Write Pythonic Code Like a Seasoned Developer Transcripts
Chapter: Python for Humans
Lecture: Human Python as a stand in for packages in general
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Let's round out the course with a little bit of Python for Humans,
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and that's a bit of a play in words from some of the most popular
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open source projects that really add power to Python.
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This section we are going to look at two separate external packages
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and how simple and lovely they make it to work with certain types of data
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and we are going to do this because it really is meant to be a stand-in
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for look at open source, look at PyPi and look to the community
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and ecosystem before you start working on your project
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for all the things that you can build your project from.
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There is an amazing set of lego blocks out there
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all you have to do is know to reach for them.
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So if you find yourself thinking "hm, how am I going to
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implement this bit?" of whatever subsystem you are working on in Python,
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stop and do a little research first.
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For example, if you are going to work with user accounts,
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and you need to store user names and passwords,
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you hopefully know that you should hash those passwords.
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Did you know you should use separate salt per user
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to go into hashing their password?
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Did you know that you should fold that hashing over and over and over again
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to make it computationally difficult?
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Not five times or ten times but something like a hundred thousand times.
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So if you are thinking oh my gosh, this is going to be a lot of work,
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that's one way to think about it, the other one could be "oh,
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there is a really great library for exactly that thing called passlib", go grab that, OK?
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So when we look at these two packages yes,
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it's great that you know about them,
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but the most important takeaway is not the details of the two packages
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we are going to focus on, but really the concept of there are so much out there
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to work from you really should start there.
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Right, so the first place to look is probably PyPi,
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the Python package index and you can see at the time of this recording,
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there is 82 000+ packages there, so about 300 new unique packages a day,
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and the power of what's available here really is the main reason
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why Python is popular.
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Another really important place to look for Python libraries and tools is of course GitHub.
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So there is this really cool site called GitHut.info, let's check that out quickly.
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So here you can see, these are all the popular languages on GitHub,
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and here is their active repositories, the total number of pushes, number of forks,
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how recent it was, what year it appeared and you can actually hover over these
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and it tells you all sorts of things,
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so for example we could compare say Python to C#, to Ruby
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and you can see that Python is more popular than Ruby, way more popular than C#,
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anyway, GitHub is such a central part of modern software development
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and look where Python lives, we have Python,
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we have Java, and we have Javascript.
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Now, my interpretation of this data is that Javascript is not really earning its position here,
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I think this counts the Javascript that are in the Java websites, the Python websites,
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the PHP websites, the Ruby websites, the C# websites, and so on,
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so I think Javascript is being over counted here, so either way,
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Python is either 3 or 2 on this list, so certainly, look to GitHub,
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look to PyPi for your packages and your features
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before you just write the whole thing from scratch,
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remember, Python comes with batteries included,
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these two places are often where you find those batteries.
