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146 changes: 73 additions & 73 deletions transcripts/01-introduction/1.txt
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0:01 Hello and welcome to the course Write Pythonic Code Like a Seasoned Developer. 
0:04 My name is Michael Kennedy and we are going to be on this journey together 
0:07 to help you write more readable, more efficient and more natural Python code. 
0:13 So what is Pythonic code anyway? 
0:01 Hello and welcome to the course Write Pythonic Code Like a Seasoned Developer.
0:04 My name is Michael Kennedy and we are going to be on this journey together
0:07 to help you write more readable, more efficient and more natural Python code.
0:13 So what is Pythonic code anyway?
0:16 When developers are new to Python, they often hear this phrase Pythonic
0:20 and they ask what exactly does that mean? 
0:23 In any language, there is a way of doing things naturally 
0:26 and a way that kind of fight the conventions to the language.
0:30 When you work naturally with the language features and the runtime features, 
0:33 this is called idiomatic code, 
0:35 and in Python when you write idiomatic Python we call this Pythonic code. 
0:40 One of the challenges in Python is it's super easy to get started 
0:43 and kind of learn the basics and start writing programs 
0:46 before you really master the language. 
0:48 And what that often means is people come in from other languages 
0:51 like C++ or Java or something like that, 
0:53 they will take algorithms or code that they have and bring it over to Python 
0:58 and they will just tweak the syntax until it executes in Python, 
1:00 but this often uses the language features of let's just focus on Java. 
1:04 In Python there is often a more concise, more natural way of doing things, 
1:10 and when you look at code that came over from Java, 
0:20 and they ask what exactly does that mean?
0:23 In any language, there is a way of doing things naturally
0:26 and a way that kind of fight the conventions of the language.
0:30 When you work naturally with the language features and the runtime features,
0:33 this is called idiomatic code,
0:35 and in Python when you write idiomatic Python we call this Pythonic code.
0:40 One of the challenges in Python is it's super easy to get started
0:43 and kind of learn the basics and start writing programs
0:46 before you really master the language.
0:48 And what that often means is people come in from other languages
0:51 like C++ or Java or something like that,
0:53 they will take algorithms or code that they have and bring it over to Python
0:57 and they will just tweak the syntax until it executes in Python,
1:00 but this often uses the language features of - let's just focus on Java.
1:04 In Python there is often a more concise, more natural way of doing things,
1:09 and when you look at code that came over from Java,
1:11 we'll just take a really simple example-
1:13 if you have a class and the class has a get value and set value, 
1:13 if you have a class and the class has a get value and set value,
1:17 because in Java that is typically the way you do encapsulation,
1:20 people bring those classes in this code over and migrate it to Python, 
1:24 they might still have this weird getter setter type of code. 
1:28 And that would look completely bizzare in Python 
1:31 because we have properties for example. 
1:33 So we are going to look at this idea of Pythonic code, 
1:36 now it's pretty easy to understand but it turns out to be fairly hard to make concrete, 
1:40 you'll see a lot of blog posts and things of people trying to put structure 
1:44 or examples behind this concept of Pythonic code. 
1:20 and people bring those classes in this code over and migrate it to Python,
1:24 they might still have this weird getter/setter type of code.
1:28 And that would look completely bizzare in Python
1:31 because we have properties for example.
1:33 So we are going to look at this idea of Pythonic code,
1:36 now, it's pretty easy to understand but it turns out to be fairly hard to make concrete,
1:40 you'll see a lot of blog posts and things of people trying to put structure
1:44 or examples behind this concept of Pythonic code.
1:48 We are going to go through over 50 examples of things I consider Pythonic
1:53 and by the end you'll have many examples, 
1:56 patterns and so on to help you have a solid grip on what Pythonic code is. 
2:01 So what is Pythonic code and why does it matter? 
1:53 and by the end you'll have many examples,
1:56 patterns and so on to help you have a solid grip on what Pythonic code is.
2:02 So what is Pythonic code and why does it matter?
2:05 Well, when you write Pythonic code,
2:07 you are leveraging the experience of 25 years of many thousands, 
2:10 maybe millions of developers, 
2:12 these guys and girls have worked in this language day in and day out 
2:16 for the last 25 years and they really perfected the way 
2:19 of working with classes, functions, loops, and so on, 
2:23 and when you are new especially, 
2:25 it's very helpful to just study what those folks have done and mimic that. 
