = 3 + 4j
# Get the conjugated complex number of complex numbersconjugate_c = ()
print(f"plural {c} 的共轭plural是: {conjugate_c}")
5. Summary and Outlook
5.1 Summary
Python's numeric types (integral, floating point, complex) provide a wealth of built-in methods, which can implement various functions, such as bit counting, byte conversion, ratio acquisition, hexadecimal conversion, and complex operations. Proficient in using these built-in methods can make developers more efficient and convenient when handling digital related tasks.
5.2 Outlook
As Python becomes increasingly widely used in scientific computing, data analysis, machine learning and other fields, the demand for processing digital types will continue to increase. In the future, Python may further improve the built-in approach to digital types and add more practical features to meet the evolving technical needs. Developers need to continuously learn and master these new features to better use Python for programming and development.
This is the end of this article about the detailed explanation of the built-in methods of number types in Python. For more related built-in content in Python, please search for my previous articles or continue browsing the related articles below. I hope everyone will support me in the future!