kandi X-RAY | behave Summary
kandi X-RAY | behave Summary
BDD, Python style.
Top functions reviewed by kandi - BETA
- Run behave
- Load all keys
- Print formatters
- Returns an iterator over the available format items
- Build a command result
- Apply preprocessors to cmdargs
- Run the given command result
- A wrapper that wraps an async function in an async loop
- Create an async context
- Setup the installation path for the given bundle
- Returns a list of tuples that match the current value provider
- Format a summary summary
- Create ModelElements with tags
- Parse text
- Parse steps
- Update translations
- Write the result
- Convert Gherkin keywords to python module
- Create a package index
- Register a type
- Create a feature report
- Update gherkin language
- Monkey patch a given scenario
- Return a string describing the given exception
- Copy files
- Discover selected scenarios
behave Key Features
behave Examples and Code Snippets
arr = np.array() # with any dtype/value arr.fill(scalar) # is now identical to: arr = scalar
Trending Discussions on behave
ANSWERAnswered 2021-Jun-16 at 01:14
The difference in behaviour can be accounted for by this behaviour, described in (for instance) the following note in ECMAScript 2022 Language Specification sect
NOTE: If a VariableDeclaration is nested within a with statement and the BindingIdentifier in the VariableDeclaration is the same as a property name of the binding object of the with statement's object Environment Record, then step 5 will assign value to the property instead of assigning to the VariableEnvironment binding of the Identifier.
In the first case:
I have a peculiar situation where I need to allow for external definitions of functions, and use them in a test suite. PHP is odd in allowing you to define global functions anywhere, but it seems to behave inconsistently.
If I run this as a standalone script,
ANSWERAnswered 2021-Jun-15 at 11:35
The most reasonable explanation is that your code is not in global namespace. Like below
We are using stream ingestion from Event Hubs to Azure Data Explorer. The Documentation states the following:
The streaming ingestion operation completes in under 10 seconds, and your data is immediately available for query after completion.
I am also aware of the limitations such as
Streaming ingestion performance and capacity scales with increased VM and cluster sizes. The number of concurrent ingestion requests is limited to six per core. For example, for 16 core SKUs, such as D14 and L16, the maximal supported load is 96 concurrent ingestion requests. For two core SKUs, such as D11, the maximal supported load is 12 concurrent ingestion requests.
But we are currently experiencing ingestion latency of 5 minutes (as shown on the Azure Metrics) and see that data is actually available for quering 10 minutes after ingestion.
Our Dev Environment is the cheapest SKU Dev(No SLA)_Standard_D11_v2 but given that we only ingest ~5000 Events per day (per metric "Events Received") in this environment this latency is very high and not usable in the streaming scenario where we need to have the data available < 1 minute for queries.
Is this the latency we have to expect from the Dev Environment or are the any tweaks we can apply in order to achieve lower latency also in those environments? How will latency behave with a production environment loke Standard_D12_v2? Do we have to expect those high numbers there as well or is there a fundamental difference in behavior between Dev/test and Production Environments in this concern?...
ANSWERAnswered 2021-Jun-15 at 08:34
Did you follow the two steps needed to enable the streaming ingestion for the specific table, i.e. enabling streaming ingestion on the cluster and on the table?
In general, this is not expected, the Dev/Test cluster should exhibit the same behavior as the production cluster with the expected limitations around the size and scale of the operations, if you test it with a few events and see the same latency it means that something is wrong.
If you did follow these steps, and it still does not work please open a support ticket.
So if Event Dispatch Thread is a separate thread from the main thread, that makes me think the next code would output...
ANSWERAnswered 2021-Jun-14 at 14:28
It is a separate thread, you're just asking the current thread to invoke the code on the EDT and wait until it has been executed.
It's just like starting a thread explicitly:
I've been playing around with Eloquent for a while, but I met a case where Eloquent::where() is not working as I expected. I managed to get Collection::where() worked instead though. However, I'm still wondering why Eloquent::where() didn't work in my case. I will keep the problem as simple as I can, here it goes:
- I have Product and ProductCategory as many-to-many relationships and the pivot table name is "product_relate_category".
