Crash due to failed assertion in fill_order

#0  0x00007ffff6c01cc9 in __GI_raise (sig=sig@entry=6) at ../nptl/sysdeps/unix/sysv/linux/raise.c:56
#1  0x00007ffff6c050d8 in __GI_abort () at abort.c:89
#2  0x00007ffff6bfab86 in __assert_fail_base (fmt=0x7ffff6d4b830 "%s%s%s:%u: %s%sAssertion `%s' failed.\n%n", assertion=assertion@entry=0x2b959d0 "order.get_collateral() >= pays",
    file=file@entry=0x2b956b8 "src/graphene/libraries/chain/db_market.cpp", line=line@entry=290,
    function=function@entry=0x2bc02c0 <graphene::chain::database::fill_order(graphene::chain::call_order_object const&, graphene::chain::asset const&, graphene::chain::asset const&)::__PRETTY_FUNCTION__> "bool graphene::chain::database::fill_order(const graphene::chain::call_order_object&, const graphene::chain::asset&, const graphene::chain::asset&)") at assert.c:92
#3  0x00007ffff6bfac32 in __GI___assert_fail (assertion=0x2b959d0 "order.get_collateral() >= pays", file=0x2b956b8 "src/graphene/libraries/chain/db_market.cpp", line=290,
    function=0x2bc02c0 <graphene::chain::database::fill_order(graphene::chain::call_order_object const&, graphene::chain::asset const&, graphene::chain::asset const&)::__PRETTY_FUNCTION__> "bool graphene::chain::database::fill_order(const graphene::chain::call_order_object&, const graphene::chain::asset&, const graphene::chain::asset&)") at assert.c:101
#4  0x00000000023dd9b0 in graphene::chain::database::fill_order (this=0x7062278, order=..., pays=..., receives=...) at src/graphene/libraries/chain/db_market.cpp:290
#5  0x00000000023dd237 in graphene::chain::database::match (this=0x7062278, call=..., settle=..., match_price=..., max_settlement=...) at src/graphene/libraries/chain/db_market.cpp:239
#6  0x00000000023e30b1 in graphene::chain::database::clear_expired_orders (this=0x7062278) at src/graphene/libraries/chain/db_update.cpp:237
#7  0x00000000023c3b50 in graphene::chain::database::_apply_block (this=0x7062278, next_block=...) at src/graphene/libraries/chain/db_block.cpp:490
#8  0x00000000023c301a in graphene::chain::database::__lambda19::operator() (__closure=0x7ffff63c9070) at src/graphene/libraries/chain/db_block.cpp:448
#9  0x00000000023e4137 in graphene::chain::detail::with_skip_flags<graphene::chain::database::apply_block(const graphene::chain::signed_block&, uint32_t)::__lambda19>(graphene::chain::database &, uint32_t, graphene::chain::database::__lambda19) (db=..., skip_flags=0, callback=...) at src/graphene/libraries/chain/include/graphene/chain/db_with.hpp:123
#10 0x00000000023c3431 in graphene::chain::database::apply_block (this=0x7062278, next_block=..., skip=0) at src/graphene/libraries/chain/db_block.cpp:449
#11 0x00000000023bc64c in graphene::chain::database::_push_block (this=0x7062278, new_block=...) at src/graphene/libraries/chain/db_block.cpp:185
#12 0x00000000023bbc31 in graphene::chain::database::__lambda15::__lambda16::operator() (__closure=0x7ffff63c9610) at src/graphene/libraries/chain/db_block.cpp:112
#13 0x00000000023e3f40 in graphene::chain::detail::without_pending_transactions<graphene::chain::database::push_block(const graphene::chain::signed_block&, uint32_t)::__lambda15::__lambda16>(graphene::chain::database &, <unknown type in src/graphene/programs/witness_node/witness_node, CU 0x10d33a9, DIE 0x13264b4>, graphene::chain::database::__lambda15::__lambda16) (db=...,
    pending_transactions=<unknown type in src/graphene/programs/witness_node/witness_node, CU 0x10d33a9, DIE 0x13264b4>, callback=...)
    at src/graphene/libraries/chain/include/graphene/chain/db_with.hpp:140
#14 0x00000000023bbcad in graphene::chain::database::__lambda15::operator() (__closure=0x7ffff63c96b0) at src/graphene/libraries/chain/db_block.cpp:113
#15 0x00000000023e3fbb in graphene::chain::detail::with_skip_flags<graphene::chain::database::push_block(const graphene::chain::signed_block&, uint32_t)::__lambda15>(graphene::chain::database &, uint32_t, graphene::chain::database::__lambda15) (db=..., skip_flags=0, callback=...) at src/graphene/libraries/chain/include/graphene/chain/db_with.hpp:123
#16 0x00000000023bbd06 in graphene::chain::database::push_block (this=0x7062278, new_block=..., skip=0) at src/graphene/libraries/chain/db_block.cpp:114
#17 0x000000000204359a in graphene::app::detail::application_impl::handle_block (this=0x7062140, blk_msg=..., sync_mode=false, contained_transaction_message_ids=...) at src/graphene/libraries/app/application.cpp:396
#18 0x00000000028ec941 in graphene::net::detail::statistics_gathering_node_delegate_wrapper::__lambda54::operator() (__closure=0x7fffd8268cf8) at src/graphene/libraries/net/node.cpp:5325
#19 0x00000000028fcf7e in fc::detail::functor_run<graphene::net::detail::statistics_gathering_node_delegate_wrapper::handle_block(const graphene::net::block_message&, bool, std::vector<fc::ripemd160>&)::__lambda54>::run(void *, void *)
    (functor=0x7fffd8268cf8, prom=0x7fffd8268de8) at src/graphene/libraries/fc/include/fc/thread/task.hpp:77
#20 0x00000000026c7035 in fc::task_base::run_impl (this=0x7fffd8268d20) at src/graphene/libraries/fc/src/thread/task.cpp:43
#21 0x00000000026c6fc6 in fc::task_base::run (this=0x7fffd8268d20) at src/graphene/libraries/fc/src/thread/task.cpp:32
#22 0x00000000026bb9e6 in fc::thread_d::run_next_task (this=0x7096110) at src/graphene/libraries/fc/src/thread/thread_d.hpp:498
#23 0x00000000026bbe8a in fc::thread_d::process_tasks (this=0x7096110) at src/graphene/libraries/fc/src/thread/thread_d.hpp:547
#24 0x00000000026bb4fd in fc::thread_d::start_process_tasks (my=118055184) at src/graphene/libraries/fc/src/thread/thread_d.hpp:475
#25 0x0000000002a14691 in make_fcontext () at libs/context/src/asm/make_x86_64_sysv_elf_gas.S:64
#26 0x0000000000000000 in ?? ()

1203002ms th_a       witness.cpp:176               block_production_loo ] Generated block #314814 with timestamp 2015-09-30T08:20:03 at time 2015-09-30T08:20:03
1203020ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1203029ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1203085ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1203102ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1203104ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1203111ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1203115ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1203258ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1203366ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1203520ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1206000ms th_a       witness.cpp:182               block_production_loo ] Not producing block because it isn't my turn
1206944ms th_a       application.cpp:388           handle_block         ] Got block #314814 with time 2015-09-30T08:20:06 from network with latency of 940 ms from mr.agsexplorer
1207000ms th_a       witness.cpp:182               block_production_loo ] Not producing block because it isn't my turn
1207022ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1207024ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1207051ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1207260ms th_a       application.cpp:518           get_item             ] Serving up block #314814
1208000ms th_a       witness.cpp:182               block_production_loo ] Not producing block because it isn't my turn
1209000ms th_a       witness.cpp:182               block_production_loo ] Not producing block because it isn't my turn
1209175ms th_a       application.cpp:388           handle_block         ] Got block #314815 with time 2015-09-30T08:20:09 from network with latency of 170 ms from dele-puppy
witness_node:src/graphene/libraries/chain/db_market.cpp:290: bool graphene::chain::database::fill_order(const graphene::chain::call_order_object&, const graphene::chain::asset&, const graphene::chain::asset&): Assertion `order.get_collateral() >= pays' failed.

Sometime between block 134000 and 135000 a margin position was updated
nt_feed.settlement_price: {"base":{"amount":995,"asset_id":"1.3.626"},"quote":{"amount":100000,"asset_id":"1.3.0"}}
42.5677%   134000 of 314793
505722ms th_a       market_evaluator.cpp:186      operator()           ] call.call_price: {"base":{"amount":24451451,"asset_id":"1.3.0"},"quote":{"amount":14000,"asset_id":"1.3.626"}} call.call_price.to_real(): 1746.53221428571418983 (~call.call_price).to_real(): 0.00057256315790830
505722ms th_a       market_evaluator.cpp:189      operator()           ] swan_price: {"base":{"amount":1000000,"asset_id":"1.3.626"},"quote":{"amount":3056431375,"asset_id":"1.3.0"}} swan_price.to_real(): 0.00032717894737617 (~swan_price).to_real(): 3056.43137500000011642
505722ms th_a       market_evaluator.cpp:251      do_apply             ] ~call_obj->call_price: {"base":{"amount":14000,"asset_id":"1.3.626"},"quote":{"amount":24451451,"asset_id":"1.3.0"}} "<": < _bitasset_data->current_feed.settlement_price: {"base":{"amount":62164,"asset_id":"1.3.626"},"quote":{"amount":95000000,"asset_id":"1.3.0"}}
43.203%   136000 of 314793
505926ms th_a       market_evaluator.cpp:204      operator()           ] call.call_price: {"base":{"amount":100502513,"asset_id":"1.3.0"},"quote":{"amount":87500,"asset_id":"1.3.626"}} call.call_price.to_real(): 1148.60014857142846267 (~call.call_price).to_real(): 0.00087062499621278
505926ms th_a       market_evaluator.cpp:205      operator()           ] swan_price: {"base":{"amount":100000,"asset_id":"1.3.626"},"quote":{"amount":201005026,"asset_id":"1.3.0"}} swan_price.to_real(): 0.00049749999783588 (~swan_price).to_real(): 2010.05025999999998021
505926ms th_a       market_evaluator.cpp:208      operator()           ] _bitasset_data->current_feed.settlement_price.to_real(): 0.00995000000000000 (~_bitasset_data->current_feed.settlement_price).to_real():<PHONE_NUMBER>6281407564 _bitasset_data->current_feed.settlement_price: {"base":{"amount":995,"asset_id":"1.3.626"},"quote":{"amount":100000,"asset_id":"1.3.0"}}
505926ms th_a       market_evaluator.cpp:251      do_apply             ] ~call_obj->call_price: {"base":{"amount":87500,"asset_id":"1.3.626"},"quote":{"amount":100502513,"asset_id":"1.3.0"}} "<": < _bitasset_data->current_feed.settlement_price: {"base":{"amount":995,"asset_id":"1.3.626"},"quote":{"amount":100000,"asset_id":"1.3.0"}}
505928ms th_a       market_evaluator.cpp:204      operator()           ] call.call_price: {"base":{"amount":9547739,"asset_id":"1.3.0"},"quote":{"amount":87500,"asset_id":"1.3.626"}} call.call_price.to_real():<PHONE_NUMBER>4285713649 (~call.call_price).to_real(): 0.00916447338998270
505935ms th_a       market_evaluator.cpp:205      operator()           ] swan_price: {"base":{"amount":100000,"asset_id":"1.3.626"},"quote":{"amount":19095478,"asset_id":"1.3.0"}} swan_price.to_real(): 0.00523684193713297 (~swan_price).to_real():<PHONE_NUMBER>9999999952
505935ms th_a       market_evaluator.cpp:208      operator()           ] _bitasset_data->current_feed.settlement_price.to_real(): 0.00995000000000000 (~_bitasset_data->current_feed.settlement_price).to_real():<PHONE_NUMBER>6281407564 _bitasset_data->current_feed.settlement_price: {"base":{"amount":995,"asset_id":"1.3.626"},"quote":{"amount":100000,"asset_id":"1.3.0"}}
This margin position set the call price to .0052  (non normalized for USD/CORE precision) which is about 10x higher than the normal price.   This was allowed at the time because the price feed was off by a factor of 10.
Time passes and the feed is corrected.
Someone issues a force settle operation, but the force settle price is beyond black swan.   This needs to be anticipated and trigger a black swan rather than halt the network.
The question remains is should the black swan have occurred between the price feed correction and the force settlement and if so, why didn't it.


