Static semantics[ edit ] The static semantics defines restrictions on the structure of valid texts that are hard or impossible to express in standard syntactic formalisms. Examples include checking that every identifier is declared before it is used in languages that require such declarations or that the labels on the arms of a case statement are distinct. Other forms of static analyses like data flow analysis may also be part of static semantics.
Various ways to iterate over sequences The sequence functions illustrated in 4. We can randomize the contents of a list s before iterating over them, using random. We can convert between these sequence types.
For example, tuple s converts any kind of sequence into a tuple, and list s converts any kind of sequence into a list. We can convert a list of strings to a single string using the join function, e. Some other objects, such as a FreqDist, can be converted into a sequence using list or sorted and support iteration, e.
We can omit the parentheses because the comma has higher precedence than assignment. It is equivalent to the following traditional way of doing such tasks that does not use tuples notice that this method needs a temporary variable tmp. There are also functions that modify the structure of a sequence and which can be handy for language processing.
Thus, zip takes the items of two or more sequences and "zips" them together into a single list of tuples. Given a sequence s, enumerate s returns pairs consisting of an index and the item at that index.
For some NLP tasks it is necessary to cut up a sequence into two or more parts. To do this we decide the location where we want to cut the datathen cut the sequence at that location. We can also verify that the ratio of the sizes of the two pieces is what we intended.
Combining Different Sequence Types Let's combine our knowledge of these three sequence types, together with list comprehensions, to perform the task of sorting the words in a string by their length. A simple string is actually an object with methods defined on it such as split.
We use a list comprehension to build a list of tupleswhere each tuple consists of a number the word length and the word, e.
We use the sort method to sort the list in-place. Finally, we discard the length information and join the words back into a single string. The underscore is just a regular Python variable, but we can use underscore by convention to indicate that we will not use its value.
We began by talking about the commonalities in these sequence types, but the above code illustrates important differences in their roles. First, strings appear at the beginning and the end: Lists and tuples are used in the middle, but for different purposes.
A list is typically a sequence of objects all having the same type, of arbitrary length. We often use lists to hold sequences of words. In contrast, a tuple is typically a collection of objects of different types, of fixed length. We often use a tuple to hold a record, a collection of different fields relating to some entity.
This distinction between the use of lists and tuples takes some getting used to, so here is another example: An individual entry is represented as a tuple because it is a collection of objects with different interpretations, such as the orthographic form, the part of speech, and the pronunciations represented in the SAMPA computer-readable phonetic alphabet http: Note that these pronunciations are stored using a list.
Note A good way to decide when to use tuples vs lists is to ask whether the interpretation of an item depends on its position. For example, a tagged token combines two strings having different interpretation, and we choose to interpret the first item as the token and the second item as the tag.
Thus we use tuples like this: In contrast, the elements of a text are all tokens, and position is not significant. Thus we use lists like this:R is a programming language and environment commonly used in statistical computing, data analytics and scientific research.
It is one of the most popular languages used by statisticians, data analysts, researchers and marketers to retrieve, clean, analyze, visualize and present data.
Computer languages have evolved into four generations now. The term computer language denotes a high-level language like C, and C++. They have a unique set of keywords that the program understands. Python Programming for Beginners: An Introduction to the Python Computer Language and Computer Programming (Python, Python 3, Python Tutorial) - Kindle edition by Jason Cannon.
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1 Computing with Language: Texts and Words. We're all very familiar with text, since we read and write it every day. Here we will treat text as raw data for the programs we write, programs that manipulate and analyze it in a variety of interesting ways.
But before we can do this, we have to get started with the Python interpreter. Scripting languages are programming languages that don't require an explicit compilation step. For example, in the normal case, you have to compile a C program before you can run it.
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