Job opportunity 🙌 🙏 is the money you have given to many of these people and I will send them some more important information about what you have done ✔️
I've barely learned anything in python and easily picked up the information. So simple, yet elegant explanations. Thank you. It has already helped me in my assignments.
Absolutely the best tutorial I’ve watched on comprehensions. Thank you for making it very understandable. I would also appreciate the same type of video covering Lambda functions. Thanks again for helping so many!!
Man list comprehensions are just amazing. I've just finished a level 1000 coding module in python. Basically, i ended up (ab)using list compre wherever I could. It's just that elegant!
You can even nest comprehensions inside of other functions, inside of user inputs... ie: print(*(list("Hello" for _ in range(int(input("How many 'Hello' would you like to print? ")))))) Python is wild...
I found the way you formatted the comprehension that calculates squares is a really helpful way to think about comprehensions, even if I compress them to a single line. In that form, it looks like the comprehension just skips the result=[ ] statement, which I always thought was ugly. And in nested loops it gets rid of all those intermediate lists and variables. For the first time they look more elegant to me.
Most comprehensions can be replaced by some combination of map and filter, which I find far cleaner. Further, in most cases, you will iterate through the iterator only once, in which case, you can leave it as an iterator (map and filter) form until you use it (unlike, for example, using comprehension to give you an iterable). This is far more pythonic and memory efficient too.
Things are a bit gray here. You can easily replace the list comprehension to a generator comprehension by just changing to parenthesis, in case you need that memory efficiency. Most developers nowadays advocate for list/gen comprehensions over map and filter statements, for readability and performance. There is nothing wrong with map and filter, though.
@@elatedbento Curious, do most developers advocate against map and filter? Why? I am just curious if there have been some benchmarking on performance or some other motivation behind it that I don't know of. In general, I love the clarity of functional constructs which explains my bias.
Oof you got me. Been writing python for 15 years and never knew that you could have multiple `if` statements in a comprehension. I have always written `and` and assumed you made a syntax error 😂
Another interesting point about generator expressions, is how they work with the all and any functions. Those functions will use the same kind of short-circuit evaluation that compound conditionals use -- that is, they will only evaluate as many items from the generator that they need in order to determine whether the result should be True or False.
Man, you grew a lot in past 3 years :)) I'm just watching your video called: Python Selenium Tutorial #2 - Locating Elements From HTML, where you are referring to your website for testing. However, it's no use as the website is now different - can you do the remake of your selenium tutorials / make it up-to date? Thank you and good luck!
Thank you Tim. I would recommend to add a profiler to show the time execution advantage (if any) for comprehensions. That wold be nice for each example.
Great video. One thing you might add is a speed comparison. I believe comprehensions are extremely fast, and while one might argue readability, performance is far superior.
@@GigasAhriman The last example in this video showed a scenario. Star with a range of like 100M. Then make a list of the integers. Do it in a for loop (with list.append()) and then in a comprehension. Use time.perfcounter() before and after.
@@BrianStDenis-pj1tq Thanks for the perf_counter tip. I ran the 3D array (1000 x 200 x 500) test both ways. The loop was 4.7 sec, the comprehension was 2.6 sec. Results varied if I used numbers too small or so large that they ate up all my RAM.
The syntax for flattening a list always feels very wrong. Given that single list comprehensions put their iterable to the left, it always feels odd that for num in row is to the right of matrix. It REALLY feels like it should have been [num for num in row for row in matrix] instead of what it actually is. I actually think this is one of the worst bits of Python and I encourage people to not do these neste/unpacking list comphrensions because of how unreadable they are. It would have been great if they gave us some kind of unpacking operator syntactic sugar here with [*row for row in matrix]. That would have been a much better syntax than [item for sublist in nested_list for item in sublist]
This is an absolutely excellent video. Your examples and explanations are always great. I think it is time for you to start working on a Python book. I am sure it will be a huge success. :)
nice synthesis. I'm using all of them(except multiple if condition, nice one). I would add another dictionary comprehension that I use often, when i want to filter items or find items in a really big dictionary: hay_dictionary = {"first": 1, "second": 2, "needle":4, "second_needle": 5, "last": 6, .................} a really big dictionary {k:v for k, v in hay_dictionary.items() if "needle" in k} this will return only the item that have in key "needle" {"needle":4, "second_needle": 5}
For number 1, it’s much easier just to write list(range(10)) or [*range(10]. Of course, this doesn’t allow for manipulation of the numbers in the range, but it’s still something to be aware of. Same type of thing goes for the conditional comprehension and the filter function.
