repo_name stringlengths 9 75 | topic stringclasses 30
values | issue_number int64 1 203k | title stringlengths 1 976 | body stringlengths 0 254k | state stringclasses 2
values | created_at stringlengths 20 20 | updated_at stringlengths 20 20 | url stringlengths 38 105 | labels listlengths 0 9 | user_login stringlengths 1 39 | comments_count int64 0 452 |
|---|---|---|---|---|---|---|---|---|---|---|---|
huggingface/datasets | pytorch | 7,337 | One or several metadata.jsonl were found, but not in the same directory or in a parent directory of | ### Describe the bug
ImageFolder with metadata.jsonl error. I downloaded liuhaotian/LLaVA-CC3M-Pretrain-595K locally from Hugging Face. According to the tutorial in https://huggingface.co/docs/datasets/image_dataset#image-captioning, only put images.zip and metadata.jsonl containing information in the same folder. However, after loading, an error was reported: One or several metadata.jsonl were found, but not in the same directory or in a parent directory of.
The data in my jsonl file is as follows:
> {"id": "GCC_train_002448550", "file_name": "GCC_train_002448550.jpg", "conversations": [{"from": "human", "value": "<image>\nProvide a brief description of the given image."}, {"from": "gpt", "value": "a view of a city , where the flyover was proposed to reduce the increasing traffic on thursday ."}]}
### Steps to reproduce the bug
from datasets import load_dataset
image = load_dataset("imagefolder",data_dir='data/opensource_data')
### Expected behavior
success
### Environment info
datasets==3.2.0 | open | 2024-12-17T12:58:43Z | 2025-01-03T15:28:13Z | https://github.com/huggingface/datasets/issues/7337 | [] | mst272 | 1 |
zappa/Zappa | django | 740 | [Migrated] Getting 'AttributeError' Exception Thrown | Originally from: https://github.com/Miserlou/Zappa/issues/1864 by [canada4663](https://github.com/canada4663)
I am getting uncaught AttributeError thrown at the line below:
https://github.com/Miserlou/Zappa/blob/3ccf7490a8d8b8fa74a61ee39bf44234f3567739/zappa/handler.py#L309
It seems that the code is designed to catch exceptions where the 'command' key doesn't exist, however, if the message doesn't included an object with the get method and is only a 'str' then this fails.
| closed | 2021-02-20T12:41:37Z | 2022-07-16T06:23:36Z | https://github.com/zappa/Zappa/issues/740 | [] | jneves | 1 |
AUTOMATIC1111/stable-diffusion-webui | deep-learning | 16,807 | [Bug]: Updated installation instructions for installing Stable Diffusion using ROCm (Linux) (Documentation and webui.sh needs updating) | ### Checklist
- [ ] The issue exists after disabling all extensions
- [x] The issue exists on a clean installation of webui
- [ ] The issue is caused by an extension, but I believe it is caused by a bug in the webui
- [x] The issue exists in the current version of the webui
- [ ] The issue has not been reported before recently
- [ ] The issue has been reported before but has not been fixed yet
### What happened?
Run the same instructions as the documentation says for the first part.
(Debian): `sudo apt install git python3.10-venv -y`
(Fedora): `sudo dnf install python-3.10`
`git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui && cd stable-diffusion-webui`
`python3.10 -m venv venv`
Then update line 156 in webui.sh
`pip install torch torchvision --index-url https://download.pytorch.org/whl/nightly/rocm5.7` --> `pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.2`
Run webui.sh with this command
`HSA_OVERRIDE_GFX_VERSION=11.0.0 HIP_VISIBLE_DEVICES=0 ./webui.sh --precision full --no-half`
VERSION=11.0.0 is specific to the 7900XTX, version number may change depending on GPU model so check ROCm documentation just in case. If you have a 7900XTX, follow instructions exactly.
### Steps to reproduce the problem
1. Follow the official documentation
### What should have happened?
Documentation and ROCm in webui.sh needs updating to make webui.sh work error free.
### What browsers do you use to access the UI ?
Brave
### Sysinfo
Not needed as the program is running with all features when instructions above is followed.
### Console logs
```Shell
################################################################
Install script for stable-diffusion + Web UI
Tested on Debian 11 (Bullseye), Fedora 34+ and openSUSE Leap 15.4 or newer.
################################################################
################################################################
Running on user user
################################################################
################################################################
Repo already cloned, using it as install directory
################################################################
################################################################
Create and activate python venv
################################################################
################################################################
Launching launch.py...
################################################################
glibc version is 2.40
Check TCMalloc: libtcmalloc_minimal.so.4
libtcmalloc_minimal.so.4 is linked with libc.so,execute LD_PRELOAD=/lib64/libtcmalloc_minimal.so.4
Python 3.10.16 (main, Dec 4 2024, 00:00:00) [GCC 14.2.1 20240912 (Red Hat 14.2.1-3)]
Version: v1.10.1
Commit hash: 82a973c04367123ae98bd9abdf80d9eda9b910e2
ControlNet init warning: Unable to install insightface automatically. Please try run `pip install insightface` manually.
Launching Web UI with arguments: --precision full --no-half
no module 'xformers'. Processing without...
no module 'xformers'. Processing without...
No module 'xformers'. Proceeding without it.
ControlNet preprocessor location: /home/user/AI/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/downloads
2025-01-21 14:56:37,167 - ControlNet - INFO - ControlNet v1.1.455
Loading weights [a31be20e08] from /home/user/AI/stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned-emaonly.safetensors
2025-01-21 14:56:37,546 - ControlNet - INFO - ControlNet UI callback registered.
Running on local URL: http://127.0.0.1:7860
To create a public link, set `share=True` in `launch()`.
Creating model from config: /home/user/AI/stable-diffusion-webui/configs/v1-inference.yaml
Startup time: 12.6s (prepare environment: 7.1s, import torch: 1.7s, import gradio: 0.4s, setup paths: 1.6s, other imports: 0.3s, load scripts: 0.6s, create ui: 0.4s, gradio launch: 0.3s).
```
### Additional information
_No response_ | open | 2025-01-21T20:02:02Z | 2025-03-01T10:33:19Z | https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/16807 | [
"bug-report"
] | theman23290 | 3 |
man-group/arctic | pandas | 197 | Libraries use cases | Hi,
I am working with historical minute data and was wondering which is the right library to store it.
Most of the columns are numerical but I have some metadata on each transaction as well, some of which that I could encode as numerical just adding more columns (dummy variables), and some that are just strings adding information on the transaction.
First thing I thought was to use TickStoreV3, but I'm struggling a bit with the metadata.
Also, in a more general way, for which kind of data are the different libraries optimized for?
Thanks!
| closed | 2016-08-12T15:28:45Z | 2016-08-20T09:36:55Z | https://github.com/man-group/arctic/issues/197 | [] | felipe-ducau7c | 8 |
pallets/flask | python | 4,910 | Deprecation of before_first_request leads to issue with Gunicorn --preload while launching a Thread in the Setup Code | Flask 2.2.2 has deprecated `before_first_request`, advising us to instead run the setup code in the the factory function that creates the `app`.
I've found a case where this solution does not work. The prerequisite is that the application is launched from Gunicorn with the `--preload` option, and that you want to have a global variable which is shared among all the workers/threads.
Running generic setup code results in the memory of the global variable apparently not being shared, while running the code in `before_first_request` behaves according to expectations.
-----
Here is the code to reproduce.
It has a global variable called `global_list`. There is a thread that is supposed to be launched in the setup code that append values onto the global variable. A GET API will return the result of the global variable.
When using `before_first_request`, it runs as expected. Calling GET will return the populated values in the list.
When using independent setup code, the global variable is not global and is not shared.
```
from flask import Flask, Blueprint
import threading
import time
global_list = []
bp = Blueprint('hello', __name__)
@bp.get('/')
def home():
return global_list
def create_app():
app = Flask(__name__)
app.register_blueprint(bp)
run_setup_code()
# this works fine but is deprecated in 2.2.2
# app.before_first_request(run_setup_code)
return app
def run_setup_code():
t = threading.Thread(target=work, daemon=True)
t.start()
def work():
for i in range(100):
global_list.append(i)
print('in _setup', global_list)
time.sleep(2)
```
Run this code via:
gunicorn --preload --workers=1 --threads=1 "app:create_app()" --bind=0.0.0.0:3000
You will see from the print statement that the global variable is being appended to. You can confirm this variable is not being shared correctly by calling the following, which will not return the values in the global list.
http GET :3000/
-------
The desired behavior here is that the global_variable will be shared between the `work` thread and the gunicorn worker process. Calling `GET /` should return a list of all the values that have been appended in the work thread.
The actual behavior is that calling `GET /` will not return the list of values.
-----
This works fine with `before_first_request` while using gunicorn's `--preload` option.
It also works fine if you remove the `--preload` option and just run the setup code in the factory function.
-----
Environment:
- Python version:3.9,3.10
- Flask version:2.2.2
| closed | 2022-12-15T17:13:53Z | 2023-01-10T00:05:52Z | https://github.com/pallets/flask/issues/4910 | [] | mkmoisen | 1 |
pydantic/bump-pydantic | pydantic | 104 | Detect missing pydantic dependency (e.g. pydantic-settings or extra types) | Hey team,
I wasn't sure if you would be comfortable with this, but what's your opinion on telling the user when they are missing a pydantic dependency, such as `pydantic-settings` is using `BaseSettings` in Pydantic V1?
This could spit out a warning (whether that's stdout, stderr, log.txt, or somewhere else) or a `# TODO` comment if the `pydantic-settings` package isn't installed.
This will help users more quickly identify when their application requires packages that are not currently installed.
To detect if a package is installed without importing it (for safety reasons), `importlib.util` can be used:
```
from importlib.util import find_spec
print(find_spec("pydantic-settings"))
# ''
print(find_spec("pydantic"))
# 'ModuleSpec(name='pydantic', loader=<_frozen_importlib_external.SourceFileLoader object at 0x104e18240>, origin='/Users/kkirsche/.asdf/installs/python/3.11.4/lib/python3.11/site-packages/pydantic/__init__.py', submodule_search_locations=['/Users/kkirsche/.asdf/installs/python/3.11.4/lib/python3.11/site-packages/pydantic'])'
```
Documentation on `find_spec`:
https://docs.python.org/3/library/importlib.html#importlib.util.find_spec | open | 2023-07-18T15:01:16Z | 2024-07-21T07:39:26Z | https://github.com/pydantic/bump-pydantic/issues/104 | [
"good first issue"
] | kkirsche | 3 |
DistrictDataLabs/yellowbrick | matplotlib | 727 | Not able to import UMAPVisualizer from yellowbrick.text | I downloaded the latest package of yellowbrick but it was file of umap_vis.py was missing from the package of yellowbrick.text
| closed | 2019-02-06T05:43:53Z | 2019-02-11T03:19:43Z | https://github.com/DistrictDataLabs/yellowbrick/issues/727 | [
"type: question"
] | soniaarora | 2 |
flasgger/flasgger | rest-api | 590 | Latest version 0.9.7.1 break Marshmallow apispec dumping | Maybe it's just an incompatible versions, but i must use this set of packages
```
apispec==5.2.2
marshmallow==3.15
flasgger==0.9.5
```
i can't upgrade apispec or marshmallow because there are other dependency.
with flasgger 0.9.7.1
```
TypeError: Object of type SchemaMeta is not JSON serializable
```
I suggest to:
- fix version requirements with apispec/marshmallow
- write versions changelog
- better error output when generating apispec. It's struggle to find which API cause the problem. I use swag_from decorator
Thanks | open | 2023-08-02T09:20:09Z | 2023-08-02T09:20:09Z | https://github.com/flasgger/flasgger/issues/590 | [] | overbost | 0 |
matplotlib/mplfinance | matplotlib | 659 | Bug Report: Typo | **Describe the bug**
mplfinance/plotting.py", line 946, in plot
fig.suptitle(title,**title_kwargs)
^^^^^^^^^^^^
AttributeError: 'NoneType' object has no attribute 'suptitle'
| closed | 2024-02-15T22:09:17Z | 2024-02-16T12:48:30Z | https://github.com/matplotlib/mplfinance/issues/659 | [
"bug"
] | aidenkwong | 1 |
NVIDIA/pix2pixHD | computer-vision | 129 | No module named 'apex' | Do someone know how to solve this problem? | open | 2019-05-31T13:34:37Z | 2019-06-03T02:12:05Z | https://github.com/NVIDIA/pix2pixHD/issues/129 | [] | ashergaga | 1 |
explosion/spaCy | machine-learning | 12,034 | TypeError: dataclass_transform() got an unexpected keyword argument 'field_specifiers' | After latest pydantic-1.10.3 release, spacy no longer can be imported, raising a TypeError.
The root cause is an incompatibility between pydantic-1.10.3 and your requirement `typing_extensions>=3.7.4,<4.2.0; python_version < "3.8"`.
See issue in pydantic:
- https://github.com/pydantic/pydantic/issues/4885
See fixing PR in pydantic (`typing-extensions>=4.2.0`), which will be incompatible with your requirement `typing_extensions>=3.7.4,<4.2.0; python_version < "3.8"`:
- https://github.com/pydantic/pydantic/pull/4886
<!-- Include a code example or the steps that led to the problem. Please try to be as specific as possible. -->
To reproduce the error:
```shell
pip install spacy
python -c "import spacy"
```
raises:
```
Traceback (most recent call last):
File "<string>", line 1, in <module>
File ".../venvs/venv-py37-spacy/lib/python3.7/site-packages/spacy/__init__.py", line 6, in <module>
from .errors import setup_default_warnings
File ".../venvs/venv-py37-spacy/lib/python3.7/site-packages/spacy/errors.py", line 2, in <module>
from .compat import Literal
File ".../venvs/venv-py37-spacy/lib/python3.7/site-packages/spacy/compat.py", line 3, in <module>
from thinc.util import copy_array
File ".../venvs/venv-py37-spacy/lib/python3.7/site-packages/thinc/__init__.py", line 5, in <module>
from .config import registry
File ".../venvs/venv-py37-spacy/lib/python3.7/site-packages/thinc/config.py", line 2, in <module>
import confection
File ".../venvs/venv-py37-spacy/lib/python3.7/site-packages/confection/__init__.py", line 10, in <module>
from pydantic import BaseModel, create_model, ValidationError, Extra
File "pydantic/__init__.py", line 2, in init pydantic.__init__
File "pydantic/dataclasses.py", line 46, in init pydantic.dataclasses
# | None | Attribute is set to None. |
File "pydantic/main.py", line 121, in init pydantic.main
TypeError: dataclass_transform() got an unexpected keyword argument 'field_specifiers'
```
## Your Environment
<!-- Include details of your environment. You can also type `python -m spacy info --markdown` and copy-paste the result here.-->
* Operating System:
* Python Version Used: 3.7.15
* spaCy Version Used: 3.4.4
* Environment Information:
| closed | 2022-12-30T06:51:22Z | 2023-03-05T00:02:40Z | https://github.com/explosion/spaCy/issues/12034 | [
"install",
"third-party"
] | albertvillanova | 9 |
rougier/from-python-to-numpy | numpy | 44 | Typos in 7.3 | Excellent work!
I noticed two minor grammatical issues in section 7.3, "Scipy & co" (file `07-beyond-numpy.rst`):
- "there is a trillion" -> "there are a trillion"
- "it was not the goal" -> "that was not the goal" | closed | 2017-01-12T20:01:19Z | 2017-01-13T14:16:51Z | https://github.com/rougier/from-python-to-numpy/issues/44 | [] | SeanDS | 3 |
yzhao062/pyod | data-science | 355 | Question: Does this repo include smoothing? | Referencing https://github.com/cerlymarco/tsmoothie | closed | 2021-11-03T06:25:45Z | 2021-11-07T22:29:43Z | https://github.com/yzhao062/pyod/issues/355 | [] | BradKML | 1 |
tensorpack/tensorpack | tensorflow | 961 | Accuracy of Res-18 is lower than expected on ImageNet | 1. I run the Res-18 by
+ run examples/ResNet/imagenet-resnet.py only with modification on reading data:
+ `def get_imagenet_dataflow(
datadir, name, batch_size,
augmentors, parallel=None):
assert name in ['train', 'val', 'test']
assert datadir is not None
assert isinstance(augmentors, list)
isTrain = name == 'train'
if parallel is None:
parallel = min(40, multiprocessing.cpu_count() // 2) # assuming hyperthreading
lmdb_data = os.path.join(datadir, 'ILSVRC-%s.lmdb'%name)
ds = LMDBData(lmdb_data, shuffle=False)
if isTrain:
ds = LocallyShuffleData(ds, 50000)
ds = PrefetchData(ds, 5000, 1)
ds = LMDBDataPoint(ds)
ds = MapDataComponent(ds, lambda x: cv2.imdecode(x, cv2.IMREAD_COLOR), 0)
ds = AugmentImageComponent(ds, augmentors, copy=False)
if parallel < 16:
logger.warn("DataFlow may become the bottleneck when too few processes are used.")
ds = BatchData(ds, batch_size, remainder=False)
ds = PrefetchDataZMQ(ds, parallel)
ds.reset_state()
return ds`
+ All hyper-parameters are set as default.
2. The top-1 accuracy is 67.5% after 105 epochs, which is 3% lower than reported.
3. Your environment:
+ Python version: 3.6.7
+ TF version: 1.10.0
+ Tensorpack version: 0.8.9
+ Hardware information: 4 * V100
| closed | 2018-11-01T06:56:35Z | 2019-01-16T23:47:00Z | https://github.com/tensorpack/tensorpack/issues/961 | [
"examples"
] | Sunasity | 8 |
hankcs/HanLP | nlp | 1,027 | 分词算法问题 | 我想把 “机器人” 分词成 “机器” “机器人” “机” “器” “人” 这五个词应该选择哪个分词算法 | closed | 2018-11-21T02:58:46Z | 2018-12-06T08:18:07Z | https://github.com/hankcs/HanLP/issues/1027 | [] | quicksandznzn | 2 |
proplot-dev/proplot | matplotlib | 28 | Stable tagged release? | It would be great if you could make a tagged version release on pip that's stable. The API changes so frequently right now that I feel like I'm rewriting my notebook cells every week when I pull down updates. Then folks could just install a specific version from pip while you continue development.
