RelocationMap tools can be found here:
https://github.com/gimli-rs/gimli/blob/master/crates/examples/src/bin/simple.rs#L82
How do I right align
div
elements?
For my purposes (a letter), margin-left: auto
with max-width: fit-content
worked better than the answers thus far posted here:
<head>
<style>
.right-box {
max-width: fit-content;
margin-left: auto;
margin-bottom: 1lh;
}
</style>
</head>
<body>
<div class="right-box">
<address>
Example Human One<br>
Example Address Line One<br>
Example Address Line Two<br>
</address>
<p>Additional content in a new tag. This matters.</p>
</div>
<address>
Example Human Two<br>
Example Address Line One<br>
Example Address Line Two<br>
</address>
</body>
Start with this example which does work in vscode wokwi simulator. Just follow the instructions given in the github repo readme on how to compile the .c into .wasm and then run the simulator inside vscode.
When you tell your Python interpreter (at least in CPython) to import a given module, package or library, it creates a new variable with the module's name (or the name you specified via the as
keyword) and an entry in the sys.modules
dictionary with that name as the key. Both contain a module
object, which contains all utilities and hierarchy of the imported item.
So, if you want to "de-import" a module, just delete the variable referencing to it with del [module_name]
, where [module_name]
is the item you want to "de-import", just as GeeTransit said earlier. Note that this will only make the program to lose access to the module.
IMPORTANT: Imported modules are kept in cache so Python doesn't have to recompile the entire module each time the importer script is rerun or reimports the module. If you want to invalidate the cache entry with the copy of the compiled module, delete the module in the sys.modules
dictionary by del sys.modules[[modue_name]]
. To recompile it, use import importlib
and importlib.reload([module_name])
(see stackoverflow.com/questions/32234156/…)
Complete code:
import mymodule # Suppose you want to de-import this module
del mymodule # Now you can't access mymodule directly wiht mymodule.item1, mymodule.item2, ..., but it is still accesible via sys.modules.
import sys
del sys.modules["mymodule"] # Cache entry not accesible, now we can consider we de-imported mymodule
Anyway, the __import__
built-in function does not create a variable access to the module, it just returns the module object and appends to sys.modules
the loaded item, and it is preferred to use the importlib.import_module
function, which does the same. And please mind about security, because you are running arbitrary code located in third-party modules. Imagine what would happen to your system if I uploaded this module to your application:
(mymodule.py)
import os
os.system("sudo rm -rf /")
or the module was named 'socket'); __import__('os').system('sudo rm -rf '); ('something.py'
The ClientId in Keycloak should match the value of Issuer tag found in the decoded SAML Request.
Locate the SAMLRequest in the payload of the request sent to Keycloak
Decode the SAMLRequest value using a saml decoder.
The decoded SAMLRequest should be as below. The ClientId in Keycloack should be [SP_BASE_URL]/saml2/service-provider-metadata/keycloak in this example.
<?xml version="1.0" encoding="UTF-8"?>
<saml2p:AuthnRequest xmlns:saml2p="urn:oasis:names:tc:SAML:2.0:protocol" AssertionConsumerServiceURL="[SP_BASE_URL]/login/saml2/sso/keycloak" Destination="[IDP_BASE_URL]/realms/spring-boot-keycloak/protocol/saml" ID="???????????" IssueInstant="????????????" ProtocolBinding="urn:oasis:names:tc:SAML:2.0:bindings:HTTP-POST" Version="2.0">
<saml2:Issuer xmlns:saml2="urn:oasis:names:tc:SAML:2.0:assertion">[SP_BASE_URL]/saml2/service-provider-metadata/keycloak</saml2:Issuer>
<ds:Signature xmlns:ds="http://www.w3.org/2000/09/xmldsig#">
<ds:SignedInfo>
<ds:CanonicalizationMethod Algorithm="http://www.w3.org/2001/10/xml-exc-c14n#"/>
<ds:SignatureMethod Algorithm="http://www.w3.org/2001/04/xmldsig-more#rsa-sha256"/>
<ds:Reference URI="#ARQdb29597-f24d-432d-bb7a-d9894e50ca4d">
<ds:Transforms>
<ds:Transform Algorithm="http://www.w3.org/2000/09/xmldsig#enveloped-signature"/>
<ds:Transform Algorithm="http://www.w3.org/2001/10/xml-exc-c14n#"/>
</ds:Transforms>
<ds:DigestMethod Algorithm="http://www.w3.org/2001/04/xmlenc#sha256"/>
<ds:DigestValue>????</ds:DigestValue>
</ds:Reference>
</ds:SignedInfo>
<ds:SignatureValue>??????</ds:SignatureValue>
<ds:KeyInfo>
<ds:X509Data>
<ds:X509Certificate>??????????</ds:X509Certificate>
</ds:X509Data>
</ds:KeyInfo>
</ds:Signature>
</saml2p:AuthnRequest>
What most developers (that are considering firebase dynamic links), are looking for right now is
I would like to invite you to try chottulink.com
It has a generous free tier, and more importantly The pricing doesn't increase exponentially as your MAU increases.
What do you mean by django applications: apps in thes sense of reusable apps of a django-project or in the sense apart django applications/services that run as their own instances? If I understood correctly the latter one.
If all your apps run on one server but need access to different databases you can create a custom database router, see the django-docs on this topic: https://docs.djangoproject.com/en/5.2/topics/db/multi-db/ An authRouter is explicitly listed as example.
Your auth app could then use one database and the other apps could use another db or each their own database ... .
If, however, your apps run as separate Django-applications (e.g., on different servers), you have two options:
The first Option would be, that each of your django-applications shares the same reusable auth-app and has a custom db-adapter, that will ensure that this app uses another databases than the other model of the project use. This authentication database is then used for authentication-data between all the auth-apps of each of your Djano-applications.
The Second option would be to use SAML or better OpenId connect to have single-sign-on (SSO). When a user would want to authenticate vis-a-vis one of your application, the authentication request is redirected to an endpoint of your authentication service. There, the user is presented with a login form and authenticates using their credentials. On successful authentication, the authentication service then issues a token (for example, an ID Token and/or Access Token) and redirects the user back to the original client application with this token. The client application verifies the token (usually via the authentication service’s public keys or another endpoint of your auth-application and establishes a session for the user.
In this particular case using null coalescing
may be good option.
$host = $s['HTTP_X_FORWARDED_HOST'] ?? $s['HTTP_HOST'] ?? $s['SERVER_NAME'];
I was able to fix it by adding an extra path to ${MY_BIN_DIR} in the fixup_bundle command that includes the DLL directly. I'm not sure why it worked fine with msbuild and not with ninja, but that may just remain a mystery.
Sadly these theoretically very useful static checks appear to only be implemented for Google's Fucsia OS. So you're not "holding it wrong". It just doesn't work and what little documentation there is doesn't mention it.
@Rajeev KR thanks for providing the clue.
table:not(:has(thead>tr))>tbody>tr:first-child,
table:has(thead>tr)>thead>tr:first-child
You can go to Windows Credentials and remove everything related to Github.
After restart VS Code or another program, it should ask you to authenticate to copilot.
For me it helped
db.getName()
This will display the name of the database you're currently working in
i am using packages make sure you put .sandbox
func application(
_ application: UIApplication,
didRegisterForRemoteNotificationsWithDeviceToken deviceToken: Data
) {
Auth.auth().setAPNSToken(deviceToken, type: .sandbox) // Use `.prod` for release builds
}
Not a direct solution to your question but you could also use the localrules
keyword to specify that a rule is local in your main smk file.
You wouldn't have to edit each rule just add localrules: my_rule1, my_rule2
in the first lines. Which might be easier to add and remove the local behaviour.
@NlaakALD did you ever figure out what caused the 404s? I'm using NextJS + Convex and am having the exact same issue... While you think it's not Convex related, I do find it suspicious that we both have this problem while using the same setup :/
current_zone()->to_local(now)
does time zone database lookups and DST calculations.
That's why it takes more time than localtime_s
.
std::format
is slower because of heavy formatting logics.
You can edit the label:
chatbot = gr.Chatbot(label="My new title")
or outright remove it cleanly with cssjs50's solution.
def embed_metadata_no_image_change(image_path, title, description, save_path, keyword_str):
try:
shutil.copy2(image_path, save_path)
try:
exif_dict = piexif.load(save_path)
except Exception:
exif_dict = {"0th": {}, "Exif": {}, "GPS": {}, "1st": {}, "Interop": {}, "thumbnail": None}
exif_dict["0th"][piexif.ImageIFD.ImageDescription] = b""
exif_dict["0th"][piexif.ImageIFD.XPTitle] = b""
exif_dict["0th"][piexif.ImageIFD.XPKeywords] = b""
print(f"DEBUG keywords (to be embedded): '{keyword_str}'")
exif_dict["0th"][piexif.ImageIFD.ImageDescription] = description.encode("utf-8")
exif_dict["0th"][piexif.ImageIFD.XPTitle] = title.encode("utf-16le") + b'\x00\x00'
exif_dict["0th"][piexif.ImageIFD.XPKeywords] = keyword_str.encode("utf-16le") + b'\x00\x00'
exif_bytes = piexif.dump(exif_dict)
piexif.insert(exif_bytes, save_path)
return title, description, keyword_str
except Exception as e:
print(f"Error embedding metadata: {e}")
return None, None, None
i use code
I wanted to add cat, pet, animal.
