Extending the design of a blocks-based python environment to support complex types

Matthew Poole
2017 2017 IEEE Blocks and Beyond Workshop (B&B)  
We are currently developing PyBlocks, a blocksbased environment which allows novice programmers to construct and execute Python programs. In the initial design of PyBlocks [1], Python's basic data types and lists are represented using colors, every expression block is colored according to its type, and each unfilled slot contains color indicating all valid argument types. In this paper we extend the design to include Python's most common built-in composite types (lists, tuples, dictionaries and
more » ... sets) and to allow nesting of these where appropriate. Using example types from a pedagogical media computation library, we also show how further types may be supported. Together, these extensions provide almost any type novice Python programmers are likely to use.
doi:10.1109/blocks.2017.8120400 fatcat:rz3nqdmn3jegnbs34qrrhb6doy