Releasing on PyPI takes < 5 minutes: https://github.com/bradyrx/climpred/blob/master/HOWTORELEASE.rst. You could tag a v1.0.0 and then follow semantic versioning (https://semver.org/) as you release more features. | closed | 2019-09-02T16:01:56Z | 2019-12-18T04:20:51Z | https://github.com/proplot-dev/proplot/issues/28 | [
"high priority",
"distribution"
] | bradyrx | 12 |
roboflow/supervision | tensorflow | 1,567 | Bug in git-committers-plugin-2, v2.4.0 | At the moment, an error is observed when running the `mkdocs build` action from develop.
```
File "/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/mkdocs_git_committers_plugin_2/plugin.py", line 121, in get_contributors_to_file
'avatar': commit['author']['avatar_url'] if user['avatar_url'] is not None else ''
UnboundLocalError: local variable 'user' referenced before assignment
```
This is due to: https://github.com/ojacques/mkdocs-git-committers-plugin-2/issues/72
| closed | 2024-10-03T21:29:35Z | 2024-10-04T23:41:07Z | https://github.com/roboflow/supervision/issues/1567 | [
"bug",
"documentation",
"github_actions"
] | LinasKo | 4 |
Lightning-AI/pytorch-lightning | pytorch | 19,992 | Fabric example trainer fails with validation | ### Bug description
Using the example fabric trainer with validation would result in:
> AttributeError: Your LightningModule code tried to access `self.trainer.model` but this attribute is not available when using Fabric with a LightningModule.
Which would occur during validation when 'on_validation_model_eval' and 'on_validation_model_train' were called, as they do not work with fabric.
### What version are you seeing the problem on?
master
### How to reproduce the bug
_No response_
### Error messages and logs
```
# AttributeError: Your LightningModule code tried to access `self.trainer.model` but this attribute is not available when using Fabric with a LightningModule.
```
### Environment
<details>
<summary>Current environment</summary>
```
#- Lightning Component (e.g. Trainer, LightningModule, LightningApp, LightningWork, LightningFlow):
#- PyTorch Lightning Version (e.g., 1.5.0):
#- Lightning App Version (e.g., 0.5.2):
#- PyTorch Version (e.g., 2.0):
#- Python version (e.g., 3.9):
#- OS (e.g., Linux):
#- CUDA/cuDNN version:
#- GPU models and configuration:
#- How you installed Lightning(`conda`, `pip`, source):
#- Running environment of LightningApp (e.g. local, cloud):
```
</details>
### More info
_No response_ | closed | 2024-06-18T21:01:03Z | 2024-06-21T14:43:31Z | https://github.com/Lightning-AI/pytorch-lightning/issues/19992 | [
"bug",
"needs triage",
"ver: 2.2.x"
] | liambsmith | 0 |
MagicStack/asyncpg | asyncio | 1,066 | Authentication issue with postgres14 : InternalClientError: unexpected error while performing authentication: Incorrect padding | <!--
Thank you for reporting an issue/feature request.
If this is a feature request, please disregard this template. If this is
a bug report, please answer to the questions below.
It will be much easier for us to fix the issue if a test case that reproduces
the problem is provided, with clear instructions on how to run it.
Thank you!
-->
* **asyncpg version**: 0.27.1
* **PostgreSQL version**: 14.6
* **Do you use a PostgreSQL SaaS? If so, which? Can you reproduce
the issue with a local PostgreSQL install?**: No.
* **Python version**: python 3.8
* **Platform**: linux/x86-64
* **Do you use pgbouncer?**: No
* **Did you install asyncpg with pip?**: Yes
* **If you built asyncpg locally, which version of Cython did you use?**: No
* **Can the issue be reproduced under both asyncio and
[uvloop](https://github.com/magicstack/uvloop)?**: No, we are unable to reproduce the issue consistently
<!-- Enter your issue details below this comment. -->
We have run into an exception `InternalClientError: unexpected error while performing authentication: Incorrect padding` while trying to establish connection to Aurora PostgresSQL.
This issue is not happening consistently, as more often than not, request to DB goes through successfully, but scouring through the logs, we've found few instances in past as well.
We are using username/password authentication to connect to postgres instance.
Below is the error trace
```
asyncpg.exceptions._base.InternalClientError: unexpected error while performing authentication: Incorrect padding
return fut.result()
File "/usr/local/lib/python3.8/site-packages/asyncpg/connection.py", line 2092, in connect
return dialect.connect(*cargs, **cparams)
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/langhelpers.py", line 70, in __exit__
dbapi_connection = rec.get_connection()
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/compat.py", line 207, in raise_
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/langhelpers.py", line 70, in __exit__
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/pool/base.py", line 424, in checkout
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/engine/base.py", line 3166, in connect
return super(Engine, self).connect()
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/orm/session.py", line 747, in _connection_for_bind
result = context.throw(*sys.exc_info())
return await greenlet_spawn(
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/ext/asyncio/session.py", line 158, in scalar
File "/app/./service_handler/api/deps.py", line 80, in get_account_or_404
solved_result = await solve_dependencies(
raise exc from None
return await self.app(scope, receive, send)
result = await app(self.scope, self.receive, self.send)
File "/usr/local/lib/python3.8/site-packages/asyncpg/compat.py", line 56, in wait_for
value = await result
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/_concurrency_py3k.py", line 115, in greenlet_spawn
return current.driver.switch(awaitable)
await_only(self.asyncpg.connect(*arg, **kw)),
return self.dbapi.connect(*cargs, **cparams)
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/pool/base.py", line 599, in __connect
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/compat.py", line 207, in raise_
compat.raise_(
compat.raise_(
return fn()
conn = bind.connect()
return self._transaction._connection_for_bind(
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/ext/asyncio/session.py", line 139, in execute
response = await func(request)
File "/usr/local/lib/python3.8/site-packages/starlette/routing.py", line 52, in app
await self.app(scope, receive, sender)
await self.app(scope, receive, send)
asyncpg.exceptions._base.InternalClientError: unexpected error while performing authentication: Incorrect padding
return await _connect_addr(
await_only(self.asyncpg.connect(*arg, **kw)),
raise exception
compat.raise_(
pool.logger.debug("Error on connect(): %s", e)
self.__connect()
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/pool/base.py", line 574, in get_connection
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/pool/base.py", line 421, in checkout
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/compat.py", line 207, in raise_
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/pool/base.py", line 424, in checkout
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/pool/base.py", line 301, in connect
conn = self._connection_for_bind(bind, close_with_result=True)
result = context.throw(*sys.exc_info())
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/ext/asyncio/session.py", line 139, in execute
account: Optional[models.Account] = await db.scalar(statement=get_account_stmt)
solved_result = await solve_dependencies(
await route.handle(scope, receive, send)
raise exc from None
return fut.result()
File "/usr/local/lib/python3.8/asyncio/tasks.py", line 494, in wait_for
File "/usr/local/lib/python3.8/site-packages/asyncpg/connect_utils.py", line 881, in _connect
return await connect_utils._connect(
value = await result
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/_concurrency_py3k.py", line 115, in greenlet_spawn
connection = pool._invoke_creator(self)
return fn()
return self._wrap_pool_connect(self.pool.connect, _connection)
return await greenlet_spawn(
File "/app/./service_handler/crud/account.py", line 83, in lookup_account_by_company_id
File "/app/./service_handler/api/deps.py", line 80, in get_account_or_404
File "/usr/local/lib/python3.8/site-packages/starlette/routing.py", line 580, in __call__
File "/usr/local/lib/python3.8/site-packages/asyncpg/compat.py", line 56, in wait_for
await compat.wait_for(connected, timeout=timeout)
return current.driver.switch(awaitable)
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/engine/default.py", line 584, in connect
return dialect.connect(*cargs, **cparams)
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/engine/create.py", line 578, in connect
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/pool/base.py", line 599, in __connect
raise exception
compat.raise_(
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/langhelpers.py", line 70, in __exit__
return super(Engine, self).connect()
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/orm/session.py", line 1676, in execute
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/_concurrency_py3k.py", line 120, in greenlet_spawn
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/ext/asyncio/session.py", line 158, in scalar
solved = await call(**sub_values)
File "/usr/local/lib/python3.8/site-packages/fastapi/routing.py", line 204, in app
await self.app(scope, receive, send)
return await asyncio.wait_for(fut, timeout)
File "/usr/local/lib/python3.8/site-packages/asyncpg/connect_utils.py", line 831, in __connect_addr
return await __connect_addr(params, timeout, True, *args)
File "/usr/local/lib/python3.8/site-packages/asyncpg/connection.py", line 2092, in connect
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/_concurrency_py3k.py", line 62, in await_only
return self.dbapi.connect(*cargs, **cparams)
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/pool/base.py", line 605, in __connect
dbapi_connection = rec.get_connection()
rec._checkin_failed(err, _fairy_was_created=False)
return _ConnectionFairy._checkout(self)
else engine.raw_connection()
return self._transaction._connection_for_bind(
result = await self.execute(
result = await account.lookup_account_by_company_id(db=session, account_id=account_id, company_id=company_id)
File "/usr/local/lib/python3.8/site-packages/fastapi/dependencies/utils.py", line 548, in solve_dependencies
response = await func(request)
File "/usr/local/lib/python3.8/site-packages/starlette/routing.py", line 52, in app
File "/usr/local/lib/python3.8/site-packages/starlette/routing.py", line 241, in handle
File "/usr/local/lib/python3.8/site-packages/starlette/exceptions.py", line 71, in __call__
File "/usr/local/lib/python3.8/site-packages/asyncpg/connect_utils.py", line 773, in _connect_addr
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/dialects/postgresql/asyncpg.py", line 747, in connect
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/compat.py", line 207, in raise_
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/util/langhelpers.py", line 70, in __exit__
fairy = _ConnectionRecord.checkout(pool)
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/pool/base.py", line 761, in _checkout
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/engine/base.py", line 3212, in _wrap_pool_connect
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/engine/base.py", line 3245, in raw_connection
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/engine/base.py", line 96, in __init__
return self._connection_cls(self, close_with_result=close_with_result)
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/engine/base.py", line 3166, in connect
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/future/engine.py", line 419, in connect
conn = bind.connect()
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/orm/session.py", line 747, in _connection_for_bind
File "/usr/local/lib/python3.8/site-packages/sqlalchemy/orm/session.py", line 1526, in _connection_for_bind
await self.app(scope, receive, sender)
await self.app(scope, receive, send)
File "/usr/local/lib/python3.8/site-packages/starlette/middleware/errors.py", line 159, in __call__
Traceback (most recent call last):
File "/usr/local/lib/python3.8/site-packages/starlette/exceptions.py", line 82, in __call__
File "/usr/local/lib/python3.8/site-packages/starlette/middleware/cors.py", line 78, in __call__
await self.app(scope, receive, _send)
```
| open | 2023-08-17T06:59:26Z | 2023-10-12T15:27:01Z | https://github.com/MagicStack/asyncpg/issues/1066 | [] | prakharg05 | 2 |
AntonOsika/gpt-engineer | python | 231 | Ability to resume after an error occurs | I didn't see a way to do this, apologies if it is described somewhere. I am attempting to build an application and I noticed any time it exits due to an error the process stops and then I'm stuck. So for example:
```
...
npm install
To run the codebase:
npm run dev
Do you want to execute this code?
npm install
npm run dev
If yes, press enter. Otherwise, type "no"
Executing the code...
npm WARN deprecated @types/googlemaps@3.43.3: Types for the Google Maps browser API have moved to @types/google.maps. Note: these types are not for the googlemaps npm package, which is a Node API.
npm WARN deprecated @material-ui/styles@4.11.5: Material UI v4 doesn't receive active development since September 2021. See the guide https://mui.com/material-ui/migration/migration-v4/ to upgrade to v5.
npm WARN deprecated @material-ui/core@4.12.4: Material UI v4 doesn't receive active development since September 2021. See the guide https://mui.com/material-ui/migration/migration-v4/ to upgrade to v5.
added 39 packages, removed 347 packages, and audited 354 packages in 5s
44 packages are looking for funding
run `npm fund` for details
5 critical severity vulnerabilities
To address all issues (including breaking changes), run:
npm audit fix --force
Run `npm audit` for details.
> scavenger@1.0.0 dev
> next dev
ready - started server on 0.0.0.0:3000, url: http://localhost:3000
info - Using webpack 5. Reason: Enabled by default https://nextjs.org/docs/messages/webpack5
It looks like you're trying to use TypeScript but do not have the required package(s) installed.
Please install @types/react by running:
yarn add --dev @types/react
If you are not trying to use TypeScript, please remove the tsconfig.json file from your package root (and any TypeScript files in your pages directory).
(venv) ➜ gpt-engineer git:(main) ✗
```
Notice the typescript error above, and the process ends and I'm back at the command prompt. Is it possible to resume after adding the missing package with `yarn add --dev @types/react`? If not, it'd be a great feature. | closed | 2023-06-19T21:26:15Z | 2023-09-12T09:31:58Z | https://github.com/AntonOsika/gpt-engineer/issues/231 | [
"good first issue",
"triage"
] | danb235 | 7 |
recommenders-team/recommenders | data-science | 2,089 | [ASK] Is binary relevance the only option in RankingMetric class for pyspark evaluation? | While testing metrics for pyspark evaluation, I've noticed that the ranking metrics like NDCG seems to be using binary relevances only, while [python evaluation](https://github.com/recommenders-team/recommenders/blob/main/recommenders/evaluation/python_evaluation.py#L573) has a parameter to chose between binary, exponential or raw relevances. The snippet below shows that behavior (it will only consider which items are relevant, but not accessing their relevances):
https://github.com/recommenders-team/recommenders/blob/c2ea583d27bb1a4d58a09a1621d5ce95672ef1dc/recommenders/evaluation/spark_evaluation.py#L292-L295
Is it possible to use exponencial or raw relevances in spark evaluation currently or am I wrong in this analysis? | open | 2024-04-18T20:17:53Z | 2024-04-18T20:22:14Z | https://github.com/recommenders-team/recommenders/issues/2089 | [] | lgabs | 0 |
home-assistant/core | python | 140,700 | Jellyfin "TypeError: 'NoneType' object is not iterable" | ### The problem
Getting this error since last update. on Jellyfin side I see regular successful auth in logs.
> 2025-03-16 00:43:30.600 ERROR (SyncWorker_11) [JELLYFIN.jellyfin_apiclient_python.api] Invalid URL 'jellyfin.mydomain.net/Users/AuthenticateByName': No scheme supplied. Perhaps you meant https://jellyfin.mydomain.net/Users/AuthenticateByName?
2025-03-16 00:45:08.175 ERROR (SyncWorker_19) [Jellyfin.jellyfin_apiclient_python.http] 500 Server Error: Internal Server Error for url: https://jellyfin.mydomain.net//Sessions
2025-03-16 00:45:08.176 ERROR (SyncWorker_19) [Jellyfin.jellyfin_apiclient_python.http] --[ 500 response ] 500 Server Error: Internal Server Error for url: https://jellyfin.mydomain.net//Sessions
2025-03-16 00:45:08.177 ERROR (MainThread) [homeassistant.components.jellyfin] Unexpected error fetching jellyfin data
Traceback (most recent call last):
File "/usr/src/homeassistant/homeassistant/helpers/update_coordinator.py", line 380, in _async_refresh
self.data = await self._async_update_data()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/src/homeassistant/homeassistant/components/jellyfin/coordinator.py", line 59, in _async_update_data
for session in sessions
^^^^^^^^
TypeError: 'NoneType' object is not iterable
### What version of Home Assistant Core has the issue?
core-2025.3.3
### What was the last working version of Home Assistant Core?
core-2025.3.2
### What type of installation are you running?
Home Assistant Container
### Integration causing the issue
Jellyfin
### Link to integration documentation on our website
https://www.home-assistant.io/integrations/jellyfin
### Diagnostics information
[home-assistant_jellyfin_2025-03-15T23-48-41.223Z.log](https://github.com/user-attachments/files/19267274/home-assistant_jellyfin_2025-03-15T23-48-41.223Z.log)
### Example YAML snippet
```yaml
```
### Anything in the logs that might be useful for us?
```txt
```
### Additional information
_No response_ | open | 2025-03-15T23:57:13Z | 2025-03-15T23:58:11Z | https://github.com/home-assistant/core/issues/140700 | [
"integration: jellyfin"
] | ytugarev | 1 |
keras-team/autokeras | tensorflow | 1,326 | The dataset should at least contain 2 batches to be split | ```
import pandas as pd
import numpy as np
import autokeras as ak
from tensorflow.keras.datasets import cifar10
from tensorflow.python.keras.utils.data_utils import Sequence
from tensorflow.keras.models import model_from_json
import os
def build_model():
input_layer =ak.Input()
cnn_layer = ak.ConvBlock()(input_layer)
cnn_layer2 =ak.ConvBlock()(cnn_layer)
dense_layer =ak.DenseBlock()(cnn_layer2)
dense_layer2 =ak.DenseBlock()(dense_layer)
output_layer =ak.ClassificationHead(num_classes=10)(dense_layer2)
automodel =ak.auto_model.AutoModel(input_layer,output_layer,max_trials=20,seed=123,project_name="automl")
return automodel
def build():
((trainX,trainY),(testX,testY))=cifar10.load_data()
automodel = build_model()
automodel.fit(trainX,trainY,validation_split=0.2,epochs=40,batch_size=64)#error here
if __name__ == '__main__':
build()
```
i got this error even trying the example in the docs
```
automodel.fit(trainX,trainY,validation_split=0.2,epochs=40,batch_size=64)
File "S:\Anaconda\envs\tensor37\lib\site-packages\autokeras\auto_model.py", line 276, in fit
validation_split=validation_split,
File "S:\Anaconda\envs\tensor37\lib\site-packages\autokeras\auto_model.py", line 409, in _prepare_data
dataset, validation_split
File "S:\Anaconda\envs\tensor37\lib\site-packages\autokeras\utils\data_utils.py", line 47, in split_dataset
"The dataset should at least contain 2 batches to be split."
ValueError: The dataset should at least contain 2 batches to be split.
```
autokeras 1.0.8
keras 2.3.1
tensorflow 2.1.0
numpy 1.19.1
pandas 1.1.1
keras-tuner 1.0.2rc1
python 3.7.7 | closed | 2020-09-01T03:14:07Z | 2021-12-03T20:30:39Z | https://github.com/keras-team/autokeras/issues/1326 | [
"bug report",
"wontfix"
] | Cariaga | 19 |
graphql-python/graphene-django | django | 756 | How to use throttling in django-graphene? | The answer says to use django-throttle-requests
[Issue 676](https://github.com/graphql-python/graphene-django/issues/676)
But how to use it, it gives the following error:
This the error with django-throttle-requests
`'ResolveInfo' object has no attribute 'META'`
for the code:
```
from django.utils.decorators import method_decorator
from throttle.decorators import throttle
class CreatePageView(graphene.Mutation):
pageview = graphene.Field(PageViewType)
class Arguments:
subscriptionkey = graphene.String(required=True)
@method_decorator(throttle(zone='default'))
def mutate(self, info, subscriptionkey):
pv = PageView(subscriptionkey=subscriptionkey)
pv.save()
return CreatePageView(pageview=pv)
``` | closed | 2019-08-23T06:40:04Z | 2019-12-26T21:38:58Z | https://github.com/graphql-python/graphene-django/issues/756 | [
"wontfix"
] | amiyatulu | 2 |
d2l-ai/d2l-en | deep-learning | 2,494 | French spelling to fix in chapter_attention-mechanisms-and-transformers/index.md | In file "chapter_attention-mechanisms-and-transformers/index.md"
> ...translating the sentence “my feet hurt” to “j’ai mal au pieds”
the french sentence should be
> ...translating the sentence “my feet hurt” to “j’ai mal aux pieds”
using "aux" which is the plural form of "au" as "pieds" is plural.
| open | 2023-05-17T17:00:12Z | 2023-05-17T17:00:12Z | https://github.com/d2l-ai/d2l-en/issues/2494 | [] | Serge-45 | 0 |
ray-project/ray | machine-learning | 51,443 | Release test aws_cluster_launcher_minimal failed | Release test **aws_cluster_launcher_minimal** failed. See https://buildkite.com/ray-project/release/builds/36144#0195a7e1-6c9b-4796-ae13-1d73d2b6e00d for more details.
Managed by OSS Test Policy | closed | 2025-03-18T06:20:19Z | 2025-03-24T16:42:37Z | https://github.com/ray-project/ray/issues/51443 | [
"bug",
"P0",
"triage",
"release-test",
"jailed-test",
"ray-test-bot",
"weekly-release-blocker",
"stability",
"clusters"
] | can-anyscale | 1 |
dask/dask | numpy | 11,383 | New "auto" rechunking can break with Zarr | It looks like the updates in https://github.com/dask/dask/pull/11354 can result in non-uniform chunks when using "auto" rechunking. This is problematic for then writing to Zarr, which needs uniform chunks.
For example, this rechunking snippet used to run with the latest `2024.8.2` release
```python
import xarray as xr
# Load dataset
ds = xr.open_zarr(
"gs://weatherbench2/datasets/era5/1959-2023_01_10-full_37-1h-0p25deg-chunk-1.zarr",
).drop_encoding()
# Subset
time_range = slice("2020-01-01", "2020-01-10")
subset = ds.sea_surface_temperature.sel(time=time_range)
# Rechunk
result = subset.chunk({"time": -1, "longitude": "auto", "latitude": "auto"})
# Write result to cloud storage
result.to_zarr("gs://coiled-scratch-space/jrbourbeau/test-rechunking-era5.zarr/", mode="w")
```
but now raises this error with `main`:
```
Traceback (most recent call last):
File "/Users/james/projects/demos/rechunking/test.py", line 16, in <module>
result.to_zarr("gs://coiled-scratch-space/jrbourbeau/test-rechunking-era5.zarr/", mode="w")
File "/Users/james/mambaforge/envs/examples/lib/python3.10/site-packages/xarray/core/dataarray.py", line 4328, in to_zarr
return to_zarr( # type: ignore[call-overload,misc]
File "/Users/james/mambaforge/envs/examples/lib/python3.10/site-packages/xarray/backends/api.py", line 1697, in to_zarr
dump_to_store(dataset, zstore, writer, encoding=encoding)
File "/Users/james/mambaforge/envs/examples/lib/python3.10/site-packages/xarray/backends/api.py", line 1384, in dump_to_store
store.store(variables, attrs, check_encoding, writer, unlimited_dims=unlimited_dims)
File "/Users/james/mambaforge/envs/examples/lib/python3.10/site-packages/xarray/backends/zarr.py", line 726, in store
self.set_variables(
File "/Users/james/mambaforge/envs/examples/lib/python3.10/site-packages/xarray/backends/zarr.py", line 772, in set_variables
encoding = extract_zarr_variable_encoding(
File "/Users/james/mambaforge/envs/examples/lib/python3.10/site-packages/xarray/backends/zarr.py", line 285, in extract_zarr_variable_encoding
chunks = _determine_zarr_chunks(
File "/Users/james/mambaforge/envs/examples/lib/python3.10/site-packages/xarray/backends/zarr.py", line 136, in _determine_zarr_chunks
raise ValueError(
ValueError: Zarr requires uniform chunk sizes except for final chunk. Variable named 'sea_surface_temperature' has incompatible dask chunks: ((240,), (241, 240, 240), (480, 480, 480)). Consider rechunking using `chunk()`.
```
cc @hendrikmakait @phofl | closed | 2024-09-10T16:45:12Z | 2024-09-12T15:08:23Z | https://github.com/dask/dask/issues/11383 | [
"array",
"bug"
] | jrbourbeau | 0 |
sherlock-project/sherlock | python | 1,798 | Cloning into kali, Sherlock cloning is stack at 30% , anyone faced this before? | closed | 2023-05-19T07:22:17Z | 2023-08-29T12:41:59Z | https://github.com/sherlock-project/sherlock/issues/1798 | [] | acrambot | 0 | |
huggingface/text-generation-inference | nlp | 2,239 | Can I somehow change attention type from 'FlashAttention' in the text-server-launcher? | closed | 2024-07-16T18:37:45Z | 2024-08-24T01:52:31Z | https://github.com/huggingface/text-generation-inference/issues/2239 | [
"question",
"Stale"
] | wasifmasood | 2 | |
flasgger/flasgger | rest-api | 574 | Please add a security policy | As per GitHub's best practices, please add a https://docs.github.com/en/code-security/getting-started/adding-a-security-policy-to-your-repository to this repo. | open | 2023-06-05T01:06:07Z | 2023-06-05T01:06:07Z | https://github.com/flasgger/flasgger/issues/574 | [] | reedy | 0 |
geopandas/geopandas | pandas | 3,434 | ENH: Have Geoseries methods called on a GeoDataFrame return a GeoDataFrame? | #### Describe the solution you'd like
When a `GeoSeries` function is called on a `GeoDataFrame`, a `GeoSeries` of the result of running the method on the geometry column is returned.
I think it would be more practical and intuitif if a copy of the `GeoDataframe` with the `geometry` column replaced with the result of the function would be returned.
This is rather a question on whether there is an explicit reason of why the behaviour is as it is or if it is rather historical or ?
Because... the non-backwards-compatibility impact would most likely be large to existing code bases, and the gains might not be worth the trouble.
#### Additional context
``` python
import geopandas as gpd
from shapely import Polygon
# Input
poly1 = Polygon([(1, 1), (8, 1), (9, 9), (1, 8)])
poly2 = Polygon([(2, 1), (8, 1), (8, 8), (2, 8)])
poly3 = Polygon([(1, 2), (9, 2), (7, 9), (2, 8)])
gdf = gpd.GeoDataFrame(geometry=[poly1, poly2, poly3])
repr_point_gdf = gdf.representative_point()
print(type(repr_point_gdf))
repr_point_series = gdf.geometry.representative_point()
print(type(repr_point_series))
```
Output:
```
<class 'geopandas.geoseries.GeoSeries'>
<class 'geopandas.geoseries.GeoSeries'>
``` | open | 2024-10-05T06:41:23Z | 2024-10-06T12:05:42Z | https://github.com/geopandas/geopandas/issues/3434 | [
"enhancement",
"wontfix"
] | theroggy | 11 |
strawberry-graphql/strawberry-django | graphql | 82 | Copied Docs, but getting: module 'strawberry_django.auth' has no attribute 'register' | All other uses of `strawberry.django.auth` are working except for `register()`. Sure enough, even when I debug, the `strawberry.django.auth` global only has three function variables: `current_user`, `login`, and `logout`.
**types.py:**
```
from django.contrib.auth import get_user_model
from strawberry.django import type, auto, input
@type(get_user_model())
class User:
username: auto
email: auto
@input(get_user_model())
class UserInput:
username: auto
password: auto
```
**schema.py:**
@strawberry.type
class Query:
me: User = auth.current_user()
@strawberry.type
class Mutation:
login: User = auth.login()
register: User = auth.register(UserInput)
logout = auth.logout()
schema = strawberry.Schema(query=Query, mutation=Mutation)
manage.py runserver:
```
...
"/usr/local/Cellar/python@3.9/3.9.9/Frameworks/Python.framework/Versions/3.9/lib/python3.9/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1030, in _gcd_import
File "<frozen importlib._bootstrap>", line 1007, in _find_and_load
File "<frozen importlib._bootstrap>", line 986, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 680, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 850, in exec_module
File "<frozen importlib._bootstrap>", line 228, in _call_with_frames_removed
File "/root_dir/app_name/urls.py", line 4, in <module>
from app_name.schema import schema
File "/root_dir/app_name/schema.py", line 18, in <module>
class Mutation:
File "/root_dir/app_name/schema.py", line 20, in Mutation
register: User = auth.register(UserInput)
AttributeError: module 'strawberry_django.auth' has no attribute 'register'
```
| closed | 2021-12-29T06:40:01Z | 2022-02-19T19:22:56Z | https://github.com/strawberry-graphql/strawberry-django/issues/82 | [] | evanheckert | 2 |
gee-community/geemap | jupyter | 1,226 | There is shift in X and Y direction of 1 pixel while downloading data using geemap.download_ee_image() | <!-- Please search existing issues to avoid creating duplicates. -->
### Environment Information
Please run the following code on your computer and share the output with us so that we can better debug your issue:
```python
import geemap
geemap.Report()
```
### Description
I am trying to download NASADEM data in EPSG:4326 coordinate system using geemap.download_ee_image(), but the downloaded data has pixel shift both in X and Y direction. The reason of error is due to the absence of crs transformation parameter.
The geemap.ee_export_image() gives correct output, but has a limitation on downloadable data. I am looking for a solution to download large image as 1 tile.
### What I Did
```
#!/usr/bin/env python
# coding: utf-8
# In[14]:
import ee,geemap,os
ee.Initialize()
# In[15]:
# NASADEM Digital Elevation 30m - version 001
elevdata=ee.Image("NASA/NASADEM_HGT/001").select('elevation')
# In[16]:
spatial_resolution_m=elevdata.projection().nominalScale().getInfo()
print(spatial_resolution_m)
# In[17]:
Map = geemap.Map()
Map
# In[23]:
# Draw any shape on the map using the Drawing tools before executing this code block
AOI=Map.user_roi
# In[21]:
print(elevdata.projection().getInfo())
# In[29]:
# geemap.ee_export_image(
# elevdata,
# r'C:\Users\rbapna\Downloads\nasadem_ee_export_image4.tif',
# scale=spatial_resolution_m,
# crs=elevdata.projection().getInfo()['crs'],
# crs_transform=elevdata.projection().getInfo()['transform'],
# region=AOI,
# dimensions=None,
# file_per_band=False,
# format='ZIPPED_GEO_TIFF',
# timeout=300,
# proxies=None,
# )
geemap.download_ee_image(
elevdata,
r'C:\Users\rbapna\Downloads\nasadem5.tif',
region=AOI,
crs=elevdata.projection().getInfo()['crs'],
scale=spatial_resolution_m,
resampling=None,
dtype='int16',
overwrite=True,
num_threads=None
)
```
| closed | 2022-08-26T11:55:52Z | 2022-08-30T16:02:18Z | https://github.com/gee-community/geemap/issues/1226 | [
"bug"
] | ravishbapna | 9 |
fastapi/sqlmodel | fastapi | 203 | The field name is python keywords, the field type is Mysql8.0 JSON | ### First Check
- [X] I added a very descriptive title to this issue.
- [X] I used the GitHub search to find a similar issue and didn't find it.
- [X] I searched the SQLModel documentation, with the integrated search.
- [X] I already searched in Google "How to X in SQLModel" and didn't find any information.
- [X] I already read and followed all the tutorial in the docs and didn't find an answer.
- [X] I already checked if it is not related to SQLModel but to [Pydantic](https://github.com/samuelcolvin/pydantic).
- [X] I already checked if it is not related to SQLModel but to [SQLAlchemy](https://github.com/sqlalchemy/sqlalchemy).
### Commit to Help
- [X] I commit to help with one of those options 👆
### Example Code
```python
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# author: TingHsi
from typing import Optional, List, Any
from sqlmodel import Field, Session, SQLModel, create_engine
from time import time
# the table is created in MySQL 8.0
# SQLModel.metadata.create_all(engine)
class Logs_Push(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
content: str
createdAt: int = int(time())
_from: str
remark: str
result: str
type: str
userIds: List[str]
engine = create_engine("mysql+cymysql://root:123@127.0.0.1:3308/db1?charset=utf8mb4")
log_1 = Logs_Push(content="log_1", createdAt=time(),_from='from',remark='remark',result='result',type='im',userIds=['0','1'])
log_2 = Logs_Push(content="log_2", createdAt=time(),_from='from',remark='remark',result='result',type='im',userIds=['2','3'])
if __name__ == '__main__':
with Session(engine) as session:
session.add(log_1)
session.add(log_2)
session.commit()
```
### Description
* I have a field, the name is "from"，rename to "_from" that's work in sqlalchemy, but sqlmodel not support;
* I have a field "userIds", the type is "json" in mysql8.0, use code "userIds = Column(JSON)" is work in sqlalchemy, use "userIds: List[str]" in sqlmodel not work.
### Operating System
macOS
### Operating System Details
_No response_
### SQLModel Version
0.0.5
### Python Version
Python 3.7.3
### Additional Context
I try patch "sqlmodel/main.py" line 378 ,function get_sqlachemy_type
add code
> if issubclass(field.type_, list) or issubclass(field.type_, dict):
> return JSON
And change my code "userIds: List[str]" to "userIds: Any"
Run this code return error:
> if issubclass(field.type_, str):
> TypeError: issubclass() arg 1 must be a class
my code not work, so i need your helps.
| open | 2021-12-27T08:12:41Z | 2021-12-29T09:44:54Z | https://github.com/fastapi/sqlmodel/issues/203 | [
"question"
] | TingHsi | 2 |
wagtail/wagtail | django | 12,459 | Replace Twitter links with Mastodon links | <!--
Summarise the documentation change you’re suggesting in the Issue title.
-->
### Details
<!--
Provide a clear and concise description of what you want to happen.
-->
Wagtail has decided to move away from Twitter/X to Mastodon (specifically Fostodon):
- https://x.com/WagtailCMS/status/1834237886285103507
- https://fosstodon.org/@wagtail
<!--
If you're suggesting a very specific change to the documentation, feel free to directly submit a pull request.
-->
### Working on this
<!--
Do you have thoughts on skills needed?
Are you keen to work on this yourself once the issue has been accepted?
Please let us know here.
-->
For the files we need to change, refer to past PRs that changed `twitter.com` to `x.com`, e.g.
- #12205
- #12234
There may be some others I have missed.
Anyone can contribute to this. View our [contributing guidelines](https://docs.wagtail.org/en/latest/contributing/index.html), add a comment to the issue once you’re ready to start.
| closed | 2024-10-24T10:30:22Z | 2024-10-24T11:10:00Z | https://github.com/wagtail/wagtail/issues/12459 | [
"Documentation",
"good first issue"
] | laymonage | 0 |
graphdeco-inria/gaussian-splatting | computer-vision | 695 | Issue with Simple-KNN's distCUDA2 function | I found a strange problem when using the ```distCUDA2``` function. If the input tensor is on my second GPU ```cuda:1```, this function will cause the following error (please also see attached screenshot):
>terminate called after throwing an instance of 'thrust::system::system_error'
> what(): CUDA free failed: cudaErrorIllegalAddress: an illegal memory access was encountered
> Aborted (core dumped)
<img width="605" alt="image" src="https://github.com/graphdeco-inria/gaussian-splatting/assets/34731246/924183b4-18d4-4049-b06c-3673c67d3976">
However, it works fine when I use ```cuda:0```.
| closed | 2024-03-06T23:12:17Z | 2024-03-06T23:25:11Z | https://github.com/graphdeco-inria/gaussian-splatting/issues/695 | [] | PeizhiYan | 1 |
biolab/orange3 | data-visualization | 7,009 | Metavariables are not excluded in feature selection methods | A longstanding issue is that metavariables are not excluded from methods. For example, in "find informative projections" for scatter plots, they appear as suggestions. Also, in feature suggestions, the metas are included. If there are many, the automatic feature selection breaks down. This is a nuisance, as metas often contain the solution to a classification problem. "Find informative mosaics" has the same issue, as does the violin plot where ordering by relevance also includes metas. Tree prediction does ignore them, though.
