How do I get the number of elements in the list items?

items = ["apple", "orange", "banana&quo开发者_JAVA技巧t;]

# There are 3 items.

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The len() function can be used with several different types in Python - both built-in types and library types. For example:

>>> len([1, 2, 3])
3

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How do I get the length of a list?

To find the number of elements in a list, use the builtin function len:

items = []
items.append("apple")
items.append("orange")
items.append("banana")

And now:

len(items)

returns 3.

Explanation

Everything in Python is an object, including lists. All objects have a header of some sort in the C implementation.

Lists and other similar builtin objects with a "size" in Python, in particular, have an attribute called ob_size, where the number of elements in the object is cached. So checking the number of objects in a list is very fast.

But if you're checking if list size is zero or not, don't use len - instead, put the list in a boolean context - it is treated as False if empty, and True if non-empty.

From the docs

len(s)

Return the length (the number of items) of an object. The argument may be a sequence (such as a string, bytes, tuple, list, or range) or a collection (such as a dictionary, set, or frozen set).

len is implemented with __len__, from the data model docs:

object.__len__(self)

Called to implement the built-in function len(). Should return the length of the object, an integer >= 0. Also, an object that doesn’t define a __nonzero__() [in Python 2 or __bool__() in Python 3] method and whose __len__() method returns zero is considered to be false in a Boolean context.

And we can also see that __len__ is a method of lists:

items.__len__()

returns 3.

Builtin types you can get the len (length) of

And in fact we see we can get this information for all of the described types:

>>> all(hasattr(cls, '__len__') for cls in (str, bytes, tuple, list, 
                                            range, dict, set, frozenset))
True

Do not use len to test for an empty or nonempty list

To test for a specific length, of course, simply test for equality:

if len(items) == required_length:
    ...

But there's a special case for testing for a zero length list or the inverse. In that case, do not test for equality.

Also, do not do:

if len(items): 
    ...

Instead, simply do:

if items:     # Then we have some items, not empty!
    ...

or

if not items: # Then we have an empty list!
    ...

I explain why here but in short, if items or if not items is both more readable and more performant.

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While this may not be useful due to the fact that it'd make a lot more sense as being "out of the box" functionality, a fairly simple hack would be to build a class with a length property:

class slist(list):
    @property
    def length(self):
        return len(self)

You can use it like so:

>>> l = slist(range(10))
>>> l.length
10
>>> print l
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

Essentially, it's exactly identical to a list object, with the added benefit of having an OOP-friendly length property.

As always, your mileage may vary.

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Besides len you can also use operator.length_hint (requires Python 3.4+). For a normal list both are equivalent, but length_hint makes it possible to get the length of a list-iterator, which could be useful in certain circumstances:

>>> from operator import length_hint
>>> l = ["apple", "orange", "banana"]
>>> len(l)
3
>>> length_hint(l)
3

>>> list_iterator = iter(l)
>>> len(list_iterator)
TypeError: object of type 'list_iterator' has no len()
>>> length_hint(list_iterator)
3

But length_hint is by definition only a "hint", so most of the time len is better.

I've seen several answers suggesting accessing __len__. This is all right when dealing with built-in classes like list, but it could lead to problems with custom classes, because len (and length_hint) implement some safety checks. For example, both do not allow negative lengths or lengths that exceed a certain value (the sys.maxsize value). So it's always safer to use the len function instead of the __len__ method!

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And for completeness (primarily educational), it is possible without using the len() function. I would not condone this as a good option DO NOT PROGRAM LIKE THIS IN PYTHON, but it serves a purpose for learning algorithms.

def count(list):
    item_count = 0
    for item in list[:]:
        item_count += 1
    return item_count

count([1,2,3,4,5])

(The index operation with colon in list[:] is implicit and is therefore also optional.)

The lesson here for new programmers is: You can’t get the number of items in a list without counting them at some point. The question becomes: when is a good time to count them? For example, high-performance code like the connect system call for sockets (written in C) connect(int sockfd, const struct sockaddr *addr, socklen_t addrlen);, does not calculate the length of elements (giving that responsibility to the calling code). Notice that the length of the address is passed along to save the step of counting the length first? Another option: computationally, it might make sense to keep track of the number of items as you add them within the object that you pass. Mind that this takes up more space in memory. See Naftuli Kay‘s answer.

