Limit list size python

How to create a fix size list in python?

There are a few ways to create a fixed size list in Python, and each method has its own advantages and disadvantages. In this tutorial, we will go through some of the most common ways to create a fixed size list in Python.

Method 1: Using the list() function

fixed_list.append(1) fixed_list.append(2) fixed_list.append(3)

• Step 3 — To create a fixed size list, you can simply use the len() function to check the length of the list and limit the number of elements in the list.

MAX_SIZE = 5 if len(fixed_list) >= MAX_SIZE: fixed_list.pop()

Method 2: Using the array.array() class

The first argument to the array() class is the type code of the elements that you want to store in the array, and the second argument is an iterable containing the elements to store in the array.

from array import array fixed_list = array("i", [1, 2, 3])

• Step 2 — As with the previous method you can use the len() function to check the length of the list and limit the number of elements in the list.

MAX_SIZE = 5 if len(fixed_list) >= MAX_SIZE: fixed_list.pop()

Method 3: Using the collections.deque() class

• Step 1 — The collections module provides a deque() class that you can use to create a fixed size list

The first argument to the deque() class is an iterable containing the elements to store in the deque, and the second argument is an optional maximum size for the deque.

from collections import deque fixed_list = deque([1, 2, 3], maxlen=5)

• Step 2 — Once the maxlen is reached, new element will be added and the oldest one will be removed from the deque

This way it will maintain the fixed size.

fixed_list.append(4) fixed_list.append(5) fixed_list.append(6)

Method 4: Using List comprehension

• Step 1 — Using list comprehension, you can create a list of a fixed size by specifying the number of elements you want in the list

This can be done using a for loop and the range function.

fixed_list = [x for x in range(5)]

• Step 2 — You can also use list comprehension to create a fixed size list by specifying the number of elements and the value of each element in the list

fixed_list = [0 for x in range(5)]

Method 5: Using the * operator

• Step 1 — You can create a fixed size list by using the * operator to replicate a single element multiple times

multiplying a single element by the number of times you want it to be replicated in the list.

Method 6: Using itertools.repeat()

• Step 1 — The itertools module provides a repeat() function that you can use to create a fixed size list

The first argument to the repeat() function is the element you want to repeat, and the second argument is the number of times you want the element to be repeated.

import itertools fixed_list = list(itertools.repeat(0, 5))

Conclusion

In conclusion, creating a fixed size list in Python can be done using a variety of methods, each with its own advantages and disadvantages. The list() function, the array.array() class, the collections.deque() class, list comprehension, the * operator and the itertools.repeat() function are all commonly used methods for creating fixed size lists in Python. The best method to use will depend on the specific use case and the requirements of the project. It’s important to understand the behavior and constraints of each method and to choose the one that best fits your needs.

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How to set a max length for a python list/set?

Setting a maximum length for a Python list or set can be useful in cases where you want to limit the size of the data structure in order to prevent memory or performance issues. There are a few different methods for implementing this restriction, depending on the specific requirements of your project.

Method 1: Using a subclass

To set a maximum length for a Python list or set using a subclass, you can create a custom class that inherits from the built-in list or set class and override the methods that modify the list or set to enforce the maximum length. Here’s an example implementation:

class MaxLengthList(list): def __init__(self, max_length): super().__init__() self.max_length = max_length def append(self, value): if len(self)  self.max_length: super().append(value) else: raise ValueError('Max length exceeded') class MaxLengthSet(set): def __init__(self, max_length): super().__init__() self.max_length = max_length def add(self, value): if len(self)  self.max_length: super().add(value) else: raise ValueError('Max length exceeded')

In this example, the MaxLengthList and MaxLengthSet classes have a max_length attribute that specifies the maximum length of the list or set. The append and add methods are overridden to check if the length of the list or set is less than the maximum length before adding a new value. If the length exceeds the maximum, a ValueError is raised.

Here’s an example usage of the MaxLengthList and MaxLengthSet classes:

>>> l = MaxLengthList(3) >>> l.append(1) >>> l.append(2) >>> l.append(3) >>> l [1, 2, 3] >>> l.append(4) Traceback (most recent call last): File "", line 1, in module> File "", line 9, in append ValueError: Max length exceeded >>> s = MaxLengthSet(2) >>> s.add(1) >>> s.add(2) >>> s 1, 2> >>> s.add(3) Traceback (most recent call last): File "", line 1, in module> File "", line 9, in add ValueError: Max length exceeded

In this example, the MaxLengthList is initialized with a maximum length of 3, so it can hold up to 3 elements. The append method is used to add 3 elements to the list, which succeeds. However, when a fourth element is added, a ValueError is raised because the maximum length has been exceeded.

Similarly, the MaxLengthSet is initialized with a maximum length of 2, so it can hold up to 2 elements. The add method is used to add 2 elements to the set, which succeeds. However, when a third element is added, a ValueError is raised because the maximum length has been exceeded.

