Connect  to DocumentDB using Python

I am trying to connect to DocumentDB from Python. I looked at some of the examples provided here. However, my setup is a bit different. I can connect to it from my terminal by creating a ssh tunnel. But, cannot connect from python.
Steps taken for connecting from my laptop's terminal.

Have with me the aws_access_key_id  and aws_secret_access_key  which provides me access to the EC2 instance. I do not have username/password.
Command that starts the tunnel AWS_REGION=us-west-2 AWS_PROFILE=<username> ssh -i ~/.ssh/ssm-tunnel-ec2.pem -L 27017:docdb-blah.docdb.amazonaws.com:27017 ec2-user@i-000000000000000 -N -v.
Command to launch mongo shell mongo --username=<DB_USER> --password=<DB_PASS>

Steps taken for connecting using pymongo library

Performed these steps, but get a Connection Timed out error as soon as i perform an operation using the client.
Also, tried to create a SSH Tunnel, but cannot start the tunnel successfully.

Can someone assist. Thanks in advance!

Can you please further explain what is working and what is not? Specifically:

If you SSH into your EC2 instance can you connect to DocumentDB via the MongoDB shell?
If you SSH into your EC2 instance can you connect to DocumentDB via Python?
Are you able to successfully start your SSH tunnel?

@tmcallaghan - Hi thanks for the reply.

Yes, works. I can start the tunnel from my laptop and connect to DocumentDB using Mongo shell
How can i go about doing this?
I can start the tunnel from the terminal, but not from inside python.

@darshakkakkad if you can start the tunnel from your laptop and that tunnel allows you to connect to DocumentDB using the MongoDB shell then I suggest you use this same tunnel for connecting to DocumentDB via Python.
What are you using for your connection string, and DO NOT include username/password here.
client = pymongo.MongoClient('mongodb://:@sample-cluster.node.us-east-1.docdb.amazonaws.com:27017/?replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')

@tmcallaghan What username and password are these - one for connecting to EC2 or the one for DocumentDB itself?
BTW, I am using the very same command you shared. I may be missing something when configuring the MongoClient.

You should be using the username and password for DocumentDB in the pymongo connection string. Also, the fully qualified domain name and port in this connection string should be localhost and the port your ssh tunnel is listening on.

Command -
client = MongoClient('mongodb://<DB_USERNAME>:<DB_PASSWORD>@localhost:27017/?replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')

Output -
Could not reach any servers in [('docdb-blah.us-west-2.docdb.amazonaws.com', 27017)]. Replica set is configured with internal hostnames or IPs?, Timeout: 30s, Topology Description: <TopologyDescription id: XYZ, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('docdb-blah.us-west-2.docdb.amazonaws.com', 27017) server_type: Unknown, rtt: None, error=NetworkTimeout('docdb-blah.us-west-2.docdb.amazonaws.com:27017: timed out')>]>

@darshakkakkad try using the following, this connects to the cluster endpoint directly (not in replica-set mode).
client = MongoClient('mongodb://<DB_USERNAME>:<DB_PASSWORD>@localhost:27017/?retryWrites=false')

@tmcallaghan That worked successfully! Could you pls explain what difference did that make?
It would be ideal if I could also get the tunneling to work inside my python script. Would you have any ideas how to get it to work? This makes running this on Jenkins possible.

@tmcallaghan I was able to start the tunnel successfully. Thanks for all your help!
For future reference this is my code to start the tunnel and connect to DocumentDB -
        from sshtunnel import SSHTunnelForwarder
        from pymongo import MongoClient

        EC2_URL = "A.B.C.D" # EC2 IP/Hostname
        DB_URI = "docdb-blah.us-west-2.docdb.amazonaws.com" # DocumentDB URI

        # Setup the tunnel connection
        server = SSHTunnelForwarder(
            (EC2_URL),
            ssh_username='ec2-user',
            ssh_pkey='~/.ssh/ssm-tunnel-ec2.pem',  # path of the keyfile here
            remote_bind_address=(DB_URI, 27017),
            local_bind_address=('localhost', 27017)
        )
        # Start the tunnel
        server.start()

        # Setup MongoClient
        client = MongoClient('mongodb://<DB_USERNAME>:<DB_PASSWORD>@localhost:27017/?retryWrites=false')

        # Print any databases. It may be empty if you do not have one created.
        print(client.list_database_names())

        # Specify the database name to be created
        db = client["docdbtest"]
        print("Sample DB created")

        # Specify the collection to be created
        col = db["docdbtestcollection"]
        print("Sample collection created")

        # Insert a single document
        col.insert_one({'hello': 'Amazon DocumentDB'})
        print("Inserted one doc")

        # Find the document that was previously written
        x = col.find_one({'hello': 'Amazon DocumentDB'})
        print("Fetched one doc")

        # Print the result to the screen
        print(x)

        # Close the connection
        client.close()
        print("Closing connection")

        # Stop the tunnel
        server.stop()

With this, I am closing this issue.


Adding a build-a-Tankoubon (volume) functionality

Imagine that you are behind in reading Bleach, or Naruto, or DragonBall and you need to catch up. We're talking about being >150 chapters behind.
You could set manga_downloader to download all of these chapters; and you could read them one by one. Once you're done with one chapter you'd have to search for the next one, open it up and read it. Rinse and repeat.
Now imagine you like to read these on your ebook reader. It becomes too much of a hassle.
What if we could group our chapters in a neatly ordered tankoubon? Like the ones you can get at any book store. You could then have a volume with 'n' number of chapters in it. It'd be easier to read in your favorite comic reader.
You should be able to control how many chapters you want in a given volume and have the option to optionally remove the individual chapter files once you are done compiling them into it.

I've been working on this feature request in my spare time and will submit a Pull Request for review.

Done in #85


setCategory() not working on Android

Hi,
I'm trying for my app to use sounds as user feedbacks (like a ping on sending a message). The idea is that if users are already listenign to music on some other back running on backgroud, it should stop the current music flow.
I used setCategory('Ambiant'), which work perfectly fine on IOS, but doesn't seems to do anything on Android : when a sound is played, it stops the background music.
Here is my implementation :

import Sound from 'react-native-sound';

Sound.setCategory('Ambient');

let pop = new Sound('pop1.mp3', Sound.MAIN_BUNDLE, (error) => {if (error) {console.log('failed to load the sound', error);}});
let notif = new Sound('notif.mp3', Sound.MAIN_BUNDLE, (error) => {if (error) {console.log('failed to load the sound', error);}});

let soundLibrarie = {
    pop : pop,
    notif : notif
};

const play= (soundName)=>{
    if (soundLibrarie[soundName] !== undefined){
        soundLibrarie[soundName].play((success)=>{})
    }
};

export default { play }

To be honnest I don't know if this is a bug, or if this is related to my implementation ...
Any ideas ?
Thanks !
React-native : 0.57.1
react-native-sound : 0.10.12

react-native-sound wiki states that it works only on iOS https://github.com/zmxv/react-native-sound/wiki/API#static-methods. However, I also want to control it on Android

Hey, I want to change the speaker of android from ear speaker to loud speaker. As the documentation says setCategory is not working on iOS. I also tried setSpeakerphoneOn method. It didn't do anything. Did anyone know how to change the output of the audio speaker using react-native-sound ?


Use an http query to find which version of the java runtime to use

Using version ranges in the pom means that maven will have to download all poms to find which one is the latest. This is bad. However, we can't fix the version in the hardcoded boilerplate otherwise we'd have to change the hardcoded boilerplate on every build of the runtime.
We need a quick fix before we tackle the wider issue of having a boilerplate generation image which revs independently from the fn cli (basically https://github.com/fnproject/fn/issues/135 ), so for now we make an http query and parse the result to get a version number.

Note for readers - this is a (temporary?)  bugfix to prevent maven from spamming away resolving versions with maven version placeholders.
Placeholders were put in to prevent us from having to rev the CLI every time we release.
We'll review when we look at build helper containers - I think that will remove the need to make calls as the API version will be tagged within the build helper (or the helper can make the call)


Clean up crate root

Currently the crate root contains a lot of items, which can be quite intimidating to new users. I propose that two new modules are created, types which contains commonly used GraphQL types and protocol which contains lower-level GraphQL types (this name is up for debate) that the user won't typically use. The following items should be moved:
Any -> types::Any
EmptyMutation -> types::EmptyMutation
EmptySubscription -> types::EmptySubscription
ID -> types::Id
Json -> types::Json
Lookahead -> protocol::Lookahead
Number -> types::Number
OutputJson -> types::OutputJson
Pos -> protocol::Pos
Positioned -> protocol::Positioned
QueryPathNode -> protocol::QueryPathNode
RuleError -> protocol::RuleError
Upload -> types::Upload
Variables -> protocol::Variables
WebSocketTransport -> http::WebSocketTransport
ParseRequestError -> protocol::ParseRequestError
Value -> types::Value

And of course the crate will also pub use types::* and pub use protocol::* so it won't be a breaking change. However, it will make it easier for people to read the library docs as the types will be better organized.
types could also be called scalars and just contain scalars.

Currently the crate root contains a lot of items, which can be quite intimidating to new users. I propose that two new modules are created, types which contains commonly used GraphQL types and protocol which contains lower-level GraphQL types (this name is up for debate) that the user won't typically use. The following items should be moved:
Any -> types::Any
EmptyMutation -> types::EmptyMutation
EmptySubscription -> types::EmptySubscription
ID -> types::Id
Json -> types::Json
Lookahead -> protocol::Lookahead
Number -> types::Number
OutputJson -> types::OutputJson
Pos -> protocol::Pos
Positioned -> protocol::Positioned
QueryPathNode -> protocol::QueryPathNode
RuleError -> protocol::RuleError
Upload -> types::Upload
Variables -> protocol::Variables
WebSocketTransport -> http::WebSocketTransport
ParseRequestError -> protocol::ParseRequestError
Value -> types::Value

And of course the crate will also pub use types::* and pub use protocol::* so it won't be a breaking change. However, it will make it easier for people to read the library docs as the types will be better organized.
types could also be called scalars and just contain scalars.

