Examples of using Python object in English and their translations into Chinese
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They can be any type of Python object.
Therefore, a and b are different names for the same Python object.
Is Python object oriented or procedural?
In Python, a for loop always iterates over a Python object:.
An exception is a Python object that represents an error.
Parsed XML documents are made up of various types of nodes,each represented by a Python object.
An exception is a Python object that represents an error.
First, let's explore a little bit andget a concrete sense of the actual memory usage of Python objects.
Not all python objects handle changes the same way.
The pickle module supports serialization of arbitrary Python objects to a binary format.
All Python objects and data structures are located in a private heap.
It provides functions that can serialize almost any Python object, including self-referential objects. .
The type of a Python object determines what kind of object it is;
Find_map uses the built-in function hash, which takes almost any Python object and returns an integer.
The type of a Python object determines what kind of object it is;
Py and contains Python object definitions and Python statements.
This means that there is a globally enforcedlock when trying to safely access Python objects from within threads.
It is simply creating a Python object that has useful helper functions.
Memory management in Python involves a private heap containing all Python objects and data structures.
A module is a Python object with arbitrarily named attributes that you can bind and reference.
The specifics of what this support function will do depend, in general,upon the states of various Python objects held in memory.
Appends any Python object as-is to the end of the list(i.e. as a last element in the list).
In scikit-learn, an estimator for classification is a Python object that implements the methods fit(X, y) and predict(T).
Because only one thread can aquire Python Objects/C API, the interpreter regularly releases and reacquires the lock every 100 bytecode of instructions.
In scikit-learn, an estimator for classification is a Python object that implements the methods fit(X, y) and predict(T).
A decorator is any callable Python object that is used to modify a function, method or class definition.
In scikit-learn, an estimator for classification is a Python object that implements the methods fit(X, y) and predict(T).
It creates a framework that can translate Python objects into R objects, pass them into R functions, and convert R output back into Python objects.