I am currently using version 338 on a Mac, and this error is present in the PC version as well.
This issue has existed in every version of Orange that I can recall.
Best larerooreal | open | 2025-01-30T13:21:18Z | 2025-02-19T10:01:28Z | https://github.com/biolab/orange3/issues/7009 | [
"needs discussion",
"bug report"
] | lareooreal | 4 |
CorentinJ/Real-Time-Voice-Cloning | deep-learning | 626 | Is this complete app ? | Can i use this on windows 10 ? | closed | 2021-01-14T10:40:37Z | 2021-01-15T18:37:55Z | https://github.com/CorentinJ/Real-Time-Voice-Cloning/issues/626 | [] | Ud4ba | 2 |
tflearn/tflearn | tensorflow | 1,078 | ModuleNotFoundError: No module named 'tensorflow.contrib.framework' | when i import tflearn, it says `ModuleNotFoundError: No module named 'tensorflow.contrib.framework'`, does someone knows how to deal with this issues? thanks. | open | 2018-07-23T11:39:06Z | 2019-08-24T14:56:26Z | https://github.com/tflearn/tflearn/issues/1078 | [] | ahbon123 | 2 |
plotly/dash | dash | 2,249 | [BUG] dash deployed with gunicorn keeps spamming _reload-hash requests | And this is how it looks like.
```
shaco_1 | 172.18.0.1 - - [24/Sep/2022:18:17:57 +0000] "GET /shaco/_reload-hash HTTP/1.1" 200 112 "http://localhost:8050/shaco/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36"
shaco_1 | 172.18.0.1 - - [24/Sep/2022:18:18:00 +0000] "GET /shaco/_reload-hash HTTP/1.1" 200 112 "http://localhost:8050/shaco/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36"
shaco_1 | 172.18.0.1 - - [24/Sep/2022:18:18:03 +0000] "GET /shaco/_reload-hash HTTP/1.1" 200 112 "http://localhost:8050/shaco/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36"
shaco_1 | 172.18.0.1 - - [24/Sep/2022:18:18:06 +0000] "GET /shaco/_reload-hash HTTP/1.1" 200 112 "http://localhost:8050/shaco/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36"
shaco_1 | 172.18.0.1 - - [24/Sep/2022:18:18:09 +0000] "GET /shaco/_reload-hash HTTP/1.1" 200 112 "http://localhost:8050/shaco/" "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36"
```
Why?
Shaco is my base_url | closed | 2022-09-24T18:25:09Z | 2022-09-24T18:32:10Z | https://github.com/plotly/dash/issues/2249 | [] | SnoozeFreddo | 0 |
databricks/koalas | pandas | 2,163 | databricks.koalas.info() doesn't show memory usage | The documentation states that _databricks.koalas.info()_ shows memory usage too but it doesn't in practice.
It doesn't show memory usage in the examples given in the documentation either. | closed | 2021-05-20T14:25:29Z | 2021-05-23T23:36:30Z | https://github.com/databricks/koalas/issues/2163 | [
"docs"
] | AliWaheed | 2 |
ultralytics/yolov5 | machine-learning | 12,715 | imgsz calculation | ### Search before asking
- [X] I have searched the YOLOv5 [issues](https://github.com/ultralytics/yolov5/issues) and [discussions](https://github.com/ultralytics/yolov5/discussions) and found no similar questions.
### Question
Hi, I would like to ask about the imgsz calculation. For example, I have an image(Dimension=Width 1143pixelsx Height 1499pixels). Based on my calculation, imgsz default as 640, so 1499 converted to 640 and 1143 is 488. Thus, the image shape should be 488x640. However, the input size torch.Size([1,3,640,512]) when I run TensorRT engine model. May I know why and how to calculate correctly? Thanks
### Additional
_No response_ | closed | 2024-02-07T08:40:00Z | 2024-03-19T00:20:32Z | https://github.com/ultralytics/yolov5/issues/12715 | [
"question",
"Stale"
] | KnightInsight | 2 |
pytorch/pytorch | python | 149,131 | nn.GaussianNLLLoss and F.gaussian_nll_loss do not work with scalar `var` | ### 🐛 Describe the bug
The documentation for [nn.GaussianNLLLoss](https://pytorch.org/docs/stable/generated/torch.nn.GaussianNLLLoss.html) states that the `var` input can be a scalar value, but an error occurs if a float is used. Similarly, the documentation for the functional version [nn.functional.gaussian_nll_loss](https://pytorch.org/docs/stable/generated/torch.nn.functional.gaussian_nll_loss.html) says `var` can be a scalar, but throws an error if a float is used.
# nn.GaussianNLLLoss
```python
import torch
import torch.nn as nn
loss = nn.GaussianNLLLoss()
input = torch.randn(5, 2, requires_grad=True)
target = torch.randn(5, 2)
var = 1.0
output = loss(input, target, var)
```
```
Traceback (most recent call last):
File "/Users/connorkrill/PycharmProjects/natural_hazards/burgers/scratch/torch_bug.py", line 8, in <module>
output = loss(input, target, var)
File "/opt/anaconda3/envs/natural_hazards/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/anaconda3/envs/natural_hazards/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/anaconda3/envs/natural_hazards/lib/python3.10/site-packages/torch/nn/modules/loss.py", line 377, in forward
return F.gaussian_nll_loss(input, target, var, full=self.full, eps=self.eps, reduction=self.reduction)
File "/opt/anaconda3/envs/natural_hazards/lib/python3.10/site-packages/torch/nn/functional.py", line 2858, in gaussian_nll_loss
raise ValueError("var is of incorrect size")
ValueError: var is of incorrect size
```
# nn.functional.gaussian_nll_loss
```python
import torch
import torch.nn.functional as F
input = torch.randn(5, 2, requires_grad=True)
target = torch.randn(5, 2)
var = 1.0
output = F.gaussian_nll_loss(input, target, var)
```
```
Traceback (most recent call last):
File "/Users/connorkrill/PycharmProjects/natural_hazards/burgers/scratch/torch_bug.py", line 16, in <module>
output = F.gaussian_nll_loss(input, target, var)
File "/opt/anaconda3/envs/natural_hazards/lib/python3.10/site-packages/torch/nn/functional.py", line 2841, in gaussian_nll_loss
if var.size() != input.size():
AttributeError: 'float' object has no attribute 'size'
```
### Versions
PyTorch version: 2.2.2
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A
OS: macOS 14.7.3 (x86_64)
GCC version: Could not collect
Clang version: 15.0.0 (clang-1500.3.9.4)
CMake version: Could not collect
Libc version: N/A
Python version: 3.10.14 (main, May 6 2024, 14:47:20) [Clang 14.0.6 ] (64-bit runtime)
Python platform: macOS-10.16-x86_64-i386-64bit
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Apple M2
Versions of relevant libraries:
[pip3] hamiltorch==0.4.1
[pip3] numpy==1.26.4
[pip3] torch==2.2.2
[pip3] torchdiffeq==0.2.4
[pip3] torchinfo==1.8.0
[pip3] torchsummary==1.5.1
[pip3] torchvision==0.17.2
[conda] hamiltorch 0.4.1 pypi_0 pypi
[conda] numpy 1.26.4 pypi_0 pypi
[conda] torch 2.2.2 pypi_0 pypi
[conda] torchdiffeq 0.2.4 pypi_0 pypi
[conda] torchinfo 1.8.0 pypi_0 pypi
[conda] torchsummary 1.5.1 pypi_0 pypi
[conda] torchvision 0.17.2 pypi_0 pypi
cc @albanD | closed | 2025-03-13T16:42:09Z | 2025-03-17T18:16:41Z | https://github.com/pytorch/pytorch/issues/149131 | [
"module: loss",
"triaged",
"module: python frontend"
] | connor-krill | 3 |
raphaelvallat/pingouin | pandas | 185 | Deprecate tail='one-sided' and rename to alternative | Since SciPy 1.6, several functions in [scipy.stats](https://docs.scipy.org/doc/scipy/reference/stats.html) accept `alternative="two-sided"` (or "greater" or "less"). To be consistent with these changes, I propose to:
1) In all relevant functions, rename the `tail` argument to `alternative` (similar to SciPy and R)
2) In all relevant functions, remove the option to pass `tail="one-sided"` (which currently would automatically select greater or less depending on the sign of the statistic). Instead, users must manually pass either "greater" or "less" to calculate a one-sided test. Therefore, `alternative` will only accept "two-sided", "greater" or "less", which is consistent with SciPy and R. | closed | 2021-07-18T20:49:26Z | 2021-08-13T18:02:31Z | https://github.com/raphaelvallat/pingouin/issues/185 | [
"deprecation :skull:"
] | raphaelvallat | 3 |
ultralytics/ultralytics | machine-learning | 19,077 | Don't know whether this is a bug. | ### Search before asking
- [x] I have searched the Ultralytics YOLO [issues](https://github.com/ultralytics/ultralytics/issues) and found no similar bug report.
### Ultralytics YOLO Component
_No response_
### Bug
I create my own custom dataset and have trained it with yolov8 successfully, but when I tried to predict the images with the best model that I got. An image in the test set was completely wrong, other images were predicted successfully, how does that happen? Here is the bug image in the test set.
The result image:
### Environment
Ultralytics YOLOv8.2.90 🚀 Python-3.11.9 torch-2.4.0+cu121 CUDA:0 (NVIDIA A100-PCIE-40GB, 40339MiB)
Setup complete ✅ (96 CPUs, 754.4 GB RAM, 401.0/438.9 GB disk)
OS Linux-5.15.0-113-generic-x86_64-with-glibc2.35
Environment Linux
Python 3.11.9
Install pip
RAM 754.35 GB
CPU Intel Xeon Gold 6248R 3.00GHz
CUDA 12.1
### Minimal Reproducible Example
```
from ultralytics import YOLO
# Load a model
model = YOLO("2_4/weights/best.pt")
# Run batched inference on a list of images
results = model(["./0007.jpg",]) # return a list of Results objects
#results = model(["./0007.jpg",]) # return a list of Results objects
# Process results list
for result in results:
boxes = result.boxes # Boxes object for bounding box outputs
masks = result.masks # Masks object for segmentation masks outputs
keypoints = result.keypoints # Keypoints object for pose outputs
probs = result.probs # Probs object for classification outputs
obb = result.obb # Oriented boxes object for OBB outputs
result.show() # display to screen
result.save(filename="result.jpg") # save to disk
```
### Additional
_No response_
### Are you willing to submit a PR?
- [ ] Yes I'd like to help by submitting a PR! | open | 2025-02-05T01:40:17Z | 2025-02-07T02:09:07Z | https://github.com/ultralytics/ultralytics/issues/19077 | [
"bug",
"detect"
] | Ilovecode93 | 3 |
kizniche/Mycodo | automation | 626 | Trigger failure | ## Mycodo Issue Report:
- Specific Mycodo Version: 7.2.1
#### Problem Description
Please list: All triggers are producing the same error. Will not function.
- what were you trying to do: Create a trigger
### Errors
2019-02-08 15:53:34,652 - mycodo.trigger_6745106f - INFO - Activated in 89.4 ms
2019-02-08 15:53:35,038 - mycodo.trigger_6745106f - ERROR - Run Error: trigger_function_actions() got an unexpected keyword argument 'last_measurement'
Traceback (most recent call last):
File "/var/mycodo-root/mycodo/controller_trigger.py", line 167, in run
self.check_triggers()
File "/var/mycodo-root/mycodo/controller_trigger.py", line 431, in check_triggers
edge=gpio_state)
TypeError: trigger_function_actions() got an unexpected keyword argument 'last_measurement'
### Steps to Reproduce the issue:
How can this issue be reproduced?
Create a trigger with a start point and wait for it to cycle/trigger.
### Additional Notes
Sorry for another bug report! No worries or rush on my end. | closed | 2019-02-08T23:59:40Z | 2019-02-09T00:33:51Z | https://github.com/kizniche/Mycodo/issues/626 | [] | ofernander | 2 |
docarray/docarray | pydantic | 1,025 | V2: rich display of `Document` and `DocumentArray` | Document:
- `doc.display_schema()` to display the Document's schema
- `doc.display()` to display the Document instance
- key, value (including type and shape)
- maybe display shorter id: `2184b5 ...` instead of `2184b53f977f566d72f72a6e706edb00 `
- if eg. list of 200 elements is part of the Document, don't show all 200 elements, keep max size of such display manageable.
DocumentArray:
- schema and length
- redundant fields for v2:
- `Homogenous Documents`
- `Common Attributes`, instead show the schema
- `Multimodal dataclass` | closed | 2023-01-17T10:35:46Z | 2023-01-25T13:23:50Z | https://github.com/docarray/docarray/issues/1025 | [] | anna-charlotte | 0 |
huggingface/diffusers | pytorch | 11,134 | Implement caching on LTX and WAN video models | `CacheConfig` is used to enable **FasterCache** and **PyramidAttentionBroadcast**
CacheConfig is present in Hunyuan, Mochi, Latte, Allegro, Cog transformer modules
but its not present in WAN or LTX transformer modules:
- `WanTransformer3DModel`
- `LTXVideoTransformer3DModel`
ask is to enable caching functionality for WAN and LTX models.
cc @a-r-r-o-w
| open | 2025-03-21T17:48:50Z | 2025-03-21T17:48:50Z | https://github.com/huggingface/diffusers/issues/11134 | [] | vladmandic | 0 |
huggingface/datasets | deep-learning | 7,220 | Custom features not compatible with special encoding/decoding logic | ### Describe the bug
It is possible to register custom features using datasets.features.features.register_feature (https://github.com/huggingface/datasets/pull/6727)
However such features are not compatible with Features.encode_example/decode_example if they require special encoding / decoding logic because encode_nested_example / decode_nested_example checks whether the feature is in a fixed list of encodable types:
https://github.com/huggingface/datasets/blob/16a121d7821a7691815a966270f577e2c503473f/src/datasets/features/features.py#L1349
This prevents the extensibility of features to complex cases
### Steps to reproduce the bug
```python
class ListOfStrs:
def encode_example(self, value):
if isinstance(value, str):
return [str]
else:
return value
feats = Features(strlist=ListOfStrs())
assert feats.encode_example({"strlist": "a"})["strlist"] = feats["strlist"].encode_example("a")}
```
### Expected behavior
Registered feature types should be encoded based on some property of the feature (e.g. requires_encoding)?
### Environment info
3.0.2 | open | 2024-10-11T19:20:11Z | 2024-11-08T15:10:58Z | https://github.com/huggingface/datasets/issues/7220 | [] | alex-hh | 2 |
autokey/autokey | automation | 4 | Error while installation | When I use command
`pip install autokey-py3`
It fails with message:
```
pip install autokey-py3
Downloading/unpacking autokey-py3
Downloading autokey-py3-0.93.2.tar.gz (130kB): 130kB downloaded
Running setup.py (path:/tmp/pip_build_root/autokey-py3/setup.py) egg_info for package autokey-py3
Traceback (most recent call last):
File "<string>", line 17, in <module>
File "/tmp/pip_build_root/autokey-py3/setup.py", line 24, in <module>
except FileNotFoundError: pass
NameError: name 'FileNotFoundError' is not defined
Complete output from command python setup.py egg_info:
Traceback (most recent call last):
File "<string>", line 17, in <module>
File "/tmp/pip_build_root/autokey-py3/setup.py", line 24, in <module>
except FileNotFoundError: pass
NameError: name 'FileNotFoundError' is not defined
```
| closed | 2014-12-06T18:34:34Z | 2014-12-06T21:31:45Z | https://github.com/autokey/autokey/issues/4 | [] | dvdvdmt | 1 |
RobertCraigie/prisma-client-py | asyncio | 258 | Improve partial model generation API for dynamic creation | ## Problem
<!-- A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] -->
A user on the Prisma Python discord showcased their partial model generator which is highly dynamic and makes use of internal features, we should improve support for this so that no internal features have to be used.
Their use case:
> build a scaffolding tool for generating fully typed RESTAPI endpoints that are glassboxed
Link to discussion: https://discord.com/channels/933860922039099444/933875073448804383/937759740061179935
## Suggested solution
<!-- A clear and concise description of what you want to happen. -->
Proposed API is still a work in progress.
| open | 2022-01-31T17:42:40Z | 2022-02-01T18:19:45Z | https://github.com/RobertCraigie/prisma-client-py/issues/258 | [
"kind/improvement",
"level/advanced",
"priority/medium"
] | RobertCraigie | 0 |
dgtlmoon/changedetection.io | web-scraping | 1,887 | [feature] Filter URLs that have errors | Be able to show listing only with URLs having errors.
It would be useful to debug and fix URLs that are having some error. At present it is taking a lot of time scrolling and finding URLs that have errors. We have a URL list that has over 5000 URLs.
Or alternatively, a button to recheck all URLs that have errors. | closed | 2023-10-23T12:05:32Z | 2023-10-23T15:55:53Z | https://github.com/dgtlmoon/changedetection.io/issues/1887 | [
"enhancement"
] | jgupta | 1 |
mwaskom/seaborn | matplotlib | 3,104 | stripplot edgecolor ignored | The `stripplot` function is ignoring my `edgecolor` choice. I'm using the Jupyter extension in VS Code, which defaults to the dark matplotlib style. Maybe that has something to do with it? An example is below, using seaborn 0.12.1
```
import seaborn as sns
tips = sns.load_dataset('tips')
sns.stripplot(
data=tips,
x='day',
y='total_bill',
edgecolor='black'
)
```
| closed | 2022-10-21T18:48:45Z | 2022-10-25T02:36:13Z | https://github.com/mwaskom/seaborn/issues/3104 | [
"mod:distributions",
"ux"
] | markmbaum | 4 |
deepinsight/insightface | pytorch | 2,656 | insightface.app的get函数返回空列表 | open | 2024-09-29T10:31:46Z | 2024-10-25T14:27:52Z | https://github.com/deepinsight/insightface/issues/2656 | [] | Qiuhao-Wu | 3 | |
OpenInterpreter/open-interpreter | python | 813 | 命令interpreter运行GTP4无法运行 | ### Describe the bug
C:\Users\16121\Desktop\open-interpreter-env_vars>interpreter
▌ Model set to gpt-4-1106-preview
Open Interpreter will require approval before running code.