2:29 When you write Pythonic code, you are writing code 
2:32 that is specifically tuned to the CPython runtime. 
2:35 The CPython interpreter and the Python language have evolved together, 
2:40 they have grown up together, 
2:42 so the idioms of the Python language are of course matched 
2:44 or paired well with the underlying runtime, 
2:47 so writing Pythonic code is an easy way 
2:07 you are leveraging the experience of 25 years of many thousands,
2:10 maybe millions of developers,
2:12 these guys and girls have worked in this language day in and day out
2:16 for the last 25 years and they really perfected the way
2:19 of working with classes, functions, loops, and so on,
2:23 and when you are new especially,
2:25 it's very helpful to just study what those folks have done and mimic that.
2:29 When you write Pythonic code, you are writing code
2:32 that is specifically tuned to the CPython runtime.
2:35 The CPython interpreter and the Python language have evolved together,
2:40 they have grown up together,
2:42 so the idioms of the Python language are of course matched
2:44 or paired well with the underlying runtime,
2:47 so writing Pythonic code is an easy way
2:50 to write code that the interpreter expects to run.
2:54 When you write Pythonic code, 
2:54 When you write Pythonic code,
2:56 you are writing code that is easily read and understood by Python developers.
2:59 A Python developer can look at standard idiomatic Python
3:03 and just glance at sections and go, 
3:05 "oh, I see what they are doing here, I see what they are doing there, bam, bam, bam" 
3:09 and quickly understand it. 
3:11 If instead it's some algorithm that is taken from another language with other idioms, 
3:15 the experienced developer has to read through and try to understand 
3:20 what is happening at a much lower level, 
3:23 and so your code is more readable to experienced developers 
3:27 and even if you are new will become probably more readable to you 
3:03 and just glance at sections and go,
3:05 "oh, I see what they are doing here, I see what they are doing there, bam, bam, bam"
3:09 and quickly understand it.
3:10 If instead it's some algorithm that is taken from another language with other idioms,
3:15 the experienced developer has to read through and try to understand
3:20 what is happening at a much lower level,
3:23 and so your code is more readable to experienced developers
3:27 and even if you are new will become probably more readable to you
3:30 if you write Pythonic code.
3:33 One of the super powers of Python is that it is a very readable 
3:36 and simple language without giving up the expressiveness of the language. 
3:40 People coming from other languages that are less simple, 
3:43 less clean and easy to work with 
3:46 will bring those programming practices or those idioms over 
3:49 and they will write code that is not as simple as it could be in Python 
3:32 One of the super powers of Python is that it is a very readable
3:36 and simple language without giving up the expressiveness of the language.
3:40 People coming from other languages that are less simple,
3:43 less clean and easy to work with
3:46 will bring those programming practices or those idioms over
3:49 and they will write code that is not as simple as it could be in Python
3:53 even though maybe it was a simple as it could be in C.
3:56 So when you write Pythonic code,
3:58 you are often writing code that is simpler and cleaner 
4:01 than otherwise would be the case. 
4:03 If you are working on an open source project, 
4:05 it will be easier for other contributors to join in because like I said, 
4:08 it's easier for them to read and understand the code at a glance, 
4:11 and they will more naturally know what you would expect them to write. 
4:14 If you are working on a software team, 
4:17 it's easier to onboard new Python developers into your team
4:20 if you are writing idiomatic code, 
4:22 because if they already know Python 
4:24 it's much easier for them to 
4:26 your large project. 
3:57 you are often writing code that is simpler and cleaner
4:00 than otherwise would be the case.
4:02 If you are working on an open source project,
4:04 it will be easier for other contributors to join in because like I said,
4:08 it's easier for them to read and understand the code at a glance,
4:11 and they will more naturally know what you would expect them to write.
4:14 If you are working on a software team,
4:16 it's easier to onboard new Python developers into your team
4:20 if you are writing idiomatic code,
4:22 because if they already know Python
4:23 it's much easier for them to grok
4:26 your large project.
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0:01 What areas are we going to cover in this class?
0:03 Well, we are going to start with the foundations and this concept called pep 8. 