Example of keeping track of the length to improve performance while taking up more space in memory. Note that I never use the len() function because the length is tracked:

class MyList(object):
    def __init__(self):
        self._data = []
        self.length = 0 # length tracker that takes up memory but makes length op O(1) time
        

        # the implicit iterator in a list class
    def __iter__(self):
        for elem in self._data:
            yield elem
            
    def add(self, elem):
        self._data.append(elem)
        self.length += 1
            
    def remove(self, elem):
        self._data.remove(elem)
        self.length -= 1
            
mylist = MyList()
mylist.add(1)
mylist.add(2)
mylist.add(3)
print(mylist.length) # 3
mylist.remove(3)
print(mylist.length) # 2

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Answering your question as the examples also given previously:

items = []
items.append("apple")
items.append("orange")
items.append("banana")

print items.__len__()

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You can use the len() function to find the length of an iterable in python.

my_list = [1, 2, 3, 4, 5]
print(len(my_list))  # OUTPUT: 5

The len() function also works with strings:

my_string = "hello"
print(len(my_string))  # OUTPUT: 5

So to conclude, len() works with any sequence or collection (or any sized object that defines __len__).

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There is an inbuilt function called len() in python which will help in these conditions.

a=[1,2,3,4,5,6]
print(len(a))     #Here the len() function counts the number of items in the list.

Output:

>>> 6

This will work slightly different in the case of string (below):

a="Hello"
print(len(a)) #Here the len() function counts the alphabets or characters in the list.

Output:

>>> 5

This is because variable (a) is a string and not a list, so it will count the number of characters or alphabets in the string and then print the output.

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There are three ways that you can find the length of the elements in the list. I will compare the 3 methods with performance analysis here.

Method 1: Using len()

items = []
items.append("apple")
items.append("orange")
items.append("banana")

print(len(items))

output:

3

Method 2: Using Naive Counter Method

items = []
items.append("apple")
items.append("orange")
items.append("banana")

counter = 0
for i in items:
    counter = counter + 1

print(counter)

output:

3

Method 3: Using length_hint()

items = []
items.append("apple")
items.append("orange")
items.append("banana")

from operator import length_hint
list_len_hint = length_hint(items)
print(list_len_hint)

output:

3

Performance Analysis – Naive vs len() vs length_hint()

Note: In order to compare, I am changing the input list into a large set that can give a good amount of time difference to compare the methods.

items = list(range(100000000))

# Performance Analysis
from operator import length_hint
import time

# Finding length of list
# using loop
# Initializing counter

start_time_naive = time.time()
counter = 0
for i in items:
    # incrementing counter
    counter = counter + 1
end_time_naive = str(time.time() - start_time_naive)

# Finding length of list
# using len()
start_time_len = time.time()
list_len = len(items)
end_time_len = str(time.time() - start_time_len)

# Finding length of list
# using length_hint()
start_time_hint = time.time()
list_len_hint = length_hint(items)
end_time_hint = str(time.time() - start_time_hint)

# Printing Times of each
print("Time taken using naive method is : " + end_time_naive)
print("Time taken using len() is : " + end_time_len)
print("Time taken using length_hint() is : " + end_time_hint)

Output:

Time taken using naive method is : 7.536813735961914
Time taken using len() is : 0.0
Time taken using length_hint() is : 0.0

Conclusion

It can be clearly seen that time taken for naive is very large compared to the other two methods, hence len() & length_hint() is the best choice to use.

