jalsol / homebase-assignment

Homebase Take Home Assignment

Homebase Take-Home Assignment

Candidate: Quang-Truong Nguyen

This is my submission for the Homebase Take-Home Assignment. There are 5 tasks in total.

The version of Python used is 3.10.12. The version of MariaDB used is 10.6.12.

Task 1: Python Programming

The solution for this task is in the task1/ directory.

• average_age.py: The script that calculates the average age of all users in the data.csv file.
• data*.csv: The data files used for testing the script.

Usage

To run the script:

• Change the variables INPUT_CSV_FILE and DELIMITER in average_age.py to the desired values.
• Run the script with python3 average_age.py.

Task 2: Data Structures: E-commerce Inventory Schema

The solution for this task is in the task2/ directory.

• schema.sql: The SQL script that creates the tables and relationships for the schema.
• diagram.png: The ER diagram for the schema.

Usage

To create the schema:

• Create a database in MariaDB.
• Run the script with mysql -u <username> -p <database_name> < schema.sql.
• The schema should be created in the database.

Task 3: Web Scraping - Real Estate Data from Batdongsan.com

The solution for this task is in the task3/ directory.

• main.py: The script that scrapes the data from the website.
• scraper.py: Scraper class for scraping the data from an URL of multiple products.
• product_parser.py: Parser class for parsing the data from the HTML of a product page.
• cache_schema.sql: The SQL script that creates the tables and relationships for the cache schema.

Usage

To run the script:

• Setup a virtual environment with python3 -m venv venv.
• Activate the virtual environment with source venv/bin/activate.
• Install the dependencies with pip3 install -r requirements.txt.
• Install sqlite3.
• Copy the .env.example file to .env and modify the variables to the desired values.
• Modify the URL variable in main.py to the desired URL.
• Run the script with python3 main.py.

Task 4: Nested Set Model Implementation

The solution for this task is in the task4/ directory.

• data_gen.py: The script that generates the data for the nested set model.
• hierarchical_to_nested_set.py: The script that converts the data from hierarchical model to nested set model.
• retrieve_parent_child_relationship.py: The script that retrieves the parent-child relationship from the nested set model.
• schema.sql: The SQL script that creates the tables and relationships for the schema.
• benchmark.txt: The output after benchmarking the performance of the above scripts.

There are also 2 example data files in the task4/ directory:

• small_example.csv: The data file with 14 nodes.
• large_example.csv: The data file with 5018 nodes.

Usage

To run the script:

• Setup a virtual environment with python3 -m venv venv.
• Activate the virtual environment with source venv/bin/activate.
• Install the dependencies with pip3 install -r requirements.txt.
• Install sqlite3.
• Create tables with sqlite3 data.sqlite < schema.sql.
• Modify the MAX_DEPTH and MAX_CHILDREN variables in data_gen.py to the desired value.
• Populate the database with python3 data_gen.py.
• Convert the data to nested set model with python3 hierarchical_to_nested_set.py.
• Retrieve the data from nested set model with python3 retrieve_parent_child_relationship.py.

Task 5: Database and SQL - Stored Procedure Creation

The solution for this task is in the task5/ directory.

• schema.sql: The SQL script that creates the tables and relationships for the schema.
• procedure.sql: The SQL script that creates the stored procedure.

Usage

To create the schema:

• Create a database in MariaDB.
• Run the script with mysql -u <username> -p <database_name> < schema.sql to create the tables.
• Run the script with mysql -u <username> -p <database_name> < procedure.sql to create the stored procedure.
• The schema should be created in the database.