- Here is the relationship between them. It's still working so you can skip
ANSWERAnswered 2021-Jun-15 at 05:32
in your where in the query, you have used the column 'id' which is existed in the product_relate_category table and products table, so the database can't determine exactly what column you mean ... in this case you should write the full column name:
I'm developing internal messaging protocol that is based on TCP. Everything works, but I want to add tests to it.
It is possible to test serialization/deserialization with
MemoryStream, but I can't find a way to test this thing as whole - with contiguous message interchange, because
MemoryStream "ends" after reading first message.
The question: Is there a stream that behaves like
NetworkStream (duplex, ends only when other end closed, can't seek) in base library or any nuget package?
Currently I can start 2
TcpClients and use them, but I think it have too much overhead for tests especially when there's hundreds of tests running simultaneously
ANSWERAnswered 2021-Jun-15 at 05:30
This is what I've been looking for Nerdbank.Streams.FullDuplexStream
I don't really know where the error is, for me, it's still a mystery. But I'm using Laravel 8 to produce a project, it was working perfectly and randomly started to return this error and all projects started to return this error too. I believe it's something with Redis, as I'm using it to store the system cache. When I go to access my endpoint in postman it returns the following error:...
ANSWERAnswered 2021-Jun-12 at 01:50
Your problem is that you have set
SESSION_CONNECTION=session, but your
SESSION_DRIVER=default, so you have to use
SESSION_DRIVER=database in your
.env. See the
I know this question has been asked many times, but I still can't figure out what to do (more below).
I'm trying to spawn a new thread using
std::thread::spawn and then run an async loop inside of it.
The async function I want to run:...
ANSWERAnswered 2021-Jun-14 at 17:28
#[tokio::main] converts your function into the following:
In the following JCL, the HFS path /u/woodsmn/jjk does not exist. It raises a JCL error and does not run the COPYHFS step, nor any other steps. I want it to detect the missing file, and run the FAILIND step.
I suspect MVS raises a JCL error and completely ignores any COND conditions that might apply. I was hoping it raise some failure step condition code and behave that way.
How can I re-write this to execute steps when a PATH does not exist?...
ANSWERAnswered 2021-Jun-13 at 14:39
Use BPXBATCH to execute a shell command to test the existence of your directory.
There is a Java 11 (SpringBoot 2.5.1) application with simple workflow:
- Upload archives (as multipart files with size 50-100 Mb each)
- Unpack them in memory
- Send each unpacked file as a message to a queue via JMS
When I run the app locally
java -jar app.jar its memory usage (in VisualVM) looks like a saw: high peaks (~ 400 Mb) over a stable baseline (~ 100 Mb).
When I run the same app in a Docker container memory consumption grows up to 700 Mb and higher until an OutOfMemoryError. It appears that GC does not work at all. Even when memory options are present (
java -Xms400m -Xmx400m -jar app.jar) the container seems to completely ignore them still consuming much more memory.
So the behavior in the container and in OS are dramatically different.
I tried this Docker image in
DockerDesktop Windows 10 and in
OpenShift 4.6 and got two similar pictures for the memory usage.
ANSWERAnswered 2021-Jun-13 at 03:31
In Java 11, you can find out the flags that have been passed to the JVM and the "ergonomic" ones that have been set by the JVM by adding
-XX:+PrintCommandLineFlags to the JVM options.
That should tell you if the container you are using is overriding the flags you have given.
Having said that, its is (IMO) unlikely that the container is what is overriding the parameters.
It is not unusual for a JVM to use more memory that the
-Xmx option says. The explanation is that that option only controls the size of the Java heap. A JVM consumes a lot of memory that is not part of the Java heap; e.g. the executable and native libraries, the native heap, metaspace, off-heap memory allocations, stack frames, mapped files, and so on. Depending on your application, this could easily exceed 300MB.
Secondly, OOMEs are not necessarily caused by running out of heap space. Check what the "reason" string says.
Finally, this could be a difference in your app's memory utilization in a containerized environment versus when you run it locally.
No vulnerabilities reported
You can use behave 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.
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