Python  Library

Python Library

1640833560

A Python Binding to The Tokenizer Ucto

Ucto for Python

This is a Python binding to the tokeniser Ucto. Tokenisation is one of the first step in almost any Natural Language Processing task, yet it is not always as trivial a task as it appears to be. This binding makes the power of the ucto tokeniser available to Python. Ucto itself is a regular-expression based, extensible, and advanced tokeniser written in C++ (https://languagemachines.github.io/ucto).

Installation

Easy

Manual (Advanced)

  • Make sure to first install ucto itself (https://languagemachines.github.io/ucto) and all its dependencies.
  • Install Cython if not yet available on your system: $ sudo apt-get cython cython3 (Debian/Ubuntu, may differ for others)
  • Clone this repository and run: $ sudo python setup.py install (Make sure to use the desired version of python)

Advanced note: If the ucto libraries and includes are installed in a non-standard location, you can set environment variables INCLUDE_DIRS and LIBRARY_DIRS to point to them prior to invocation of setup.py install.

Usage

Import and instantiate the Tokenizer class with a configuration file.

import ucto
configurationfile = "tokconfig-eng"
tokenizer = ucto.Tokenizer(configurationfile)

The configuration files supplied with ucto are named tokconfig-xxx where xxx corresponds to a three letter iso-639-3 language code. There is also a tokconfig-generic one that has no language-specific rules. Alternatively, you can make and supply your own configuration file. Note that for older versions of ucto you may need to provide the absolute path, but the latest versions will find the configurations supplied with ucto automatically. See here for a list of available configuration in the latest version.

The constructor for the Tokenizer class takes the following keyword arguments:

  • lowercase (defaults to False) -- Lowercase all text
  • uppercase (defaults to False) -- Uppercase all text
  • sentenceperlineinput (defaults to False) -- Set this to True if each sentence in your input is on one line already and you do not require further sentence boundary detection from ucto.
  • sentenceperlineoutput (defaults to False) -- Set this if you want each sentence to be outputted on one line. Has not much effect within the context of Python.
  • paragraphdetection (defaults to True) -- Do paragraph detection. Paragraphs are simply delimited by an empty line.
  • quotedetection (defaults to False) -- Set this if you want to enable the experimental quote detection, to detect quoted text (enclosed within some sort of single/double quote)
  • debug (defaults to False) -- Enable verbose debug output

Text is passed to the tokeniser using the process() method, this method returns the number of tokens rather than the tokens itself. It may be called multiple times in sequence. The tokens themselves will be buffered in the Tokenizer instance and can be obtained by iterating over it, after which the buffer will be cleared:

#pass the text (a str) (may be called multiple times),
tokenizer.process(text)

#read the tokenised data
for token in tokenizer:
    #token is an instance of ucto.Token, serialise to string using str()
    print(str(token))

    #tokens remember whether they are followed by a space
    if token.isendofsentence():
        print()
    elif not token.nospace():
        print(" ",end="")

The process() method takes a single string (str), as parameter. The string may contain newlines, and newlines are not necessary sentence bounds unless you instantiated the tokenizer with sentenceperlineinput=True.

Each token is an instance of ucto.Token. It can be serialised to string using str() as shown in the example above.

The following methods are available on ucto.Token instances: * isendofsentence() -- Returns a boolean indicating whether this is the last token of a sentence. * nospace() -- Returns a boolean, if True there is no space following this token in the original input text. * isnewparagraph() -- Returns True if this token is the start of a new paragraph. * isbeginofquote() * isendofquote() * tokentype -- This is an attribute, not a method. It contains the type or class of the token (e.g. a string like WORD, ABBREVIATION, PUNCTUATION, URL, EMAIL, SMILEY, etc..)

In addition to the low-level process() method, the tokenizer can also read an input file and produce an output file, in the same fashion as ucto itself does when invoked from the command line. This is achieved using the tokenize(inputfilename, outputfilename) method:

tokenizer.tokenize("input.txt","output.txt")

Input and output files may be either plain text, or in the FoLiA XML format. Upon instantiation of the Tokenizer class, there are two keyword arguments to indicate this:

  • xmlinput or foliainput -- A boolean that indicates whether the input is FoLiA XML (True) or plain text (False). Defaults to False.
  • xmloutput or foliaoutput -- A boolean that indicates whether the input is FoLiA XML (True) or plain text (False). Defaults to False. If this option is enabled, you can set an additional keyword parameter docid (string) to set the document ID.

An example for plain text input and FoLiA output:

tokenizer = ucto.Tokenizer(configurationfile, foliaoutput=True)
tokenizer.tokenize("input.txt", "ucto_output.folia.xml")

FoLiA documents retain all the information ucto can output, unlike the plain text representation. These documents can be read and manipulated from Python using the FoLiaPy library. FoLiA is especially recommended if you intend to further enrich the document with linguistic annotation. A small example of reading ucto's FoLiA output using this library follows, but consult the documentation for more:

import folia.main as folia
doc = folia.Document(file="ucto_output.folia.xml")
for paragraph in doc.paragraphs():
    for sentence in paragraph.sentence():
        for word in sentence.words()
            print(word.text(), end="")
            if word.space:
                print(" ", end="")
        print()
    print()

Test and Example

Run and inspect example.py

Download Details:
Author: proycon
Source Code: https://github.com/proycon/python-ucto
License: 

#python 

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A Python Binding to The Tokenizer Ucto
Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Shardul Bhatt

Shardul Bhatt

1626775355

Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

Art  Lind

Art Lind

1602968400

Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development

Art  Lind

Art Lind

1602666000

How to Remove all Duplicate Files on your Drive via Python

Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.

Intro

In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.

Heres a solution

Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.

But How do we do it?

If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?

The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.

There’s a variety of hashing algorithms out there such as

  • md5
  • sha1
  • sha224, sha256, sha384 and sha512

#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips

How To Compare Tesla and Ford Company By Using Magic Methods in Python

Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc…

You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like init, call, str etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).

Now there are a number of such special methods, which you might have come across too, in Python. We will just be taking an example of a few of them to understand how they work and how we can use them.

1. init

class AnyClass:
    def __init__():
        print("Init called on its own")
obj = AnyClass()

The first example is _init, _and as the name suggests, it is used for initializing objects. Init method is called on its own, ie. whenever an object is created for the class, the init method is called on its own.

The output of the above code will be given below. Note how we did not call the init method and it got invoked as we created an object for class AnyClass.

Init called on its own

2. add

Let’s move to some other example, add gives us the ability to access the built in syntax feature of the character +. Let’s see how,

class AnyClass:
    def __init__(self, var):
        self.some_var = var
    def __add__(self, other_obj):
        print("Calling the add method")
        return self.some_var + other_obj.some_var
obj1 = AnyClass(5)
obj2 = AnyClass(6)
obj1 + obj2

#python3 #python #python-programming #python-web-development #python-tutorials #python-top-story #python-tips #learn-python