It looks great! 😁


Fix typos in Javadoc

Context

Contributor Checklist

[x] Review Contribution Guidelines
[x] Make sure that all commits are signed off to indicate that you agree to the terms of Developer Certificate of Origin.
[x] Make sure all contributed code can be distributed under the terms of the Apache License 2.0, e.g. the code was written by yourself or the original code is licensed under a license compatible to Apache License 2.0.
[x] Check "Allow edit from maintainers" option in pull request so that additional changes can be pushed by Gradle team
~- [x] Provide integration tests (under <subproject>/src/integTest) to verify changes from a user perspective~
~- [x] Provide unit tests (under <subproject>/src/test) to verify logic~
[x] Update User Guide, DSL Reference, and Javadoc for public-facing changes
[x] Ensure that tests pass sanity check: ./gradlew sanityCheck
[x] Ensure that tests pass locally: ./gradlew <changed-subproject>:quickTest

Reviewing cheatsheet
Before merging the PR, comments starting with

❌ ❓must be fixed
🤔 💅 should be fixed
💭 may be fixed
🎉 celebrate happy things

@bot-gradle test and merge

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blood-red phone

About the PR
added it to the nukie planet
Why / Balance
resolves #22528
Technical details
no
Media

[X] I have added screenshots/videos to this PR showcasing its changes ingame, or this PR does not require an ingame showcase

Breaking changes
no
Changelog
no cl no fun

valid

perfect

i thought they already had a way to contact admins

fax only goes to centcom i think


xview2 dataset

I want to include xview2 dataset in training by setting data directory using "-dd-xview2", and got the following error. Could you please give me some suggestions on how to fix it? Thanks very much!
  File ".../Catalyst/lib/python3.7/site-packages/catalyst/core/runner.py", line 987, in run_experiment
    self._run_event("on_exception")
  File ".../Catalyst/lib/python3.7/site-packages/catalyst/core/runner.py", line 780, in _run_event
    getattr(callback, event)(self)
  File ".../Catalyst/lib/python3.7/site-packages/catalyst/core/callbacks/exception.py", line 24, in on_exception
    raise exception
  File ".../Catalyst/lib/python3.7/site-packages/catalyst/core/runner.py", line 975, in run_experiment
    self._run_stage(stage)
  File ".../Catalyst/lib/python3.7/site-packages/catalyst/core/runner.py", line 943, in _run_stage
    self._run_epoch(stage=stage, epoch=self.epoch)
  File ".../Catalyst/lib/python3.7/site-packages/catalyst/core/runner.py", line 922, in _run_epoch
    self._run_loader(loader)
  File ".../Catalyst/lib/python3.7/site-packages/catalyst/core/runner.py", line 854, in _run_loader
    for i, batch in enumerate(loader):
  File ".../Catalyst/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 435, in __next__
    data = self._next_data()
  File ".../Catalyst/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1085, in _next_data
    return self._process_data(data)
  File ".../Catalyst/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1111, in _process_data
    data.reraise()
  File ".../Catalyst/lib/python3.7/site-packages/torch/_utils.py", line 428, in reraise
    raise self.exc_type(msg)
TypeError: Caught TypeError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File ".../Catalyst/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 198, in _worker_loop
    data = fetcher.fetch(index)
  File ".../Catalyst/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File ".../Catalyst/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File ".../Catalyst/lib/python3.7/site-packages/torch/utils/data/dataset.py", line 218, in __getitem__
    return self.datasets[dataset_idx][sample_idx]
  File ".../Catalyst/lib/python3.7/site-packages/torch/utils/data/dataset.py", line 218, in __getitem__
    return self.datasets[dataset_idx][sample_idx]
  File ".../BuildingSegmentation/inria/dataset.py", line 145, in __getitem__
    data = self.transform(image=image, mask=mask)
  File ".../Catalyst/lib/python3.7/site-packages/albumentations/core/composition.py", line 182, in __call__
    data = t(force_apply=force_apply, **data)
TypeError: 'list' object is not callable
python-BaseException```

Greetings, it's hard to tell, from the stacktrace, but it seems there is type mismatch somewhere in xview2 dataset part.
The code is under active refactoring at this point as I'm preparing pre-trained model zoo, which is likely to be released by the end of the year. So right now I can't provide support on this matter.

Thank you for your reply! I am looking forward to the pre-trained model zoo!


[PAPER, WIP] Joss paper

This is the JOSS paper for intracranial EEG electrode location. It's still a work in progress at the moment but I am opening a PR so that @agramfort @larsoner and others can check that names and affiliations etc. are okay. I should have time to finish this pretty soon.

@drammock, I think paper.md has to be where it is in this PR for JOSS but would it be appropriate to have it live somewhere in doc/ if it gets accepted just so it lives somewhere as markdown?

would it be appropriate to have it live somewhere in doc/ if it gets accepted just so it lives somewhere as markdown?

Eventually will this be the entire paper text? I don't think this should live in the MNE-Python repository itself. Ideally it would live in a separate repo dedicated to the paper. Do they really require the paper text to live in the repo that houses the software? That seems like an onerous requirement actually. Even using git submodule would be annoying / we don't need the actual paper in our docs. At the end of the day once the paper is accepted, as far as the MNE-Python repo is concerned there should be a :footcite: and new entry in doc/references.bib and nothing more...

would it be appropriate to have it live somewhere in doc/ if it gets accepted just so it lives somewhere as markdown?

Eventually will this be the entire paper text? I don't think this should live in the MNE-Python repository itself. Ideally it would live in a separate repo dedicated to the paper. Do they really require the paper text to live in the repo that houses the software? That seems like an onerous requirement actually. Even using git submodule would be annoying / we don't need the actual paper in our docs. At the end of the day once the paper is accepted, as far as the MNE-Python repo is concerned there should be a :footcite: and new entry in doc/references.bib and nothing more...

No, it doesn't have to be in the repo, the branch is not required to be merged.
This was just to share the source code which is done in mne-bids but I'm fine not doing it, I thought it was a bit preferential since there are other mne-python papers and was unsure about doing it which is why I was checking.

there are other mne-python papers and was unsure about doing it which is why I was checking.

Typically these papers have their own repos / source control of some sort, completely separate from MNE-Python itself. No need to mix changesets for a paper with changesets for code. I think the Frontiers paper was maybe an Overleaf document for example

JOSS works with .md files so no overleaf but I agree I would not put this
in mne-python repo.
Let's create a dedicated repo which can be on mne-tools org

If you have a chance to review a first draft @larsoner and @agramfort, that would be great

repeating the request that this move to its own repo.  I see you using skip tags on some commits, but if you forget to do that it will waste CI cycles (which wastes electricity, which in most cases is generated with fossil fuel).

Good point, I think it has to be part of MNE-Python for the JOSS review though... that's how the paper preview and review works. The branch doesn't have to be merged, but after it's closed maybe that would be a good time to open the repo.

I just looked at the JOSS submission guidelines, which say quite prominently

Your paper (paper.md and BibTeX files, plus any figures) must be hosted in a Git-based repository together with your software (although they may be in a short-lived branch which is never merged with the default).

So it definitely needs to be part of either the MNE-Python repo, or possibly it's good enough if it just lives in your fork (?)
It would have been nice if you had simply pasted in that bit of the guidelines when this question originally arose...  your prior responses all said "I think..." and it would have saved us all some time if that guidance were clear from the get-go.

Yes in trying to sound like a nice guy I've lost a bit of the clarity, those are definitely the rules they lay out in the guidelines. I'm happy to open another repository but it will over complicate the review so we should do it after.

Sounds good to me

based on my reading of the JOSS guidelines, the paper and the software must be in the same repo.  Therefore as I said above:

I think the right approach is to work on the paper in a branch of your fork of MNE-Python

so basically do what you've been doing, but don't open a PR until you're done iterating w/ your co-authors and you're ready to submit to JOSS.  In the meantime, you should contact JOSS and ask whether it's OK if the paper is submitted directly from your fork, or if it must be on a (temporary) branch of the upstream repo.

But if there is no PR open then we can't use any GitHub web review features.

ah, good point.  In that case I'd do a PR from alexrockhill/joss to alexrockhill/main, yes.  And I'd do a draft PR so that you don't accidentally merge it and mess up your main.  When you and your co-authors are all satisfied, you can close that PR and open a new one into mne-tools/joss (we can create that branch if needed).


[BugFix] right join need use right child to derive output property

What type of PR is this：

[x] BugFix
[ ] Feature
[ ] Enhancement
[ ] Refactor
[ ] UT
[ ] Doc
[ ] Tool

Which issues of this PR fixes ：

Fixes #
Problem Summary(Required) ：

When it's a right join, it means the join output distribution info is dominated by its right child.
According to the unit test result, this pr may help optimize tpch-q13, tpch-q21, tpcds-q94.
Checklist:

[x] I have added test cases for my bug fix or my new feature
[ ] This pr will affect users' behaviors
[ ] This pr needs user documentation (for new or modified features or behaviors)

[ ] I have added documentation for my new feature or new function

[FE PR Coverage Check]
:heart_eyes: pass : 17 / 21 (80.95%)
file detail

path
covered_line
new_line
coverage
not_covered_line_detail

:large_blue_circle:
com/starrocks/sql/optimizer/OutputPropertyDeriver.java
17
21
80.95%
[223, 226, 229, 232]

run starrocks_be_unittest

run starrocks_admit_test

run starrocks_admit_test


access to yjaf-transitions for Greg and Thomas

Use this issue template if you do not feel comfortable raising a PR with the required changes to files in the terraform/ directory.
Please supply all the requested information, so that your request can be processed as quickly as possible.
Which MoJ repository are you requesting access to (e.g. money-to-prisoners)?
yjaf-transitions
What is the GitHub username of the person who needs access?
ttipler
gregi2n
What is their full name?
Thomas Tipler
Gregory Whiting
What is their email address?
<EMAIL_ADDRESS><EMAIL_ADDRESS>What company/organisation do they belong to (e.g. "MadeTech", "Department for Education")?
NEC SWS
What level of access should they have?