Use interpreter -y to bypass this.
Press CTRL-C to exit.
> interpreter -y
Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new
LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True'.
You do not have access to gpt-4-1106-preview. Would you like to try gpt-3.5-turbo instead? (y/n)
### Reproduce
![Uploading QQ截图20231204152243.png…]()
### Expected behavior
### Screenshots
>
>
### Open Interpreter version
0.1.1
### Python version
3.11
### Operating System name and version
win11
### Additional context
| closed | 2023-12-04T07:24:38Z | 2023-12-04T15:30:49Z | https://github.com/OpenInterpreter/open-interpreter/issues/813 | [
"Bug"
] | af6464 | 0 |
fastapi-users/fastapi-users | fastapi | 1,229 | Missing type information when dependencies are specified using AsyncIterator | ## Describe the bug
The type information for classes such as AuthenticationBackend causes mypy errors when using a dependency whose return type is AsyncIterator rather than AsyncGenerator.
## To Reproduce
Consider a dependency:
```python
async def get_redis_strategy(
config: t.Annotated[Config, config_dependency],
redis: t.Annotated[Redis, redis_dependency], # type: ignore[type-arg]
) -> t.AsyncGenerator[RedisStrategy[User, UUID], None]:
yield RedisStrategy(redis, lifetime_seconds=config.SESSION_EXPIRY_SECONDS)
```
Which could also be written more succinctly as:
```python
async def get_redis_strategy(
config: t.Annotated[Config, config_dependency],
redis: t.Annotated[Redis, redis_dependency], # type: ignore[type-arg]
) -> t.AsyncIterator[RedisStrategy[User, UUID]]:
yield RedisStrategy(redis, lifetime_seconds=config.SESSION_EXPIRY_SECONDS)
```
In the latter case mypy reports a type issue, as DependencyCallable defined in fastapi_users/types.py does not allow for AsyncIterator (even though it's semantically the same in this case).
## Expected behavior
Using a dependency that returns an AsyncIterator as the `get_strategy` argument to `AuthenticationBackend` should not cause a mypy error.
## Configuration
- Python version : 3.11.3
- FastAPI version : 0.95.2
- FastAPI Users version : 11.0.0 | closed | 2023-06-16T17:54:09Z | 2023-06-23T08:38:31Z | https://github.com/fastapi-users/fastapi-users/issues/1229 | [
"enhancement",
"good first issue"
] | jameswilliams1 | 2 |
marimo-team/marimo | data-visualization | 3,302 | Autocomplete does not find suggestions in polars namespaces | ### Describe the bug
When using polars the marimo autocomplete is unable to find any suggestions for names that are within namespaces. For example, here is what the autocomplete shows for the `dt` namespace.
Here is what VS Code shows:
### Environment
{
"marimo": "0.10.7",
"OS": "Darwin",
"OS Version": "24.2.0",
"Processor": "arm",
"Python Version": "3.13.1",
"Binaries": {
"Browser": "--",
"Node": "v23.5.0"
},
"Dependencies": {
"click": "8.1.3",
"docutils": "0.21.2",
"itsdangerous": "2.2.0",
"jedi": "0.19.2",
"markdown": "3.7",
"narwhals": "1.19.1",
"packaging": "24.2",
"psutil": "6.1.1",
"pygments": "2.18.0",
"pymdown-extensions": "10.13",
"pyyaml": "6.0.2",
"ruff": "0.6.9",
"starlette": "0.42.0",
"tomlkit": "0.13.2",
"typing-extensions": "4.12.2",
"uvicorn": "0.34.0",
"websockets": "14.1"
},
"Optional Dependencies": {
"altair": "5.5.0",
"duckdb": "1.1.3",
"pandas": "2.2.3",
"polars": "1.17.1",
"pyarrow": "18.1.0"
}
}
### Code to reproduce
```python
import polars as pl
pl.col("col_name").dt
``` | open | 2024-12-27T21:03:15Z | 2025-01-03T10:17:17Z | https://github.com/marimo-team/marimo/issues/3302 | [
"bug",
"upstream"
] | kjgoodrick | 3 |
databricks/spark-sklearn | scikit-learn | 59 | AttributeError: 'function' object has no attribute '_input_kwargs' | I am using python 2.7, spark-2.2.0 with hadoop2.7 and sklearn 0.19.
I get the following error:
Traceback (most recent call last):
File "test.py", line 19, in <module>
km = KeyedEstimator(sklearnEstimator=LinearRegression(), yCol="y").fit(df)
File "C:\spark-2.2.0-bin-hadoop2.7\python\pyspark\\_\_init\_\_.py", line 104, in wrapper
return func(self, **kwargs)
File "C:\Python27\lib\site-packages\spark_sklearn\keyed_models.py", line 323, in \_\_init\_\_
kwargs = KeyedEstimator._inferredParams(sklearnEstimator, self.\_\_init\_\_._input_kwargs)
AttributeError: 'function' object has no attribute '_input_kwargs'
when I try to run the code:
km = KeyedEstimator(sklearnEstimator=LinearRegression(), yCol="y").fit(df)
From the origian example code available in the welcome page.
I also tried the Kmeans clustering, but it caused the same error.
I downloaded the source code and checked line 323 in keyed_models.py, which was:
kwargs = KeyedEstimator._inferredParams(sklearnEstimator, self._input_kwargs)
Please correct me if I'm wrong but the two, do not seem to match | closed | 2017-08-22T14:26:54Z | 2018-12-09T21:56:41Z | https://github.com/databricks/spark-sklearn/issues/59 | [] | sounakban | 1 |
ScottfreeLLC/AlphaPy | pandas | 28 | AttributeError: type object 'DataFrame' has no attribute 'from_items' | Winbash python3.7 running mflow:
Traceback (most recent call last):
File "/home/freefall/.local/bin/mflow", line 8, in <module>
sys.exit(main())
File "/home/d/.local/lib/python3.7/site-packages/alphapy/market_flow.py", line 430, in main
model = market_pipeline(model, market_specs)
File "/home/d/.local/lib/python3.7/site-packages/alphapy/market_flow.py", line 318, in market_pipeline
tfs = run_system(model, system, group, intraday)
File "/home/fredefall/.local/lib/python3.7/site-packages/alphapy/system.py", line 370, in run_system
tf = DataFrame.from_items(gtlist, orient='index', columns=Trade.states)
AttributeError: type object 'DataFrame' has no attribute 'from_items' | closed | 2020-03-01T02:59:07Z | 2020-03-03T01:57:19Z | https://github.com/ScottfreeLLC/AlphaPy/issues/28 | [] | thegamecat | 2 |
awesto/django-shop | django | 697 | Ordering is ignored for product.images.all() | Expected behavior: `product.images.all()` should be ordered based on the `order` column defined in the m2m-through model.
Actual behavior: No ordering is applied by default.
`ProductImage` model which is a m2m-through model between `Product` and `Image` has `order` column defined, but that column is not used when making ORM queries.
```python
>>> from myshop.all_models import *
>>> product1 = Product.objects.all()[0]
>>> product1.images.all().ordered
False
>>> str(product1.images.all().query)
'SELECT "filer_file"."id", "filer_file"."polymorphic_ctype_id", "filer_file"."folder_id", "filer_file"."file", "filer_file"."_file_size", "filer_file"."sha1", "filer_file"."has_all_mandatory_data", "filer_file"."original_filename", "filer_file"."name", "filer_file"."description", "filer_file"."owner_id", "filer_file"."uploaded_at", "filer_file"."modified_at", "filer_file"."is_public", "filer_image"."_height", "filer_image"."_width", "filer_image"."default_alt_text", "filer_image"."default_caption", "filer_image"."subject_location", "filer_image"."file_ptr_id", "filer_image"."date_taken", "filer_image"."author", "filer_image"."must_always_publish_author_credit", "filer_image"."must_always_publish_copyright" FROM "filer_image" INNER JOIN "myshop_productimage" ON ("filer_image"."file_ptr_id" = "myshop_productimage"."image_id") INNER JOIN "filer_file" ON ("filer_image"."file_ptr_id" = "filer_file"."id") WHERE "myshop_productimage"."product_id" = 1'
```
`product1.images.all().ordered` returns `False`. It's not clear to me why the ordering is not applied. It is specified in the `Meta` of the `ProductImage` model. | open | 2017-12-28T11:45:01Z | 2021-01-04T13:52:43Z | https://github.com/awesto/django-shop/issues/697 | [
"bug"
] | sniku | 2 |
InstaPy/InstaPy | automation | 5,885 | not sure whats going on |
## Expected Behavior
thought the code would execute
## Current Behavior
Traceback (most recent call last):
File "C:\Users\Dakot\AppData\Local\Programs\Python\Python39\Lib\site-packages\quickstart.py", line 13, in <module>
session = InstaPy(username='Dakota_cardone', password='dakota')
File "C:\Users\Dakot\AppData\Local\Programs\Python\Python39\Lib\site-packages\instapy\instapy.py", line 322, in __init__
self.browser, err_msg = set_selenium_local_session(
File "C:\Users\Dakot\AppData\Local\Programs\Python\Python39\Lib\site-packages\instapy\browser.py", line 132, in set_selenium_local_session
browser = webdriver.Firefox(
File "C:\Users\Dakot\AppData\Local\Programs\Python\Python39\Lib\site-packages\selenium\webdriver\firefox\webdriver.py", line 170, in __init__
RemoteWebDriver.__init__(
File "C:\Users\Dakot\AppData\Local\Programs\Python\Python39\Lib\site-packages\selenium\webdriver\remote\webdriver.py", line 157, in __init__
self.start_session(capabilities, browser_profile)
File "C:\Users\Dakot\AppData\Local\Programs\Python\Python39\Lib\site-packages\selenium\webdriver\remote\webdriver.py", line 252, in start_session
response = self.execute(Command.NEW_SESSION, parameters)
File "C:\Users\Dakot\AppData\Local\Programs\Python\Python39\Lib\site-packages\selenium\webdriver\remote\webdriver.py", line 321, in execute
self.error_handler.check_response(response)
File "C:\Users\Dakot\AppData\Local\Programs\Python\Python39\Lib\site-packages\selenium\webdriver\remote\errorhandler.py", line 242, in check_response
raise exception_class(message, screen, stacktrace)
selenium.common.exceptions.SessionNotCreatedException: Message: Expected browser binary location, but unable to find binary in default location, no 'moz:firefoxOptions.binary' capability provided, and no binary flag set on the command line
## Possible Solution (optional)
## InstaPy configuration
| closed | 2020-11-12T03:22:27Z | 2020-11-12T04:30:13Z | https://github.com/InstaPy/InstaPy/issues/5885 | [] | VoidNebula13 | 0 |
waditu/tushare | pandas | 906 | 停复牌数据不准确 | 002506.SZ在20140429到20150812期间都是停牌的，停复牌数据没有体现出来
000950.SZ在20170426到20180828期间都是停牌的，停复牌数据没有体现出来
目前获取到的停复牌信息数据(suspend接口)有点奇怪，有些有resume_date，有些没有，让人觉得比较困惑，能否调整一下，有两种方案：1、所有停复牌区间都记suspend_date和resume_date，没有resume_date说明依旧处于停牌中；2、针对每个停牌日，都记录一条数据，不记录resume_date。十分感谢。 | closed | 2019-01-24T08:18:21Z | 2019-01-24T14:48:29Z | https://github.com/waditu/tushare/issues/906 | [] | wangyaochong | 1 |
lexiforest/curl_cffi | web-scraping | 181 | Support `base_url` when initializing sessions |
**Describe alternatives you've considered**]
https://www.python-httpx.org/advanced/#other-client-only-configuration-options
| closed | 2023-12-18T05:18:26Z | 2024-03-27T16:09:53Z | https://github.com/lexiforest/curl_cffi/issues/181 | [
"enhancement",
"good first issue"
] | T-256 | 2 |
tinyfish-io/agentql | web-scraping | 108 | Recommended deployment pipeline for self-hosting | At the moment it appears the REST API / cloud service is limited to scraping single pages (doesn't handle pagination, cookies etc.).
Given this, what is the team's recommended deployment pipeline for self-hosting?
FastAPI + AgentQL + Playwright Stealth seems like a good combination.
Are there any recommended proxy services in addition?
Super impressed by the Python SDK so far - just looking to get this into production as soon as. | open | 2024-12-20T17:30:29Z | 2025-01-27T09:51:34Z | https://github.com/tinyfish-io/agentql/issues/108 | [] | Ches-ctrl | 1 |
neuml/txtai | nlp | 750 | Translation: AttributeError: 'ModelInfo' object has no attribute 'modelId' | Translation stopped working for me and I'm not sure what changed.
```python
from txtai.pipeline import Translation
# Create and run pipeline
translate = Translation()
translate("This is a test translation into Spanish", "es")
```
```
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[17], line 4
1 from txtai.pipeline import Translation
3 # Create and run pipeline
----> 4 translate = Translation()
5 translate("This is a test translation into Spanish", "es")
File ~/Development/notebooks/.venv/lib/python3.10/site-packages/txtai/pipeline/text/translation.py:54, in Translation.__init__(self, path, quantize, gpu, batch, langdetect, findmodels)
52 # Language models
53 self.models = {}
---> 54 self.ids = self.modelids()
File ~/Development/notebooks/.venv/lib/python3.10/site-packages/txtai/pipeline/text/translation.py:115, in Translation.modelids(self)
107 def modelids(self):
108 """
109 Runs a query to get a list of available language models from the Hugging Face API.
110
111 Returns:
112 list of source-target language model ids
113 """
--> 115 ids = [x.modelId for x in HfApi().list_models(author="Helsinki-NLP")] if self.findmodels else []
116 return set(ids)
File ~/Development/notebooks/.venv/lib/python3.10/site-packages/txtai/pipeline/text/translation.py:115, in <listcomp>(.0)
107 def modelids(self):
108 """
109 Runs a query to get a list of available language models from the Hugging Face API.
110
111 Returns:
112 list of source-target language model ids
113 """
--> 115 ids = [x.modelId for x in HfApi().list_models(author="Helsinki-NLP")] if self.findmodels else []
116 return set(ids)
AttributeError: 'ModelInfo' object has no attribute 'modelId'
```
```
> pip freeze | grep -e huggingface -e txtai
huggingface-hub==0.24.0
txtai==7.3.0
```
It looks like the last version of huggingface-hub that used `modelId` was [v0.18 ](https://huggingface.co/docs/huggingface_hub/v0.18.0.rc0/en/package_reference/hf_api#huggingface_hub.hf_api.ModelInfo)
It isn't available in [v0.19](https://huggingface.co/docs/huggingface_hub/v0.19.3/en/package_reference/hf_api#huggingface_hub.hf_api.ModelInfo) or [later](https://huggingface.co/docs/huggingface_hub/v0.24.0/en/package_reference/hf_api#huggingface_hub.hf_api.ModelInfo)
| closed | 2024-07-22T17:03:29Z | 2024-07-23T08:59:12Z | https://github.com/neuml/txtai/issues/750 | [
"bug"
] | adieyal | 5 |
piskvorky/gensim | machine-learning | 2,735 | Word2vec: loss tally maxes at 134217728.0 due to float32 limited-precision |
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#### Cumulative loss of word2vec maxes out at 134217728.0
I'm training a word2vec model with 2,793,404 sentences / 33,499,912 words, vocabulary size 162,253 (words with at least 5 occurrences).
Expected behaviour: with `compute_loss=True`, gensim's word2vec should compute the loss in the expected way.
Actual behaviour: the cumulative loss seems to be maxing out at `134217728.0`:
Building vocab...
Vocab done. Training model for 120 epochs, with 16 workers...
Loss after epoch 1: 16162246.0 / cumulative loss: 16162246.0
Loss after epoch 2: 11594642.0 / cumulative loss: 27756888.0
[ - snip - ]
Loss after epoch 110: 570688.0 / cumulative loss: 133002056.0
Loss after epoch 111: 564448.0 / cumulative loss: 133566504.0
Loss after epoch 112: 557848.0 / cumulative loss: 134124352.0
Loss after epoch 113: 93376.0 / cumulative loss: 134217728.0
Loss after epoch 114: 0.0 / cumulative loss: 134217728.0
Loss after epoch 115: 0.0 / cumulative loss: 134217728.0
And it stays at `134217728.0` thereafter. The value `134217728.0` is of course exactly `128*1024*1024`, which does not seem like a coincidence.
#### Steps to reproduce
My code is as follows:
class MyLossCalculator(CallbackAny2Vec):
def __init__(self):
self.epoch = 1
self.losses = []
self.cumu_losses = []
def on_epoch_end(self, model):
cumu_loss = model.get_latest_training_loss()
loss = cumu_loss if self.epoch <= 1 else cumu_loss - self.cumu_losses[-1]
print(f"Loss after epoch {self.epoch}: {loss} / cumulative loss: {cumu_loss}")
self.epoch += 1
self.losses.append(loss)
self.cumu_losses.append(cumu_loss)
def train_and_check(my_sentences, my_epochs, my_workers=8):
print(f"Building vocab...")
my_model: Word2Vec = Word2Vec(sg=1, compute_loss=True, workers=my_workers)
my_model.build_vocab(my_sentences)
print(f"Vocab done. Training model for {my_epochs} epochs, with {my_workers} workers...")
loss_calc = MyLossCalculator()
trained_word_count, raw_word_count = my_model.train(my_sentences, total_examples=my_model.corpus_count, compute_loss=True,
epochs=my_epochs, callbacks=[loss_calc])
loss = loss_calc.losses[-1]
print(trained_word_count, raw_word_count, loss)
loss_df = pd.DataFrame({"training loss": loss_calc.losses})
loss_df.plot(color="blue")
# print(f"Calculating accuracy...")
# acc, details = my_model.wv.evaluate_word_analogies(questions_file, case_insensitive=True)
# print(acc)
return loss_calc, my_model
The data is a news article corpus in Finnish; I'm not at liberty to share all of it (and anyway it's a bit big), but it looks like one would expect:
[7]: df.head(2)
[7]: [Row(file_and_id='data_in_json/2018/04/0001.json.gz%%3-10169118', index_in_file='853', headline='Parainen pyristelee pois lastensuojelun kriisistä: irtisanoutuneiden tilalle houkutellaan uusia sosiaalityöntekijöitä paremmilla työeduilla', publication_date='2018-04-20 11:59:35+03:00', publication_year='2018', publication_month='04', sentence='hän tiesi minkälaiseen tilanteeseen tulee', lemmatised_sentence='hän tietää minkälainen tilanne tulla', source='yle', rnd=8.436637410902392e-08),
Row(file_and_id='data_in_xml/arkistosiirto2018.zip%%arkistosiirto2018/102054668.xml', index_in_file=None, headline='*** Tiedote/SDP: Medialle tiedoksi: SDP:n puheenjohtaja Antti Rinteen puhe puoluevaltuuston kokouksessa ***', publication_date='2018-04-21T12:51:44', publication_year='2018', publication_month='04', sentence='me haluamme jättää hallitukselle välikysymyksen siitä miksi nuorten ihmisten tulevaisuuden uskoa halutaan horjuttaa miksi epävarmuutta ja näköalattomuutta sekä pelkoa tulevaisuuden suhteen halutaan lisätä', lemmatised_sentence='me haluta jättää hallitus välikysymys se miksi nuori ihminen tulevaisuus usko haluta horjuttaa miksi epävarmuus ja näköalattomuus sekä pelko tulevaisuus suhteen haluta lisätä', source='stt', rnd=8.547760445010155e-07)]
sentences = list(map(lambda r: r["lemmatised_sentence"].split(" "), df.select("lemmatised_sentence").collect()))
[18]: sentences[0]
[18]: ['hän', 'tietää', 'minkälainen', 'tilanne', 'tulla']
#### Versions
The output of:
```python
import platform; print(platform.platform())
import sys; print("Python", sys.version)
import numpy; print("NumPy", numpy.__version__)
import scipy; print("SciPy", scipy.__version__)
import gensim; print("gensim", gensim.__version__)
from gensim.models import word2vec;print("FAST_VERSION", word2vec.FAST_VERSION)
```
is:
Windows-10-10.0.18362-SP0
Python 3.7.3 | packaged by conda-forge | (default, Jul 1 2019, 22:01:29) [MSC v.1900 64 bit (AMD64)]
NumPy 1.17.3
SciPy 1.3.1
gensim 3.8.1
FAST_VERSION 1
Finally, I'm not the only one who has encountered this issue. I found the following related links:
https://groups.google.com/forum/#!topic/gensim/IH5-nWoR_ZI
https://stackoverflow.com/questions/59823688/gensim-word2vec-model-loss-becomes-0-after-few-epochs
I'm not sure if this is only a display issue and the training continues normally even after the cumulative loss reaches its "maximum", or if the training in fact stops at that point. The trained word vectors seem reasonably ok, judging by `my_model.wv.evaluate_word_analogies()`, though they do need more training than this.
| open | 2020-01-26T13:28:16Z | 2023-09-28T19:12:03Z | https://github.com/piskvorky/gensim/issues/2735 | [
"bug",
"difficulty medium"
] | tsaastam | 24 |
albumentations-team/albumentations | machine-learning | 2,104 | [Add transform] Add RandomPlasmaContrast | https://kornia.readthedocs.io/en/latest/augmentation.module.html#kornia.augmentation.RandomPlasmaContrast | closed | 2024-11-08T15:56:44Z | 2024-11-18T03:57:20Z | https://github.com/albumentations-team/albumentations/issues/2104 | [
"enhancement"
] | ternaus | 1 |
babysor/MockingBird | pytorch | 837 | 新版本模型训练问题与解决方法 | 新版本主目录里没有synthesizer_train.py，查找了一下发现...\control\cli里面有synthesizer_train.py文件，但是运行称缺一个models的依赖，pip安装models提示需要base依赖，遂安装base，提示gbk编码器错误，按照网上教程为base的setup.py第21行指定编码器为utf-8依旧报错，遂放弃使用命令行进行训练，改用web中自带的模型训练功能进行训练，正常，然后关闭，再启动命令行训练，即可正常使用。 | open | 2023-02-24T03:36:31Z | 2023-05-16T03:08:38Z | https://github.com/babysor/MockingBird/issues/837 | [] | YIZXIY | 1 |
PrefectHQ/prefect | automation | 17,127 | Improve UX for flow with parameterised schedules | ### Describe the current behavior
Prefect 3.2 added the option to specify parameters in the schedule but it's hard to see in the UI which schedule a flow run belongs to. See:
Currently, the only way to see on the flows page what schedule triggered the flow run is to click on the parameters.
### Describe the proposed behavior
As a first improvement, I would propose adding the schedule slug with the flow run. This way the user can directly identify which schedule triggered a certain flow run. Further improvements could be to make it possible to filter based on the schedule slug to easily find flow runs with specific parameters.
### Example Use
_No response_
### Additional context
The reason for asking for this feature is that these parameterized schedules can be used for a ML pipeline with different parameters/experiments. Being able to immediately spot which experiment we are looking at will speed up the user experience.
Before parameterized schedules existed, I used a single flow function that had many deployments depending on the parameters. While this is impractical because it resulted in many deployments, at least Prefect makes it easy to search based on the deployment name (and tags). Ideally, schedules would be upgraded to a similar status with search functionality and filtering in the flow run page. | open | 2025-02-13T09:10:38Z | 2025-02-19T17:18:10Z | https://github.com/PrefectHQ/prefect/issues/17127 | [
"enhancement"
] | mvdb-enspi | 1 |
lepture/authlib | flask | 176 | Decoding a JWS token with ES256 doesn't work | **Describe the bug**
Hi!
I'm trying to implement an OAuth2 server with authlib and I found a bug in the library with ES256. I was trying to decode a JWS token signed with ES256 but the library has raised an exception.
The generation of a JWT with ES256 works, but not the decoding.
Here it's the small piece of code that raises an exception :
```
def gen_refresh_token(self, client, grant_type, user, scope):
jws = JsonWebSignature(algorithms=JWS_ALGORITHMS)
header = {'alg': 'ES256'}
date = datetime.utcnow()
payload = {
'client_id': client.get_client_id(),
'iat': int(date.timestamp()),
'user_id': user["id"],
'scope': scope,
'exp': 604800
}
try:
key = open("my_ec_key.pem", 'r').read()
s = jws.serialize_compact(header, json.dumps(payload), key)
except Exception as e:
logger.exception('JWS exception', e)
return s.decode("utf-8")
...
class RefreshTokenGrant(grants.RefreshTokenGrant):
INCLUDE_NEW_REFRESH_TOKEN = True
def authenticate_refresh_token(self, refresh_token):
jws = JsonWebSignature(algorithms=JWS_ALGORITHMS)
try:
key = open("my_ec_pub.pem", 'r').read()
jws_obj = jws.deserialize_compact(refresh_token, key)
...
except Exception as e:
logger.exception('JWS exception', e)
```
And the traceback :
```
Traceback (most recent call last):
File "/mnt/d/documents/exo1/src/exo1/rest/flask/oauth2.py", line 64, in authenticate_refresh_token
jws_obj = jws.deserialize_compact(refresh_token, key)
File "/home/yohann/.local/lib/python3.6/site-packages/authlib/jose/rfc7515/jws.py", line 115, in deserialize_compact
self._algorithms, jws_header, payload, key)
File "/home/yohann/.local/lib/python3.6/site-packages/authlib/jose/util.py", line 14, in prepare_algorithm_key
key = algorithm.prepare_public_key(key)
File "/home/yohann/.local/lib/python3.6/site-packages/authlib/jose/rfc7518/_backends/_key_cryptography.py", line 42, in prepare_public_key
if key.startswith(b'ecdsa-sha2-'):
TypeError: startswith first arg must be str or a tuple of str, not bytes
```
**To Reproduce**
I put a small example of the code above.
**Expected behavior**
I should get the content of the token.
**Environment:**
- OS: Windows Subsystem for Linux
- Python Version: 3.6.8
- Authlib Version: 0.13.0
**Additional context**
I found a patch for my use case. You have to edit the file in :
authlib/jose/rfc7518/_backends/_key_cryptography.py
In the class ECKey, the method prepare_public_key doesn't convert the key to bytes. I did the following patch :
```
def prepare_public_key(self, key):
if isinstance(key, EllipticCurvePublicKey):
return key
key = to_bytes(key)
if key.startswith(b'ecdsa-sha2-'):
return load_ssh_public_key(key, backend=default_backend())
else:
return load_pem_public_key(key, backend=default_backend())
```
Add any other context about the problem here.
| closed | 2019-12-30T09:39:09Z | 2020-02-11T11:00:10Z | https://github.com/lepture/authlib/issues/176 | [
"bug"
] | fenix01 | 5 |
mitmproxy/pdoc | api | 296 | Error when parsing reStructuredText when its located in between sections | #### Problem Description
Error when parsing reStructuredText when its located in between sections as it detects it as if it is part of the section
#### Code:
```py
def testing():
"""This is a test docstring.
Parameters
----------
testing_param: str
Some parameter.
.. warning::
Warning for this parameter.
.. note::
This is really important, but it will be rendered incorrectly.
"""
```
#### Render:
*Generated with `pdoc <file> -d numpy`*
#### System Information
```
pdoc: 7.4.0
Python: 3.8.10
Platform: Linux-5.13.1-051301-generic-x86_64-with-glibc2.29
```
| closed | 2021-08-21T13:26:52Z | 2021-08-22T18:06:35Z | https://github.com/mitmproxy/pdoc/issues/296 | [
"wontfix"
] | davfsa | 3 |
Josh-XT/AGiXT | automation | 1,380 | Add Commands to Convert Markdown to docx, xlsx, and pdf | We need to add commands to AGiXT that allow users to convert markdown files into docx, xlsx, and pdf formats. This feature will be useful for generating reports, documentation, and other formatted outputs directly from markdown content. The commands should handle the conversion process efficiently and support customization options for formatting and styling. | closed | 2025-01-20T18:05:10Z | 2025-03-16T21:43:55Z | https://github.com/Josh-XT/AGiXT/issues/1380 | [
"20K Bounty"
] | Josh-XT | 1 |
sinaptik-ai/pandas-ai | data-science | 1,360 | Unable to analyze the DataFrame when it contains data in list format. | ### System Info
OS version: MacOS Sonoma
Python version: 3.12.5
The current version of `pandasai` being used: 2.2.14
### 🐛 Describe the bug
I tried using pandasai `Agent` to analyze my data in DataFrame format, but I found that if the DataFrame contains data in list format, the analysis fails, and there are no error logs in `pandasai.log`. The following is a simple example code:
```python
import pandas as pd
data = {
'Employee_ID': [101, 102, 103, 104],
'Employee_Name': ['Alice', 'Bob', 'Charlie', 'Diana'],
'Projects': [['Project A', 'Project B'], ['Project C'], ['Project D', 'Project E', 'Project F'], ['Project G']],
'Salary': [70000, 80000, 75000, 90000]
}
df = pd.DataFrame(data)
agent = Agent(
dfs=df,
config=Config(llm=OpenAI(api_token=os.getenv("OAI_API_KEY"), model="gpt-4o"))
)
print(agent.chat('Tell me the average salary of the employees'))
```
Here is the output:
```python
"Unfortunately, I was not able to get your answers, because of the following error:\n\nunhashable type: 'list'\n"
``` | closed | 2024-09-08T06:30:09Z | 2024-12-15T16:08:08Z | https://github.com/sinaptik-ai/pandas-ai/issues/1360 | [
"bug"
] | ReeveWu | 1 |
postmanlabs/httpbin | api | 334 | Random sub-domains no longer open the website | Up until yesterday, any random sub-domain would open the website, i.e. https://dsaf.httpbin.org/ would open the same page as https://httpbin.org/ (not redirected), just like https://eu.httpbin.org/ still does now.
Since yesterday, it gives a "This site can’t be reached" error (DNS_PROBE_FINISHED_NXDOMAIN) for a random sub-domain. | closed | 2017-03-17T09:03:39Z | 2018-04-26T17:51:12Z | https://github.com/postmanlabs/httpbin/issues/334 | [] | macroshadow | 2 |
rougier/numpy-100 | numpy | 163 | An alternative solution for Q.82 | > 82. Compute a matrix rank (★★★)
> hint: np.linalg.svd
>
> \# Author: Stefan van der Walt
>
> Z = np.random.uniform(0,1,(10,10))
> U, S, V = np.linalg.svd(Z) # Singular Value Decomposition
> rank = np.sum(S > 1e-10)
> print(rank)
>
`numpy.linalg.matrix_rank` [Doc](https://numpy.org/doc/stable/reference/generated/numpy.linalg.matrix_rank.html?highlight=rank#numpy.linalg.matrix_rank) provides an alternative way to compute matrix rank.
The alternative solution will be:
```python3
from numpy.linalg import matrix_rank
Z = np.random.uniform(0,1,(10,10))
print(matrix_rank(Z))
``` | open | 2021-12-11T13:50:23Z | 2021-12-15T18:31:13Z | https://github.com/rougier/numpy-100/issues/163 | [] | iamyifan | 3 |
pallets-eco/flask-sqlalchemy | flask | 739 | create_engine() missing 1 required positional argument: 'engine_opts | I'm trying to use `db.create_engine` to connect to a second database in a view. My app was working yesterday, but after I tried it on a new machine with a fresh virtualenv, it's no longer working. I think this is due to the changes in #684.
```python
x = 'postgres://*****'
engine = db.create_engine(x)
```
```pytb
create_engine() missing 1 required positional argument: 'engine_opts'
``` | closed | 2019-05-19T19:26:53Z | 2020-12-05T20:21:51Z | https://github.com/pallets-eco/flask-sqlalchemy/issues/739 | [] | jjRick | 5 |
healthchecks/healthchecks | django | 310 | Bug: Deprecated function call breaking `manage.py collectstatic --noinput` | It seems like django deprecated `admin_static` which is causing the following exception when running `manage.py collectstatic --noinput` command.
Is there a way to resolve this exception??
[Some posts suggest](https://stackoverflow.com/questions/59148185/django-error-cannot-import-name-removedindjango30warning) uninstalling and reinstalling django which I tried with no luck.
```
Traceback (most recent call last):
File "/usr/lib/python3.7/site-packages/django/template/utils.py", line 66, in __getitem__
return self._engines[alias]
KeyError: 'django'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/lib/python3.7/site-packages/django/template/backends/django.py", line 121, in get_package_libraries
module = import_module(entry[1])
File "/usr/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1006, in _gcd_import
File "<frozen importlib._bootstrap>", line 983, in _find_and_load
File "<frozen importlib._bootstrap>", line 967, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 677, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 728, in exec_module
File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
File "/usr/lib/python3.7/site-packages/django/contrib/admin/templatetags/admin_static.py", line 5, in <module>
from django.utils.deprecation import RemovedInDjango30Warning
ImportError: cannot import name 'RemovedInDjango30Warning' from 'django.utils.deprecation' (/usr/lib/python3.7/site-packages/django/utils/deprecation.py)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "manage.py", line 10, in <module>
execute_from_command_line(sys.argv)
File "/usr/lib/python3.7/site-packages/django/core/management/__init__.py", line 401, in execute_from_command_line
utility.execute()
File "/usr/lib/python3.7/site-packages/django/core/management/__init__.py", line 395, in execute
self.fetch_command(subcommand).run_from_argv(self.argv)
File "/usr/lib/python3.7/site-packages/django/core/management/base.py", line 328, in run_from_argv
self.execute(*args, **cmd_options)
File "/usr/lib/python3.7/site-packages/django/core/management/base.py", line 369, in execute
output = self.handle(*args, **options)
File "/usr/lib/python3.7/site-packages/compressor/management/commands/compress.py", line 277, in handle
self.handle_inner(**options)
File "/usr/lib/python3.7/site-packages/compressor/management/commands/compress.py", line 300, in handle_inner
offline_manifest, block_count, results = self.compress(engine, extensions, verbosity, follow_links, log)
File "/usr/lib/python3.7/site-packages/compressor/management/commands/compress.py", line 100, in compress
if not self.get_loaders():
File "/usr/lib/python3.7/site-packages/compressor/management/commands/compress.py", line 50, in get_loaders
for e in engines.all():
File "/usr/lib/python3.7/site-packages/django/template/utils.py", line 90, in all
return [self[alias] for alias in self]
File "/usr/lib/python3.7/site-packages/django/template/utils.py", line 90, in <listcomp>
return [self[alias] for alias in self]
File "/usr/lib/python3.7/site-packages/django/template/utils.py", line 81, in __getitem__
engine = engine_cls(params)
File "/usr/lib/python3.7/site-packages/django/template/backends/django.py", line 25, in __init__
options['libraries'] = self.get_templatetag_libraries(libraries)
File "/usr/lib/python3.7/site-packages/django/template/backends/django.py", line 43, in get_templatetag_libraries
libraries = get_installed_libraries()
File "/usr/lib/python3.7/site-packages/django/template/backends/django.py", line 108, in get_installed_libraries
for name in get_package_libraries(pkg):
File "/usr/lib/python3.7/site-packages/django/template/backends/django.py", line 125, in get_package_libraries
"trying to load '%s': %s" % (entry[1], e)
django.template.library.InvalidTemplateLibrary: Invalid template library specified. ImportError raised when trying to load 'django.contrib.admin.templatetags.admin_static': cannot import name 'RemovedInDjango30Warning' from 'django.utils.deprecation' (/usr/lib/python3.7/site-packages/django/utils/deprecation.py)
```
Reference: https://django.readthedocs.io/en/2.2.x/releases/2.1.html#id2 | closed | 2019-12-03T16:41:29Z | 2019-12-05T15:55:29Z | https://github.com/healthchecks/healthchecks/issues/310 | [] | gganeshan | 13 |
deezer/spleeter | tensorflow | 564 | How get output as bytes or assign to variable from Python API | <!-- Please respect the title [Discussion] tag. -->
How to get the output as bytes or assign to a variable from Python API | open | 2021-01-22T08:35:56Z | 2022-02-15T04:28:31Z | https://github.com/deezer/spleeter/issues/564 | [
"question"
] | pranavansp | 1 |
seleniumbase/SeleniumBase | pytest | 3,381 | uc_gui_click_captcha fails to click cloudflare checkbox | Hello, I encountered the same problem as a guy in this issue https://github.com/seleniumbase/SeleniumBase/issues/3345
, I tried to update to the latest version, unfortunately it did not help me, my project is quite large, unfortunately, in what format would it be more convenient for you if I provided it to you? I also attach a video with the problem, in some areas of the site, if it was used with.
