Short Python 3 In-Memory Database Test

# In Memory Database ### This test is made up of 2 different sections. First section is coding basic functionality for an in memory database and should take about an hour to complete. <!-- ### VARIABLE ANSWERS # Second section focuses on more high level design/architecture and is open ended. This section typically takes 1 to 2 hours to complete, but candidate will have up to 24 hours to submit answers to section 2. Answers to questions in this section can contain diagrams if necessary. # You are allowed to use more than the allotted time for each of the sections, but do note that extra time used may be a factor in evaluating your results. --> ## Section 1 Implement basic SQL-like operations, such as select, where, join, etc., of an in-memory database. ## Instructions Assume the following data is stored in the in-memory database **departments** | id | name | | ----|-------------| | 0 | engineering | | 1 | finance | **users** | id | department_id | name | | ---|---------------|--------| | 0 | 0 | Ian | | 1 | 0 | John | | 2 | 1 | Eddie | | 3 | 1 | Mark | **salaries** | id | user_id | amount | | ---|----------|--------| | 0 | 0 | 100 | | 1 | 1 | 150 | | 2 | 1 | 200 | | 3 | 3 | 200 | | 4 | 3 | 300 | | 5 | 4 | 400 | ### First step Please implement `select` and `where` in `Table` class. For the sake of simplicity, you can assume all operations will be passed valid parameters. You do not need to concern yourself with error handling for occurrences like selecting an arbitrary column from a non-existent table. For example, ~~~python # Should print something like # id, department_id, name # 1, 0, John print(db.table('users') .where('id', 1) .select(['id', 'department_id', 'name'])) ~~~ ### Second step Please implement `inner_join` in `Database` class. ~~~python # Should print something like # users.name, departments.name # Ian, engineering # John, engineering print(db.inner_join(db.table('users'), 'department_id', db.table('departments'), 'id') .where('departments.name', 'engineering') .select(['users.name', 'departments.name'])) ~~~ ### Third step Please implement `left_join`, `right_join` and `outer_join` in `Database` class. ~~~python # Should print something like # users.name, salaries.amount # Ian, 100 # John, 150 # John, 200 # Mark, 200 # Mark, 300 # Eddie, None print(db.left_join(db.table('users'), 'id', db.table('salaries'), 'user_id') .select(['users.name', 'salaries.amount'])) # Should print something like # users.name, salaries.amount # Ian, 100 # John, 150 # John, 200 # Mark, 200 # Mark, 300 # None, 400 print(db.right_join(db.table('users'), 'id', db.table('salaries'), 'user_id') .select(['users.name', 'salaries.amount'])) # should print something like # users.name, salaries.amount # Ian, 100 # John, 150 # John, 200 # Mark, 200 # Mark, 300 # Eddie, None # None, 400 print(db.outer_join(db.table('users'), 'id', db.table('salaries'), 'user_id') .select(['users.name', 'salaries.amount'])) ~~~ ### Your solution will be scored in the descending priority of correctness, memory & time complexity, and comprehensibility.