[ ] Read
[ ] Triage
[ ] Write
[ ] Maintain
[x] Admin

Why is this access being requested?
Working on pipeline for deployment of microservice
Which MoJ team/person is responsible for this request? This must be someone with a "*.justice.gov.uk" email address.
This should be in the form Awesome Team<EMAIL_ADDRESS>Team details are preferred, rather than individuals, to make it easier to follow-up at a later date.
Jon Dent<EMAIL_ADDRESS>Review date
Date after which this collaborator's access should be reviewed. This should be a date in the format: 2021-01-15, no more than one year into the future.
24/03/2023

approved for both - thanks

Hi Thomas,
Nick has opened a PR for you, once its merged access will be granted.
PR: https://github.com/ministryofjustice/github-collaborators/pull/570
Cheers,
Ben


fix(babble): fix args check

Seems like this was broken during a refactor

Seems like the behavior was changed in e19b3bde5355770271fa3d453f01a11f0224f729


[BUG] CSVLocalFileSystemImporter can't load datetime from csv

Memgraph version Which version did you use?
Memgraph v2.13.0
Environment Some information about the environment you are using Memgraph
on: operating system, how do you connect, with or without docker, which driver
etc.
Docker
Describe the bug
Cant load datetime string from csv to memgraph.
To Reproduce Steps to reproduce the behavior:
Use following scripts
importer = loaders.CSVLocalFileSystemImporter(
    data_configuration=yaml.safe_load(DATA_CONFIG),
    path = "tmp/airflow/data",
    memgraph=memgraph
)
importer.translate(drop_database_on_start=True)

Expected behavior
No error
Logs If applicable, add logs of Memgraph, CLI output or screenshots to help
explain your problem.
Loading data from table tmp/airflow/data/a.csv...
Traceback (most recent call last):
  File "/Users/superbo/Workspace/airflow-pipelines/test_memgraph_load.py", line 36, in <module>
    load_data()
  File "/Users/superbo/Workspace/airflow-pipelines/test_memgraph_load.py", line 32, in load_data
    importer.translate(drop_database_on_start=True)
  File "/Users/superbo/Workspace/airflow-pipelines/.venv/lib/python3.11/site-packages/gqlalchemy/transformations/importing/loaders.py", line 472, in translate
    self._load_nodes()
  File "/Users/superbo/Workspace/airflow-pipelines/.venv/lib/python3.11/site-packages/gqlalchemy/transformations/importing/loaders.py", line 480, in _load_nodes
    self._save_row_as_node(label=collection_name, row=row)
  File "/Users/superbo/Workspace/airflow-pipelines/.venv/lib/python3.11/site-packages/gqlalchemy/transformations/importing/loaders.py", line 591, in _save_row_as_node
    QueryBuilder(connection=self._memgraph)
  File "/Users/superbo/Workspace/airflow-pipelines/.venv/lib/python3.11/site-packages/gqlalchemy/query_builders/declarative_base.py", line 748, in node
    properties_str = to_cypher_properties(kwargs)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/superbo/Workspace/airflow-pipelines/.venv/lib/python3.11/site-packages/gqlalchemy/utilities.py", line 157, in to_cypher_properties
    value_str = to_cypher_value(value, config)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/superbo/Workspace/airflow-pipelines/.venv/lib/python3.11/site-packages/gqlalchemy/utilities.py", line 109, in to_cypher_value
    return f"{datetimeKwMapping[value_type]}('{_format_timedelta(value) if isinstance(value, timedelta) else value.isoformat()}')"
              ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^
KeyError: <class 'pandas._libs.tslibs.timestamps.Timestamp'>

Additional context Add any other context about the problem here.

Hi @SuperBo, thank you for reporting this. Would you be able to share your DATA_CONFIG file in order for us to replicate your issue? You don't have to share real data if it's sensitive, I'm just interested in the format of the file

@matea16, here is example data, i'm using pyarrow==13.0.0
account_id,phone_no,created_dt,updated_dt
abc1,+1212423,2019-08-28 12:19:18,
bcd2,+12123232,2021-06-09 09:05:41,2021-06-09 09:05:41
b11e,+94745734,2021-12-13 16:42:45,2021-12-13 16:42:45

Thank you for providing the data, we'll take a look at your issue shortly. I'll let you know if we have any additional questions to help us with the debugging :)

Hi @SuperBo, I see that you shared your CSV data, but did you create a data configuration object, similar to the the documentation? If yes, can you share that too?

@SuperBo, I believe the issue with your CSV file could be due to the format of your date field. In our docs, you can see supported formats of temporal types, including the local time format. Let me know if adjusting that format helps

Hi @matea16, I also tested with iso datetime format "yyyy-MM-ddThh:mm:ss", and still met the same error.
@katarinasupe : of course, I created a data configuration like this
indices:
    accounts:
        - account_id
    transactions:
        - transaction_number

name_mappings:
    accounts:
        label: Account
    transactions:
        label: INTERACT

one_to_many_relations:
    accounts: []
    transactions: []

@matea16, I think this error will happens depends on your dependencies, please test with following dependencies

python==3.11.5

requirments.txt
pyarrow==13.0.0
pandas==2.1.4
GQLAlchemy==1.5.1

hello @matea16 , new update, the problem comes from the remaining file. In that file, I put timestamp format as follwing:
2024-01-04T03:48:11.336Z

that format is unfortunately not supported since timezones are not supported, does it work without the timezone at the end?

I removed the last "Z" and the same error still occurs. However, when I remove the microseconds part, it works.

I will close this issue since it was related to how Memgraph handles time format.

Hi @SuperBo, I'm happy to let you know that zoned datetime data type has been added to Memgraph to the latest release with the following PR: https://github.com/memgraph/memgraph/pull/1866

Thank you Memgraph team, you rocks 👍

Zoned datetime has been added to Memgraph, but in order for it to work properly in GQLAlchemy, I think datetime keyword should still be added to the GQLAlchemy in order for OGM to work properly.

@matea16 I set a new milestone for GQLAlchemy. Will you be able to implement this until July 3rd?

Yes, I'll make sure to have it ready by July 3rd


Error when calling ethereum node

An error happen with an event forwardwer being run by validators, seems like the call to infura returns more results than expected, not sure what is the source of this, but could be nice to investigate.
/root/ethereum-event-forwarder/node_modules/nanoeth/http.js:29
      const error = new Error(res.body.error.message)
                    ^

Error: query returned more than 10000 results
    at RPC.request (/root/ethereum-event-forwarder/node_modules/nanoeth/http.js:29:21)
    at runMicrotasks (<anonymous>)
    at processTicksAndRejections (node:internal/process/task_queues:96:5)
    at async Promise.all (index 0)
    at async EthLogIterator._loop (/root/ethereum-event-forwarder/lib/eth-log-iterator.js:69:29) {
  code: -32005
}

Closed by https://github.com/vegaprotocol/ethereum-event-forwarder/commit/b97519a5f7ae9c7534ac3bdd38ebe342a875c02f


Bugfix empty integration

When having an empty integration or an integration with only one step, kamelet-support threw errors that made the frontend freeze.

Codecov Report

Merging #31 (fad0fca) into main (50ac14b) will decrease coverage by 1.30%.
The diff coverage is 67.39%.

:exclamation: Current head fad0fca differs from pull request most recent head 19c7433. Consider uploading reports for the commit 19c7433 to get more accurate results

@@             Coverage Diff              @@
##               main      #31      +/-   ##
============================================
- Coverage     84.96%   83.65%   -1.31%
+ Complexity       83       82       -1
============================================
  Files            28       28
  Lines           858      869      +11
  Branches        116      117       +1
============================================
- Hits            729      727       -2
- Misses           82       94      +12
- Partials         47       48       +1

Impacted Files
Coverage Δ

...o/backend/api/resource/ViewDefinitionResource.java
47.82% <40.00%> (-17.56%)
:arrow_down:

...kend/api/service/deployment/DeploymentService.java
66.66% <40.00%> (-6.07%)
:arrow_down:

...arser/kamelet/KameletBindingStepParserService.java
83.33% <71.42%> (-5.86%)
:arrow_down:

...va/io/kaoto/backend/deployment/ClusterService.java
80.48% <80.00%> (-5.23%)
:arrow_down:

Continue to review full report at Codecov.

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Allow modification of robot account permissions without replacement

Is your feature request related to a problem? Please describe.
Modifying Robot account permissions without requiring robot account replacement
Describe the solution you'd like
Permissions changes do not force harbor_robot_account replacement
  # harbor_robot_account.terraform must be replaced
-/+ resource "harbor_robot_account" "terraform" {
      ~ full_name   = "robot$terraform" -> (known after apply)
      ~ id          = "/robots/249" -> (known after apply)
        name        = "terraform"
      ~ robot_id    = "249" -> (known after apply)
      ~ secret      = (sensitive value)
        # (4 unchanged attributes hidden)

      + permissions { # forces replacement
          + kind      = "system"
          + namespace = "/"

          + access {
              + action   = "*"
              + effect   = "allow"
              + resource = "replication"
            }
        }
        # (1 unchanged block hidden)
    }

@sidewinder12s could please provide the terraform code?

It's been a bit since I touched this but it looks like it was a pretty stock harbor_robot_account.
resource "harbor_robot_account" "terraform" {
  name        = "terraform"
  description = "Robot Account for Terraform"
  level       = "system"
  permissions {
    access {
      action   = "*"
      resource = "robot"
    }
    kind      = "system"
    namespace = "/"
  }
  permissions {
    access {
      action   = "*"
      resource = "replication"
    }
    kind      = "system"
    namespace = "/"
  }
}

And any change to the permissions config triggered a full replacement of the robot account, which isn't great if you've put the creds for it places.
With version 3.1.9 of the provider.

Thank you sir!


Prepare version 2.1.1

Bump the version number and update the changelog for version 2.1.1.

Current coverage is 94.63% (diff: 100%)

Merging #118 into develop will not change coverage

@@            develop       #118   diff @@
==========================================
  Files             6          6
  Lines           373        373
  Methods           0          0
  Messages          0          0
  Branches          0          0
==========================================
  Hits            353        353
  Misses           20         20
  Partials          0          0

Powered by Codecov. Last update ae98993...6c8c2c5


Model loading fails on Apple Silicon Mac because of device = 0 in cpu mode

[x] I have confirmed this bug exists on the latest version of cell2location. See https://github.com/BayraktarLab/cell2location#installation
[x] I follow the instructions from the scvi-tools tutorial.

