random-scripts | Just some random scripts | Generator Utils library

 by   KenesuEXE Python Version: Current License: MIT

kandi X-RAY | random-scripts Summary

kandi X-RAY | random-scripts Summary

random-scripts is a Python library typically used in Generator, Generator Utils applications. random-scripts has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However random-scripts build file is not available. You can download it from GitHub.

Just some random scripts
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              random-scripts has a low active ecosystem.
              It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
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              It had no major release in the last 6 months.
              random-scripts has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of random-scripts is current.

            kandi-Quality Quality

              random-scripts has no bugs reported.

            kandi-Security Security

              random-scripts has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              random-scripts is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

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              random-scripts releases are not available. You will need to build from source code and install.
              random-scripts has no build file. You will be need to create the build yourself to build the component from source.

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            random-scripts Key Features

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            random-scripts Examples and Code Snippets

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            Community Discussions

            QUESTION

            How can I make an object with an interface like a random number generator, but that actually generates a specified sequence?
            Asked 2022-Mar-31 at 13:47

            I'd like to construct an object that works like a random number generator, but generates numbers in a specified sequence.

            ...

            ANSWER

            Answered 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.

            Source https://stackoverflow.com/questions/71655179

            QUESTION

            Translating async generator into sync one
            Asked 2022-Mar-23 at 02:39

            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:

            ...

            ANSWER

            Answered 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.

            Source https://stackoverflow.com/questions/71580727

            QUESTION

            Return generator instead of list from df.to_dict()
            Asked 2022-Feb-25 at 22:32

            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 orient option:

            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?

            ...

            ANSWER

            Answered 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:

            Source https://stackoverflow.com/questions/71272151

            QUESTION

            python call generator function from other function
            Asked 2022-Feb-19 at 16:06

            For the below code

            ...

            ANSWER

            Answered 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:

            Source https://stackoverflow.com/questions/71186546

            QUESTION

            Mixing yield and return. `yield [cand]; return` vs `return [[cand]]`. Why do they lead to different output?
            Asked 2022-Feb-17 at 20:53

            Why does

            ...

            ANSWER

            Answered 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:

            Source https://stackoverflow.com/questions/71164795

            QUESTION

            Python Ruler Sequence Generator
            Asked 2022-Jan-29 at 16:12

            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:

            ...

            ANSWER

            Answered 2022-Jan-28 at 18:43

            QUESTION

            Are generators with context managers an anti-pattern?
            Asked 2022-Jan-17 at 17:17

            I'm wondering about code like this:

            ...

            ANSWER

            Answered 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.

            Source https://stackoverflow.com/questions/70729329

            QUESTION

            Python: Generate a unique batch from given dataset
            Asked 2021-Nov-27 at 06:30

            I'm applying a CNN to classify a given dataset.

            My function:

            ...

            ANSWER

            Answered 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

            Source https://stackoverflow.com/questions/70114892

            QUESTION

            Can I get the current value of generator in JavaScript?
            Asked 2021-Nov-06 at 22:06

            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 button-green again.

            I know other techniques how to do it, I'm not asking for implementation advice. I made up this example to understand something about generators in JavaScript.

            Here's my code with generator:

            ...

            ANSWER

            Answered 2021-Nov-06 at 19:59

            JavaScript "native" APIs generally are willing to create new objects with wild abandon. Conserving memory is generally not, by any appearances, a fundamental goal of the language committee.

            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.

            Source https://stackoverflow.com/questions/69867197

            QUESTION

            Continue to other generators once a generator has been exhausted in a list of generators?
            Asked 2021-Oct-29 at 19:08

            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:

            ...

            ANSWER

            Answered 2021-Oct-29 at 19:08

            See Kaya's answer, it is much better.

            Source https://stackoverflow.com/questions/69748145

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install random-scripts

            You can download it from GitHub.
            You can use random-scripts like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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