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action icon action

a GitHub action to run `pre-commit`

gitignore icon gitignore

A collection of useful .gitignore templates

pre-commit icon pre-commit

A framework for managing and maintaining multi-language pre-commit hooks.

project-yelp-dataset icon project-yelp-dataset

Part 1 - Download the Yelp dataset from Camino. Look at each JSON file and understand what information the JSON objects provide. Pay attention to the data items in JSON objects that you will need for your application (For example, categories,attributes,...etc.) - You may have to modify your database design from Homework 2 to model the database for the described application scenario on page-1. Your database schema doesn’t necessarily need to include all the data items provided in the JSON files. Your schema should be precise but yet complete. It should be designed in sucha way that all queries/data retrievals on/from the database run efficiently and effectively. - Produce DDL SQL statements for creating the corresponding tables in a relational DBMS. Note the constraints, including key constraints, referential integrity constraints, not NULL constraints, etc. needed for the relational schema to capture and enforce the semantics of your ER design. - Populate your database with the Yelp data. Generate INSERT statements for your tables and run those to insert data into your DB. II. Part 2 Implement the application for searching local businesses as explained in section “Overview & Requirements”. In this milestone you would: - Write the SQL queries to search your database. - Establish connectivity with the DBMS. - Embed/execute queries in/from the code. Retrieve query results and parse the returned results to generate the output that will be displayed on the GUI. - Implement a GUI where the user can, o browse through main and sub-categories for the businesses; select the business categories that user wants to search for; (note: The list of the main categories is given in Appendix-C. All other categories that appear in the business objects are sub-categories. Such a distinction is made for easier browsing of the business categories.) o browse through theattributes of theselected categories ;specify the attributes she/he is interested in; o search for the businesses that belong to the main and sub-categories that user specifies and have the attributes that user selects, (The user should be able to search for the businesses that have either all the attributes (AND condition) or that have any of the attributes specified (ORcondition)) o filteroutthesearchresultsforaspecificstate,city,orzipcode, o filteroutthebusinesseswhichareopenorclosedonspecificdaysoftheweek, o selectacertainbusinessinthesearchresultsandlistallthereviewsforthatbusiness.(note:The review list should also include the names of the users who provided thosereviews)

tanner-abraham icon tanner-abraham

TANNER is a remote data analysis and classification service to evaluate HTTP requests and composing the response then served by SNARE. TANNER uses multiple application vulnerability type emulation techniques when providing responses for SNARE. In addition, TANNER provides Dorks for SNARE powering its luring capabilities.

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