Minimal code sample (that we can run without your data, using public data)
Sorry I don't have a minimal working example right now because I am working on a notebook, so I am for the moment reporting the bug in case someone else is also finding it.
I have trained and saved a model, and then I try to load it with
adata_vis = ad.read_h5ad("mouse_brain.h5ad")
mod = cell2location.models.Cell2location.load("cell2location_model", adata_vis)

I am using an Apple Silicon Mac with the option
os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"

The load call causes a problem with PyTorch Lightning that tries to use a CPUAccelerator with devices=0, while it should be a int > 0.
Here is the full traceback.
TypeError                                 Traceback (most recent call last)
Cell In[31], line 1
----> 1 mod = RegressionModel.load("data/reference_signatures", adata_ref)

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/scvi/model/base/_base_model.py:721, in BaseModelClass.load(cls, dir_path, adata, use_gpu, accelerator, device, prefix, backup_url)
    716 getattr(cls, method_name)(
    717     adata, source_registry=registry, **registry[_SETUP_ARGS_KEY]
    718 )
    720 model = _initialize_model(cls, adata, attr_dict)
--> 721 model.module.on_load(model)
    722 model.module.load_state_dict(model_state_dict)
    724 model.to_device(device)

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/scvi/module/base/_base_module.py:394, in PyroBaseModuleClass.on_load(self, model)
    389 """Callback function run in :method:`~scvi.model.base.BaseModelClass.load` prior to loading module state dict.
    390
    391 For some Pyro modules with AutoGuides, run one training step prior to loading state dict.
    392 """
    393 old_history = model.history_.copy()
--> 394 model.train(max_steps=1, **self.on_load_kwargs)
    395 model.history_ = old_history
    396 pyro.clear_param_store()

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/cell2location/models/reference/_reference_model.py:157, in RegressionModel.train(self, max_epochs, batch_size, train_size, lr, **kwargs)
    154 kwargs["train_size"] = train_size
    155 kwargs["lr"] = lr
--> 157 super().train(**kwargs)

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/scvi/model/base/_pyromixin.py:174, in PyroSviTrainMixin.train(self, max_epochs, use_gpu, accelerator, device, train_size, validation_size, shuffle_set_split, batch_size, early_stopping, lr, training_plan, plan_kwargs, **trainer_kwargs)
    171     trainer_kwargs["callbacks"] = []
    172 trainer_kwargs["callbacks"].append(PyroJitGuideWarmup())
--> 174 runner = self._train_runner_cls(
    175     self,
    176     training_plan=training_plan,
    177     data_splitter=data_splitter,
    178     max_epochs=max_epochs,
    179     use_gpu=use_gpu,
    180     accelerator=accelerator,
    181     devices=device,
    182     **trainer_kwargs,
    183 )
    184 return runner()

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/scvi/train/_trainrunner.py:85, in TrainRunner.__init__(self, model, training_plan, data_splitter, max_epochs, use_gpu, accelerator, devices, **trainer_kwargs)
     83 self.lightning_devices = lightning_devices
     84 self.device = device
---> 85 self.trainer = self._trainer_cls(
     86     max_epochs=max_epochs,
     87     accelerator=accelerator,
     88     devices=lightning_devices,
     89     **trainer_kwargs,
     90 )

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/scvi/train/_trainer.py:139, in Trainer.__init__(self, accelerator, devices, benchmark, check_val_every_n_epoch, max_epochs, default_root_dir, enable_checkpointing, num_sanity_val_steps, enable_model_summary, early_stopping, early_stopping_monitor, early_stopping_min_delta, early_stopping_patience, early_stopping_mode, enable_progress_bar, progress_bar_refresh_rate, simple_progress_bar, logger, log_every_n_steps, **kwargs)
    136 if logger is None:
    137     logger = SimpleLogger()
--> 139 super().__init__(
    140     accelerator=accelerator,
    141     devices=devices,
    142     benchmark=benchmark,
    143     check_val_every_n_epoch=check_val_every_n_epoch,
    144     max_epochs=max_epochs,
    145     default_root_dir=default_root_dir,
    146     enable_checkpointing=enable_checkpointing,
    147     num_sanity_val_steps=num_sanity_val_steps,
    148     enable_model_summary=enable_model_summary,
    149     logger=logger,
    150     log_every_n_steps=log_every_n_steps,
    151     enable_progress_bar=enable_progress_bar,
    152     **kwargs,
    153 )

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/lightning/pytorch/utilities/argparse.py:70, in _defaults_from_env_vars.<locals>.insert_env_defaults(self, *args, **kwargs)
     67 kwargs = dict(list(env_variables.items()) + list(kwargs.items()))
     69 # all args were already moved to kwargs
---> 70 return fn(self, **kwargs)

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/lightning/pytorch/trainer/trainer.py:399, in Trainer.__init__(self, accelerator, strategy, devices, num_nodes, precision, logger, callbacks, fast_dev_run, max_epochs, min_epochs, max_steps, min_steps, max_time, limit_train_batches, limit_val_batches, limit_test_batches, limit_predict_batches, overfit_batches, val_check_interval, check_val_every_n_epoch, num_sanity_val_steps, log_every_n_steps, enable_checkpointing, enable_progress_bar, enable_model_summary, accumulate_grad_batches, gradient_clip_val, gradient_clip_algorithm, deterministic, benchmark, inference_mode, use_distributed_sampler, profiler, detect_anomaly, barebones, plugins, sync_batchnorm, reload_dataloaders_every_n_epochs, default_root_dir)
    396 # init connectors
    397 self._data_connector = _DataConnector(self)
--> 399 self._accelerator_connector = _AcceleratorConnector(
    400     devices=devices,
    401     accelerator=accelerator,
    402     strategy=strategy,
    403     num_nodes=num_nodes,
    404     sync_batchnorm=sync_batchnorm,
    405     benchmark=benchmark,
    406     use_distributed_sampler=use_distributed_sampler,
    407     deterministic=deterministic,
    408     precision=precision,
    409     plugins=plugins,
    410 )
    411 self._logger_connector = _LoggerConnector(self)
    412 self._callback_connector = _CallbackConnector(self)

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/lightning/pytorch/trainer/connectors/accelerator_connector.py:157, in _AcceleratorConnector.__init__(self, devices, num_nodes, accelerator, strategy, plugins, precision, sync_batchnorm, benchmark, use_distributed_sampler, deterministic)
    154     self._accelerator_flag = self._choose_gpu_accelerator_backend()
    156 self._check_device_config_and_set_final_flags(devices=devices, num_nodes=num_nodes)
--> 157 self._set_parallel_devices_and_init_accelerator()
    159 # 3. Instantiate ClusterEnvironment
    160 self.cluster_environment: ClusterEnvironment = self._choose_and_init_cluster_environment()

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/lightning/pytorch/trainer/connectors/accelerator_connector.py:390, in _AcceleratorConnector._set_parallel_devices_and_init_accelerator(self)
    382     raise MisconfigurationException(
    383         f"`{accelerator_cls.__qualname__}` can not run on your system"
    384         " since the accelerator is not available. The following accelerator(s)"
    385         " is available and can be passed into `accelerator` argument of"
    386         f" `Trainer`: {available_accelerator}."
    387     )
    389 self._set_devices_flag_if_auto_passed()
--> 390 self._devices_flag = accelerator_cls.parse_devices(self._devices_flag)
    391 if not self._parallel_devices:
    392     self._parallel_devices = accelerator_cls.get_parallel_devices(self._devices_flag)

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/lightning/pytorch/accelerators/cpu.py:48, in CPUAccelerator.parse_devices(devices)
     45 @staticmethod
     46 def parse_devices(devices: Union[int, str, List[int]]) -> int:
     47     """Accelerator device parsing logic."""
---> 48     return _parse_cpu_cores(devices)

File ~/miniconda3/envs/day4-YML/lib/python3.9/site-packages/lightning/fabric/accelerators/cpu.py:85, in _parse_cpu_cores(cpu_cores)
     82     cpu_cores = int(cpu_cores)
     84 if not isinstance(cpu_cores, int) or cpu_cores <= 0:
---> 85     raise TypeError("`devices` selected with `CPUAccelerator` should be an int > 0.")
     87 return cpu_cores

TypeError: `devices` selected with `CPUAccelerator` should be an int > 0.

Sorry for the lack of reproducibility of this bug, unfortunately I don't have time to make and it occurred as part of a notebook that I don't need. So I am just reporting to make the developers aware of this bug for Apple Silicon Macs and in case someone else wants to follow up.

Actually the bug triggers the error in pytorch_lightning code but seems to original from scvi code: at some points parse_device_args() from scvi/model/_utils.py returns the tuple
(_accelerator, _devices, device) == ('cpu', [0], torch.device('cpu'))

while it should return
(_accelerator, _devices, device) == ('cpu', 1, torch.device('cpu'))

I get the same error, @LucaMarconato did you ever find a solution to this? (I'm on an M2 Mac).
I trained the data no problem but when I load it as suggested in the tutorial with:
mod = cell2location.models.Cell2location.load(f'{run_name}', adata_vis)
The same 'TypeError' is produced.

Does this happen in a clean conda environment with github version of cell2location?

@vitkl thanks for the reply, I used a clean Conda env and installed cell2location and the problem was resolved.
I previously just pip installed cell2location and as Luca reported:
from scvi.model._utils import parse_device_args parse_device_args()
outputs: '('cpu', [0])'


Async Crypto Endeavour

@dignifiedquire I completely missed that this PR existed when making https://github.com/ipfs/interface-ipfs-core/pull/78 as I didn't thought there was a PR to update this repo when the remaining components necessary to actually run the tests where there yet, I'm sorry for duplicating work. When I got your ping in IRC, I was pretty close to an end (finished now) and solved some bugs in js-ipfs-api and dag-pb along the way.

Closing in favour of a new one


测试例子

能否提供更多的简单示例？

Hi, we appreciate English communication in this project, for the convenience of developers worldwide.
What's your issue when running the example?

Can you please provide more samples?

What kind of examples do you want? File IO ? HTTP server ?

Personally I think the echo server example is sophisticated enough...


Controlled Vocabulary IUCN SSC ISSG Invasiveness Vocabulary

http://oefendata.inbo.be/ipt/admin/vocabulary.do?id=http://rs.gbif.org/vocabulary/issg/invasiveness
&
http://oefendata.inbo.be/ipt/admin/extension.do?id=http%3A%2F%2Frs.gbif.org%2Fissg%2Fterms%2FDistribution
Added some sandbox extensions on the 'oefenIPT'. Not sure if these were already noticed.
Can we use this in one way or another?

Also this is a rather new extension:
http://oefendata.inbo.be/ipt/admin/extension.do?id=http%3A%2F%2Frs.gbif.org%2Fissg%2Fterms%2FPathways

Public versions:

http://rs.gbif.org/sandbox/vocabulary/issg/
http://rs.gbif.org/sandbox/extension/issg-distribution.xml
http://rs.gbif.org/sandbox/extension/issg-pathway.xml

This is standard related and I assume all of this will be discussed at the IAS session at TDWG, so I'm closing the issue here.


