Python Comparisons let you perform the comparison of multiple items by using Python programming language. Learn more.

**Parameter Details**

First item to be compared

`Second item to be compared`

## Python Comparisons: Chain Comparisons

You can compare multiple items with multiple comparison operators with chain comparison. For example

x > y > z

is just a short form of:

x > y and y > z

This will evaluate to True only if both comparisons are True.

The general form is

a OP b OP c OP d …

Where OP represents one of the multiple comparison operations you can use, and the letters represent arbitrary valid expressions.

Note that 0 != 1 != 0 evaluates to True, even though 0 != 0 is False. Unlike the common mathematical notation in which x != y != z means that x, y and z have diﬀerent values. Chaining == operations has the natural meaning in most cases, since equality is generally transitive.

#### Style

There is no theoretical limit on how many items and comparison operations you use as long you have proper syntax:

1>-1<2>0.5<100!=24

The above returns True if each comparison returns True. However, using convoluted chaining is not a good style. A good chaining will be “directional”, not more complicated than

1 > x > -4 > y != 8

### Side eﬀects

As soon as one comparison returns False, the expression evaluates immediately to False, skipping all remaining comparisons.

Note that the expression exp in a > exp > b will be evaluated only once, whereas in the case of

a > exp and exp > b

exp will be computed twice if a > exp is true.

## Python Comparisons: Comparison by `is`

vs `==`

A common pitfall is confusing the equality comparison operators is and ==.

```
== b compares the value of a and b.
is b will compare the identities of a and b. To illustrate:
```

a = 'Python is fun!'

b = 'Python is fun!'

a == b # returns True

a is b # returns False

a = [1, 2, 3, 4, 5]

b = a # b references a

a == b # True

a is b # True

b = a[:] # b now references a copy of a

a == b # True

a is b # False [!!]

Basically, is can be thought of as shorthand for id(a) == id(b).

Beyond this, there are quirks of the run-time environment that further complicate things. Short strings and small integers will return True when compared with is, due to the Python machine attempting to use less memory for identical objects.

a = 'short'

b = 'short'

c =5

d = 5

a is b # True

c is d # True

But longer strings and larger integers will be stored separately.

a = 'not so short'

b = 'not so short'

c = 1000

d = 1000

a is b # False

c is d # False

You should use is to test for None:

if myvar is not None:

not None pass

if myvar is None:

None

pass

A use of is is to test for a “sentinel” (i.e. a unique object).

sentinel = object() def myfunc(var=sentinel):

if var is sentinel:

value wasn’t provided pass

else:

value was provided pass

## Python Comparisons: Greater than or less than

x > y

x < y

These operators compare two types of values, they’re the less than and greater than operators. For numbers this simply compares the numerical values to see which is larger:

12>4

True 12<4

False

1 < 4

True

For strings they will compare lexicographically, which is similar to alphabetical order but not quite the same.

"alpha" < "beta"

### True

"gamma" > "beta"

### True

"gamma" < "OMEGA"

### False

In these comparisons, lowercase letters are considered ‘greater than’ uppercase, which is why “gamma” < “OMEGA”

is false. If they were all uppercase it would return the expected alphabetical ordering result:

"GAMMA" < "OMEGA"

#### True

Each type defines it’s calculation with the < and > operators diﬀerently, so you should investigate what the operators mean with a given type before using it.

## Python Comparisons: Not equal to

x != y

This returns True if x and y are not equal and otherwise returns False.

12!=1

### True

12 != '12'

### True

'12' != '12'

### False

## Python Comparisons: Equal To

x == y

This expression evaluates if x and y are the same value and returns the result as a boolean value. Generally both type and value need to match, so the int 12 is not the same as the string ’12’.

12 == 12

True 12==1

False

'12' == '12'

### True

'spam' == 'spam'

### True

'spam' == 'spam '

False '12' == 12

False

Note that each type has to define a function that will be used to evaluate if two values are the same. For builtin types these functions behave as you’d expect, and just evaluate things based on being the same value. However custom types could define equality testing as whatever they’d like, including always returning True or always returning False.

## Python Comparisons: Comparing Objects

In order to compare the equality of custom classes, you can override == and != by defining **eq** and **ne** methods. You can also override **lt** (<), **le** (<=), **gt** (>), and **ge** (>). Note that you only need to override two comparison methods, and Python can handle the rest (== is the same as not < and not >, etc.)

class Foo(object):

definit(self, item):

self.my_item = item

defeq(self, other):

return self.my_item == other.my_item

a = Foo(5)

b = Foo(5)

a == b # True

a != b # False

a is b # False

Note that this simple comparison assumes that other (the object being compared to) is the same object type.

Comparing to another type will throw an error:

class Bar(object): definit(self, item): self.other_item = item defeq(self, other): return self.other_item == other.other_item defne(self, other): return self.other_item != other.other_item c = Bar(5) a == c # throws AttributeError: 'Foo' object has no attribute 'other_item'

Checking isinstance() or similar will help prevent this (if desired).

### Must Read Python Interview Questions

### 200+ Python Tutorials With Coding Examples

#### Other Python Tutorials

- What is Python?
- Python Advantages
- Python For Beginners
- Python For Machine Learning
- Machine Learning For Beginners
- 130+ Python Projects With Source Code On GitHub