In "Comprehension with Multiple Conditions", if len(string) >=2 is not needed. The following will do valid_strings = [option for option in options if option[0]=='a' and option[-1]=='y' ]
Yeah personally, these comprehensions would confuse the hell out of someone who's unfamiliar and probably would have understood the more verbose syntax easier.
regarding the check on string length (5:40): string[slice(None, 1)] == 'a' and string[slice(None, -2, -1)] == 'y' works so: >>>valid_string = list(filter(lambda string: string[slice(None, 1)] == 'a' and string[slice(None, -2, -1)] == 'y', options)) takes care of business, buy may necessitate a code comment.
This is a great video but I've been having the issue of figuring out when I would use these in real life scenarios m it would be great if I had applicable examples
Is there anything else among features of Python that is on the level of usefulness of comprehensions? I've been programming in Python for over 5 years now, and that's the only half-advanced feature of it that I'm using. Oh, also tiny lambdas and context managers.
hey! curous about the last example where you do: sum(x**2 for x in range(10000000)) instead of sum([x**2 for x in range(10000000)]). I just tested it out, but I see that using the list comprehension is a bit faster to execute. Why is it that the execution time is slower for a more efficient approach using the generator?
The have a paid course on algoexpert. But that's not for beginners. i have a year of experience. even that's was a little bit hard for me. but now i am smooth. mmmm it was great "i think".
even/odd. since if is the new goto (harmful), I select with: {0: 'even', 1: 'odd'}[x % 2] which is why devs hate me. Actually, I'd map the list to (2).__rmod__ and map that to dict.getitem.
This is generator: sub_of_squares = (x**2 for x in range(100)) and you can use next(sub_of_squares) And this is sum function that call generator instead create whole list sub_of_squares = sum(x**2 for x in range(100))
In the first group the unwanted options are being filtered out, (toss out anything too short), and in the comprehension he is selecting for those strings that match the requirements. Same end result but one test is the inverse.
TIIIIMMMMM i copy the the script "strings that start with 'a" and end with "y" as it shows in the screen and when i run it give me 3 errors for every instance that you have "string" and asked me for "strings" and the code runned great, so I think you made 3 typos.
I understand the intention… but I dont understand why you dont show the differences in execution time. If there is no difference its not worth it at the moment in my opinion.
It’s been pointed out in other comments that comprehensions are faster…. Someone suggested Time.perf_counter() Programmers reading code efficiently (see what’s written, faster and more reliably) has value too.
I guess this is mostly about readability, the performance increase varies from version to version of python (just got a boost in 3.12, see mcoding's video)
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Job opportunity 🙌 🙏 is the money you have given to many of these people and I will send them some more important information about what you have done ✔️
could you do javascript beginner to pro challenges on code wars or anyotherway
May I ask, what is your keyboard, it sounds great btw
Ok
boy do you know str.startswith() and str.endswith ?
I've barely learned anything in python and easily picked up the information. So simple, yet elegant explanations. Thank you. It has already helped me in my assignments.
Absolutely the best tutorial I’ve watched on comprehensions. Thank you for making it very understandable. I would also appreciate the same type of video covering Lambda functions. Thanks again for helping so many!!
Man list comprehensions are just amazing. I've just finished a level 1000 coding module in python. Basically, i ended up (ab)using list compre wherever I could. It's just that elegant!
You can even nest comprehensions inside of other functions, inside of user inputs...
ie:
print(*(list("Hello" for _ in range(int(input("How many 'Hello' would you like to print? "))))))
Python is wild...