Add git commit to deployed previews

Currently just says "dev".
Would be nice to also make the hash a clickable link: https://github.com/commaai/connect/commit/<hash>.

#505


Generative VQVAE Model for the OASIS Dataset - s4698512

Name: Hugo Burton
Student Number: s4698512
This pull request implements a generative model of the OASIS dataset using a Vector Quantised Variational Auto Encoder. Please see the README file for more details regarding the model, implementation, usage and performance.
Task: Create a generative model of one of the OASIS brain, ADNI brain or OAI AKOA knee data set using a VQVAE or VQVAE2 that has a "reasonably clear image" and a Structured Similarity (SSIM) of over 0.6. [Hard Difficulty]
Model: A VQVAE model was implemented in Pytorch with 3 convolutional layers plus an additional two ResBlock layers in both the encoder and decoder, each with a hidden layer count of 128. Input and output images and 256x256 greyscale. A codebook with 32 latent embeddings was used in between the encoder and decoder.
Usage: Download the OASIS dataset and place it in a folder ../PatternAnalysisData/datasets/OASIS/. Ensure you are running in a conda environment with PyTorch installed. Some other dependencies are also required as documented in the README.
This pull request also features support for the ADNI dataset. Simply change the dataset variable in the train and predict modules to switch.
Performance: The model achieved a structured similarity of 0.849 on the test data.
Files Added:

README.md Report and overview of the VQVAE model, implementation, usage, results and performance
dataset.py Loads the OASIS and ADNI datasets and performs pre-processing
modules.py Contains all the model structure for the VQVAE as well as helper functions to handle backpropagation
train.py Driver script for training on the model
predict.py Reads a save file for the model and generates sample images as well as plots performance metrics about the model
./Assets figures and other data used in the README file.

This is an initial inspection, no action is required at this point
Difficulty: Hard
Readme:

Project Overview: Good
Model: Good
Data + Preprocessing: Good
Usage: Good
Training / Loss Curve(s): Good
Result Demonstration: Good, but no image generation results
References: Good

Functionality:

Reconstruction: Good
Generation: Not completed

Code:

Consistent with Results: Yes
File Structure: Good
Commenting: Good but could be a bit more descriptive
Commit frequency: Good
Commit messages: Good

Other Comments:
N/A

Marking
Good Practice (Design/Commenting, TF/Torch Usage)
Adequate design and implementation
Good spacing and comments
Header blocks
Recognition Problem
Solves problem (no generation) -1
Driver Script present
File structure present
Shows Usage & Demo & Visualisation & Data usage (no generation results) -1
Module present
Commenting
No Data leakage
Difficulty: Hard
Commit Log
Meaningful commit messages
Progressive commits used
Documentation
ReadMe acceptable
Model/technical explanation
Good Description and Comments
Markdown used and PDF submitted
Pull Request
Successful Pull Request (Working Algorithm Delivered on Time in Correct Branch)
No Feedback required
Request Description good


A bug with markdown.

all markdown output in one line? so it can not start a new line? and how tu fix it? THX!

That is how markdown works, it is not a bug. Documentation regarding line breaks and paragraphs: https://daringfireball.net/projects/markdown/syntax#p

@miguelgrinberg  ah ...get it , THX!


[api] Use request helper syntax

Updates this spec to utilize a helper method for this request
expectation.
Addresses https://github.com/ManageIQ/manageiq/pull/3846#discussion_r37579979

@abellotti Please review...this looks good to me.  Are there other places we can leverage these built-in methods?

@Fryguy just did an ag for last_response for api request specs and that's the only place where that's used

:cake:


Multiple single resources related to apterous Ichneumonidae

[x] https://www.zobodat.at/pdf/LBB_0027_1_0005-0105.pdf
[x] https://kerfdier.nl/19242/, https://kerfdier.nl/18849
[x] https://www.biodiversitylibrary.org/part/67675
[x] https://repository.naturalis.nl/pub/317552/ZV1966079001.pdf
[x] #17
[x] https://www.biotaxa.org/Zootaxa/article/view/zootaxa.4444.4.4

Continued in #17


[5.5] Allow for configuration of sticky databases

Allow https://github.com/laravel/framework/pull/20445 to be configurable
I can forsee edge cases where people might not want this functionality (i.e. doing a small write followed by unrelated large read in same request - such as an application that logs all user actions) - so we can easily make it configurable for those that want either behavior.
Also this way we preserve current behavior - because the config will be null on existing applications (since the value doesnt exist) - so this reduces risk of strange breaking behavior during a 5.5 upgrade.
Instead I propose to mention this new config option in the 5.5 upgrade guide, for those that want to enable it. And meanwhile I can do another PR for laravel/laravel to include it in the default config stack and in the docs.
I'll do the other PR's for you if this gets accepted.

So it will default to false / null I guess? That's your intention?

That's the idea. It means the current behaviour is kept, but we offer
the ability/knowledge to change during the upgrade.
My fear is issues being posted after 5.5 where people's prod
environment suffers due to heavy reads on the write database (if they
are doing both on the same cycle).
This gives the best of both worlds.
It could even be set to 'true' on Laravel/Laravel defaults - so new
apps get the benefit. Just existing ones won't get hit...


Convenient BSON factory functions (micro-DSL)

To create following BSON doc:
{ "name": "Johny", "surname": "Doe", "age": 28, "months": [1, 2, 3] }

import reactivemongo.bson._
document ++ ("name" -> "Johny") ++ ("surname" -> "Doe") ++
  ("age" -> 28) ++ ("months" -> array(1, 2, 3))

// Instead of :
BSONDocument() ++ ("name" -> "Johny") ++ ("surname" -> "Doe") ++
  ("age" -> 28) ++ ("months" -> array(1, 2, 3))

Just a minor syntax sugar about BSONDocument() with document.

To create a more complex doc:
{
  "_id": generatedId,
  "name": "Jane",
  "surname": "Doe",
  "age": 28,
  "months": [1, 2, 3],
  "details": {
    "salary": 12345,
    "inventory": ["foo", 7.8, 0, false]
  }
}

document(
  "_id" -> generateId,
  "name" -> "Jane",
  "surname" -> "Doe",
  "age" -> 28, "months" -> (array ++ (1, 2) ++ 3),
  "details" -> document ++ (
    "salary" -> 12345L,
    "inventory" -> array("foo", 7.8, 0L, false)
  )
)

@cchantep ReactiveMongo-Extensions already provides a complex DSL. Are you sure about bundling this with ReactiveMongo?

I think that's sufficiently minimal to be provided without external dependency.

+1


Try out Huggingface's transformers

Notes:

batch_size = 2 is the highest it can be set to
No multi GPU support (AFAIK)

No confidence output. Possible solution: https://discuss.huggingface.co/t/get-scores-from-whisper-using-asr-pipeline/53821 (although I have to keep in mind that the author says it fails. Maybe it can work somehow; I will try it myself also)

UPDATE: The output does not contain the confidence/probability scores. Additional tuning of the code might be required, which is not practical. However, we will proceed with this implementation as it still contains word-level timestamps.


Icons for all

Jeez, that there's no simple solution for the jungle of icons needed for various platforms still strikes me as ..... perfectly understandable.

I thank my lucky stars that other developers have created some helpful tools to generate them rather quickly, but you're not wrong...

Don't you worry, bot, I'll be doing so, soon.


Attack of the Error Uploading Message

I was trying to help troubleshoot a separate issue today, where someone was mentioning that when they change the background of an unpublished theme, it's also changing the live theme on their store. I haven't substantiated that yet. I do see another issue about not being able to upload themes which I have heard as well (will create separate issue once I have more details).
While looking into the first issue I mentioned though, I attempted to test changing a file, then using force deploy and I got this which attacked my screen until I was able to close out of the app (fresh install):

@meeech is there anywhere else those log files would be located(other then where you mention in the Readme?) I'm not able to find them at all.
Personally, I'm using Version 1.0.6 (1.0.6) with OS X El Capitan 10.11.1 - I'm wondering if maybe there's an issue with the latest OS release. I'll update once I know the OS of others who are facing issues.

hey @alanhill definitely not a good thing. It looks like as access issue. topped with the fact I am expecting an array of errors, but am instead getting a string, which is then sent out one at a time. Look closely at those last letters - they seem to be complaning about bad password  or whatnot - so I will def add a fix to that.
NO idea where else on el capitaine the logs would be. I'm still on 10.10
let me know when you have some more info

Hey @meeech was able to replicate this in OS X 10.11.3 El Capitan - found some log files for these errors as well. Looks like it's hitting an Unauthorized error on the PUT. Could you take a look?
[15:34:33:426] [Ti.Host] [Information] Loaded module = app
[15:34:33:427] [Ti.Host] [Information] Loaded module = codec
[15:34:33:428] [Ti.Host] [Information] Loaded module = database
[15:34:33:429] [Ti.Host] [Information] Loaded module = filesystem
[15:34:33:430] [Ti.Host] [Information] Loaded module = media
[15:34:33:431] [Ti.Host] [Information] Loaded module = monkey
[15:34:33:435] [Ti.Host] [Information] Loaded module = network
[15:34:33:437] [Ti.Host] [Information] Loaded module = platform
[15:34:33:439] [Ti.Host] [Information] Loaded module = process
[15:34:33:442] [Ti.Host] [Information] Loaded module = ui
[15:34:33:444] [Ti.Host] [Information] Loaded module = worker
[15:34:33:485] [Ti.Host] [Information] Loaded module = php
[15:34:33:486] [Ti.JavaScript] [Information] Loading JS path=/Users/Test/Downloads/Shopify Theme.app/Contents/modules/filesystem/1.3.1-beta/tifilesystemmodule.js
[15:34:33:488] [Ti.Host] [Information] Loaded module = tifilesystem
[15:34:33:488] [Ti.JavaScript] [Information] Loading JS path=/Users/Test/Downloads/Shopify Theme.app/Contents/modules/network/1.3.1-beta/tinetworkmodule.js
[15:34:33:491] [Ti.Host] [Information] Loaded module = tinetwork
[15:34:33:491] [Ti.JavaScript] [Information] Loading JS path=/Users/Test/Downloads/Shopify Theme.app/Contents/modules/process/1.3.1-beta/tiprocessmodule.js
[15:34:33:492] [Ti.Host] [Information] Loaded module = tiprocess
[15:34:33:663] [Ti.API] [Information] Fixing perms on: /Users/Test/Downloads/Shopify Theme.app/Contents/Resources/lib/watch_server.rb
[15:34:33:666] [Ti.API] [Information] No upgrade required
[15:34:34:096] [Ti.API] [Information] appView: Initializer
[15:34:34:102] [Ti.API] [Information] appView: render
[15:34:34:102] [Ti.API] [Information] render shop id:shopify-dev
[15:34:34:103] [Ti.API] [Information] ShopView: initializer
[15:34:34:104] [Ti.API] [Information] Render Shopview
[15:34:34:360] [Ti.API] [Information] Port Available.