Using only VIO without mapping & loop closures

Hi, I am building the docker file but it is taking an extremely long time to compile the Foxy dependencies such as rviz and ompl. If I only intend to use VIO, do i still need to install nav2, rviz, ompl, velodyne, triton, tao converter, pytorch, onnx in the docker container?
Thanks

Tested, yes to speed up build just for VIO/vSLAM on a realsense, please remove everything i mentioned on top. There could still be more packages that can be removed. Yet to test.


obfuscation feedback ui: accepting none should replace multi tagged field with single none tag

adds ability to replace all annotations for a compliance field with identifierType none when the suggestion is accepted
refactors StackedAvatarList component api with action to handle any menu option selection

Codecov Report

Merging #1427 into master will decrease coverage by 0.02%.
The diff coverage is 53.33%.

@@            Coverage Diff             @@
##           master    #1427      +/-   ##
==========================================
- Coverage   60.63%   60.61%   -0.03%
==========================================
  Files         184      184
  Lines        4044     4047       +3
  Branches      936      935       -1
==========================================
+ Hits         2452     2453       +1
- Misses       1592     1594       +2

Impacted Files
Coverage Δ

wherehows-web/app/components/dataset-aclaccess.ts
75% <ø> (ø)
:arrow_up:

wherehows-web/app/constants/datasets/owner.ts
92.3% <ø> (+3.41%)
:arrow_up:

...mponents/datasets/containers/dataset-owner-list.ts
34.61% <100%> (-1.75%)
:arrow_down:

wherehows-web/app/routes/application.js
83.33% <100%> (ø)
:arrow_up:

wherehows-web/app/constants/avatars/avatars.ts
100% <100%> (ø)
:arrow_up:

wherehows-web/app/components/dataset-authors.ts
92.95% <100%> (ø)
:arrow_up:

...eb/app/components/dataset-compliance-rollup-row.ts
21.62% <16.66%> (+6.55%)
:arrow_up:

...web/app/components/avatars/stacked-avatars-list.ts
46.15% <33.33%> (+1.7%)
:arrow_up:

wherehows-web/app/components/purge-policy.ts
81.48% <0%> (-18.52%)
:arrow_down:

... and 3 more

Continue to review full report at Codecov.

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 34bcbfc...797bf72. Read the comment docs.

Coverage remained the same at 22.974% when pulling 797bf7265bed96fd5e472ede30617547a6669e41 on theseyi:obfuscation-feedback-ui into 34bcbfc56d56c6063b28120519717827bd03db71 on linkedin:master.


Shall we move ahead even if file var is invalid (or null) ?

https://github.com/hnccbits/passgen-cpp/blob/77d17295a96bac7382ee9fd9f5df489f8e19d870/src/engine.cpp#L25

Thanks for pointing out. The program should stop in this case  :)


Added generator support for PlatformIO

Thanks.
I wonder if automatic test for this could be added somehow. Preferrably as a GitHub CI task or similar.

Ok, I will add test

@PetteriAimonen where to put test platformio project?
I think tests folder is not good place beacuse it has specific structure?
I can make something like tests_extra folder for this case, or could you point me to better place?

If it is possible to do as a Github workflow, .github/workflows would be the correct place.
The tests folder is indeed mainly for unit tests, while this is more like an integration test.

I know about workflows, but tests require some specific C-code with hello world and ini file.
So, seems that workflows folder is not good place for that.
I think it will be better to put to workflows only some commands which run actual test.
Workflow plan:

Setup platformio
Run platformio build of the some test project(s).

So, I need some place inside repository to put test projects for step 2.

Could the test project go into examples/platformio?
CMake builds are currently tested in a similar way by building examples/cmake_simple.

Could the test project go into examples/platformio?

Ok. I will do in this way.
Thank you.

@PetteriAimonen all tests done

Awesome! Thanks a lot!


Chore: go mod update

updated go mod dependency to latest version
Signed-off-by: Tanryberdi<EMAIL_ADDRESS>
See #3

@vaguecoder could you please review? 🙏

Thanks @tanryberdi


fine-tuning of toNumber function

parseFloat() support only one param, see MDN: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/parseFloat
maybe it's better to use isNaN() to judge the conversion result?

Thanks!


[WIP] Set priority of layers to 12

To make sure that specific components can override/redefine settings from more generic levels, we set the following priorities for levels:
meta-xt-common     -  8
meta-xt-<platform> - 10
meta-<product>     - 12

Signed-off-by: Ruslan Shymkevych<EMAIL_ADDRESS>

Testing is ongoing.


no show font

hi
I user pivotUI() loaded from CSV but I use a non-English character as a weird character.
Please introduce me thanks.

I can solve the problem by changing Files format CVS to TXT
Thank for pivottable. It was wonderful I Love more.


[📚] Link to docs is broken

Please describe your documentation issue or suggested improvement in detail here and provide links to any pre-existing/relevant documentation and screenshots if necessary:
The link to the docs is broken, the current link is:
https://firebase.flutter.dev/docs/dynamic-links/usage
The correct link is:
https://firebase.flutter.dev/docs/dynamic-links/overview
Thanks.

Hi @tinyCoder32, @daikini , @anaisbetts , @sethladd , @kevmoo . I also noticed that a few links under "Next Steps" heading are broken which are named as:

creating link with  Flutter Client
Receive Dynamic Links:

in the file path :docs/dynamic-links/overview.mdx.
Thus, I was wondering can I fix it if you could provide me with the correct link?
Thanks 😃

@Akshit6828
Please don't unnecessarily tag people who may not be directly related to this issue or plugin. Please refrain from doing so going forward.

Hi, @darshankawar apologies for any inconvenience. Actually, I wasn't sure about who is the right person for it. Thus I thought, to bring it to notice!

Closing in favour of tracking this issue here. Thanks!


Add density test to load test

What type of PR is this?
/kind feature

What this PR does / why we need it:
Which issue(s) this PR fixes:

Fixes #
Special notes for your reviewer:
Does this PR introduce a user-facing change?:

Additional documentation e.g., KEPs (Kubernetes Enhancement Proposals), usage docs, etc.:

/ok-to-test

This failure suggests that something is broken:
- PodStartupLatency error: metric PodStartupLatency has not been started

@wojtek-t yes, I saw it. I will check it ;)

/retest

@marseel, LGTM once you flip "ENABLE_DENSITY_TEST" back to "false".

@marseel - something strange happened to this PR - it has a lot of lines.
Also - please squash the commits.

@wojtek-t yea, I was rebasing it.
I've squash commits.

/lgtm
/approve


⚠ Bofrost.de has degraded performance

In c7bf1f2, Bofrost.de (https://www.bofrost.de) experienced degraded performance:

HTTP code: 200
Response time: 1116 ms

Resolved: Bofrost.de performance has improved in 51aa739.


Fix - Impacting SLA: System.ArgumentNullException

Description
Fixed SLA impacting issue where customer's request without content-type header somehow made it to the service. This was resulting in a 5xx error because of the EnsureArg check in place.
I have removed this check and also updated the Handler and Reader tests such that we validate the possible input values for content-type header.
After this change, instead of 5xx status code, user should receive a 415 result code indicating that the media type is unsupported.
Related issues
AB#94228.
Testing

Updated handler and receiver tests.
All existing tests are passing.

Are we able to reproduce the conditions that would lead to this happening?

No, we were not able to reproduce it. The controller has a Consumes attribute filter for the ContentType header. This should not have happened in the first place. I also synced with Smitha on this, and removing the EnsureArg check seemed to be the proper solution for this issue.


What APIs does esp_radar use?

Are the APIs used by esp_radar available to everyone (e.g. wifi_csi_info_t)or does it have access to additional low level information? Will it be open source?

The wifi_csi_info_t is used, but the processing is encapsulated
There are open source plans


Problems in using dev tools

It is difficult to use the dev tools as whenever we type d, it closes (hence cannot use any words that have the letter d).
Possible solution: Using CTRL + d or CMD + d or the default one as mentioned in Chrome-devtools/shortcuts

@apnerve this is a very good point indeed, juste updated the shortcut to "Control+d"


🔴 Ecosystem Project Idea: Embedded Gateway Widget

What is an Ecosystem Project Idea?
An Ecosystem Project Idea is an idea for a project that someone could build within the Optimism ecosystem. As opposed to an Ecosystem Concept or an Ecosystem Idea, an Ecosystem Project is generally more fleshed out and corresponds to a relatively clear product to be built.

Summary
The Optimism Gateway app is an easy way to transfer funds to and from OP Mainnet. Can you create an embedded version of the Gateway that other applications can easily include in their own websites? Ideally, this looks like a widget with a great design that mirrors the Optimism Gateway design.
Possible Features

Allow app developers to add the Embedded Gateway Widget to their own websites.
Allow users to bridge funds to/from OP Mainnet via the Embedded Gateway Widget.

Would you consider this as a solution?

has OP gateway
a bunch of third party bridges as well for fast withdraws
is completely open source and charges no fee
is really good and being used in production by good teams

https://docs.socket.tech/socket-liquidity-layer/use-socketll/socket-plugin

hi im going to start working on this

hi im going to start working on this

That'll be great


Add CI job to build macOS dependencies

This would not generate a container image, but provide the equivalent machine setup for macOS.

We have this in https://github.com/acts-project/ci-dependencies


netlify api Command doesn't work when you don't pass the data flag to it

- Do you want to request a feature or report a bug?
bug/feature
- What is the current behavior?
I don't know if it's intended or not (it seems like it is, but I can't find out why). but the netlify api command doesn't work at all when no data is passed to it. I've struggled with it a lot until I found that I need to pass a JSON even when the API endpoint doesn't need it (for example the getCurrentUser endpoint)
- What is the expected behavior?
CLI sends the request with an empty JSON as the payload when no data is provided.
I'm going to open a pull request that solves this issue. please review it when you found time.

