/Juntos

Assignment

Primary LanguagePythonMIT LicenseMIT

Juntos Assignment
Author: Josuel Musambaghani
Email: joshlixmus@gmail.com

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Description

  • Project Title: Concordance

  • Overview A 'concordance' is an alphabetical list of the words present in a text with a count of how often each word appears and citations of where each word appears in the text (e.g. page number).

  • Example usage A concordance is used in books to show how many times each word occurs, and the specific location where the word may be found.

  • Getting Started The main language used in this project is Python. The repository (on GitHub) containing the code for the project is called Juntos and the python file itself in the repository is called Josuel_Concordance.py.

  • Design Goals The goal of our project is to write a code that will be able to get input from one file (in my case, I used a .txt file), to read and manipulate data from the input, and at the end, the code must write, in an empty file, an ordered (sorted) list of words that shows the number of occurences and the specific location of the word at each occurence.

  • Detailed Usage In this project, we assumed that data from the input file are simple; they only contain punctuation marks and spaces. As talking about punctuations, it is to be noted that a library called nltk had to prealably be installed in the directory for our python compiler to deal with punctuation marks.

Formatting

Prealably, two modules has to be imported for the Program to compile:

import nltk helps to deal with the input from the file.

import string helps to manipulate punctuations.

The program (the code itself) is structured into three parts:

  1. Part 1: Getting data from the user (From the first file)

After importing the necessary modules (nltk and string), this part prompts the user to enter a file name from which data should be read.

Once data are accessed, the operation nltk.sent_tokenize(text) breaks the data into elements with resect to punctuations marks. The output here is a list of strings, each string representing a sentence from the input file.

Note:
  • The nltk module needs to prealably installed in the PC (directory) for the code to run.
  • The nltk presents some weaknesses when it comes to sequence sentences containing parenthesis. This minor issue were solved in the next part (Manipulating data).
  1. Part 2: Manipulating data

This part essentially does three main tasks:

  • Firstly, the code solve the issue of the nltk's weakness faced to parenthesis.
  • Secondly, it eliminate punctuations that might complicate the count of words' occurences.
  • Thirdly, the part count appearances of each word and stores it in a dictionary.
  1. Part 3: Results: Writing ouptput to the second file.

This last part focuses on three main tasks:

  • It sort by key every word in the dictionary called myDict
  • Next, the code prompts the user to enter the name of a file where to write the ouptut.
  • And then, finally the code writes the results in the file entered by the user.

Supporting documentation

The project mainly used for loops. Outside documentations did not apply. However, some materials were helpful to double-check some skills that may have been forgotten about libraries and modules. We have: