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Python uses the following syntax to express list comprehensions over finite lists: S = [ 2 * x for x in range ( 100 ) if x ** 2 > 3 ] A generator expression may be used in Python versions >= 2.4 which gives lazy evaluation over its input, and can be used with generators to iterate over 'infinite' input such as the count generator function which ...
Here, the list [0..] represents , x^2>3 represents the predicate, and 2*x represents the output expression.. List comprehensions give results in a defined order (unlike the members of sets); and list comprehensions may generate the members of a list in order, rather than produce the entirety of the list thus allowing, for example, the previous Haskell definition of the members of an infinite list.
A recursive function named foo, which is passed a single parameter, x, and if the parameter is 0 will call a different function named bar and otherwise will call baz, passing x, and also call itself recursively, passing x-1 as the parameter, could be implemented like this in Python:
The enclosed text becomes a string literal, which Python usually ignores (except when it is the first statement in the body of a module, class or function; see docstring). Elixir. The above trick used in Python also works in Elixir, but the compiler will throw a warning if it spots this.
Python's is operator may be used to compare object identities (comparison by reference), and comparisons may be chained—for example, a <= b <= c. Python uses and, or, and not as Boolean operators. Python has a type of expression named a list comprehension, and a more general expression named a generator expression. [78]
a declarator_list is a comma-separated list of declarators, which can be of the form identifier As object_creation_expression (object initializer declarator) , modified_identifier «As non_array_type « array_rank_specifier »»« = initial_value» (single declarator) , or
# This function has no guard clause def f_noguard (x): if isinstance (x, int): #code #code #code return x + 1 else: return None # Equivalent function with a guard clause. Note that most of the code is less indented, which makes it easier to read and reason about def f_guard (x): if not isinstance (x, int): return None #code #code #code return x + 1
Iterators in Python are a fundamental part of the language and in many cases go unseen as they are implicitly used in the for statement, in list comprehensions, and in generator expressions. All of Python's standard built-in collection types support iteration, as well as many classes that are part of the standard library. The following example ...