Seems like the PR fixed this one. Thanks @Eddie-CooRo


CLI won't fail if mlcube task returns a python Error

Medperf currently identifies runtime errors by checking the subprocess exitcode and failing if it is not 0. This won't catch errors caused inside the MLCube, as even though the task fails, MLCube returns exitcode 0.
Example log:
2021-12-15 14:35:01,403 | INFO: Running Cube 'xrv_prep': mlcube run --mlcube=/Users/aristizabal-factored/.medperf/cubes/1/mlcube.yaml --task=sanity_check data_path=/Users/aristizabal-factored/.medperf/data/tmp_1639614896/data
2021-12-15 14:35:03,154 | DEBUG: Traceback (most recent call last):
2021-12-15 14:35:03,154 | DEBUG:
2021-12-15 14:35:03,155 | DEBUG: File "check.py", line 51, in <module>
2021-12-15 14:35:03,155 | DEBUG:
2021-12-15 14:35:03,156 | DEBUG: checker = Checker(args.data_path, params["output_datafile"])
2021-12-15 14:35:03,156 | DEBUG:
2021-12-15 14:35:03,157 | DEBUG: File "check.py", line 13, in __init__
2021-12-15 14:35:03,157 | DEBUG:
2021-12-15 14:35:03,158 | DEBUG: self.df = pd.read_csv(self.data_file)
2021-12-15 14:35:03,158 | DEBUG:
2021-12-15 14:35:03,159 | DEBUG: File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 688, in read_csv
2021-12-15 14:35:03,159 | DEBUG:
2021-12-15 14:35:03,160 | DEBUG: return _read(filepath_or_buffer, kwds)
2021-12-15 14:35:03,160 | DEBUG:
2021-12-15 14:35:03,162 | DEBUG: File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 454, in _read
2021-12-15 14:35:03,162 | DEBUG:
2021-12-15 14:35:03,162 | DEBUG: parser = TextFileReader(fp_or_buf, **kwds)
2021-12-15 14:35:03,163 | DEBUG:
2021-12-15 14:35:03,164 | DEBUG: File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 948, in __init__
2021-12-15 14:35:03,164 | DEBUG:
2021-12-15 14:35:03,165 | DEBUG: self._make_engine(self.engine)
2021-12-15 14:35:03,165 | DEBUG:
2021-12-15 14:35:03,167 | DEBUG: File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 1180, in _make_engine
2021-12-15 14:35:03,167 | DEBUG:
2021-12-15 14:35:03,168 | DEBUG: self._engine = CParserWrapper(self.f, **self.options)
2021-12-15 14:35:03,168 | DEBUG:
2021-12-15 14:35:03,169 | DEBUG: File "/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py", line 2010, in __init__
2021-12-15 14:35:03,170 | DEBUG:
2021-12-15 14:35:03,170 | DEBUG: self._reader = parsers.TextReader(src, **kwds)
2021-12-15 14:35:03,170 | DEBUG:
2021-12-15 14:35:03,171 | DEBUG: File "pandas/_libs/parsers.pyx", line 382, in pandas._libs.parsers.TextReader.__cinit__
2021-12-15 14:35:03,172 | DEBUG:
2021-12-15 14:35:03,172 | DEBUG:
2021-12-15 14:35:03,173 | DEBUG: File "pandas/_libs/parsers.pyx", line 674, in pandas._libs.parsers.TextReader._setup_parser_source
2021-12-15 14:35:03,173 | DEBUG:
2021-12-15 14:35:03,175 | DEBUG: FileNotFoundError: [Errno 2] No such file or directory: '/mlcube_io0/data/data.csv'
2021-12-15 14:35:03,175 | DEBUG:
2021-12-15 14:35:03,505 | DEBUG: Cube processes returned 0

This has been reported to the MLCube team, and they'll see how they can propagate exit status / termination status so it can be detected by Medperf

MLCube v0.0.6 fixes this issue


ND imagery

now, 3- and 4-band images are accommodated, but needs to be generalized to ND images, stored as nparrays or multiband tiffs

makedatasets needs to be updated so it can store the image as an ND array

train model needs to be updated so it can use the ND array (and detect automatically / generalize to any N)

seg_images needs a utility pre-processing script to get multiple coincident bands into an input npz

function that

points at a directory containing multiple coincident/concurrent bands with the same file root
pairs them up and puts them into npz files
also put any geosptial metadata into that npz file

3 options

preprocessing + make datasets reads config > 3 bands
separate make and train routines
super function / loaders --> calls appropriate functions - remove the if/else options

The only sane way to deal with this is to have one "makedatasets" function that deals with all cases

unpadded 1-3 band imagery
padded 1-3 band imagery
unpadded 4+ band imagery
padded 4+ band imagery (basically, satellite data i.e. most of the data I will use going forward)

currently, only 1 and 2 implemented and tested
However, I will implement a "make_nd_datasets" function first that will generalize all 4 cases. Case 1 users (above) can keep using 'make_datasets' for now

images need to be padded first
then a non-augmented set created (just 1! current implementation makes AUG LOOPS copies...)
then (and only then) an augmented set
generators need to be generalized to deal with more than 1 image file

ideally, we move away from the keras imagedatagenerator routine entirely

makedatasets should eventually

automatically resize all imagery (all bands) to a common size if not already so (use target size)
generate a non-augmented set
generate an augmented set
generate additional augmented sets according to AUG_LOOPS (allows AUG_LOOPS to equal 1)
create identical npz files for 1, 3 and >3 band images

I notice that all augmentation and image rescaling options used so far can introduce quite horrible interpolation artifacts for the discrete label images, even rescale from skimage.io with zero-order interpolation, anti-aliasing, and clipping to original range because it first recodes to float .... grrr.
Labels dont ever need interpolation, only resizing through nearest neighbour (up-pad, then infilling, or a spatial replacement operation for downsizing)
Labels will now therefore adopt this approach which does not create floats or use interpolation
def scale(im, nR, nC):
  '''
  for reszing 2d integer arrays
  '''
  nR0 = len(im)     # source number of rows
  nC0 = len(im[0])  # source number of columns
  tmp = [[ im[int(nR0 * r / nR)][int(nC0 * c / nC)]
             for c in range(nC)] for r in range(nR)]
  return np.array(tmp).reshape((nR,nC))

lab2 = scale_label(lab,TARGET_SIZE[0],TARGET_SIZE[1])

modified from here

also, padded labels will be stored as lossless pngs, instead of jpegs
imsave(..., check_contrast=False, compression=0)

before resize

after resize with no interpolation

"makedatasets ND":

[ ]  automatically resize all imagery (all bands) to a common size if not already so (use target size)
[ ]  generate a non-augmented set
[ ]  generate an augmented set
[ ]  generate additional augmented sets according to AUG_LOOPS (allows AUG_LOOPS to equal 1)
[ ]  create identical npz files for 1, 3 and >3 band images

new function make_nd_dataset,py  is for N-D imagery that is stored across multiple files, each of which are a separate band or combination of bands from the same sensor, or otherwise coincident and concurrent bands stored in different files (e.g. orthomosaics and digital elevation models). The program has been tested with a set of 3-band rgb images, a coincident set of 1-band NIR images, and a set of 1-band SWIR images, fused to form a 5-band raster stack

user prompted for config file
user prompted for directory to store output files (npzs for model training)
user prompted for directory of label images
user prompted for directory of images
user is prompted for directory of additional images until the 'no' button is pressed in response to the on-screen dialog box "More directories of images?"
if the entire set of label images are the same size, do_resize will be set of False, and images will not be padded or resized, otherwise do_resize will be True, and all images smaller than TARGET_SIZE will be padded and all images larger than TARGET_SIZE will be resized. Note that this version produces much better labels, due to the use of remapping rather than interpolation of 2d label arrays larger than TARGET_SIZE
if do_resize is True, lists of padded images and labels are compiled, otherwise lists of the original unpadded/unresized imagery are compiled (not yet tested the condition do_resize is False)
non-augmented set of npz files are created from the input lists. if do_resize is True, these will be padded/resized, otherwise the original size
non-augmented npzs are read back in as a tf.dataset, to simulate model training, and examples are printed to file (as before)
augmented sets are created.  if do_resize is True, these will be padded/resized, otherwise the original size
augmented npzs are read back in as a tf.dataset, to simulate model training, and examples are printed to file (as before)

new function make_nd_dataset,py is supposed to be generic and should eventually replace make_dataset.py, now for the N_DATA_BANDS <= 3 situation only

some random augmented examples

SOme ranodm non-augmented samples:

The next stage of this task is to create a utility that a user can merge (and optionally pad/resize) ND sample imagery for use in deployment/prediction mode
New function utils\merge_nd_inputs4pred.py . It is essentially the same as make_nd_datasets except:

it only operates on sample imagery (not corresponding labels)
it does not carry out augmentation (therefore no config file is required)

Prompts the user for

imagery (keep adding bands from file using tkinter dialogs)
a place to store outputs (merged data as npz file)

root = Tk()
root.filename =  filedialog.askdirectory(initialdir = os.getcwd(),title = "Select directory for storing OUTPUT files")
output_data_path = root.filename
print(output_data_path)
root.withdraw()

root = Tk()
root.filename =  filedialog.askdirectory(initialdir = os.getcwd(),title = "Select FIRST directory of IMAGE files")
data_path = root.filename
print(data_path)
root.withdraw()

W=[]
W.append(data_path)

result = 'yes'
while result == 'yes':
    result = messagebox.askquestion("More directories of images?", "More directories of images?", icon='warning')
    if result == 'yes':
        root = Tk()
        root.filename =  filedialog.askdirectory(initialdir = os.getcwd(),title = "Select directory of image files")
        data_path = root.filename
        print(data_path)
        root.withdraw()
        W.append(data_path)

target size (if the program detects variable image size) for padding/resizing

## neeed resizing?
szs = [imread(f).shape for f in files[:,0]]
szs = np.vstack(szs)[:,0]
if len(np.unique(szs))>1:
    do_resize=True
else:
    do_resize=False

from tkinter import simpledialog
application_window = Tk()
TARGET_X = simpledialog.askinteger("Imagery are different sizes and will be resized.",
                                "What is the TARGET_SIZE (X) of the intended model?",
                                 parent=application_window,
                                 minvalue=32, maxvalue=8192)

TARGET_Y = simpledialog.askinteger("Imagery are different sizes and will be resized.",
                                "What is the TARGET_SIZE (Y) of the intended model?",
                                 parent=application_window,
                                 minvalue=32, maxvalue=8192)