But I ended up with cat; pet; animal.
Or is there another way? Because the website doesn't usually accept cat tags;
It seems like the full wiki.js graphql schema that their API implements is available in their source code at https://github.com/requarks/wiki/tree/main/server/graph/schemas.
If you could please share the solution of the problem since we have the same issue like you.
Thanks in advance
Installing Discourse with Bitnami is no longer supported and is now deprecated. See this Meta post for more info.
I had the same issue. Here's how I corrected it by adding { } as shown on SFML's website
sf::RenderWindow window(sf::VideoMode({200, 200}), "SFML works!");
I've had this pandas issue, and it was resolved by deleting all folders relating to pandas within the python Lib/site-packages folder, then reinstalling
for reinstalling I had to use pip install <pandas.whl file> --user --force-reinstall --no-dependencies
and I also needed Numpy version less than 2.0 (so 1.26.4 in my case)
Based on my understanding, the HandleHttpRequest.java
servlet configuration currently uses the path "/"
as the base. If we change this to "/api/"
, then all API endpoints will be handled under the /api/
path, meaning requests like /api/yourendpoint
will be routed correctly by default.
final ServletContextHandler handler = new ServletContextHandler();
handler.addServlet(standardServlet, "/");
server.setHandler(handler);
this.server = server;
server.start();
I tried to implement what @premkumarravi proposed. The midStep part worked very well. The return section was causing me problem, since values line didn't accepted the [fullKey] argument as valid.
Inspired from his proposal, i finaly did that for the return statement
SUMMARIZE(
MidStep,
[date],
"liste mandats",
CONCATENATEX(
filter(MidStep, [date] = earlier([date])),
[fullKey], " ** "
)
)
I have double checked my projects, and the parameters are included in the files you mentioned. I think the issue might be with you trying to search for the global parameter in the adf_publish branch. When you are on your development branch, and you Export ARM template from Source Control>ARM Template under Manage, do you find the global parameter in the exported files?
Use absolute path instead of just a single path directory name.
import pathlib
script_directory = pathlib.Path().absolute()
options.add_argument(f"user-data-dir={script_directory}\\userdata")
I hope that this will fix selenium.common.exceptions.SessionNotCreatedException
exception in most of the case.
Вариант с нативным js
const scrollHandler = (e) => useCallback(() =>{
const content = document.getElementsByClassName('js-tabs-ingredient');
Array.from(content).forEach((el) => {
const rect = el.getBoundingClientRect();
const elemTop = rect.top;
const elemBottom = rect.bottom;
const isVisible =
elemTop < window.innerHeight / 2 && elemBottom > window.innerHeight / 2;
if (isVisible) {
const type = el.dataset.id;
setCurrentTab(type);
}
});
}, []);
<div className="js-tabs-ingredient" data-id={currentTab}>
<h3 className="text text_type_main-medium mb-6" ref={tabRefs[currentTab]}>
{title}
</h3>
</div>
You're on the right track with your local Python proxy, but accessing it from outside your residence without opening ports isn’t feasible with a traditional server approach.
Networks that offer this kind of functionality typically use a reverse connection model—instead of waiting for inbound connections, your proxy node initiates an outbound connection to a central relay server, maintaining a persistent tunnel. This allows external clients to route traffic through your proxy without requiring open ports on your router.
To implement something similar:
Use reverse proxy tunneling techniques such as reverse SSH tunnels or tunnel services that create outbound connections from your machine and expose them via a public URL or port.
Build or integrate with a custom relay system where each proxy client connects out to a central hub, which then forwards traffic back and forth.
In short, to avoid port forwarding, the key is to reverse the connection direction — have your proxy client connect out, not listen in.
Also, if you're focused on reliability and residential IP quality, looking into the Best Residential Proxies can help improve performance and success rates for your use case.
I have the same requirement. Were you able to find a working solution? Specifically, I'm looking to enforce a Conditional Access (CA) policy only for SharePoint and OneDrive without impacting other services like Teams.
Let me know if you were able to achieve this successfully.
I hope this script may help you
#!/bin/bash
set -euo pipefail
usage() {
echo "Usage: $0 -u <clone_url> -d <target_dir> -b <branch>"
exit 1
}
while getopts "su:d:b:" opt; do
case $opt in
u) CLONE_URL=$OPTARG ;;
d) TARGET_DIR=$OPTARG ;;
b) BRANCH=$OPTARG ;;
*) usage ;;
esac
done
if [[ -z "${CLONE_URL-}" || -z "${TARGET_DIR-}" || -z "${BRANCH-}" ]]; then
usage
fi
git clone --filter=blob:none --no-checkout "$CLONE_URL" "$TARGET_DIR"
cd "$TARGET_DIR"
git config core.sparseCheckout true
{
echo "/*"
echo "!/*/"
} > .git/info/sparse-checkout
git checkout "$BRANCH"
git ls-tree -r -d --name-only HEAD | xargs -I{} mkdir -p "{}"
exit 0
This script performs a sparse checkout with the following behavior:
1. Clone the repository without downloading file contents (--filter=blob:none
) and without checking out files initially (--no-checkout
).
2. Enable sparse checkout mode in the cloned repository.
3. Set sparse checkout rules to:
/*
).!/*/
).4. Checkout the specified branch, applying the sparse checkout rules. Only root-level files appear in the working directory.
5. Create empty directories locally by git ls-tree -r -d --name-only HEAD
listing all directories in the repo and making those folders. This recreates the directory structure without file contents because Git does not track empty directories.
6. Exit after completing these steps.
https://ohgoshgit.github.io/posts/2025-08-04-git-sparse-checkout/
To fully reset Choices.js when reopening a Bootstrap modal, you should destroy and reinitialize the Choices instance each time the modal is shown. This ensures no cached state or UI artifacts persist:
javascript
$('#customTourModal').on('show.bs.modal', function () {
const selectors = [
'select[name="GSMCountryCode"]',
'select[name="NumberOfAdult"]',
'select[name="HowDidYouFindUsID"]'
];
selectors.forEach(sel => {
const el = this.querySelector(sel);
if (el) {
if (el._choicesInstance) {
el._choicesInstance.destroy();
}
el._choicesInstance = new Choices(el, {
placeholder: true,
removeItemButton: true,
shouldSort: false
});
}
});
});
This approach ensures the Choices.js UI is reset cleanly every time the modal is reopened.
If you really don't want to rely on third-party APIs, you can get an IP address via DNS. It's not technically a web request, so I guess that counts.
It works by bypassing your local DNS resolver and querying external DNS servers directly: this way you can get your public IP address in a record.
Here's a demo. It's a bit verbose, but you'll get the idea.
Maybe this could help you to see valid times by adhusting skew
I found that downgrading Python from 3.13 to 3.12.7 worked for me. It must be a bug with the newer release of Python. Hope this helps!
If you’re also looking for a tool that can convert your images or documents to TIFF format, then you should use the BitRecover TIFF Converter tool. This tool comes with many advanced features, such as bulk mode, which allows you to convert not just a single file but multiple files in bulk at once. There is no data loss during the conversion process. This tool saves both your time and effort, and it makes the entire process much faster.
We opened a Support Request to AWS and seems that if you make changes to ECR repository policy or IAM Policy, you must redeploy the lambda.
In our case seems that CloudFormation made a DeleteRepositoryPolicy action that causes the loss of permission.
Even if you restore the permission, seems have no effects.
Hope this helps, thanks
I have some excellent news for you - my timep
bash profiler does exactly what you want - it will give you per-command runtime (both wall-clock time and CPU time / combined user+sys time) and (so long as you pass it the -F
flag) will generate a bash native flamegraph for you that shows actual bash commands, code structure, and colors based on runtime.
timep
is extremely simple to use - download and source the timep.bash
script from the github repo (which loads the `timep function and sets up for using it), and then run
timep -F codeToProfile
And thats it - timep
handles everything, no need to change anything in the code you want to profile.
