[bug] MAX_CONCURRENT_JOBS is no longer being used

Describe the bug
The environment variable "MAX_CONCURRENT_JOBS" is no longer being utilized in guacone collect files. This was utilized to allow the concurrency and allow the backend to process multiple files simultaneously. This functionality was removed in: https://github.com/guacsec/guac/pull/1195
To Reproduce
Steps to reproduce the behavior:

set export MAX_CONCURRENT_JOBS=3
run go run ./cmd/guacone collect files ../guac-data/top-dh-sboms

Expected behavior
Based on the value set for MAX_CONCURRENT_JOBS, it should concurrently try to ingest multiple documents
GUAC version
main and v0.3.0

Based on testing, this may no longer be a viable option for the inmem backend as it will cause concurrent map read and map write.

For now should we just remove this option for now? and we can decide later on if we want to have it again? or is this still being used in some other context?

Yeah we should just remove the option as its not being used.

I'll work on this

We have batch processing in place. So this is no longer needed.


Add Helm chart for MongoDB sharded cluster

What this PR does / why we need it:
This PR adds a Helm chart for MongoDB, supporting both standalone mode and sharded cluster mode.
Shard rules, including shard keys, shard methods, and unique constraints, are defined and managed in the values.yaml.
This chart depends on the Bitnami's mongodb-sharded chart (https://github.com/bitnami/charts/tree/main/bitnami/mongodb-sharded).
There are a few known issues with it:

A problem with livenessProbe and readinessProbe

Issues

https://github.com/bitnami/charts/issues/21957

Solution: use custom livenessProbe and readinessProbe instead

Lack of ARM64 support in the Bitnami mongodb-sharded container

Issues

https://github.com/bitnami/charts/issues/7305#issuecomment-1443187343
https://github.com/bitnami/containers/issues/40947

Solution: use the official mongo 6.0 image instead and set up the cluster via a Job.

How to install and uninstall

Create mongodb namespace

kubectl create namespace mongodb

Install helm chart with the set flag and the namespace flag (The reason why the namespace flag is needed to be set is due to the misguided value in the Bitnami chart. In here, it uses .Release.Namespace without offering an option to override it.

helm install mongodb . --namespace mongodb --set=sharded.enabled=true

Uninstall helm chart with the namespace flag

helm install mongodb . --namespace mongodb

Which issue(s) this PR fixes:

Addresses #673
Special notes for your reviewer:
We need to do following tasks in the future:

[ ] Enable livenessProbe, readinessProbe
[ ] Connect to Prometheus via PodMonitors

Does this PR introduce a user-facing change?:

Additional documentation:

Checklist:

[x] Added relevant tests or not required
[x] Didn't break anything

Question 1
It seems like yorkie-cluster Helm chart no longer has mongoDB subshart. This means that we now need to install both yorkie-cluster and yorkie-mongodb Helm chart to fully use yorkie cluster. Is there any reason for this separation?
Question 2
It seems like yorkie-mongodb Helm chart performs sharded mongoDB setup by using Job object. Is there any reason for this approach?
I can see that mongodb-sharded Helm chart provides common.initScriptsCM value to initialize mongoDB instances (Nevertheless I also think using Job is the best approach for this kind of operation, I just want to know the reasons for this approach).

Lack of ARM64 support in the Bitnami mongodb-sharded container
Solution: use the official mongo 6.0 image instead and set up the cluster via a Job.

Also, is there any relations between ARM64 support and setting up cluster via Job?

Thanks for your careful review.
Here are my answers for your questions.
Answer 1
After separating MongoDB from yorkie-cluster, there are now two options for users: self-hosted or managed databases (e.g., MongoDB Atlas, AWS DynamoDB). I believe we can focus on supporting self-hosted clusters by solely maintaining yorkie-mongodb.
Answer 2
I initially explored the approach using Bitnami options and tools. Bitnami charts are designed to be used with Bitnami containers together. However, issues arose, including the lack of ARM64 images in the Bitnami mongodb-sharded container. Instead of incurring the current and potential future engineering costs associated with external tools, I opted to implement and maintain the code ourselves.
I believe the current requirements for this are relatively simple and manageable. If future requirements become more complex and there is a good alternative, that would be the time to consider such an option.


Fix export_lib.make_tensor_spec

Fixes #19913
a simple repro from the original issue with minor changes:
import keras
import numpy as np

class SomeModel(keras.Model):
    def __init__(self, output_channels: int):
        super().__init__()
        self.output_channels = output_channels
        self.fc1 = keras.layers.Dense(256, activation="relu")
        self.fc2 = keras.layers.Dense(
            self.output_channels * 2,
            bias_initializer="ones",
            kernel_initializer="zeros",
        )

    def build(self, input_shape):
        super().build(input_shape)
        self.fc1.build(input_shape)
        fc1_out = self.fc1.compute_output_shape(input_shape)
        self.fc2.build(fc1_out)

    def call(self, inputs):
        features = self.fc1(inputs)
        return self.fc2(features)

class SomeParentModel(keras.Model):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.fx = SomeModel(20)

    def call(self, im_batch):
        features = self.fx(im_batch)
        ...
        return features

parent_inst = SomeParentModel()
random_data = np.random.random((1, 512)).astype('float32')

parent_inst(random_data)
parent_inst.save('test_model.keras')

reloaded = keras.models.load_model('test_model.keras', custom_objects={'SomeParentModel': SomeParentModel})
reloaded(random_data)
reloaded.export('test')

Codecov Report
Attention: Patch coverage is 0% with 6 lines in your changes missing coverage. Please review.

Project coverage is 57.22%. Comparing base (f0bae91) to head (33891bf).

Files
Patch %
Lines

keras/src/export/export_lib.py
0.00%
6 Missing :warning:

:exclamation:  There is a different number of reports uploaded between BASE (f0bae91) and HEAD (33891bf). Click for more details.
HEAD has 8 uploads less than BASE
| Flag | BASE (f0bae91) | HEAD (33891bf) |
|------|------|------|
|keras|8|1|
|keras-numpy|2|1|

Additional details and impacted files
@@             Coverage Diff             @@
##           master   #19915       +/-   ##
===========================================
- Coverage   79.02%   57.22%   -21.80%
===========================================
  Files         499      499
  Lines       46433    46436        +3
  Branches     8545     8548        +3
===========================================
- Hits        36692    26572    -10120
- Misses       8015    18217    +10202
+ Partials     1726     1647       -79

Flag
Coverage Δ

keras
57.22% <0.00%> (-21.66%)
:arrow_down:

keras-jax
?

keras-numpy
57.22% <0.00%> (-0.01%)
:arrow_down:

keras-tensorflow
?

keras-torch
?

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feat(typescript): bump to 3.7.5

Coverage increased (+0.04%) to 87.778% when pulling 3e5f150c1664479f63ae73ee3145f1e6152bc053 on typescript_3_7 into 80cefddd7defcf8dd47bd4a991b13916c4f485e4 on master.


.NET target version

My package requires .NET 4.5, yet it is packaged in the "net40" directory in the .nupkg file. How can I tell Pepita to use the correct target framework name ("net45")? That string doesn't seem to be hard-coded but I couldn't find where it is set.

closing this as stale. if it is still an problem please raise a new issue


Grafana Cloud and Local instances can't locate Plugin Datasource

As of this morning, local Grafana instances and Grafana Cloud seem to have lost the ability to locate the FlightSQL plugin. Datasources appear to be broken now and When trying to test them "Plugin not found" error is being thrown.

There is an update to the plugin which fixes the problem!


Chiyue Zhuang's review

1. Summary
This study explores vocabulary development in children aged 16–30 months using MacArthur-Bates data and logistic regression. Age is the strongest predictor, with older children scoring higher. Foundational words, like function words, are learned more consistently than complex ones, such as sensory words. Children in structured linguistic settings perform better, highlighting the importance of systematic exposure. The findings suggest strategies to address variability in complex vocabulary acquisition and support balanced language growth.
2. Strong positive points

The workflow is highly professional and systematically organized.
The project provides a clear and structured framework, making it easy for others to replicate and validate the results.
The model section is exceptionally well-executed, showcasing a clear rationale for model selection and thorough validation documented in the appendix.

3. Critical improvements needed

Improved title: Lacks a meaningful and precise title and subtitle that reflects the main conclusions of the study.
Streamline Model and Results Sections: The explanations in these sections are overly detailed, leading to redundancy. Simplifying the mathematical notation and avoiding repeated points across different parts of the text will make the content more concise and reader-friendly.

4. Suggestions for improvement
The following evaluation has identified the problems and given suggestions, such as the title and discussion needed to provide more details on the weighting mechanism for different predictors. Clearly introduce the reference to the data table to avoid confusion.
6. Evaluation
R/Python cited (1/1 pts)
Good.
Data cited (1/1 pts)
Good.
Class paper (1/1 pts)
Good.
LLM documentation (1/1 pts)
Good.
Title (1/2 pts)
A more specific and representative title to show the findings is needed.
Author, date, and repo (2/2 pts)
Good.
Abstract (3/4 pts)
Need to be more specific about your motivation and findings of the research.
Introduction (2/4 pts)
Better to add some references for credibility.
Estimand (1/1 pts)
Good.
Data (8/10 pts)
The variable explanations could be more succinct, as some points are repeated. Minimize the use of excessive subheadings.
Measurement (4/4 pts)
Good.
Model (10/10 pts)
Good.
Results (8/10 pts)
Better to discuss more about the findings and what you can conclude from the findings.
Discussion (10/10 pts)
Good.
Prose (2/6 pts)
Repetition existed.
Cross-references (1/1 pts)
Good.
Captions (2/2 pts)
Good.
Graphs/tables/etc (4/4 pts)
Good.
Surveys, sampling, and observational data appendix (10/10 pts)
Good.
Referencing (4/4 pts)
Good.
Commits (2/2 pts)
Well done.
Sketches (2/2 pts)
Well done.
Simulation (4/4 pts)
Good.
Tests (4/4 pts)
Good.
Parquet (0/1 pts)
Simulated data is not saved as a Parquet file.
Reproducible workflow (4/4 pts)
Good.
Enhancements (4/4 pts)
Good.
Miscellaneous (2/3 pts)
Overall well done and more improvements needed.
7. Estimated overall mark
105 out of 112.

Hi Chiyue,
Revisions have been made based on your review. Thanks!


nam install graceful-fs

common i use: npm install --save-dev graceful-fs
result:
npm WARN optional Skipping failed optional dependency /noble/bluetooth-hci-socket:
npm WARN notsup Not compatible with your operating system or architecture<EMAIL_ADDRESS>

@TomasPangzi i think this is related to https://github.com/sandeepmistry/noble/issues/414 which you've closed, so I am closing it.