Permissions seem to be good. App is installed on shop, and full access user. Anything else that could cause this?

@audition still happening? Canyou upload scss directly? or do they need to be .scss.liquid?


Breaking change "/" as division with<EMAIL_ADDRESS>

Using Foundation for sites 6.6.3 with sass 1.33.0 throw a lot of deprecation warnings in the console output.

See:

https://github.com/sass/dart-sass/blob/be1a414f07bdc2a862ead7d349f2195216dbf6dc/CHANGELOG.md#1330
https://sass-lang.com/documentation/breaking-changes/slash-div

@DanielRuf, should I open a dedicated pull request for that to bump the current 6.6.3 version? Thanks!

@DanielRuf, should I open a dedicated pull request for that to bump the current 6.6.3 version? Thanks!

Which version do you want to bump? Afaik we don't use dart-sass in this project. I guess you mean a PR to migrate / update all the relevant code parts to use math.div(), correct?
If so, is this compatible with all previous Sass versions?

@DanielRuf Exactly. Sounds like the latest sass replace all the / divisions with math.div. I need to check if this is supported by old sass version. I will let you know soon. A bump version from 6.6.3 to 6.6.4 should be enought.

Typo about dart sass, sorry!

A bump version from 6.6.3 to 6.6.4 should be enought.

I'm not involved in Foundation Sites anymore so @joeworkman has to do this then.

Hey @DanielRuf, sad to hear :crying_cat_face:
It looks like math.div has been introduced in<EMAIL_ADDRESS>as described here:

https://sass-lang.com/documentation/modules/math#div
https://github.com/sass/dart-sass/releases/tag/1.33.0

I am using Foundation in a webpack project that run sass (meaning "dart sass") for the compilation, and all the warnings comes from the fact that current<EMAIL_ADDRESS>version is using "/" as a division operator.

Note that there is a sass migration tool to migrate.

cc @joeworkman

According to the note it is not supported by libsass / node-sass.
Not sure how many already use sass instead of libsass / node-sass.
https://www.npmjs.com/package/node-sass
Dart Sass
since 1.33.0
LibSass
✗
Ruby Sass
✗
That makes it hard(er) to support all users.
For me this looks like a major change as it is also documented as breaking change by the sass language team.
https://sass-lang.com/documentation/breaking-changes/slash-div
Personally I would not bump the patch version of Foundation Sites, because this could break many setups which use ~ or even ^ SemVer selectors for Foundation Sites.

Both node-sass and libsass are deprecated, see https://github.com/sass/node-sass#node-sass.
The core webpack team recommend using dart-sass for all new web projects since many years.

Right, but I try to understand what the consequences for all Foundation Sites projects will be.
See also our template projects:
https://github.com/foundation/foundation-sites-template/blob/master/package.json#L28
https://github.com/foundation/foundation-zurb-template/blob/master/package.json#L35
https://www.npmjs.com/package/gulp-sass?activeTab=dependencies (uses node-sass 4.x)
https://github.com/dlmanning/gulp-sass/blob/master/package.json#L29
https://github.com/sass/node-sass/tree/v4.14.1

An update to dart-sass did reduce the number of deprecation warnings by a lot. See: https://github.com/sass/dart-sass/releases/tag/1.34.0
Might this be something to upgrade in version 7? As that would be fitting because of the major upgrade.

Hi @pataar! Yes, I am just discovering that, thanks :wink:
But the fact is that it's not acceptable to work with those kind of deprecation warnings all the time.
Last Foundation version was released a year ago, and from my point of view it would be better to patch this kind of "easy issue" and move Foundation forward instead of accumulate a lot of issues/features that would increase the migration process later.
Having a 6.7.0 version should be better :thinking: ?

It's a breaking change IMO, as certain versions and libraries would be suddenly incompatible

Ok so this should be part of Foundation v7 #11847, agree with that.

I'm going to ask the obvious question, if this gets bumped to Foundation v7, what is the time frame for that release.
It doesn't look all that imminent. Is it likely to be this year?
Because having this SASS problem for another 6+ months is going to be a problem.

cc @joeworkman

Problem is that in that specific case, we are "stuck" to<EMAIL_ADDRESS>and can't update our version without having log output in the terminal. This is a problem when using tools like Github Actions where log output can be full of warnings.
Thanks for taking the time to give a clear answer to the community :wink:

For those running into this with dart SASS, there is a work around.
They have added a flag to suppress the deprecated warnings.
--quiet-deps
Add that to the command line and make sure that foundation is in the load-path of the command line. Any relative paths in your SASS will cause the warnings.
https://github.com/sass/dart-sass/issues/672
This is a work around of course, it would be better to have a new version of Foundation in which this is not present.

@katie1348 I know about this flag, but it's a CLI flag, and I am running sass through a sass-loader with webpack, and there is not dart-sass javascript option at this time to quiet warnings.

It's unfortunate, that there are multiple ways of running sass, but only one supports the flag.
I don't know of any other solution sorry.
I hope that this gets sorted out soon, as it is proving very disruptive and not being able to easily switch it off is a huge problem. I appreciate the need to provide warning about a breaking change, but this seems to be a break everyones workflow way of doing.

Sorry for the delay. I was heads down getting a project shipped. Finally got it done last night. I think that @katie1348's suggestion is the best at this time. As I work on F7, I will ensure that the Sass side works perfectly with dart-sass. At this point, trying to get F6 warning free with dart-sass feels like a fruitless effort. I would rather put that time and energy into working on F7.

Thanks @joeworkman! :sunglasses:
I let you close this issue or pinned to Foundation v7 Github project.
Waiting for the next major release right now :coffee: :kissing_heart:


Error [ERR_UNSUPPORTED_DIR_IMPORT] when trying to use @heroicons/vue with histoire

Describe the bug
When importing Hero Icons from the @heroicons/vue in a Histoire story, histoire will throw the following error:
Error [ERR_UNSUPPORTED_DIR_IMPORT]: Directory import '/node_modules/@heroicons/vue/24/outline/esm' is not supported resolving ES modules imported from /node_modules/vite-node/dist/client.mjs

npm run dev and npm run build are both able to load the icons in Vue components. This error is only present when running npm run story:dev and npm run story:build
Reproduction
This is a StackBlitz link that reproduces the error: https://stackblitz.com/edit/histoire-vue3-starter-zyx8z5?file=package.json
Unfortunately the error StackBlitz shows is different from the one node shows, so I have also added the code to a GitHub repo so it can be run locally. https://github.com/nfaucher8/histoire-heroicons-example
Also this example shows that when running the same project with older versions of the dependencies the error is not present https://stackblitz.com/edit/histoire-vue3-starter-rmib7n?file=package.json
System Info
System:
    OS: macOS 13.6.2
    CPU: (10) arm64 Apple M1 Max
    Memory: 3.17 GB / 64.00 GB
    Shell: 5.9 - /bin/zsh
  Binaries:
    Node: 18.18.2 - ~/.nvm/versions/node/v18.18.2/bin/node
    Yarn: 1.22.19 - /opt/homebrew/bin/yarn
    npm: 9.8.1 - ~/.nvm/versions/node/v18.18.2/bin/npm
    pnpm: 7.30.0 - /usr/local/bin/pnpm
  Browsers:
    Chrome: 119.0.6045.105
    Firefox Nightly: 77.0a1
    Safari: 16.6
  npmPackages:
    @histoire/plugin-vue: ^0.17.12 => 0.17.12
    @vitejs/plugin-vue: ^5.0.4 => 5.0.4
    histoire: ^0.17.9 => 0.17.9
    vite: ^5.1.4 => 5.1.4

Used Package Manager
npm
Validations

[X] Follow our Code of Conduct
[X] Read the Contributing Guidelines.
[X] Read the docs.
[X] Check that there isn't already an issue that reports the same bug to avoid creating a duplicate.
[X] Check that this is a concrete bug. For Q&A open a GitHub Discussion.
[X] The provided reproduction is a minimal reproducible example of the bug.

I have run into this issue too. Trying to work out what is going wrong. At the moment from what I can see the package milly's isValidNodeImport is returning false for heroicons imports on the non-working reproduction you link and true on the new versions which then treats heroicons as an externalized module and is causing errors.
isValidImport on older versions
/Users/gerard/Downloads/histoire-vue3-working/node_modules/@heroicons/vue/24/outline/esm false

isValidImport on newer versions
/Users/gerard/Downloads/histoire-vue3-broken/node_modules/@heroicons/vue/24/outline/esm true

I believe this issue is because histoire is using quite an old version of vite-node. The _shouldExternalize function in vite-node doesnt seem to play nicely with this newer mlly version that is being used.

This issue can be worked around for now by pinning the version of mlly:
"mlly": "1.4.2",

Ran into the same issue.

1.4.2

This does help indeed, thank you.

Just reported a possibly related issue when using csv-parse: https://github.com/histoire-dev/histoire/issues/712


systemctl should log to stdout/stderr

hi,
around line 600 I see the code below
	if ($pid == 0) {
		open(STDOUT, '>>', '/var/log/systemctl.log');
		open(STDERR, '>>', '/var/log/systemctl.log');
		open(STDIN, '<', '/dev/null');
		POSIX::setsid();
		exec "$ENV@paths";
	}

but it's good for containers to log to /dev/stderr and /dev/stdout instead of files
to avoid writing to containers files (overlayfs / device mapper)
and to allow logs to be collected later by host logging like docker logs -f and hosts journald
I can send pull request but I believe the fix is obvious.

The /var/log is a symlink to /data/var/log so the logs do not end up in overlayfs / devicemapper backends.
In the master-systemd branch we move to the native systemd/systemctl, so we will be able to have proper solution there. In the current master, I prefer to keep the logging the way it was from the beginning, not to disrupt people's existing setups.