0:06 So, pep 8 is a standardized document 
0:09 that talks about the way code should be formatted, 
0:11 and even some of the Pythonic ideas and Pythonic code examples. 
0:15 However, we are going to go way beyond pep 8 in this course, 
0:19 and so we'll probably spend 15 minutes talking about pep 8 
0:22 and then we'll move onto other foundational items. 
0:25 Then we are going to focus on dictionaries, 
0:28 dictionaries play a super important role in Python, 
0:01 What areas are we going to cover in this class?
0:03 Well, we are going to start with the foundations and this concept called PEP 8.
0:06 So, PEP 8 is a standardized document
0:09 that talks about the way code should be formatted,
0:11 and even some of the Pythonic ideas and Pythonic code examples.
0:16 However, we are going to go way beyond PEP 8 in this course,
0:19 and so we'll probably spend 15 minutes talking about PEP 8
0:22 and then we'll move onto other foundational items.
0:25 Then we are going to focus on dictionaries,
0:28 dictionaries play a super important role in Python,
0:30 they are basically the backing store for classes,
0:34 they are used for data exchange all over the place, 
0:37 and there are a lot of interesting use cases and ways 
0:40 in which dictionaries are used in a language. 
0:43 We are going to talk about a lot of interesting aspects 
0:45 and optimal ways to use and leverage dictionaries. 
0:48 Next up are working with collections, 
0:51 things called list comprehensions and generator expressions. 
0:55 And we'll see that Python has a lot of interesting flexibility 
0:58 around working with sequences, 
1:01 and we'll see the best way to do this here. 
1:04 Next, functions and methods. 
1:06 This will include the use of things like lambda expressions for small inline methods, 
1:11 as well as returning multiple values from methods and that sort of things. 
1:14 There is a lot to look at to write Pythonic functions. 
1:17 One of the great powers of Python 
1:19 is the ability to import or pip install a whole variety of packages, 
1:25 there is even a great xkcd cartoon about importing packages in Python, 
1:31 and we'll see that there are a lot of interesting Pythonic conventions 
1:33 around working with packages and modules. 
1:36 Next up, we are going to look at classes and objects. 
1:40 Object oriented programming in Python is a key corner stone concept, 
1:44 even though it may play a slightly less important role 
1:47 than languages like Java and CSharp, 
1:50 still, classes are really important 
1:52 and there is a lot of idiomatic conventions around working with classes, 
1:55 we'll focus on that in this section. 
1:57 Python has a lot of powerful ways of working with loops, 
2:01 one of the first giveaways if somebody is brand new to Python 
2:04 is they are not using loops correctly, 
2:07 so we'll talk about when and how you should use loops 
2:10 and we'll even talk about the controversial else clause 
2:12 for for in and while loops. 
2:14 Next, we'll talk about tuples. 
2:16 Tuples are smallish, read-only collections 
2:18 that let you package up related possible heterogeneous data 
2:23 and pass it around, 
2:25 If we go into a basic database queries and the built in db api 
2:28 you'll see that the rows come back as tuples. 
2:31 Some of the powerful techniques we'll learn about loops involve tuples 
2:34 and we'll see that tuples in general play a really important role, 
2:37 and there is some powerful and useful conventions 
2:40 around working with tuples in Python. 
2:42 Finally, we are going to look beyond the standard library, 
2:45 with something I am calling Python for Humans; 
2:47 one of the great powers of Python is the ability to go out to PyPi 
2:51 and grab one of the over 80 000 packages, 
0:34 they are used for data exchange all over the place,
0:37 and there are a lot of interesting use cases and ways
0:40 in which dictionaries are used in a language.
0:43 We are going to talk about a lot of interesting aspects
0:45 and optimal ways to use and leverage dictionaries.
0:49 Next up are working with collections,
0:51 things called list comprehensions and generator expressions.
0:55 And we'll see that Python has a lot of interesting flexibility
0:58 around working with sequences,
1:01 and we'll see the best way to do this here.
1:04 Next, functions and methods.
1:06 This will include the use of things like lambda expressions for small inline methods,
1:11 as well as returning multiple values from methods and that sort of things.
1:14 There is a lot to look at to write Pythonic functions.
