clear_cache | clear cakephp caches with shell or within your app | Caching library
kandi X-RAY | clear_cache Summary
kandi X-RAY | clear_cache Summary
clear cakephp caches with shell or within your app, also includes debugkit panel to clean caches
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Trending Discussions on clear_cache
QUESTION
I run streamlit
script with a few caches.
When I use the following code it clears all the caches:
...ANSWER
Answered 2020-Mar-11 at 05:32This isn’t currently (easily) doable.
This is an optional solution that can be applied to some cases:
You can use the allow_output_mutation
option:
QUESTION
I sometimes have to write qmake pro file like this:
...ANSWER
Answered 2020-Mar-28 at 08:00qmake knowns about if/else: https://doc.qt.io/qt-5/qmake-language.html#scopes
QUESTION
I have a website running Django 2.0 on AWS ElasticBeanstalk. I have a couple views on my website that take some time to calculate, so I thought I'd look into some simple caching. I decided on LocMemCache because it looked like the quickest to set up that would meet my needs. (I'm using AWS, so using Memcached apparently requires ElastiCache, which adds cost and is additional setup overhead that I wanted to avoid.)
The views do not change often, and the site is not high-traffic, so I put long timeouts on the caches. There are three views where I have enabled caching:
- A report generated inside a template – uses Template Fragment caching
- A list of locations requested by AJAX and used in a JS library – uses per-view caching
- A dynamically-generated binary file download – uses per-view caching
The caching is set up and works great.
The data that goes into these views is added and edited by other staff at my company, that are used to their changes appearing immediately. So in order to address questions such as, "I updated this data, why has the webpage not updated?" I wanted to create a "Clear Server Cache" button, accessible by staff, to force a cache reset.
The button is set up and functioning. It requests a view that calls cache.clear()
from django.core.cache
. I used the sledgehammer cache.clear()
approach because the way to specify an individual per-view cache in code seems to be a bit clunky and convoluted, so the "clear it all" approach seemed adequate. And at the very least it should always "work" in the sense that all the data will get re-loaded again.
When I use the button to call cache.clear()
, it only clears the Template Fragment cache. It does not seem to clear the per-view caches. Why?
According to Django Documentation,
Be careful with this;
clear()
will remove everything from the cache, not just the keys set by your application.
So why is it not touching the per-view caches? Doesn't the warning seem to indicate that clear()
is dangerous specifically because it's a sledgehammer and nothing at all is spared? What am I missing?
Does AWS use some kind of special memory that's immune to this sort of culling? (If this is the case, then why are the Template Fragments successfully cleared?) I did notice (and find it interesting) that the cache remains even after deploying a new image to the same environment.
I could switch to using Database caching, but I'd like to understand why this isn't working so I don't need to abandon LocMemCache as an option to ever use in the future.
I could also move the others to use Template Fragment caching, but if I ever expand the caching to fit other needs, I will want to be able to use per-view caching. Also, this solution would be less than ideal for a binary-file-download view.
settings.py
...ANSWER
Answered 2020-Jan-13 at 22:36The problem is in the response headers. The cache_page
decorator automatically adds a max-age
option to the Cache-Control
header in the response. So the cache clear was working properly, clearing the local memory on the server, but the user's browser was instructed not to ask the server for updated data for the duration of the timeout. And my browser was happily complying (even after Ctrl-F5).
Fortunately, there are other decorators you can use to deal with this without much difficulty, now that it's clear what's happening. Django provides a number of other decorators, such as cache_control
or never_cache
.
I ended up using never_cache
, which turned the urls files into...
QUESTION
Upgrading from Rails 5.2.3 to 6.0.0 or 6.0.1, with Ruby 2.6.3, after bundling succeeds, the rails app:update
command has been carefully run, and webpacker updated, a request to any page that requires no authentication gives:
ANSWER
Answered 2019-Nov-21 at 18:37I have the exact same error and I have had no progress debugging it thus far. My suspicion is that it is caused by a gem but I just don't know yet.
@snowangel if you want to compare Gemfiles I've posted mine here: https://gist.github.com/biscuitvile/7bf0d4423ce0b2aa79e0ccc08bff4295
QUESTION
I want to execute the cap equivalent of
...ANSWER
Answered 2018-Sep-28 at 01:21I suggest that you should create a rake task for clearing cache and invoke them using capistrano hooks. For example:
lib/tasks/cache.rb
QUESTION
I have a Codeigniter 2.2 project. without no changing in the code my browser somehow holding cache for previous logged user. If i reload with clearing cache then it shows currently logged user.
