10 Pure Python Functions for Ad Hoc Text Analysis

Text****data is the most common format of the data out there. An abundance of articles, tweets, documents, books and else, fly around us every day. The amount of insights you can extract is immense and the tools to help on extracting them are improving continuously.

In Python, you can use external libraries to process text data. One issue with these libraries is that they are not lightweight and they do have a steep learning curve for starters. In many cases, functions written in pure Python can do great if your sole intention is to explore and get to know with the data.

Below I’ve provided a list of 10 such functions that I use mostly. These functions are mainly **heuristic functions **that work properly under assumptions made. These assumptions are stated at the points below at functions where they are considered.

#1 Get Sentences

Assumption: Everything that ends with a dot, question mark or exclamation mark, is taken as a sentence.

def get_sentences(text):
    import re
    pattern = r'([A-Z][^\.!?]*[\.!?])'
    pattern_compiled = re.compile(pattern, re.M)
    list_of_sentences = re.findall(pattern, text)
    return list_of_sentences


# Test
text = """This is the most frequent question we're asked by prospective students. And our response? Absolutely! We've trained people from all walks of life."""
get_sentences(text)


# [
#     "This is the most frequent questions we're asked by prospective students.",
#     'And our response?',
#     'Absolutely!',
#     "We've trained people from all walks of life."
# ]

#2 Get List of Items per Sentence

Assumption: A colon followed by a list of items separated with comma is taken.

def get_listed_items_with_colon(text):
    import re
    list_of_items = []
    list_of_sentences = re.split('\.|\?|\!', text)
    for sentence in list_of_sentences:
        if ':' in sentence:
            start_index = sentence.find(':')
            sub_sentence = sentence[start_index+1:]
            list_of_items.append([word.strip() for word in sub_sentence.split(',')])
    return list_of_items


# Test
text = """The house has everything I need: two bedrooms, a backyard, and a garage. I have several favorite genres of movies: drama, science fiction, and mystery."""
get_listed_items_with_colon(text)

# [ ['two bedrooms', 'a backyard', 'and a garage'], ['drama', 'science fiction', 'and mystery'] ]

#data-science #nlp #programming #text-mining #python

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10 Pure Python Functions for Ad Hoc Text Analysis

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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:

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Learn how to convert your Text into Voice with Python and Google APIs

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Project Prerequisites

To implement this project, we will use the basic concepts of Python, Tkinter, gTTS, and playsound libraries.

Tkinter is a standard GUI Python library that is one of the fastest and easiest ways to build GUI applications using Tkinter.
gTTS (Google Text-to-Speech) is a Python library, which is a very easy library that converts the text into audio.
The playsound module is used to play audio files. With this module, we can play a sound file with a single line of code.

To install the required libraries, you can use pip install command:

pip install tkinter
pip install gTTS
pip install playsound

Download Python Text to Speech Project Code

Please download the source code of Text to Speech Project: Python Text to Speech

Text to Speech Python Project

The objective of this project is to convert the text into voice with the click of a button. This project will be developed using Tkinter, gTTs, and playsound library.

In this project, we add a message which we want to convert into voice and click on play button to play the voice of that text message.

Importing the modules
Create the display window
Define functions

So these are the basic steps that we will do in this Python project. Let’s start.

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