1:17 One of the great powers of Python
1:20 is the ability to import or pip install a whole variety of packages,
1:25 there is even a great xkcd cartoon about importing packages in Python,
1:31 and we'll see that there are a lot of interesting Pythonic conventions
1:33 around working with packages and modules.
1:36 Next up, we are going to look at classes and objects.
1:40 Object oriented programming in Python is a key cornerstone concept,
1:44 even though it may play a slightly less important role
1:47 than languages like Java and C#,
1:50 still, classes are really important
1:52 and there is a lot of idiomatic conventions around working with classes,
1:55 we'll focus on that in this section.
1:57 Python has a lot of powerful ways of working with loops,
2:01 one of the first giveaways if somebody is brand new to Python
2:04 is they are not using loops correctly,
2:07 so we'll talk about when and how you should use loops
2:10 and we'll even talk about the controversial else clause
2:12 for "for...in" and "while" loops.
2:14 Next, we'll talk about tuples.
2:16 Tuples are smallish, read-only collections
2:18 that let you package up related possibly heterogeneous data
2:23 and pass it around,
2:25 If we go into a basic database queries and the built in DB API
2:28 you'll see that the rows come back as tuples.
2:31 Some of the powerful techniques we'll learn about loops involve tuples
2:34 and we'll see that tuples in general play a really important role,
2:37 and there is some powerful and useful conventions
2:40 around working with tuples in Python.
2:42 Finally, we are going to look beyond the standard library,
2:45 with something I am calling Python for Humans;
2:47 one of the great powers of Python is the ability to go out to PyPi
2:51 and grab one of the over 80 000 packages,
2:54 install them using pip or something like this
2:57 and add amazing powers to your application. 
3:00 People who are new to Python often skip this step 
3:03 and they look at something they have to do and are just like 
3:07 ok I think I can implement it in these 20 lines of code.
3:10 It's very likely that there is already a package out there 
3:14 that you can use to do this, 
3:16 so we are going to study two packages one for http 
3:18 and one for database access to really bring home this point of look to PyPi 
3:24 and look to open source first before you start writing your own algorithms. 
3:28 Of course, over time, we may add more topics than what are described here, 
3:32 I am sure as more and more people take this class they will say, 
3:35 "Hey Michael, did you think about having this", 
3:38 or "I also consider this little bit to be idiomatic." 
3:40 Now I don't want to just grab every single detail that I can find, 
3:44 that is possibly Pythonic code and cram it in here, 
3:48 I want to cover the stuff that's most important and not waste your time, 
3:50 but of course, I am sure we'll hear about some new ones 
3:53 that are great and those may be folded in over time. 

2:57 and add amazing powers to your application.
3:00 People who are new to Python often skip this step
3:03 and they look at something they have to do and are just like
3:07 OK I think "I can implement it in these 20 lines of code".
3:10 It's very likely that there is already a package out there
3:14 that you can use to do this,
3:16 so we are going to study two packages one for HTTP
3:18 and one for database access to really bring home this point of look to PyPi
3:24 and look to open source first before you start writing your own algorithms.
3:28 Of course, over time, we may add more topics than what are described here,
3:32 I am sure as more and more people take this class they will say,
3:35 "Hey Michael, did you think about having this",
3:38 or "I also consider this little bit to be idiomatic."
3:40 Now I don't want to just grab every single detail that I can find,
3:44 that is possibly Pythonic code and cram it in here,
3:48 I want to cover the stuff that's most important and not waste your time,
3:50 but of course, I am sure we'll hear about some new ones
3:53 that are great and those may be folded in over time.
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0:01 We are going to write a lot of code in this course. 
0:02 And you want to download it and play with it 
0:04 and experiment with it and so on 
0:07 so of course I am going to put this into a github repository, 
0:10 here you can see github.com/mikeckennedy/write-pythonic-code-demos
0:14 so I recommend that you go out there 
0:17 and star this so you have it as a reference. 
0:01 We are going to write a lot of code in this course.
0:02 And you want to download it and play with it
0:04 and experiment with it and so on
0:06 so of course I am going to put this into a GitHub repository,
0:09 here you can see github.com/mikeckennedy/write-pythonic-code-demos
0:14 so I recommend that you go out there
0:16 and star this so you have it as a reference.
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