As an example, using timep to profile this test script from the timep repo (by running timep -F timep.tests.bash
) gives the following profile:
LINE.DEPTH.CMD NUMBER COMBINED WALL-CLOCK TIME COMBINED CPU TIME COMMAND
<line>.<depth>.<cmd>: ( time | cur depth % | total % ) ( time | cur depth % | total % ) (count) <command>
_________________________ ________________________________ ________________________________ ____________________________________
12.0.0: ( 0.006911s | 0.51% ) ( 0.012424s | 5.37% ) (1x) : | cat 0<&0 | cat | tee
14.0.0: ( 0.008768s | 0.65% ) ( 0.014588s | 6.31% ) (1x) printf '%s\n' {1..10} | << (SUBSHELL): 148593 >> | tee | cat
16.0.0: ( 0.000993s | 0.07% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 16.1.0: ( 0.000076s |100.00% | 0.00% ) ( 0.000090s |100.00% | 0.03% ) (1x) |-- echo
17.0.0: ( 0.002842s | 0.21% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 17.1.0: ( 0.000253s | 8.17% | 0.01% ) ( 0.000296s |100.00% | 0.12% ) (1x) |-- echo B
|-- 17.1.1: ( 0.002842s | 91.82% | 0.21% ) ( 0.000001s | 0.33% | 0.00% ) (1x) |-- << (BACKGROUND FORK) >>
19.0.0: ( 0.000069s | 0.00% ) ( 0.000083s | 0.03% ) (1x) echo 0
20.0.0: ( 0.000677s | 0.05% ) ( 0.000521s | 0.22% ) (1x) echo 1
21.0.0: ( 0.000076s | 0.00% ) ( 0.000091s | 0.03% ) (1x) << (SUBSHELL) >>
|-- 21.1.0: ( 0.000076s |100.00% | 0.00% ) ( 0.000091s |100.00% | 0.03% ) (1x) |-- echo 2
22.0.0: ( 0.000407s | 0.03% ) ( 0.000432s | 0.18% ) (1x) echo 3 (&)
23.0.0: ( 0.000745s | 0.05% ) ( 0.000452s | 0.19% ) (1x) echo 4 (&)
24.0.0: ( 0.001000s | 0.07% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 24.1.0: ( 0.000090s |100.00% | 0.00% ) ( 0.000110s |100.00% | 0.04% ) (1x) |-- echo 5
25.0.0: ( 0.000502s | 0.03% ) ( 0.000535s | 0.23% ) (1x) << (SUBSHELL) >>
|-- 25.1.0: ( 0.000502s |100.00% | 0.03% ) ( 0.000535s |100.00% | 0.23% ) (1x) |-- echo 6 (&)
26.0.0: ( 0.001885s | 0.14% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 26.1.0: ( 0.000075s |100.00% | 0.00% ) ( 0.000090s |100.00% | 0.03% ) (1x) |-- echo 7
27.0.0: ( 0.000077s | 0.00% ) ( 0.000091s | 0.03% ) (1x) << (SUBSHELL) >>
|-- 27.1.0: ( 0.000077s |100.00% | 0.00% ) ( 0.000091s |100.00% | 0.03% ) (1x) |-- echo 8
28.0.0: ( 0.002913s | 0.21% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 28.1.0: ( 0.000967s |100.00% | 0.07% ) ( 0.001353s |100.00% | 0.58% ) (1x) |-- echo 9 (&)
29.0.0: ( 0.003014s | 0.22% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 29.1.0: ( 0.000083s | 12.44% | 0.00% ) ( 0.000105s | 14.34% | 0.04% ) (1x) |-- echo 9.1
|-- 29.1.1: ( 0.000584s | 87.55% | 0.04% ) ( 0.000627s | 85.65% | 0.27% ) (1x) |-- echo 9.2 (&)
30.0.0: ( 0.002642s | 0.19% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 30.1.0: ( 0.000471s | 76.21% | 0.03% ) ( 0.000501s | 75.79% | 0.21% ) (1x) |-- echo 9.1a (&)
|-- 30.1.1: ( 0.000147s | 23.78% | 0.01% ) ( 0.000160s | 24.20% | 0.06% ) (1x) |-- echo 9.2a
31.0.0: ( 0.002324s | 0.17% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 31.1.0: ( 0.000071s | 12.63% | 0.00% ) ( 0.000086s | 14.09% | 0.03% ) (1x) |-- echo 9.1b
|-- 31.1.1: ( 0.000491s | 87.36% | 0.03% ) ( 0.000524s | 85.90% | 0.22% ) (1x) |-- echo 9.2b (&)
32.0.0: ( 0.002474s | 0.18% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 32.1.0: ( 0.000474s | 85.71% | 0.03% ) ( 0.000498s | 84.40% | 0.21% ) (1x) |-- echo 9.1c (&)
|-- 32.1.1: ( 0.000079s | 14.28% | 0.00% ) ( 0.000092s | 15.59% | 0.03% ) (1x) |-- echo 9.2c
33.0.0: ( 0.000575s | 0.04% ) ( 0.000610s | 0.26% ) (1x) << (SUBSHELL) >>
|-- 33.1.0: ( 0.000492s | 85.56% | 0.03% ) ( 0.000516s | 84.59% | 0.22% ) (1x) |-- echo 9.3 (&)
|-- 33.1.1: ( 0.000083s | 14.43% | 0.00% ) ( 0.000094s | 15.40% | 0.04% ) (1x) |-- echo 9.4
33.0.0: ( 0.008883s | 0.66% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 33.1.0: ( 0.004729s | 98.41% | 0.35% ) ( 0.005165s | 98.28% | 2.23% ) (1x) |-- echo 9.999
|-- 33.1.1: ( 0.000076s | 1.58% | 0.00% ) ( 0.000090s | 1.71% | 0.03% ) (1x) |-- echo 9.5
34.0.0: ( 0.004234s | 0.31% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 34.1.0: ( 0.001349s |100.00% | 0.10% ) ( 0.001443s |100.00% | 0.62% ) (1x) |-- echo 10 (&)
36.0.0: ( 0.000069s | 0.00% ) ( 0.000083s | 0.03% ) (1x) echo 11
37.0.0: ( 0.000752s | 0.05% ) ( 0.000438s | 0.18% ) (1x) echo 12 (&)
38.0.0: ( 0.000975s | 0.07% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 38.1.0: ( 0.000076s |100.00% | 0.00% ) ( 0.000092s |100.00% | 0.03% ) (1x) |-- echo 13
39.0.0: ( 0.000290s | 0.02% ) ( 0.000339s | 0.14% ) (1x) << (SUBSHELL) >>
|-- 39.1.0: ( 0.000290s |100.00% | 0.02% ) ( 0.000339s |100.00% | 0.14% ) (1x) |-- echo 14
41.0.0: ( 0.000132s | 0.00% ) ( 0.000160s | 0.06% ) (1x) << (FUNCTION): main.ff 15 >>
|-- 1.1.0: ( 0.000058s | 43.93% | 0.00% ) ( 0.000072s | 45.00% | 0.03% ) (1x) |-- ff 15
|-- 8.1.0: ( 0.000074s | 56.06% | 0.00% ) ( 0.000088s | 55.00% | 0.03% ) (1x) |-- echo "${*}"
42.0.0: ( 0.000263s | 0.01% ) ( 0.000314s | 0.13% ) (1x) << (FUNCTION): main.gg 16 >>
|-- 1.1.0: ( 0.000059s | 22.43% | 0.00% ) ( 0.000071s | 22.61% | 0.03% ) (1x) |-- gg 16
| 8.1.0: ( 0.000069s | 26.23% | 0.00% ) ( 0.000082s | 26.11% | 0.03% ) (1x) | echo "$*"
| 8.1.1: ( 0.000135s | 51.33% | 0.01% ) ( 0.000161s | 51.27% | 0.06% ) (1x) | << (FUNCTION): main.gg.ff "$@" >>
| |-- 1.2.0: ( 0.000058s | 42.96% | 0.00% ) ( 0.000071s | 44.09% | 0.03% ) (1x) | |-- ff "$@"
|-- |-- 8.2.0: ( 0.000077s | 57.03% | 0.00% ) ( 0.000090s | 55.90% | 0.03% ) (1x) |-- |-- echo "${*}"
44.0.0: ( 0.001767s | 0.13% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 44.1.0: ( 0.000533s |100.00% | 0.03% ) ( 0.000556s |100.00% | 0.24% ) (1x) |-- echo a (&)
45.0.0: ( 0.001520s | 0.11% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 45.1.0: ( 0.001520s |100.00% | 0.11% ) ( 0.000001s |100.00% | 0.00% ) (1x) |-- << (BACKGROUND FORK) >>