Explicitly inherit from default profile

Component
Forge
Describe the feature you would like
Always inherit from default

optionally add an inherits = "profile" to determine what kind of profile to inherit from

Additional context
No response

Is this not already the case? When I used Foundry on one of my projects it at least seemed to be the case


Columns in configuration settings table are not resizable

Version Info
OSCM v19
Describe the bug
The editing of configuration settings in the UI is unhandy, having narrow input fields that can't be resized.
How to Reproduce

Log in as platform operator administrator
Landing on the configuration settings page check the table column for the value

Expected behavior
Value column has a propper default width and resizing is possible.
Observed behavior
Value column is too narrow while the key column is too wide. There is no justified need as there still unnecessary space right beneath the longest key name. Furthermore the width is fix so that the user can't adjust it.
Screenshots

Additional context
Ask me

I've built and deployed the fix by 2020-11-26. The resizing works well and also the columns have an appropriate width.
Just one thing to be improved, is that after pressing save the row height increases.
How to Reproduce

Log in as platform operator administrator
In the configuration settings page resize the table
click save

Expected behavior
Success message appears in the header and data is saved. The table does not change in any way. Row height and input alignment stays fix.
Observed behavior
Success message appears in the header and data is saved. The row height is increased to approximate 150% of original height. In this case the input fields still appear small and vertically wrong aligned.
After reloading the page the rows are back to normal.

I am using Chrome Version 86.0.4240.198

Describe the bug
The alerts for an empty required field or the wrong value disappear after the form is submitted. The content is loaded 2 times, which extends the page loading time.
How to Reproduce

Open any page in the administrator portal
Submit form
Check network load requests

Expected behavior
Alerts should load and be visible. Content only needs to be uploaded once


Use Rocketeer for deploying

https://github.com/rocketeers/rocketeer

Probably wait until v3 is released


Here are my 4 files interaction: display words and set words, Logic: …

You mainly need to check these two files

Interaction: set words,
Logic: repeat characters

The other two files are fine and no need to review them

I viewed your code and it seems good to me.. I try also to run it and it's all passed 👍 only wait the review from @krakla and @Cyngyz

I review it and it's fine. You can merge it @AnisyaPurnama


Ansys 5.7

cherry pick the SpMV mixed precision

not sure I understand why there is conflicts here.


✨ add new devcontainer feature ruby-asdf to install Ruby via asdf

Goal
Add new devcontainer feature ruby-asdf to install Ruby via asdf. Resolves #526.
Changes

Add src and test for ruby-asdf feature (taken from erlang-asdf, then adapted)

apt packages necessary for Ruby development are taken from the Ruby (via rvm) devcontainer feature.

Hi @danielbraun89, have you noticed this and my other two PRs 👀 ? Any chance you could find the time to review them 🙏 ?
Regards from Germany!
Christoph

Hi @danielbraun89, have you noticed this and my other two PRs 👀 ? Any chance you could find the time to review them 🙏 ?
Regards from Germany!
Christoph

done :)

Thanks a lot 💛 .


Better error handling

Library needs to silently fail rather than crash on errors.

v0.0.32 has been released where exceptions now disconnect from ARENA and terminate the program. I also added a try-except block in the message parsing code which will hopefully be triggered, print something, but allow the program to continue.
I'm going to keep this issue open in case anything else needs to be done


Cherry-pick #23145 to release

See https://github.com/gradle/gradle-private/issues/3657

@bot-gradle test and merge

OK, I've already triggered a build for you.


Added createContext method and ability to pass context id & persist boolean to session create options

As per my conversation with Paul. Not sure if you'll want this createContext method or not but figured i'd add it anyways - the ability to add a context to the session is what i'm after.

Published in v1.4.0 🚀 https://www.npmjs.com/package/@browserbasehq/sdk


TransactionScope disappears during test execution with 4.7.2

In our tests we currently use TransactionScope at a high level so that we can rollback the transaction after completing the test so that we get a clean slate for every test we run.
Some of our developers have recently installed the latest Windows 10 update  and since then we have seen tests fail because of data being inserted into the database that already exists. After some investigation it seems that somehow the TransactionScope disappears (ie. System.Transactions.Transaction.Current is NULL). This typically occurs at the same time that we create our first SqlConnection, but this might just be a coincidence.
Unfortunately I have been unable to reproduce this issue with a simple console app or unit test. Additionally it seems related to the fact that the test class (we are using MSTest) inherits from ContextBoundObject, since removing the inheritance seems to fix the issue.
Looking at the reference source for both 4.7.1 and 4.7.2 I noticed that the context key being stored in the LogicalCallContext used to locate the TransactionScope was changed from a ContextKey class (which itself is a MarshalByRefObject) to a string. This seems somehow related, but again I haven't been able to reproduce it consistently.

Another question - is your test using multiple threads?
If you are NOT using TransactionScopeAsyncFlowOption.Enabled, then, as you know, Transaction.Current is a thread static, which means it will be different for every thread. So if you create a TransactionScope on one thread and then do a System.Data operation on another thread, Transaction.Current will be null on that second thread unless you specifically create a TransactionScope on that second thread. And if you don't use the Transaction.Current value from the first thread when creating the TransactionScope on the second thread, the two threads will work with different transactions.
Jim

I have been playing around with this a bit.
I wrote a little program that starts a TransactionScope, opens up a single SqlConnection, and does 5 inserts into a table. The TransactionScope is NOT completed, which would result in the transaction aborting and the DB inserts being "undone".
class Program
{
    public static string ConnectionString = "Data Source=localhost;Initial Catalog=DBName;Integrated Security=SSPI";

    static void Main(string[] args)
    {
        using (TransactionScope ts = new TransactionScope())
        {
            using (SqlConnection connection = new SqlConnection(ConnectionString))
            {
                connection.Open();

                SqlCommand cmd = new SqlCommand();
                cmd.CommandText = "insert into table1 ([StringData]) values ('one')";
                cmd.Connection = connection;
                cmd.ExecuteNonQuery();

                cmd = new SqlCommand();
                cmd.CommandText = "insert into table1 ([StringData]) values ('two')";
                cmd.Connection = connection;
                cmd.ExecuteNonQuery();

                cmd = new SqlCommand();
                cmd.CommandText = "insert into table1 ([StringData]) values ('three')";
                cmd.Connection = connection;
                cmd.ExecuteNonQuery();

                cmd = new SqlCommand();
                cmd.CommandText = "insert into table1 ([StringData]) values ('four')";
                cmd.Connection = connection;
                cmd.ExecuteNonQuery();

                cmd = new SqlCommand();
                cmd.CommandText = "insert into table1 ([StringData]) values ('five')";
                cmd.Connection = connection;
                cmd.ExecuteNonQuery();

            }
        }
    }
}

However, if I add the following between the commands to insert "three" and "four", the table ends up with rows for "four" and "five".
Transaction.Current.Rollback();
Transaction.Current.Dispose();
The Rollback will undo the rows for "one", "two", and "three".
Without the "Transaction.Current.Dispose()", the insert commands for "four" and "five" threw an exception because the transaction was aborted and still associated with the connection.
But the Dispose() caused the transaction to get "disconnected" from the connection. So the inserts for "four" and "five" to use a "SQL Transaction" for each statement, rather than Transaction.Current.
So, if something is causing the transaction to be aborted and disposed "early", before your test is done with database work, it is POSSIBLE that the SqlConnection is reverting to using SQL transactions for each of the statements after that point.
Just a possible explanation. Until we are able to reproduce your issue on a consistent basis and debug it to verify that the problem is caused by the change to System.Transactions that modified what gets put into the CallContext, we are stuck.
Knowing whether or not your test utilizes TransactionScopeAsyncFlowOption.Enabled will help to know if we need to pursue debugging this further. System.Transactions only uses the CallContext if TransactionScopeAsyncFlowOption.Enabled is specified.
Jim

I'm sorry for the late reply, been rather busy lately ;).
So first of all, yes, we do use TransactionScopeAsyncFlowOption.Enabled. In fact, we changed this when we first moved to .NET 4.5 and wanted to do async/await in our code base.
To give a bit more context, we are currently using a data access library that was written way back when .NET 1.1 came out or something. It is no longer supported by the original creators, but we have the source code and we have made some changes to it over the years. Unfortunately we've never taken the time to get rid of it and replace it with something a bit more modern.
In addition to that third-party data access library we also use a third-party library for loading test data into our database. This library used some kind of aspect oriented programming approach so that one can place a LoadTestData attribute on a test method and it will load a particular data set (a bunch of XML files) into the database using SqlBulkCopy. The aspect oriented part relied on ContextBoundObject. I have since replaced it with simply getting the test method through reflection and discovering any attributes on it in the TestInitialize, without having to resort to all kinds of crazy ContextBoundObject stuff. That seems to have fixed our immediate issue for now.
That being said, I still find it weird that TransactionContext.Current is suddenly null. I thought it might even have to do with the garbage collector running, but even a simple console application in which I trigger the GC explicitly didn't produce the same issues.

I think I am going to need a little more information about these ContextBoundObjects that you are using and how they interact with Transaction.Current and how they interact with the method that creates the TransactionScope and the various async methods you have and the associated await usage.


