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Alek Binion - CMA Developer Code Test

Part 1: Data Transformation

Solution :

The solution to part 1 can be found in the file part1.py. I wrote part1.py in Python 3.6.3. The .JSON file produced is table.JSON.

Assignment:

A 5-table SQLite database has been provided. The database contains a table of 100 artworks, a table of creators, a table of departments, and 2 linking tables containing the relationships between artworks, departments, and creators.

Using python, write a script that extracts the data from the tables and writes them to a single array of JSON objects. Each object should contain all the information relevant to an artwork. Write the resulting data to a file.

Part 2: Front-End Data Presentation

Solution:

My solution to part 2 can be found in the part2 directory. My solution uses JQuery to assist in generating the interface. Interface is generated in part2/js/displayDBinfo.js, and is styled in part2/css/art-view.css. The result can be seen at the following url https://biniona.github.io/developer-code-test/part2/index.html. The solution works well on mobile as well so check it out on a phone if you are interested.

Assignment:

Using the web or mobile framework of your choice, create a simple app that ingests the JSON file from Part 1 and displays all the information in a clear interface. Feel free to be creative and keep in mind that each artwork record will have a lot of data, so displaying all the data, all at once, will not result in a “clear interface”. Also provided is a folder of artwork images that are referenced in the artwork data. The images are named by the accession number of the artwork (a unique identifier assigned to an artwork when it is acquired by a musuem). These images should also be incorporated into the final app.

Completion and Submission

Completed work should include all code to arrive at the solution, plus all code, assets, and resources required to run the final result of part 2. All completed work should be pushed to a public repo on GitHub.

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  • CSS 45.9%
  • JavaScript 30.8%
  • HTML 14.6%
  • Python 8.7%