TARGET_SIZE = [TARGET_X,TARGET_Y]

the same padding/resiizng commands are used as make_nd_dataset. Padded imagery is created and put into folders
why is this important? Imagery of the same spatial extent may have different grid sizes. Take these two Landsat scenes, downloaded using CoastSat
This one is 906x792 pixels

and this is the same spatial extent, but 830 x 790 px

the same two images padded/resized

If I apply the same procedure to all bands, then I can stack all bands into coincident N-D rasters. Non-augmented imagery is simply stored in npz files for prediction

[ ] merge functionality of seg_images_in_folder.py and ensemble_seg_images_in_folder
[ ] test new seg_images_in_folder.py with 5D hatteras / solo and ensemble models
[ ] merge functionality of make_dataset and make_nd_dataset
[ ] end-to end test (make datasets, train_model,  and seg_images_in_folder) of 1-band imagery + binary classes (use sidescan data from doodler paper)
[ ] end-to end test of 1-band imagery + multiple classes (use sidescan data from doodler paper)
[ ] end-to end test of padded/resized 3-band imagery + multiple classes (use C/T L8 data)
[ ] end-to end test of padded/resized 5-band imagery + multiple classes (use C/T L8 data)
[ ] end-to end test of padded/resized 3-band imagery + binary classes (use C/T L8 data and REMAP classes)
[ ] end-to end test of no-padded 3-band imagery + multiple classes (use NOAA data)
[ ] end-to end test of no-padded 3-band imagery + binary classes (use NOAA data and REMAP classes)


Catalog Feature: Link to cards for easier sharing

As the catalog gets populated with more datasets, I think we need a way to link to a specific dataset.
For example: If I want to load the AWS NOAA Optimum Interpolated SST right now, I have to navigate to the url, and either scroll or filter for the dataset. This is either slow, or might get error prone (when more datasets with similar names are added for instance).
I would like to be able to link to a specific dataset, so that I can use that link in docs, share with people on github etc.
cc @katamartin @andersy005

👋🏽 @jbusecke,
kata and i have discussed this issue and identified two potential solutions, each with varying levels of effort required:
option 1: update the URL state based on user searches. currently, when you visit catalog.leap.columbia.edu and search for "AWS NOAA Optimum Interpolated SST," the feedstocks are filtered, but the search state is not encoded in the URL. It would be great to update the URL to something like https://catalog.leap.columbia.edu/?search=AWS%20NOAA%20Optimum%20Interpolated%20SST. this way, when someone shares the URL with others, they will see the same search results.
option 2: create dedicated pages for each feedstock. with this approach, if someone wanted to share or navigate to "AWS NOAA Optimum Interpolated SST," the link would be something like https://catalog.leap.columbia.edu/AWS%20NOAA%20Optimum%20Interpolated%20SST. however, this option requires some design work before implementation.
option 1 is a low-hanging fruit that we can implement in the near future, while option 2 is a more comprehensive solution that we can work on when we have more time and resources.
What do you think about these options?

I think that option 2 is ultimately the best solution, but 1 seems like a good intermediate solution.
would it be possible to have a "share" button that copies the url+search to the clipboard?

Closing this as it has been implemented in

https://github.com/carbonplan/leap-data-catalog/pull/82


Sidebar accessible in Kiosk-Mode - wanted behavior?

Home Assistant release (hass --version):
0.49.0
Python release (python3 --version):
3.6
Component/platform:
Kiosk
Description of problem:
When 'activating' kiosk mode, tabs and menu-icon are hidden. It's still possible to access the sidebar by sliding from the left edge to the center. I think the fact that the menu-icon is removed means that the sidebar shouldn't be accessible at all. Is this the expected behavior or a bug?

Fixed in https://github.com/home-assistant/home-assistant-polymer/pull/338


Update container_name for docker-compose YAML files

Description
It's a suggestion to have the default container_name  (django, postgres, docs)
set to
container_<image_name>
Rationale
The names "django", "postgres" and "docs" are not unique if one plans to create two projects and work on them simultaneously until they change one explicitly.

Agree, or <project_slug>_django, <project_slug>_postgres, <project_slug>_docs and etc..

Also related: #2849

Yes, would be my first time ever. What should I do? Just fork, fix, run tox(and pass) and make a PR?

First contribution, nice 😄
You can do everything from your browser. Don't worry too much about tests, they are being run in our CI (more on that later). Here is what I recommend to do:

Fork the repo under your own account
Create a branch using the branch drop down:

Press "." which should redirect you to a VSCode in your browser, where you can make the changes you need
Commit using the source control panel:

Open your fork on github.com again, you should see a notification to create a pull request. If you go to the "Actions" tab on your fork, you can see the results of the tests.

If you want more details, GitHub has a guide on how to create pull requests, which you might find helpful.

@browniebroke what do you think of this approach? https://github.com/djangopackages/djangopackages/pull/755/files

@luzfcb sounds quite similar to the solution we're discussing, no? Is the difference that you're prefixing volume names as well?

@luzfcb I've added what you suggested to #3528.
Without it (using the same volume name), I was having the known authentication error in Postgres. It caused some confution in the past, and this seems like a nicer solution. See old issues:

#1678
#1785
#1672


Write new embed generation system

A while ago, osekai-embed-renderer was written and put into testing on Osekai medals. It was soon discovered that when rendering, it would leave multiple processes behind, and this would quickly eat up ram and crash the server.
A rewrite of this module would be best to be looking towards, with more support for multiple templates for each app. Might be interesting to use a similar method to what bathbot does to render it's user cards.

this one scares me

moved to octon


Experiment: Do not skip disjunction choices unless explicitly disabled.

@swift-ci Please test source compatibility

@rudkx I have tried that recently, it breaks a bunch of perf tests

@xedin I’m sure it does. I want to get some logs for several experiments and see what gets slow.

@xedin ...more importantly see what the impact is on the source company suite.

@rudkx Sure, some of the project became too complex too unfortunately :(

Interesting. We cannot even build the stdlib. I am pretty sure it built locally, so that's really odd.

Failing Tests (14):
    Swift(macosx-x86_64) :: Sema/complex_expressions.swift
    Swift(macosx-x86_64) :: stdlib/FixedPointDiagnostics.swift.gyb
    Swift(macosx-x86_64) :: compiler_crashers/28739-unreachable-executed-at-swift-lib-ast-type-cpp-229.swift
    Swift(macosx-x86_64) :: Sema/type_checker_perf/fast/rdar23327871.swift.gyb
    Swift(macosx-x86_64) :: Sema/type_checker_perf/fast/rdar22836718.swift.gyb
    Swift(macosx-x86_64) :: Sema/type_checker_perf/fast/rdar19738292.swift.gyb
    Swift(macosx-x86_64) :: stdlib/SIMDParameterPassing.swift.gyb
    Swift(macosx-x86_64) :: stdlib/ParameterPassing.swift.gyb
    Swift(macosx-x86_64) :: stdlib/IntegerCompatibility.swift
    Swift(macosx-x86_64) :: expr/expressions.swift
    Swift(macosx-x86_64) :: SILGen/coverage_label.swift
    Swift(macosx-x86_64) :: SILGen/conditionally_unreachable.swift
    Swift(macosx-x86_64) :: Interpreter/binary_operator_perf.swift
    Swift(macosx-x86_64) :: ClangImporter/custom-include.swift

We're able to build the standard library in the Linux and macOS smoke test runs, but not on the build used for the source compatibility tests. Very strange.


upd vs vxlan, whose performance is better

When I ping another flannel on one iaas from another flannel on differnet iaas, the latency is >4ms (both vxlan and udp, very little diffence), have anyone done test on that ? udp and vxlan, which has lower latency, esp. on virtual machines across different iaas?

vxlan will have lower latency overhead but the difference obviously becomes less noticeable when the overall latency increases, as is the case if you're going across cloud providers.


v10.5.1 not published to Maven Central

About this issue
Renovate opened an automatic PR to bump the dependency, but the artifacts weren't found from Maven Central: https://github.com/tachiyomiorg/tachiyomi/pull/8207
I can verify that 10.5.1 does not appear in https://repo1.maven.org/maven2/com/mikepenz/aboutlibraries-compose/
Details

Used library version: 10.5.1

Checklist

[x] Searched for similar issues
[ ] Checked out the sample application
[ ] Read the README
[x] Checked out the CHANGELOG
[ ] Read the MIGRATION GUIDE

Sonatype had some issues yesterday and I couldn't yet publish the artifacts. Hope today works

Looks things are back to normal. Just did the release via sonatype. Should become available on maven central in the next hour


WIP: Feature/nuget package prep

Please review this PR and test if you are able to make a package using proposed chances.
It looks like nuget pack no longer works with .net standard, so I've updated the script. Any comments/feedback are welcome.
I also noticed that add-externals.ps1 script stopped working. At least it does not download Oracle JDK, i've traced this issue down to Oracle changes - they now require you to log in with Oracle to actually download the binary and the trick with cookies no longer work.

I changed add-externals to use OpenJDK instead. It does not have those problems

Actually, you may want to try Amazon JDK https://aws.amazon.com/corretto/ It's compatible with Java 8 (and newer) but has long term support and is a drop in replacement. We had great success using it as a drop it replacement


Add information about COMBINE 2023

COMBINE 2023 will be held as a satellite of ICSB in Connecticut. Need to add preliminary information to the website to give a placeholder to link to when promoting the event.

This has been done. Initially as a future event and now as the current event


Small improvements for ECPIX5

Could you split this PR into two, please?

Could you split this PR into two, please?

Sure. See #194.

Thank you!


Tensorflow 2.0 overwrites logging config

System information

Linux Ubuntu 16.04
Python 3.6.7
packages: logging <IP_ADDRESS>, tensorflow 2.0.0-alpha0

When importing tensorflow any logging user-defined config is ignored and tf config is used instead. Here is an example where logging format and level is changed. Note that the info isn't printed at all.
Code:
import logging

import tensorflow

logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s")
logger = logging.getLogger(__name__)
logger.info("Some info")
logger.error("Some error")

Output:
WARNING: Logging before flag parsing goes to stderr.
E0425 11:22:27.150884<PHONE_NUMBER>82208 temp.py:9] Some error

Expected output (as if you delete import tensorflow or with older version of tf):
INFO Some info
ERROR Some error

@jankislinger Thanks for finding the issue. I could reproduce the issue with TF2.0.0-alpha0 and tf-nightly. However, with TF1.13.1, the above code outputs expected output. Thanks!

I was able to reproduce this bug in tensorflow 1.14.0, which means it is now present in released code.

Posten this in the issue you mentioned @jre21, but posting it here as well, as it is relevant:
Just importing tensorflow intrusively adds a logging handler to the root logger:
import logging

logger = logging.getLogger(__name__)

if __name__ == '__main__':
    logger.warning("Hi!")

(stderr)>>>
Hi!

vs
import logging

import tensorflow as tf

logger = logging.getLogger(__name__)

if __name__ == '__main__':
    logger.warning("Hi!")

(stderr)>>>
WARNING: Logging before flag parsing goes to stderr.
W0628 20:51:13.387141<PHONE_NUMBER>46048 test.py:9] Hi!

This is due to absl adding its own handler to the root logger when importing tensorflow.

