Python 1501: Practice Missions II

Evolutionary Activities & Professional Practices

An extremely capable scripting language, Python is a natural choice for new, as well as experienced software developers.

What you’ll learn

  • Understand common / industry-wide terms, acronyms, as well as “best practice” app-creation techniques.
  • Continue to understand how to apply industry-standard requirement & design practices.
  • Apply what you have designed to incrementally create a data management application.
  • Use modules to organize & protect your Functions.
  • Discover how to use Package & “Access Diagrams” to discuss & document Functional Python.
  • Complete Python 1500’s CRUDS activity.
  • Enjoy more interview-worthy questions & answers over Mission topics.

Course Content

  • Part Three: Functional Applications (CONTINUED!) –> 1 lecture • 15min.
  • More C.R.U.D.s ‘Ops –> 1 lecture • 10min.
  • Basic Modules & Member Access –> 3 lectures • 21min.

Python 1501: Practice Missions II


An extremely capable scripting language, Python is a natural choice for new, as well as experienced software developers.


Targeting students needing to design & implement software on-the-job, this functional approach is faster way to start building you ‘Pythonic powers! -Not only can Python’s Packages & Modules be used quickly, but discovering how to create, manage, share functional creations is all we need to start using Python on the job.


Indeed, since classes themselves are made up of functions, students destined for various I.T roles must first master the in’s and out’s of Functional Python. A frequently ignored first-step, applying Functional Python just might be all concepts a DevOps professional might ever need to know to get the job done!


Next, collaborating over software design & patterns is usually important for testing, deploying as well as managing past, present, and future software development activities as well.

Even when we are working for ourselves – let alone working for others – unearthing hidden requirements, planning software versions, defining code / data relationships in advance, testing, as well as planning for feature regressions can usually become just as – if not often more – important!


Thus while our own academic and / or “for-personal-use-only” projects are often fast, loose and “code-only” creations, creating world-class software must usually be planned, tested, maintained… as well as deliberately designed to be feature-rich.


Please note that Python 1501 assumes that students have completed Python 1500.  -But those who have completed our Python 1000 and 1100 educational opportunities will also have no problem completing these Missions too!


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