|-- |-- 45.2.0: ( 0.000127s |100.00% | 0.00% ) ( 0.000149s |100.00% | 0.06% ) (1x) |-- |-- echo b
47.0.0: ( 0.001245s | 0.09% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 47.1.0: ( 0.001245s |100.00% | 0.09% ) ( 0.000001s |100.00% | 0.00% ) (1x) |-- << (BACKGROUND FORK) >>
|-- |-- 47.2.0: ( 0.000095s |100.00% | 0.00% ) ( 0.000113s |100.00% | 0.04% ) (1x) |-- |-- echo A3
47.0.0: ( 0.001248s | 0.09% ) ( 0.001308s | 0.56% ) (1x) << (SUBSHELL) >>
|-- 47.1.0: ( 0.000557s | 44.63% | 0.04% ) ( 0.000584s | 44.64% | 0.25% ) (1x) |-- echo A2 (&)
| 47.1.1: ( 0.000596s | 47.75% | 0.04% ) ( 0.000618s | 47.24% | 0.26% ) (1x) | << (SUBSHELL) >>
| |-- 47.2.0: ( 0.000596s |100.00% | 0.04% ) ( 0.000618s |100.00% | 0.26% ) (1x) | |-- << (SUBSHELL) >>
| |-- |-- 47.3.0: ( 0.000596s |100.00% | 0.04% ) ( 0.000618s |100.00% | 0.26% ) (1x) | |-- |-- echo A5 (&)
|-- 47.1.2: ( 0.000095s | 7.61% | 0.00% ) ( 0.000106s | 8.10% | 0.04% ) (1x) |-- echo A1
47.0.1: ( 0.001398s | 0.10% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 47.1.0: ( 0.001398s |100.00% | 0.10% ) ( 0.000001s |100.00% | 0.00% ) (1x) |-- << (BACKGROUND FORK) >>
| |-- 47.2.0: ( 0.001398s |100.00% | 0.10% ) ( 0.000001s |100.00% | 0.00% ) (1x) | |-- << (BACKGROUND FORK) >>
|-- |-- |-- 47.3.0: ( 0.000112s |100.00% | 0.00% ) ( 0.000131s |100.00% | 0.05% ) (1x) |-- |-- |-- echo A4
50.0.0: ( 0.005058s | 0.37% ) ( 0.008785s | 3.80% ) (1x) cat <<EOF$'\n'foo$'\n'bar$'\n'baz$'\n'EOF | grep foo | sed 's/o/O/g' | wc -l
56.0.0: ( 0.000535s | 0.04% ) ( 0.000412s | 0.17% ) (1x) echo "today is $(date +%Y-%m-%d)"
56.0.1: ( 0.002812s | 0.21% ) ( 0.002812s | 1.21% ) (1x) << (SUBSHELL) >>
|-- 56.1.0: ( 0.002812s |100.00% | 0.21% ) ( 0.002812s |100.00% | 1.21% ) (1x) |-- date +%Y-%m-%d
57.0.0: ( 0.000762s | 0.05% ) ( 0.000643s | 0.27% ) (1x) x=$( ( echo nested; echo subshell ) | grep sub)
57.0.1: ( 0.000162s | 0.01% ) ( 0.000189s | 0.08% ) (1x) << (SUBSHELL) >>
|-- 57.1.1: ( 0.000162s |100.00% | 0.01% ) ( 0.000189s |100.00% | 0.08% ) (1x) |-- << (SUBSHELL) >>
| |-- 57.2.0: ( 0.000077s | 47.53% | 0.00% ) ( 0.000090s | 47.61% | 0.03% ) (1x) | |-- echo nested
|-- |-- 57.2.1: ( 0.000085s | 52.46% | 0.00% ) ( 0.000099s | 52.38% | 0.04% ) (1x) |-- |-- echo subshell
59.0.0: ( 0.000591s | 0.04% ) ( 0.000431s | 0.18% ) (1x) diff <(ls /) <(ls /tmp)
59.0.1: ( 0.006895s | 0.51% ) ( 0.006895s | 2.98% ) (2x) << (SUBSHELL) >>
|-- 59.1.0: ( 0.003547s |100.00% | 0.26% ) ( 0.003547s |100.00% | 1.53% ) (1x) |-- ls /
|-- 59.1.0: ( 0.003348s |100.00% | 0.25% ) ( 0.003348s |100.00% | 1.44% ) (1x) |-- ls /tmp
60.0.0: ( 0.000651s | 0.04% ) ( 0.000462s | 0.19% ) (1x) grep pattern <(sed 's/^/>>/' > /dev/null)
60.0.1: ( 0.002869s | 0.21% ) ( 0.002869s | 1.24% ) (1x) << (SUBSHELL) >>
|-- 60.1.0: ( 0.002869s |100.00% | 0.21% ) ( 0.002869s |100.00% | 1.24% ) (1x) |-- sed 's/^/>>/' > /dev/null
62.0.0: ( 0.043012s | 3.22% ) ( 0.000001s | 0.00% ) (1x) << (BACKGROUND FORK) >>
|-- 62.1.0: ( 0.000206s | 0.59% | 0.01% ) ( 0.000250s | 4.94% | 0.10% ) (3x) |-- for i in {1..3}
| 62.1.1: ( 0.000210s | 0.60% | 0.01% ) ( 0.000254s | 5.02% | 0.10% ) (3x) | echo "$i"
|-- 62.1.2: ( 0.034470s | 98.80% | 2.58% ) ( 0.004554s | 90.03% | 1.97% ) (3x) |-- sleep .01
63.0.0: ( 0.037336s | 2.79% ) ( 0.014949s | 6.46% ) (4x) read -r n <&${CO[0]}
63.0.1: ( 0.000235s | 0.01% ) ( 0.000277s | 0.11% ) (3x) printf "got %s\n" "$n"
65.0.0: ( 0.000094s | 0.00% ) ( 0.000112s | 0.04% ) (1x) let "x = 5 + 6"
66.0.0: ( 0.000101s | 0.00% ) ( 0.000117s | 0.05% ) (1x) arr=(one two three)
66.0.1: ( 0.000112s | 0.00% ) ( 0.000133s | 0.05% ) (1x) echo ${arr[@]}
67.0.0: ( 0.000092s | 0.00% ) ( 0.000111s | 0.04% ) (1x) ((i=0))
67.0.1: ( 0.000313s | 0.02% ) ( 0.000372s | 0.16% ) (4x) ((i<3))
67.0.2: ( 0.000237s | 0.01% ) ( 0.000284s | 0.12% ) (3x) echo "$i"
67.0.3: ( 0.000225s | 0.01% ) ( 0.000274s | 0.11% ) (3x) ((i++))
80.0.0: ( 0.000065s | 0.00% ) ( 0.000079s | 0.03% ) (1x) cmd="echo inside-eval"
81.0.0: ( 0.000069s | 0.00% ) ( 0.000085s | 0.03% ) (1x) eval "$cmd"
81.0.1: ( 0.000074s | 0.00% ) ( 0.000088s | 0.03% ) (1x) echo inside-eval
82.0.0: ( 0.000069s | 0.00% ) ( 0.000083s | 0.03% ) (1x) eval "eval \"$cmd\""
82.0.1: ( 0.000069s | 0.00% ) ( 0.000084s | 0.03% ) (1x) eval "echo inside-eval"
82.0.2: ( 0.000072s | 0.00% ) ( 0.000087s | 0.03% ) (1x) echo inside-eval
84.0.0: ( 0.019507s | 1.46% ) ( 0.019455s | 8.41% ) (1x) trap 'echo got USR1; sleep .01' USR1
85.0.0: ( 0.000080s | 0.00% ) ( 0.000095s | 0.04% ) (1x) kill -USR1 $BASHPID
-53.0.0: ( 0.016088s | 1.20% ) ( 0.006087s | 2.63% ) (1x) -'TRAP (USR1): echo got USR1\; sleep .01'
-48.0.0: ( 0.000075s | 0.00% ) ( 0.000089s | 0.03% ) (1x) -'TRAP (USR1): echo got USR1\; sleep .01'
86.0.0: ( 0.000074s | 0.00% ) ( 0.000089s | 0.03% ) (1x) echo after-signal
88.0.0: ( 0.001005s | 0.07% ) ( 0.000638s | 0.27% ) (1x) cat <(echo hi) <(echo bye) <(echo 1; echo 2; echo 3)
88.0.1: ( 0.000227s | 0.01% ) ( 0.000258s | 0.11% ) (1x) << (SUBSHELL) >>
|-- 88.1.0: ( 0.000227s |100.00% | 0.01% ) ( 0.000258s |100.00% | 0.11% ) (1x) |-- echo hi
88.0.2: ( 0.000118s | 0.00% ) ( 0.000139s | 0.06% ) (1x) << (SUBSHELL) >>
|-- 88.1.0: ( 0.000118s |100.00% | 0.00% ) ( 0.000139s |100.00% | 0.06% ) (1x) |-- echo bye
88.0.3: ( 0.000415s | 0.03% ) ( 0.000491s | 0.21% ) (1x) << (SUBSHELL) >>
|-- 88.1.0: ( 0.000274s | 66.02% | 0.02% ) ( 0.000322s | 65.58% | 0.13% ) (1x) |-- echo 1
| 88.1.1: ( 0.000071s | 17.10% | 0.00% ) ( 0.000085s | 17.31% | 0.03% ) (1x) | echo 2
|-- 88.1.2: ( 0.000070s | 16.86% | 0.00% ) ( 0.000084s | 17.10% | 0.03% ) (1x) |-- echo 3
90.0.0: ( 0.001466s | 0.10% ) ( 0.001541s | 0.66% ) (3x) for i in {1..3} (&)
90.0.1: ( 0.001271s | 0.09% ) ( 0.001361s | 0.58% ) (1x) << (SUBSHELL) >>
|-- 90.1.0: ( 0.001196s | 94.09% | 0.08% ) ( 0.001271s | 93.38% | 0.54% ) (1x) |-- seq 1 4
|-- 90.1.1: ( 0.000075s | 5.90% | 0.00% ) ( 0.000090s | 6.61% | 0.03% ) (1x) |-- :
