Sometimes, we want to deep copy a list with Python.
In this article, we’ll look at how to deep copy a list with Python.
To deep copy a list with Python, we can use the copy.deepcopy method.
For instance, we write
import copy
a = [[1, 2, 3], [4, 5, 6]]
b = copy.deepcopy(a)
to call copy.deepcopy with a to return a deep copy of a and assign it to b.
To deep copy a list with Python, we can use the copy.deepcopy method.
Sometimes, we want to combine two dicts and add values for keys that appear in both with Python.
In this article, we’ll look at how to combine two dicts and add values for keys that appear in both with Python.
To combine two dicts and add values for keys that appear in both with Python, we can use the Counter class.
For instance, we write
from collections import Counter
A = Counter({'a':1, 'b':2, 'c':3})
B = Counter({'b':3, 'c':4, 'd':5})
C = A + B
to create Counter objects from the dicts.
Then we combine them into one and add the values with the given keys together with +.
To combine two dicts and add values for keys that appear in both with Python, we can use the Counter class.
Sometimes, we want to plot in real-time in a while loop using Python matplotlib.
In this article, we’ll look at how to plot in real-time in a while loop using Python matplotlib.
To plot in real-time in a while loop using Python matplotlib, we can create a loop to plot the data and then call pause.
For instance, we write
import numpy as np
import matplotlib.pyplot as plt
plt.axis([0, 10, 0, 1])
for i in range(10):
y = np.random.random()
plt.scatter(i, y)
plt.pause(0.05)
plt.show()
to call scatter to plot a scatterplot.
Then we call pause to draw the new data and run the GUI’s `event loop.
And then we call show to show the GUI.
To plot in real-time in a while loop using Python matplotlib, we can create a loop to plot the data and then call pause.
Sometimes, we want to fix Python multiprocessing PicklingError: Can’t pickle function error.
In this article, we’ll look at how to fix Python multiprocessing PicklingError: Can’t pickle function error.
To fix Python multiprocessing PicklingError: Can’t pickle function error, we should only run pickle in top level functions.
For instance, we write
import multiprocessing as mp
# ...
def work(foo):
foo.work()
if __name__ == '__main__':
pool = mp.Pool()
pool.apply_async(work, args=(foo,))
pool.close()
pool.join()
to define the work top level function,
And then we call pool.apply_async with work and the args arguments to run work which runs foo.work, which runs the pickle code.
To fix Python multiprocessing PicklingError: Can’t pickle function error, we should only pickle top level functions.
Sometimes, we want to use global variables between files with Python.
In this article, we’ll look at how to use global variables between files with Python.
To use global variables between files with Python, we can import the variable in another module.
For instance, we write
settings.py
def init():
global my_list
my_list = []
to add the my_list global variable.
Then we import the variable in foo.py and use it by writing
import settings
def stuff():
settings.my_list.append('abc')
to import the global variables from settings.py with
import settings
And then we use it by calling settings.my_list.append.
To use global variables between files with Python, we can import the variable in another module.