As for tf 1.14, the problem seems to stem for how absl is used in tf 2.0:
https://github.com/tensorflow/tensorflow/blob/8e423e3d56390671f0d954c90f4fd163ab02a9c1/tensorflow/python/platform/app.py#L23
This results in an undesirable ABSLHandler being installed on the root logger.

@revan I think this is a duplicate of your assigned issue #26691.


Fix flaky replay coordinator spec

Codecov Report

Merging #86 (728c033) into main (046e738) will increase coverage by 0.03%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##             main      #86      +/-   ##
==========================================
+ Coverage   76.37%   76.41%   +0.03%
==========================================
  Files         157      157
  Lines        2993     2993
  Branches       77       77
==========================================
+ Hits         2286     2287       +1
+ Misses        707      706       -1

Impacted Files
Coverage Δ

...a/surge/internal/persistence/PersistentActor.scala
95.65% <0.00%> (-0.63%)
:arrow_down:

...a/surge/kafka/KafkaPartitionShardRouterActor.scala
62.77% <0.00%> (+0.72%)
:arrow_up:

...health/windows/actor/HealthSignalWindowActor.scala
93.10% <0.00%> (+1.14%)
:arrow_up:

Continue to review full report at Codecov.

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i18n.go - undefined: Asset

Is this a request for help?: yes

Is this an ISSUE or FEATURE REQUEST? (choose one): ISSUE

What version of acs-engine?: master

running "go get github.com/Azure/acs-engine" yields the following error:
src/github.com/Azure/acs-engine/pkg/i18n/i18n.go:65: undefined: Asset
Orchestrator and version (e.g. Kubernetes, DC/OS, Swarm)
What happened:
Undefined: Asset
What you expected to happen:
No error
How to reproduce it (as minimally and precisely as possible):
go get github.com/Azure/acs-engine
Anything else we need to know:

This is with go version 1.8.3

Also, after running "go get all", getting:
package github.com/go-playground/pure/examples/middleware/logging-recovery: cannot find package "github.com/go-playground/pure/examples/middleware/logging-recovery" in any of:
With various GOROOT and GOPATH directories listed.

This is the same problem mentioned https://github.com/Azure/acs-engine/issues/1068#issuecomment-318776434. We have text templates that need to be compiled before running, which go get doesn't do. It's an ugly error on cloning but harmless otherwise. If you don't need to develop on acs-engine, you're better off downloading the binary releases.

Got it. I used the docker method and it works

Is there any ETA for the fix? Thanks.

Getting the same error with go get github.com/Azure/acs-engine on windows.


[webapi] Update manual tests to bdd

Impacted tests(approved):new 0,update 10,delete 0
Unit test platform:[Android]
Unit test result summary:pass 10,fail 0,block 0

please don't change the htm name and remove "-manual", as the cases still manual execute when webdriver blocked. And per our confirm with yugang about testkit-lite rules, these webdriver automated cases execution type still keep as "manual" in tests.xml


What is the command to script a change to the Data Category?

See below for a picture. I am looking to change a columns Data Category to Longitude / Latitude but can't seem to make it work.
I assume its uses the c.DataCategory function but don't actually know how to use it. Can anyone help me out?

If you're trying to do this in Advanced Scripting, see the code below. If you're changing the Data Category manually, there's a dropdown in the properties window (same window as your screenshot).
var c = Model.Tables["TableName"].Columns["ColumnName"];
c.DataCategory = "Latitude";

Thanks!! @m-kovalsky


Add Resource Request: PreReg

What is the resource called?:
PreReg
What is the link to the resource?:
https://prereg-psych.org/index.php/rrp
Please provide a short description of the resource (1-3 sentences):
A domain-specific repository for preregistrations.
Which step of the research cycle does the resource belong to?:
Study implementation

Added to nodes dataset


Proposal: Option to bind listener on backend that is handled without spawning a new thread

Describe the Feature
From my reading of the code, it looks like every websocket message received on the backend is handled on a separate thread. I think it would be valuable to call (some) message handlers directly to run on the receiver thread.
Use Case
Being able to handle messages on the receiver thread unlocks some new possibilities:

Messages can be handled in the order they are sent guaranteed (with corresponding sequential sending on the frontend)
Better integration with other concurrency systems (BYO runtime). Spawning many threads does not necessarily play well with other runtimes

This also comes with some drawbacks:

Added complexity both in implementation and in the API (users have to understand when to use which kind of binding)
Users can create problems if handlers bound in this way block for too long

For example, to handle messages in a guaranteed order on the backend, a user could bind the handler using this new kind of binding and then have the handler copy the message data and add it to a blocking queue for another (single) thread to process. That way, the messages stay in order, there is minimal overhead in handling the message (no thread per message), and the handler returns quickly so the receiver thread isn't blocked.
Proposed Solution
Create a new function called something like bindBlocking (real name TBD). The websocket listener does not spawn a new thread for each message intended for an event handler that is bound with bindBlocking. All event handlers bound with the existing API are handled the same way (the receiver spawns a new thread and the handler is called on that thread).
Other Information
No response
Implementation

[X] I may be able to implement the feature.
[X] It might incur a breaking change.

Version
2.5.0-beta.1
Environment details (OS name and version, etc.)
Darwin 23.5.0 arm64

I like that! I like it because it reduces complexity (you are only ever dealing with one system or the other). And I like it because my guess would be that most users would really only want one or the other for a single app: all events are ordered (or not), we have a separate runtime system (or we want webui to handle it).
I'm happy to give the implementation a shot. Or if you'd rather do it since it is a fundamental change, I understand.

Oh I see. I misunderstood the distinction. Yes I think that makes sense, too.


fs: rename the mountpoint should go through pseudorename branch

Summary
to avoid this type of error:
mount -t procfs /a/b
mv /a/b /
mv: rename failed: 88
Impact
Testing

LGTM


No module found

I imported openalpr-android into android studio but i don't find any module to run! How to configure it and run the sample in android studio!! I'm using android studio 2.1 preview 4!! If its silly I apologies but help me Please!!

Hi @Arunkarthicknallasami,
you need to open the android studio from this directory: https://github.com/SandroMachado/openalpr-android/tree/master/Sample/OpenALPRSample to run the sample.
Please let me know if this works for you.
If you just want to check the sample, you can find the sample APK at the releases tab.

Thank you its working!! I have one more doubt, Is it possible to recognize data with video stream instead of processing image after taking picture. If its not subjected to be asked over the issue coloumn i can email you my doubts.

Unfortunately not, the library is only prepared to deal with static images.


Crash on launch on macOS

I'm trying to run mtproto_proxy in Docker on macOS Catalina as described in the instructions, and I'm getting an error. Please see the crash report in the attachment.
mtproto_proxy.log

My guess is that you are trying to connect from your hone computer that is
behind the NAT that doesn't preserve tcp port numbers.
Proxy doesn't work in such conditions because tcp port is included in
encryption key.
чт, 19 сент. 2019 г., 21:42 sirburpalot<EMAIL_ADDRESS>
I'm trying to run mtproto_proxy in Docker on macOS Catalina as described
in the instructions, and I'm getting an error. Please see the crash report
in the attachment.
mtproto_proxy.log
https://github.com/seriyps/mtproto_proxy/files/3632900/mtproto_proxy.log
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I am indeed trying to connect from a home computer that's behind a NAT, but other MTProto proxies seem to work fine. Is this not something that can be fixed?

@sirburpalot which proxies do work fine? Python / MTG / official?

@seriyps, Python.

python proxy disables advertizing and uses another protocol in such conditions. This is not implemented in Erlang proxy and there is no plans to implement that.


Add missing function getVersion in TypeScript typings

Global function ms.getVersion() is missing from TypeScript typings

Thanks, I will have a look and add other methods that also are missing.

If you would like to help out with adding missing methods to the type script definitions, it would be very welcome.


Unable to perform make_evaluation_predictions

Description
When trying to invoke make_evaluation_predictions in my backtesting function the output does not stop at
Running evaluation: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 12.65it/s]
but proceeds to invoke training processes that first exhaust the VRAM, and the scheduler so that new CUDA processes can no longer be started, then it proceeds to occupy 99% of the available CPU cycles (the kernel does not kill the processes so I am assuming it is not 100%) and proceeds to start new training cycles.
To Reproduce
Plug in this function in your code and feed it the data it needs:
def backtest_model(test_dataset, model):
    # Make forecast
    forecast_it, ts_it = make_evaluation_predictions(
        dataset=test_dataset,  # test dataset
        predictor=model,  # model
        num_samples=100,  # number of sample paths we want for evaluation
    )

    forecasts = list(forecast_it)
    tss = list(ts_it)

    # Calculate accuracy metrics
    evaluator = Evaluator(quantiles=[0.1, 0.5, 0.9])
    agg_metrics, item_metrics = evaluator(iter(tss), iter(forecasts), num_series=len(test_dataset))

    return agg_metrics, item_metrics

3.10.9

Error message or code output
The cascade of events is too long to paste in its entirety so here is a tiny snippet of what ends up on the console:

`Trainer.fit` stopped: `max_epochs=75` reached.
Epoch 74: : 50it [00:07,  6.77it/s, v_num=83, val_loss=361.0, train_loss=173.0]
/home/******/anaconda3/envs/gluonts/lib/python3.10/site-packages/pytorch_lightning/utilities/parsing.py:197: UserWarning: Attribute 'model' is an instance of `nn.Module` and is already saved during checkpointing. It is recommended to ignore them using `self.save_hyperparameters(ignore=['model'])`.
  rank_zero_warn(
Running evaluation: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 12.65it/s]
/home/******/anaconda3/envs/gluonts/lib/python3.10/site-packages/pytorch_lightning/utilities/parsing.py:197: UserWarning: Attribute 'model' is an instance of `nn.Module` and is already saved during checkpointing. It is recommended to ignore them using `self.save_hyperparameters(ignore=['model'])`.
  rank_zero_warn(
...
/home/******/anaconda3/envs/gluonts/lib/python3.10/site-packages/pytorch_lightning/utilities/parsing.py:197: UserWarning: Attribute 'model' is an instance of `nn.Module` and is already saved during checkpointing. It is recommended to ignore them using `self.save_hyperparameters(ignore=['model'])`.
  rank_zero_warn(
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
/home/******/anaconda3/envs/gluonts/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:67: UserWarning: Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the `pytorch_lightning` package, due to potential conflicts with other packages in the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard` or `tensorboardX` packages are found. Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default
  warning_cache.warn(
/home/******/anaconda3/envs/gluonts/lib/python3.10/site-packages/pytorch_lightning/utilities/parsing.py:197: UserWarning: Attribute 'model' is an instance of `nn.Module` and is already saved during checkpointing. It is recommended to ignore them using `self.save_hyperparameters(ignore=['model'])`.
  rank_zero_warn(
...
/home/******/anaconda3/envs/gluonts/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:67: UserWarning: Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the `pytorch_lightning` package, due to potential conflicts with other packages in the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard` or `tensorboardX` packages are found. Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default
  warning_cache.warn(
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
/home/******/anaconda3/envs/gluonts/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:67: UserWarning: Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the `pytorch_lightning` package, due to potential conflicts with other packages in the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard` or `tensorboardX` packages are found. Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default
  warning_cache.warn(
...
 File "/home/******/anaconda3/envs/gluonts/lib/python3.10/site-packages/torch/cuda/__init__.py", line 247, in _lazy_init
    torch._C._cuda_init()
RuntimeError: No CUDA GPUs are available
...
 return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
RuntimeError: CUDA error: out of memory
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
...
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]

  | Name  | Type                           | Params | In sizes                                                                           | Out sizes
----------------------------------------------------------------------------------------------------------------------------------------------------------
0 | model | TemporalFusionTransformerModel | 222 K  | [[1, 30], [1, 30], [1, 1], [1, 1], [1, 37, 4], [1, 37, 0], [1, 30, 0], [1, 30, 0]] | [1, 9, 7]
----------------------------------------------------------------------------------------------------------------------------------------------------------
222 K     Trainable params
0         Non-trainable params
222 K     Total params
0.890     Total estimated model params size (MB)
...
Sanity Checking: 0it [00:00, ?it/s]/home/******/anaconda3/envs/gluonts/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:430: PossibleUserWarning: The dataloader, val_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 24 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.
  rank_zero_warn(
...
  rank_zero_warn(
Epoch 0: : 5it [00:00,  5.36it/s, v_num=84]/home/******/anaconda3/envs/gluonts/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:430: PossibleUserWarning: The dataloader, val_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 24 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.
  rank_zero_warn(
...