I found the way you formatted the comprehension that calculates squares is a really helpful way to think about comprehensions, even if I compress them to a single line. In that form, it looks like the comprehension just skips the result=[ ] statement, which I always thought was ugly. And in nested loops it gets rid of all those intermediate lists and variables. For the first time they look more elegant to me.
Most comprehensions can be replaced by some combination of map and filter, which I find far cleaner. Further, in most cases, you will iterate through the iterator only once, in which case, you can leave it as an iterator (map and filter) form until you use it (unlike, for example, using comprehension to give you an iterable). This is far more pythonic and memory efficient too.
Things are a bit gray here. You can easily replace the list comprehension to a generator comprehension by just changing to parenthesis, in case you need that memory efficiency. Most developers nowadays advocate for list/gen comprehensions over map and filter statements, for readability and performance. There is nothing wrong with map and filter, though.
@@elatedbento Curious, do most developers advocate against map and filter? Why? I am just curious if there have been some benchmarking on performance or some other motivation behind it that I don't know of.
In general, I love the clarity of functional constructs which explains my bias.
Oof you got me. Been writing python for 15 years and never knew that you could have multiple `if` statements in a comprehension. I have always written `and` and assumed you made a syntax error 😂
nah jit bro got a whole level of python knowledge but still dont know that
@@wandksitesupport2777 it doesnt matter to be honest correct me if i wrong but if you replace all if's with and expect first it would work the same
Writing "and" is much cleaner and more readable, I find it odd that multiple if statements are valid.
Is this list comprehensive of all comprehensions ? 😅
Is your comprehension comprehensive?
As a connoisseur of dad jokes I want to thank you for this contribution. 🎉
Comprehensive list of comprehensions to help comprehend a list of comprehensions within which the list comprehension is included.
@@NearLWatson Comprende?
07:28 I actually never knew you could insert multiple conditions like that, pretty cool!
what's the difference between that and simply chaining the conditions together with the "and" operator?
Nested list comp:
>>>flattened = list(chain(*matrix))
chain is from itertools.
They also have a chain_from_iterable for this case... but I agree, I'd rather just type the star
Another interesting point about generator expressions, is how they work with the all and any functions. Those functions will use the same kind of short-circuit evaluation that compound conditionals use -- that is, they will only evaluate as many items from the generator that they need in order to determine whether the result should be True or False.
Man, you grew a lot in past 3 years :))
I'm just watching your video called: Python Selenium Tutorial #2 - Locating Elements From HTML, where you are referring to your website for testing. However, it's no use as the website is now different - can you do the remake of your selenium tutorials / make it up-to date?
Thank you and good luck!
Thank you Tim. I would recommend to add a profiler to show the time execution advantage (if any) for comprehensions. That wold be nice for each example.
Great video. One thing you might add is a speed comparison. I believe comprehensions are extremely fast, and while one might argue readability, performance is far superior.
I've always wondered about speed comparison but I have no idea how to set that one up
@@GigasAhriman The last example in this video showed a scenario. Star with a range of like 100M. Then make a list of the integers. Do it in a for loop (with list.append()) and then in a comprehension. Use time.perfcounter() before and after.
@@BrianStDenis-pj1tq that's the first time I've heard of time.perfcounter()
Ty
@@GigasAhriman BTW, I left out a character, its time.perf_counter()
@@BrianStDenis-pj1tq Thanks for the perf_counter tip. I ran the 3D array (1000 x 200 x 500) test both ways. The loop was 4.7 sec, the comprehension was 2.6 sec. Results varied if I used numbers too small or so large that they ate up all my RAM.
The syntax for flattening a list always feels very wrong. Given that single list comprehensions put their iterable to the left, it always feels odd that for num in row is to the right of matrix. It REALLY feels like it should have been [num for num in row for row in matrix] instead of what it actually is. I actually think this is one of the worst bits of Python and I encourage people to not do these neste/unpacking list comphrensions because of how unreadable they are. It would have been great if they gave us some kind of unpacking operator syntactic sugar here with [*row for row in matrix]. That would have been a much better syntax than [item for sublist in nested_list for item in sublist]
better variable names improve comprehension
I love your teaching style. Very easy to follow. Thank you for all your hard work.
