Find the project spec here.

• Use tests to drive both the design and implementation of code
• Decompose a large application into components
• Use test fixtures instead of actual data when testing
• Connect related objects together through references
• Learn an agile approach to building software

git clone https://github.com/Maxscores/black_thursday.git
cd black_thursday
bundle

To Run Test Suite: rake

This project was assessed with the help of a spec harness. The README.md file includes instructions for setup and usage.

Make sure you're at the same level as the black_thursday project:

<my_code_directory>
|
|\
| \black_thursday/
|
|\
| \black_thursday_spec_harness/
|

git clone https://github.com/Maxscores/black_thursday_spec_harness
cd black_thursday_spec_harness
bundle

To Run Test Suite: bundle exec rake spec NOTE All Tests of Iteration 4 should be failing. We chose to do Iteration 5 instead.

To Interact from the command line run:

irb
require './lib/sales_engine.rb'
se = SalesEngine.load_default

Then start the analysis layer like so:

sa = SalesAnalyst.new(se)

Do most of our merchants offer just a few items or do they represent a warehouse?

sa.average_items_per_merchant # => 2.88

And what's the standard deviation?

sa.average_items_per_merchant_standard_deviation # => 3.26

Maybe we could set a good example for our lower sellers by displaying the merchants who have the most items for sale. Which merchants are more than one standard deviation above the average number of products offered?

sa.merchants_with_high_item_count # => [merchant, merchant, merchant]

Are these merchants selling commodity or luxury goods? Let's find the average price of a merchant's items (by supplying the merchant ID):

sa.average_item_price_for_merchant(6) # => BigDecimal

Then we can sum all of the averages and find the average price across all merchants (this implies that each merchant's average has equal weight in the calculation):

sa.average_average_price_per_merchant # => BigDecimal

Given that our platform is going to charge merchants based on their sales, expensive items are extra exciting to us. Which are our "Golden Items", those two standard-deviations above the average item price? Return the item objects of these "Golden Items".

sa.golden_items # => [<item>, <item>, <item>, <item>]

sa.average_invoices_per_merchant # => 8.5
sa.average_invoices_per_merchant_standard_deviation # => 1.2

Which merchants are more than two standard deviations above the mean?

sa.top_merchants_by_invoice_count # => [merchant, merchant, merchant]

Which merchants are more than two standard deviations below the mean?

sa.bottom_merchants_by_invoice_count # => [merchant, merchant, merchant]

On which days are invoices created at more than one standard deviation above the mean?

sa.top_days_by_invoice_count # => ["Sunday", "Saturday"]

What percentage of invoices are shipped vs pending vs returned? (takes symbol as argument)

sa.invoice_status(:pending) # => 5.25
sa.invoice_status(:shipped) # => 93.75
sa.invoice_status(:returned) # => 1.00