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GitHub repository for sysadmin related solutions
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QUESTION
In C++20, we got the capability to sleep on atomic variables, waiting for their value to change.
We do so by using the std::atomic::wait method.
Unfortunately, while wait has been standardized, wait_for and wait_until are not. Meaning that we cannot sleep on an atomic variable with a timeout.
Sleeping on an atomic variable is anyway implemented behind the scenes with WaitOnAddress on Windows and the futex system call on Linux.
Working around the above problem (no way to sleep on an atomic variable with a timeout), I could pass the memory address of an std::atomic to WaitOnAddress on Windows and it will (kinda) work with no UB, as the function gets void* as a parameter, and it's valid to cast std::atomic to void*
On Linux, it is unclear whether it's ok to mix std::atomic with futex. futex gets either a uint32_t* or a int32_t* (depending which manual you read), and casting std::atomic to u/int* is UB. On the other hand, the manual says
The uaddr argument points to the futex word. On all platforms, futexes are four-byte integers that must be aligned on a four- byte boundary. The operation to perform on the futex is specified in the futex_op argument; val is a value whose meaning and purpose depends on futex_op.
Hinting that alignas(4) std::atomic should work, and it doesn't matter which integer type is it is as long as the type has the size of 4 bytes and the alignment of 4.
Also, I have seen many places where this trick of combining atomics and futexes is implemented, including boost and TBB.
So what is the best way to sleep on an atomic variable with a timeout in a non UB way? Do we have to implement our own atomic class with OS primitives to achieve it correctly?
(Solutions like mixing atomics and condition variables exist, but sub-optimal)
...ANSWER
Answered 2021-Jun-15 at 20:48You shouldn't necessarily have to implement a full custom atomic API, it should actually be safe to simply pull out a pointer to the underlying data from the atomic and pass it to the system.
Since std::atomic does not offer some equivalent of native_handle like other synchronization primitives offer, you're going to be stuck doing some implementation-specific hacks to try to get it to interface with the native API.
For the most part, it's reasonably safe to assume that first member of these types in implementations will be the same as the T type -- at least for integral values [1]. This is an assurance that will make it possible to extract out this value.
... and casting
std::atomictou/int*is UB
This isn't actually the case.
std::atomic is guaranteed by the standard to be Standard-Layout Type. One helpful but often esoteric properties of standard layout types is that it is safe to reinterpret_cast a T to a value or reference of the first sub-object (e.g. the first member of the std::atomic).
As long as we can guarantee that the std::atomic contains only the u/int as a member (or at least, as its first member), then it's completely safe to extract out the type in this manner:
QUESTION
I need to pass this:
...ANSWER
Answered 2021-Jun-15 at 19:49You can use simply intent.putExtra instead of worrying about which variant like put_____Extra to use.
When extracting the value, you can use intent.extras to get the Bundle and then you can use get() on the Bundle and cast to the appropriate type. This is easier than trying to figure out which intent.get____Extra function to use to extract it, since you will have to cast it anyway.
The below code works whether your data class is Serializeable or Parcelable. You don't need to use arrays, because ArrayLists themselves are Serializeable, but you do need to convert from MutableList to ArrayList.
QUESTION
I have found some similar questions to this. The problem is that none of those solutions work for me and some are too advanced. I'm trying to read the two JSON files and return the difference between them.
I want to be able to return the missing object from file2 and write it into file1.
These are both the JSON files
...ANSWER
Answered 2021-Jun-14 at 19:20with open("file1.json", "r") as f1:
file1 = json.loads(f1.read())
with open("file2.json", "r") as f2:
file2 = json.loads(f2.read())
for item in file2:
if item not in file1:
print(f"Found difference: {item}")
file1.append(item)
print(f"New file1: {file1}")
QUESTION
I saw some solutions that accessed the THREE.BoxGeometry faces like that:
...ANSWER
Answered 2021-Jun-15 at 17:54Try it like so:
QUESTION
I am trying to proxy requests from my containerized React application to my containerized Flask application.
I was starting the application using npm start (in Docker), and I did not have any issues proxying requests. However, I learned that npm start is not a good way to proceed in production.
Following the advice here: Run a React App in a Docker Container , I am able to start my containerized production React, but now the requests are not proxied.
Within the React app, all requests are handled with axios and are formatted: "/api/v1/endpoint". It seems that others have had issues between "http://localhost:80/api/v1/endpoint" and "/api/v1/endpoint". I do not believe this is my issue, unless it arises only in the production environment.
I have also tried changing my "proxy" address in package.json to the location of the dockerized flask container, and later to the name of the docker container, but I have not been able to make either solution work.
If anyone can provide guidance on launching a containerized, production React app that proxies requests to a backend container, please advise.
I am open to using a different server, if the procedures in "Run a React App in a Docker Container" need to be updated.
I have looked these solutions:
Proxy React requests to Flask app using Docker
...ANSWER
Answered 2021-Jun-15 at 16:20After digging around and trying a bunch of solutions, here is what worked:
1.) I changed my docker file to run an nginx server:
QUESTION
My dataframe looks something like these
...ANSWER
Answered 2021-Jun-15 at 13:55You can use duplicated and set keep=False in order to mark all duplicates as True.
QUESTION
I want to initialize a structure with an array of string without doing dynamic allocation. Is it possible? I had thought of something like this but it doesn't work:
...ANSWER
Answered 2021-Jun-15 at 13:52There are several variants possible, here two of them:
QUESTION
I am modeling a Time-constrained CVRP. The problem is to minimize the total travel time (not including the package dropping time) subject to vehicle (delivery) capacity and total time spent (per vehicle) constraints. The package dropping time refers to an additional time to be spent at each node, and the total time spent equals to the travel time plus this additional time. I have the below model that works for a single vehicle-type case. I would like to introduce two-vehicle type concept in there, meaning that I have a set of V1 type vehicles and another set of V2 type vehicles. The only difference of the vehicle-types is the per time cost of travel. Let x denote the per time unit cost of travel by V1, and y denote the per time unit travel cost of V2. How can I design the model so that it incorporates this additional aspect?
ANSWER
Answered 2021-Jun-13 at 13:34Simply register two transits callbacks (i.e. one per vehicle type)
Then use the overload of AddDimension() to pass an array of registered transit callback index.
QUESTION
I was wondering if i could return a Vec<&str> type from to_lowercase() below?
Here is my code:
...ANSWER
Answered 2021-Jun-15 at 11:42This is not possible. The reason is that converting a Unicode String to lowercase/uppercase may need to reallocate the String, as case folding within Unicode might need more/fewer characters and/or bytes to encode the folded variant.
Either you can return a Vec, where the new String holds the conversion. Or, if you are sure that your input is pure ASCII, you take use make_ascii_lowercase to do the conversion in-place; this has the downside that if proper Unicode folding requires more/less characters/bytes, no folding takes place.
QUESTION
I have a table with posts that can have multiple categories, and a table with categories that can have multiple posts. models.py:
...ANSWER
Answered 2021-Jun-15 at 11:16This might help you:
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