TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #15404 · Jan 9
#shell Superpowers turns a coding agent into a disciplined helper that first clarifies what you want, then designs, plans, and implements features using clear steps and strict test‑driven development. It automatically manages branches, breaks work into tiny tasks, uses sub‑agents with built‑in reviews, and enforces quality checks before merging. You benefit by getting more reliable code, less babysitting of the AI, safer experimentation in isolated branches, and a repeatable workflow that feels like working with a careful junior engineer who always follows best practices. https://github.com/obra/superpowers
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@djangoproject · Post #574 · 02/25/2018, 02:34 PM
http://www.paulbrownmagic.com/blog/python_partial_application Python Partial: Code Your Intention Of all the functional programming inspired features in Python, partial application must be the best kept secret that you really need to know. Partial application lets you create highly abstract functions and make them more specific for use, pass a function arguments without calling it yet, and so much more. #tuple#sort
@djangoproject · Post #153 · 09/03/2016, 08:20 PM
http://wla.berkeley.edu/~cs61a/fa11/lectures/streams.html In this chapter, we continue our discussion of real-world applications by developing new tools to process #sequential#data. In Chapter 2, we introduced a sequence interface, implemented in Python by built-in data types such as #tuple and #list. #Sequences supported two operations: querying their length and accessing an element by index. In Chapter 3, we developed a user-defined implementations of the sequence interface, the Rlist class for representing recursive lists. These sequence types proved effective for representing and accessing a wide variety of sequential #datasets.