sb.cdp.minimize()
sb.cdp.medimize()
click occurs at
the bottom edge of the checkbox is literally pixel by pixel, suitable for clicking, but not in all cases.I have attached a case in which the click does not occur to this message. I apologize for any grammatical errors in this message, English is not my native language, and also thank you in advance for your answer
| closed | 2025-01-01T17:01:38Z | 2025-01-01T18:35:17Z | https://github.com/seleniumbase/SeleniumBase/issues/3381 | [
"invalid usage",
"can't reproduce",
"UC Mode / CDP Mode"
] | mkuchuman | 6 |
eriklindernoren/ML-From-Scratch | deep-learning | 111 | No module named 'mlfromscratch.utils.loss_functions' | Traceback (most recent call last):
File "C:\G\ML-From-Scratch\mlfromscratch\examples\gradient_boosting_regressor.py", line 9, in <module>
from mlfromscratch.utils.loss_functions import SquareLoss
ModuleNotFoundError: No module named 'mlfromscratch.utils.loss_functions' | open | 2024-11-20T08:51:03Z | 2024-11-20T08:51:03Z | https://github.com/eriklindernoren/ML-From-Scratch/issues/111 | [] | LeiYangGH | 0 |
PokeAPI/pokeapi | graphql | 693 | Honey tree encounters | In Generation IV, diamond pearl and platinum, you can encounter certain Pokemon only through honey trees: https://bulbapedia.bulbagarden.net/wiki/Honey_Tree
The API currently does not include these encounters, so burmy and wormadam have no encounters in the game they were introduced in. Munchlax is also listed as impossible to encounter.
My current project uses this API to calculate which games are required for which Pokemon. If this feature were not added, then I would have to manually override the API's calls for these Pokemon. | open | 2022-02-19T19:37:14Z | 2022-02-19T19:37:14Z | https://github.com/PokeAPI/pokeapi/issues/693 | [] | Hyreon | 0 |
3b1b/manim | python | 1,683 | DEBUG The error could be: `Undefined control sequence.` tex_file_writing.py:94 | ### Describe the error
<!-- A clear and concise description of what you want to make. -->
Unable to render `LaTex` file. And prior to this issue, the problem was [this](https://github.com/3b1b/manim/issues/1661), but I manged to installed the `texlive-full` on my ubuntu 20.04. and still unable to render tex
### Code and Error
**Code**:
[My code was copied from here](https://docs.manim.org.cn/getting_started/example_scenes.html#updatersexample)
**Error**:
```
INFO If you want to create a local configuration file, you can config.py:232
create a file named `custom_config.yml`, or run `manimgl
--config`
Writing "\lim_{n \to \infty} \left\lfloor \sqrt{\frac{1}{n !} \mathrm{e}^{n} a_{n} + b_{n}^{p}} \otimes \sqrt[n]{\sum_{m = 0}^{n^{2}} \tilde{c}_{m \cdot n}^{b_{n}^{p} \cos \left( \the ERROR LaTeX Error! Not a worry, it happens to the best tex_file_writing.py:90
of us.
DEBUG The error could be: `Undefined control sequence.` tex_file_writing.py:94
```
The .tex file was generated by manimlib, and here is the log
```
This is TeX, Version 3.14159265 (TeX Live 2019/Debian) (preloaded format=tex)
(./Tex/e4d7da810f12ab27.tex
! Undefined control sequence.
l.1 \documentclass
[preview]{standalone}
?
! Undefined control sequence.
l.3 \usepackage
[english]{babel}
?
! Undefined control sequence.
l.4 \usepackage
[utf8]{inputenc}
?
! Undefined control sequence.
l.5 \usepackage
[T1]{fontenc}
```
### Environment
**OS System**:
Ubuntu 20.04
**manim version**: master <!-- make sure you are using the latest version of master branch -->
**python version**:
```
pdfTeX 3.14159265-2.6-1.40.20 (TeX Live 2019/Debian)
kpathsea version 6.3.1
Copyright 2019 Han The Thanh (pdfTeX) et al.
There is NO warranty. Redistribution of this software is
covered by the terms of both the pdfTeX copyright and
the Lesser GNU General Public License.
For more information about these matters, see the file
named COPYING and the pdfTeX source.
Primary author of pdfTeX: Han The Thanh (pdfTeX) et al.
Compiled with libpng 1.6.37; using libpng 1.6.37
Compiled with zlib 1.2.11; using zlib 1.2.11
Compiled with xpdf version 4.01
``` | closed | 2021-11-17T16:05:43Z | 2021-11-18T17:50:00Z | https://github.com/3b1b/manim/issues/1683 | [] | gxshao | 2 |
Skyvern-AI/skyvern | automation | 1,753 | Can I change AI Mode to others，such deepseek R1 | Find only can configure open ai api key, could we change to other LLM model, such as Deepseek R1? | closed | 2025-02-10T06:31:10Z | 2025-02-10T12:17:11Z | https://github.com/Skyvern-AI/skyvern/issues/1753 | [] | zhenzhen-wang | 1 |
NVIDIA/pix2pixHD | computer-vision | 95 | Strange patterns in the output image | In some of my output images, there are strange patterns occurred like the pics below:
I can't figure out why those things came out upon my output images. Do anybody know the reason?
In addition, I think my loss curves are also strange:
 | open | 2019-01-15T03:08:16Z | 2021-01-07T08:36:05Z | https://github.com/NVIDIA/pix2pixHD/issues/95 | [] | cfanyyx | 6 |
1313e/CMasher | matplotlib | 26 | Instructions for R/IDL/Matlab/DS9/etc. users | Would be good to have instructions on how `R`/`IDL`/`Matlab`/etc users might be able to use the `cmasher` colourmaps.
Similarly, for certain application, this might be a good idea as well.
Perhaps in the README or in the online documentation.
- [X] R (3ce67f9)
- [ ] IDL
- [ ] MATLAB
- [ ] DS9 | open | 2020-10-20T04:45:33Z | 2023-04-12T23:36:30Z | https://github.com/1313e/CMasher/issues/26 | [
"documentation",
"help wanted"
] | manodeep | 6 |
flasgger/flasgger | rest-api | 257 | Unable to load inline defintions. |
`assets with pagination.
---
tags:
- asset
parameters:
- name: authorization
in: header
description: Please add the authentication token to here.
required: true
type: string
- name: search
in: query
description: This value will be searched in the product number, product description, and barcode fields.
type: string
- name: barcode
in: query
description: Assets that have this barcode value will be returned.
type: string
- name: external_resource_url
in: query
description: Assets that have this external resource url will be returned.
type: string
- name: product_group
in: query
description: Assets that are included this product group will be returned.
type: string
- name: division
in: query
description: Assets that are located this division will be returned.
type: string
- name: status_code
in: query
description: Assets that are in this status code will be returned.
type: string
- name: page
in: query
description: The page number that you want to recieve.
type: integer
- name: per_page
in: query
description: The resource count that you want to see per page.
type: integer
responses:
200:
description: If the request is valid, the response will have a status of '200' and a body that includes the list of assets.
schema:
type: object
properties:
assets:
type: array
items:
$ref: '#/definitions/Asset'
pages:
type: object
$ref: '#/definitions/Page'
examples:
responses:
{
"assets": [
{
"_link": {
"fileAttachments": "http://localhost:8000/assets/MR/file_attachments/",
"groupRates": "http://localhost:8000/assets/MR/group_rates/",
"inspectionForms": "http://localhost:8000/assets/MR/inspection_form/",
"locations": "http://localhost:8000/assets/MR/locations/",
"meterHistories": "http://localhost:8000/assets/MR/meter_histories/",
"productRates": "http://localhost:8000/assets/MR/product_rates/",
"tags": "http://localhost:8000/assets/MR/tags/"
},
"averageCostEach": 0,
"barcodes": [
"BWC90001"
],
"bulkItem": "Y",
"cycleBill": "Y",
"dateOfManufacture": "2017-07-07",
"description": "MISC RENTAL PRODUCT",
"fuelTypes": [],
"inventory": "Y",
"listPrice": 0,
"make": "",
"markupPercentage": 0,
"currentMeter": 0,
"meterType": "N",
"modelNumber": "",
"multipleTags": "Y",
"notes": "",
"productClass": "32",
"productGroup": "3201",
"productNumber": "MR",
"quantityOnHand": 9999,
"ratebook": "Y",
"replacementCost": 0,
"safetyNotes": [],
"showOnWebsite": "",
"sslNumber": "",
"statusCode": "",
"vendorDescription": "MISC RENTAL",
"vendorNumber": "",
"vendorProductNumber": "MR"
},
{
"_link": {
"fileAttachments": "http://localhost:8000/assets/T4/file_attachments/",
"groupRates": "http://localhost:8000/assets/T4/group_rates/",
"inspectionForms": "http://localhost:8000/assets/T4/inspection_form/",
"locations": "http://localhost:8000/assets/T4/locations/",
"meterHistories": "http://localhost:8000/assets/T4/meter_histories/",
"productRates": "http://localhost:8000/assets/T4/product_rates/",
"tags": "http://localhost:8000/assets/T4/tags/"
},
"averageCostEach": 50,
"barcodes": [],
"bulkItem": "Y",
"cycleBill": "Y",
"dateOfManufacture": "2018-07-07",
"description": "OXYGEN TANK",
"fuelTypes": [],
"inventory": "Y",
"listPrice": 61.5,
"make": "",
"markupPercentage": 23,
"currentMeter": 0,
"meterType": "N",
"modelNumber": "",
"multipleTags": "Y",
"notes": "",
"productClass": "60",
"productGroup": "6001",
"productNumber": "T4",
"quantityOnHand": 11999995,
"ratebook": "Y",
"replacementCost": 0,
"safetyNotes": [],
"showOnWebsite": "",
"sslNumber": "",
"statusCode": "",
"vendorDescription": "OXYGEN TANK",
"vendorNumber": "8",
"vendorProductNumber": "T4"
}
],
"pages": {
"firstUrl": "http://127.0.0.1:8000/assets/?page=1&per_page=2",
"lastUrl": "http://127.0.0.1:8000/assets/?page=391&per_page=2",
"nextUrl": "http://127.0.0.1:8000/assets/?page=2&per_page=2",
"page": 1,
"pages": 391,
"perPage": 2,
"prevUrl": null,
"total": 782
}
}
definitions:
Asset:
type: object
required:
- description
- productNumber
- vendorNumber
- productGroup
- productClass
- statusCode
- meterType
properties:
averageCostEach:
type: number
readonly: true
barcodes:
type: array
items:
type: string
bulkItem:
type: string
enum: ["Y", "N"]
maxLength: 1
cycleBill:
type: string
enum: ["Y", "N"]
maxLength: 1
dateOfManufacture:
type: string
format: date
description:
type: string
maxLength: 15
fuelTypes:
type: array
items:
$ref: '#/definitions/AssetFuelType'
inventory:
type: string
enum: ["Y", "N"]
maxLength: 1
listPrice:
type: number
format: float
make:
type: string
maxLength: 20
markupPercentage:
type: number
meterType:
type: string
enum: ["M", "B", "N"]
maxLength: 1
currentMeter:
type: number
description: If the meter type is 'M' or 'B', this value should be prompted.
initialMeter:
type: number
description: If the meter type is 'M' or 'B', this value should be prompted.
currentMeterDate:
type: string
format: date
description: If the meter type is 'M' or 'B', this value should be prompted.
initialMeterDate:
type: string
format: date
description: If the meter type is 'M' or 'B', this value should be prompted.
meterDigits:
type: number
description: If the meter type is 'M', this value should be prompted.
modelNumber:
type: string
maxLength: 15
multipleTags:
type: string
enum: ["Y", "N"]
maxLength: 1
notes:
type: string
maxLength: 50
productClass:
type: string
maxLength: 5
productGroup:
type: string
maxLength: 5
productNumber:
type: string
maxLength: 12
quantityOnHand:
type: number
readonly: true
ratebook:
type: string
enum: ["Y", "N"]
maxLength: 1
replacementCost:
type: number
safetyNotes:
type: array
items:
type: string
showOnWebsite:
type: string
enum: ["Y", "N"]
maxLength: 1
sslNumber:
type: string
maxLength: 9
statusCode:
type: string
maxLength: 2
vendorDescription:
type: string
maxLength: 30
vendorNumber:
type: string
maxLength: 6
vendorProductNumber:
type: string
maxLength: 20
externalResourceUrl:
type: string
maxLength: 500
Page:
type: object
properties:
firstUrl:
type: string
lastUrl:
type: string
nextUrl:
type: string
page:
type: number
pages:
type: number
perPage:
type: number
prevUrl:
type: string
total:
type: number
AssetFuelType:
type: object
required:
- fuelType
- capacity
properties:
fuelType:
type: string
maxLength: 3
capacity:
type: number
I am using a customize validation function and in Flasgger validate function.
`validate(
request_data,
'Asset',
'swagger/assets_get.yml',
validation_error_handler=validation_error_handler,
validation_function=validate_response_handler,
)`
`def validate_response_handler(data, schema):
try:
jsonschema.validate(data, schema, format_checker=jsonschema.FormatChecker())
except Exception as e:
raise e`
as I debugged and checked schema's definitions property is blank and it has properties of Asset definition and it is now throwing an exception of RefResolution error for AssetFuelType. and how I changed the code
`def validate_response_handler(data, schema):
try:
schema['definitions'] = {
"AssetFuelType": {
"type": "object",
"required": [
"fuelType",
"capacity"
],
"properties": {
"fuelType": {
"type": "string",
"maxLength": 3
},
"capacity": {
"type": "number"
}
}
}
}
jsonschema.validate(data, schema, format_checker=jsonschema.FormatChecker())
except Exception as e:
raise e`
and it works, so Flassger validate has any problem to parse the Yaml file or I am doing something wrong. | open | 2018-11-07T06:40:18Z | 2018-11-07T06:44:43Z | https://github.com/flasgger/flasgger/issues/257 | [] | ghost | 0 |
erdewit/ib_insync | asyncio | 665 | cancelMktDepth causes errors | I'm getting errors calling cancelMktDepth. Looks like it clears domBids and domAsks right away [1], but IB server keeps sending the level2 updates for a while, and when the decoder decodes them it tries to access domBids and domAsks, which have been cleared, causing an error. Below is a small example demonstrating the issue. It looks like there is a second issue as well with "can't find the subscribed market depth..",
BTW my version.py shows __version_info__ = (0, 9, 86), but for some reason the line number in wrapper.py in the error message I get is line 921, but in the source here it looks like line 975 (?).
[1] https://github.com/erdewit/ib_insync/blob/d31241f2fcb16f5a61dc075d6f458721cb95eebd/ib_insync/ib.py#L1352
[2] https://github.com/erdewit/ib_insync/blob/d31241f2fcb16f5a61dc075d6f458721cb95eebd/ib_insync/wrapper.py#L975
-Neal
--- code demonstrating the issue:
```
import ib_insync as ibs
ib = ibs.IB()
ib.connect()
ib.sleep(1)
contract = ibs.Stock("SPY", "SMART", "USD")
ib.qualifyContracts(contract)
ib.sleep(1)
ticker = ib.reqMktDepth(contract, numRows=50, isSmartDepth=True)
ib.sleep(2)
ib.cancelMktDepth(contract)
ib.sleep(2)
# now we get the following errors:
#
# Error 310, reqId 15049: Can't find the subscribed market depth with tickerId:15049
# Error for updateMktDepthL2:
# Traceback (most recent call last):
# File "/Users/neal/Desktop/IB/curses_app/ib_insync/decoder.py", line 187, in handler
# method(*args)
# File "/Users/neal/Desktop/IB/curses_app/ib_insync/wrapper.py", line 921, in updateMktDepthL2
# dom[position] = DOMLevel(price, size, marketMaker)
# ~~~^^^^^^^^^^
# IndexError: list assignment index out of range
ib.disconnect()
``` | closed | 2023-11-29T22:20:36Z | 2023-12-01T14:23:07Z | https://github.com/erdewit/ib_insync/issues/665 | [] | nealeyoung | 4 |
jupyterhub/repo2docker | jupyter | 971 | Detect default branch instead of assuming master (at least for GitHub repos) | <!-- Thank you for contributing. These HTML commments will not render in the issue, but you can delete them once you've read them if you prefer! -->
### Proposed change
<!-- Use this section to describe the feature you'd like to be added. -->
GitHub (at least) now supports setting your default branch to something other than `master`, the recommended option being `main`. https://www.zdnet.com/article/github-to-replace-master-with-main-starting-next-month/
This can be confusing for new users of mybinder.org, e.g. https://discourse.jupyter.org/t/cant-solve-could-not-resolve-ref-for-gh-fredericfoulonlycee-math-spe-python-master/6301
We should change repo2docker's behaviour to search for/fetch the default branch name of the git repository, rather than assuming/hard code it to being `master`.