Add branding for Canada Economic Development for Quebec Regions

Summary | Résumé

Adds Canada Economic Development for Quebec Regions branding
Also fixed #2121

Settings

En

Fr

https://github.com/cds-snc/platform-forms-client/pull/2218/files#diff-731b2b567e4a5089f2a8f3ba33e8f5ef8a71257768e9e1da25de9c37f761519aR94
Test instructions | Instructions pour tester la modification

Create a new form
Set branding to Canada Economic Development for Quebec Regions

Pull Request Checklist
Please complete the following items in the checklist before you request a review:

[x] Have you completely tested the functionality of change introduced in this PR? Is the PR solving the problem it's meant to solve within the scope of the related issue?
[x] The PR does not introduce any new issues such as failed tests, console warnings or new bugs.
[ ] If this PR adds a package have you ensured its licensed correctly and does not add additional security issues?
[ ] Is the code clean, readable and maintainable? Is it easy to understand and comprehend.
[ ] Does your code have adequate comprehensible comments? Do new functions have docstrings?
[ ] Have you modified the change log and updated any relevant documentation?
[ ] Is there adequate test coverage? Both unit tests and end-to-end tests where applicable?
[ ] If your PR is touching any UI is it accessible? Have you tested it with a screen reader? Have you tested it with automated testing tools such as axe?

Nothing there's a bug with the form preview showing the incorrect logo
EN

FR


Add the possibility of changing key store location of Mbed Crypto provider

Keys are currently stored where the service is run but there should be a configuration parameter to choose where.
Is only possible after #38

Instead of using the "native" mbed crypto storage, we could/should use PSA Trusted Storage: https://github.com/ARMmbed/psa_trusted_storage_linux
https://confluence.arm.com/display/mbedlinux/PSA+Storage+Software+HLD

Managed to link in PTSL with the following steps:

unset MBEDTLS_PSA_ITS_FILE_C in Mbed Crypto (include/mbedtls/config.h)
clone PTSL and add a step in the lib Makefile to create libpsastorage.a
build Mbed Crypto, including the PSA ITS headers and linking to libpsastorage.so (CFLAGS="-I<...>/psa_trusted_storage_linux/inc/" LDFLAGS="-L/usr/local/lib/ -lpsastorage")
update build.rs to include the path to libpsastorage.a in the link path and to also link statically against the storage library

Thus, if we want to use PTSL, we might require to push an upstream patch to allow for a static library to be built "natively".

I guess we should transfer this issue to the psa-crypto repository now? Or is it no longer needed?

No, I think this is Mbed Crypto-specific, for our provider. I think every PSA lib will have its own thing

Is this still wanted you think? As the Mbed Crypto is something just for protyping/tests I am wondering if that's worth it. Also feels wrong to add Mbed Crypto specific things in a provider that could maybe be one day PSA generic.

Yeah, I came across the issue a few days ago and was wondering the same. I'd be ok with just closing this, we've not had requests for it.

Also feels wrong to add Mbed Crypto specific things in a provider that could maybe be one day PSA generic.

Well, given that the provider is called Mbed Crypto Provider, I'd say that approach is ok to take. But not today.


test:integration fails on travis

See for example https://travis-ci.org/datproject/dat-desktop/jobs/212894584
Since they're passing locally (they do for me), this might best be investigated running the travis environment on your machine via docker and seeing what's going on. See https://docs.travis-ci.com/user/common-build-problems/#Troubleshooting-Locally-in-a-Docker-Image for a manual.
I removed the test:integration target from test for now, so our builds work again.

Yeah sounds reasonable
On Tue, Mar 21, 2017 at 8:39 AM Julian Gruber<EMAIL_ADDRESS>wrote:

See for example
https://travis-ci.org/datproject/dat-desktop/jobs/212894584
Since they're passing locally (they do for me), this might best be
investigated running the travis environment on your machine via docker and
seeing what's going on. See
https://docs.travis-ci.com/user/common-build-problems/#Troubleshooting-Locally-in-a-Docker-Image
for a manual.
I removed the test:integration target from test for now, so our builds
work again.
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.

@karissa do you have any ideas here?

Heyo,
Figuring out how to re enable our integration tests and writing new ones will be important to reduce chance of regressions.. it's unclear how Travis is failing us here.

my guess is because the window is created in a virtual frame buffer...I've noticed the integration tests failing locally when you switch to other windows while they're running

WIP pull request here: https://github.com/datproject/dat-desktop/pull/344

nice!


README: There is no stable repository, just unstable.

Previously, the README mentioned two repositories, one stable and one unstable. However, the stable one is empty and therefore not used. Furthermore, clarified what the term 'distro-name' refers to.

Well, currently you're correct. But it's all prepared so that a release can be promoted to the stable repo. Not sure it's worth removing the info now.

By the way, the stable folder contains a very large, 4 GByte file called oci. Not sure if that is intended.

It is, please drop me an e-mail if you want to know more.

it's all prepared so that a release can be promoted to the stable repo

That is OK. However, then the example below should be consistent and use stable as well. Furthermore, until that release, I would use unstable for both. I took me quite a while to understand this. And at the start, I went for the not yet used repository.


Google cloud run volume mounting

Documentation description
I run DLT in google cloudrun and have noticed when I load big tables it can get OOM even if it writes to files, as cloudrun doesn't have any "real" storage. What I've been doing instead is mounting a storage bucket and using pipeline_dir to direct the pipeline to use that as the directory. This seems to work well for me in the cases I've tested. But I've also seen that there are limitations with mounting a storage bucket as a directory, listed here https://cloud.google.com/run/docs/configuring/jobs/cloud-storage-volume-mounts . It would be good to have someone who knows how DLT works under the hood take a look at this and see if these limitations might cause issues (For example if two or more processes/ threads would write to the same file etc). If the limitations wouldn't cause issues I think it would be nice to include a section about it here
https://dlthub.com/docs/walkthroughs/deploy-a-pipeline/deploy-with-google-cloud-run
to help other in the future.

Yes, I run dlt in production.

@loveeklund-osttra dlt works correctly on mounted volumes. indeed there are limitations ie. lack of atomic renames. we are pretty sure we work with GCP mounted volumes: Composer maps data folder like this we support keeping working directories there.
lack of atomic renames may be a problem in certain cases. in your case AFAIK you'll start with always clean storage so you should not have problems with half commited files from previous runs.
you can also look at #2131 if you can read your data in the same order you'll be able to extract it chunk by chunk

Perfect, then I'll continue using it! Thanks for response!
I don't think it start with an empty folder if I just mount a volume, ( it uses same directory between runs and I can see previous runs content in storage after it is complete) but I call pipeline.drop() in the start anyways so shouldn't be a problem for me.
If you decide to add this into the documentation it can be worth mentioning that you probably  want to up the rename-dir-limit . Otherwise it shows an error( I assume from when it tries to move files between directories), but complete anyways.
I did it like this in terraform
     volume_mounts {
          mount_path = "/usr/src/ingestion/pipeline_storage"
          name       = "pipeline_bucket"
        }
      volumes {
        name = "pipeline_bucket"
        gcs {
          bucket    = google_storage_bucket.dlt_pipeline_data_bucket.name
          read_only = false
          mount_options = [
            "rename-dir-limit=100000"
          ]
        }
      }

Also described here
https://cloud.google.com/run/docs/configuring/services/cloud-storage-volume-mounts .
Re https://github.com/dlt-hub/dlt/pull/2131
Most of my data is from sql-databases / apis and I have experimented a bit there with chunking using limit. One thing noticed with that though  is that it seems like it "recreates" the generator, so It will run the query again every time I call pipeline.run() . So I don't really know when to stop updating, I guess I could do something like loaded_rows < limit, but a more "inbuilt" way to do it would also be nice, but might be super difficult to actually implement (haven't looked into the code).

thx for the doc suggestion. I added that to our performance guide.
yes we recreate the whole extract step when you use add_limit. if you have incremental loading enabled, we are able to do a WHERE query that will skip already loaded rows. make sure you set row_order to ASC in incremental. (and you need to wait for the PR above to be merged...)
then you can run your pipeline in a loop as long as there's a load_package in load_info you get from pipeline.run. no load package indicates no more data. you can also inspect the load metrics in load_info to get the number of rows processed

He, just wanted to come back to this, I've run with fuse now for a while and noticed that while it writes out files to storage buckets, it seems like it doesn't "flush" the files from memory ( it is as if they stay in a cache until the process quits). Meaning that it can still go OOM if the total size of all files loaded if more than the container limit. This seems to not be tied to DLT, I have tested just writing out files with a simple python script and I experience the same thing there. There might be some setting that I've missed in configuring GCSfuse, I'm looking into it. I just thought I'd let you know so you can adjust any documentation accordingly.


Free mass barsprings!


Update nuxt-loading-indicator.ts

Opacity controlling is unnecessary here to avoid hydration issue.
🔗 Linked issue

📚 Description

Would you provide a bug report/reproduction?
(Or a test for this PR?)


SW-102 Switch 1/2/3 gang Switch modules

I have amazon smart life SW-102 Switches 1/2/3 gang Switch modules.
Main Module: 1.0.2
mcu module: 1.0.2
images
sw-102-2

sw-102-1

The closest profile is generic switch 102 however it's on a different version (main/mcu).
Can these be added?

It looks like you have two different devices with two different modules, you'll need to check the firmware version on each one of them.  Without a firmware dump, we can't directly add support for new devices (see https://github.com/tuya-cloudcutter/tuya-cloudcutter#device-dumps for information on dumping firmware), however you can try by firmware version and name.
Feel free to re-open this ticket if you are able to provide firmware dumps for these devices for support to be added.


Prepare release of v4.0.2

Description
Prepare for v4.0.2
When it get's merged we will create the new tag, build the image, update OLM channels repo etc.

Thanks for the pointers @pb82 i have fixed the label generation and I have manually edited so the operator-sdk is called v1.13.1.
Please have a second look


How can a window with two cells merged?

How can a window with two cells merged  like below
+-----------+
|           |
+-----+-----+
|     |     |
+-----+-----+

Thank you for great splitter control!

For this, 2 SplitterCtrl objects should be used.

Create a SplitterCtrl with two cells vertically.

+-----------+
|           |
+-----+-----+
|           |
+-----+-----+

Create and place another SplitterCtrl with two cells horizontally in the bottom cell.

                  +-----------+
                  |           |
+-----+-----+     +-----+-----+
|     |     | ----|---->      |
+-----+-----+     +-----+-----+

But also MultiPaneCtrl can be used for this task. Just set the 'Hide single tab' property to it.