I have added My_Output core controller. and added $this->output->clear_cache()
in the logout function. I have also added
ANSWER
Answered 2019-Sep-27 at 06:55You have to send the proper headers to the client.
QUESTION
I have some property methods in a Class and I want to clear the cache of this property at some point.
Example :
...ANSWER
Answered 2019-Apr-03 at 14:37You need to access the cache attributes on the getter attribute of the property object, so .fget
. You can only access the property object on the class:
QUESTION
Trying out the example in Section 5.9.2 Class monotonic_buffer_resource of the following article on Polymorphic Memory Resources by Pablo Halpern :
Doc No: N3816
Date: 2013-10-13
Author: Pablo Halpern
phalpern@halpernwightsoftware.com
Polymorphic Memory Resources - r1
(Originally N3525 – Polymorphic Allocators)
The article claims that :
The monotonic_buffer_resource class is designed for very fast memory allocations in situations where memory is used to build up a few objects and then is released all at once when those objects go out of scope.
and that :
A particularly good use for a monotonic_buffer_resource is to provide memory for a local variable of container or string type. For example, the following code concatenates two strings, looks for the word “hello” in the concatenated string, and then discards the concatenated string after the word is found or not found. The concatenated string is expected to be no more than 80 bytes long, so the code is optimized for these short strings using a small monotonic_buffer_resource [...]
I've benchmarked the example using the google benchmark library and boost.container 1.69's polymorphic resources, compiled and linked to release binaries with g++-8 on an Ubuntu 18.04 LTS hyper-v virtual machine with the following code :
...ANSWER
Answered 2019-Mar-07 at 07:54There is a combination of things that makes boost pmr::basic_string
slower:
- Construction of the
pmr::monotonic_buffer_resource
has some cost (17 nano-seconds here). pmr::basic_string::reserve
reserves more than one requires. It reserves 96 bytes in this case, which is more than the 80 bytes you have.- Reserving in
pmr::basic_string
is not free, even when the buffer is big enough (extra 8 nano-seconds here). - The concatenation of strings is costly (extra 64 ns here).
pmr::basic_string::find
has a suboptimal implementation. This is the real cost for the poor speed. In GCC'sstd::basic_string::find
uses__builtin_memchr
to find the first character that might match, which boost is doing it all in one big loop. Apparently this is the main cost, and what makes boost run slower than std.
So, after increasing the buffer, and comparing boost::container::string
with boost::container::pmr::string
, the pmr version comes slightly slower (293 ns vs.
276 ns). This is because new
and delete
are actually quite fast for such micro-benchmarks, and are faster than the complicated machinery of the pmr (just 17 ns for construction). In fact, the default Linux/gcc new/delete reuse the same pointer again and again. This optimization has a very simple and fast implementation, that also works great with the CPU cache.
As a proof, try this out (without optimization):
QUESTION
Tried to replicate this code using fastai lib, but I'm running in two major issues.
This par of code:
data_lm = TextLMDataBunch.from_df('data', train_df, valid_df, text_cols='idea')
Gives this kind of error:
...ANSWER
Answered 2019-Mar-04 at 10:14Well, your question was 2 months ago and the library went through a lot of changes since then. It seems to me that your first error is because you don't specify a column with labels, self.labels_cols is set to [0] and as a result, it is not in the index of your Dataframe. I believe this behaviour has changed since your post and that today, not specifying label_cols will work as intended.
Concerning your second issue, languague_model_learner used to be call differently before a refactor. Were you on the latest version of fastai when trying to use it. Feel free to test that again with the latest version of fastai and see if you get the same errors.
QUESTION
I have a working site on GAE, and in order to keep it that way I'm trying to add some unit tests.
One of the first things I'd like is a basic smoke test that confirms an authenticated user can load the home page. Here's my attempt:
...ANSWER
Answered 2019-Jan-14 at 19:21Your query User.query(User.user_email == active_email).fetch(1)
is eventually consistent, so the results of the put() may not show up immediately. Compounding this, you have self.policy = datastore_stub_util.PseudoRandomHRConsistencyPolicy(
probability=0)
which causes the datastore emulator to be very inconsistent. You probably want to consider changing your query to be strongly consistent or trying Cloud Firestore in Datastore mode.
For your test, you can set probability=1.0 to see if the problem is an eventually consistent query or not.
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Install clear_cache
PHP requires the Visual C runtime (CRT). The Microsoft Visual C++ Redistributable for Visual Studio 2019 is suitable for all these PHP versions, see visualstudio.microsoft.com. You MUST download the x86 CRT for PHP x86 builds and the x64 CRT for PHP x64 builds. The CRT installer supports the /quiet and /norestart command-line switches, so you can also script it.
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