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HELLO - Start Building Your Own ORM

Use ruby to reshape the kinds of objects coming from a SQL database (via a gem called PG)

Learning Objectives

Learn about the challenges with converting SQL (rows and tables into JSON)
Practice using ruby to reshape objects
etc.

Prerequisites

Experience with RESTful routes
Basic Ruby
Familiarity with JSON
Familiarity with SQL

Getting Started

You'll be working in one ruby file, and building out your answers as you work through this hw.

Deliverables

Technical Requirements

Must run without syntax errors (comment out code that doesn't work and add comments)
Must complete parts 1 - 6

Submission Guidelines

Must be submitted no later than before the start of next class

Context

The founder of the start-up H.E.L.L.O (Housing Elite Leveraged Location Organization) wants you to help launch her amazing idea.

Too many college graduates these days have too high loans to pay back. This is preventing them from being able to get into premium housing locations, where everything is in walking distance and work is a sweet sweet short commute away.

One night, our brilliant entrepreneur was reminiscing about how much she enjoyed living in a dorm and thought, why can't people keep on living in a dorm?

And thus H.E.L.L.O. was founded. A premier housing solution. For the low low starting price of $3999 a month for a bunk bed shared with one other person and a co-ed bathroom shared by everyone on the same floor, anyone's housing dreams can come true!

H.E.L.L.O already has funding for one location!

Your first task is to help build a tenant tracker.

Part 1 - explanation

SQL stores data in rows and columns, so in order to get the data to display on a web page, we need to convert the data from rows and columns into hashes with keys and values. We can use the ruby gem PG to query Postgres and give us back an array of hashes(objects) that represents the rows and columns of the DB.

If we just have one table with the following keys and values:

name	age
Chase	30

PG will turn this into the following:

[
    {
        "name" => "Chase",
        "age" => "30"
    }
]

If we had more than one person...

name	age
Chase	30
Gert	23

PG will give us:

[
    {
        "name" => "Chase",
        "age" => "30"
    },
    {
        "name" => "Gert",
        "age" => "23"
    }
]

This is straightforward. However, we start to get a few wrinkles once we start joining tables. In this homework's situation, our location HAS MANY people (and each person HAS ONE location). This is also called a ONE to MANY relationship. If we were to join Chase's info with his location's info, our table would look like the following:

name	age	home_id	home_street	home_city	home_state	home_zip_code
Chase	30	1	"1600 Broadway"	"New York"	"NY"	10019

PG would give us just one blob:

Original Format

[
    {
        "name"=>"Chase",
        "age"=>"30",
        "home_id"=>"1",
        "home_street"=>"1600 Broadway",
        "home_city"=>"New York",
        "home_state"=>"NY",
        "home_zip_code"=>"10019"
    }
]

But what we really want is to change the shape of the data and have home as a nested object. We'd also want to convert our numbers back into numbers from strings:

New Format

{
    "name"=>"Chase",
    "age"=>30,
    "home"=> {
      "id"=> 1,
      "street"=>"1600 Broadway",
      "city"=>"New York",
      "state"=>"NY",
      "zip_code"=> 10019
    }
}

Part 2 - code along

First, let's define a new method data_transform. It will take a single hash inside of an array called person_array:

def data_transform(person_array)
end

Now let's create a fake people array, containing a single hash. This will represent what the PG gem will give us from Postgres when we use it in rails. Next, call data_transform and pass that fake people array in as a parameter:

people = [
    {
        "name"=>"Chase",
        "age"=>"30",
        "home_id"=>"1",
        "home_street"=>"1600 Broadway",
        "home_city"=>"New York",
        "home_state"=>"NY",
        "home_zip_code"=>"10019"
    }
]

def data_transform(person_array)
end

p data_transform people

Second, inside of data_transform, let's make a new object called person

def data_transform(person_array)
    person = {}
end

We can make whatever keys we want for our new object:

def data_transform(person_array)
    person = {
      "name" => "Chase",
      "age" => "30"
    }
end

And we can ALMOST place our values from our person_array into our new hash

person = {
  "name" => person_array["age"],
  "age" => person_array["age"]
}

Check it! This won't quite work because our person_array is an array. We can easily take the single hash out of the array using a ruby method .first

def data_transform(person_array)
    person = person_array.first
    return {
      "name" => person["name"],
      "age" => person["age"]
    }
end

Now try again! The full code:

people = [
    {
        "name"=>"Chase",
        "age"=>"30",
        "home_id"=>"1",
        "home_street"=>"1600 Broadway",
        "home_city"=>"New York",
        "home_state"=>"NY",
        "home_zip_code"=>"10019"
    }
]

def data_transform(person_array)
    person = person_array.first
    return {
      "name" => person["name"],
      "age" => person["age"]
    }
end

p data_transform people

should print a hash containing just the name and the age of the person:

{"name"=>"Chase", "age"=>"30"}

It ALMOST matches the New Format, but the age is a string. We can use a method to fix that in a snap!

return {
    "name" => person["name"],
    "age" => person["age"].to_i
}

Check it again!

{"name"=>"Chase", "age"=>30}

Part 3 - build it

Don't forget, we want our data_transform function to return an object that also includes the other information about our person.

{
    "name"=>"Chase",
    "age"=>30,
    "home"=> {
      "id"=> 1,
      "street"=>"1600 Broadway",
      "city"=>"New York",
      "state"=>"NY",
      "zip_code"=> 10019
    }
}

How do we get that nested home hash in the results?