Thank you for your reply!
I understand what should I do for I have to do.
and Finally, I have one more question. What should I do when I set the
reisze mode to static and I want to designate a cell whose size needs to
change as a middle cell?
2023년 5월 18일 (목) 오전 9:34, Aleh Baradzenka @.***>님이 작성:

For this, 2 SplitterCtrl objects should be used.

Create a SplitterCtrl with two cells vertically.

+-----------+
|           |
+-----+-----+
|           |
+-----+-----+

Create and place another SplitterCtrl with two cells horizontally
in the bottom cell.
        +-----------+
        |           |

+-----+-----+     +-----+-----+
|     |     | ----|---->      |
+-----+-----+     +-----+-----+
But also MultiPaneCtrl https://github.com/baradzenka/MultiPaneCtrl can
be used for this task. Just set the 'Hide single tab' property to it.
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Not able to query "day of week" for sessions on TheSession.

On the webpage of TheSession, you can query day of week:
https://thesession.org/sessions
But we don't have this data in the dumped CSV.
I tried using SPARQL query with ChatGPT's help, but neither of its solution worked.
[Solution 1]
prefix wdt: <http://www.wikidata.org/prop/direct/>
select * from <http://sample/thesession/reconciled/updated>
where {
  ?session a <https://thesession.org/sessions>;  # Asserting the type is important
           wdt:P17 "Australia";
           wdt:P2561 ?name;
           wdt:P585 ?date.

  # Convert the date to xsd:dateTime
  BIND(xsd:dateTime(?date) AS ?dateTime)

  # Filter for Sundays (DAYOFWEEK returns 7 for Sunday)
  FILTER(DAYOFWEEK(?dateTime) = 7)
}
limit 20

[Solution 2]Use some indirect approach(math method).

Please add day-of-the-week to the RDF during CVS2RDF.
Use Python's datetime object.

This will be fixed together with the datetime recognition PR.


MailTrackerBlocker and GPG Mail Extension do not work together

Describe the bug
If MailTrackerBlocker extension is activated the extension for GPG Mail does not work in Mail (macOS Sonoma 14.5).
To Reproduce
Steps to reproduce the behavior:
Deactivating MailTrackerBlocker let's GPG Mail work again
Activated MailTrackerBlocker extension causes problems with GPG. I see the encryption button in Mail, but it can't be activated. Encrypted e-mails cannot be decrypted. The extension of GPG Mail does not work.
Environment (please complete the following information):

OS: macOS Sonoma 14.5
Other enabled plugins/extensions: GPG Mail and SpamSieve (that does work with GPG Mail)

Additional context
Add any other context about the problem here.

Yes, here is the same situation.

This repo is for the older mail plugin. Moved this to https://github.com/apparition47/MailTrackerBlockerApp/issues/20


Support YAML groups/profiles

It would be nice if bootcfg would again support YAML groups and profiles. Valid JSON is hard to generate, while YAML can be generated more easily from simple templates.
E.g. when building a group config file, JSON is harder to generate:
{
  "thearray": [
    "element1",
    "element2"
  ]
}

than YAML, because one does not have to deal with preventing trailing commata:
thearray:
- element1
- element2

From IRC:
My aim is for the bootcfg objects (profiles, groups, ...) to have a single JSON representation in the store (filesystem, etc). Those objects can be written by hand in /var/lib/bootcfg (typical case today) but problems like with commas are best addressed by higher level tools talking to the gRPC API (the CLI, graphical apps, etc.) That's not to say the CLI couldn't allow YAML as the input type potentially. bootcmd group create -f mygroup.yaml but at the storage layer I'd avoid YAML.

If it would be helpful, I can see a case for the CLI allowing a YAML format, similar to how Kubernetes does. That should be a separate issue. Any interest in adding it since I can't prioritize that for a while?
bootcmd group create -f mygroup.yaml

The implementation should use CoreOS' Fuze for conversion? If not, what other YAML-to-JSON conversion library do you (CoreOS) use usually?
How do you usually deal with different formats? Try different parsers until one succeeds (I'd call that the Unix style), and if none succeeds, output the parsing errors of all of them? Or do you just use the parser that is associated with the file extension (which I would call the Windows style)?


Grouping problem with ui-grid - v3.0.0-rc.22

I updated ui grid from  ui-grid - v3.0.0-rc.21 to  ui-grid - v3.0.0-rc.22 and suddenly my grouping stopped working I have it setup as follows:

 in gridOptions:

        grouping: {
          aggregation: uiGridGroupingConstants.aggregation.SUM
        },
        groupingSuppressAggregationText: true,
        cellFilter: 'floatFilter:' + decimals

  ...

in app.js:

   .filter('floatFilter', function() {
    return function(value, decimals) {

      if (value.toFixed !== undefined)
        return value.toFixed(decimals);
      else
        return value;

    };
  });

Value comes in floatfilter is always undefined for the grouped item. Anyone know what is wrong. What has been changed?

I see there is a customTreeAggregationFinalizerText now but can't figure out how this works.


Performance difference between Debug and Release build

New issue checklist

[X] I have reviewed the README and documentation
[X] I have searched existing issues and this is not a duplicate

General information

IGListKit version: 3.1.1
iOS version(s): 10.3
CocoaPods/Carthage version:
Xcode version: 8.3.2
Devices/Simulators affected: All
Reproducible in the demo project? (Yes/No):
Related issues:

Debug information
# Please include debug logs using the following lldb command:
po [IGListDebugger dump]

Hello I am having a major performance difference between creating Debug builds and creating Release builds. While in debug performUpdates(animated:completion:) runs in the milliseconds. Once I change my scheme settings to build release, my performance of the above method goes to seconds and scrolling becomes near impossible. Is there any known reason for this? I checked the debug statements of my code and nothing that I have should impede on the perform of the scrolling nor performUpdates.
One thing I noticed between the Debug build and the Release build is that the - (void)collectionView:(UICollectionView *)collectionView willDisplayCell:(UICollectionViewCell *)cell forItemAtIndexPath:(NSIndexPath *)indexPath is called an extremely large amount of times in Release vs Debug (Debug calls it only when needed while Release calls it to the point that my console can't even keep up with it). I am calling performUpdates maybe once or twice, but every scroll or load on the page causes that method to fire a lot.

Figured out the issue, I was using a helper method that counted the number of items in an enum. This method performed differently in Release than it did in Debug causing it to result in a much higher number for the ListSectionController.numberOfItems() call.

@DMCApps thanks for following up! I'm really curious what about the release build made it slow?
Sent with GitHawk

@rnystrom I didn't investigate the extension mentioned above too thoroughly, but the extension that I list above would return 256 for an enum with 3 items in it in Release, but in Debug would return 3.
e.g.
enum SectionContent {
    case row1
    case row2
    case row3
}

// In ListSectionController
...
func numberOfItems() -> {
    return SectionContent.elementsCount // returned 3 in Debug, returned 256 in Release.
}
...

This basically cause the collection view to create and attempt to display 256 cells in one section which  I had a default size of CGSize(width: width, height: 0) and a default cell of one of my custom cell types returned and had 3-4 section on the screen so it basically attempted to render over 1000 cells at any given time which brought the UI to an abrupt stutter.

Ah! Good to know.
Sent with GitHawk


Not working in rails 5.0.2

I use early byebyg and web_console - all work correct. At now i want use this gem, but browser return defaul rails errors pages. My settings
  BetterErrors.editor = :sublime
  config.consider_all_requests_local = true

  BetterErrors::Middleware.allow_ip! "<IP_ADDRESS>/0"

I use it from my local pc - not virtualbox, docker and similar. Why its not working?

Were you able to figure out a work around or fix? Just starting a new rails 5 project and I would like to use better errors with it...

Sounds like the issue in #371, can you confirm?

Version 2.2.0 of the gem has been released, so assuming this is the same as #371, this issue seems to be fixed.


Autoplug can't update velocity plugins. Add support for reading velocity-plugin.json

Importance: 5/10
Problem:
Autoplug is unable to update Velocity plugins because velocity plugins use a velocity-plugin.json instead of a plugin.yml
Solution:
Make it so that when the server type is set to velocity it looks for a velocity-plugin.json instead of a plugin.yml file and pulls the version from there instead.

supported in 5.11.0


Revising Metric: Issues New

Name of the Metric Being Revised
Issues New

Website: https://chaoss.community/metric-issues-new/
File: https://github.com/chaoss/wg-evolution/blob/main/focus-areas/issue-resolution/issues-new.md

Link to Original Metric Release Issue
Original Issue: https://github.com/chaoss/wg-evolution/issues/286
Specific Metric Details that Require Attention

There is no "Tools" section, nor a mention of Grimoire Lab or Augur at all
This is one of our more heavily referenced metrics, so we should read through it to make sure it meets our standards. It hasn't been reviewed in years.
Definitions are in "Data Collection Strategies" but they should be in the "synonyms" section
There are "parameters" which seem like they could be filters to me

Checklist

Process

[x] Create the “revising metric” labeled issue in the authoring WG’s repo for comments during review period
[ ] Create pull request of revised metric to WG’s repo (after checking Content Quality and Technical Requirements below)
[ ] Add the metric revision to release notes issue in working group repo
[ ] Update the Metrics Spreadsheet to indicate that the revised metric is under review
[ ] Create issue in CHAOSS/Translations repository to kick-off translation to other languages (please use the the translation issue template)
[ ] "Metric Candidate Release" label added to the metric release candidate issue when fully ready fo release

When above steps are completed:

[ ] Announce new/updated metric on mailing list, newsletter, community Zoom call, and Twitter. This can be coordinated with the community manager and can be done as a collective of all revised metrics from the CHAOSS community.

Content Quality (check all that apply)

[ ] Date of last review has been added to the revised metric at the bottom of the markdown file (month/year)
[ ] Formatting changes have been made
[ ] Minor editorial changes have been made
[ ] Major editorial changes have been made
[ ] Metric adheres to the current metrics template
[ ] Metric name has changed and necessary updates are made to the WG README table and metrics tracking spreadsheet

Technical Requirements for any Revisions

[ ] Metric file name is the full metric name and only contains lower case letters and hyphens (“-”) for spaces
[ ] Images are included using markdown and absolute path links (as described in the metrics template)
[ ] Images have at least one empty line above and below them
[ ] Images are placed in image folder and followed naming convention
[ ] If new a focus area is created, ensure focus area is added to wg repo readme and focus area folder readme
[ ] There is no HTML code in the metrics markdown file

Of particular note are the "Specific Details that require attention" section above