CrudBasic2

An enhanced version of the CRUD Capstone Project with Online visitors can register on-line and obtain their own password and receive a confirming e-mail that is automatically sent from the site. The code also works in the test environment on localhost. If visitors forget their password they can recover their account if they remember the hint. The email is handled by means of the PHPMailer freeware package installed using the compose package. The site was developed using the Apache2 server on localhost in the Microsoft Ubuntu extension for Windows 10 and the online site runs on nginx server in an Ubuntu cloud droplet. At the welcome page, the user can see a summary list of the profiles except for profiles made with the guest login. The Resume View page can be viewed using a link without logging in. Upon logging-in, the user can only see their own profiles. The profile information is enhanced to be more like an person's resume. There is new entry for the person's occupation. The current headline textbox is called Goals. The profile is followed by a list of the person’s skills. Skills are Skill-Set table with multiple entries for each profile is very similar to the Education table. The Skill-Set table is used in conjunction with a Skill table just as the Education table is used with an Institution table. Similarly, a major subject box was added to education. The work experience has similarly been expanded into separate company and summary blocks. There are two new database tables named Dictionary and Offensive. Extending my SQL course work, a programmed loop loaded the 11,000 word dictionary into the database from a delimited text file. The data is screened for offensive language to help make the main page suitable for a general audience, increasing the data verification performed with JavaScript for the browser and further checking at the website. After removing punctuation and exploding text phrases into an array, the information is automatically entered into the database if the words exist in the dictionary of 11,000 English words. If the words are not in the dictionary, the data is still entered into the database after further filtering for offensive words using the Offensive table. This method helps eliminate unnecessary rejections of legitimate words by reducing the need for offensive word checking. The offensive word list only exists in unreadable coded form in the database. The dictionary was constructed for my text-prediction Capstone Project using Twitter chat data for the Data Science Certificate by Johns Hopkins University on Coursera. The GitHub offensive word list of about 100 words was taken from the same project. A further enhancement was the use of JavaScript to directly construct new DOM elements based on a logical if condition for mobile device detection adding to the course project techniques of hot element insertion block as well as the jQuery append method. The inline insertion block method permits modify certain words such as edu1, edu2, ect; but the other method can change anything. An if statement could also be used with the append method so it's not clear how much direct construction of DOM elements helped and it used a number of lines of code that require a certain level of understanding.