Execution of cells blocked due to variable viewer

Applies To

[ ] Notebooks (.ipynb files)
[X] Interactive Window and/or Cell Scripts (.py files with #%% markers)

What happened?
When I run my script in the interactive window, the first few cells execute normally, but subsequent cells do not run. The Jupyter output acknowledges that the cell has been sent to the kernel but never starts execution.
Jupyter logs
Visual Studio Code (1.87.0, undefined, desktop)
Jupyter Extension Version: 2024.2.0.
Python Extension Version: 2024.2.1.
Pylance Extension Version: 2024.2.3.
Platform: darwin (arm64).
Workspace folder ~/Dropbox/Cornell/insurance holdings/data - 2023, Home = /Users/pietro
17:21:45.897 [debug] Get Custom Env Variables, Class name = Rm (started execution), Arg 1: undefined, Arg 2: "RunPythonCode"
17:21:45.898 [info] Start refreshing Kernel Picker<PHONE_NUMBER>898)
17:21:45.904 [info] Using Pylance
17:21:45.935 [debug] Get Custom Env Variables, Class name = Rm, completed in 38ms, has a truthy return value, Arg 1: undefined, Arg 2: "RunPythonCode"
17:21:45.935 [debug] Jupyter Paths /kernels:
17:21:45.935 [debug] Kernel Spec Root Paths, /usr/share/jupyter/kernels, /usr/local/share/jupyter/kernels, ~/Library/Jupyter/kernels
17:21:45.938 [debug] Search for KernelSpecs in Interpreter /usr/bin/python3
17:21:45.938 [debug] Finding Global Python KernelSpecs
17:21:45.939 [warn] No interpreter with path ~/opt/anaconda3/bin/python found in Python API, will convert Uri path to string as Id ~/opt/anaconda3/bin/python
17:21:45.940 [warn] No interpreter with path ~/opt/anaconda3/envs/XCS224N_MAC/bin/python found in Python API, will convert Uri path to string as Id ~/opt/anaconda3/envs/XCS224N_MAC/bin/python
17:21:45.940 [warn] No interpreter with path ~/opt/anaconda3/envs/test_env/bin/python found in Python API, will convert Uri path to string as Id ~/opt/anaconda3/envs/test_env/bin/python
17:21:45.942 [debug] Search for KernelSpecs in Interpreter ~/anaconda3/bin/python
17:21:45.943 [debug] Search for KernelSpecs in Interpreter ~/opt/anaconda3/envs/XCS224N/bin/python
17:21:45.945 [debug] Search for KernelSpecs in Interpreter ~/opt/anaconda3/envs/ap_env/bin/python
17:21:45.947 [debug] Search for KernelSpecs in Interpreter ~/opt/anaconda3/envs/rl_env/bin/python
17:21:45.951 [debug] Search for KernelSpecs in Interpreter ~/anaconda3/envs/apenv_MPS/bin/python
17:21:45.953 [debug] Search for KernelSpecs in Interpreter /opt/homebrew/Caskroom/miniforge/base/bin/python
17:21:45.956 [debug] Search for KernelSpecs in Interpreter ~/anaconda3/envs/insurance/bin/python
17:21:45.959 [debug] Search for KernelSpecs in Interpreter ~/anaconda3/envs/test_env/bin/python
17:21:45.963 [debug] Search for KernelSpecs in Interpreter ~/anaconda3/envs/mps_env/bin/python
17:21:45.967 [debug] Search for KernelSpecs in Interpreter ~/anaconda3/envs/insurance_quant/bin/python
17:21:45.975 [debug] Full interpreter list is length: 12, /usr/bin/python3::Unknown:/usr/bin/python3, ~/anaconda3/bin/python:base:Conda:~/anaconda3/bin/python, ~/opt/anaconda3/envs/XCS224N/bin/python::Conda:~/opt/anaconda3/envs/XCS224N/bin/python, ~/opt/anaconda3/envs/ap_env/bin/python::Conda:~/opt/anaconda3/envs/ap_env/bin/python, ~/opt/anaconda3/envs/rl_env/bin/python::Conda:~/opt/anaconda3/envs/rl_env/bin/python, ~/anaconda3/envs/apenv_MPS/bin/python:apenv_MPS:Conda:~/anaconda3/envs/apenv_MPS/bin/python, /opt/homebrew/Caskroom/miniforge/base/bin/python:base:Conda:/opt/homebrew/Caskroom/miniforge/base/bin/python, ~/anaconda3/envs/insurance/bin/python:insurance:Conda:~/anaconda3/envs/insurance/bin/python, ~/anaconda3/envs/test_env/bin/python:test_env:Conda:~/anaconda3/envs/test_env/bin/python, ~/anaconda3/envs/mps_env/bin/python:mps_env:Conda:~/anaconda3/envs/mps_env/bin/python, ~/anaconda3/envs/mps_env/bin/python:mps_env:Conda:~/anaconda3/envs/mps_env/bin/python, ~/anaconda3/envs/insurance_quant/bin/python:insurance_quant:Conda:~/anaconda3/envs/insurance_quant/bin/python
17:21:45.976 [debug] Getting activated env variables, Class name = yp (started execution), Arg 1: "~/Dropbox/Cornell/insurance holdings/data - 2023", Arg 2: "~/anaconda3/envs/insurance/bin/python", Arg 3: undefined
17:21:45.976 [debug] Get Custom Env Variables, Class name = Rm (started execution), Arg 1: "~/Dropbox/Cornell/insurance holdings/data - 2023", Arg 2: "RunPythonCode"
17:21:45.976 [debug] Get Custom Env Variables, Class name = Rm, completed in 0ms, has a truthy return value, Arg 1: "~/Dropbox/Cornell/insurance holdings/data - 2023", Arg 2: "RunPythonCode"
17:21:46.154 [debug] Kernels for interpreter /usr/bin/python3 are .jvsc74a57bd031f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6./usr/bin/python3./usr/bin/python3.-m#ipykernel_launcher
17:21:46.157 [debug] Kernels for interpreter /opt/homebrew/Caskroom/miniforge/base/bin/python are .jvsc74a57bd0c6e4e9f98eb68ad3b7c296f83d20e6de614cb42e90992a65aa266555a3137d0d./opt/homebrew/Caskroom/miniforge/base/python./opt/homebrew/Caskroom/miniforge/base/python.-m#ipykernel_launcher
17:21:46.184 [debug] Loading kernelspec from ~/Library/Jupyter/kernels/ap_env/kernel.json
17:21:46.184 [debug] Loading kernelspec from ~/Library/Jupyter/kernels/base/kernel.json
17:21:46.184 [debug] Loading kernelspec from ~/Library/Jupyter/kernels/rl_env/kernel.json
17:21:46.184 [debug] Loading kernelspec from ~/Library/Jupyter/kernels/test_env/kernel.json
17:21:46.184 [debug] Loading kernelspec from ~/Library/Jupyter/kernels/xcs224n_mac/kernel.json
17:21:46.184 [debug] Loading kernelspec from ~/Library/Jupyter/kernels/xcs224n/kernel.json
17:21:46.188 [debug] Loading kernelspec from ~/opt/anaconda3/envs/XCS224N/share/jupyter/kernels/python3/kernel.json for ~/opt/anaconda3/envs/XCS224N/bin/python
17:21:46.188 [debug] Loading kernelspec from ~/anaconda3/share/jupyter/kernels/python3/kernel.json for ~/anaconda3/bin/python
17:21:46.188 [debug] Loading kernelspec from ~/opt/anaconda3/envs/rl_env/share/jupyter/kernels/python3/kernel.json for ~/opt/anaconda3/envs/rl_env/bin/python
17:21:46.188 [debug] Loading kernelspec from ~/opt/anaconda3/envs/ap_env/share/jupyter/kernels/python3/kernel.json for ~/opt/anaconda3/envs/ap_env/bin/python
17:21:46.188 [debug] Loading kernelspec from ~/anaconda3/envs/apenv_MPS/share/jupyter/kernels/python3/kernel.json for ~/anaconda3/envs/apenv_MPS/bin/python
17:21:46.188 [debug] Loading kernelspec from ~/anaconda3/envs/test_env/share/jupyter/kernels/python3/kernel.json for ~/anaconda3/envs/test_env/bin/python
17:21:46.188 [debug] Loading kernelspec from ~/anaconda3/envs/insurance/share/jupyter/kernels/python3/kernel.json for ~/anaconda3/envs/insurance/bin/python
17:21:46.189 [debug] Loading kernelspec from ~/anaconda3/envs/insurance_quant/share/jupyter/kernels/python3/kernel.json for ~/anaconda3/envs/insurance_quant/bin/python
17:21:46.189 [debug] Loading kernelspec from ~/anaconda3/envs/mps_env/share/jupyter/kernels/python3/kernel.json for ~/anaconda3/envs/mps_env/bin/python
17:21:46.300 [debug] creating new code watcher with matching document file://~/Dropbox/Cornell/insurance%20holdings/data%20-%202023/codes/6B_weights_20240304.py
17:21:46.357 [debug] Hiding default kernel spec 'Python 3 (ipykernel)', 'python3916jvsc74a57bd023bdcbcefc934dfe69983f0c7df3dc57ff17d195649bda66364f6428b4fe7993', ~/opt/anaconda3/envs/rl_env/bin/python for interpreter ~/opt/anaconda3/envs/rl_env/bin/python and spec ~/opt/anaconda3/envs/rl_env/share/jupyter/kernels/python3/kernel.json
17:21:46.357 [debug] Kernels for interpreter ~/opt/anaconda3/envs/rl_env/bin/python are .jvsc74a57bd023bdcbcefc934dfe69983f0c7df3dc57ff17d195649bda66364f6428b4fe7993.~/opt/anaconda3/envs/rl_env/python.~/opt/anaconda3/envs/rl_env/python.-m#ipykernel_launcher
17:21:46.358 [debug] Hiding default kernel spec 'Python 3 (ipykernel)', 'python3816jvsc74a57bd08312df2c8bbbde0291f201f87b9941663600fa338039fb5847929143bd80724a', ~/opt/anaconda3/envs/XCS224N/bin/python for interpreter ~/opt/anaconda3/envs/XCS224N/bin/python and spec ~/opt/anaconda3/envs/XCS224N/share/jupyter/kernels/python3/kernel.json
17:21:46.358 [debug] Kernels for interpreter ~/opt/anaconda3/envs/XCS224N/bin/python are .jvsc74a57bd08312df2c8bbbde0291f201f87b9941663600fa338039fb5847929143bd80724a.~/opt/anaconda3/envs/XCS224N/python.~/opt/anaconda3/envs/XCS224N/python.-m#ipykernel_launcher
17:21:46.358 [debug] Hiding default kernel spec 'Python 3 (ipykernel)', 'python3114jvsc74a57bd0542238ec44c35636042ce97683d77280b46c3a630492e0e6cbfd243d3e7c4cbe', ~/anaconda3/bin/python for interpreter ~/anaconda3/bin/python and spec ~/anaconda3/share/jupyter/kernels/python3/kernel.json
17:21:46.358 [debug] Kernels for interpreter ~/anaconda3/bin/python are .jvsc74a57bd0542238ec44c35636042ce97683d77280b46c3a630492e0e6cbfd243d3e7c4cbe.~/anaconda3/python.~/anaconda3/python.-m#ipykernel_launcher
17:21:46.358 [debug] Hiding default kernel spec 'Python 3 (ipykernel)', 'python3916jvsc74a57bd0543949b80c79a1e8c0254461769a7e4eed4e8439ee16309e104e5c4dcbc438fc', ~/opt/anaconda3/envs/ap_env/bin/python for interpreter ~/opt/anaconda3/envs/ap_env/bin/python and spec ~/opt/anaconda3/envs/ap_env/share/jupyter/kernels/python3/kernel.json
17:21:46.358 [debug] Kernels for interpreter ~/opt/anaconda3/envs/ap_env/bin/python are .jvsc74a57bd0543949b80c79a1e8c0254461769a7e4eed4e8439ee16309e104e5c4dcbc438fc.~/opt/anaconda3/envs/ap_env/python.~/opt/anaconda3/envs/ap_env/python.-m#ipykernel_launcher
17:21:46.358 [debug] Hiding default kernel spec 'Python 3 (ipykernel)', 'python3918jvsc74a57bd0d0e18151e95e23f1835839219fb8bb03fdc0eca2e1ee2c76ced867841fadaac7', ~/anaconda3/envs/apenv_MPS/bin/python for interpreter ~/anaconda3/envs/apenv_MPS/bin/python and spec ~/anaconda3/envs/apenv_MPS/share/jupyter/kernels/python3/kernel.json
17:21:46.359 [debug] Kernels for interpreter ~/anaconda3/envs/apenv_MPS/bin/python are .jvsc74a57bd0d0e18151e95e23f1835839219fb8bb03fdc0eca2e1ee2c76ced867841fadaac7.~/anaconda3/envs/apenv_MPS/python.~/anaconda3/envs/apenv_MPS/python.-m#ipykernel_launcher
17:21:46.359 [debug] Hiding default kernel spec 'Python 3 (ipykernel)', 'python3918jvsc74a57bd056ced0f84cd932c524064ef756ac60f3c3529a050aadaf72d1d7cd6d6e80d296', ~/anaconda3/envs/test_env/bin/python for interpreter ~/anaconda3/envs/test_env/bin/python and spec ~/anaconda3/envs/test_env/share/jupyter/kernels/python3/kernel.json
