Text Analyzer

important links

Code Style

PEP8 was implemented as style for the Python code written in this project.

Text Analyzer features

Feature 1

Basic Text Analysis

This feature will analyze the text that was input by the user prior the option menu, the analysis will count the number of words, characters, lines and paragraphs of the input text, as well as the lenguage of it. The results will be displayed in a list.

Note: lenguages will be displayed as 'EN' for english, 'ES' for spanish, 'DE' for German, etc...

Feature 2

Word Frequency Analysis

Allow users to know the Top 5 most frequent words, the program will count and display how many times each word appears in the text.

Feature 3

Keywords Extractions

Allow users to extract the most frequent non-stop words from the text. Additionally, provide contextual analysis by displaying the sentences where each keyword appears.

Note: This process is set up to run the natural language process over texts written in English, Spanish, Italian, German, and French.

Documentation

Hardware Requirements

Operating System:

Linux: RHEL 6/7, 64-bit (almost all libraries also work in Ubuntu)
x86 64-bit CPU (Intel / AMD architecture). ARM CPUs are not supported.
4 GB RAM
5 GB free disk space

reference: Enthought Python Minimum Hardware Requirements

Software Requirements

Python 3. to install Python3 guide here
Windows 7 or 10
Mac OS X 10.11 or higher, 64-bit

Required dependencies

altgraph==0.17.4
click==8.1.7
exceptiongroup==1.1.3
iniconfig==2.0.0
joblib==1.3.2
langdetect==1.0.9
nltk==3.8.1
packaging==23.2
pluggy==1.3.0
pyinstaller==6.1.0
pyinstaller-hooks-contrib==2023.10
pytest==7.4.2
rake-nltk==1.0.6
regex==2023.10.3
six==1.16.0
textblob==0.17.1
tomli==2.0.1
tqdm==4.66.1

Installation

Check in your terminal for Python if it is installed.

 python --version

It should return the python version, example below. Anything above 3 is good.

Python 3.10.12

if python it is not installed, go back to how to install it here

2.Download text analyzer

Download the text analyzer file by navigating to the Github repository and select 'Download ZIP'

zip

3.In your terminal, navigate to the directory 'T1A3-Terminal'

 cd T1A3-Terminal

4.From inside the 'T1A3-Terminal' directory, navigate the source folder.

cd src

5.Run 'script.sh' to install dependencies.

 ./script.sh

or alternatively run

 bash script.sh

the app should open after installing. if the app does not run, run the code below inside the 'T1A3-Terminal' directory.

 python3 src/main.py

Notes: sometimes the terminal will prompt suggestions to install or update some dependencies, please follow the terminal instructions as these are vital for the app.

Text Analyzer app instructions

you are going to be welcome by the app then ask you to enter your text to be analyzed. ( simply copy and paste your text or write yours) then press 'enter'.

input

text

2.Four options will pop, please type 1, 2, 3 or 4 then 'enter' , the analisis will be shown after.

3.'Would you like to continue? (yes/no):' will prompt after the analysis result, and then you will have the option of going back to the menu, and using the others analysis for your text or exit the app.

4.A 'Thanks' message will be shown meaning the app is terminated.

exit

Implementation Plan

The Text Analyzer project utilized the GitHub projects tool in order to execute features, tests, checklists, and any tasks related to the project. First, a creation of tasks for features 1, 2, and 3 was performed followed by checklists. example: Featuare #1 = 1.1 Build functions for counting words, Feature #1 = 1.2 Build functions for counting characters... etc. Then tasks such as error handlers, menu options, corrections, scripts, and more were specified. Majority of tasks contains comments, screenshots and sources links.

The implementation plan was reviewed and updated every day as well after tasks completed successfully, tasks completed at the end of the day were moved to the 'DONE' column list, while tasks not started yet were in 'TODO' column list, and the tasks being performed were in 'PROGRESS' column list. I created a new column named 'ISSUES' for tasks that presented difficulty issues.

The first screenshot below shows the timeline of the duration of the project with the dates of the tasks completed.

timeline