put error or undesired output here

Environment

Operating system: <IP_ADDRESS>-microsoft-standard-WSL2+ #2 SMP Sun Oct 2 09:50:15 CEST 2022 x86_64 x86_64 x86_64 GNU/Linux
Python version: 3.10.9
GluonTS version: 0.12.7
MXNet version: 1.9.1
PyTorch version: 2.0.1
Lightning version: 2.0.2

omg... no. I was "too busy" building a program to encapsulate the invocations inside
main()
...
if __name__ == '__main__':
    main()

It works well now. Thank you!


Feature request: make config.ui.preselect_current more general

Hi, checking #21, would be nice if we could refactor config.ui.preselect_current to something like config.ui.preselect, this option could accept from a predefined list of strings (%, # and false for example) so we can preselect the current (%) buffer, the alternate (#) buffer or none (false).
This would allow us to mimic Telescope's telescope.builtin.buffers() with sort_lastused flag (to preselect last used buffer).
@ lua/snipe/init.lua:237 @ function Snipe.open_buffer_menu()
   end
   Snipe.global_menu:add_new_buffer_callback(Snipe.default_keymaps)

-  if Snipe.config.ui.preselect_current then
+  if Snipe.config.ui.preselect then
     local opened = false
     for i, b in ipairs(Snipe.global_items) do
-      if b.classifiers:sub(2,2) == "%" then
+      if b.classifiers:sub(2,2) == Snipe.config.ui.preselect then
         Snipe.global_menu:open(Snipe.global_items, Snipe.default_select, Snipe.default_fmt, i)
         opened = true
       end

More generally, we could allow this to also be a function with global_items as an argument and return the item to preselect.
What do you think? Thanks.

Hi, checking #21, would be nice if we could refactor config.ui.preselect_current to something like config.ui.preselect, this option could accept from a predefined list of strings (%, # and false for example) so we can preselect the current (%) buffer, the alternate (#) buffer or none (false).
This would allow us to mimic Telescope's telescope.builtin.buffers() with sort_lastused flag (to preselect last used buffer).
@ lua/snipe/init.lua:237 @ function Snipe.open_buffer_menu()
   end
   Snipe.global_menu:add_new_buffer_callback(Snipe.default_keymaps)

-  if Snipe.config.ui.preselect_current then
+  if Snipe.config.ui.preselect then
     local opened = false
     for i, b in ipairs(Snipe.global_items) do
-      if b.classifiers:sub(2,2) == "%" then
+      if b.classifiers:sub(2,2) == Snipe.config.ui.preselect then
         Snipe.global_menu:open(Snipe.global_items, Snipe.default_select, Snipe.default_fmt, i)
         opened = true
       end

More generally, we could allow this to also be a function with global_items as an argument and return the item to preselect.
What do you think? Thanks.

I think the function approach is better and we can have some predefined preselectors. Ill have a look this should be pretty easy to add

Let me know if this fixes your issue, There is a new option: ui.preselect which is a function that just takes the buffer list and returns an index, this can now be used for pre-selection. There is also a builtin helper: require("snipe").preselect_by_classifier which you could for example use as follows to pre-select the alternate buffer:
...
  preselect = require("snipe").preselect_by_classifier("#"),
...


Must have files on disk; no way to pass in file content through terraform

In my use case, I'd like to pull a file from a remote data source (like using the http provider), kustomize it, and then launch the kustomized resources.
But I am unable to do so with the provider in it's current state.
This is because the kustomize data sources only rely on folders written to disk and cannot accept a yaml file whose content is generated in terraform.
i.e. To perform my use case, I'd have to 1) use a data source to fetch the file, 2) create a local_file resource based on the data source, and 3) create a kustomization_overlay or kustomization_build data source based on said resource.
This creates a data>resource>data dependency and gives errors when using a for_each or count when reading from the final data source.
The "for_each" value depends on resource attributes that cannot be determined until apply, so Terraform cannot predict how many instances will be created
If there was a way to directly pass in the content of yaml files into the data sources (instead of relying on pre-written files), this error wouldn't exist.

Hi @BrandonALXEllisSS
As an alternative, you can use the kustomize build looking to remote targets.
Just like using kustomize, you can do that using kustomization_overlay.
An important thing is that your URL should follow hashicorp/go-getter URL format. For example:
data "kustomization_overlay" "horusec_operator" {
  resources = [
    "https://github.com/ZupIT/horusec-operator/config/default?ref=develop"
  ]
}

resource "kustomization_resource" "horusec_operator" {
  for_each = data.kustomization_overlay.horusec_operator.ids
  manifest = data.kustomization_overlay.horusec_operator.manifests[each.value]
}

The list of strings passed to resources should support anything that is supported in the kustomization.yaml. I don't think it makes sense to have the provider support different things than Kustomize does itself.

This makes it difficult to use for something like customizing flux installations that use manifests built by terraform, e.g., with the flux terraform provider.
Fundamentally, kustomize is slurping strings. It's a shame to not be able to use this provider with terraform-native resources.

If the manifests generated by the flux provider do not meet your requirements, I suggest you open an issue with the flux provider to allow configuring the manifests it will generate.
This provider integrates Kustomize into Terraform. It's my opinion, that it should support everything that's supported in a kustomization.yaml. Nothing less, but also nothing more.

Another use-case for this – if I want to pass some id from terraform to kustomize as a parameter
For example I use kustomize+helm and I often need to hardcode subnets, security groups, iam roles ids in values.yaml files for helm


BUG: Bottom sheet is hidden then displayed on lifecycle update

https://github.com/user-attachments/assets/a38c8217-d027-48ed-992a-d7daf8354a5e

I found the cause, I just need to figure out how to fix it :smile:


Rasa core action server taking long and entire system become slow

rasa                          1.0.0rc8  /home/skj/rasachat/rasa_nlu
rasa-core                     0.14.4
rasa-core-sdk                 0.14.0
rasa-demo                     1.1       /home/skj/sara/rasa-demo
rasa-nlu                      0.15.0
rasa-sdk                      1.0.0rc4
Rasa version:
Python version:
3.6
Operating system (windows, osx, ...):
Issue:
my action server.py code deals with large excel file >75mb. Action server works well for small files. But takes longer for large files and after 7-8 min whole system gets slowed down and finally become unresponsive... pls help
Content of configuration file (config.yml):
language: "en"

pipeline: tensorflow_embedding

Content of domain file (domain.yml) (if used & relevant):
action_endpoint:
  url: http://localhost:5055/webhook

#nlg:
# url: http://localhost:5056/nlg

core_endpoint:
  url: http://localhost:5055

I assume that's something to do with the computing power of your machine and how you've written your action code -- i don't think it has anything to do with the implementation of the action server. I think this kind of question is better to ask in the forum


Update Accordion Panel and Calc Titles

This PR resolves the issue noted in Issue #122. Chart has a second item that needed to be labeled "Calc" and Accordion has a second item that needed to be labeled "Accordion Panel".

If we could also add a fix for Tabs as part of this PR that will be great... :)


bug: event.preventDefault() doesn't work in view lifecycle events

Type: bug
Platform: all
Hi Ionic team,
the call to event.preventDefault() doesn't work in a view lifecycle event and a state change will be performed.
$scope.$on('$ionicView.beforeLeave', function (event) {
 event.preventDefault();
});

Will this be changed in future, or do i have to use a ui-router event (e.g. $stateChangeStart) to prevent a state change?
Thanks in advance for your answer.

Greetings @bastiss!
My sensors indicate that you need to update your issue through our custom issue form. We are now requiring all issues to be submitted this way, to ensure that we have all of the information necessary to fix them as quickly as possible.
Click Here To Update Your Issue
I will have no choice but to close this issue if it is not resubmitted through the form. Please fill out the rest of the form, so that I may use my friendly robot powers to assist you.
Thank you!

@adamdbradley, was this the way transitions were intended to be cancelable?

I was curious about this as well. My use case is making sure to call a save method before transitioning in beforeLeave() to the back view which will then query for the updated data. Currently it's a race condition and sometimes displays the previous information. Any updates on this?

Any updates on this?

@bastiss, even the $stateChangeStart doesn't prevent a state change.  Relevant plnkr http://plnkr.co/edit/Ov25xiUuEhVVH7ucKFAc?p=preview

+1

+1

Hello all! We are currently doing alot of work with the lifecycle events for the next release. Be on the lookout for Ionic 1.3.1 soon, which will have these fixes. Thanks! Once 1.3.1 is released i will update this issue.

@jgw96 here's a codepen where a state change is prevented successfully using $stateChangeStart from a child-view, in this case 'Facts' shares the 'home-tab' ui-view with 'Home'
If you click on "Scientific Facts" and toggle the ion-toggle. Then clicking "< Home" in the nav-bar doesnt allow navigation. However, if you go to About and toggle, you can still navigate between tabs.
I presume this is because tabs.home and tabs.facts share a nav stack, while tabs.home and tabs.about do not?
http://codepen.io/skotturi/pen/yOGEJg?editors=1010

Hey @skotturi ! Would you be interested in doing some testing for the 1.3.1 RC? If so, here is a link on how to test it.

Hello all! As it seems it has been a while since there was any activity on this issue i will be closing it for now. Feel free to comment if you are still running into this issue. Thanks for using Ionic!

Hello, I am experiencing this problem while trying to use $stateChangeStart in my Ionic app.
I call event.preventDefault() in the $stateChangeStart event handler, but the transition continues regardless.
There is some similarity between my project and the example posted by @skotturi, but my event handler is attached at the $rootScope instead.