Your video helped me comprehend this concept. Thank you!
Looks good. I'm just now learning it but as far as I can tell it looks way better than the original code.
note that the implementation with generator that uses less memory, is slower overall
This is an absolutely excellent video. Your examples and explanations are always great. I think it is time for you to start working on a Python book. I am sure it will be a huge success. :)
Man... I love how clean this looks
Multi-conditional filtering is new to me but the if-else isn't too unusual since it's just the expression-if (ternary operator) making itself known
What a comprehensive guide.
nice synthesis. I'm using all of them(except multiple if condition, nice one).
I would add another dictionary comprehension that I use often, when i want to filter items or find items in a really big dictionary:
hay_dictionary = {"first": 1, "second": 2, "needle":4, "second_needle": 5, "last": 6, .................} a really big dictionary
{k:v for k, v in hay_dictionary.items() if "needle" in k}
this will return only the item that have in key "needle"
{"needle":4, "second_needle": 5}
I did not know sum() would store the internal value. That is very interesting.
You can apply sum(),max(),min(), len() and other functions as well
For number 1, it’s much easier just to write list(range(10)) or [*range(10]. Of course, this doesn’t allow for manipulation of the numbers in the range, but it’s still something to be aware of. Same type of thing goes for the conditional comprehension and the filter function.
Awesome tutorial and excellently explained.
Comprendre! Thanks Tim.
In "Comprehension with Multiple Conditions", if len(string) >=2 is not needed. The following will do
valid_strings = [option for option in options if option[0]=='a' and option[-1]=='y' ]
Another benefit is that variables don't leak out the way they do with for loops. Less of an issue if you're using underscores, but still.
This is the only way we populated list where I work.
Literly appending is I'll advised
Comprehension with multiple conditions
Yeah personally, these comprehensions would confuse the hell out of someone who's unfamiliar and probably would have understood the more verbose syntax easier.
Great one. Tnx 🥰. If you could please compare the perfomance using timeit module, it would be perfect.
regarding the check on string length (5:40):
string[slice(None, 1)] == 'a' and string[slice(None, -2, -1)] == 'y'
works so:
>>>valid_string = list(filter(lambda string: string[slice(None, 1)] == 'a' and string[slice(None, -2, -1)] == 'y', options))
takes care of business, buy may necessitate a code comment.
The nested list comprehension would be more readable to me if the syntax goes inside out. For example:
flattened = [num for num in row in array]
Hi Tim! Great stuff!! Do you use any Python's book to create this video? If so, could you please recommend us ?
Hi. Great video. Do you have a video that teaches you how to change the text color (scope) such as print, for, if statements in Sublime 3? Thanks
Thanks
I needed this kind of videos thx so much
And these are the best kind of tips 👌
my guy tim. cheers buddy
valid_strings = [option for option in options if option[0]!='a' and option[-1]!='y' ]
Brilliant!!!!!
Thanks, pretty edutaining stuff
I'm surprised that Tim didn't mention the time-performance benefits of using comprehensions.
Ah yeah!! Good stuff aahhhhhhhhh!! More baby boi !!!
Very well done. Thanks!
This is a great video but I've been having the issue of figuring out when I would use these in real life scenarios m it would be great if I had applicable examples
Thanks alot again
Great content, like always from you. Thanks Tim! Greetings from Poland 😊
Thanks a lot ❤
😊
[
x
for x in [[1,2],[3],[4,5]] if len(x) >1
for y in x if y % 2 == 0
]
So basically, sintactic sugar for reduce/map , got it.
Is there anything else among features of Python that is on the level of usefulness of comprehensions? I've been programming in Python for over 5 years now, and that's the only half-advanced feature of it that I'm using.
Oh, also tiny lambdas and context managers.
hey! curous about the last example where you do: sum(x**2 for x in range(10000000)) instead of sum([x**2 for x in range(10000000)]). I just tested it out, but I see that using the list comprehension is a bit faster to execute. Why is it that the execution time is slower for a more efficient approach using the generator?