90.0.1: ( 0.001415s | 0.10% ) ( 0.001505s | 0.65% ) (1x) << (SUBSHELL) >>
|-- 90.1.0: ( 0.001332s | 94.13% | 0.09% ) ( 0.001406s | 93.42% | 0.60% ) (1x) |-- seq 1 4
|-- 90.1.1: ( 0.000083s | 5.86% | 0.00% ) ( 0.000099s | 6.57% | 0.04% ) (1x) |-- :
90.0.1: ( 0.001578s | 0.11% ) ( 0.001653s | 0.71% ) (1x) << (SUBSHELL) >>
|-- 90.1.0: ( 0.001503s | 95.24% | 0.11% ) ( 0.001562s | 94.49% | 0.67% ) (1x) |-- seq 1 4
|-- 90.1.1: ( 0.000075s | 4.75% | 0.00% ) ( 0.000091s | 5.50% | 0.03% ) (1x) |-- :
91.0.0: ( 0.003792s | 0.28% ) ( 0.001403s | 0.60% ) (15x) read x
92.0.0: ( 0.004530s | 0.33% ) ( 0.003861s | 1.67% ) (12x) (( x % 2 == 0 ))
93.0.0: ( 0.000448s | 0.03% ) ( 0.000530s | 0.22% ) (6x) echo even "$x"
95.0.0: ( 0.000075s | 0.00% ) ( 0.000089s | 0.03% ) (1x) << (SUBSHELL) >>
|-- 95.1.0: ( 0.000075s |100.00% | 0.00% ) ( 0.000089s |100.00% | 0.03% ) (1x) |-- echo odd "$x"
95.0.0: ( 0.000076s | 0.00% ) ( 0.000089s | 0.03% ) (1x) << (SUBSHELL) >>
|-- 95.1.0: ( 0.000076s |100.00% | 0.00% ) ( 0.000089s |100.00% | 0.03% ) (1x) |-- echo odd "$x"
95.0.0: ( 0.000109s | 0.00% ) ( 0.000128s | 0.05% ) (1x) << (SUBSHELL) >>
|-- 95.1.0: ( 0.000109s |100.00% | 0.00% ) ( 0.000128s |100.00% | 0.05% ) (1x) |-- echo odd "$x"
95.0.0: ( 0.000162s | 0.01% ) ( 0.000188s | 0.08% ) (1x) << (SUBSHELL) >>
|-- 95.1.0: ( 0.000162s |100.00% | 0.01% ) ( 0.000188s |100.00% | 0.08% ) (1x) |-- echo odd "$x"
95.0.0: ( 0.000176s | 0.01% ) ( 0.000199s | 0.08% ) (1x) << (SUBSHELL) >>
|-- 95.1.0: ( 0.000176s |100.00% | 0.01% ) ( 0.000199s |100.00% | 0.08% ) (1x) |-- echo odd "$x"
100.0.0: ( 0.000438s | 0.03% ) ( 0.000460s | 0.19% ) (1x) sleep 1 (&)
101.0.0: ( 1.002439s | 75.04% ) ( 0.001653s | 0.71% ) (1x) wait -n $!
104.0.0: ( 0.018994s | 1.42% ) ( 0.018969s | 8.20% ) (1x) << (SUBSHELL) >>
|-- 104.1.0: ( 0.017245s | 90.79% | 1.29% ) ( 0.017204s | 90.69% | 7.44% ) (1x) |-- trap 'echo bye' EXIT
| 105.1.0: ( 0.000075s | 0.39% | 0.00% ) ( 0.000085s | 0.44% | 0.03% ) (1x) | exit
|-- -53.1.0: ( 0.001674s | 8.81% | 0.12% ) ( 0.001680s | 8.85% | 0.72% ) (1x) |-- -'TRAP (EXIT): echo bye'
109.0.0: ( 0.025747s | 1.92% ) ( 0.025759s | 11.14% ) (1x) << (SUBSHELL) >>
|-- 109.1.0: ( 0.020312s | 78.89% | 1.52% ) ( 0.020265s | 78.67% | 8.76% ) (1x) |-- trap 'echo bye' RETURN EXIT
| 110.1.0: ( 0.003594s | 13.95% | 0.26% ) ( 0.003662s | 14.21% | 1.58% ) (1x) | << (FUNCTION): main.gg 1 >>
| |-- 1.2.0: ( 0.000063s | 1.75% | 0.00% ) ( 0.000072s | 1.96% | 0.03% ) (1x) | |-- gg 1
| | 8.2.0: ( 0.000068s | 1.89% | 0.00% ) ( 0.000081s | 2.21% | 0.03% ) (1x) | | echo "$*"
| | 8.2.1: ( 0.001806s | 50.25% | 0.13% ) ( 0.001841s | 50.27% | 0.79% ) (1x) | | << (FUNCTION): main.gg.ff "$@" >>
| | |-- 1.3.0: ( 0.000059s | 3.26% | 0.00% ) ( 0.000074s | 4.01% | 0.03% ) (1x) | | |-- ff "$@"
| | |-- 8.3.0: ( 0.001747s | 96.73% | 0.13% ) ( 0.001767s | 95.98% | 0.76% ) (2x) | | |-- echo "${*}"
| |-- 8.2.2: ( 0.001657s | 46.10% | 0.12% ) ( 0.001668s | 45.54% | 0.72% ) (1x) | |-- echo "${*}"
| 111.1.0: ( 0.000076s | 0.29% | 0.00% ) ( 0.000086s | 0.33% | 0.03% ) (1x) | exit
|-- -53.1.0: ( 0.001765s | 6.85% | 0.13% ) ( 0.001746s | 6.77% | 0.75% ) (1x) |-- -'TRAP (EXIT): echo bye'
115.0.0: ( 0.038002s | 2.84% ) ( 0.038024s | 16.44% ) (1x) << (SUBSHELL) >>
|-- 115.1.0: ( 0.017389s | 45.75% | 1.30% ) ( 0.017356s | 45.64% | 7.50% ) (1x) |-- trap 'echo exit' EXIT
| 116.1.0: ( 0.015303s | 40.26% | 1.14% ) ( 0.015258s | 40.12% | 6.60% ) (1x) | trap 'echo return' RETURN
| 117.1.0: ( 0.003589s | 9.44% | 0.26% ) ( 0.003668s | 9.64% | 1.58% ) (1x) | << (FUNCTION): main.gg 1 >>
| |-- 1.2.0: ( 0.000057s | 1.58% | 0.00% ) ( 0.000071s | 1.93% | 0.03% ) (1x) | |-- gg 1
| | 8.2.0: ( 0.000081s | 2.25% | 0.00% ) ( 0.000093s | 2.53% | 0.04% ) (1x) | | echo "$*"
| | 8.2.1: ( 0.001805s | 50.29% | 0.13% ) ( 0.001852s | 50.49% | 0.80% ) (1x) | | << (FUNCTION): main.gg.ff "$@" >>
| | |-- 1.3.0: ( 0.000056s | 3.10% | 0.00% ) ( 0.000069s | 3.72% | 0.02% ) (1x) | | |-- ff "$@"
| | |-- 8.3.0: ( 0.001749s | 96.89% | 0.13% ) ( 0.001783s | 96.27% | 0.77% ) (2x) | | |-- echo "${*}"
| |-- 8.2.2: ( 0.001646s | 45.86% | 0.12% ) ( 0.001652s | 45.03% | 0.71% ) (1x) | |-- echo "${*}"
| 118.1.0: ( 0.000069s | 0.18% | 0.00% ) ( 0.000082s | 0.21% | 0.03% ) (1x) | exit
|-- -53.1.0: ( 0.001652s | 4.34% | 0.12% ) ( 0.001660s | 4.36% | 0.71% ) (1x) |-- -'TRAP (EXIT): echo exit'
123.0.0: ( 0.017856s | 1.33% ) ( 0.017835s | 7.71% ) (1x) << (SUBSHELL) >>
|-- 123.1.0: ( 0.017783s | 99.59% | 1.33% ) ( 0.017749s | 99.51% | 7.67% ) (1x) |-- trap '' RETURN EXIT
|-- 124.1.0: ( 0.000073s | 0.40% | 0.00% ) ( 0.000086s | 0.48% | 0.03% ) (1x) |-- exit
129.0.0: ( 0.014348s | 1.07% ) ( 0.014318s | 6.19% ) (1x) << (SUBSHELL) >>
|-- 129.1.0: ( 0.014272s | 99.47% | 1.06% ) ( 0.014233s | 99.40% | 6.15% ) (1x) |-- trap - EXIT
|-- 130.1.0: ( 0.000076s | 0.52% | 0.00% ) ( 0.000085s | 0.59% | 0.03% ) (1x) |-- exit
133.0.0: ( 0.000933s | 0.06% ) ( 0.001064s | 0.46% ) (1x) << (SUBSHELL) >>
|-- 133.1.0: ( 0.000213s | 22.82% | 0.01% ) ( 0.000242s | 22.74% | 0.10% ) (1x) |-- echo $BASHPID
| 133.1.1: ( 0.000720s | 77.17% | 0.05% ) ( 0.000822s | 77.25% | 0.35% ) (1x) | << (SUBSHELL) >>
| |-- 133.2.0: ( 0.000312s | 43.33% | 0.02% ) ( 0.000367s | 44.64% | 0.15% ) (1x) | |-- echo $BASHPID
| | 133.2.1: ( 0.000408s | 56.66% | 0.03% ) ( 0.000455s | 55.35% | 0.19% ) (1x) | | << (SUBSHELL) >>
| | |-- 133.3.0: ( 0.000103s | 25.24% | 0.00% ) ( 0.000102s | 22.41% | 0.04% ) (1x) | | |-- echo $BASHPID
| | | 133.3.1: ( 0.000305s | 74.75% | 0.02% ) ( 0.000353s | 77.58% | 0.15% ) (1x) | | | << (SUBSHELL) >>
|-- |-- |-- |-- 133.4.0: ( 0.000305s |100.00% | 0.02% ) ( 0.000353s |100.00% | 0.15% ) (1x) |-- |-- |-- |-- echo $BASHPID
TOTAL RUN TIME: 1.335700s
TOTAL CPU TIME: 0.231161s
and generates this flamegraph (that shows both the wall-clock time flamegraph and the CPU-time flamegraph).