17:21:46.359 [debug] Kernels for interpreter ~/anaconda3/envs/test_env/bin/python are .jvsc74a57bd056ced0f84cd932c524064ef756ac60f3c3529a050aadaf72d1d7cd6d6e80d296.~/anaconda3/envs/test_env/python.~/anaconda3/envs/test_env/python.-m#ipykernel_launcher
17:21:46.359 [debug] Hiding default kernel spec 'Python 3 (ipykernel)', 'python3918jvsc74a57bd0781382444f7e6de4f70eb98cafa2f33a2ab1aa7e94b8aea32a152433c56a74c6', ~/anaconda3/envs/insurance/bin/python for interpreter ~/anaconda3/envs/insurance/bin/python and spec ~/anaconda3/envs/insurance/share/jupyter/kernels/python3/kernel.json
17:21:46.359 [debug] Kernels for interpreter ~/anaconda3/envs/insurance/bin/python are .jvsc74a57bd0781382444f7e6de4f70eb98cafa2f33a2ab1aa7e94b8aea32a152433c56a74c6.~/anaconda3/envs/insurance/python.~/anaconda3/envs/insurance/python.-m#ipykernel_launcher
17:21:46.359 [debug] Hiding default kernel spec 'Python 3 (ipykernel)', 'python3918jvsc74a57bd05eb47c1207cdf30eef9942cb72135fdfb5fa8f258573d5f6b1ce5f8a5c18ff4f', ~/anaconda3/envs/insurance_quant/bin/python for interpreter ~/anaconda3/envs/insurance_quant/bin/python and spec ~/anaconda3/envs/insurance_quant/share/jupyter/kernels/python3/kernel.json
17:21:46.359 [debug] Kernels for interpreter ~/anaconda3/envs/insurance_quant/bin/python are .jvsc74a57bd05eb47c1207cdf30eef9942cb72135fdfb5fa8f258573d5f6b1ce5f8a5c18ff4f.~/anaconda3/envs/insurance_quant/python.~/anaconda3/envs/insurance_quant/python.-m#ipykernel_launcher
17:21:46.359 [debug] Hiding default kernel spec 'Python 3 (ipykernel)', 'python31013jvsc74a57bd0685bb1e1d585b6d3ea810b2afa91035df27837cf8642ccfbfae427c7b77c8387', ~/anaconda3/envs/mps_env/bin/python for interpreter ~/anaconda3/envs/mps_env/bin/python and spec ~/anaconda3/envs/mps_env/share/jupyter/kernels/python3/kernel.json
17:21:46.360 [debug] Kernels for interpreter ~/anaconda3/envs/mps_env/bin/python are .jvsc74a57bd0685bb1e1d585b6d3ea810b2afa91035df27837cf8642ccfbfae427c7b77c8387.~/anaconda3/envs/mps_env/python.~/anaconda3/envs/mps_env/python.-m#ipykernel_launcher
17:21:48.477 [warn] Kernel Spec for 'XCS224N_MAC' (~/Library/Jupyter/kernels/xcs224n_mac/kernel.json) hidden, as we cannot find a matching interpreter argv = '~/opt/anaconda3/envs/XCS224N_MAC/bin/python'. To resolve this, please change '~/opt/anaconda3/envs/XCS224N_MAC/bin/python' to point to the fully qualified Python executable.
17:21:48.478 [warn] Kernel Spec for 'Python (base)' (~/Library/Jupyter/kernels/base/kernel.json) hidden, as we cannot find a matching interpreter argv = '~/opt/anaconda3/bin/python'. To resolve this, please change '~/opt/anaconda3/bin/python' to point to the fully qualified Python executable.
17:21:48.479 [warn] Kernel Spec for 'test_env' (~/Library/Jupyter/kernels/test_env/kernel.json) hidden, as we cannot find a matching interpreter argv = '~/opt/anaconda3/envs/test_env/bin/python'. To resolve this, please change '~/opt/anaconda3/envs/test_env/bin/python' to point to the fully qualified Python executable.
17:21:48.514 [info] End refreshing Kernel Picker<PHONE_NUMBER>898)
17:21:50.657 [debug] Conda file returned by Python Extension is conda
17:21:51.482 [debug] Got env vars with python ~/anaconda3/envs/insurance/bin/python, with env var count 48 in 5506ms.
    PATH value is ~/anaconda3/envs/insurance/bin:~/anaconda3/condabin:/opt/homebrew/bin:/opt/homebrew/sbin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin:/Library/TeX/texbin:/opt/X11/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/local/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/appleinternal/bin and
    Path value is undefined
17:21:51.482 [debug] Prepend PATH with python bin for ~/anaconda3/envs/insurance/bin/python
17:21:51.482 [debug] Activated Env Variables for ~/anaconda3/envs/insurance/bin/python,
    PATH value is ~/anaconda3/envs/insurance/bin:~/anaconda3/condabin:/opt/homebrew/bin:/opt/homebrew/sbin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin:/Library/TeX/texbin:/opt/X11/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/local/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/appleinternal/bin and
    Path value is undefined
17:21:51.482 [debug] Getting activated env variables, Class name = yp, completed in 5506ms, has a truthy return value, Arg 1: "~/Dropbox/Cornell/insurance holdings/data - 2023", Arg 2: "~/anaconda3/envs/insurance/bin/python", Arg 3: undefined
17:21:51.483 [info] Process Execution: ~/anaconda3/envs/insurance/bin/python -m pip list
17:22:27.254 [info] Starting interactive window for resource '~/Dropbox/Cornell/insurance holdings/data - 2023/codes/6B_weights_20240304.py' with controller '.jvsc74a57bd0781382444f7e6de4f70eb98cafa2f33a2ab1aa7e94b8aea32a152433c56a74c6.~/anaconda3/envs/insurance/python.~/anaconda3/envs/insurance/python.-m#ipykernel_launcher (Interactive)'
17:22:27.307 [info] Start refreshing Interpreter Kernel Picker
17:22:27.307 [info] Start refreshing Kernel Picker<PHONE_NUMBER>307)
17:22:27.311 [debug] No controller, hence notebook communications cannot be initialized for editor /Interactive-1.interactive
17:22:27.323 [debug] Initialize notebook communications for editor /Interactive-1.interactive
17:22:27.323 [debug] Resolving notebook UI Comms (resolve) for /Interactive-1.interactive
17:22:27.323 [debug] initialize CommonMessageCoordinator
17:22:27.328 [debug] IPyWidgetMessageDispatcher.initialize
17:22:27.328 [debug] Attempting to determine version of IPyWidgets
17:22:27.328 [debug] Controller selection change completed
17:22:27.394 [debug] Interactive Window Editor Created: untitled:/Interactive-1.interactive with input box: vscode-interactive-input:/InteractiveInput-1
17:22:27.397 [debug] start the kernel, options.disableUI=false for /Interactive-1.interactive
17:22:27.397 [debug] Waiting for IPyWidgets version
17:22:27.397 [debug] Waiting for IPyWidgets version promise
17:22:27.398 [info] Starting Kernel startUsingPythonInterpreter, .jvsc74a57bd0781382444f7e6de4f70eb98cafa2f33a2ab1aa7e94b8aea32a152433c56a74c6.~/anaconda3/envs/insurance/python.~/anaconda3/envs/insurance/python.-m#ipykernel_launcher  (Python Path: ~/anaconda3/envs/insurance/bin/python, Conda, insurance, 3.9.18) for '/Interactive-1.interactive' (disableUI=false)
17:22:27.399 [debug] Creating raw notebook for resource '~/Dropbox/Cornell/insurance holdings/data - 2023/codes/6B_weights_20240304.py'
17:22:27.406 [debug] Getting activated env variables, Class name = yp (started execution), Arg 1: "~/Dropbox/Cornell/insurance holdings/data - 2023/codes/6B_weights_20240304.py", Arg 2: "~/anaconda3/envs/insurance/bin/python", Arg 3: undefined
17:22:27.406 [debug] Get Custom Env Variables, Class name = Rm (started execution), Arg 1: "~/Dropbox/Cornell/insurance holdings/data - 2023/codes/6B_weights_20240304.py", Arg 2: "RunPythonCode"
17:22:27.406 [debug] Get Custom Env Variables, Class name = Rm, completed in 0ms, has a truthy return value, Arg 1: "~/Dropbox/Cornell/insurance holdings/data - 2023/codes/6B_weights_20240304.py", Arg 2: "RunPythonCode"
17:22:27.406 [debug] Got env vars with python ~/anaconda3/envs/insurance/bin/python, with env var count 48 in 0ms.
    PATH value is ~/anaconda3/envs/insurance/bin:~/anaconda3/condabin:/opt/homebrew/bin:/opt/homebrew/sbin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin:/Library/TeX/texbin:/opt/X11/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/local/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/appleinternal/bin and
    Path value is undefined
17:22:27.406 [debug] Prepend PATH with python bin for ~/anaconda3/envs/insurance/bin/python
17:22:27.406 [debug] Activated Env Variables for ~/anaconda3/envs/insurance/bin/python,
    PATH value is ~/anaconda3/envs/insurance/bin:~/anaconda3/condabin:/opt/homebrew/bin:/opt/homebrew/sbin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin:/Library/TeX/texbin:/opt/X11/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/local/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/appleinternal/bin and
    Path value is undefined
17:22:27.406 [debug] Getting activated env variables, Class name = yp, completed in 0ms, has a truthy return value, Arg 1: "~/Dropbox/Cornell/insurance holdings/data - 2023/codes/6B_weights_20240304.py", Arg 2: "~/anaconda3/envs/insurance/bin/python", Arg 3: undefined
17:22:27.407 [info] Process Execution: ~/anaconda3/envs/insurance/bin/python -c "import ipykernel; print(ipykernel.__version__); print("5dc3a68c-e34e-4080-9c3e-2a532b2ccb4d"); print(ipykernel.__file__)"
17:22:27.420 [debug] Launching kernel .jvsc74a57bd0781382444f7e6de4f70eb98cafa2f33a2ab1aa7e94b8aea32a152433c56a74c6.~/anaconda3/envs/insurance/python.~/anaconda3/envs/insurance/python.-m#ipykernel_launcher for ~/Dropbox/Cornell/insurance holdings/data - 2023/codes/6B_weights_20240304.py in ~/Dropbox/Cornell/insurance holdings/data - 2023/codes with ports 9001, 9000, 9004, 9002, 9003
17:22:27.421 [debug] Kernel Env Variables for ~/.vscode/extensions/ms-toolsai.jupyter-2024.2.0-darwin-arm64/temp/jupyter/kernels/python3918jvsc74a57bd0781382444f7e6de4f70eb98cafa2f33a2ab1aa7e94b8aea32a152433c56a74c6/kernel.json, PATH value is ~/anaconda3/envs/insurance/bin:~/anaconda3/condabin:/opt/homebrew/bin:/opt/homebrew/sbin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin:/Library/TeX/texbin:/opt/X11/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/local/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/appleinternal/bin
17:22:27.422 [info] Process Execution: ~/anaconda3/envs/insurance/bin/python -m ipykernel_launcher --f=~/Library/Jupyter/runtime/kernel-v2-1438YbbCclx2VLJH.json
    > cwd: ~/Dropbox/Cornell/insurance holdings/data - 2023/codes
17:22:27.422 [info] Kernel process 2106.
17:22:27.433 [debug] Attempting to determine version of IPyWidgets
17:22:27.433 [debug] Waiting for IPyWidgets version
17:22:27.433 [debug] Waiting for IPyWidgets version promise
17:22:28.038 [debug] ipykernel version & path 6.28.0, ~/anaconda3/envs/insurance/lib/python3.9/site-packages/ipykernel/__init__.py for ~/anaconda3/envs/insurance/bin/python
17:22:28.628 [debug] Kernel output: NOTE: When using the `ipython kernel` entry point, Ctrl-C will not work.