Part 4 - build it

As we get new clients, not all of them will have a home right away. We need to add a way to check if a person has a home address, and if true, return the reshaped hash else just return the person hash

Don't forget to test it, there is sample 'data' available in Part 1 for you to use

Part 5 - build it

HELLO already has three tenants! Converting each object's format one by one is a drag. Write a new function data_transforms that converts an array of many people hashes into the New Format shape:

Original Format

people = [
    {
        "name"=>"Gert",
        "age"=>"23",
        "home_id"=> "1",
        "home_street"=>"1600 Broadway",
        "home_city"=>"New York",
        "home_state"=>"NY",
        "home_zip_code"=> "10019"
    },
    {
        "name"=>"Alex",
        "age"=>"42",
        "home_id"=> "1",
        "home_street"=>"1600 Broadway",
        "home_city"=>"New York",
        "home_state"=>"NY",
        "home_zip_code"=> "10019"
    },
    {
        "name"=>"Nico",
        "age"=>"61",
        "home_id"=> "1",
        "home_street"=>"1600 Broadway",
        "home_city"=>"New York",
        "home_state"=>"NY",
        "home_zip_code"=> "10019"
    }
]

Check yourself: does your method still work if a person doesn't yet have a home address?

New Format

people = [
    {
        "name"=>"Gert",
        "age"=>23,
        "home"=> {
          "id"=> 1,
          "street"=>"1600 Broadway",
          "city"=>"New York",
          "state"=>"NY",
          "zip_code"=> 10019
        }
    },
    {
        "name"=>"Alex",
        "age"=>42,
        "home"=> {
          "id"=> 1,
          "street"=>"1600 Broadway",
          "city"=>"New York",
          "state"=>"NY",
          "zip_code"=> 10019
        }
    },
    {
        "name"=>"Nico",
        "age"=> 61,
        "home"=> {
          "id"=> 1,
          "street"=>"1600 Broadway",
          "city"=>"New York",
          "state"=>"NY",
          "zip_code"=> 10019
        }
    }
]

Part 6

For this part, write a brand new data_transforms_locations method. Save your previous one(s)

HELLO is growing rapidly and has acquired an amazing high profile space for their next luxury dorm experience. So next, we'd like to be able to show a list of all our addresses with their corresponding tenants:

Original Format

NOTE assume all people with home_id of 1 are next to each other in the array. Same with home_id of 2, 3, etc

people = [
    {
        "name"=>"Gert",
        "age"=>"23",
        "home_id"=> "1",
        "home_street"=>"1600 Broadway",
        "home_city"=>"New York",
        "home_state"=>"NY",
        "home_zip_code"=> "10019"
    },
    {
        "name"=>"Alex",
        "age"=>"42",
        "home_id"=> "1",
        "home_street"=>"1600 Broadway",
        "home_city"=>"New York",
        "home_state"=>"NY",
        "home_zip_code"=> "10019"
    },
    {
        "name"=>"Nico",
        "age"=>"61",
        "home_id"=> "1",
        "home_street"=>"1600 Broadway",
        "home_city"=>"New York",
        "home_state"=>"NY",
        "home_zip_code"=> "10019"
    },
    {
        "name"=>"Molly",
        "age"=>"55",
        "home_id"=> "2",
        "home_street"=>"1 Alcatraz Island",
        "home_city"=>"San Francisco",
        "home_state"=>"CA",
        "home_zip_code"=> "94133"
    },
    {
        "name"=>"Karolina",
        "age"=>"82",
        "home_id"=> "2",
        "home_street"=>"1 Alcatraz Island",
        "home_city"=>"San Francisco",
        "home_state"=>"CA",
        "home_zip_code"=> "94133"
    }
]

New Format

[
    {
      "id"=> 1,
      "street"=>"1600 Broadway",
      "city"=>"New York",
      "state"=>"NY",
      "zip_code"=> 10019,
      "tenants" => [
            {
                "name"=>"Gert",
                "age"=>23
            },
            {
                "name"=>"Alex",
                "age"=>42
            },
            {
                "name"=>"Nico",
                "age"=>61
            }
        ]
    },
    {
      "id"=> 2,
      "street"=>"1 Alcatraz Island",
      "city"=>"San Francisco",
      "state"=>"CA",
      "zip_code"=> 94133,
      "tenants" => [
            {
                "name"=>"Molly",
                "age"=>23
            },
            {
                "name"=>"Karolina",
                "age"=>42
            }
        ]
    }
]

Part 7 - Hungry for more

Create the ability for data_transform_location to optionally return a specific home (with its tenants), based on an optional second home_id param:

p data_transform_location people, 2

should return

{
    "id"=> 2,
    "street"=>"1 Alcatraz Island",
    "city"=>"San Francisco",
    "state"=>"CA",
    "zip_code"=> 94133,
    "tenants" => [
        {
            "name"=>"Molly",
            "age"=>23
        },
        {
            "name"=>"Karolina",
            "age"=>42
        }
    ]
}

You did it! You started building your own ORM (Object Relational Mapping)

12 KiB Raw Blame History

HELLO - Start Building Your Own ORM

Learning Objectives

Prerequisites

Getting Started

Deliverables

Technical Requirements

Submission Guidelines

Context

Part 1 - explanation

Part 2 - code along

Part 3 - build it

Part 4 - build it

Part 5 - build it

Original Format

New Format

Part 6

Original Format

New Format

Part 7 - Hungry for more

12 KiB

Raw Blame History