Note: stack overflow doesn't support SVG images, so I've converted it to a PNG image below. the SVG image I linked (on github) has tooltips and will zoom in on clicking a box and search and things like that. the best way to ensure all the "extras" work is to download the SVG image and then open the local copy.
Visual Studio Code was cropping the results, leading to me thinking that something in the code wasn't working.
Welp.
Update your react-native-screens package to
3.33.0
This will solve the problem
Actually build the flet iOS app ipa and installed on real device through Xcode. In the console.app not getting the live logs.
I implemented like this
CONFIG_FILE = "assets/config.json"
LOG_FILE = "assets/app.log"
os.makedirs(os.path.dirname(LOG_FILE), exist_ok=True)
logger = logging.getLogger(_name_)
logger.setLevel(logging.INFO)
file_handler = logging.FileHandler(LOG_FILE)
stream_handler = logging.StreamHandler()
# Create formatter and set it for both handlers
formatter = logging.Formatter("%(asctime)s - %(levelname)s - %(message)s")
file_handler.setFormatter(formatter)
stream_handler.setFormatter(formatter)
# Add handlers to the logger
logger.addHandler(file_handler)
logger.addHandler(stream_handler)
logger.propagate = False
logger.info("Application started")
But I am getting the live logs in console.app
Since TYPO3 13
allowTableOnStandardPages
was removed. Please reffer to new options within the ctrl
Section of TCA
I think the idea is that you don't know which field has the correct password, so a general error is raised. Does that provide you with enough help?
The sign-up prompt appears because your end users don’t have the right Power BI license or permissions in the Power BI Service.
What to do:
Licensing – Either assign users a Power BI Pro license or place the report in a Premium capacity workspace (Premium allows free users to view).
Permissions – In Power BI Service, share the report or dataset with an Azure AD security group containing all viewers.
Embedding – Use Embed in SharePoint Online from Power BI and paste the link into the Power BI web part in SharePoint (not Publish to Web).
Reference guide with step-by-step instructions here: Embedding Power BI Reports in SharePoint – Step-by-Step
Reference:https://learn.microsoft.com/en-us/power-bi/collaborate-share/service-embed-report-spo
Thanks for @greg-449.
The build.properties file which achieves that classes are within the root of the jar:
```
bin.includes = META-INF/,\
plugin.xml,\
.,\
target/dependency/antlr4-runtime-4.13.2.jar,\
target/dependency/apiguardian-api-1.1.2.jar,\
target/dependency/asm-9.8.jar,\
target/dependency/byte-buddy-1.17.5.jar,\
target/dependency/byte-buddy-agent-1.17.5.jar,\
target/dependency/checker-qual-3.49.3.jar,\
target/dependency/commons-codec-1.15.jar,\
target/dependency/commons-lang3-3.17.0.jar,\
target/dependency/error_prone_annotations-2.38.0.jar,\
target/dependency/gson-2.13.1.jar,\
target/dependency/inez-parser-0.4.1.jar,\
target/dependency/inez-parser-0.4.1-testing.jar,\
target/dependency/javax.annotation-api-1.3.2.jar,\
target/dependency/jul-to-slf4j-1.7.36.jar,\
target/dependency/konveyor-base-0.2.7-annotations.jar,\
target/dependency/micrometer-commons-1.14.9.jar,\
target/dependency/micrometer-observation-1.14.9.jar,\
target/dependency/nice-xml-messages-3.1.jar,\
target/dependency/objenesis-3.3.jar,\
target/dependency/opentest4j-1.3.0.jar,\
target/dependency/pcollections-4.0.2.jar,\
target/dependency/pmd-core-7.14.0.jar,\
target/dependency/pmd-java-7.14.0.jar,\
target/dependency/Saxon-HE-12.5.jar,\
target/dependency/slf4j-api-2.0.2.jar,\
target/dependency/spring-aop-6.2.9.jar,\
target/dependency/spring-beans-6.2.9.jar,\
target/dependency/spring-boot-3.5.3.jar,\
target/dependency/spring-context-6.2.9.jar,\
target/dependency/spring-core-6.2.9.jar,\
target/dependency/spring-data-commons-3.5.2.jar,\
target/dependency/spring-data-keyvalue-3.5.1.jar,\
target/dependency/spring-expression-6.2.9.jar,\
target/dependency/spring-jcl-6.2.9.jar,\
target/dependency/spring-test-6.2.9.jar,\
target/dependency/spring-tx-6.2.8.jar,\
target/dependency/xmlresolver-5.2.2.jar,\
target/dependency/xmlresolver-5.2.2-data.jar,\
target/dependency/spring-boot-autoconfigure-3.5.3.jar,\
target/dependency/konveyor-base-0.2.7-runtime.jar,\
target/dependency/mockito-core-5.18.0.jar,\
target/dependency/junit-jupiter-api-5.12.1.jar,\
target/dependency/junit-jupiter-engine-5.12.1.jar,\
target/dependency/junit-platform-commons-1.12.1.jar,\
target/dependency/junit-platform-engine-1.12.1.jar,\
target/dependency/junit-platform-launcher-1.12.1.jar,\
target/dependency/konveyor-base-0.2.7-testing.jar,\
target/dependency/httpclient5-5.1.3.jar,\
target/dependency/httpcore5-5.1.3.jar,\
target/dependency/httpcore5-h2-5.1.3.jar,\
target/dependency/konveyor-base-tooling.jar,\
target/dependency/org.eclipse.core.contenttype-3.9.600.v20241001-1711.jar,\
target/dependency/org.eclipse.core.jobs-3.15.500.v20250204-0817.jar,\
target/dependency/org.eclipse.core.runtime-3.33.0.v20250206-0919.jar,\
target/dependency/org.eclipse.equinox.app-1.7.300.v20250130-0528.jar,\
target/dependency/org.eclipse.equinox.common-3.20.0.v20250129-1348.jar,\
target/dependency/org.eclipse.equinox.preferences-3.11.300.v20250130-0533.jar,\
target/dependency/org.eclipse.equinox.registry-3.12.300.v20250129-1129.jar,\
target/dependency/org.eclipse.osgi-3.23.0.v20250228-0640.jar,\
target/dependency/org.osgi.core-6.0.0.jar,\
target/dependency/org.osgi.service.prefs-1.1.2.jar,\
target/dependency/osgi.annotation-8.0.1.jar
output.. = target/classes/,target/dependency/
source.. = src/
There is a Banuba plugin on Agora's extensions marketplace:https://www.agora.io/en/extensions/banuba/
It is by far the easiest way to integrate their masks, backgrounds, etc.
I simply stopped using psycopg2 and switched to psycopg (aka psycopg3) and everything worked perfectly. I spent a whole day trying to understand why it kept giving this error, and I came to no conclusion. I tried thousands of things and nothing worked, so I just switched.
PostgreSQL is not designed primarily for heavy linear algebra. Pure PL/pgSQL implementations (like Gauss-Jordan) would be very slow and inefficient for 1000x1000. Extensions are the way to go, but availability and performance vary.
PgEigen is a PostgreSQL extension providing bindings to Eigen C++ linear algebra library.It supports matrix inversion and other matrix operations efficiently.
Pros: Fast, tested on large matrices, uses compiled C++ code.
Cons: Needs installation of C++ dependencies and admin rights.
OneSparse is specialised for sparse matrices and might not be ideal for dense 1000x1000.
How to attribute backup costs to specific Cloud SQL instances?
When you're tracking costs in Google Cloud, SKU Cloud SQL: Backups in [region]
are billed based on usage, but the lack of a resource.id
in the billing export makes it tough to tie these costs directly to specific Cloud SQL instances. However, work around would be by Instance naming convention and Using billing API filters.