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To get the number of elements in any sequential objects, your goto method in Python is len() eg.

a = range(1000) # range
b = 'abcdefghijklmnopqrstuvwxyz' # string
c = [10, 20, 30] # List
d = (30, 40, 50, 60, 70) # tuple
e = {11, 21, 31, 41} # set

len() method can work on all the above data types because they are iterable i.e You can iterate over them.

all_var = [a, b, c, d, e] # All variables are stored to a list
for var in all_var:
    print(len(var))

A rough estimate of the len() method

def len(iterable, /):
    total = 0
    for i in iterable:
        total += 1
    return total

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In terms of how len() actually works, this is its C implementation:

static PyObject *
builtin_len(PyObject *module, PyObject *obj)
/*[clinic end generated code: output=fa7a270d314dfb6c input=bc55598da9e9c9b5]*/
{
    Py_ssize_t res;

    res = PyObject_Size(obj);
    if (res < 0) {
        assert(PyErr_Occurred());
        return NULL;
    }
    return PyLong_FromSsize_t(res);
}

Py_ssize_t is the maximum length that the object can have. PyObject_Size() is a function that returns the size of an object. If it cannot determine the size of an object, it returns -1. In that case, this code block will be executed:

    if (res < 0) {
        assert(PyErr_Occurred());
        return NULL;
    }

And an exception is raised as a result. Otherwise, this code block will be executed:

    return PyLong_FromSsize_t(res);

res which is a C integer, is converted into a Python int (which is still called a "Long" in the C code because Python 2 had two types for storing integers) and returned.

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How to Find Length of List in Python

List in Python is implemented to store the sequence of various types of data that is ordered and changeable, it can have duplicate values as well. Here, Python has three methods to find the length of list:

1. len()

It is build-in function called len() for getting the total number of elements in a list. The len() method takes argument where you may provide a list and returns the length of the given list. It is the most convenient ways to find the length of list in Python.

    #Finding length of list by using len() method
    list_example = [1, 2, 3, 4, 5,6,7,8,9]
    print("The length of list is: ", len(list_example))
    The output will be:
    
    Output:
    The length of list is:  9

2. Naive Method

length of list can be easily found using for loop and this method is called as Naive method. It can be summarized as follows:

Firstly, declare a counter variable and initialize it to zero.

Using for loop,traverse through all the data elements and after encountering every element,increment the counter variable by 1.

Now, the length of the array will be stored in the counter variables and it will represent the number of elements in the list.

#Finding length of list by using Naive method
#Initializing list
list_example = [1, 2, 3, 4, 5,6,7,8,9]
print("The list is: ", str(list_example))
#finding length of list using loop
counter = 0
for i in list_example:
    counter = counter + 1
print ("Length of list using Naive Method is: ", str(counter))

3. length_hint()

This method is defined in operator class and it can also define the length of list.

#Using Length_hint() Method
from operator import length_hint
list_len_1 = [1, 2, 3, 5, 6, 'PickupBrain']
list_len_hint = length_hint(list_len_1)
print(list_len_hint)

Performance test of len(), Naive Method and lenght_list Methods

This time analysis will help to understand how much time it takes to execute all the methods, which will help you to chose one over another.

#Code for Performance Analysis
from operator import length_hint
import time
#define list
list_example = [1, 2, 3, 4, 5,6,7,8,9]
print("The list is: ", list_example)
# Using Naive method & loop to find length of list
# Initializing counter
start_naive_time = time.time()
counter = 0
for i in list_example:
    counter = counter + 1
    end_naive_time = float(time.time() - start_naive_time)
# Using len() method
start_len_time = time.time()
list_len = len(list_example)
end_len_time = float(time.time()- start_len_time)
# Using length_hint() method
start_hint_time = time.time()
list_hint = length_hint(list_example)
end_hint_time = float(time.time()- start_hint_time)
#Printing time for each method
print("Time taken by Naive Method: ", end_naive_time)
print("Time taken by Length_hint() Method: ", end_len_time)
print("Time taken by len() Method: ", end_hint_time)
The output will be this:

Output:

The list is:  [1, 2, 3, 4, 5, 6, 7, 8, 9]
Time taken by Naive Method:  3.0994415283203125e-06
Time taken by Length_hint() Method:  4.76837158203125e-07
Time taken by len() Method:  1.1920928955078125e-06

Conclusion The time taken is Naive Method >> len() >length_hint()