To exit, you will have to explicitly quit this process, by either sending
"quit" from a client, or using Ctrl-\ in UNIX-like environments.

To read more about this, see https://github.com/ipython/ipython/issues/2049

To connect another client to this kernel, use:
    --existing kernel-v2-1438YbbCclx2VLJH.json

17:22:28.659 [debug] Waiting for Raw Session to be ready in postStartRawSession
17:22:28.659 [debug] Waiting for Raw session to be ready, status: connected
17:22:28.659 [debug] Raw session connected
17:22:28.659 [debug] Waiting for Raw session to be ready
17:22:28.660 [debug] Waited for Raw session to be ready & got status: connected
17:22:28.660 [debug] Successfully waited for Raw Session to be ready in postStartRawSession
17:22:28.660 [debug] Kernel status is 'unknown' before requesting kernel info and after ready
17:22:28.660 [debug] Sending request for kernelInfo
17:22:28.702 [debug] Got response for requestKernelInfo
17:22:28.702 [debug] Successfully completed postStartRawSession after 1 attempt(s) in 42ms
17:22:28.703 [debug] Executing silently Code (idle) = import sys as _VSCODE_sys\nprint(_VSCODE_sys.executable); del _VSCODE_sys
17:22:28.711 [debug] Executing silently Code (completed) = import sys as _VSCODE_sys\nprint(_VSCODE_sys.executable); del _VSCODE_sys with 1 output(s)
17:22:28.711 [debug] End sendTelemetryForPythonKernelExecutable after 8ms
17:22:28.711 [debug] Started running kernel initialization for /Interactive-1.interactive
17:22:28.712 [debug] Executing silently Code (idle) = try:\nimport ipywidgets as _VSCODE_ipywidgets\nprint("e976ee50-99ed-4aba-9b6b-9dcd5634d07d:IPy
17:22:28.756 [debug] Executing silently Code (completed) = try:\nimport ipywidgets as _VSCODE_ipywidgets\nprint("e976ee50-99ed-4aba-9b6b-9dcd5634d07d:IPy with 1 output(s)
17:22:28.756 [debug] Determined IPyWidgets Version as 8
17:22:28.756 [debug] Version of IPyWidgets 8 determined after 1.428s
17:22:28.756 [debug] Version of IPyWidgets 8 determined after 1.323s
17:22:28.757 [debug] Executing silently Code (idle) = import types as _VSCODE_types\nimport os\nimport hashlib as _VSCODE_hashlib\nfrom IPython import get_ip
17:22:28.774 [debug] Executing silently Code (completed) = import types as _VSCODE_types\nimport os\nimport hashlib as _VSCODE_hashlib\nfrom IPython import get_ip with 1 output(s)
17:22:28.774 [debug] Requesting Kernel info
17:22:28.775 [debug] Got Kernel info
17:22:28.775 [debug] End running kernel initialization, now waiting for idle
17:22:28.775 [debug] Waiting for idle on (kernel): e8db641f-6c60-45c7-a217-02b2cfa09c2c -> idle
17:22:28.775 [debug] Finished waiting for idle on (kernel): e8db641f-6c60-45c7-a217-02b2cfa09c2c -> idle
17:22:28.775 [debug] End running kernel initialization, session is idle
17:22:28.776 [info] Registering Kernel Completion Provider from kernel insurance (Python 3.9.18) for language python
17:22:28.777 [debug] IPyWidgetScriptSource.initialize
17:22:28.777 [debug] Registering commtarget jupyter.widget
17:22:28.777 [debug] IPyWidgetMessageDispatcher.initialize
17:22:28.778 [debug] getDataDirsImpl, Class name = Fr (started execution), Arg 1: "~/Dropbox/Cornell/insurance holdings/data - 2023/codes/6B_weights_20240304.py", Arg 2: "~/anaconda3/envs/insurance/bin/python"
17:22:28.779 [debug] Get Custom Env Variables, Class name = Rm (started execution), Arg 1: undefined, Arg 2: "RunPythonCode"
17:22:28.779 [debug] Get Custom Env Variables, Class name = Rm, completed in 0ms, has a truthy return value, Arg 1: undefined, Arg 2: "RunPythonCode"
17:22:28.779 [debug] Jupyter Paths :
17:22:28.779 [debug] Initializing __file__ in setFileInKernel with file://~/Dropbox/Cornell/insurance%20holdings/data%20-%202023/codes/6B_weights_20240304.py for mode perFile
17:22:28.781 [debug] Executing silently Code (idle) = __file__ = '~/Dropbox/Cornell/insurance holdings/data - 2023/codes/6B_weights_20240304.p
17:22:28.781 [info] Process Execution: ~/anaconda3/envs/insurance/bin/python ~/.vscode/extensions/ms-toolsai.jupyter-2024.2.0-darwin-arm64/pythonFiles/printJupyterDataDir.py
17:22:28.782 [info] Generated code for 1 = <ipython-input-1-e7d1624574e1> with 52 lines
17:22:28.786 [debug] Executing silently Code (completed) = __file__ = '~/Dropbox/Cornell/insurance holdings/data - 2023/codes/6B_weights_20240304.p with 0 output(s)
17:22:28.789 [debug] Cell Index:1 sent to kernel
17:22:28.797 [debug] Start cell 1 execution @<PHONE_NUMBER>797 (clear output)
17:22:28.797 [info] Kernel acknowledged execution of cell 1 @<PHONE_NUMBER>797
17:22:28.798 [warn] Got a non-existent Jupyter Data Dir file://~/.local/share/jupyter
17:22:28.798 [debug] getDataDirsImpl, Class name = Fr, completed in 20ms, has a truthy return value, Arg 1: "~/Dropbox/Cornell/insurance holdings/data - 2023/codes/6B_weights_20240304.py", Arg 2: "~/anaconda3/envs/insurance/bin/python", Return Value: <Uri:~/Library/Jupyter>, <Uri:~/anaconda3/envs/insurance/share/jupyter>, <Uri:/usr/local/share/jupyter>, <Uri:/usr/share/jupyter>
17:22:28.894 [debug] Full interpreter list is length: 12, /usr/bin/python3::Unknown:/usr/bin/python3, ~/anaconda3/bin/python:base:Conda:~/anaconda3/bin/python, ~/opt/anaconda3/envs/XCS224N/bin/python::Conda:~/opt/anaconda3/envs/XCS224N/bin/python, ~/opt/anaconda3/envs/ap_env/bin/python::Conda:~/opt/anaconda3/envs/ap_env/bin/python, ~/opt/anaconda3/envs/rl_env/bin/python::Conda:~/opt/anaconda3/envs/rl_env/bin/python, ~/anaconda3/envs/apenv_MPS/bin/python:apenv_MPS:Conda:~/anaconda3/envs/apenv_MPS/bin/python, /opt/homebrew/Caskroom/miniforge/base/bin/python:base:Conda:/opt/homebrew/Caskroom/miniforge/base/bin/python, ~/anaconda3/envs/insurance/bin/python:insurance:Conda:~/anaconda3/envs/insurance/bin/python, ~/anaconda3/envs/test_env/bin/python:test_env:Conda:~/anaconda3/envs/test_env/bin/python, ~/anaconda3/envs/mps_env/bin/python:mps_env:Conda:~/anaconda3/envs/mps_env/bin/python, ~/anaconda3/envs/mps_env/bin/python:mps_env:Conda:~/anaconda3/envs/mps_env/bin/python, ~/anaconda3/envs/insurance_quant/bin/python:insurance_quant:Conda:~/anaconda3/envs/insurance_quant/bin/python
17:22:28.894 [debug] Refreshed Environments
17:22:29.326 [debug] IPyWidgetMessageDispatcher.initialize
17:22:29.327 [debug] Web view is ready to receive widget messages
17:22:29.336 [debug] Widget Message: Received IPyWidgets_kernelOptions in ScriptManager
17:22:29.336 [debug] Widget Message: Received IPyWidgetMessages.IPyWidgets_kernelOptions
17:22:29.340 [debug] IPyWidgetMessageDispatcher.initialize
17:22:29.340 [debug] IPyWidgetMessageDispatcher.initialize
17:22:29.348 [debug] Widget Message: data-base-url set to https://file%2B.vscode-resource.vscode-cdn.net~/.vscode/extensions/ms-toolsai.jupyter-2024.2.0-darwin-arm64/temp/scripts/120f3d3e554943f3cbc3c2597be1af8a8ebcddeb7fc8fc86d6650b2f67b81778/jupyter
17:22:29.349 [debug] Widget Message: Received IPyWidgets_kernelOptions in ScriptManager
17:22:29.349 [debug] Widget Message: Received IPyWidgetMessages.IPyWidgets_kernelOptions
17:22:29.349 [debug] Widget Message: data-base-url set to https://file%2B.vscode-resource.vscode-cdn.net~/.vscode/extensions/ms-toolsai.jupyter-2024.2.0-darwin-arm64/temp/scripts/120f3d3e554943f3cbc3c2597be1af8a8ebcddeb7fc8fc86d6650b2f67b81778/jupyter
17:22:29.349 [debug] Widget Message: Received IPyWidget scripts [{"moduleName":"jupyterlab-plotly","scriptUri":"https://file%2B.vscode-resource.vscode-cdn.net~/.vscode/extensions/ms-toolsai.jupyter-2024.2.0-darwin-arm64/temp/scripts/120f3d3e554943f3cbc3c2597be1af8a8ebcddeb7fc8fc86d6650b2f67b81778/jupyter/nbextensions/jupyterlab-plotly/index","source":"local"}]
17:22:29.349 [debug] Widget Message: Source for IPyWidget jupyterlab-plotly found in local @ https://file%2B.vscode-resource.vscode-cdn.net~/.vscode/extensions/ms-toolsai.jupyter-2024.2.0-darwin-arm64/temp/scripts/120f3d3e554943f3cbc3c2597be1af8a8ebcddeb7fc8fc86d6650b2f67b81778/jupyter/nbextensions/jupyterlab-plotly/index.
17:22:29.349 [debug] Widget Message: Registering IPyWidget jupyterlab-plotly found in https://file%2B.vscode-resource.vscode-cdn.net~/.vscode/extensions/ms-toolsai.jupyter-2024.2.0-darwin-arm64/temp/scripts/120f3d3e554943f3cbc3c2597be1af8a8ebcddeb7fc8fc86d6650b2f67b81778/jupyter/nbextensions/jupyterlab-plotly/index.
17:22:29.899 [info] End refreshing Kernel Picker<PHONE_NUMBER>307)
17:23:12.435 [info] End cell 1 execution after 43.637s, completed @<PHONE_NUMBER>434, started @<PHONE_NUMBER>797
17:23:12.435 [debug] Cell 1 executed successfully
17:23:25.301 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:23:25.326 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:23:29.516 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:23:29.546 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:23:30.675 [info] Generated code for 2 = <ipython-input-2-80f765278e1b> with 127 lines
17:23:30.692 [debug] Cell Index:2 sent to kernel
17:23:32.166 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:23:41.393 [debug] Start cell 2 execution @<PHONE_NUMBER>393 (clear output)
17:23:41.393 [info] Kernel acknowledged execution of cell 2 @<PHONE_NUMBER>393
17:23:41.394 [info] End cell 2 execution after 0.001s, completed @<PHONE_NUMBER>394, started @<PHONE_NUMBER>393
17:23:41.394 [debug] Cell 2 executed successfully
17:23:41.415 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:23:48.349 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:23:48.389 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:23:48.734 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:23:48.776 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:23:49.071 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:23:49.111 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:23:56.771 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:23:56.809 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:23:57.108 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:23:57.150 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:24:04.580 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:04.581 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:04.602 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:24:04.622 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:24:07.873 [info] Generated code for 3 = <ipython-input-3-580a1d29c2ff> with 9 lines
17:24:07.882 [debug] Cell Index:3 sent to kernel
17:24:09.141 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:09.144 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:09.145 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:10.357 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:10.358 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:10.361 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:11.781 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:27.011 [debug] Start cell 3 execution @<PHONE_NUMBER>011 (clear output)
17:24:27.011 [info] Kernel acknowledged execution of cell 3 @<PHONE_NUMBER>011
17:25:05.711 [info] End cell 3 execution after 38.7s, completed @<PHONE_NUMBER>711, started @<PHONE_NUMBER>011
17:25:05.711 [debug] Cell 3 executed successfully
17:25:05.732 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:05.753 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:05.774 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:05.794 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:05.815 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:05.836 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:05.858 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:05.912 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:25:05.916 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:25:05.920 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:25:05.923 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:25:05.926 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:25:05.930 [debug] Executing silently Code (idle) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:25:05.946 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:05.960 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:05.974 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:05.987 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:06.013 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:06.015 [debug] Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a with 1 output(s)
17:25:11.247 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:25:11.248 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:25:17.616 [info] Generated code for 4 = <ipython-input-4-51c3feeeec8b> with 1 lines
17:25:17.619 [debug] Cell Index:4 sent to kernel