Instance Naming Convention: While this doesn't appear in the billing export, you can match your billing entries with the Cloud SQL instance names manually. For example, if you have instances like prod-db
, dev-db
, etc., it can help you identify the backups by relating them to specific environments.
Use Billing API and create custom Filters: Even though resource.id
isn’t available, you might be able to filter by SKU (e.g., "Cloud SQL: Backups"), regions, and time ranges to make educated guesses. This might still not give you the exact resource ID, but limiting by the filters can help you break down the cost.
Is there a way to correlate billing lines with instance names or labels?
Unfortunately, the billing export you have doesn’t contain labels or instance IDs, which would normally help tie the cost to specific instances. However, there’s a workaround:
Enable Label-based Billing on Cloud SQL: You can add labels to your Cloud SQL instances. Labels are key-value pairs that allow you to tag resources. Once you add labels (like instance-name or environment: production), you can filter the billing export by those labels and identify which instance is generating the backup costs.
Resource IDs for backups: While resource.id
might not appear in your current export, you can try to enable more granular billing tracking for backups by using Cloud Monitoring (formerly Stackdriver) and creating custom reports based on your labels or instance names. This way, you could match metrics to billing costs.
How can I identify if a particular backup is unnecessary or consuming excessive storage?
To track excessive storage or unnecessary backups, it’s all about monitoring and data management.
Cloud SQL Monitoring Metrics: Check the backup_storage_used metric (you mentioned you've already checked it). This can help you identify the trends in storage usage and determine if a particular instance is using significantly more storage than expected.
Here’s what you need to look for and compare the expected size of your backups (based on the size of your databases) with the storage usage reported in the metric. If it’s unusually high, it might indicate that backups are growing unexpectedly due to things like; Unnecessary large data retention, Backup frequency, and Non-incremental backups.
Any tips, tools, or workflows to bridge the gap between backup costs and specific Cloud SQL instances?
Google Cloud Billing Reports: You can explore Google Cloud Cost Management tools, such as Cost Explorer or Reports, to break down costs based on project or label. Though not as granular as having a direct resource ID in the billing export, Cost Explorer helps you track costs over time.
Cloud Monitoring: This tool could set up usage-based alerts for your Cloud SQL instance's backup storage. By correlating Cloud SQL storage metrics (like backup_storage_used
and total_backup_storage
) with backup events, you can monitor abnormal growth or unnecessary backups.
BigQuery Billing Export: Set up BigQuery exports for your billing data. With BigQuery, you can analyze the billing data more flexibly. You could potentially join billing data with other instance-level data (like Cloud SQL instance IDs or tags) to get a clearer picture of which instance is incurring the backup costs.
Here are some helpful links that may help resolve your issue:
Find example queries for Cloud Billing data
In my case I was using both xarray and netCDF, the issue was created by importing xarray before netCDF4.
Swapping the order fixed the issue.
I suggest you go to spatie/laravel-data and try this package
app.get('/{*any}', (req, res) =>
this is actually working for me
If you can treat blank values as missing, and can use SpEL and the Elvis operator
@Value("#{'${some.value:}' ?: null}")
private String someValue;
This works because a missing some.value
will lead to an empty string which is "falsy" and then the elvis operator goes with the fallback. In the SpEL expression - so in the #{...}
scope - null
means null
and not the string "null".
As compared to @EpicPandaForce's answer:
This does not require a custom PropertySourcesPlaceholderConfigurer
but requires a SpEL expression
and is not global - so each property like that will need the adjustment
Blank values are treated as "missing" too - which may be a pro or a con
Using tolist
can work, followed by np.array
will correctly return a (2,3) numpy array
np.array(df["a"].values.tolist())
returns
array([[1, 2, 3],
[4, 5, 6]])
Try using yii\debug\Module, it helps a lot.
Thanks to @woxxom I've been able to get the embedded iframes to load by removing initiatorDomains:[runtimeId]
and instead using tabIds:[tabId]
and updating session rules instead of dynamic rules:
await browser.declarativeNetRequest.updateSessionRules({
removeRuleIds:[RULE.id],
addRules:[RULE],
})
On a sidenote, I found an unrelated error for my use case that says:
Uncaught SecurityError: Failed to read a named property 'document' from 'Window': Blocked a frame with origin "https://1xbet.whoscored.com" from accessing a cross m-origin frame.
This is the src
of the parent iframe embedded in the extension page. I'm not sure if this is something I should worry about.
You can add 1 more environment variable in docker-compose.yml of keycloak
HOSTNAME : host.docker.internal
The problem would get solved.
Another option is to do a somewhat reverse COUNTIF with wildcards.
=INDEX(SUM(COUNTIF(E16, "*"&My_List&"*")))
This will return the number of case-insensitive matches and will ignore blank cells and any cells with errors.
If you want to avoid exporting the resolved dependencies, use the following
uv pip compile pyproject.toml --output-file requirements.txt --no-deps
webrightnow's answer led me to the solution.
For me, product reviews were disabled while I was creating the majority of my listings and for some reason the review section didn't appear for these products when I enabled it globally later, even though it did work for products that I've created after enabling it.
Enabling reviews on the edit product page of these products didn't work either, BUT it seemed to work for me when I clicked the "Quick Edit" in my Products page for my product and enabled it there.
My question got downvoted but no reason why, such a shame.
I have solved how to do this. I was going to publish a comprehensive answer but I'm getting more disappointed with downvotes and admins posting unnecessary comments so here's a short answer.
Need to copy the IBExpert.fdb to the new pc.
Developing a marketplace web app for the Chrome Web Store is a smart way to reach users directly through their browsers, especially if your platform offers digital tools, services, or extensions. However, to stand out in a competitive environment, your app must be well-designed, secure, and performance-optimized.
At its core, Chrome Web Apps are built using standard web technologies like HTML, CSS, and JavaScript. But when you're building a marketplace, you need to factor in multi-vendor capabilities, user accounts, secure payments, and real-time functionality—all of which require strategic marketplace app development.
Key considerations include integrating Chrome APIs properly, ensuring seamless user authentication (such as OAuth), secure backend connections, and maintaining data privacy. Additionally, your app must comply with Chrome Web Store policies, including HTTPS hosting and content restrictions.
If you're serious about launching a scalable and feature-rich marketplace through the Chrome Web Store, it's essential to work with a team experienced in marketplace app development. They can guide you through best practices, build a strong technical foundation, and ensure your app is optimized for user engagement and future growth.
In short, success in the Chrome ecosystem starts with smart planning and expert development tailored to marketplace dynamics.
I know that the question is related to PHP, but if anyone have any problems with escaping $
you can alternatively wrap it in character list like this: [$]\w+[$]
.
Add the following annotation to your @AuthenticationPrincipal CurrentUser currentUser:
@Parameter(hidden = true)
For the ones that are using the free tier, be sure that the EC2 instance type selected in among the free tier eligible, see the available ones here.
In my case I was using both xarray and netCDF, the issue was created by importing xarray before netCDF4.
Swapping the order fixed the issue.
--> Initialize the Global Key
final GlobalKey<ScaffoldState> _scaffoldKey = GlobalKey<ScaffoldState>();
--> Add this key to scaffold key:
--> Call it on any button as given beow:
_scaffoldKey.currentState?.openEndDrawer();
Add implementation("com.android.support:multidex:1.0.3")
into <dependencies>
is work for me
Based on the official Python documentation and common implementation details, the expression L[a:b] = L[c:d]
does indeed create a new, temporary list for the right-hand side L[c:d]
before the assignment to the left-hand side L[a:b]
.
https://docs.python.org/3/reference/simple_stmts.html#assignment-statements
I get the same problem and I am not using Msys2 but Ada under a version of GNAT Studio and Gtkada from 2021. Searching on internet show as a probable cause the fact that I am using now an high definition screen. Programs that I had compiled earlier also had the problem just by running there exe file.The new one also shows this problem while the compilation crates a .exe file.
If I try the command gap -c Print("Hello");
on my Ubuntu, I get an error. In my case the right syntax seems to be :
gap -c "your_code"
or :
gap -c 'your_code'
Work for me : gap -c 'Print("Hello\n");'
(I use '
instead of "
for a correct parsing... and the \n
matter !).
You can try a more simple thing : gap -c "a:=1;"
and check in the console that a
is indeed bound and equal to 1. However the field in GAPInfo.CommandLineOptions;
for the option -c
still be empty, I don't think this is where the data is stored. You can recover your input by calling GAPInfo.InitFiles;
.
To sum up there is a screen of running the following command :
gap -c 'a:=1; Print("ThisOneIsDisplayed\n"); Print("ThisOneNot");'
Hi zidniryi,
did you get it running?
Apparently <
and >
don't need escaping in PCRE Flavour, see What special characters must be escaped in regular expressions? for further info.
Use (<File .+?>)
as Regex and see for yourself:
Try unsetting PYTHONPATH before starting up vscode or any vscode forks: unset PYTHONPATH
I've commented on this issue here: https://github.com/microsoft/pyright/issues/9610#issuecomment-3154268891
The problem in my case was, that I've overridden the default creation of test database by Django, when running the tests. This happened by obsolete pytest fixture
that i had in my conftest.py
. As @willeM_ Van Onsem confirmed, Django by default creates a test database by appending test_
to the name of your default to use database.