@jgw96 Apologies for the delay, I've tested this on 1.3.1 and I'm still seeing the same issue.
The codepen still accurately reflects the issue. To reproduce this:

Click "Scientific Facts" in the state tabs.home
This will take you 'tabs.facts' which shares the home-tab view.
Toggle "Thou shall not leave"
Click "< Home" in the nav-bar. Nav is prevented.
Click "About" tab, nav is sort of prevented. The view goes white, however, the actual About page is not rendered (unless you previously have loaded the view in which case its rendered from cache).

http://codepen.io/skotturi/pen/yOGEJg?editors=1010

@jgw96 Just wanted to follow up on this.
Not sure if the plunkr above works as demo.
If you drop the following snippet into any v1 app controller, inject $state into the ctrl, and add some $scope.somethingImportantIsHappening = true, the problem should be reproducible at that point.
    $scope.$on('$stateChangeStart', function (event, next, nextParams, fromState) {
                if (somethingImportantIsHappening) {
                    event.preventDefault();
                    // $state.go(fromState.name);           // tried this, doesn't work.
                    window.location.assign('#/' + fromState.name);                // also doesn't work.
                }
            });

Is there a way to achieve this in v1.3.1 with the changes to the life cycle events?

@jgw96, any updates on what the status is of this?  The Codepen provided by @skotturi seems to still demonstrate the problem.
I'd like to use this functionality to implement an "Unsaved changes" popup... What's the "second best" way accomplish this given that event.preventDefault() doesn't seem to work on lifecycle events?

@rinogo It's pretty hacky but the best way I've found to prevent navigation from the tabs is to hide the tabs all together... Mike has a code-pen on this unofficial hack: http://codepen.io/mhartington/pen/MwPRNp?editors=001
This works for me because I want to disable nav from a page with tabs at all times, not in a state dependent way like unsaved changes but maybe you can use ng-attr-x to apply the hide-tab-bar directive attribute.

@skotturi Thanks for sharing your solution!  It unfortunately doesn't really help in our situation as we actually want the user to be able to navigate away.  If there are unsaved changes when a user tries to navigate away from the view, we wanted to show a modal saying something like, "Unsaved changes - are you sure you want to leave?"  If the user taps "No", we should stay on the active view.  However, with Ionic in its current state, we have no way of canceling the navigation.
The solution we went with was to change the workflow a bit.  Instead, we say, "Unsaved changes, would you live to save them?"  In other words, the navigation occurs no matter what, but the user can choose whether or not to save their changes.
This still isn't really ideal (the modal actually shows up after the view has changed), but it is a decent compromise.

@skotturi Hopefully your solution and my workaround can help other devs with this problem until Ionic can issue a proper fix.


Add enum binding parameter support

It is nice to be able to pass enum as a parameter for sql query. This minifix add's this possibility. Enum is transformed to String, because it is recommended way of saving enums to database since Archimedes. Have never seen anyone who uses ordinal for this.

As it turns out, it is standard for JDBC drivers to not expect enums in binding parameters.


[WIP] Remove NSString from Accepts and cookies

WIP - needs rebasing once #1401 merged
Improves performance by avoiding NSString bridging (see #1388)
Replaces the use of String.components with String.split when processing cookie headers, replaces String.range(of:) with String.firstIndex(of:), and replaces a Foundation function String.trimmingCharacters(in: .whitespaces) with a custom function that trims ASCII whitespace chars (0x20 and 0x09).
Also, for Linux only, replaces a Foundation function String.caseInsensitiveCompare used in Accept header processing with a custom function that lowercases a String and then compares for equality with an already lowercased String.
Both changes pass the Kitura tests.
In terms of performance, a microbenchmark shows that performance is better on both Mac and Linux with these changes:
trimmingCharacters(in: .whitespaces) vs trimAsciiWhitespace

String with no whitespace: Linux = 47x (faster),  Mac = 2.1x (faster)
String with single whitespace prefix and suffix: Linux = 17x (faster),  Mac = 1.5x (faster)
String with 20 whitespaces at start and end: Linux = 14.4x (faster),  Mac = 0.5x (2x slower)

The Foundation method on Mac is fairly fast, so with a large number of whitespace characters my method ends up slower, however the improvements on Linux are significant.  In practice, I doubt we would encounter more than 1 consecutive whitespace character at either end of a value.
caseInsensitiveCompare vs equalsLowercased
Unfortunately because the Mac performance with NSString API is quite high, this method is always slower (substantially so for long inputs).  I've guarded this implementation so it is only used on Linux.

Strings that are equal (6 chars):  Linux = 3.1x (faster),  Mac = 0.88x (slower)
Strings that are equal (460 chars):  Linux = 2.4x (faster),  Mac = 0.04x (20 times slower)
Strings that differ in the first position (6 chars):  Linux = 8.2x (faster),  Mac = 0.8x (slower)
Strings that differ in the first position (460 chars): Linux = 0.34x  (3 times slower),  Mac = 0.01x (100 times slower)

For Linux, we get a nice speed-up in most cases.  With strings that are different, the worst-case is where the user-input differs in the first character and is very long, because my method goes to the effort of lowercasing the entire string before comparing for equality.  The break-even point for the two methods in this case is ~150 chars.
Since we're in the context of where we use this function (comparing HTTP header names), I doubt this would be an issue as headers are typically short strings. and we should consistently gain from this change.

aeb4371 was necessary due to Foundation on Linux not accepting Substrings as values for HTTPCookie's properties.  I've raised a bug: https://bugs.swift.org/browse/SR-9887

@ianpartridge review comments addressed in 857cdb9


BSD license in setup.py while LICENSE.txt is MIT

might need to fix this to avoid confusion.

Nice catch, I'll change all to MIT.

Fixed in @b105feb


Document package repositories in https://k8s.io/releases/download/

fixes #43460

Deploy Preview -> https://deploy-preview-44485--kubernetes-io-main-staging.netlify.app/releases/download/#official-package-repositories

Have a look at the banner at the top of https://k8s.io/

Changes to the location of Linux packages for Kubernetes
The legacy Linux package repositories (apt.kubernetes.io and yum.kubernetes.io AKA packages.cloud.google.com)
have been frozen starting from September 13, 2023 and are going away in January 2024, users must migrate.
Please read our announcement for more details.

Those are the kind of repositories we need to explain. Not the source code repositories on GitHub.

Those are the kind of repositories we need to explain. Not the source code repositories on GitHub.
that means that i need to explain about the official package repositories pkgs.k8s.io which will be replacement  for the Google-hosted package repositories ?

this means that i need to explain about the official package repositories pkgs.k8s.io which will be replacement for the Google-hosted package repositories ?

@sftim am i right here?

// @dipesh-rawat can i get a review here?

@dipesh-rawat @shannonxtreme can i get a review on this?


Requesting write access for CIPD

Per Flutter's CIPD tutorial I'd like write access to https://chrome-infra-packages.appspot.com/p/flutter/tools/ so that I can upload v1.8.0 of cosign and sget. Let me know if there's more information I need to provide!

CC: @godofredoc

done!


IBApiNext: Add support market depth

New functions:

IBApiNext.getMarketDepth()

New tools:

market-depth.js

New tests (RxJS wrappers only):

get-market-depth-l2.test.ts

If you can test onUpdateMktDepthL2 callback somehow, please do so before approving.
Only have L2 CME futures, they call onUpdateMktDepth, but not onUpdateMktDepthL2.
Think you will need ISE / NASDAQ ECN L2 subscription or something similar to get onUpdateMktDepthL2.

I'll test it after market opens.

Annoying extra step with it, is to find the contractId for the instrument we are looking market data for. Needs more testing from my side.

Yep, think so. Was not able to in-depth test it, now it needs some conflict resolving.
But as I have a user with live data available, we should be soon able to test it aswell.


Add section type (Lec/Dis/Lab) to Title in Calendar Popup

Sometimes the type gets obscured on mobile for a short class, so I think that would be nice. I spent a good 30 second trying to figure out the type of a section on my schedule when I was on my phone.

Change: Add the type to the title name (e.g., COMPSCI 161 Dis)

@EricPedley do you think this is a good idea?

@EricPedley do you think this is a good idea?


Add secret cache doc

Thank you for helping make the Dapr documentation better!
Please follow this checklist before submitting:

[x] Read the contribution guide
[x] Commands include options for Linux, MacOS, and Windows within codetabs
[x] New file and folder names are globally unique
[x] Page references use shortcodes instead of markdown or URL links
[x] Images use HTML style and have alternative text
[x] Places where multiple code/command options are given have codetabs

In addition, please fill out the following to help reviewers understand this pull request:
Description
Add cache feature for secret stores.

Related to dapr/dapr#3941

Issue reference
Please reference the issue this PR will close: #2004

Closing this PR. Can be re-opened if the code is accepted


iOS Build Error

Every time I try to run my app on an iOS emulator, I get this error:
Error output from Xcode build:
↳
** BUILD FAILED **
Xcode's output:
↳
warning: Stale file '/Users/batuhankarababa/iban-flutter-1/build/ios/Debug-iphonesimulator/flutter_tesseract_ocr/flutter_tesseract_ocr.framework/Modules/flutter_tesseract_ocr.swiftmodule/arm64-apple-ios-simulator.swiftinterface' is located outside of the allowed root paths.
warning: Stale file '/Users/batuhankarababa/iban-flutter-1/build/ios/Debug-iphonesimulator/flutter_tesseract_ocr/flutter_tesseract_ocr.framework/Modules/flutter_tesseract_ocr.swiftmodule/arm64.swiftinterface' is located outside of the allowed root paths.
warning: Stale file '/Users/batuhankarababa/iban-flutter-1/build/ios/Debug-iphonesimulator/flutter_tesseract_ocr/flutter_tesseract_ocr.framework/Modules/flutter_tesseract_ocr.swiftmodule/x86_64-apple-ios-simulator.swiftinterface' is located outside of the allowed root paths.
warning: Stale file '/Users/batuhankarababa/iban-flutter-1/build/ios/Debug-iphonesimulator/flutter_tesseract_ocr/flutter_tesseract_ocr.framework/Modules/flutter_tesseract_ocr.swiftmodule/x86_64.swiftinterface' is located outside of the allowed root paths.
Command CompileSwift failed with a nonzero exit code
/Users/batuhankarababa/Developer/flutter/.pub-cache/hosted/pub.dartlang.org/flutter_tesseract_ocr-0.4.14/ios/Classes/SwiftFlutterTesseractOcrPlugin.swift:3:8: error: could not find module 'SwiftyTesseract' for target 'arm64-apple-ios-simulator'; found: x86_64-apple-ios-simulator, x86_64
import SwiftyTesseract
^
note: Using new build system
note: Building targets in parallel
note: Planning build
note: Constructing build description

I don't have a Mac machine so I can't test it.
I'm sorry.

hey! Yes that method has solved it. It didn't solve at first since I try to move folders on vscode. We should move folders on Xcode


Wrong GH capitalization

You can check out the source code on my github.

