In Python, __all__ is a list of strings that defines the names that should be imported when from <module> import * is used.
Python module Python __import__ Python class What does __all__ mean in Python? - Stack OverflowBashir Alam He is a Computer Science graduate from the University of Central Asia, currently employed as a full-time Machine Learning Engineer at uExel. His expertise lies in Python, Java, Machin...
https://stackoverflow.com/questions/14379753/what-does-mean-in-python-function-definitions https://www.python.org/dev/peps/pep-3107/ Wow, I missed quite a broad area of knowledge - not only return value annotations, but also parameter annotations. Thank you very much :) And the__annotations...
** -> using the magic method __pow__ Let's say this is our code: a = 5 B = 2 Typing a**B is the same as (a).__pow__(B) The name for this sign is "exponential" This topic is explained more in the object oriented programming lessons 11th Jun 2017, 4:35 PM Elad Goldenbe...
If you come from C/C++, you may be confused about the standalone _ in Python code. It a...
Do you want to add a value into a Python string? You need not look further than the %s operator. This operator lets you format a value inside a string. The %s syntax is more elegant than the concatenation operator with which you may be familiar. In this guide, we talk about what the...
https://stackoverflow.com/questions/14379753/what-does-mean-in-python-function-definitions https://www.python.org/dev/peps/pep-3107/ Wow, I missed quite a broad area of knowledge - not only return value annotations, but also parameter annotations. Thank you very much :) ...
operator in Python. Python uses "not" instead. != means not equal. 24th May 2019, 6:53 AM Anna + 1 Exclamation mark is represented not operator which convert 1 to 0 and 0 to 1 24th May 2019, 6:35 AM Abhi + 1 Well Not operator (!) Is a logical operator that returns the ...
numpy.reshape(): In this tutorial, we will learn about the numpy.reshape() method, and what does -1 mean in this method.
Python code to demonstrate the use of [:, :] in NumPy arrays # Import numpyimportnumpyasnp# Creating a numpy arrayarr=np.zeros((3,3))# Display original imageprint("Original Array:\n",arr,"\n")# working on all rows but a specific columnarr[1, :]=3# Display resultprint("Result:...