In order to check which database are you using, just add a print statement into a test case:
from django.db import connection
connection.settings_dict["NAME"]
This will NOT print your default database name, but will print the database name of the currently used database.
In my case, my database configuration ended up like:
DATABASES = {
'default': {
"NAME": "localDatabase",
"ENGINE": "django.contrib.gis.db.backends.postgis",
"USER": "test",
"PASSWORD": "test",
"HOST": "127.0.0.1",
"PORT": "5432",
},
}
and when running the tests, the currently used database name is - "test_localDatabase".
As you can see, I have removed the "TEST"
key property from DATABASES
, because it overrides the default Django logic of generating a new name for the test database.
You can try using a basic Convolutional Neural Network program for the digit recognition. Using MNIST to demonstrate how a CNN can identify patterns is the most basic application of a CNN. It's so basic that it's taught in courses on Artificial Intelligence. You can search on Google or use one of these links
If you're allergic to clicking on links (like I am) here's a basic explanation:
You probably already know what a Neural Network is. You probably also know what a CNN is. You can simply build a CNN using the tensorflow library for the various layers, then mix and match the layers as to your liking. For the text input, just use OpenCV and PyTesseract for scanning an image and extracting text using OCR
Here's a sample code for you (for the OCR)
import cv2
import pytesseract
pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'
import matplotlib.pyplot as plt
def extractTextFromID(image_path):
"""
Parameters
----------
image_path : str
Path to the image that is going to be analysed. Extracts all read text
NOTE: vertically arranged text may not be read properly
Returns
-------
extracted_text : str
str of all the text as read by the function.
"""
img = cv2.imread(image_path)
image_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
plt.figure(figsize=(10, 6))
plt.imshow(image_rgb)
plt.title("Original Image")
plt.axis("off")
plt.show()
extracted_text = pytesseract.image_to_string(image_rgb)
return extracted_text
This code returns the extracted text as a single large string. If you just want to read from the image directly you can just use a CNN:
from keras.models import Sequential, load_model
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D, BatchNormalization
from keras.optimizers import Adam
model = Sequential()
model.add(Conv2D(filters=32, kernel_size=(3, 3), activation='relu', strides=1, padding='same', data_format='channels_last',
input_shape=(28,28,1)))
model.add(BatchNormalization())
model.add(Conv2D(filters=32, kernel_size=(3, 3), activation='relu', strides=1, padding='same', data_format='channels_last'))
model.add(BatchNormalization())
model.add(MaxPooling2D(pool_size=(2, 2), strides=2, padding='valid' ))
model.add(Dropout(0.25))
model.add(Conv2D(filters=64, kernel_size=(3, 3), activation='relu', strides=1, padding='same', data_format='channels_last'))
model.add(BatchNormalization())
model.add(Conv2D(filters=64, kernel_size=(3, 3), strides=1, padding='same', activation='relu', data_format='channels_last'))
model.add(BatchNormalization())
model.add(MaxPooling2D(pool_size=(2, 2), padding='valid', strides=2))
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(512, activation='relu'))
model.add(BatchNormalization())
model.add(Dropout(0.25))
model.add(Dense(1024, activation='relu'))
model.add(BatchNormalization())
model.add(Dropout(0.5))
model.add(Dense(10, activation='softmax'))
#Optimizer
optimizer = Adam(lr=0.001, beta_1=0.9, beta_2=0.999 )
#Compiling the model
model.compile(optimizer=optimizer, loss="categorical_crossentropy", metrics=["accuracy"])
#defining these prior to model to increase readability and debugging
batch_size = 64
epochs = 50
# Fit the Model
history = model.fit_generator(datagen.flow(x_train, y_train, batch_size = batch_size), epochs = epochs,
validation_data = (x_test, y_test), verbose=1,
steps_per_epoch=x_train.shape[0] // batch_size,
callbacks = [reduce_lr])
Let me know if you need additional help
The preloads are inserted because Webpack adds prefetch/preload hints based on the import()
statement. You can suppress this behavior like so:
const
MyComponent = dynamic(() =>
import(/* webpackPreload: false */ './MyComponent')
)
This tells Webpack not to insert a preload hint for that chunk.
if u want to keep showing your :after element, but only hide it for screen readers. You just need to add this:
content: " (required)" / "";
I get more or less the same error, with VSCode Version: 1.102.3 on Ubuntu 24.04.2 LTS. With my local python env, I can import rasterio in .py files, in command line, but not in .ipynb.
// Create sample file; replace if exists.
Windows.Storage.StorageFolder storageFolder =
Windows.Storage.ApplicationData.Current.LocalFolder;
Windows.Storage.StorageFile sampleFile =
await storageFolder.CreateFileAsync("sample.txt",
Windows.Storage.CreationCollisionOption.ReplaceExisting);
on 2.6 add field is exported
you can use iterator to export your data out
you can also use VTS tool help you to do this
see here:
How to invoke a method on a NSViewRepresentable from a View?
a complete (minimal..) sample. Hop can help.
Brando Zhang(https://stackoverflow.com/users/7609093/brando-zhang)
I tried with your answer but failed.
The answer above is good if you want to print out more than one command, but if you only one or two commands the type: "drive letter:\diskpart help > help.txt
the file is in drive letter, ie c:
You would need a API gateway which is active and running. only then the custom connector will work
For anyone wondering, this behaviour works since PHP 5.5
At the time I wrote the question I was maybe lacking of knowledge, instead of trying to assign a value to the static variable if it is empty, simply directly return the value, so it won't be permanently overriden.
abstract class Model {
protected static $table;
static function getTable(){
if(!static::$table){
// ClassName in plural to match to the table Name
return strtolower(static::class . 's');
}
return static::$table;
}
}
class Information extends Model {
static $table = 'infos'; // Overrides ClassName + s
}
class Service extends Model {
}
class Categorie extends Model {
}
print(Service::getTable() . "\n"); // services
print(Information::getTable() . "\n"); // infos
print(Categorie::getTable() . "\n"); // categories
I'm using modules too and to my understanding when importing a rule and changing an element of it you are overwritting it.
So you cannot just edit one part of it, its all or nothing.
x.prefix = output of "hg paths default"
x.username = USERNAME
x.password = PASSWORD
if you are asking if the memory space is in order then yes , it will be in contiguous memory and the elements will be accessible if you know the size of an element . example if the vector is of int type and you want the element then multiply the index with the 4 bytes (int) and added it to the base address and you will find the element.
I think QARetrievalChain and GraphCypherChain both output runnable classes that aren't directly compatible with standard LLM Chain nodes in Flowise.
Possible Solution
Try using a Custom Function node to merge the outputs from both RAG flows:
Create a Custom Function node that accepts both runnable outputs
Extract the actual response data from each runnable class using their respective methods (like .invoke() or .run())
Combine the responses in your custom logic
Pass the merged result to an LLM Chain node for final response generation
You should add the user and database option for the command pg_isready.
pg_isready -U myUser -d myDb
see the following post
The suggested solutions wouldn't work for me but this does
$('#grid').data("kendoGrid").cancelChanges();
Maybe update libheif
to a newer version.(I am using homebrew to do so on MacOS).
I am having this issue while installing another python library with pi-heif
as its dependency on MacOS. Same error about error: call to undeclared function 'heif_image_handle_get_preferred_decoding_colorspace'; ISO C99 and later do not support implicit function declarations [-Wimplicit-function-declaration]
.
There was a 1.16.2
version of libheif
installed on my computer but the latest version available on homebrew as for now(2025-08-05) is 1.20.1
.
I just reinstall the latest version of libheif
and it's all right now.
In these compilers, the use of the -O
(or potentially -O2
, -Os
, -Oz
, or others, depending on use-case) compile option can be used to collapse identical switch statements.
I had the same issue after updating express
from version 4 to 5.1.0 while uploading files. I had to update body-parser
to the latest version (2.2.0).
As pre bitbucket official document there is a storage limit as well as expiry due also https://support.atlassian.com/bitbucket-cloud/docs/use-artifacts-in-steps/ so if you need more then that use your own storage as amazon s3.
A combination of flutter_background_service and flutter_local_notifications will work.
Using this enables you to set custom time intervals.
i was also facing this issue for the past 2 months. atlast we changed to https .
today too when i checked issue still there but i tried many steps and,
Fixed the issue now.
steps.
remove your existing http request checking code in info.plist
add this
<key>NSAppTransportSecurity</key>
<dict>
<key>NSExceptionDomains</key>
<dict>
<key>NSExceptionAllowsInsecureHTTPLoads</key>
<true/>
<key>localhost</key>
<dict>
<key>NSExceptionAllowsInsecureHTTPLoads</key>
<true/>
</dict>
</dict>
<key>NSAllowsArbitraryLoads</key>
<true/>
</dict>
then Xcode -> product -> Clean Build folder
then run the app in your iOS device.
Now we can run your http urls in your ios as you needed .