wordpress-theme-boilerplate | Funkhaus programming style guide and WordPress template | Generator Utils library
kandi X-RAY | wordpress-theme-boilerplate Summary
kandi X-RAY | wordpress-theme-boilerplate Summary
This is the Funkhaus programming style guide. The purpose of this style guide is to get you started in our Vuehaus system and to get you acquainted with our coding conventions, styles, and best practices. Also included are some tips for how to do some things that may not be immediately obvious when working with our stack.
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Community Discussions
Trending Discussions on Generator
QUESTION
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 00:47You 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.
QUESTION
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 02:39For 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.
QUESTION
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 22:32There 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:
QUESTION
For the below code
...ANSWER
Answered 2022-Feb-19 at 15:58The 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:
QUESTION
Why does
...ANSWER
Answered 2022-Feb-17 at 20:53In 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:
QUESTION
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 18:43How about itertools.repeat
?
QUESTION
I'm wondering about code like this:
...ANSWER
Answered 2022-Jan-17 at 14:48There 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.
QUESTION
I'm applying a CNN to classify a given dataset.
My function:
...ANSWER
Answered 2021-Nov-25 at 17:50As @jodag suggests, using DataLoaders is a good idea.
I have a snippet of that I use for some of my CNN in Pytorch
QUESTION
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 19:59JavaScript "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.
QUESTION
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 19:08See Kaya's answer, it is much better.
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The theme directory name should be something short and indicative of the client's name, with the year the theme was built. For example, bullitt2018, or storyattic2018. We do it this way so we can quickly tell how old a code base is, and easily build a new theme years later, and not worry about local caching of files.
Install Flywheel Local // Drew will fill this in
Open Flywheel Local and pull down the website you want.
Clone Vuehaus into the /ClientNamedWordpress/app/public/wp-content/themes folder you just pulled from Flywheel. Once you've done that, rename it using our naming convention of clientname2018.
cd into that folder and run npm install to get all the npm modules.
Run npm run dev to get the Vuehaus theme running.
On Flywheel, run the website by pressing the play button to get the Wordpress install running locally. Open http://clientname2018.local/wp-login or use the Flywheel ADMIN button to get to the Wordpress backend. Log in.
Navigate to Appearance -> Themes in the Wordpress dashboard and enable the clientname2018 theme you installed earlier and then it'll prompt you to install the required plugins that accompany Vuehaus. Install these plugins and activate them.
Set up your Wordpress view/page structure with the Nested Pages plugin and then replicate that structure in /ClientNamedWordpress/app/public/wp-content/themes/clientname2018/functions/router.php
Add all Advanced Custom Fields to the pages that you anticipate you'll need. This can take a bit of planning. You want to use ACF sparingly, but you also want to avoid putting data in places that they don't belong in for convenience.
Create a Vue view for each of the required pages in your application's structure in /ClientNamedWordpress/app/public/wp-content/themes/clientname2018/src/views
Set up your base styles including z-indexes.
Get your global components set up like your hamburger, header, menu, footer, cookie crumbs, social links, etc.
Flesh out your pages and componentize where you can.
Push up to Flywheel using the up cloud button on Flywheel Local. This will allow for live content to be added to the website. Once you push up using Flywheel be careful that you don't push up again because you'll override any content that was added. Use npm run deploy from that point on to update the logic, styling, and code content. If you want to use content from the live Flywheel site then copy your Vuehaus theme folder onto your Desktop and then pull from Flywheel and then put the theme back, overriding what you got from Flywheel. npm run deploy updates the theme, Flywheel pull and push updates everything, Wordpress, database, and theme.
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