What is the use of empty function in python?

The numpy module of Python provides a function called numpy.empty(). This function is used to create an array without initializing the entries of given shape and type.

Just like numpy.zeros(), the numpy.empty() function doesn't set the array values to zero, and it is quite faster than the numpy.zeros(). This function requires the user to set all the values in the array manually and should be used with caution.

Syntax

Parameters:

shape: int or tuple of ints

This parameter defines the shape of the empty array, such as (3, 2) or (3, 3).

dtype: data-type(optional)

This parameter defines the data type, which is desired for the output array.

order: {'C', 'F'}(optional)

This parameter defines the order in which the multi-dimensional array is going to be stored either in row-major or column-major. By default, the order parameter is set to 'C'.

Returns:

This function returns the array of uninitialized data that have the shape, dtype, and order defined in the function.

Example 1:

Output:

array([[7.56544226e-316, 2.07617768e-316],
       	[2.02322570e-316, 1.93432036e-316],
       	[1.93431918e-316, 1.93431799e-316]])

In the above code

• We have imported numpy with alias name np.
• We have declared the variable 'x' and assigned the returned value of the np.empty() function.
• We have passed the shape in the function.
• Lastly, we tried to print the value of 'x' and the difference between elements.

Example 2:

Output:

array([[ 2.94197848e+120, -2.70534020e+252, -4.25371363e+003],
       	[ 1.44429964e-088,  3.12897830e-053,  1.11313317e+253],
       	[-2.28920735e+294, -5.11507284e+039,  0.00000000e+000]])

Example 3:

Output:

array([[ 2.94197848e+120, -2.70534020e+252, -4.25371363e+003],
       	[ 1.44429964e-088,  3.12897830e-053,  1.11313317e+253],
       	[-2.28920735e+294, -5.11507284e+039,  0.00000000e+000]]) 

In the above code

• We have imported numpy with alias name np.
• We have declared the variable 'x' and assigned the returned value of the np.empty() function.
• We have passed the shape, data-type, and order in the function.
• Lastly, we tried to print the value of 'x' and the difference between elements.

In the output, it shows an array of uninitialized values of defined shape, data type, and order.

Example 4:

Output:

array([[ 2.94197848e+120,  1.44429964e-088, -2.28920735e+294],
       	[-2.70534020e+252,  3.12897830e-053, -5.11507284e+039],
       	[-4.25371363e+003,  1.11313317e+253,  0.00000000e+000]])

First, the reason this doesn't work:

a = lamdba: pass

… is that lambda only allows an expression, and defines a function that returns the value of the expression. Since pass is a statement, not an expression, this is illegal.

However, this works just fine:

a = lambda: None

In Python, a function that falls off the end without a return statement always returns None. So, these are equivalent:

def a(): return None
def a(): pass

However, I don't see why you want to write this as a lambda and an assignment anyway; the def is shorter, and more readable, and gives you an introspectable function object with a nice name (a instead of <lambda>), and so on. The only reasons to ever use lambda are when you don't want to give the function a name, or when you need to define the function inside an expression. Obviously neither of those are true, because you use the lambda directly inside an assignment statement. So, just use def.

Meanwhile, this is in a sense an "empty function", or at least as empty as possible (as you can see by, e.g., calling dis.dis(a), it still takes two bytecodes to do nothing but fall off the end and return None), but it's not useful for your case. You don't want an "empty function". If you try passing your a to map, you're just going to get a TypeError, because you're trying to call a function of no arguments with one argument. (Because that's what map does.)

What you might want is an identity function, which just returns its argument as-is. Like this:

def a(x): return x

But I'm not sure that's what you want. Did you want to append data as-is in that case? Or did you want to do something different, like return early, or raise an exception, or not append anything, or …?

Finally, I don't see why you want a function at all. Why not just not call map if you have nothing to map? You have a perfectly good else clause that already catches that case (especially handy if what you want to do is return early or raise…). Or, if you prefer, you can start with f = None, and then use an if f: do decide whether to map or not. Or, if you really want:

added_property = [f(element) if f else element for element in data]

… or …

added_property = map(f, data) if f else data

As one last note, instead of a long if/elif chain that repeats the same thing over and over again, you might want a dict:

propfuncs = {'prop1': make_property1(),
             'prop2': make_property2(),
             'prop3': make_property3(),
             'prop4': make_property4()}

Then, all that cruft turns into these two lines:

f = propfuncs.get(self.property_currently_being_added)
added_property = map(f, data) if f else data

Or course an even better design might be to replace all those make_propertyN functions with a single function that you call as make_property(1) or make_property('prop1')… but without seeing what they actually do, I can't be sure of that.

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