Method 2: Using a collections.deque

To set a maximum length for a Python list/set, you can use the collections.deque class. A deque is a double-ended queue that allows you to add and remove elements from both ends. By setting the maximum length of the deque, you can limit the number of elements that can be added to the deque.

Here’s an example of how to create a deque with a maximum length of 5:

from collections import deque my_deque = deque(maxlen=5)

Now, you can add elements to the deque using the append() method:

my_deque.append(1) my_deque.append(2) my_deque.append(3) my_deque.append(4) my_deque.append(5)

If you try to add another element to the deque, it will automatically remove the oldest element:

my_deque.append(6) print(my_deque)

You can also add multiple elements at once using the extend() method:

my_deque.extend([7, 8, 9]) print(my_deque)

To remove elements from the deque, you can use the popleft() method to remove the oldest element or the pop() method to remove the newest element:

my_deque.popleft() print(my_deque) my_deque.pop() print(my_deque)

In conclusion, using a collections.deque with a maximum length is a simple and efficient way to limit the number of elements in a Python list/set.

Method 3: Using a queue.Queue

If you want to limit the size of a list or set in Python, you can use the queue.Queue class. This class provides a thread-safe way to implement a FIFO (first-in, first-out) queue, which can be used to enforce a maximum size on a list or set.

Here is an example code that demonstrates how to use queue.Queue to limit the size of a list:

import queue q = queue.Queue(maxsize=3) q.put(1) q.put(2) q.put(3) q.put(4) q.get() q.put(4) elements = [] while not q.empty(): elements.append(q.get()) print(elements)

In this example, we create a queue.Queue object with a maximum size of 3. We then add 3 elements to the queue, and try to add a fourth element. Since the queue is already full, the put() method will block until an element is removed from the queue.

We then remove one element from the queue using the get() method, and add another element to the queue. Finally, we retrieve all elements from the queue using a loop, and print them out.

Using queue.Queue to limit the size of a set is very similar. Here is an example code:

import queue q = queue.Queue(maxsize=3) s = set() s.add(1) s.add(2) s.add(3) q.put(4) s.add(q.get()) q.put(4) s.add(q.get()) print(s)

In this example, we create a queue.Queue object with a maximum size of 3, and a set. We add 3 elements to the set, and try to add a fourth element. Since the set is already full, we remove one element from the queue using the get() method, and add the new element to the set.

We then add another element to the queue, remove another element from the queue using the get() method, and add the new element to the set. Finally, we print out the set.

Overall, using queue.Queue to limit the size of a list or set is a simple and effective way to enforce a maximum size constraint.

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Limit size of a List

Hi bumsfeld,

I believe that the array data structure in the Numeric/NumPy package is both typed and non-resizable, just like C arrays (actually, I’m pretty sure that these data structures are C arrays wearing a Python hat). Check out:

http://numeric.scipy.org

Thanks G-Do for your information, so NumPy eventually replaces Numeric and Numarray. Interesting!

When I was coding in C, I used to sample lab data and put it into a circular or ring buffer to keep the thing from overflowing. This was an easy way to calculate a moving …

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Hi bumsfeld, I believe that the array data structure in the Numeric/NumPy package is both typed and non-resizable, just like C arrays (actually, I’m pretty sure that these data structures are C arrays wearing a Python hat). Check out: http://numeric.scipy.org

Thanks G-Do for your information, so NumPy eventually replaces Numeric and Numarray. Interesting! When I was coding in C, I used to sample lab data and put it into a circular or ring buffer to keep the thing from overflowing. This was an easy way to calculate a moving average. You can do a similar thing in Python using a list and keeping track of the index. When the index reaches the limit you have set, new data starts at index zero again. A queue makes this simpler, particularly the deque container, because you can add to the end and pop the front. Here is an example, I hope you can see what is happening:

# the equivalent of a circular size limited list # also known as ring buffer, pops the oldest data item # to make room for newest data item when max size is reached # uses the double ended queue available in Python24 from collections import deque class RingBuffer(deque): """ inherits deque, pops the oldest data to make room for the newest data when size is reached """ def __init__(self, size): deque.__init__(self) self.size = size def full_append(self, item): deque.append(self, item) # full, pop the oldest item, left most item self.popleft() def append(self, item): deque.append(self, item) # max size reached, append becomes full_append if len(self) == self.size: self.append = self.full_append def get(self): """returns a list of size items (newest items)""" return list(self) # testing if __name__ == '__main__': size = 5 ring = RingBuffer(size) for x in range(9): ring.append(x) print ring.get() # test """ notice that the left most item is popped to make room result = [0] [0, 1] [0, 1, 2] [0, 1, 2, 3] [0, 1, 2, 3, 4] [1, 2, 3, 4, 5] [2, 3, 4, 5, 6] [3, 4, 5, 6, 7] [4, 5, 6, 7, 8] """

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