Coding Language and Runtime Version
Python 3.9.18
Language Extension Version (if applicable)
Python Extension Version: 2024.2.1.
Anaconda Version (if applicable)
No response
Running Jupyter locally or remotely?
Local

@pietro1000
Please can you hide the variable viewer and see if this makes a difference.
The Jupyter variables viewer is either displayed on your left (Debugger Panel) or on the bottom Panel.
You can optionally hide/collapse both side bar and the output panels.
This should make a difference.
Please let me know.

Based on the following logs Cell 3 was sent at 17:24:07 & the kernel received the cell at 17:24:27
Looks like the kernel is busy.
17:24:07.873 [info] Generated code for 3 = <ipython-input-3-580a1d29c2ff> with 9 lines
17:24:07.882 [debug] Cell Index:3 sent to kernel
17:24:09.141 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:09.144 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:09.145 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:10.357 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:10.358 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:10.361 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:11.781 [debug] Executing silently Code (busy) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info a
17:24:27.011 [debug] Start cell 3 execution @<PHONE_NUMBER>011 (clear output)
17:24:27.011 [info] Kernel acknowledged execution of cell 3 @<PHONE_NUMBER>011

I have hidden the Jupyter variable viewer, and this helps—thank you so much!
Is it possible to add back the variables viewer without causing the kernel to get stuck retrieving variables? I do not understand why this happens; the code I am trying to run only uses 5 data frames

You could try the new built-in variable view with the setting "notebook.experimental.variablesView": true - A tree view with the variables should show up in the sidebar debug panel once you execute a cell. I'd be curious to see if that handles your scenario any better.
I'm not sure why it would take so long just to gather the variable info for 5 dataframes though, that is pretty strange. Does it repro for something simple like this:
df1 = pd.DataFrame({"Name": ["Alice", "Bob", "Charlie"],"Age": [25, 30, 35],"Gender": ["F", "M", "M"],})
df2 = pd.DataFrame({"Name": ["Alice", "Bob", "Charlie"],"Age": [25, 30, 35],"Gender": ["F", "M", "M"],})
df3 = pd.DataFrame({"Name": ["Alice", "Bob", "Charlie"],"Age": [25, 30, 35],"Gender": ["F", "M", "M"],})
df4 = pd.DataFrame({"Name": ["Alice", "Bob", "Charlie"],"Age": [25, 30, 35],"Gender": ["F", "M", "M"],})
df5 = pd.DataFrame({"Name": ["Alice", "Bob", "Charlie"],"Age": [25, 30, 35],"Gender": ["F", "M", "M"],})

@amunger, thank you so much for your help!
I've set "notebook.experimental.variablesView": true, and it works well. The variables are displayed in the left panel under "notebook variables" and the code executes without issues. However, I encounter a problem when I click on any of the data frames in the notebook variables panel: the kernel freezes. I suspect the issue arises because the data frames I'm working with are relatively large for Jupyter, despite consuming less than one-third of available RAM.
This issue does not occur with the example you provided or with smaller data frames.
Do you have any suggestions for using the interactive window with large datasets? Are there alternatives to closing the variables viewer or running the code through the Python debugger? Many thanks!

Thanks for the info, very helpful for us to test out the limitations. It sounds like were trying to pass too much data to the context menu.
Are you right clicking to try and get to the dataviewer for a dataframe? That isn't implemented yet for the new view.
I don't have a workaround for you currently, but we are trying to improve this area so hopefully it'll be solved soon.

I clicked on the dropdown menu next to the dataframe name out of curiosity to see what information was available. But, doing so caused the kernel to freeze. The screenshot below shows where it got stuck when I clicked on the ">" next to bond_char.

Also, if I leave the variables view from the debugger open without clicking on any variable, the Jupyter log still keeps printing Executing silently Code (completed) = def _VSCODE_getVariable(what_to_get, is_debugging, *args):\n# Query Jupyter server for the info with 1 output(s), but this time it doesn’t seem to interfere with the kernel's execution speed.
I also noticed that with the Jupyter variable viewer open the kernel uses significant CPU even while idle. Switching to the debugger's variables viewer solves this issue.
So the debugger variables viewer definitely helps! Thank you again!