Should be GitHub, not github

This should be a PR, not an issue


[SPARK-33050][BUILD] Upgrade Apache ORC to 1.5.12

What changes were proposed in this pull request?
This PR aims to upgrade Apache ORC to 1.5.12.
Why are the changes needed?
This brings us the latest bug patches like the followings.

ORC-644 nested struct evolution does not respect to orc.force.positional.evolution
ORC-667 Positional mapping for nested struct types should not applied by default

Does this PR introduce any user-facing change?
No.
How was this patch tested?
Pass the CI.

Test build #129330 has started for PR 29930 at commit fc5c331.

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Test build #129330 has finished for PR 29930 at commit fc5c331.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test FAILed.

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retest this please

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Thank you, @HyukjinKwon and @viirya . GitHub Action passed.
Merged to master

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Open and Close

Hi,
Is there a way to get the daily change value? either in percentage or numerical.
Thanks in advance!

Hello amirshahmiri,
I believe you can't do that. Here is an example of what data you can get using python-tradingview-ta: TradingView.
Please reply if you have another question, I'm happy to help.

You can get open and close price directly from an exchange or external API.

I currently am working on a personal project with this project being a central point and also would find it convenient to get the daily percentage change and found this to be a way of achieving it. To be put shortly, you just do it manually. Here is what I am working with.
`
def percent_change_24h():
handler = TA_Handler(
    symbol=BTC,
    screener="crypto",
    exchange="COINBASE",
    interval=Interval.INTERVAL_1_DAY
)

analysis = handler.get_analysis()

price = analysis.indicators['open']

daily_change = ((price - btc_price()) / btc_price()) * 100

print(price)
print(btc_price())
print(daily_change)

#Example usage
if daily_change <= -20.0000:
print("Decent Dip to DCA")
def btc_price():
btc_price = TA_Handler(
    symbol=BTC,
    screener="crypto",
    exchange="COINBASE",
    interval=Interval.INTERVAL_1_MINUTE
)

analysis = btc_price.get_analysis()

price = analysis.indicators['close']

return price

`

Hey everyone, this issue has been open for nearly a year. Recently, sina-rostami added the "change" indicator in #59. I will release these changes soon.

Released in v3.2.8. Please update tradingview-ta using pip install -U tradingview-ta.
To get the daily change value in percentage, set the interval to 1 day. Code example:
from tradingview_ta import TA_Handler, Interval

btcusdt = TA_Handler(
  symbol="BTCUSDT",
  exchange="binance",
  screener="crypto",
  interval=Interval.INTERVAL_1_DAY
)

analysis = btcusdt.get_analysis()
change = analysis.indicators["change"]
print(f"Over the last 24h, the price of BTC/USDT changes by {change}%")
# Output: Over the last 24h, the price of BTC/USDT changes by -0.15517712%

I'll close this issue. If you have any questions, please comment below.


[3pt]  - Add tests for items counter - Student A

Make sure that function for the items counter is covered with unit tests using Jest.

Pull request for this task


Remove version: Peppy.Osu! version 2024.130.2

https://github.com/microsoft/winget-pkgs/issues/152768#issuecomment-2102735187

Resolves #152768

Microsoft Reviewers: Open in CodeFlow

URL: https://github.com/ppy/osu/releases/download/2024.130.2/install.exe
OK
(Automated message - build 882)


The uploader demo

The demo includes:

Upload-it notebook extension
Matching upload server implemented in Golang

There is no authentication yet.

This PR is a little bit long and I can review it easily if you can separate golang server part.

I have addressed the comments and split the PR into two independent ones (nbextension and golang server).


TypeError("'>' not supported between instances of 'NoneType' and 'int'")

As requested by Michael on TG
Apologies in advance if I haven't posted this correctly.
Been running bot version 7.0.36 with no issues on Win10. Python version 3.9.7
I'm a total noob and run the bot from the folder on my desktop, using a .bat file to start the bot, everything working perfectly.
Downloaded version 8.0.5 copied the config.json and kucoin.key files across and get the following error on startup
Bot1  2023-04-16 22:46:52  BTC-GBP  900  TypeError("'>' not supported between instances of 'NoneType' and 'int'")
Config file below.
{
"kucoin": {
"api_url": "https://api.kucoin.com",
"api_key_file": "kucoin.key",
"config": {
"autorestart": 1,
"base_currency": "ADA",
"disablebuynearhigh": 1,
"enableinsufficientfundslogging": 1,
"enabletelegrambotcontrol": 1,
"granularity": "5m",
"live": 1,
"buylastsellsize": 1,
"buymaxsize": 19,
"nobuynearhighpcnt": 1,
"predictions": 1,
"quote_currency": "USDT",
"sellatresistance": 1,
"selllowerpcnt": -12,
"telegram": 1,
"telegrambotcontrol": 1,
"nosellmaxpcnt": 3,
"nosellminpcnt": -9,
"disablebuymacd": 0,
"disablebuyema": 0,
"disablebuyobv": 1,
"bbands_s1": 0,
"trailingbuypcnt": 0.5,
"trailingsellpcnt": -0.5,
"trailingstoploss": -1,
"trailingstoplosstrigger": 2,
"stats": 0,
"verbose": 0,
"graphs": 1,
"log": 1,
"websocket": 0
}
},
"telegram": {
"token": "REMOVED",
"user_id": "REMOVED",
"client_id": "REMOVED",
"datafolder": ""
},
"scanner": {
"atr72_pcnt": 1.0,
"exitaftersell": 0,
"enableleverage": 0,
"use_default_scanner": 1,
"maxbotcount": 5,
"autoscandelay": 0,
"enable_buy_next": 1
}
}

I see what the problem is. It's not auto detecting the KuCoin exchange. If you add "--exchange kucoin" it works. I'll track down the issue and fix it this evening.

Fixed in 8.0.6


Dynamic Form

new control: Dynamic form
Approved here https://github.com/pnp/sp-dev-fx-controls-react/issues/878

Q
A

Bug fix?
[ ]

New feature?
[x]

New sample?
[ ]

Related issues?
fixes #X, partially #Y, mentioned in #Z

What's in this Pull Request?
Dynamic form control

Hi @ravichandran-blog,
Thank you very much for the new control!
Could you please reference dev as target branch instead of master? Just close this PR and create a new one with dev as a target.
Thanks!

Moved to https://github.com/pnp/sp-dev-fx-controls-react/pull/903


The count of topics on the bundle is less than 2，skip split

Motivation
The count of topics on the bundle is less than 2，skip split
https://github.com/apache/pulsar/blob/52dffda16facef0047081a4b6f0f4e06fecb6349/pulsar-broker/src/main/java/org/apache/pulsar/broker/loadbalance/impl/BundleSplitterTask.java#L75-L78
Documentation

[x] no-need-doc

It's an internal change, no need doc

/pulsarbot run-failure-checks

/pulsarbot run-failure-checks

This is an improvement to #11937 changes. Just adding the link for cross-reference.


Showing symbols in docs is broken

In Xcode 11.5, the symbols can't be displayed in the docs anymore (as described in #37 and implemented in #38):

This should be investigated and fixed. If fixing is not possible, the docs should be removed again.

This is working again in Xcode 11.6


about FLUX version for training subject-driven model

Hi, thanks for your open source.
I have some question about the flux version.
I find that the flux_path in train/config/subject_512.yaml is "black-forest-labs/FLUX.1-dev".
But as said in Limitations, the subject-driven generation model may not work well with FLUX.1-dev.
Which version should we use for training subject-driven model.
The results of training with FLUX.1-dev after 15,000 iterations indeed seem inferior to the results of  "experimental/subject" model.

Hi @Weizhi-Zhong ,
Thanks for raising this question.
The model performance should be better than the model experimental/subject since the training settings in the released code are more optimized. If you're seeing inferior results, here are some suggestions:

Try increasing gradient accumulation steps in your yaml config for more stable training.
Experiment with different checkpoints (e.g. 14k, 13k, or even 5k iterations) as training stability can vary.

The training process isn't completely stable in our observations, so trying these adjustments may help improve your results.
Additionally, we're optimizing our training code and will continue to release improved training settings through updates.


Implement PCIC Client as a PIMPL

The current pcicclient module exposes unnecessary information in its public headers which causes steeper than necessary dependencies on users of the library and also makes expressing usage of the pcicclient in an external project unnecessarily verbose. Specifically, all of the Boost related dependencies, which are declared private in the PCIC client interface class should move to a pimpl. The camera and framegrabber modules would be good models to follow.

The syntron team is currently working on this. There will be a PR against dev-0.9.0 soon.

This has been merged via #60


Support displacement mapping via shaders

I'm no expert on this, but we should be able to shift a vertex in the vertex shader by the displacement map's level in the normal direction

Depending on your usecase, you might be interested in parallax mapping[1] (POM).
Usecase:

:red_square:  Terrain height map: do not use POM for height map, in this case, it is indeed better to use a vertex shader, or even use a dedicated terrain plugin[2] for very large maps.
:green_square: Fancy textures: POM is good for stuff like cobblestone, rocks, brickwork. It's like normal mapping, but with actual depth.

links:

[1] https://github.com/nicopap/bevy_mod_paramap/
[2] https://github.com/kurtkuehnert/bevy_terrain

Thanks for the suggestion, your crate looks perferct for my use-case! Is there a way to automatically use a displacement map that is included in a GLTF, like how StandardMaterial imports normal and roughness maps from the GLTF?

Annoyingly, the base GLTF spec doesn't include an height map (or bump map) https://registry.khronos.org/glTF/specs/2.0/glTF-2.0.html#reference-material. There is a proposal to extend the standard with such a texture here: https://github.com/KhronosGroup/glTF/pull/2196. though it does look like a lot of work is needed to get it merged.
Furthermore, it is bevy that loads the GLTF, so we are stuck with whatever material & textures it loads. I think generating a height map based on the normal map is possible (see the TODO section of the README) But doing that at runtime is a bit beyond what I find acceptable in terms of performance. This is where a bevy asset preprocessing pipeline would be useful (planned for 0.11 I think)

So if by "at runtime" you mean "in user code" the answer currently is "yes". As long as we don't somehow push the depth map (for parallax mapping, we should talk about "depth map" over height map) into the gltf model, we'll have to somehow tell bevy to load height maps. Currently the only way to tell bevy anything is through code. cart has been talking about "meta files" for the future asset pipeline which could also fulfills this role.
Though, time to plug my normal2depth map plugin. :rocket: If your gltf comes with a normal map but not a depth map, you can now generate it! Nothing easier, use the bevy_mod_n2dmap crate and call standard_material.generate_depth_map(&mut images_asset) and now your material should have a depth map, enabling directly parallax mapping on it. https://github.com/devildahu/n2dmap :rocket:

Woah, that crate sounds really useful, thanks! I'll be sure to use it once Bevy 0.11 rolls out.

well, I've just started testing it and it doesn't work quite well yet. :sweat_smile: So I'd reserve judgement until it's complete.

I decided that this is out of scope for the template