kandi X-RAY | WeChatQRCode Summary
kandi X-RAY | WeChatQRCode Summary
⛄ Android scan code recognition library ported based on OpenCV open source WeChat QR code engine
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Trending Discussions on Generator
I'd like to construct an object that works like a random number generator, but generates numbers in a specified sequence....
ANSWERAnswered 2022-Mar-29 at 00:47
You can call
next() with a generator or iterator as an argument to withdraw exactly one element from it. Saving the generator to a variable beforehand allows you to do this multiple times.
Imagine we have an original API that returns a generator (it really is a mechanisms that brings pages/chunks of results from a server while the providing a simple generator to the user, and lets him iterate over these results one by one. For simplicity:...
ANSWERAnswered 2022-Mar-23 at 02:39
For the reason that asyncio is contagious, it's hard to write elegant code to integrate asyncio code into the old codes. For the scenario above, the flowing code is a little better, but I don't think it's elegant enough.
I am working on a large Pandas DataFrame which needs to be converted into dictionaries before being processed by another API.
The required dictionaries can be generated by calling the
.to_dict(orient='records') method. As stated in the docs, the returned value depends on the
Returns: dict, list or collections.abc.Mapping
Return a collections.abc.Mapping object representing the DataFrame. The resulting transformation depends on the orient parameter.
For my case, passing
orient='records', a list of dictionaries is returned. When dealing with lists, the complete memory required to store the list items, is reserved/allocated. As my dataframe can get rather large, this might lead to memory issues especially as the code might be executed on lower spec target systems.
I could certainly circumvent this issue by processing the dataframe chunk-wise and generate the list of dictionaries for each chunk which is then passed to the API. Furthermore, calling
iter(df.to_dict(orient='records')) would return the desired generator, but would not reduce the required memory footprint as the list is created intermediately.
Is there a way to directly return a generator expression from
df.to_dict(orient='records') instead of a list in order to reduce the memory footprint?
ANSWERAnswered 2022-Feb-25 at 22:32
There is not a way to get a generator directly from
to_dict(orient='records'). However, it is possible to modify the
to_dict source code to be a generator instead of returning a list comprehension:
For the below code...
ANSWERAnswered 2022-Feb-19 at 15:58
The problem is you call next on all values every time you call switchAction, since you define the dict over and over again. A solution to your problem can be as follows:
ANSWERAnswered 2022-Feb-17 at 20:53
In a generator function,
return just defines the value associated with the
StopIteration exception implicitly raised to indicate an iterator is exhausted. It's not produced during iteration, and most iterating constructs (e.g.
for loops) intentionally ignore the
StopIteration exception (it means the loop is over, you don't care if someone attached random garbage to a message that just means "we're done").
For example, try:
I have been struggling for a long time to figure how to define a generator function of a ruler sequence in Python, that follows the rules that the first number of the sequence (starting with 1) shows up once, the next two numbers will show up twice, next three numbers will show up three times, etc.
So what I am trying to get is 1, 2, 2, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 7 etc.
I understand that the way to do this is to have two separate count generators (itertools.count(1)) and then for every number in one generator yield number from the other generator:...
ANSWERAnswered 2022-Jan-28 at 18:43
I'm wondering about code like this:...
ANSWERAnswered 2022-Jan-17 at 14:48
There are two answers to your question :
- the absolutist : indeed, the context managers will not serve their role, the GC will have to clean the mess that should not have happened
- the pragmatic : true, but is it actually a problem ? Your file handle will get released a few milliseconds later, what's the bother ? Does it have a measurable impact on production, or is it just bikeshedding ?
I'm not an expert to Python alt implementations' differences (see this page for PyPy's example), but I posit that this lifetime problem will not occur in 99% of cases. If you happen to hit in prod, then yes, you should address it (either with your proposal, or a mix of generator with context manager) otherwise, why bother ? I mean it in a kind way : your point is strictly valid, but irrelevant to most cases.
I'm applying a CNN to classify a given dataset.
ANSWERAnswered 2021-Nov-25 at 17:50
As @jodag suggests, using DataLoaders is a good idea.
I have a snippet of that I use for some of my CNN in Pytorch
Let's say I want to rotate class names for my button on click. Clicked once becomes
button-green, twice -
button-yellow, thrice -
button-red. And then it repeats, so fourth click makes it
Here's my code with generator:...
ANSWERAnswered 2021-Nov-06 at 19:59
It would be quite simple to create a general facility to wrap the result of invoking a generator in an object that delegates the
.next() method to the actual result object, but also saves each returned value as a
.current() value (or whatever works for your application). Having a
.current() is useful, for such purposes as a lexical analyzer for a programming language. The basic generator API, however, does not make provisions for that.
I have a list of generators in a function
alternate_all(*args) that alternates between each generator in the list to print their first item, second item, ..., etc. until all generators are exhausted.
My code works until a generator is exhausted and once the StopIteration occurs, it stops printing, when I want it to continue with the rest of the generators and ignore the exhausted one:...
ANSWERAnswered 2021-Oct-29 at 19:08
See Kaya's answer, it is much better.
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