The difference is about memory
Thanks 😊
tq bro.. I have learned lot. 🥺🥺
Welcome 😊
thank you
I might be crazy, but these comprehensions only make it harder to read code... IMO the oldschool multiline for loop is much more readable... xD
Thank god I am not the only one. Comprehensions are faster and low on memory. However, the readability is way less.
Hey tim, i was wondering if you had any videos on your channel that could help me with DSA in python. Do you have like a youtube playlist?
The have a paid course on algoexpert. But that's not for beginners. i have a year of experience. even that's was a little bit hard for me. but now i am smooth. mmmm it was great "i think".
even/odd. since if is the new goto (harmful), I select with:
{0: 'even', 1: 'odd'}[x % 2]
which is why devs hate me. Actually, I'd map the list to (2).__rmod__ and map that to dict.getitem.
i like to watch your video especially in coursecareer im trying to get a job with software engeneer
i would prefer to use this type lis=[i for i in a if i[0]=='a' and i[-1]=='y']
Can you teach us how to create a CMS for a website
Instead of [x for x in range(10)], one can simply use list(range(10)).
I don't get a generator for your last example:
>>> sub_of_squares = sum(x**2 for x in range(100))
>>> type(sub_of_squares)
This is generator:
sub_of_squares = (x**2 for x in range(100))
and you can use next(sub_of_squares)
And this is sum function that call generator instead create whole list
sub_of_squares = sum(x**2 for x in range(100))
A little heavy on the reverb, could use a tiny bit of bass boost to the voice as well.
Agree unfortunately my recording setup isn’t the best right now as I’m moving around
@@TechWithTim Great content thought...waiting for some Golang.....
i'm wondering is there a way to use dict comperhensions but not using a list of tuples?
can you make an efficient fibonacci program in a list (IDK HOW)
How does the example at &t6:30 work? you don't have to terminate login in []?
for first `values = list(range(10))` is better
nice
3D example would be more clear if you used different range values for each dimension.
Good point that was not the best example
why in 17:42 you got 16 on the first spot and the rest in order? I don't think that was supposed to happen
values = list(range(10))👀👀👀👀👀👀
Didn't even know this wizardry existed
Shouldn't at 5:59 the first condition be greater than or equals to 2 like you show after?
In the first group the unwanted options are being filtered out, (toss out anything too short), and in the comprehension he is selecting for those strings that match the requirements. Same end result but one test is the inverse.
You are right, thank you
Hi
c# does it so much getter
TIIIIMMMMM i copy the the script "strings that start with 'a" and end with "y" as it shows in the screen and when i run it give me 3 errors for every instance that you have "string" and asked me for "strings" and the code runned great, so I think you made 3 typos.
Check from your side, it might be you made the typo.
Keyboard name please.
I understand the intention… but I dont understand why you dont show the differences in execution time. If there is no difference its not worth it at the moment in my opinion.
It’s been pointed out in other comments that comprehensions are faster…. Someone suggested Time.perf_counter()
Programmers reading code efficiently (see what’s written, faster and more reliably) has value too.
I guess this is mostly about readability, the performance increase varies from version to version of python (just got a boost in 3.12, see mcoding's video)
Good day Tim. Your text is not visible, please find a way. Your lessons are good though...
Hmmm turn up your resolution
@@TechWithTim the red text is quite hard to see, especially when highlighted.
Text is perfectly fine, just find a way to read it 😉
All text colors look fine on this tablet. Adjust monitor, or try a different one.
Hi Tim,
I would enjoy watching just as much without the orange jiggy transitions… not needed IMO. (Overstimulated) Tx!
After posting that I also noticed that because we are learning to read code (as well) we’re watching REALLY closely…
Ummmm, use LISP…
is this pythonic?
Turn that frown upside down
Still waiting for a reason to need, never mind use python.
I preferred the more verbose code until I saw this video.
4:09 that isnt easier, nothing is clear
You're doing something as complicated as Comprehensions, but you use multiple If's instead of Boolean operators??? ROFL
chatGPT just killed all these tutorial videos....