🎉 Add new action:// step for creating TSV files and committing to Github repos

Motivation:
We often want to do something after we create the dataset - create TSV explorer file for commit to owid-content or pushing data as csv to Github repository. These side effects or "actions" currently require manual effort.
Solution:
Add new ActionStep named action://actions/namespace/version/short_name. This step can call arbitrary functions (e.g. create_explorer or commit_file_to_github) and will be executed only once (and again if dependencies change). It is triggered with --action flag (similar to --grapher flag).
This is an extension to Pablo's explorers solution (see the discussion in Notion).
TSV files for explorers
In addition to creating a local file in owid-content, we'll also upload it to the staging server.
Committing to Github repositories
Call commit_file_to_github to commit the file. It runs in dry mode unless ETL_ACTIONS_COMMIT is set in .env (supposed to be true only in production env).
I tried migrating co2_data step from external channel. It's just a proof of concept, we might not want to update it whenever there's a minor change in data (we are not creating new commits if files are identical).
TODO before merging

[ ] Make sure all files like minerals.py for creating explorer have the most recent changes from master

@pabloarosado I renamed it to ExportStep and used directory structure like export://github/co2_data/latest/owid_co2 or export://explorers/minerals/latest/minerals. Let me know what you think.


rubocop-daemon-wrapper removes escape characters if -s or --stdin args are present

When formatting a file on VSCode using rubocop-daemon-wrapper with ruby-rubocop, all escape characters like \t\r\n\a are removed from the current .rb file.
They seems to get removed when reading stdin with cat: https://github.com/fohte/rubocop-daemon/blob/master/bin/rubocop-daemon-wrapper#L53.
Expected after auto-correct on save:
def something
  puts "Test \t\r\n\a"
rescue StandardError => e
  Rails.logger.error "Exception occurred :\n#{@message}"
end

Actual behavior:
def something
  puts "Test
"
rescue StandardError => e
  Rails.logger.error "Exception occurred :
#{@message}"
end

PS: The daemon is a must when using rubocop auto-correct! Thanks you very much.

Hi @ericmatte, thanks for reporting this issue!
I've fixed the issue in e7e517e092aab5ece4a400c5eaf81c8d976fa82c (PR #9).
This fix is already merged in master, so could you try this?
Please let me know if there are any problems :)

This seems like quite a scary bug, and I need to go through our commit logs to see if we accidentally broke something in a subtle way... Would it be possible to add a test for this edge case to prevent future occurrences?

Hi @fohte, thank you for your quick response. It works great!

And @gurgeous, on our side, it was mostly some \n in strings, which were converted to a real newline. But this remains a valid syntax for newline in Ruby strings.

That said, a simple test would surely be a good idea.

Hi @gurgeous,
I also think that adding a simple test for the rubocop-daemon-wrapper would improve maintainablity.
I was trying out to add some test cases with Bats, but they are complicated a little.
For example, we have to mock the rubocop-daemon server.
I think it would be complicated and difficult to maintain continuously.
Futhermore, with Bash, we have to handle slightly different commands for each OS, like nc (#5).
So instead, I'm planning to switch to write lightweight rubocop-daemon client in Go.
That issues would be resolved by writing in Go. Because it can support cross-platform easily, and easy to read.

Great! Just out of curiosity - have you considered rewriting rubocop-daemon in ruby? At our company we have a policy that we write all scripts (no matter how long or short) in Ruby. It's worked out quite well for our team.

I had not considered rewritting rubocop-daemon client in Ruby.
It sounds like a great idea for me, as a first step!
However, Go is faster than Ruby, so I would like to provide the client written in Go in the future.
I think you might know, the client is already implemented in rubocop-daemon gem (you can use rubocop-daemon exec command), but it is not easy to integrate with editor because its interface is different from rubocop command.
First of all, I'll try to reimplement the client in Ruby with same interface as rubocop command! :smile:


Don't disable pay form if no routes are found

Right now we disable the pay form if we can't find any routes. The issue with the is lnd doesn't yet support private channels in queryRoutes/sendToRoute so if a user is trying to send to an invoice with hop hints Zap will not allow them to send.
We should still allow the user to attempt to send even if we don't find any routes.

closing with #1056 merged


Latest release is v1.9 and latest tag is v1.11

Why is version 1.9 being pointed as latest release under https://github.com/rupa/z/releases?
See https://github.com/Homebrew/homebrew-core/pull/19185/files/544bfac54391ee88d3c94ff14a114ff998cace9a

Oh, I see #205. Maybe you could consider removing the latest tags for the "unreleased" versions.


update cluster colocation profile

Signed-off-by: zwzhang0107<EMAIL_ADDRESS>Ⅰ. Describe what this PR does
Ⅱ. Does this pull request fix one issue?

Ⅲ. Describe how to verify it
Ⅳ. Special notes for reviews

/lgtm

/approve


Docker file fix.

[Goal]
Need to fix docker file to run devnet

Thanks for this fix, I couldn't run docker before now it works (macos).
One thing I was wondering, why do get the code from github (main branch) instead of local source?


Preview on a route with multiple dynamic segments breaking due to params leaking from other routes

Preview mode is breaking on a route with multiple dynamic segments learn/[courseSlug]/[sectionSlug]/[postSlug].
Is this a flawed implementation of the bottom up approach? When I console.log(params) I am getting the params for every post.
export async function generateStaticParams() {
  const paths = await getAllPostsSlugs();

  function loopParams(posts: Post[]) {
    const params: { courseSlug: string; sectionSlug: string; postSlug: string }[] = [];

    posts.forEach((post) => {
      const postSlug = post?.slug;
      post?.sections?.forEach((section) => {
        const sectionSlug = section?.slug;
        section?.courses?.forEach((course) => {
          const courseSlug = course?.slug;

          params.push({ courseSlug, sectionSlug, postSlug });
        });
      });
    });

    return params;
  }

  return loopParams(paths);
}

Let's say I have a post 1 and 2.
If I visit /course/section/1, I get:
{
  courseSlug: 'course',
  sectionSlug: 'section',
  postSlug: '1'
}
{
  courseSlug: 'course',
  sectionSlug: 'section',
  postSlug: '2'
}

Instead of just:
{
  courseSlug: 'course',
  sectionSlug: 'section',
  postSlug: '1'
}

Seems to be a Next.js issue, or my implementation of generateStaticParams is bad.

Hi, yeah there's not much we can do about the routing from next-sanity's side 😅


History export does not seem to be working

History export does not seem to be working. A transient tooltip says history is being exported.

No confirmation that the export has completed
No notification to open the file (like in the list export feature)
No way to share the file using the Android Share Sheet.
Possibly a broken export.

We should try to fix or implement as much of 1, 2, 3 and 4 as possible.

We should refresh this issue.

We should refresh this issue.

I think the history export and remove buttons have been disabled right now.
@VaiTon  @teolemon Does this issue need to be updated?

I think the history export and remove buttons have been disabled right now.
@VaiTon  @teolemon Does this issue need to be updated?

mostly fixed, closing


don't reuse the encoder in the integration tests

On first use, the encoder emits the required insert count. When comparing the lengths between a value encoded with and without using the static table, we need to make sure that both of them include the same overhead.

Codecov Report

Merging #18 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master      #18   +/-   ##
=======================================
  Coverage   91.42%   91.42%
=======================================
  Files           5        5
  Lines         233      233
=======================================
  Hits          213      213
  Misses         11       11
  Partials        9        9

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Backport: HBASE-24183 [flakey test] replication.TestAddToSerialReplicationPeer …

…(#1514)
Signed-off-by: Duo Zhang<EMAIL_ADDRESS>Signed-off-by: stack<EMAIL_ADDRESS>

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Something happened between Sage 9.0.0 and 9.0.1

Submit a feature request or bug report

[x] I've read the guidelines for Contributing to Roots Projects
[ ] This is a feature request
[x] This is a bug report
[x] This request isn't a duplicate of an existing issue
[x] I've read the docs and NPM Debugging Guidelines post and followed them (if applicable)
[x] This is not a personal support request that should be posted on the Roots Discourse forums

What is the current behavior?
Really can't debug this so hopefully someone can help my with it.
In my previous project based on Sage (9.0.0) I used https://jonsuh.com/hamburgers/
I'm adding file: autoload/_hamburgers.scss with following:
@import "~hamburgers/_sass/hamburgers/hamburgers"
when running:
yarn run build:production
all is working fine.
When I will use Sage 9.0.1 and do the same, only bootstrap is compiled and added to final css (like something breaked within hamburgers.scss)
This is not working only with production flag. In any other case it works fine.
No errors, no warnings or anything is thrown during this.
What is the expected or desired behavior?
To build all assets with success.

Bug report

Please provide steps to reproduce, including full log output:

Install fresh sage 9.0.1 (with bootstrap)
Install hamburgers by yarn add hamburgers
Add file autoload/_hamburgers.scss with content as specified above.
Add any style to main.scss after autoload (like body background red).
Run yarn run build:production

Please describe your local environment:
WordPress version: 4.9.6
OS: macOS Sierra 10.12.6
NPM/Node version: NPM 6.0.6 / Node 8.9.1
Where did the bug happen? Development or remote servers?
Both
Is there a related Discourse thread or were any utilized (please link them)?
No

Does yarn lint:styles pass?

Yup.
yarn lint:styles
yarn run v1.3.2
$ stylelint "resources/assets/styles/**/*.{css,sass,scss,sss,less}"
✨  Done in 1.13s.

@import "~hamburgers/_sass/hamburgers/hamburgers.scss";

@koentjuh1 The docs say the '.scss' extension isn't needed.

I think for now this would be better as a support request on Discourse as the ambiguity of the error/issue ("Something happened between Sage 9.0.0 and 9.0.1") requires a lot of back and forth for testing which notifies everyone who is watching Sage.
In my testing I was encountering the same issue — no styles after a production build — with the given instructions, however, I tested it in both 9.0.1 and 9.0.0 and received the same results. This leads me to believe it’s an issue of configuration and not a bug with Sage itself.
There is an official community contributed guide for setting up Hamburgers in Sage 9 which I do know works as I’ve setup my last few projects using it (even my personal fork of Sage which is on 9.0.1).

This solves the issue: https://github.com/roots/sage/issues/2017#issuecomment-361054297

Thanks @knowler for pointing this out. I'm closing this issue, as it's not an issue actually.
It works.


Add fixlayoutenuk extension

Description

Screencast

Checklist

[x] I read the extension guidelines
[x] I read the documentation about publishing
[x] I ran npm run build and tested this distribution build in Raycast
[x] I checked that files in the assets folder are used by the extension itself
[x] I checked that assets used by the README are placed outside of the metadata folder

This seems to be the same as this extension by @danulqua

This seems to be the same as this extension by @danulqua

Yes, it is similar but it have different behavior. Mentioned extension transforms the text only in one chosen direction. This extension transforms text in any direction depending on typed symbols, requires to select the text being transformed and also switches input language to continue typing in a proper lang.

This seems to be the same as this extension by @danulqua

Definitely 🙂

Hi @canab,
Still, your extension solves the same problem. But mine was built in a way that it's easy to add new languages for people who want to contribute, and it features all characters hidden behind additional layers (when holding ⌥ and ⇧).
Also, your extension has a huge problem:
tell application "System Events"
  keystroke space using {control down}
end tell

The shortcut is hardcoded, but people use different shortcuts for switching languages (I use Caps Lock). Additionally, a user could switch the input source after finishing typing. In that case, the language would be switched to the wrong one because there is no checking.
I didn't implement language auto-detection because of the problems you encountered, and there are many others. It's not that easy 🙂

Hi @danulqua, this is the first version and I am going to improve language detection before switching. I created it to fit my (and coworkers) needs. Bidirectional transformation is on of them. BTW, I am OK to cancel this submission if it does not fit in the reycast requirements.

