Category: Python
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Thinking with “map”
In the free Webinar I gave yesterday about functional programming, I mentioned that “map,” or its equivalent (e.g., Python’s list comprehensions), is a powerful tool that I use nearly every day. Once you get into the functional mode of thinking, you’re constantly finding ways to turn one collection into another collection. It’s a mindset that…
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The relative speeds of str.format and %
My most recent blog post talked about the use of str.format instead of the % operator for interpolating values into strings. Some people who read the post wondered about their relative speeds. I should first note that my first response to this is: I don’t really care that much. I’m not saying that speed isn’t…
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Teaching an old dog new tricks — or, how I learned to love Python’s str.format, and gave up on %
I have been programming in Python for many years. One of the things that I wondered, soon after starting to work in Python, was how you can get Perl-style variable interpolation. After all, Perl (like the Unix shell) supports two types of quotes — single quotes (in which everything is taken literally) and double quotes…
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Three Pythonic products: A (free) Webinar, a course, and an ebook
I love developing software. I also love helping people to learn how to develop better. That’s why I have been teaching programming classes for more than a decade, and why I write about programming. There is so much to learn; it’s a rare day on which I don’t learn something new, and it’s a rare…
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Summary of my “reduce” series
I teach Ruby and Python to a lot of people — in formal courses, and in one-on-one pairing sessions, both online and in person. I’ve found that for many people, the whole notion of functional programming seems strange and difficult, as well as something of a waste of time. After all, if you have objects,…
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Implementing “filter” with “reduce”, in Ruby and Python
We’re nearly at the end of my tour of the “reduce” function in Ruby and Python. Just as I showed in the previous installment how we can implement the “map” function using “reduce”, I want to show how we can implement another functional-programming standard, “filter”, using “reduce” as well. As before, I’ll show examples in…
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Implementing “map” with “reduce”, in Ruby and Python
This is another installment in my “reduce” series of posts, aimed at helping programmers understand this function, with examples in both Ruby and Python. So far, we have seen how we can build a number of different types of data structures — integers, strings, arrays, and hashes — using “reduce”. But the really interesting use…
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Creating Python dictionaries with “reduce”
In the last few installments (first, second, third, and fourth) of this series, we saw how “reduce” can be used to build up a scalar value (such as a number or string), or even a simple collection, such as a list (in Python) or an array (in Ruby). The jewel in the data-structure crown for…
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Creating collections with “reduce”
In the first few parts of this series (first, second, and third), I introduced the “reduce” function, and showed how it can be used in a number of ways. However, in all of the examples we have seen so far, the output from our invocations of “reduce” were integers or strings. If we reduce with…
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Implementing “min” and “max” with “reduce”
This is the third installment of my “reduce” series of blog posts. For the first, see here, and for the second, see here. If you have been reading this series, then you know that “reduce” can be used to sum numbers, or to calculate scores. In that sense, “reduce” justifies its name; we’re invoking a…