I don't know if r2d assumes everything is a git repository or if this is something we'll specifically have to build into the GitHub repo handling section.
### Alternative options
<!-- Use this section to describe alternative options and why you've decided on the proposed feature above. -->
We continue to wait until this is more common before carrying out this work. Perhaps adding an information box to the front page of mybinder.org so folks are aware.
### Who would use this feature?
<!-- Describe the audience for this feature. This information will affect who chooses to work on the feature with you. -->
Everybody who has created a new GitHub repository since 1st October 2020 or have manually renamed their default branches.
### How much effort will adding it take?
<!-- Try to estimate how much work adding this feature will require. This information will affect who chooses to work on the feature with you. -->
I imagine there's a git command we can run to fetch the default branch name and then parse that into our standard branch handling code for non-`master` branches.
### Who can do this work?
<!-- What skills are needed? Who can be recruited to add this feature? This information will affect who chooses to work on the feature with you. -->
Useful skills:
- Knowledge of the r2d codebase: where things are being parsed to, etc
- Some git fu to detect the default branch name
| closed | 2020-10-16T10:43:14Z | 2020-10-22T08:44:31Z | https://github.com/jupyterhub/repo2docker/issues/971 | [
"needs: discussion"
] | sgibson91 | 1 |
iterative/dvc | data-science | 9,899 | exp show: unexpected error - 'checkpoint_tip' when using -A option | # Bug Report
<!--
## Issue name
Issue names must follow the pattern `command: description` where the command is the dvc command that you are trying to run. The description should describe the consequence of the bug.
Example: `repro: doesn't detect input changes`
-->
## Description
<!--
A clear and concise description of what the bug is.
-->
Command `dvc exp show -A` raises the following error without any output:
```
ERROR: unexpected error - 'checkpoint_tip'
```
### Reproduce
<!--
Step list of how to reproduce the bug
-->
<!--
Example:
1. dvc init
2. Copy dataset.zip to the directory
3. dvc add dataset.zip
4. dvc run -d dataset.zip -o model ./train.sh
5. modify dataset.zip
6. dvc repro
-->
Not sure what is causing this issue. Could it be related to breaking changes moving from DVC 2 to 3?
### Expected
<!--
A clear and concise description of what you expect to happen.
-->
The command should show me an overview of all experiments I ran in the DVC project folder of the Git repository.
### Environment information
<!--
This is required to ensure that we can reproduce the bug.
-->
**Output of `dvc doctor`:**
```console
$ dvc doctor
DVC version: 3.17.0 (conda)
---------------------------
Platform: Python 3.10.6 on Linux-3.10.0-1127.8.2.el7.x86_64-x86_64-with-glibc2.17
Subprojects:
dvc_data = 2.15.4
dvc_objects = 1.0.1
dvc_render = 0.5.3
dvc_task = 0.3.0
scmrepo = 1.3.1
Supports:
http (aiohttp = 3.8.5, aiohttp-retry = 2.8.3),
https (aiohttp = 3.8.5, aiohttp-retry = 2.8.3),
s3 (s3fs = 2023.6.0, boto3 = 1.26.76)
Config:
Global: /home/aschuh/.config/dvc
System: /etc/xdg/dvc
Cache types: hardlink, symlink
Cache directory: xfs on /dev/sda1
Caches: local
Remotes: s3, s3
Workspace directory: xfs on /dev/sda1
Repo: dvc (subdir), git
Repo.site_cache_dir: /var/tmp/dvc/repo/8d2f5d68bb223da9776a9d6301681efd
```
**Additional Information (if any):**
<!--
Please check https://github.com/iterative/dvc/wiki/Debugging-DVC on ways to gather more information regarding the issue.
If applicable, please also provide a `--verbose` output of the command, eg: `dvc add --verbose`.
If the issue is regarding the performance, please attach the profiling information and the benchmark comparisons.
-->
`dvc exp list -A` works and does not cause this issue. | closed | 2023-08-31T22:45:42Z | 2023-09-06T05:58:54Z | https://github.com/iterative/dvc/issues/9899 | [
"bug",
"A: experiments"
] | aschuh-hf | 6 |
krish-adi/barfi | streamlit | 32 | I want to improve barfi but i need help | Hi krish !
I'm huge fan of barfi and i want to build a projet with it but for this i need new functionnalities that i want to add but i don't really know javascript i'm profficient in python and i'm already building a script to create easily schemas with code.
I need help on how to open and modify the graphic part to change the buttons and make them "streatlit activable" and also a way to group different nodes.
Can you help me if you have a minute ?
Thank you man ! I really love your work ! | closed | 2024-05-13T19:32:38Z | 2025-01-16T16:08:27Z | https://github.com/krish-adi/barfi/issues/32 | [
"help wanted"
] | Silectio | 4 |
SYSTRAN/faster-whisper | deep-learning | 206 | requests.exceptions.ConnectionError | requests.exceptions.ConnectionError: HTTPSConnectionPool(host='huggingface.co', port=443): Max retries exceeded with url: /api/models/guillaumekln/faster-whisper-large-v2/revision/main (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f0e915670a0>: Failed to establish a new connection: [Errno 101] Network is unreachable')) | closed | 2023-05-07T13:33:27Z | 2023-05-08T07:54:16Z | https://github.com/SYSTRAN/faster-whisper/issues/206 | [] | wwfcnu | 4 |
vimalloc/flask-jwt-extended | flask | 505 | Direct call to decorator (jwt_required) | jwt_required(func(arg))
Previously, in version 3.x, it was called and used as above.
A TypeError occurred in version 4.4.4.
->
Traceback (most recent call last):
File "/Users/user/PycharmProjects/flaskTestProject/venv/lib/python3.8/site-packages/flask/app.py", line 2525, in wsgi_app
response = self.full_dispatch_request()
File "/Users/user/PycharmProjects/flaskTestProject/venv/lib/python3.8/site-packages/flask/app.py", line 1823, in full_dispatch_request
return self.finalize_request(rv)
File "/Users/user/PycharmProjects/flaskTestProject/venv/lib/python3.8/site-packages/flask/app.py", line 1842, in finalize_request
response = self.make_response(rv)
File "/Users/user/PycharmProjects/flaskTestProject/venv/lib/python3.8/site-packages/flask/app.py", line 2162, in make_response
raise TypeError(
File "/Users/user/PycharmProjects/flaskTestProject/venv/lib/python3.8/site-packages/flask/app.py", line 2158, in make_response
rv = self.response_class.force_type(
File "/Users/user/PycharmProjects/flaskTestProject/venv/lib/python3.8/site-packages/werkzeug/wrappers/response.py", line 268, in force_type
response = Response(*run_wsgi_app(response, environ))
File "/Users/user/PycharmProjects/flaskTestProject/venv/lib/python3.8/site-packages/werkzeug/test.py", line 1242, in run_wsgi_app
app_rv = app(environ, start_response)
TypeError: wrapper() takes 1 positional argument but 2 were given
How should I call it in version 4.4.4?
https://github.com/vimalloc/flask-jwt-extended/blob/88a628ec88eb3c0e766300613a1367ac3eb3f34f/flask_jwt_extended/view_decorators.py#L112-L158
| closed | 2022-12-21T02:30:47Z | 2022-12-23T01:59:57Z | https://github.com/vimalloc/flask-jwt-extended/issues/505 | [] | 0coolcard0 | 2 |
remsky/Kokoro-FastAPI | fastapi | 38 | Bake Models into Docker images | Baked models in to improve stability, deployment | closed | 2025-01-13T06:21:44Z | 2025-01-13T06:21:45Z | https://github.com/remsky/Kokoro-FastAPI/issues/38 | [] | remsky | 0 |
rthalley/dnspython | asyncio | 446 | crash in dnssec with gmp-6.2.0 during initialization | This one liner:
- - -
import dns.rdtypes.ANY.DNSKEY
- - -
gives:
```
(dskm_p37) [root@hermes /usr/local/src]# python test.py
Fatal Python error: Illegal instruction
Current thread 0x0000000800a24000 (most recent call first):
File "/usr/local/py_venv/dskm_p37/lib/python3.7/site-packages/Crypto/Math/_IntegerGMP.py", line 163 in __init__
File "/usr/local/py_venv/dskm_p37/lib/python3.7/site-packages/Crypto/PublicKey/ECC.py", line 123 in init_p256
File "/usr/local/py_venv/dskm_p37/lib/python3.7/site-packages/Crypto/PublicKey/ECC.py", line 138 in <module>
File "<frozen importlib._bootstrap>", line 219 in _call_with_frames_removed
File "<frozen importlib._bootstrap_external>", line 728 in exec_module
File "<frozen importlib._bootstrap>", line 677 in _load_unlocked
File "<frozen importlib._bootstrap>", line 967 in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 983 in _find_and_load
File "/usr/local/py_venv/dskm_p37/lib/python3.7/site-packages/Crypto/Signature/DSS.py", line 42 in <module>
File "<frozen importlib._bootstrap>", line 219 in _call_with_frames_removed
File "<frozen importlib._bootstrap_external>", line 728 in exec_module
File "<frozen importlib._bootstrap>", line 677 in _load_unlocked
File "<frozen importlib._bootstrap>", line 967 in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 983 in _find_and_load
File "<frozen importlib._bootstrap>", line 219 in _call_with_frames_removed
File "<frozen importlib._bootstrap>", line 1035 in _handle_fromlist
File "/usr/local/py_venv/dskm_p37/lib/python3.7/site-packages/dns/dnssec.py", line 484 in <module>
File "<frozen importlib._bootstrap>", line 219 in _call_with_frames_removed
File "<frozen importlib._bootstrap_external>", line 728 in exec_module
File "<frozen importlib._bootstrap>", line 677 in _load_unlocked
File "<frozen importlib._bootstrap>", line 967 in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 983 in _find_and_load
File "/usr/local/py_venv/dskm_p37/lib/python3.7/site-packages/dns/rdtypes/dnskeybase.py", line 22 in <module>
File "<frozen importlib._bootstrap>", line 219 in _call_with_frames_removed
File "<frozen importlib._bootstrap_external>", line 728 in exec_module
File "<frozen importlib._bootstrap>", line 677 in _load_unlocked
File "<frozen importlib._bootstrap>", line 967 in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 983 in _find_and_load
File "/usr/local/py_venv/dskm_p37/lib/python3.7/site-packages/dns/rdtypes/ANY/DNSKEY.py", line 18 in <module>
File "<frozen importlib._bootstrap>", line 219 in _call_with_frames_removed
File "<frozen importlib._bootstrap_external>", line 728 in exec_module
File "<frozen importlib._bootstrap>", line 677 in _load_unlocked
File "<frozen importlib._bootstrap>", line 967 in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 983 in _find_and_load
File "test.py", line 1 in <module>
Illegal instruction (core dumped)
```
This does not happen with this one liner:
```
import dns.rdtypes.ANY
```
or with gmp-6.1.2_1
Environment:
```
FreeBSD 12.1-RELEASE-p3 GENERIC amd64
OpenSSL 1.1.1d-freebsd
python37-3.7.6
virtualenv-16.7.5 Tool for creating isolated Python environments
virtualenv-clone-0.4.0_1 Python virtualenv cloning script
virtualenvwrapper-4.8.4 Enhancements to virtualenv
Package Version Location
------------ ------- -------------------
dnspython 1.16.0
DSKM 0.9.1 /usr/local/src/DSKM
ecdsa 0.15
pip 20.0.2
pycryptodome 3.9.7
script 1.7.2
setuptools 46.0.0
six 1.14.0
wheel 0.34.2
``` | closed | 2020-04-03T14:13:25Z | 2020-05-04T12:11:13Z | https://github.com/rthalley/dnspython/issues/446 | [] | mc3 | 4 |
psf/requests | python | 6,051 | HTTP/3 / QUIC? | Hi,
is it planned to wrap around QUIC in the future?
| closed | 2022-01-28T01:17:34Z | 2022-04-28T05:17:28Z | https://github.com/psf/requests/issues/6051 | [] | ksaadDE | 1 |
onnx/onnx | deep-learning | 6,365 | codeformatter / linter for yaml files? | # Ask a Question
### Question
Do we have a codeformatter / linter for yaml files? | open | 2024-09-14T16:20:23Z | 2024-09-16T16:29:41Z | https://github.com/onnx/onnx/issues/6365 | [
"question"
] | andife | 4 |
tqdm/tqdm | jupyter | 968 | "Notebook validation failed" for "tqdm.notebook.tqdm" output | When using `from tqdm.notebook import tqdm` in jupyter, the jupyter server complains `Notebook validation failed` on output cells containing a progressbar.
* tqdm.__version__: 4.45.0
* sys.__version__ : 3.7.6 (default, Jan 28 2020, 14:26:04) [GCC 5.4.0 20160609]
* sys.platform: linux (particularly Ubuntu 16.04)
* jupyter.__version__: 1.0.0
The error appears after running, and trying to save the notebook:
from tqdm.notebook import tqdm
for _ in tqdm(range(10)):
pass
The error disappears after clearing the output of the cell, and saving again.
The error is a pop-up from Jupyter after saving the notebook:
**Notebook validation failed**
The save operation succeeded, but the notebook does not appear to be valid. The validation error was:
Notebook validation failed: {'version_major': 2, 'version_minor': 0, 'model_id':
'0531a121a60a46b3a9815504e28d415c'} is not valid under any of the given schemas:
{
"version_major": 2,
"version_minor": 0,
"model_id": "0531a121a60a46b3a9815504e28d415c"
}
This is the json-content of the cell:
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "51bd2bf126484d088ff2c7547803ad6b",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"HBox(children=(FloatProgress(value=0.0, max=10.0), HTML(value='')))"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"from tqdm.notebook import tqdm\n",
"\n",
"for _ in tqdm(range(10)):\n",
" pass"
]
},
PS: thanks for this wonderful library. | open | 2020-05-12T11:36:15Z | 2020-05-12T12:50:23Z | https://github.com/tqdm/tqdm/issues/968 | [
"invalid ⛔",
"need-feedback 📢",
"p2-bug-warning ⚠",
"submodule-notebook 📓"
] | prhbrt | 2 |
ultralytics/yolov5 | deep-learning | 13,098 | low precision | ### Search before asking
- [X] I have searched the YOLOv5 [issues](https://github.com/ultralytics/yolov5/issues) and [discussions](https://github.com/ultralytics/yolov5/discussions) and found no similar questions.
### Question
i am using yolov5 on mydataset which is panoramic dental xrays. the goal is to detect the infected tooth and produce 3 labels for it: quadrant number, tooth number and the disease. a tooth my have more then 1 disease. so as a work around to achieve multi label object detection i split each label for a single tooth into separate line which looks like this:
000013 0.6431219110378913 0.45246010638297873 0.0671334431630972 0.2293882978723404
009 0.6431219110378913 0.45246010638297873 0.0671334431630972 0.2293882978723404
5 0.6431219110378913 0.45246010638297873 0.0671334431630972 0.2293882978723404
those are the quadrant number, tooth number and the disease for 1 tooth.
i have a total of 704 images for training and validation. 70% - 30%
all image sizes are not the same size and they are large. the highest precision i achieved when training yolov5m was 0.6. how can i achieve a 0.95 precision ? and what could be the issues that caused such low precision and how can i see the accuracy ? I aslo tried yolov5l and there was no difference. I trained for 300 epochs
### Additional
_No response_ | closed | 2024-06-17T19:29:02Z | 2024-10-20T19:48:04Z | https://github.com/ultralytics/yolov5/issues/13098 | [
"question"
] | mamdouhhz | 1 |
statsmodels/statsmodels | data-science | 8,982 | Allow `sm.OLS` to work with `Float64` values | When working with `Float64` values form `pandas`, `sm.OLS` raises an error
`ValueError: Pandas data cast to numpy dtype of object. Check input data with np.asarray(data).`
Example
```
impor pandas as pd
import statsmodels.api as sm
x = pd.Series([1,2,3,4]).astype('Float64')
y = pd.Series([1,2,3,4]).astype('Float64')
sm.OLS(y,x).fit()
```
It is easy to convert the `Float64` into a `float64` value, but it would be nice if `sm.OLS` can handle that. | open | 2023-08-22T15:15:32Z | 2023-08-22T15:37:26Z | https://github.com/statsmodels/statsmodels/issues/8982 | [] | marcdelabarrera | 1 |
Ehco1996/django-sspanel | django | 548 | 给clash pro添加tun模式配置(主要针对Windows clash用户) | ## Feature Request
**Is your feature request related to a problem? Please describe:**
<!-- A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] -->
NO
**Describe the feature you'd like:**
<!-- A clear and concise description of what you want to happen. -->
给clash pro添加tun模式配置(主要针对Windows clash用户)
**Describe alternatives you've considered:**
<!-- A clear and concise description of any alternative solutions or features you've considered. -->
``` yaml
dns:
enable: true
enhanced-mode: redir-host
listen: 0.0.0.0:53
.......
tun:
enable: true
stack: gvisor # 使用 system 需要 Clash Premium 2021.05.08 及更高版本
dns-hijack:
- 198.18.0.2:53
macOS-auto-route: true
macOS-auto-detect-interface: true # 自动检测出口网卡
```
同时Windows用户还需要根据[文档](https://docs.cfw.lbyczf.com/contents/tun.html)下载一个[Wintun](https://www.wintun.net/)，然后把`Wintun`放到`Home Directory`目录下，安装`Service Mode`开启
**PR**
稍后补充PR，在本地做些测试，目前已配通，~~暂不知添加`tun`配置后是否影响macOS的`ClashX`~~,已检测不影响
| closed | 2021-07-01T07:38:08Z | 2021-07-02T01:57:02Z | https://github.com/Ehco1996/django-sspanel/issues/548 | [] | Gkirito | 3 |
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