Raycast has awesome feature called "Organizations".

You can create internal extensions and all users in your organization will have access to it.
Check out how the Raycast team benefits from it (link with the time code): https://youtu.be/xRnMXJcH9Pg?t=270

@danulqua thanks, I will look into it. It maybe a better solution for us.

Sounds like an organizational extension might be a better match here. I agree.


.save_gdf_shapefile returns ValueError

Trying to save building gdf's to a shapefile and getting a value error. Seems like it might be an issue with GeoPandas or Fiona? It returns the same error when I designate a specific filename and folder path.
I'm on Mac OS 10.12.3, using python 2.7.13, OSMnx 0.5.1
import osmnx as ox
%matplotlib inline
ox.config(log_console=True, use_cache=True)

G = ox.buildings_from_place(place='Piedmont, California, USA')
G_proj = ox.project_gdf(G)
ox.save_gdf_shapefile(G_proj)

error:
ValueError                                Traceback (most recent call last)
<ipython-input-12-820a8cb18c25> in <module>()
      1 G = ox.buildings_from_place(place='Piedmont, California, USA')
      2 G_proj = ox.project_gdf(G)
----> 3 ox.save_gdf_shapefile(G_proj)

/Users/kaseyklimes/anaconda2/lib/python2.7/site-packages/osmnx/save_load.pyc in save_gdf_shapefile(gdf, filename, folder)
     50     if not os.path.exists(folder_path):
     51         os.makedirs(folder_path)
---> 52     gdf.to_file(folder_path)
     53     if not hasattr(gdf, 'gdf_name'):
     54         gdf.gdf_name = 'unnamed'

/Users/kaseyklimes/anaconda2/lib/python2.7/site-packages/geopandas/geodataframe.pyc in to_file(self, filename, driver, schema, **kwargs)
    341         """
    342         from geopandas.io.file import to_file
--> 343         to_file(self, filename, driver, schema, **kwargs)
    344
    345     def to_crs(self, crs=None, epsg=None, inplace=False):

/Users/kaseyklimes/anaconda2/lib/python2.7/site-packages/geopandas/io/file.pyc in to_file(df, filename, driver, schema, **kwargs)
     61                     schema=schema, **kwargs) as c:
     62         for feature in df.iterfeatures():
---> 63             c.write(feature)
     64
     65

/Users/kaseyklimes/anaconda2/lib/python2.7/site-packages/fiona/collection.pyc in write(self, record)
    339     def write(self, record):
    340         """Stages a record for writing to disk."""
--> 341         self.writerecords([record])
    342
    343     def validate_record(self, record):

/Users/kaseyklimes/anaconda2/lib/python2.7/site-packages/fiona/collection.pyc in writerecords(self, records)
    333         if self.mode not in ('a', 'w'):
    334             raise IOError("collection not open for writing")
--> 335         self.session.writerecs(records, self)
    336         self._len = self.session.get_length()
    337         self._bounds = self.session.get_extent()

fiona/ogrext.pyx in fiona.ogrext.WritingSession.writerecs (fiona/ogrext2.c:17987)()

fiona/ogrext.pyx in fiona.ogrext.OGRFeatureBuilder.build (fiona/ogrext2.c:7030)()

ValueError: Invalid field type <type 'list'>

Right... the use case for which save_gdf_shapefile was designed was to save place shape GeoDataFrames. But this should be able to save building footprint GeoDataFrames as well. I changed the function so it converts all non-geometry columns to string type, so Fiona can save it as a shapefile, in 29dc216. Should work now. You can install the latest GitHub version to get this code now and I'll plan to release as a minor version soon.

when i use ox.gdfs_to_graph(nodes, edges)
i got this error:
AttributeError: 'GeoDataFrame' object has no attribute 'gdf_name'

the '.shp' files were downloaded before

(correctly download and save, '***' is only to hide the city)

when i use ox.gdfs_to_graph(nodes, edges)
i got this error:
AttributeError: 'GeoDataFrame' object has no attribute 'gdf_name'

the '.shp' files were downloaded before

(correctly download and save, '***' is only to hide the city)

@gboeing thanks
sorry, i haven't described it clearly. i just want to create a graph from the data i have downloaded from these apis:

so i use that function and data read by GeoPandas, is that right?  Or other methods?

@SqySimmon if you want to re-load data you previously downloaded using OSMnx, use the graphml file format via ox.save_graphml and ox.load_graphml. See the documentation and example notebooks for demonstration.


VM-like masking of total memory and CPUs at /proc

I'm not sure if this is out-of-scope or not, but yet I'm opening this issue for discussing.
When we run:
$ docker run --rm --memory 500Mi ubuntu free -h
              total        used        free      shared  buff/cache   available
Mem:          7.7Gi       2.6Gi       186Mi       4.1Gi       4.9Gi       839Mi
Swap:         2.0Gi       1.0Gi       1.0Gi

It shows the total memory of the host machine despite of the --memory constraint. The same happens when using sysbox-runc. This is intended.
The thing is: as Sysbox claims to transform containers to VM-like ones, would it be possible to allow Sysbox to enforce the total memory which the container will recognize just like normal VMs?
By using --memory today, if my containers trespass the limit, they gets killed. Ideally, I would like the containers not to recognize the total memory, so they handle the available memory the way they want without being killed by the daemon. In a CI/CD build pool it's a very desired feature, as I can set a given number of resources for each build and I do not have control over what happens in such builds.
The same rationale and use case applies for CPUs as well.

Hi @felipecrs, yes this is very much a feature we have in mind for Sysbox. Not just for memory, but also for CPUs.
The key is to have Sysbox "virtualize" the /proc/meminfo and /proc/cpuinfo resources exposed inside the containers, according to the corresponding cgroup limits assigned to the container. While Sysbox has the underlying infrastructure to do this already, we've not had the work cycles yet to implement this feature.
Also, it's not clear to us if this will be a Sysbox Enterprise only feature, or if it will go into Sysbox Community Edition too. It's one of those things we must carefully think about to create a balance between community benefit vs. sustainable business.

I'm very happy to know that this feature is considered!
And yes, I should have included CPUs in the original story as the rationale and use case applies for both.
Regarding CE vs EE:

Any features that mainly benefit individual practitioners are made part of the Sysbox open-source project. Any features that mainly address enterprise-level needs are reserved for the Sysbox Enterprise Edition.

I'm not sure yet if it applies more to the first than to the second, despite it would be certainly useful for individual practitioners. As contrast, the limit on the number of containers allocated per worker being limited to 16 on the CE is clearly something that is not a blocker for individual practitioners but certainly a considerable constraint for enterprise-level needs.

FYI, we are hoping to get to get to this feature before the year is over.

Out of curiosity, I found https://github.com/fabiokung/procg. I'm sending here in case it can be useful as a reference for implementation, or something like that.

Out of curiosity, I found https://github.com/fabiokung/procg. I'm sending here in case it can be useful as a reference for implementation, or something like that.

Thanks @felipecrs; I'll take a look as several users are now asking for /proc/cpuinfo and /proc/meminfo emulation in Sysbox containers. We were hoping to get to this by last year's end, but looks like it will be closer to first half of this year.

For completeness, in a K8s environment, I was able to achieve this result by using:

https://github.com/cndoit18/lxcfs-on-kubernetes

Together with CPU Management Policy as Static:

https://kubernetes.io/docs/tasks/administer-cluster/cpu-management-policies/#static-policy

Because for some reason, lxcfs isn't masking CPU by itself (but it works for memory).

lxcfs by itself is easy to setup using this helm chart, but changing the CPU Management Policy configuration in kubelet can be a challenge depending on how your cluster is provisioned.
Not to mention that it would apply such a policy for all pods, without the option to customize.

So, it would still be extremely nice to have this feature in Sysbox itself.

Thanks @felipecrs, that all makes sense. And yes, a Sysbox based approach should provide more flexibility by allowing the user to specify per-pod resources, ideally by honoring the cgroup constraints defined by the user.

I noticed this in the latest release notes:

Fix sysbox emulation of /proc and /sys in containers for kernels 6.5+

Is there any chance this is implemented already?

I noticed this in the latest release notes:

Fix sysbox emulation of /proc and /sys in containers for kernels 6.5+

Hi @felipecrs, no I don't believe so; the fix described above refers to a problem where starting with kernel 6.5+, sysbox's emulation of /proc and /sys inside a container was totally broken due to a change in the kernel. It does not address this current issue unfortunately. Thanks.

Got it. Thank you!


Add support of Pandas 1.0.* in python client

Pandas 1.0.0 has been release in January 2020.
Update the pandas dependency in the Python client to that version or later.

Closed with release of client V2


Spider: Clayton Board Of Aldermen

URL: https://www.claytonmo.gov/government/mayor-board-of-aldermen
Calendar URL: https://www.claytonmo.gov/calendar/meetings/-toggle-all/-seldept-2
Spider Name: clay_aldermen
Agency Name: Clayton Board Of Aldermen
See the contribution guide for information on how to get started

I can work on this spider


CLOUD-50403 mesos/marathon support

Please @akanto or @keyki

Jenkins build failed.
Refer to this link for build results: http://ci.sequenceiq.com/job/cloudbreak-pull-request/2125/

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Fix failing to build iModelPlatform performance tests

Changes

Addressed breaking changes for iModelPlatform performance tests

Note: the changes do not make all the tests pass, just enable means to build and run them in a simplified manner.

Added documentation on how to build the performance tests, as well as launch.json tasks for each of the performance test batches for Windows environment.
Organized launch.json tasks by platform and/or purpose (additionally removed duplicate tasks)

Before
After

/azp run imodel-native

/azp run imodel-native


Update build.gradle to improve compatibility with other projects that use Cardinal Components API

This should fix a bug I found when setting up a dev environment for an addon that uses Artifacts API. It was putting two copies of CC in the dev environment, one under the maven group "io.github.OnyxStudios.Cardinal-Components-API" and one under "io.github.onyxstudios.Cardinal-Components-API", and since the CC README says to use the lowercase version, the latter would likely offer better compatibility. Note that without the temporary fix I used in my buildscript, the project could build as normal, but the launch profile would not run correctly.

This is implemented in 0.7.1, however I did it myself when I also changed some other stuff about the dependencies (such as which repo CCA is pulled from, etc). Therefore I'll close this PR.