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will match elements such as A[1], A[2], or more generally A[x] where x is any entity. In this case, A is the concrete element, while _ denotes the piece of tree that can be varied. A symbol prepended to _ binds the match to that variable name while a symbol appended to _ restricts the matches to nodes of that symbol.
The closeness of a match is measured in terms of the number of primitive operations necessary to convert the string into an exact match. This number is called the edit distance between the string and the pattern. The usual primitive operations are: [1] insertion: cot → coat; deletion: coat → cot; substitution: coat → cost
[2] Views represent how many times a video is watched. To ensure that traffic is coming from actual humans and not scripts or other deceptive methods, YouTube has a secret algorithm to separate legitimate views from illegitimate ones, and only legitimate views are included in the view count. [3]
One thing the most visited websites have in common is that they are dynamic websites.Their development typically involves server-side coding, client-side coding and database technology.
In Python 3.x the range() function [28] returns a generator which computes elements of the list on demand. Elements are only generated when they are needed (e.g., when print(r[3]) is evaluated in the following example), so this is an example of lazy or deferred evaluation:
Add 1 cup cubed tempeh and cook until golden brown on all sides, 5 to 7 minutes. Add 2 minced garlic cloves and 1 cup broccoli florets. Stir-fry until the broccoli starts to char, 3 to 4 minutes ...
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Introduced in Python 2.2 as an optional feature and finalized in version 2.3, generators are Python's mechanism for lazy evaluation of a function that would otherwise return a space-prohibitive or computationally intensive list. This is an example to lazily generate the prime numbers: