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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
keras-team/keras | python | 20,790 | Conv2D with torch backend causes errors (RuntimeError: view size is not compatible with input tensor's size and stride) | Running on Apple M1. This code works for `tensorflow` and `jax` backends, but fails when the backend is `torch`.
The reported error is:
`RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.`
Python 3.12, miniforge3, keras 3.8.0, torch 2.5.1
The error seems to relate to the Conv2D layer. If I remove Conv2D, the error disappears.
```python
import os
os.environ["KERAS_BACKEND"] = "torch"
import keras, numpy as np
model = keras.models.Sequential([
keras.layers.Input(shape=(32, 32, 3)),
keras.layers.Conv2D(filters=10, kernel_size=(3, 3), strides=(1,1), activation='relu'),
keras.layers.Flatten(),
keras.layers.Dense(10, activation='softmax')
])
model.compile(optimizer='adam', loss='mse')
model.summary()
x_train = np.zeros((64, 32, 32, 3), dtype=np.float32)
y_train = np.zeros((64, 10), dtype=np.float32)
model.fit(x=x_train, y=y_train, batch_size=64, epochs=1)
``` | closed | 2025-01-21T12:29:26Z | 2025-01-21T13:54:58Z | https://github.com/keras-team/keras/issues/20790 | [
"backend:torch"
] | gyohng | 5 |
datadvance/DjangoChannelsGraphqlWs | graphql | 46 | WebSocket connection to 'wss://api-such.andsuch.xyz/graphql/' failed: Error during WebSocket handshake: Unexpected response code: 400 | Hello @prokher, thanks for this great library. I recently deployed my application which uses [`django-graphql-playground`](https://github.com/jaydenwindle/django-graphql-playground) to test subscriptions. It works great locally. However in production, I get the following error in my browser console:
```
WebSocket connection to 'wss://api-such.andsuch.xyz/graphql/' failed: Error during WebSocket handshake: Unexpected response code: 400
```
...and in `graphql-playground`, I get:
```
{
"error": "Could not connect to websocket endpoint wss://api-such.andsuch.xyz/graphql/. Please check if the endpoint url is correct."
}
```
I checked Network tab in Chrome and discovered that websocket connections are closing immediately. What could be causing this?
Here's what my `docker-compose.yml` looks like:
```
version: '3.7'
services:
nginx:
container_name: nginx
image: nginx
restart: always
depends_on:
- web
volumes:
- ./web/dev.nginx.template:/etc/nginx/conf.d/dev.nginx.template
- ./static:/static
- ./media:/media
ports:
- "8080:80"
networks:
- SOME_NETWORK
command: /bin/bash -c "envsubst \"`env | awk -F = '{printf \" $$%s\", $$1}'`\" < /etc/nginx/conf.d/dev.nginx.template > /etc/nginx/conf.d/default.conf && exec nginx -g 'daemon off;'"
web:
container_name: web
restart: always
build: ./web
networks:
- SOME_NETWORK
depends_on:
- postgres
- redis
volumes:
- ./web:/usr/src/app/
environment:
- REDIS_HOST=redis
- REDIS_PORT=6379
- GRAPHQL_ENDPOINT=https://api-such.andsuch.xyz/graphql/
command: bash -c /start.sh
postgres:
container_name: postgres
restart: always
image: postgres:latest
networks:
- SOME_NETWORK
volumes:
- pgdata:/var/lib/postgresql/data/
redis:
container_name: redis
restart: always
image: redis:latest
networks:
- SOME_NETWORK
ports:
- "6379:6379"
volumes:
- redisdata:/data
volumes:
pgdata:
redisdata:
networks:
SOME_NETWORK:
name: SOME_NETWORK
driver: bridge
```
`settings.py`
```python
...
...
CHANNEL_LAYERS = {
'default': {
'BACKEND': 'channels_redis.core.RedisChannelLayer',
'CONFIG': {
'hosts': [(os.getenv('REDIS_HOST', 'redis'), os.getenv('REDIS_PORT', 6379))],
}
}
}
...
...
```
`urls.py`
```python
...
...
from graphql_playground.views import GraphQLPlaygroundView
urlpatterns = [
path('admin/', admin.site.urls),
path('playground/', GraphQLPlaygroundView.as_view(
endpoint=os.getenv('GRAPHQL_ENDPOINT'))),
]
...
```
`nginx`
```
server {
client_max_body_size 10M;
listen 443 ssl;
listen [::]:443 ssl;
server_name api-such.andsuch.xyz;
ssl_certificate /etc/ssl/certs/andsuch.xyz.pem;
ssl_certificate_key /etc/ssl/certs/andsuch.xyz.key;
location = /favicon.ico { access_log off; log_not_found off; }
location / {
proxy_set_header Host $http_host;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection ‘upgrade’;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
proxy_pass http://0.0.0.0:8080;
}
}
```
What could be wrong? I'm out of ideas | closed | 2020-09-01T05:13:07Z | 2020-10-17T04:09:10Z | https://github.com/datadvance/DjangoChannelsGraphqlWs/issues/46 | [] | Cimmanuel | 3 |
voxel51/fiftyone | data-science | 5,060 | [FR] Way to Pre-render thumbnails of the patches you see in patch view |
### Proposal Summary
maybe this already exists, but I want to be able to pre-render out the crops of the views you see in patch view, and have those load at run time
### Motivation
I have a dataset that i have been having major performance issues with. The full size images at 10,000 pixels wide and i have about 500 of them. Each image can have like 1-30 detections that are generally like 200 pixels and smaller. When i load them up in the fiftyone app, stuff gets real slow (to the point of unusability) and often crashes. I have been battling with this for a couple months now, and one solution i had was to generate thumbnails for all the samples with some code like this:
```
samples_to_process = []
for sample in dataset:
filename = os.path.basename(sample.filepath)
thumbnail_path = f"{output_dir}/{filename}"
sample["thumbnail_path"]=thumbnail_path
sample.save()
if not os.path.exists(thumbnail_path):
samples_to_process.append(sample)
else:
sample["thumbnail_path"]=thumbnail_path
if samples_to_process:
# Create a new dataset with the samples to process
dataset_to_process = fo.Dataset()
dataset_to_process.add_samples(samples_to_process)
print("making extra thumbnails")
print(samples_to_process)
foui.transform_images(
dataset_to_process,
size=target_size,
output_field="thumbnail_path",
output_dir=output_dir,
)
dataset.save()
```
now i get two options when using the app! I have speed, but pixelation, or full res but un-usable.
patches taken from shrunken samples (runs fast! can't ID them too pixely)
patches from full size images (goes super slow and often crashes everything)
Instead it would make more sense to be able to have the patch view load pre-rendered thumbnails of each patch (not a thumbnail of the FULL sample, but rather the patches)
Since the patches are generally like 200 pixels and smaller the performance would be great, and this performance wouldn't lower the cropped image quality.
maybe this is something one can already do, but i don't really know how?
This "tips and tricks" thing suggests something related, but i don't really understand it.
https://voxel51.com/blog/fiftyone-computer-vision-tips-and-tricks-may-19-2023/
### What areas of FiftyOne does this feature affect?
- [X ] App: FiftyOne application
- [ ] Core: Core `fiftyone` Python library
- [ ] Server: FiftyOne server
### Details
### Willingness to contribute
The FiftyOne Community welcomes contributions! Would you or another member of your organization be willing to contribute an implementation of this feature?
- [ ] Yes. I can contribute this feature independently
- [ ] Yes. I would be willing to contribute this feature with guidance from the FiftyOne community
- [x ] No. I cannot contribute this feature at this time, i dont know how to code a fiftyone
| open | 2024-11-07T01:53:43Z | 2024-11-20T15:40:34Z | https://github.com/voxel51/fiftyone/issues/5060 | [
"feature"
] | quitmeyer | 3 |
clovaai/donut | computer-vision | 245 | Query Regarding Tree-Based Accuracy Calculation in Donut Model | Hello,
I am currently working on understanding the code within the donut model repository, specifically focusing on the tree-based accuracy calculation. While examining the codebase, I came across the utilization of the zss.distance function for accuracy calculation.
My inquiry pertains to the distance function, particularly concerning the concept of "keyroots of tree." I am seeking clarification on the definition and significance of these "keyroots of tree" within the context of the accuracy calculation process. Could someone kindly provide an explanation or insight into this matter?
Thank you. | open | 2023-08-31T09:38:02Z | 2023-08-31T09:38:02Z | https://github.com/clovaai/donut/issues/245 | [] | Mann1904 | 0 |
PaddlePaddle/PaddleHub | nlp | 2,072 | 安装模型报错 | 
想试用模型，可是却报错了
paddlepaddle 2.3.0
paddle hub 2.3.0 | closed | 2022-10-14T03:11:37Z | 2022-10-14T06:52:15Z | https://github.com/PaddlePaddle/PaddleHub/issues/2072 | [] | hbo-lambda | 3 |
JoeanAmier/TikTokDownloader | api | 416 | 如何正确获取自己的账号主页链接？ | 开始获取收藏数据
获取账号简略失败
self 获取账号信息失败
程序运行耗时 0 分钟 3 秒
已退出批量下载收藏作品(抖音)模式
请选择采集功能: | closed | 2025-03-04T01:26:14Z | 2025-03-04T10:50:35Z | https://github.com/JoeanAmier/TikTokDownloader/issues/416 | [
"文档补充(docs)",
"适合新手(good first issue)"
] | lenmao | 3 |
iperov/DeepFaceLab | machine-learning | 5,737 | not working on AMD GPU | After following the instructions and selecting a video file, the application stops working. It responds to inputs, but does not detect faces, swap them, or play the video.
OS: Windows 11
GPU: RX 7900 XTX 24Gb (latest drivers) | open | 2023-10-16T20:54:21Z | 2023-10-16T20:54:21Z | https://github.com/iperov/DeepFaceLab/issues/5737 | [] | f1am3d | 0 |
CorentinJ/Real-Time-Voice-Cloning | pytorch | 592 | Training on custom data | is there a guide for training this using custom voice data we collect on our own?
| closed | 2020-11-09T14:23:34Z | 2021-04-28T19:41:00Z | https://github.com/CorentinJ/Real-Time-Voice-Cloning/issues/592 | [] | michaellin99999 | 1 |
facebookresearch/fairseq | pytorch | 5,195 | Dialogue Speech-to-Unit Encoder for dGSLM - checkpoint issues | ## 🐛 Bug
I tried to load the checkpoints (Fisher HuBERT model and k-means model) from
[Dialogue Speech-to-Unit Encoder for dGSLM: The Fisher HuBERT model](https://github.com/facebookresearch/fairseq/tree/main/examples/textless_nlp/dgslm/hubert_fisher)
and got the following error:
`No such file or directory: '/checkpoint/ntuanh/experiments/dialogue-LM/hubert/fisher-vad-10s-separated/kmeans/hubert_iter2/km500/dict.km.txt'`
After trying to fix it with an external k-means dictionary file, I got dimension mismatch in the weights.
### To Reproduce
1. Download the checkpoint files under [Fisher HuBERT model](https://dl.fbaipublicfiles.com/textless_nlp/dgslm/checkpoints/hubert/hubert_fisher.pt) and [k-means model](https://dl.fbaipublicfiles.com/textless_nlp/dgslm/checkpoints/hubert/hubert_fisher_km_500.bin) from [Dialogue Speech-to-Unit Encoder for dGSLM: The Fisher HuBERT model](https://github.com/facebookresearch/fairseq/tree/main/examples/textless_nlp/dgslm/hubert_fisher)
3. Create a Python script using the code snippet shown at the bottom of the readme file
4. Refer to these checkpoint files when passing the paths to HubertTokenizer
5. Include the path to a (dummy) audio file
6. Run Python script
7. See error
Note: I tried the other method as well (by using quantize_with_kmeans.py) but got the same error.
Trace:
```
Traceback (most recent call last):
File "/home/user/fairseq/examples/textless_nlp/gslm/speech2unit/clustering/quantize_with_kmeans.py", line 144, in <module>
main(args, logger)
File "/home/user/fairseq/examples/textless_nlp/gslm/speech2unit/clustering/quantize_with_kmeans.py", line 101, in main
features_batch = get_features(
File "/home/user/fairseq/examples/textless_nlp/gslm/speech2unit/pretrained/utils.py", line 73, in get_features
generator, num_files = get_feature_iterator(
File "/home/user/fairseq/examples/textless_nlp/gslm/speech2unit/pretrained/utils.py", line 58, in get_feature_iterator
reader = feature_reader_cls(
File "/home/user/fairseq/examples/textless_nlp/gslm/speech2unit/pretrained/hubert_feature_reader.py", line 23, in __init__
) = fairseq.checkpoint_utils.load_model_ensemble_and_task(
File "/home/user/fairseq/fairseq/checkpoint_utils.py", line 484, in load_model_ensemble_and_task
model = task.build_model(cfg.model, from_checkpoint=True)
File "/home/user/fairseq/fairseq/tasks/fairseq_task.py", line 355, in build_model
model = models.build_model(cfg, self, from_checkpoint)
File "/home/user/fairseq/fairseq/models/__init__.py", line 106, in build_model
return model.build_model(cfg, task)
File "/home/user/fairseq/fairseq/models/hubert/hubert.py", line 335, in build_model
model = HubertModel(cfg, task.cfg, task.dictionaries)
File "/home/user/fairseq/fairseq/tasks/hubert_pretraining.py", line 139, in dictionaries
return self.state.dictionaries
File "/home/user/fairseq/fairseq/tasks/fairseq_task.py", line 42, in __getattr__
self._state[name] = self._factories[name]()
File "/home/user/fairseq/fairseq/tasks/hubert_pretraining.py", line 149, in load_dictionaries
dictionaries = [
File "/home/user/fairseq/fairseq/tasks/hubert_pretraining.py", line 150, in <listcomp>
Dictionary.load(f"{label_dir}/dict.{label}.txt")
File "/home/user/fairseq/fairseq/data/dictionary.py", line 228, in load
d.add_from_file(f)
File "/home/user/fairseq/fairseq/data/dictionary.py", line 241, in add_from_file
raise fnfe
File "/home/user/fairseq/fairseq/data/dictionary.py", line 238, in add_from_file
with open(PathManager.get_local_path(f), "r", encoding="utf-8") as fd:
FileNotFoundError: [Errno 2] No such file or directory: '/checkpoint/ntuanh/experiments/dialogue-LM/hubert/fisher-vad-10s-separated/kmeans/hubert_iter2/km500/dict.km.txt'
```
#### Code sample
```
# Load the Hubert tokenizer
from examples.textless_nlp.dgslm.dgslm_utils import HubertTokenizer
encoder = HubertTokenizer(
hubert_path = "/path/to/hubert_ckpt.pt",
hubert_layer = 12,
km_path = "path/to/km.bin"
)
# Encode the audio to units
path = "/path/to/stereo/audio.wav"
codes = encoder.wav2codes(path)
```
### Expected behavior
I assume that the path to the k-means dictionary file should be a relative path and that the dictionary file should be included in the HuBERT model checkpoint itself.
Note: As a temporary measure, I tried to overwrite the path that causes the error with [dictionary1](https://dl.fbaipublicfiles.com/textless_nlp/dgslm/checkpoints/speech_dlm/dict.unitA.txt) in [Generative Spoken Dialogue Language Modeling](https://github.com/facebookresearch/fairseq/tree/main/examples/textless_nlp/dgslm) which has exactly 500 elements. After this, I got another error:
```
Traceback (most recent call last):
File "/home/user/hubert.py", line 6, in <module>
encoder = HubertTokenizer(
File "/home/user/fairseq/examples/textless_nlp/dgslm/dgslm_utils.py", line 27, in __init__
self.feature_extractor = HubertFeatureReader(hubert_path, hubert_layer, use_cuda=use_cuda)
File "/home/user/fairseq/examples/textless_nlp/gslm/speech2unit/pretrained/hubert_feature_reader.py", line 23, in __init__
) = fairseq.checkpoint_utils.load_model_ensemble_and_task(
File "/home/user/fairseq/fairseq/checkpoint_utils.py", line 493, in load_model_ensemble_and_task
model.load_state_dict(
File "/home/user/fairseq/fairseq/models/fairseq_model.py", line 128, in load_state_dict
return super().load_state_dict(new_state_dict, strict)
File "/home/liviaq/miniconda3/envs/asr/lib/python3.9/site-packages/torch/nn/modules/module.py", line 2041, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for HubertModel:
size mismatch for label_embs_concat: copying a param with shape torch.Size([504, 256]) from checkpoint, the shape in current model is torch.Size([1008, 256]).
size mismatch for final_proj.weight: copying a param with shape torch.Size([256, 768]) from checkpoint, the shape in current model is torch.Size([512, 768]).
size mismatch for final_proj.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
```
Based on this, I believe that there is also some dimension mismatch between the pre-trained weights and the actual model weights.
### Environment
- fairseq Version: main
- PyTorch Version: 2.0.1
- OS (e.g., Linux): Linux
- How you installed fairseq (`pip`, source): source
- Build command you used (if compiling from source): `pip install --editable ./`
- Python version: 3.9.12
- CUDA/cuDNN version: 11.8
- GPU models and configuration: 1 GPU (24 GB), Driver Version: 520.61.05
| closed | 2023-06-06T10:55:16Z | 2023-06-06T15:26:00Z | https://github.com/facebookresearch/fairseq/issues/5195 | [
"bug",
"needs triage"
] | qianlivia | 2 |
JaidedAI/EasyOCR | machine-learning | 1,342 | Fine-Tuning EasyOCR on Urdu Textbooks | I'm fine-tuning the EasyOCR model (arabic.pth) for Urdu TextBooks text recognition. Currently, I'm passing the image of an entire page as input and providing the corresponding text for the entire page. However, the performance is almost zero.
My question is: Is this approach correct, or should I split the page (image) into smaller regions for better performance? | open | 2024-12-04T11:58:03Z | 2024-12-04T11:58:03Z | https://github.com/JaidedAI/EasyOCR/issues/1342 | [] | mujeeb-merwat | 0 |
man-group/notebooker | jupyter | 166 | pdf report generation broken in python 3.8 | In python 3.8 pdf reports are not showing correct charts but instead their string versions | closed | 2024-01-09T16:45:05Z | 2024-02-29T08:28:50Z | https://github.com/man-group/notebooker/issues/166 | [] | marcinapostoluk | 2 |
slackapi/python-slack-sdk | asyncio | 1,651 | How to share files in a ephermal way to a user in a channel or DM without making the files publicly available on the internet? | This is the upload method I'm using, to upload and post PDF files to Slack. The files are generated via a script on on google cloud run and uploaded directly to slack, they're not hosted on Google cloud run, it's serverless.
```
def upload_file(
self,
channel_id: str,
user_id: str,
file_bytes: bytes,
filename: str,
title: str,
initial_comment: str = "",
) -> dict:
"""
Uploads a file to Slack using the external file upload workflow and posts
an ephemeral message (visible only to the specified user) with an attachment
referencing the uploaded file.
"""
# Step 1: Get the upload URL from Slack.
file_length = len(file_bytes)
upload_url_resp = self.client.files_getUploadURLExternal(
filename=filename, length=file_length
)
if not upload_url_resp.get("ok"):
raise ValueError(f"Failed to get upload URL: {upload_url_resp}")
upload_url = upload_url_resp["upload_url"]
file_id = upload_url_resp["file_id"]
# Step 2: Upload the file bytes using an HTTP POST.
payload = {
"filename": filename,
"token": self.token,
}
post_response = requests.post(upload_url, params=payload, data=file_bytes)
if post_response.status_code != 200:
raise ValueError(
f"File upload failed (status {post_response.status_code}): {post_response.text}"
)
# Step 3: Complete the external upload so the file appears in Slack.
complete_resp = self.client.files_completeUploadExternal(
files=[{"id": file_id, "title": title}],
channel_id=channel_id,
initial_comment=initial_comment,
thread_ts=None,
)
if not complete_resp.get("ok"):
raise ValueError(f"Failed to complete file upload: {complete_resp}")
# Step 4: Post an ephemeral message with an attachment referencing the file.
attachment = {
"title": title,
"image_url": upload_url,
}
post_msg_resp = self.client.chat_postEphemeral(
channel=channel_id,
user=user_id,
text=initial_comment or f"File uploaded: {title}",
attachments=[attachment],
)
return post_msg_resp
```
I want to share files in a ephermal way, this method shares files publicly only.
```
post_msg_resp = self.client.chat_postEphemeral(
channel=channel_id,
user=user_id,
text=initial_comment or f"File uploaded: {title}",
attachments=[attachment],
)
```
so I must remove the `channel_id` and then grab the link and use `chat_postEphemeral` to send the URL to the user. Therefore `files_completeUploadExternal` can no longer post files directly to Slack.
- I'm unable to show the PDF as an embeddable attachment, the way that `files_completeUploadExternal` shows the file
- I'm unable to use `files_completeUploadExternal` to post to a channel privately (ephermal) or to send the PDF via DM
- I don't want to make the permalinks shareable publicly, and then send the links via `chat_postEphemeral` because the data is sensitive and belongs to my company.
If I make the data public, I'd have to create another service that deletes the data every few days and use database to keep track of the visible files. It's a whole other project.
| closed | 2025-02-04T18:29:50Z | 2025-02-19T16:18:47Z | https://github.com/slackapi/python-slack-sdk/issues/1651 | [
"question",
"web-client",
"Version: 3x"
] | elieobeid7 | 4 |
huggingface/datasets | pytorch | 7,418 | pyarrow.lib.arrowinvalid: cannot mix list and non-list, non-null values with map function | ### Describe the bug
Encounter pyarrow.lib.arrowinvalid error with map function in some example when loading the dataset
### Steps to reproduce the bug
```
from datasets import load_dataset
from PIL import Image, PngImagePlugin
dataset = load_dataset("leonardPKU/GEOQA_R1V_Train_8K")
system_prompt="You are a helpful AI Assistant"
def make_conversation(example):
prompt = []
prompt.append({"role": "system", "content": system_prompt})
prompt.append(
{
"role": "user",
"content": [
{"type": "image"},
{"type": "text", "text": example["problem"]},
]
}
)
return {"prompt": prompt}
def check_data_types(example):
for key, value in example.items():
if key == 'image':
if not isinstance(value, PngImagePlugin.PngImageFile):
print(value)
if key == "problem" or key == "solution":
if not isinstance(value, str):
print(value)
return example
dataset = dataset.map(check_data_types)
dataset = dataset.map(make_conversation)
```
### Expected behavior
Successfully process the dataset with map
### Environment info
datasets==3.3.1 | open | 2025-02-21T10:58:06Z | 2025-02-25T15:26:46Z | https://github.com/huggingface/datasets/issues/7418 | [] | alexxchen | 4 |
huggingface/datasets | machine-learning | 6,451 | Unable to read "marsyas/gtzan" data | Hi, this is my code and the error:
```
from datasets import load_dataset
gtzan = load_dataset("marsyas/gtzan", "all")
```
[error_trace.txt](https://github.com/huggingface/datasets/files/13464397/error_trace.txt)
[audio_yml.txt](https://github.com/huggingface/datasets/files/13464410/audio_yml.txt)
Python 3.11.5
Jupyter Notebook 6.5.4
Windows 10
I'm able to download and work with other datasets, but not this one. For example, both these below work fine:
```
from datasets import load_dataset
dataset = load_dataset("facebook/voxpopuli", "pl", split="train", streaming=True)
minds = load_dataset("PolyAI/minds14", name="en-US", split="train")
```
Thanks for your help
https://huggingface.co/datasets/marsyas/gtzan/tree/main | closed | 2023-11-25T15:13:17Z | 2023-12-01T12:53:46Z | https://github.com/huggingface/datasets/issues/6451 | [] | gerald-wrona | 3 |
matplotlib/mplfinance | matplotlib | 450 | Where can I find help documentation of mplfinance parameters? | Hi, I saw other people mentioning "mpf.plot(df, type='pnf', pnf_params=dict(box_size=7))" parameters in other issue, but I did not find any documents containing these parameters on the mplfinance webpage(including github and pypi.org). Where did these parameters come from? Are there any more optional parameters can use of mplfinance?
Thank you ! | closed | 2021-10-02T23:59:37Z | 2021-10-03T01:23:13Z | https://github.com/matplotlib/mplfinance/issues/450 | [
"question"
] | sunjar2020 | 1 |
zappa/Zappa | django | 558 | [Migrated] import routes causing 404 error | Originally from: https://github.com/Miserlou/Zappa/issues/1475 by [johnedstone](https://github.com/johnedstone)
What is it about the import statement `from app import routes` in this [example](https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-i-hello-world) that causes the app to fail (returns 404) when deployed as a lambda package with Zappa?
Later: I just realized that if I changed the `app_function` value in `zappa_settings.json` generated by `zappa init` to `microblog.app` (or `app.app` ) that it would work. The default: `"app_function": "microblog.__init__.app"`, though it works with `flask run`, doesn't work when deployed with zappa. You can close this issue. Thanks again for this awesome project! | closed | 2021-02-20T12:22:44Z | 2022-07-16T07:07:35Z | https://github.com/zappa/Zappa/issues/558 | [] | jneves | 1 |
axnsan12/drf-yasg | django | 422 | AttributeError: module 'ruamel.yaml' has no attribute 'SafeDumper' | Hello! After docker image build, trying to run containers via docker-compose up, and facing error:
Traceback (most recent call last):
django_1 | File "manage.py", line 21, in <module>
django_1 | main()
django_1 | File "manage.py", line 17, in main
django_1 | execute_from_command_line(sys.argv)
django_1 | File "/usr/local/lib/python3.6/site-packages/django/core/management/__init__.py", line 381, in execute_from_command_line
django_1 | utility.execute()
django_1 | File "/usr/local/lib/python3.6/site-packages/django/core/management/__init__.py", line 375, in execute
django_1 | self.fetch_command(subcommand).run_from_argv(self.argv)
django_1 | File "/usr/local/lib/python3.6/site-packages/django/core/management/base.py", line 323, in run_from_argv
django_1 | self.execute(*args, **cmd_options)
django_1 | File "/usr/local/lib/python3.6/site-packages/django/core/management/base.py", line 361, in execute
django_1 | self.check()
django_1 | File "/usr/local/lib/python3.6/site-packages/django/core/management/base.py", line 390, in check
django_1 | include_deployment_checks=include_deployment_checks,
django_1 | File "/usr/local/lib/python3.6/site-packages/django/core/management/commands/migrate.py", line 65, in _run_checks
django_1 | issues.extend(super()._run_checks(**kwargs))
django_1 | File "/usr/local/lib/python3.6/site-packages/django/core/management/base.py", line 377, in _run_checks
django_1 | return checks.run_checks(**kwargs)
django_1 | File "/usr/local/lib/python3.6/site-packages/django/core/checks/registry.py", line 72, in run_checks
django_1 | new_errors = check(app_configs=app_configs)
django_1 | File "/usr/local/lib/python3.6/site-packages/django/core/checks/urls.py", line 13, in check_url_config
django_1 | return check_resolver(resolver)
django_1 | File "/usr/local/lib/python3.6/site-packages/django/core/checks/urls.py", line 23, in check_resolver
django_1 | return check_method()
django_1 | File "/usr/local/lib/python3.6/site-packages/django/urls/resolvers.py", line 398, in check
django_1 | for pattern in self.url_patterns:
django_1 | File "/usr/local/lib/python3.6/site-packages/django/utils/functional.py", line 80, in __get__
django_1 | res = instance.__dict__[self.name] = self.func(instance)
django_1 | File "/usr/local/lib/python3.6/site-packages/django/urls/resolvers.py", line 579, in url_patterns
django_1 | patterns = getattr(self.urlconf_module, "urlpatterns", self.urlconf_module)
django_1 | File "/usr/local/lib/python3.6/site-packages/django/utils/functional.py", line 80, in __get__
django_1 | res = instance.__dict__[self.name] = self.func(instance)
django_1 | File "/usr/local/lib/python3.6/site-packages/django/urls/resolvers.py", line 572, in urlconf_module
django_1 | return import_module(self.urlconf_name)
django_1 | File "/usr/local/lib/python3.6/importlib/__init__.py", line 126, in import_module
django_1 | return _bootstrap._gcd_import(name[level:], package, level)
django_1 | File "<frozen importlib._bootstrap>", line 994, in _gcd_import
django_1 | File "<frozen importlib._bootstrap>", line 971, in _find_and_load
django_1 | File "<frozen importlib._bootstrap>", line 955, in _find_and_load_unlocked
django_1 | File "<frozen importlib._bootstrap>", line 665, in _load_unlocked
django_1 | File "<frozen importlib._bootstrap_external>", line 678, in exec_module
django_1 | File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
django_1 | File "/app/config/urls.py", line 20, in <module>
django_1 | from drf_yasg.views import get_schema_view
django_1 | File "/usr/local/lib/python3.6/site-packages/drf_yasg/views.py", line 14, in <module>
django_1 | from .renderers import (
django_1 | File "/usr/local/lib/python3.6/site-packages/drf_yasg/renderers.py", line 11, in <module>
django_1 | from .codecs import VALIDATORS, OpenAPICodecJson, OpenAPICodecYaml
django_1 | File "/usr/local/lib/python3.6/site-packages/drf_yasg/codecs.py", line 133, in <module>
django_1 | class SaneYamlDumper(yaml.SafeDumper):
django_1 | AttributeError: module 'ruamel.yaml' has no attribute 'SafeDumper' | closed | 2019-07-26T10:52:12Z | 2019-09-29T15:41:58Z | https://github.com/axnsan12/drf-yasg/issues/422 | [] | Almaz97 | 2 |
sqlalchemy/alembic | sqlalchemy | 548 | create_module_proxy can be fooled when it wraps methods that have explciit arguments | There's an import artifact of some kind that is changing the behavior of `@contextlib.contextmanager` in one environment, such that `inspect.getargspec(fn)` of the function is returning it's full set of keyword defaults, rather than a generic `*arg, **kw`. We can simulate this by removing it from the method in question:
```diff
diff --git a/alembic/operations/base.py b/alembic/operations/base.py
index 90b3500..a5b0706 100644
--- a/alembic/operations/base.py
+++ b/alembic/operations/base.py
@@ -171,7 +171,7 @@ class Operations(util.ModuleClsProxy):
yield op
op._remove_proxy()
- @contextmanager
+ #@contextmanager
def batch_alter_table(
self,
table_name,
```
then we get a simple import error:
```
$ PYTHONPATH=~/dev/sqlalchemy/lib/ python -m alembic
Traceback (most recent call last):
File "/opt/python-3.7.0/lib/python3.7/runpy.py", line 183, in _run_module_as_main
mod_name, mod_spec, code = _get_module_details(mod_name, _Error)
File "/opt/python-3.7.0/lib/python3.7/runpy.py", line 142, in _get_module_details
return _get_module_details(pkg_main_name, error)
File "/opt/python-3.7.0/lib/python3.7/runpy.py", line 109, in _get_module_details
__import__(pkg_name)
File "/home/classic/dev/alembic/alembic/__init__.py", line 5, in <module>
from . import op # noqa
File "/home/classic/dev/alembic/alembic/op.py", line 5, in <module>
Operations.create_module_class_proxy(globals(), locals())
File "/home/classic/dev/alembic/alembic/util/langhelpers.py", line 56, in create_module_class_proxy
cls._setup_proxy(globals_, locals_, attr_names)
File "/home/classic/dev/alembic/alembic/util/langhelpers.py", line 61, in _setup_proxy
cls._add_proxied_attribute(methname, globals_, locals_, attr_names)
File "/home/classic/dev/alembic/alembic/util/langhelpers.py", line 69, in _add_proxied_attribute
methname, globals_, locals_
File "/home/classic/dev/alembic/alembic/util/langhelpers.py", line 176, in _create_method_proxy
exec_(func_text, globals_, lcl)
File "<string>", line 1, in <module>
NameError: name 'immutabledict' is not defined
```
because it doesn't have the "util" prefix that the actual code does:
```
def batch_alter_table(
self,
table_name,
schema=None,
recreate="auto",
copy_from=None,
table_args=(),
table_kwargs=util.immutabledict(),
reflect_args=(),
reflect_kwargs=util.immutabledict(),
naming_convention=None,
):
``` | closed | 2019-03-29T17:18:23Z | 2019-03-30T03:28:15Z | https://github.com/sqlalchemy/alembic/issues/548 | [] | zzzeek | 1 |
xuebinqin/U-2-Net | computer-vision | 160 | ModuleNotFoundError: No module named 'PIL' | Having problems with
from PIL import Image
though I have the following installed in PyCharm venv on Windows 10:
pillow
When trying to install PIL it tells me:
`pip install PIL
ERROR: Could not find a version that satisfies the requirement PIL
ERROR: No matching distribution found for PIL
` | open | 2021-01-31T13:45:58Z | 2021-01-31T13:45:58Z | https://github.com/xuebinqin/U-2-Net/issues/160 | [] | coveritytest | 0 |
strawberry-graphql/strawberry | django | 3,503 | Support explicit setting of federation version | ## Feature Request Type
- [ ] Core functionality
- [x] Alteration (enhancement/optimization) of existing feature(s)
- [ ] New behavior
## Description
The latest version of strawberry supports federation v2.7 and hardcodes the directive urls as such: https://github.com/strawberry-graphql/strawberry/pull/3420
The apollo federation version at my company is v2.5 so I've updated our schema generator to manually replace `v2.7` with `v2.5`
It would be nice to be able to set this at the schema level, e.g.
`federation.Schema(query=Query, federation_version="v2.5")`
At first glance it seems relatively straightforward:
1. Add `federation_version` argument to the schema, default to `"v2.7"` if `enable_federation_2=True`
2. Set `enable_federation_2=True` if federation_version >= 2
3. Update schema urls with the version so the schema generator writes that version
But I imagine that the versioning actually changes underlying support, so then there are outstanding questions:
* Would we support old federation versions and new ones?
* Would we have to validate the version number against what features are supported?
* Would we just trust the user that they know which features are available if they're setting the version explicity?
* Would it be preferable to overwrite the `print_schema` function with version instead?
Not sure what the approach should be, but I don't think this library should dictate the federation version, and more explicitly, I think that users of this library should be able to get library updates unrelated to federation version, rather than having to pin to the version before some federation version was explicitly supported / mandated. | open | 2024-05-16T16:46:49Z | 2025-03-20T15:56:44Z | https://github.com/strawberry-graphql/strawberry/issues/3503 | [
"enhancement",
"discussion",
"federation"
] | bradleyoesch | 5 |
Yorko/mlcourse.ai | seaborn | 678 | time series part 1: weighted_average, weights order | In the `weighted_average` function [here](https://mlcourse.ai/articles/topic9-part1-time-series/), larger weights need to be assigned to more recent observations, however, that's not the case for the implementation. | closed | 2021-01-03T23:52:28Z | 2021-01-04T00:15:14Z | https://github.com/Yorko/mlcourse.ai/issues/678 | [
"minor_fix"
] | Yorko | 1 |
suitenumerique/docs | django | 245 | Can't copy paste content from the doc itself | ## Bug Report
**Problematic behavior**
I can't copy paste content from the doc I'm working on.
When I copy paste from outside the docs it works
**Steps to Reproduce**
1. Select content on the doc
2. Ctrl + C
3. Ctrl + V
4. Nothing happens
**Environment**
docs.numerique.gouv.fr on firefox
- Impress version:
- Platform:
**Possible Solution**
<!--- Only if you have suggestions on a fix for the bug -->
**Additional context/Screenshots**
Add any other context about the problem here. If applicable, add screenshots to help explain.
| closed | 2024-09-11T13:39:16Z | 2024-10-17T15:15:23Z | https://github.com/suitenumerique/docs/issues/245 | [
"bug",
"good first issue",
"frontend",
"editor",
"Firefox"
] | virgile-dev | 3 |
piskvorky/gensim | nlp | 2,760 | Proper tokenizers for pretrained word embeddings models? | #### Problem description
I wan't to tokenize the text the same way it was tokenized when the model was trained. For example, google-news word2vec has separate vectors for common phrases, like San Francisco. It is also not clear which tokenizer to use for other models, like, how to handle apostrophes in words like "shouldn't".
Is there any general way to do so? | closed | 2020-02-24T09:29:42Z | 2020-02-24T10:18:02Z | https://github.com/piskvorky/gensim/issues/2760 | [] | IvanLazarevsky | 1 |
jupyter/docker-stacks | jupyter | 1,908 | Support installing RStudio Server on jupyter/datascience-notebook | ### What docker image(s) is this feature applicable to?
datascience-notebook
### What changes are you proposing?
I'm trying to install Rstudio-Server on `jupyter/datascience-notebook:hub-4.0.0`. However, facing error `libc6-i386 : Depends: libc6 (= 2.31-0ubuntu9.9) but 2.35-0ubuntu3.1 is to be installed`. Thanks.
```
FROM jupyter/datascience-notebook:hub-4.0.0
USER root
WORKDIR /tmp
# https://posit.co/download/rstudio-server/
RUN apt-get update && \
apt-get install -y --no-install-recommends \
file \
git \
libapparmor1 \
libclang-dev \
libcurl4-openssl-dev \
libedit2 \
libobjc4 \
libssl-dev \
libpq5 \
lsb-release \
psmisc \
procps \
python-setuptools \
pwgen \
sudo \
wget
RUN wget https://download2.rstudio.org/server/jammy/amd64/rstudio-server-2023.03.1-446-amd64.deb -O rstudio-server.deb && \
dpkg -i rstudio-server.deb && \
rm rstudio-server.deb
```
### How does this affect the user?
New feature for Rstudio users.
### Anything else?
_No response_ | closed | 2023-05-28T12:10:01Z | 2023-06-02T12:48:29Z | https://github.com/jupyter/docker-stacks/issues/1908 | [
"type:Enhancement",
"status:Need Info"
] | ShichenXie | 3 |
chezou/tabula-py | pandas | 217 | ImportError: No module named 'pandas.errors' while importing tabula | <!--- Provide a general summary of your changes in the Title above -->
# Summary of your issue
<!-- Write the summary of your issue here -->
`import tabula`
```
ImportError Traceback (most recent call last)
<ipython-input-36-21d3fd5ede8c> in <module>
----> 1 import tabula
/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/tabula/__init__.py in <module>
1 from pkg_resources import DistributionNotFound, get_distribution
2
----> 3 from .io import convert_into, convert_into_by_batch, read_pdf, read_pdf_with_template
4 from .util import environment_info
5
/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/tabula/io.py in <module>
31 import pandas as pd
32
---> 33 from .errors import CSVParseError, JavaNotFoundError
34 from .file_util import localize_file
35 from .template import load_template
/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/tabula/errors/__init__.py in <module>
----> 1 from pandas.errors import ParserError
2
3
4 class CSVParseError(ParserError):
5 """Error represents CSV parse error, which mainly caused by pandas.
ImportError: No module named 'pandas.errors'
```
## environment_info
Running ipython notebook in python3 environment
`>>ipython3 notebook`
`>> python3 --version`
`Python 3.5.0`
`>>java -version`
`java version "1.8.0_60"
Java(TM) SE Runtime Environment (build 1.8.0_60-b27)
Java HotSpot(TM) 64-Bit Server VM (build 25.60-b23, mixed mode)`
`MacOS High Seria`
```
Package Version
---------------------------
ipykernel 5.1.4
ipython 7.9.0
notebook 6.0.3
numpy 1.11.2
pandas 0.19.0
pip 20.0.2
six 1.14.0
tabula-py 2.0.4
wheel 0.31.0
```
| closed | 2020-02-13T02:40:01Z | 2020-02-13T03:08:32Z | https://github.com/chezou/tabula-py/issues/217 | [] | zkid18 | 2 |
thtrieu/darkflow | tensorflow | 421 | AssertionError with four byte size difference when converting | I'm getting a rather weird error trying to convert a `darknet` trained Tiny YOLO (adjusted model, transfer learned using a custom dataset) using `flow --savepb`, which complains about finding an unexpected file size. The size difference appears to be exactly four bytes though:
```python
Traceback (most recent call last):
File "./flow", line 6, in <module>
cliHandler(sys.argv)
File "/home/mmayer/dev/ml/darkflow/darkflow/cli.py", line 22, in cliHandler
tfnet = TFNet(FLAGS)
File "/home/mmayer/dev/ml/darkflow/darkflow/net/build.py", line 58, in __init__
darknet = Darknet(FLAGS)
File "/home/mmayer/dev/ml/darkflow/darkflow/dark/darknet.py", line 27, in __init__
self.load_weights()
File "/home/mmayer/dev/ml/darkflow/darkflow/dark/darknet.py", line 82, in load_weights
wgts_loader = loader.create_loader(*args)
File "/home/mmayer/dev/ml/darkflow/darkflow/utils/loader.py", line 105, in create_loader
return load_type(path, cfg)
File "/home/mmayer/dev/ml/darkflow/darkflow/utils/loader.py", line 19, in __init__
self.load(*args)
File "/home/mmayer/dev/ml/darkflow/darkflow/utils/loader.py", line 77, in load
walker.offset, walker.size)
AssertionError: expect 63184556 bytes, found 63184560
```
I was trying it with different versions of TensorFlow, specifically 1.0.1 and 1.3.1, but that didn't change anything.
Does anyone have an idea what could trigger this issue?
| open | 2017-11-03T12:53:45Z | 2019-09-23T08:16:19Z | https://github.com/thtrieu/darkflow/issues/421 | [] | sunsided | 17 |
kiwicom/pytest-recording | pytest | 78 | [FEATURE] Parameterize vcr_config | **Is your feature request related to a problem? Please describe.**
I'm working on a library that supports multiple web services behind a single interface.
Now I've written some tests for that interface and would like to run them for each of the web services I support. This is where pytest's fixture parameterization shines and it works well without VCR in the picture, the implementations simply make real requests.
Obviously that's not ideal, so I wanna use VCR. I need different configurations for each web service though. Unfortunately I can't find a way to parameterize vcr_config.
**Describe the solution you'd like**
No idea, sorry.
**Describe alternatives you've considered**
I guess I could use the vcr fixture somehow?
| open | 2021-10-10T21:19:04Z | 2021-10-10T21:19:04Z | https://github.com/kiwicom/pytest-recording/issues/78 | [
"Status: Review Needed",
"Type: Feature"
] | dAnjou | 0 |
vimalloc/flask-jwt-extended | flask | 145 | Why do we need a separate fresh login endpoint? | Hi,
It's more of a best practice question. I've been working on this extension recently. And I noticed that in the documentation, it is recommended to create three endpoints `/login`, `/refresh` and `/fresh-login`.
I can understand that we don't want the user to login via credentials every time thus we need the `/refresh` endpoint. But I'm not sure about the `/fresh-login` endpoint, since that the `/login` endpoint gives us a fresh access token already.
I understand the concern that we don't want to generate refresh tokens over and over again. But my argument would be that, in practice, we only need the user authenticates via credentials once in a long period of time, and meanwhile, he only needs to use the refresh token to re-authenticate. I feel like using the `/login` endpoint would be sufficient as opposed to introducing another `/fresh-login` endpoint, and there wouldn't be an abuse of generating refresh tokens.
Please let me know if I erred. Thank you.
| closed | 2018-05-03T19:46:38Z | 2018-05-03T22:31:09Z | https://github.com/vimalloc/flask-jwt-extended/issues/145 | [] | CristianoYL | 4 |
3b1b/manim | python | 1,294 | Subsequent fade on submobject of TexMobject not behaving as epected | I would like to fade out and fade in a submobject of a TexMobject. In my example below, I would like to see the "B" disappearing and appearing again. However, on my system the fade in does not work. The B remains faded out.
Is my assumption on the expected behavior correct? Or am I using the wrong approach for the second call to the fade method? I would appreciate any tips or hints!
I am on manimlib 0.1.11 in a linux environment.
Thanks for the great library!
```
class FadeInFadeOutSubMobject(Scene):
def construct(self):
text = TexMobject("A","B","C")
self.play(FadeIn(text))
self.wait(1)
self.play(FadeOut(text))
text[1].fade(1)
self.wait(1)
self.play(FadeIn(text))
self.wait(1)
self.play(FadeOut(text))
text[1].fade(0)
self.play(FadeIn(text))
self.wait(1)
```
| closed | 2020-12-19T18:15:04Z | 2020-12-20T08:24:05Z | https://github.com/3b1b/manim/issues/1294 | [] | msmart | 2 |
proplot-dev/proplot | matplotlib | 359 | ax.step where parameter | ### Description
In `ax.step`, the 'where' parameter doesn't do anything in proplot.
### Steps to reproduce
```python
import numpy as np
import proplot as pplt
x = np.linspace(-5.0, 5.0, 11)
y = np.exp(-0.5 * x**2)
fig, axes = pplt.subplots(nrows=3, figsize=(4.0, 3.0), spany=False)
for ax, where in zip(axes, ['pre', 'post', 'mid']):
ax.step(x, y, where=where, color='black', alpha=0.2)
ax.scatter(x, y, color='black', marker='.')
ax.format(ylabel=where)
```
**Expected behavior**: The `where` parameter should shift the locations of the steps.
**Actual behavior**: The `where` parameter does not shift the locations of the steps.
### Equivalent steps in matplotlib
```python
import numpy as np
from matplotlib import pyplot as plt
x = np.linspace(-5.0, 5.0, 11)
y = np.exp(-0.5 * x**2)
fig, axes = plt.subplots(nrows=3, figsize=(4.0, 3.0), sharex=True)
for ax, where in zip(axes, ['pre', 'post', 'mid']):
ax.step(x, y, where=where, color='black', alpha=0.2)
ax.scatter(x, y, color='black', marker='.')
ax.set_ylabel(where)
```
### Proplot version
matplotlib=3.4.3
proplot=0.9.5 | closed | 2022-05-15T18:27:42Z | 2023-03-29T22:11:56Z | https://github.com/proplot-dev/proplot/issues/359 | [
"bug"
] | austin-hoover | 3 |
plotly/dash-table | dash | 450 | Conditional formatting in for loop broken since upgrade to 0.3.7 | The conditional formatting stopped working since upgrading to 0.3.7 when used in a for loop.
Below code used to work fine in previous versions:
```
[{
'if': {'column_id': str(x), 'filter': '{} < num(0.9)'.format(x)},
'background-color': '#9cd5ac'
} for x in ['column1','column2']
]
```
I found out that the numbers expression needs to be changed from num(0.9) to just 0.9, otherwise it will throw an error: "unable to evaluate target: syntax tree is invalid"
When I remove the num(), the error is gone but the conditional formatting still does not work.
How do I have to adapt my code? | closed | 2019-05-30T14:11:16Z | 2019-05-30T19:40:20Z | https://github.com/plotly/dash-table/issues/450 | [] | philspbr | 3 |
flairNLP/flair | nlp | 2,991 | Building token embeddings from subtokens (subtoken_pooling) | I have a question regarding how the (FLAIR) token embeddings are generated from the subtoken embeddings, which are the outputs of the TransformerWordEmbeddings.
In the [docs ](https://github.com/flairNLP/flair/blob/master/resources/docs/TUTORIAL_7_TRAINING_A_MODEL.md#training-a-named-entity-recognition-ner-model-with-transformers) and [paper](https://arxiv.org/pdf/2011.06993.pdf) you recommend using the `subtoken_pooling="first"`.
However, I have found the following paper **[Subword Pooling Makes a Difference](https://aclanthology.org/2021.eacl-main.194.pdf)** that actually advises the opposite, that is using the "last" subtoken. This is proven by using an attention mechanism on the token level.
My question is, have you experimented with other subtokien_pooling policies? | closed | 2022-11-16T10:08:57Z | 2023-06-11T11:25:47Z | https://github.com/flairNLP/flair/issues/2991 | [
"question",
"wontfix"
] | kobiche | 3 |
pallets/flask | flask | 4,656 | Two Flask server spawned using multiprocessing not working as expected. | **Issue Outline**
I tried to spawn two Flask processes using `multiprocessing` library as mentioned below.
The response from the server is fluctuating/crossing between the two server's '/' route.
More information on: https://stackoverflow.com/questions/72758633/two-flask-processes-spawned-using-multiprocessing-are-not-working-properly
**Reproducer Code:**
```
# ======================= server 1 ======================
from flask import Flask
app1 = Flask("App1")
@app1.route('/')
def index1():
return "Hello This is app 1"
class FlaskApp1:
def start(self):
global app1
app1.run(host="0.0.0.0", port=6000, debug=True)
# ======================= server 2 ======================
app2 = Flask("App2")
@app2.route('/')
def index2():
return "Hello This is app 2"
class FlaskApp2:
def start(self):
global app2
app2.run(host="0.0.0.0", port=7000, debug=True)
# ======================= MAIN ======================
from multiprocessing import Process
if __name__ == "__main__":
p1 = Process(target=FlaskApp1().start, args=())
p2 = Process(target=FlaskApp2().start, args=())
p1.start()
p2.start()
p1.join()
p2.join()
```
**Output:**
The response is fluctuating between the '/' route of two servers
```
======== From Server 1 ==========
# curl localhost:6000
Hello This is app 1
# curl localhost:6000
Hello This is app 2
# curl localhost:6000
Hello This is app 1
# curl localhost:6000
Hello This is app 2
# curl localhost:6000
Hello This is app 1
# curl localhost:6000
Hello This is app 2
# curl localhost:6000
Hello This is app 1
# curl localhost:6000
Hello This is app 2
========= From server 2 ==========
# curl localhost:7000
Hello This is app 1
# curl localhost:7000
Hello This is app 2
# curl localhost:7000
Hello This is app 1
# curl localhost:7000
Hello This is app 2
# curl localhost:7000
Hello This is app 1
# curl localhost:7000
Hello This is app 1
# curl localhost:7000
Hello This is app 2
```
**Expected Behavior:**
The request on port 6000 should consistently return `Hello This is app 1` and server for port 7000 should consistently return `Hello This is app 2` on multiple request request.
**Environment:**
python3 = 3.7.10
Flask = 1.1.2, 2.1.2
| closed | 2022-06-28T15:32:51Z | 2022-07-02T21:56:23Z | https://github.com/pallets/flask/issues/4656 | [] | sssyam | 3 |
ckan/ckan | api | 7,576 | Cannot update language translations | CKAN version 2.9.8
Trying to update language translation in English to change default CKAN labels following: https://docs.ckan.org/en/2.9/contributing/i18n.html
No error messages when compiling po file to generate mo file. However, interface labels are not being updated. Tested this across different languages with the same outcome. This was previously working. Any suggestions?
| open | 2023-05-04T21:15:35Z | 2023-06-03T10:23:45Z | https://github.com/ckan/ckan/issues/7576 | [] | isomemo | 4 |
ray-project/ray | machine-learning | 51,634 | [core/scheduler] Split giant ray core C++ target into small ones | Subissue of #50586 . | open | 2025-03-24T06:35:47Z | 2025-03-24T06:37:37Z | https://github.com/ray-project/ray/issues/51634 | [
"enhancement",
"core"
] | Ziy1-Tan | 1 |
marcomusy/vedo | numpy | 939 | Allow for cloning a mesh-inherited class to retain its class type | Currently if you clone a vedo.Plane, it converts it into a vedo.Mesh (the parent class) and loses attributes such as "normal". It would be useful for the copy to remain as a vedo.Plane. | closed | 2023-10-03T22:44:49Z | 2023-11-16T10:53:10Z | https://github.com/marcomusy/vedo/issues/939 | [
"enhancement",
"fixed"
] | JeffreyWardman | 1 |
paperless-ngx/paperless-ngx | machine-learning | 8,418 | 2006, 'Server has gone away' | I see some issues and at least one discussion, regarding topic "2006, 'Server has gone away'". All of them are closed, some are marked as being not a bug. However, I am facing this issue as well when using paperless-ngx via docker compose, but using an external MariaDB instance.
It happens predictable, when processing a PDF takes some time. In my case when analysing a PDF attachment from an E-Mail being retrieved by a workflow.
| closed | 2024-12-03T14:52:47Z | 2024-12-03T15:00:41Z | https://github.com/paperless-ngx/paperless-ngx/issues/8418 | [
"not a bug"
] | m0wlheld | 2 |
python-gino/gino | asyncio | 632 | [question] how manage alter with Gino | * GINO version: 0.8.5
* Python version: 3.8.1
* asyncpg version: 0.20.1
* aiocontextvars version: 0.2.2
* PostgreSQL version: 11
### Description
I created a table `test` to see if alter are manager by Gino,
```
class Test(db.Model):
__tablename__ = "test"
id = db.Column(db.Integer(), primary_key=True)
foo = db.Column(db.Integer())
async def main():
await db.set_bind("postgresql://test:test@localhost/test")
await db.gino.create_all()
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
```
the table is created successfully but I'm thinking about if it's possible to avoid "migration/upgrade script" or at least avoid an alter part, like
```
class Test(db.Model):
__tablename__ = "test"
id = db.Column(db.Integer(), primary_key=True)
foo = db.Column(db.Integer())
bar = db.Column(db.Integer())
```
will automatically altert the table (btw in this case it should raise exception because there is no default value or nullable=True) | closed | 2020-02-17T10:56:03Z | 2020-04-20T23:04:32Z | https://github.com/python-gino/gino/issues/632 | [
"question"
] | flapili | 4 |
google-research/bert | nlp | 885 | How many "num_tpu_cores" be set ? | I try to pretraining with **run_pretraining.py** using **tpu-v2-32**
How many "num_tpu_cores" be set ?
When tested with tpu-v2-8 worked fine(num_tpu_cores=8).
python3 run_pretraining.py \
--input_file=gs://... \
--output_dir=gs://... \
--do_train=True \
--do_eval=True \
--bert_config_file=/data/workspace/bert/bert_config.json \
--train_batch_size=64 \
--max_seq_length=128 \
--max_predictions_per_seq=19 \
--num_train_steps=100 \
--num_warmup_steps=70 \
--learning_rate=1e-4 \
--use_tpu=True \
--num_tpu_cores=32 \
--tpu_name=grpc://ip:8470 \
--tpu_zone=us-central1-a \
--gcp_project=myproject
**This are parameters to run. Is that correct? When i do this, i got an error like this :**
ValueError: TPUConfig.num_shards is not set correctly. According to TPU system metadata for Tensorflow master (grpc://...:8470): num_replicas should be (8), got (32). For non-model-parallelism, num_replicas should be the total num of TPU cores in the system. For model-parallelism, the total number of TPU cores should be num_cores_per_replica * num_replicas. Please set it accordingly or leave it as `None`
**When i set "num_tpu_cores=8", I got the following error :**
I1025 05:22:42.688320 140065835681600 tpu_estimator.py:557] Init TPU system
ERROR:tensorflow:Error recorded from evaluation_loop: From /job:worker/replica:0/task:0:
Cloud TPU: Invalid TPU configuration, ensure ClusterResolver is passed to tpu.RunConfig
[[{{node configure_distributed_tpu/_0}}]]
Am I missing something else? Or which one should I set?
| closed | 2019-10-25T05:27:02Z | 2020-08-08T12:39:57Z | https://github.com/google-research/bert/issues/885 | [] | jwkim912 | 2 |
microsoft/qlib | deep-learning | 1,791 | Client Error when downloading data | Dear authors:
I've just faced the client error when executing the codes illustrated in your official documentation:
> # download 1d
> python scripts/get_data.py qlib_data --target_dir ~/.qlib/qlib_data/cn_data --region cn
>
> # download 1min
> python scripts/get_data.py qlib_data --target_dir ~/.qlib/qlib_data/qlib_cn_1min --region cn --interval 1min
>
>
or
> from qlib.tests.data import GetData
>
> GetData().qlib_data(exists_skip=True)
> requests.exceptions.HTTPError: 403 Client Error: Server failed to authenticate the request. Make sure the value of Authorization header is formed correctly including the signature. for url: https://qlibpublic.blob.core.windows.net/data/default/stock_data/v2/qlib_data_cn_1d_0.9.zip?sv=2020-10-02&st=2023-06-21T00%3A58%3A06Z&se=2043-06-22T00%3A58%3A00Z&sr=c&sp=rl&sig=ykiWECM7%2BsPLXE32ZM6p2Tc1mMDeUaCmo8LD%2BOKiAo4%3D
May I wonder is there any solution?
Envs:
Mac ( Intel )
python3.8
the latest version of qlib | closed | 2024-05-22T07:57:25Z | 2024-05-24T05:44:23Z | https://github.com/microsoft/qlib/issues/1791 | [
"question"
] | Yottaxx | 1 |
scrapy/scrapy | web-scraping | 6,553 | Recommendation for docstring for functions and classes in the file exporters.py | <!--
Thanks for taking an interest in Scrapy!
If you have a question that starts with "How to...", please see the Scrapy Community page: https://scrapy.org/community/.
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The following is a suggested template to structure your issue, you can find more guidelines at https://doc.scrapy.org/en/latest/contributing.html#reporting-bugs
-->
### Description
The exporters.py file lacks consistent docstrings for its functions and classes. While some docstrings are present, many are either missing or incomplete. This inconsistency can make it challenging for developers, especially newcomers, to understand the purpose and usage of these components without delving deep into the implementation. This affects the maintainability and readability of the code.
### Steps to Reproduce
- Open the exporters.py file in the Scrapy codebase.
- Inspect the classes and functions, noting missing or incomplete docstrings.
- Compare this with the expectations outlined in Python's PEP 257 guidelines for docstrings.
**Expected behavior:**
Each class should have a clear and concise docstring describing:
- The purpose of the class.
- An overview of its main methods and attributes.
Each function should have a docstring explaining:
- Its purpose.
- Input parameters, their types, and expected values.
- Return values and their types.
- Any side effects, exceptions raised, or special behaviors.
**Actual behavior:**
Many classes and functions in exporters.py lack docstrings. Existing docstrings, where present, are inconsistent in detail and format.
**Reproduces how often:**
100% of the time when inspecting exporters.py.
### Versions
Please paste here the output of executing `scrapy version --verbose` in the command line.
### Additional context
Any additional information, configuration, data or output from commands that might be necessary to reproduce or understand the issue. Please try not to include screenshots of code or the command line, paste the contents as text instead. You can use [GitHub Flavored Markdown](https://help.github.com/en/articles/creating-and-highlighting-code-blocks) to make the text look better.
| closed | 2024-11-20T04:20:53Z | 2024-11-20T19:13:56Z | https://github.com/scrapy/scrapy/issues/6553 | [] | dami1025 | 2 |
horovod/horovod | tensorflow | 3,268 | Unable to load most recent checkpoint for Pytorch and Pytorch lightning Estimator | **Environment:**
1. Framework: PyTorch
2. Framework version: 1.8.1
3. Horovod version: 0.23.0
4. MPI version:
5. CUDA version:
6. NCCL version:
7. Python version: 3.8
8. Spark / PySpark version: 3.1.2
9. Ray version:
10. OS and version:
11. GCC version:
12. CMake version:
**Bug report:**
In case of pytorch lightning estimator, the _read_checkpoint() API does not return the latest checkpoint stored in the run path.
Reason: Pytorch lightning estimator calls store.get_checkpoints() which looks for a folder named 'checkpoint' in run path while there is no folder named checkpoint, instead there is a temp folder generated via tempfile.TemporaryDirectory()
In case of pytorch estimator, the checkpoint stored in run path is not overwritten if multiple iterations are done using the same run path, which leads to _load_checkpoint() API returning the stale checkpoint.
| closed | 2021-11-10T11:34:06Z | 2021-11-23T07:12:35Z | https://github.com/horovod/horovod/issues/3268 | [
"bug"
] | kamalsharma2 | 3 |
learning-at-home/hivemind | asyncio | 581 | forking before initialization of the MPFuture handler - server runtime not initialized in WSL --new_hive | Apparently there is an issue of forking before initialization of the MPFuture handler. It happens when running private hive under WSL. No such problem happens when runnging pure linux or WSL with real hive.
What likely happens:
--> The ConnectionHandlers were created - as a process - while we were still initializing the background thread - the MPFuture handler - and they forked the state of the main process, in which the MPFuture handler was not fully initialized - and was broken.
--> the `ConnectionHandlers` could not write self.ready.set_result - this method is serviced by their (broken) MPFuture handler.
--> the ModuleContainer got stuck in run -> handler.run_in_background -> handler.wait_until_ready().
--> the ModuleContainer never reached Runtime.run() - it was called after handler.run_in_background().
--> the Runtime never started processing batches.
--> the connection handlers, which received a request from the client, gave the task to the Runtime, but did not receive a response - the Runtime was never launched.
--> the client did not receive a response from the server.
How to reproduce:
run in WSL: `HIVEMIND_LOGLEVEL=DEBUG python -m petals.cli.run_server bigscience/bloom-560m --new_swarm --identity tests/test.id --host_maddrs /ip4/127.0.0.1/tcp/32337 --throughput 1 --torch_dtype float32 --compression NONE --attn_cache_tokens 2048 --max_chunk_size_bytes 1024`
Problem symptoms:
Server runtime seems inactive.
- no message `Started`
- not responding to client calls
**Environment**
Please list:
* python version (e.g. 3.8.1); 3.10
* hivemind.__version__; 1.1.9
* Please copy and paste the output from pytorch [environment collection script](https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py)
If the script doesn't work, please report pytorch and numpy versions manually. We also encourage you to include any additional information that you believe can help us solve the issue.
PyTorch version: 2.0.1
Is debug build: False
CUDA used to build PyTorch: 11.7
ROCM used to build PyTorch: N/A
OS: Ubuntu 20.04.5 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.16.3
Libc version: glibc-2.31
Python version: 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:40:32) [GCC 12.3.0] (64-bit runtime)
Python platform: Linux-5.15.90.1-microsoft-standard-WSL2-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3090
Nvidia driver version: 531.79
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
Address sizes: 48 bits physical, 48 bits virtual
CPU(s): 16
On-line CPU(s) list: 0-15
Thread(s) per core: 2
Core(s) per socket: 8
Socket(s): 1
Vendor ID: AuthenticAMD
CPU family: 23
Model: 8
Model name: AMD Ryzen 7 2700X Eight-Core Processor
Stepping: 2
CPU MHz: 3700.062
BogoMIPS: 7400.12
Hypervisor vendor: Microsoft
Virtualization type: full
L1d cache: 256 KiB
L1i cache: 512 KiB
L2 cache: 4 MiB
L3 cache: 16 MiB
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Retbleed: Mitigation; untrained return thunk; SMT vulnerable
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Retpolines, IBPB conditional, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid pni pclmulqdq ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext ssbd ibpb vmmcall fsgsbase bmi1 avx2 smep bmi2 rdseed adx smap clflushopt sha_ni xsaveopt xsavec xgetbv1 xsaves clzero xsaveerptr virt_ssbd arat
Versions of relevant libraries:
[pip3] mypy==0.991
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.22.4
[pip3] torch==2.0.1
[pip3] triton==2.0.0
[conda] blas 2.16 mkl conda-forge
[conda] libblas 3.8.0 16_mkl conda-forge
[conda] libcblas 3.8.0 16_mkl conda-forge
[conda] liblapack 3.8.0 16_mkl conda-forge
[conda] liblapacke 3.8.0 16_mkl conda-forge
[conda] mkl 2020.2 256
[conda] numpy 1.25.1 pypi_0 pypi
[conda] pytorch 2.0.1 py3.10_cuda11.7_cudnn8.5.0_0 pytorch
[conda] pytorch-cuda 11.7 h778d358_5 pytorch
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torchtriton 2.0.0 py310 pytorch | open | 2023-08-01T22:31:50Z | 2023-08-03T20:48:38Z | https://github.com/learning-at-home/hivemind/issues/581 | [
"bug"
] | poedator | 1 |
lanpa/tensorboardX | numpy | 158 | the problem about add_image | Hello,I want to draw a attention picture,but when I use the function of add_image,I find have no image to writer.However, the function of add_scaler to be used will generate some files.
PyTorch 0.4 / torchvision 0.2 / tensorboard 1.7.0 | closed | 2018-06-04T08:40:52Z | 2018-06-11T02:09:35Z | https://github.com/lanpa/tensorboardX/issues/158 | [] | travel-go | 3 |
AutoViML/AutoViz | scikit-learn | 115 | Issue installing AutoViz on Kaggle Notebook | Hi!
I have encountered the below error when trying to install AutoViz on Kaggle Notebook. Is there any solutions? thanks.
| closed | 2024-11-11T14:32:59Z | 2025-01-28T21:37:08Z | https://github.com/AutoViML/AutoViz/issues/115 | [] | vincentfeng9109 | 1 |
biolab/orange3 | data-visualization | 6,065 | Group By: Add quartile outputs | <!--
Thanks for taking the time to submit a feature request!
For the best chance at our team considering your request, please answer the following questions to the best of your ability.
-->
**What's your use case?**
I would like to summarize large datasets through the 5-number set (minimum, Q1, median, Q3, maximum) + mean, but quartiles are not available in the Group By GUI.
**What's your proposed solution?**
<!-- Be specific, clear, and concise. -->
Integrate quartile computations and 1 or 2 check boxes ("Quartiles" or "First quartile" / "Third quartile") in the GUI of the Group By widget.
**Are there any alternative solutions?**
These can be computed with a custom python script using pandas in the meantime.
| closed | 2022-07-18T13:27:47Z | 2023-01-27T13:55:22Z | https://github.com/biolab/orange3/issues/6065 | [
"wish",
"snack"
] | chourroutm | 4 |
onnx/onnx | machine-learning | 5,989 | SegFault during shape inference if the schema not be set inference function | # Bug Report
### Describe the bug
SegFault during shape inference if the schema not be set inference function
### Reproduction instructions
cpp (Optional):
```
ONNX_OPERATOR_SCHEMA(CustomOp);
```
python:
```
import onnx
from onnx import defs
input = """
<
ir_version: 7,
opset_import: [
"" : 1
]
>
agraph (float[N, 128] X, int32 Y) => (float[N] Z)
{
Z = CustomOp(X, Y)
}
"""
model = onnx.parser.parse_model(input)
op_schema = defs.OpSchema(
'CustomOp',
'',
1,
inputs=[
],
outputs=[
],
)
# Uncomment if not register in cpp
# onnx.defs.register_schema(op_schema)
onnx.shape_inference.infer_shapes(model, True)
```
### Expected behavior
Raise a python exception rather than crash.
### Notes
The root case is the input or output of schema is empty and the corresponding field in graph is no-empty. So the `input.back` from schema will invalid.
| closed | 2024-03-02T15:23:13Z | 2024-03-04T22:07:42Z | https://github.com/onnx/onnx/issues/5989 | [
"bug"
] | OYCN | 0 |
adbar/trafilatura | web-scraping | 196 | updated benchmarks | there have been several significant releases since the last benchmark 10 months ago, I'm curious if there have been any notable changes there.
https://trafilatura.readthedocs.io/en/latest/evaluation.html#results-2021-06-07 | closed | 2022-04-13T21:57:58Z | 2022-05-18T20:41:00Z | https://github.com/adbar/trafilatura/issues/196 | [
"question"
] | derekperkins | 3 |
1313e/CMasher | matplotlib | 32 | Colormap summary table | You mention in a documentation note that colormaps are sorted according to minimum and maximum lightness values, Starting (sequential) or central (diverging and cyclic) lightness value, Difference between the minimum and maximum lightness values and RMSE (root mean square error) of the derivative of the lightness profile. Could these quantities be centralized in a table?
| closed | 2021-04-06T10:02:44Z | 2021-05-11T06:48:32Z | https://github.com/1313e/CMasher/issues/32 | [
"feature request",
"awaiting response"
] | ycopin | 22 |
flairNLP/flair | nlp | 3,395 | Assertion error while reading training data | i am building it for my organisation, for indian addresses, i can import the libraries, make the labelled dataset
but while training the model there is a connection error, as my organisation doesn't allow pull requests from GitHub i guess
any workaround? | open | 2024-01-16T05:04:17Z | 2024-01-17T05:54:17Z | https://github.com/flairNLP/flair/issues/3395 | [
"question"
] | shubh-singhal | 0 |
pyqtgraph/pyqtgraph | numpy | 2,685 | This is not working in case parameterTree example | https://github.com/pyqtgraph/pyqtgraph/blob/7642e18e1d1ff569b1ef6db844c09280fc5fcddf/pyqtgraph/examples/_buildParamTypes.py#L1 | closed | 2023-04-11T11:54:56Z | 2023-05-24T00:09:33Z | https://github.com/pyqtgraph/pyqtgraph/issues/2685 | [
"cannot reproduce"
] | yashwanth-eng | 3 |
A3M4/YouTube-Report | matplotlib | 13 | Step 5 console error | I get this error when I try to do step 5. I tried to upgrade pip using 'python -m pip installs --upgrade pip' but still doesn't works.
| closed | 2019-12-15T12:23:24Z | 2019-12-15T22:28:31Z | https://github.com/A3M4/YouTube-Report/issues/13 | [] | SpicySnow | 2 |
s3rius/FastAPI-template | fastapi | 40 | Database is not initialized without migrations | If you choose to skip adding migrations, you'll face this issue.
We must add a function in application's startup that initializes database using metadata. | closed | 2021-10-10T05:57:07Z | 2021-10-13T10:03:45Z | https://github.com/s3rius/FastAPI-template/issues/40 | [
"bug"
] | s3rius | 2 |
pytest-dev/pytest-qt | pytest | 437 | BUG: Multiple `PyQt`/`PySide` Versions Not Supported | ### Bug
I ran into this issue when trying to fix a bug with [pyvistaqt](https://qtdocs.pyvista.org/). It appears, for some reason, when all of
- `PyQt5`
- `PySide2`
- `PyQt6`
- `PySide6`
are installed, `pytest-qt` fails to create a `QApplication` instance, causing tests to silently fail.
**NOTE**: `QT_API` is not set to anything on my system when this occurs.
### System Information
OS: Windows 10, x64-bit
Python: 3.8.10 x64-bit (CPython)
pytest-qt: 4.1.0
### Steps to Reproduce
1. Clone the `pyvistaqt` repo and cd into the folder
```powershell
git clone https://github.com/pyvista/pyvistaqt.git
cd pyvistaqt
```
2. Create and activate a virtual environment
```powershell
py -m venv .venv && .venv\Scripts\Activate.ps1
```
3. Install dependencies
```powershell
py -m pip install --upgrade pip
py -m pip install -r requirements_test.txt
py -m pip install -r requirements_docs.txt
```
5. First, install only `PySide6`
```powershell
py -m pip install pyside6
```
6. Sanity Check: Run tests to verify everything is working correctly (All Pass)
```powershell
pytest
```
7. Now install `PyQt5`, `PySide2`, and `PyQt6`
```powershell
py -m pip install pyqt5 pyside2 pyqt6
```
8. Rerun `pytest` and tests will fail silently
```powershell
PS> pytest
=================================== test session starts =======================================
platform win32 -- Python 3.8.10, pytest-7.1.2, pluggy-1.0.0
PySide6 6.3.1 -- Qt runtime 6.3.1 -- Qt compiled 6.3.1
rootdir: %USERPROFILE%\Code\external\pyvistaqt-demo\pyvistaqt, configfile: pytest.ini
plugins: cov-3.0.0, memprof-0.2.0, mypy-plugins-1.9.3, mypy-testing-0.0.11, qt-4.1.0, sphinx-0.4.0
collected 2 items
tests\test_plotting.py
```
9. Re-run `pytest` in verbose mode while printing output to stdout/stderr
```powershell
PS> pytest -v -s
==================================== test session starts ======================================
platform win32 -- Python 3.8.10, pytest-7.1.2, pluggy-1.0.0 -- %USERPROFILE%\code\external\pyvistaqt-demo\pyvistaqt\.venv\scripts\python.exe
cachedir: .pytest_cache
PySide6 6.3.1 -- Qt runtime 6.3.1 -- Qt compiled 6.3.1
rootdir: %USERPROFILE%\Code\external\pyvistaqt-demo\pyvistaqt, configfile: pytest.ini
plugins: cov-3.0.0, memprof-0.2.0, mypy-plugins-1.9.3, mypy-testing-0.0.11, qt-4.1.0, sphinx-0.4.0
collected 2 items
tests/test_plotting.py::test_create_menu_bar QWidget: Must construct a QApplication before a QWidget
```
10. Add an `assert` to the offending test for details
```python
def test_create_menu_bar(qtbot):
assert QtWidgets.QApplication.instance() is not None
menu_bar = _create_menu_bar(parent=None)
qtbot.addWidget(menu_bar)
```
11. Rerun test in verbose mode while outputing to stdout/stderr
```powershell
PS> pytest -v -s
==================================== test session starts ======================================
platform win32 -- Python 3.8.10, pytest-7.1.2, pluggy-1.0.0 -- %USERPROFILE%\code\external\pyvistaqt-demo\pyvistaqt\.venv\scripts\python.exe
cachedir: .pytest_cache
PySide6 6.3.1 -- Qt runtime 6.3.1 -- Qt compiled 6.3.1
rootdir: %USERPROFILE%\Code\external\pyvistaqt-demo\pyvistaqt, configfile: pytest.ini
plugins: cov-3.0.0, memprof-0.2.0, mypy-plugins-1.9.3, mypy-testing-0.0.11, qt-4.1.0, sphinx-0.4.0
collected 2 items
tests/test_plotting.py::test_create_menu_bar FAILED
tests/test_qt.py::test_no_qt_binding PASSED
========================================= FAILURES ======================================
____________________________________________________________ test_create_menu_bar _________________________________________________________
qtbot = <pytestqt.qtbot.QtBot object at 0x00000237D940E160>
def test_create_menu_bar(qtbot):
> assert QtWidgets.QApplication.instance() is not None
E AssertionError: assert None is not None
E + where None = <built-in function instance>()
E + where <built-in function instance> = <class 'PyQt5.QtWidgets.QApplication'>.instance
E + where <class 'PyQt5.QtWidgets.QApplication'> = QtWidgets.QApplication
tests\test_plotting.py:79: AssertionError
================================== memory consumption estimates ==============================
tests::test_plotting.py::test_create_menu_bar - 40.0 KB
================================== short test summary info ====================================
FAILED tests/test_plotting.py::test_create_menu_bar - AssertionError: assert None is not None
================================== 1 failed, 1 passed in 0.79s ===================================
```
It appears there is a disconnect between the python `Qt` library registered by `pytest`:
```
PySide6 6.3.1 -- Qt runtime 6.3.1 -- Qt compiled 6.3.1
```
and the one picked up by `pytest-qt`
```
> assert QtWidgets.QApplication.instance() is not None
E AssertionError: assert None is not None
E + where None = <built-in function instance>()
E + where <built-in function instance> = <class 'PyQt5.QtWidgets.QApplication'>.instance
E + where <class 'PyQt5.QtWidgets.QApplication'> = QtWidgets.QApplication
```
### Expected Behavior
`pytest-qt` can be run with multiple versions of python Qt libraries installed simultaneously for testing purposes.
### Actual Behavior
`pytest-qt` has a disconnect between the python Qt binding registered with `pytest` and the one it uses. | open | 2022-06-27T16:19:50Z | 2022-07-04T04:28:52Z | https://github.com/pytest-dev/pytest-qt/issues/437 | [] | adam-grant-hendry | 9 |
ijl/orjson | numpy | 133 | orjson installation failed on github action MacOS + python 3.9 | Hi,
I'm using github action for CI and getting an error when trying to install orjson using pip.
Seems like a rustc issue. This only happens on python 3.9 + MacOS. I think Ubuntu and Windows + python 3.9 and MacOS + python 3.8- works fine.
I also tried to install the tool chain using actions-rs/toolchain@v1 but it's still failing.
Any suggestions?
Collecting orjson
Downloading orjson-3.4.0.tar.gz (655 kB)
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing wheel metadata: started
Preparing wheel metadata: finished with status 'error'
ERROR: Command errored out with exit status 1:
command: /Users/runner/hostedtoolcache/Python/3.9.0/x64/bin/python /Users/runner/hostedtoolcache/Python/3.9.0/x64/lib/python3.9/site-packages/pip/_vendor/pep517/_in_process.py prepare_metadata_for_build_wheel /var/folders/24/8k48jl6d249_n_qfxwsl6xvm0000gn/T/tmp78inzpcr
cwd: /private/var/folders/24/8k48jl6d249_n_qfxwsl6xvm0000gn/T/pip-install-7sqzbgf7/orjson
Complete output (13 lines):
💥 maturin failed
Caused by: Cargo metadata failed. Do you have cargo in your PATH?
Caused by: Error during execution of `cargo metadata`: error: failed to run `rustc` to learn about target-specific information
Caused by:
process didn't exit successfully: `rustc - --crate-name ___ --print=file-names -Z mutable-noalias --crate-type bin --crate-type rlib --crate-type dylib --crate-type cdylib --crate-type staticlib --crate-type proc-macro --print=sysroot --print=cfg` (exit code: 1)
--- stderr
error: the option `Z` is only accepted on the nightly compiler
Checking for Rust toolchain....
Running `maturin pep517 write-dist-info --metadata-directory /private/var/folders/24/8k48jl6d249_n_qfxwsl6xvm0000gn/T/pip-modern-metadata-sxuwjso1 --interpreter /Users/runner/hostedtoolcache/Python/3.9.0/x64/bin/python --manylinux=off --strip=on`
Error: Command '['maturin', 'pep517', 'write-dist-info', '--metadata-directory', '/private/var/folders/24/8k48jl6d249_n_qfxwsl6xvm0000gn/T/pip-modern-metadata-sxuwjso1', '--interpreter', '/Users/runner/hostedtoolcache/Python/3.9.0/x64/bin/python', '--manylinux=off', '--strip=on']' returned non-zero exit status 1.
----------------------------------------
ERROR: Command errored out with exit status 1: /Users/runner/hostedtoolcache/Python/3.9.0/x64/bin/python /Users/runner/hostedtoolcache/Python/3.9.0/x64/lib/python3.9/site-packages/pip/_vendor/pep517/_in_process.py prepare_metadata_for_build_wheel /var/folders/24/8k48jl6d249_n_qfxwsl6xvm0000gn/T/tmp78inzpcr Check the logs for full command output.
Error: Process completed with exit code 1. | closed | 2020-10-07T04:56:38Z | 2020-10-07T05:10:22Z | https://github.com/ijl/orjson/issues/133 | [] | gaogaotiantian | 1 |
liangliangyy/DjangoBlog | django | 682 | sidebar bug: when not commented in template, this does not render. | <!--
如果你不认真勾选下面的内容，我可能会直接关闭你的 Issue。
提问之前，建议先阅读 https://github.com/ruby-china/How-To-Ask-Questions-The-Smart-Way
-->
**我确定我已经查看了** (标注`[ ]`为`[x]`)
- [ ] [DjangoBlog的readme](https://github.com/liangliangyy/DjangoBlog/blob/master/README.md)
- [ ] [配置说明](https://github.com/liangliangyy/DjangoBlog/blob/master/bin/config.md)
- [X] [其他 Issues](https://github.com/liangliangyy/DjangoBlog/issues)
----
**我要申请** (标注`[ ]`为`[x]`)
- [X] BUG 反馈
- [ ] 添加新的特性或者功能
- [ ] 请求技术支持
| closed | 2023-10-04T17:32:53Z | 2023-11-06T06:15:43Z | https://github.com/liangliangyy/DjangoBlog/issues/682 | [] | jonascarvalh | 2 |
mckinsey/vizro | data-visualization | 220 | The graph sample from the doc doesn't work | ### Description
The vm.Graph sample doesn't work:
https://vizro.readthedocs.io/en/stable/pages/user_guides/graph/
### Expected behavior
_No response_
### vizro version
0.1.7
### Python version
3.11.5
### OS
Mac OS Sonoma 14.2
### How to Reproduce
Copy the sample to app.py and run
python app.py
### Output
It returns this error message:
AttributeError: 'DataFrame' object has no attribute 'iteritems'
(might be due to pandas version 2.0.3?)
### Code of Conduct
- [X] I agree to follow the [Code of Conduct](https://github.com/mckinsey/vizro/blob/main/CODE_OF_CONDUCT.md). | closed | 2023-12-15T22:19:56Z | 2023-12-19T12:16:49Z | https://github.com/mckinsey/vizro/issues/220 | [
"Bug Report :bug:"
] | maajdl | 2 |
wger-project/wger | django | 1,402 | Add language dependant decimal separators | ## Steps to Reproduce
1. ... Open https://wger.de/en/software/features
2. ... Open https://wger.de/hr/software/features
3. ... Open https://wger.de/de/software/features
## See screenshot
**Expected results:** <!-- what did you expect to see? -->
The counts should have decimal separators
**Actual results:** <!-- what did you see? -->
The counts don't have decimal separators
Take a look at https://en.wikipedia.org/wiki/Decimal_separator | closed | 2023-08-01T13:18:55Z | 2023-08-10T09:32:56Z | https://github.com/wger-project/wger/issues/1402 | [] | milotype | 6 |
mwaskom/seaborn | data-science | 2,785 | histplot stat=count does not count all data points | `import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
sns.set(style="whitegrid")
data_a = [1, 2, 3]
data_b = [2.4, 2.5, 2.6]
sns.histplot(np.array(data_a), color="red", binwidth=0.01, stat="count")
sns.histplot(np.array(data_b), color="blue", binwidth=0.01, stat="count")
`plt.savefig("output.png")``
This produces [https://i.stack.imgur.com/TM6al.png](url)
The data point 2.6 is omitted in the output produced by histplot.
The problem also exists, if the first sns.histplot command is removed.
Interestingly, it has been pointed out to me that the following command works:
`sns.histplot([data_a, data_b], palette=['red', 'blue'], binwidth=0.01, stat="count")`
but as I said, the single command
`sns.histplot(np.array(data_b), color="blue", binwidth=0.01, stat="count")`
also does not work.
| closed | 2022-04-28T08:18:26Z | 2022-05-18T10:47:26Z | https://github.com/mwaskom/seaborn/issues/2785 | [
"bug",
"mod:distributions"
] | cmayer | 1 |
sqlalchemy/sqlalchemy | sqlalchemy | 11,026 | Include dialect for YugabyteDB in documentation | ### Describe the use case
YugabyteDB is a cloud native distributed database compatible with Postgresql.
We have developed a YugabyteDB dialect for SQLAlchemy for adding enhancements specific to YugabyteDB.
Please let us know what are the steps to get it added in the documentation.
### Databases / Backends / Drivers targeted
Database: YugabyteDB (YSQL)
Drivers: `psycopg2` and `psycopg2-yugabytedb`
### Example Use
To connect to a local YugabyteDB cluster using `psycopg2` and `sqlalchemy_yugabytedb` plugin:
```
from sqlalchemy import create_engine
engine = create_engine('yugabytedb://yugabyte@localhost:5433/yugabyte')
```
### Additional context
_No response_ | closed | 2024-02-16T06:30:33Z | 2024-02-22T19:38:31Z | https://github.com/sqlalchemy/sqlalchemy/issues/11026 | [
"documentation",
"use case"
] | Sfurti-yb | 2 |
jonaswinkler/paperless-ng | django | 520 | [BUG] Incorrect thumbnail on documents view | **Describe the bug**
I was doing a bulk import into a new paperless instance, and when browsing the documents view and previewing some documents I happen to notice that some have the incorrect thumbnail.
It seems to be incorrect on around 10% of the documents I've checked so far
Only the thumbnail image is incorrect. The filename and other metadata reflect the "opened" PDF.
Is there a command I can run to re-generate the thumbnails to see if it happens again?
I did try a complete wipe and reinstall of paperless but the same thing happens again, although of note it's different files that it happens to with different thumbnails than before. Very odd.
**To Reproduce**
Steps to reproduce the behavior:
Import files via the consume folder
Browse documents view. Note some thumbnails are not correct.
**Expected behavior**
The thumbnails to be correct
**Screenshots**
I've created a video which I hope shows the issue clearly where you can see the thumbnail does not match the first page of the document when it's opened fully (they're completely different document thumbnails from other files):
(the data visible within the documents is all very old or out of date/inaccurate so happy to share these).
**Webserver logs**
I'm not seeing any significant errors in the logs. The only kind of errors aside from duplicates I can see are:
```
webserver_1 | [2021-02-09 19:27:50,547] [INFO] [paperless.consumer] Consuming 12ba2a84-e495-428d-b751-1edb613d6657.pdf
webserver_1 | **** Error: stream Length incorrect.
webserver_1 | Output may be incorrect.
webserver_1 | **** Error: stream Length incorrect.
webserver_1 | Output may be incorrect.
webserver_1 | **** Error: stream Length incorrect.
webserver_1 | Output may be incorrect.
webserver_1 | **** Error: stream Length incorrect.
webserver_1 | Output may be incorrect.
webserver_1 | **** Error: stream Length incorrect.
webserver_1 | Output may be incorrect.
webserver_1 | **** Error: stream Length incorrect.
webserver_1 | Output may be incorrect.
webserver_1 | **** Error: stream Length incorrect.
webserver_1 | Output may be incorrect.
```
**Relevant information**
- Host OS of the machine running paperless: Ubuntu 20.04
- Browser: Chrome. Also happens on Safari and Firefox
- Installation method: Docker compose with Tika
- Any configuration changes you made in `docker-compose.yml`, `docker-compose.env` or `paperless.conf`:
My env vars:
```
environment:
PAPERLESS_REDIS: redis://broker:6379
PAPERLESS_DBHOST: db
PAPERLESS_TIKA_ENABLED: 1
PAPERLESS_TIKA_GOTENBERG_ENDPOINT: http://gotenberg:3000
PAPERLESS_TIKA_ENDPOINT: http://tika:9998
USERMAP_UID: 1000
USERMAP_GID: 1000
PAPERLESS_OCR_LANGUAGE: eng
PAPERLESS_TIME_ZONE: "Europe/London"
PAPERLESS_OCR_MODE: redo
PAPERLESS_TASK_WORKERS: 3
PAPERLESS_THREADS_PER_WORKER: 4
# PAPERLESS_CONSUMER_POLLING: 15
PAPERLESS_IGNORE_DATES: "1990-06-26"
PAPERLESS_AUTO_LOGIN_USERNAME: rob
PAPERLESS_FILENAME_FORMAT: "{correspondent}/{created_year}/{title}"
```
| closed | 2021-02-09T20:10:19Z | 2021-02-09T20:23:29Z | https://github.com/jonaswinkler/paperless-ng/issues/520 | [] | rknightion | 3 |
Johnserf-Seed/TikTokDownload | api | 673 | 下载抖音视频的时候，可以指定只下载视频吗？不下载图文 | 如题，与版本无关。 | closed | 2024-03-04T10:54:26Z | 2024-03-04T11:12:00Z | https://github.com/Johnserf-Seed/TikTokDownload/issues/673 | [] | gkj17 | 2 |
harry0703/MoneyPrinterTurbo | automation | 571 | 我使用conda部署，在Linux服务器上。 前面的步骤都过去了。执行sh webui.sh端口也启动起来了。但是浏览器输入地址访问就出现了下面的问题 | ### 是否已存在类似问题？
- [X] 我已搜索现有问题
### 当前行为
ModuleNotFoundError: No module named 'app'
Traceback:
File "/root/anaconda3/envs/MoneyPrinterTurbo/lib/python3.10/site-packages/streamlit/runtime/scriptrunner/exec_code.py", line 88, in exec_func_with_error_handling
result = func()
File "/root/anaconda3/envs/MoneyPrinterTurbo/lib/python3.10/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 579, in code_to_exec
exec(code, module.__dict__)
File "/root/MoneyPrinterTurbo/webui/Main.py", line 9, in <module>
from app.config import config
### 预期行为
正常显示
### 重现步骤
输入 http://39.101.175.96:8502/ 访问的时候报错Lee
### 堆栈追踪/日志
ModuleNotFoundError: No module named 'app'
Traceback:
File "/root/anaconda3/envs/MoneyPrinterTurbo/lib/python3.10/site-packages/streamlit/runtime/scriptrunner/exec_code.py", line 88, in exec_func_with_error_handling
result = func()
File "/root/anaconda3/envs/MoneyPrinterTurbo/lib/python3.10/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 579, in code_to_exec
exec(code, module.__dict__)
File "/root/MoneyPrinterTurbo/webui/Main.py", line 9, in <module>
from app.config import config
### Python 版本
Python 3.10.16
### 操作系统
linux
### MoneyPrinterTurbo 版本
v1.2.2
### 其他信息
_No response_ | closed | 2025-01-16T08:08:23Z | 2025-02-19T09:41:08Z | https://github.com/harry0703/MoneyPrinterTurbo/issues/571 | [
"bug"
] | mark988 | 2 |
paperless-ngx/paperless-ngx | django | 8,539 | [BUG] when using .devcontainer with VSCode | ### Description
when using .devcontainer with VSCode i get the error here below
An error has occurred: InvalidManifestError:
==> File /usr/src/paperless/.cache/pre-commit/repoggyqxbty/.pre-commit-hooks.yaml
==> At Hook(id='check-added-large-files')
==> At key: stages
==> At index 0
=====> Expected one of commit, commit-msg, manual, merge-commit, post-checkout, post-commit, post-merge, post-rewrite, prepare-commit-msg, push but got: 'pre-commit'
Check the log at /usr/src/paperless/.cache/pre-commit/pre-commit.log
[5742 ms] **postCreateCommand failed with exit code 1. Skipping any further user-provided commands.**
Done. Press any key to close the terminal.
### Steps to reproduce
- clone repo
- open it in VSCode
- accept the propmpt "Open in Container"
### Webserver logs
```bash
no webserver logs
```
### Browser logs
_No response_
### Paperless-ngx version
Paperless-ngx v2.13.5
### Host OS
macos arm running devcontainer
### Installation method
Other (please describe above)
### System status
_No response_
### Browser
Chrome
### Configuration changes
_No response_
### Please confirm the following
- [X] I believe this issue is a bug that affects all users of Paperless-ngx, not something specific to my installation.
- [X] This issue is not about the OCR or archive creation of a specific file(s). Otherwise, please see above regarding OCR tools.
- [X] I have already searched for relevant existing issues and discussions before opening this report.
- [X] I have updated the title field above with a concise description. | closed | 2024-12-22T21:56:27Z | 2024-12-22T22:03:03Z | https://github.com/paperless-ngx/paperless-ngx/issues/8539 | [
"not a bug"
] | orcema | 0 |
huggingface/diffusers | pytorch | 10,375 | [low priority] Please fix links in documentation | https://huggingface.co/docs/diffusers/main/en/api/pipelines/hunyuan_video
Both links are broken
Make sure to check out the Schedulers [guide](https://huggingface.co/docs/diffusers/main/en/using-diffusers/schedulers.md) to learn how to explore the tradeoff between scheduler speed and quality, and see the [reuse components across pipelines](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading.md#reuse-a-pipeline) section to learn how to efficiently load the same components into multiple pipelines. | closed | 2024-12-25T09:04:33Z | 2024-12-28T20:01:27Z | https://github.com/huggingface/diffusers/issues/10375 | [] | nitinmukesh | 0 |
ionelmc/pytest-benchmark | pytest | 212 | Add type annotations | Type annotations would improve the editor experience and support static type checking. Type annotations would only *really* have to be added to user facing code but it would still be beneficial to type the whole codebase as well.
I'd be happy to help with this if it is deemed acceptable :) | open | 2022-01-16T00:33:01Z | 2024-12-19T09:02:34Z | https://github.com/ionelmc/pytest-benchmark/issues/212 | [] | RobertCraigie | 3 |
clovaai/donut | nlp | 118 | HuggingFace VisualEncoderDecoderModel performs better (but slower) | I first used the huggingface implementation of Donut to train for my specific use-case and it was working well but very slow, (10x times on epochs for example).
So I decided to switch to the official implementation and saw a massive increase in my training times, however I noticed that the valuation loss was actually worse for the same relative epoch time for training and this was apparent when doing inference.
Here are some graphs to illustrate:
<img width="686" alt="Screenshot 2022-12-31 at 13 05 23" src="https://user-images.githubusercontent.com/35901228/210137764-2352e3e3-7334-4cb8-96ab-a5de1056ee37.png">
The green line is the huggingface implementation and the others is donut installed from source from this git repo.
As you can see, the the training time is much larger for the same relative epochs (its the same dataset across all of them), however the score is also better for the huggingface implementation.
I printed out both models to check their differences, which can be found here https://www.diffchecker.com/11ZHWVyn/
I'm a novice when it comes to machine learning, but I think that these models are essentially the same...
So why is one performing better than the other, but slower, and the other faster, but worse.
Could it be something to do with this?
```
Some weights of DonutModel were not initialized from the model checkpoint at naver-clova-ix/donut-base and are newly initialized because the shapes did not match:
- encoder.model.layers.0.blocks.1.attn_mask: found shape torch.Size([3072, 100, 100]) in the checkpoint and torch.Size([768, 100, 100]) in the model instantiated
- encoder.model.layers.1.blocks.1.attn_mask: found shape torch.Size([768, 100, 100]) in the checkpoint and torch.Size([192, 100, 100]) in the model instantiated
- encoder.model.layers.2.blocks.1.attn_mask: found shape torch.Size([192, 100, 100]) in the checkpoint and torch.Size([48, 100, 100]) in the model instantiated
- encoder.model.layers.2.blocks.3.attn_mask: found shape torch.Size([192, 100, 100]) in the checkpoint and torch.Size([48, 100, 100]) in the model instantiated
- encoder.model.layers.2.blocks.5.attn_mask: found shape torch.Size([192, 100, 100]) in the checkpoint and torch.Size([48, 100, 100]) in the model instantiated
- encoder.model.layers.2.blocks.7.attn_mask: found shape torch.Size([192, 100, 100]) in the checkpoint and torch.Size([48, 100, 100]) in the model instantiated
- encoder.model.layers.2.blocks.9.attn_mask: found shape torch.Size([192, 100, 100]) in the checkpoint and torch.Size([48, 100, 100]) in the model instantiated
- encoder.model.layers.2.blocks.11.attn_mask: found shape torch.Size([192, 100, 100]) in the checkpoint and torch.Size([48, 100, 100]) in the model instantiated
- encoder.model.layers.2.blocks.13.attn_mask: found shape torch.Size([192, 100, 100]) in the checkpoint and torch.Size([48, 100, 100]) in the model instantiated
```
| open | 2022-12-31T13:10:49Z | 2023-08-25T08:23:54Z | https://github.com/clovaai/donut/issues/118 | [] | maxjay | 2 |
inducer/pudb | pytest | 317 | ValueError: I/O operation on closed file | I run with pytorch dataloader and have this problem.
```
File "/home/foo/miniconda2/envs/env3.6/lib/python3.6/bdb.py", line 48, in trace_dispatch
return self.dispatch_line(frame)
File "/home/foo/miniconda2/envs/env3.6/lib/python3.6/site-packages/pudb/debugger.py", line 187, in dispatch_line
self.user_line(frame)
File "/home/foo/miniconda2/envs/env3.6/lib/python3.6/site-packages/pudb/debugger.py", line 408, in user_line
self.interaction(frame)
File "/home/foo/miniconda2/envs/env3.6/lib/python3.6/site-packages/pudb/debugger.py", line 376, in interaction
show_exc_dialog=show_exc_dialog)
File "/home/foo/miniconda2/envs/env3.6/lib/python3.6/site-packages/pudb/debugger.py", line 2116, in call_with_ui
self.show()
File "/home/foo/miniconda2/envs/env3.6/lib/python3.6/site-packages/pudb/debugger.py", line 2107, in show
self.screen.start()
File "/home/foo/miniconda2/envs/env3.6/lib/python3.6/site-packages/urwid/display_common.py", line 751, in start
self._start(*args, **kwargs)
File "/home/foo/miniconda2/envs/env3.6/lib/python3.6/site-packages/urwid/raw_display.py", line 219, in _start
fd = self._term_input_file.fileno()
ValueError: I/O operation on closed file
``` | closed | 2018-10-13T10:00:44Z | 2018-10-13T15:50:36Z | https://github.com/inducer/pudb/issues/317 | [] | Fangyh09 | 1 |
Miserlou/Zappa | flask | 2,136 | werkzeug==0.16.1 needs to be updated | Cannot set SameSite=None on session cookie | @Miserlou Long time :)
Please update werkzeug in requirement.txt to the latest. It has a fix for https://github.com/pallets/flask/issues/3469 | open | 2020-07-15T15:42:33Z | 2020-09-27T08:50:09Z | https://github.com/Miserlou/Zappa/issues/2136 | [] | wobeng | 1 |
ets-labs/python-dependency-injector | flask | 326 | How to inject dependency in class | i have class to be injected by repositry class with DI, it looks like this:
// handler.py
```
class Handler:
@inject
def __init__(self, rating_repo: Provide[Container.repo.rating] = None):
self.rating_repo = rating_repo
def save_rating(self, cmd: SaveRating):
runner_rating = RunnerRating()
runner_rating.add_runner(cmd.runner)
runner_rating.add_merchant(cmd.childMerchant)
runner_rating.add_rating(cmd.rating)
self.rating_repo.add(runner_rating)
```
then i try to test the class with unittest:
```
import unittest
from src.container import Container
from src.runner_rating.service.handler import Handler
from src.runner_rating.domain.commands import SaveRating
from src.runner_rating.domain.models import Rating, Runner, ChildMerchant
class HandlerTest(unittest.TestCase):
def setUp(self):
self.container = Container()
self.container.config.from_ini('env.dev.ini')
self.container.wire(modules=[Handler])
rating = Rating(**{
"value": 5,
"tags": [
"ketepatan waktu pengiriman",
"kondisi barang",
"keramahan pengirim"
]
})
runner = Runner(**{
"id": "25b1c252-104c-4ebe-804d-ab6e63007ca1",
"employeeNumber": "916452",
"name": 'namarunner'
})
merchant = ChildMerchant(**{
"id": "96cc8d00-f48f-4731-a477-52dbe82a3e15",
"code": "3412409",
"mor": "3",
"name": "SPBU 3412409",
})
self.data = SaveRating(id='tes', runner=runner, rating=rating, childMerchant=merchant)
def test_save_rating(self):
handler = Handler()
handler.save_rating(self.data)
```
but the repo_rating is None/ empty? how to do DI in class?
if i remove None default param, the test show error thant Handler class need 1 argument in initializaiton
thank you | closed | 2020-11-19T09:52:22Z | 2020-11-19T16:02:16Z | https://github.com/ets-labs/python-dependency-injector/issues/326 | [
"question"
] | ijalalfrz | 2 |
graphistry/pygraphistry | jupyter | 83 | Increase CI warning sensitivity | See https://github.com/graphistry/pygraphistry/pull/81 : ` try removing --exit-zero from the second call into flake8` | closed | 2017-08-21T06:14:34Z | 2020-10-14T19:43:16Z | https://github.com/graphistry/pygraphistry/issues/83 | [
"p4"
] | lmeyerov | 1 |
faif/python-patterns | python | 29 | Make use of informal string representation for abstract_factory | Hey, thanks for putting this together. I noticed that in the `abstract_factory.py` script, the `show_pet` function does not format the strings together:
``` python
def show_pet(self):
"""Creates and shows a pet using the
abstract factory"""
pet = self.pet_factory.get_pet()
print("This is a lovely", pet)
# Prints ('This is a lovely', <__main__.Cat instance at...>)
print("It says", pet.speak())
# Prints ('It says', 'meow')
print("It eats", self.pet_factory.get_food())
# Prints ('It eats', 'cat food')
```
This leads to two things: Odd formatting, and printing the memory address of `pet`, instead of the class name. I suggest we change it to:
``` python
def show_pet(self):
"""Creates and shows a pet using the
abstract factory"""
pet = self.pet_factory.get_pet()
print "This is a lovely {}".format(pet)
# Prints This is a lovely Cat
print "It says {}".format(pet.speak())
# Prints It says meow
print "It eats {}".format(self.pet_factory.get_food())
# Prints It eats cat food
```
That way, we can make the `print` functions more pythonic (dropping the unnecessary parentheses), and make use of the `__str__()` functions defined within the `Pet` class.
Thanks!
| closed | 2013-11-04T02:27:37Z | 2013-11-14T18:44:13Z | https://github.com/faif/python-patterns/issues/29 | [] | faizandfurious | 3 |
LibreTranslate/LibreTranslate | api | 667 | bug: Exception raised while handling cache file due to incomplete buffer | **Version:** libretranslate/libretranslate:v1.6.0 (`sha256:275ecc12a296a7f28148882c412298a212e1ccffd5595759d30bac5300ea5dbb`)
**Description:**
I am experiencing a recurring issue where LibreTranslate throws a `struct.error` exception when trying to remove expired cache files. The stacktrace suggests that the issue is caused by an incomplete buffer when reading from the cache file. This results in a continuous stream of warnings being logged until the container is stopped.
**Stacktrace:**
```bash
2024-08-30 12:41:41 Updating language models
2024-08-30 12:41:41 Found 88 models
2024-08-30 12:41:42 Loaded support for 44 languages (88 models total)!
2024-08-30 12:41:42 Running on http://*:5000
2024-08-30 12:42:09 WARNING:root:Exception raised while handling cache file 'db/sessions/a14d1d697f4d3c6496f2d5b2a4f6e712'
2024-08-30 12:42:09 Traceback (most recent call last):
2024-08-30 12:42:09 File "/app/venv/lib/python3.11/site-packages/cachelib/file.py", line 137, in _remove_expired
2024-08-30 12:42:09 expires = struct.unpack("I", f.read(4))[0]
2024-08-30 12:42:09 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
2024-08-30 12:42:09 struct.error: unpack requires a buffer of 4 bytes
2024-08-30 12:42:09 WARNING:root:Exception raised while handling cache file 'db/sessions/a14d1d697f4d3c6496f2d5b2a4f6e712'
2024-08-30 12:42:09 Traceback (most recent call last):
2024-08-30 12:42:09 File "/app/venv/lib/python3.11/site-packages/cachelib/file.py", line 155, in _remove_older
2024-08-30 12:42:09 timestamp = struct.unpack("I", f.read(4))[0]
2024-08-30 12:42:09 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
2024-08-30 12:42:09 struct.error: unpack requires a buffer of 4 bytes
```
**Steps to Reproduce:**
1. Run the `libretranslate` container using the provided image version.
2. Observe the continuous stream of warnings in the Docker Desktop logs.
**Expected Behavior:**
The container should not throw exceptions by simply running it and should run without any issues.
**Workaround:**
Stopping the container resolves the issue.
Edit: I believe a better solution I have found to the problem is to delete the problematic file. | open | 2024-08-25T06:18:19Z | 2024-09-02T05:57:24Z | https://github.com/LibreTranslate/LibreTranslate/issues/667 | [
"possible bug"
] | silentoplayz | 0 |
roboflow/supervision | deep-learning | 1,719 | How to call YOLO's built-in API? | ### Search before asking
- [X] I have searched the Supervision [issues](https://github.com/roboflow/supervision/issues) and found no similar feature requests.
### Question
I want to call yolo's model.track so that I can use GPU or other yolo interfaces through yolo. Is this possible? thank you
import cv2
import supervision
from ultralytics import YOLO
model = YOLO("yolov8n.pt")
image = cv2.imread("videos/img.png")
#results = model(image)[0]
results = model.track(image, persist=True, classes=[0], verbose=False, device='0')[0]
detections = supervision.Detections.from_ultralytics(results)
### Additional
_No response_ | closed | 2024-12-09T03:09:02Z | 2024-12-10T08:44:33Z | https://github.com/roboflow/supervision/issues/1719 | [
"question"
] | DreamerYinYu | 1 |
encode/httpx | asyncio | 2,248 | Async DELETE request with JSON payload | ### Discussed in https://github.com/encode/httpx/discussions/2242
<div type='discussions-op-text'>
<sup>Originally posted by **myslak71** May 23, 2022</sup>
Hi!
I know the client doesn't support DELETE requests with JSON and in order to achieve that `httpx.request(...)` gotta be used. Is there a way to achieve such effect with async?</div> | closed | 2022-05-26T10:03:04Z | 2022-05-26T12:51:15Z | https://github.com/encode/httpx/issues/2248 | [] | myslak71 | 0 |
onnx/onnx | deep-learning | 6,368 | graph.input disappeared in extract_model | # Bug Report
### Is the issue related to model conversion?
<!-- If the ONNX checker reports issues with this model then this is most probably related to the converter used to convert the original framework model to ONNX. Please create this bug in the appropriate converter's GitHub repo (pytorch, tensorflow-onnx, sklearn-onnx, keras-onnx, onnxmltools) to get the best help. -->
### Describe the bug
<!-- Please describe the bug clearly and concisely -->
I'm planning to split a UNet model.
I use `optimum-cli export onnx -m "CompVis/stable-diffusion-v1-4" models`
to get the onnx of the UNet2DConditionModel (in `models/unet/model.onnx` after the above command is executed).
Assume the unet model is `y = M(x)`
Now I want to split it into two models M1 and M2 s.t. `M2(M1(x)) = y`.
I'm facing problems in extracting M1.
The `extract_model` function keeps complaining that it cannot identify the input from the graph.
### System information
- OS Platform and Distribution Linux Ubuntu 24.04:
- ONNX version: 1.16.2
- Python version: 3.12.3
### Reproduction instructions
- Describe the code to reproduce the behavior.
```python
import onnx
model_path = "unet/model.onnx"
model = onnx.load(model_path)
utils.extract_model(
input_path=model_path,
output_path=new_model_1_path,
input_names=[node.name for node in model.graph.input],
output_names=outputs_M1,
)
```
Error messages:
```
Traceback (most recent call last):
File ".../utils/split_model.py", line 86, in split_model_and_save
utils.extract_model(
File ".../venv/lib/python3.12/site-packages/onnx/utils.py", line 219, in extract_model
extracted = e.extract_model(input_names, output_names)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".../venv/lib/python3.12/site-packages/onnx/utils.py", line 173, in extract_model
inputs = self._collect_new_inputs(input_names)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".../venv/lib/python3.12/site-packages/onnx/utils.py", line 52, in _collect_new_inputs
return self._collect_new_io_core(self.graph.input, names) # type: ignore
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".../venv/lib/python3.12/site-packages/onnx/utils.py", line 45, in _collect_new_io_core
new_io_tensors.append(self.vimap[name])
~~~~~~~~~~^^^^^^
KeyError: 'sample'
```
According to my inspection, this error is caused by the loss of `graph.input` after line `self.model = onnx.shape_inference.infer_shapes(model)` at
https://github.com/onnx/onnx/blob/fe2433d3dd677ed5c582e194a49a632e707d0543/onnx/utils.py#L20
The `graph.input` becomes an empty list after the `infer_shapes`.
I'm new to onnx and please let me know if you need any other information. Thanks. | closed | 2024-09-15T21:57:52Z | 2024-10-03T18:06:25Z | https://github.com/onnx/onnx/issues/6368 | [
"bug"
] | tonypottera24 | 4 |
Yorko/mlcourse.ai | scikit-learn | 364 | assignment1_pandas_olympic Q10 | https://github.com/Yorko/mlcourse.ai/blob/master/jupyter_english/assignments_fall2018/assignment1_pandas_olympic.ipynb
There was a question
> 10. What is the absolute difference between the number of unique sports at the 1995 Olympics and 2016 Olympics?
But in 1995 there was no official Olympic game. Nearest games was at 1996 https://en.wikipedia.org/wiki/1996_Summer_Olympics
If you analysis results of that games at 1996 then the possible option is not presented (43 new Event in 33 Sports in 2006)
| closed | 2018-10-07T16:09:16Z | 2018-10-09T15:47:39Z | https://github.com/Yorko/mlcourse.ai/issues/364 | [
"invalid"
] | VolodymyrGavrysh | 1 |
aminalaee/sqladmin | asyncio | 868 | Show Login error message on same page | ### Checklist
- [X] There are no similar issues or pull requests for this yet.
### Is your feature related to a problem? Please describe.
While login to the admin panel if there is any error it shows the error on another page.
### Describe the solution you would like.
Can we show the error message on the same page below the form fields or any popup modal?
<img width="1173" alt="image" src="https://github.com/user-attachments/assets/b9d86000-d2af-42ca-a56b-991955de8b8b" />
### Describe alternatives you considered
_No response_
### Additional context
_No response_ | open | 2025-01-01T06:26:50Z | 2025-01-01T06:26:50Z | https://github.com/aminalaee/sqladmin/issues/868 | [] | Suraj1089 | 0 |
marimo-team/marimo | data-visualization | 4,165 | Ability to hide columns in table viewer | ### Description
I want to be able to hide/show columns in the table viewer, so that I don't have to keep editing the code cell to specify what columns to show
### Suggested solution
similar to Excel functionality, where you can hide columns and then expand them again
### Alternative
_No response_
### Additional context
_No response_ | open | 2025-03-19T19:12:45Z | 2025-03-19T21:12:37Z | https://github.com/marimo-team/marimo/issues/4165 | [
"enhancement"
] | delennc | 1 |
keras-team/autokeras | tensorflow | 1,204 | Training does not start if we feed ImageClassifier.fit with tf.Dataset | ### Bug Description
The first batch of images seems to load due to memory usage, but training does not start. I am using ImageClassifier and I feed the fit() method with a tf.Dataset.
### Bug Reproduction
Code for reproducing the bug:
```
import autokeras as ak
import os
from tensorflow.keras.preprocessing.image import ImageDataGenerator
import tensorflow.keras.models
import tensorflow as tf
# The path for the partition
base_path = "/mnt/sdd/vicastro/SubBDFinal5cv1/partition0/"
train_path = os.path.join(base_path, "train")
# The size each image will be transformed onto (should be compatible with the network input size)
target_size = (256, 256)
# The size for each training batch
batch_size = 32
# The ImageDataGenerator class allows reading images batch by batch
# and preprocessing them on the fly.
preprocessing_images = ImageDataGenerator(
rotation_range=0., # tested rotation options = 0, 3
horizontal_flip=True
)
# This instance is created without preprocessing options, for
# validation and test.
validation_images = ImageDataGenerator()
# Calling `flow_from_directory` produces a generator object that can
# be fed into a keras training call.
def get_train_generator():
train_generator = preprocessing_images.flow_from_directory(
train_path,
target_size=target_size,
batch_size=batch_size,
class_mode="categorical", # classes are provided in categorical format for a 2-unit output layer
shuffle=True,
color_mode="rgb",
seed=1234567890
)
return train_generator
train_generator = tf.data.Dataset.from_generator(get_train_generator,output_types=('float32', 'uint8'),
output_shapes=(tf.TensorShape((32, 256, 256, 3)), tf.TensorShape((32,2))))
clf = ak.ImageClassifier(max_trials=1)
clf.fit(train_generator, epochs=1)
model = clf.export_model()
model.save("/mnt/sdd/vicastro/model.h5")
```
Data used by the code:
Can't provide the actual dataset since it's not public, but under directories N/P there are .png images. Here is the tree structure:
.
├── train
│ ├── N
│ └── P
### Expected Behavior
Start the epoch to fit a model.
### Setup Details
Include the details about the versions of:
- OS type and version: Linux 3.13.0-88-generic x86_64
- Python: 3.8.3
- autokeras: 1.0.3 (1.0.2 doesn't work either)
- keras-tuner: 1.0.2rc0
- scikit-learn: 0.23.1
- numpy: 1.18.15
- pandas: 1.0.5
- tensorflow: tensorflow-gpu 2.2.0
### Additional context
The epoch status is not printed, it stops at the beginning of the fitting. Neither the process finish nor error shows up.
It has been tested on a GPU server, it does not work either in a local machine.
| closed | 2020-06-24T15:51:05Z | 2021-03-24T16:35:39Z | https://github.com/keras-team/autokeras/issues/1204 | [
"bug report",
"wontfix"
] | castrovictor | 4 |
aimhubio/aim | tensorflow | 2,629 | Runs are in accessible from the web interface if NaNs are logged | ## 🐛 Bug
The website reports 500 and the server says:
`ValueError: Out of range float values are not JSON compliant` if NaN is added as run attribute.
### To reproduce
```python
run = aim.Run()
run['test'] = np.nan
```
### Environment
- Aim Version 3.17.2
- Python version 3.11
### Additional context
```
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/middleware/errors.py", line 162, in __call__
await self.app(scope, receive, _send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/middleware/cors.py", line 84, in __call__
await self.app(scope, receive, send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/middleware/exceptions.py", line 79, in __call__
raise exc
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/middleware/exceptions.py", line 68, in __call__
await self.app(scope, receive, sender)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/fastapi/middleware/asyncexitstack.py", line 21, in __call__
raise e
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/fastapi/middleware/asyncexitstack.py", line 18, in __call__
await self.app(scope, receive, send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/routing.py", line 718, in __call__
await route.handle(scope, receive, send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/routing.py", line 443, in handle
await self.app(scope, receive, send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/fastapi/applications.py", line 276, in __call__
await super().__call__(scope, receive, send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/applications.py", line 122, in __call__
await self.middleware_stack(scope, receive, send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/middleware/errors.py", line 184, in __call__
raise exc
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/middleware/errors.py", line 162, in __call__
await self.app(scope, receive, _send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/middleware/gzip.py", line 24, in __call__
await responder(scope, receive, send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/middleware/gzip.py", line 44, in __call__
await self.app(scope, receive, self.send_with_gzip)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/middleware/exceptions.py", line 79, in __call__
raise exc
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/middleware/exceptions.py", line 68, in __call__
await self.app(scope, receive, sender)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/fastapi/middleware/asyncexitstack.py", line 21, in __call__
raise e
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/fastapi/middleware/asyncexitstack.py", line 18, in __call__
await self.app(scope, receive, send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/routing.py", line 718, in __call__
await route.handle(scope, receive, send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/routing.py", line 276, in handle
await self.app(scope, receive, send)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/routing.py", line 66, in app
response = await func(request)
^^^^^^^^^^^^^^^^^^^
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/fastapi/routing.py", line 266, in app
response = actual_response_class(content, **response_args)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/responses.py", line 196, in __init__
super().__init__(content, status_code, headers, media_type, background)
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/responses.py", line 55, in __init__
self.body = self.render(content)
^^^^^^^^^^^^^^^^^^^^
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/site-packages/starlette/responses.py", line 199, in render
return json.dumps(
^^^^^^^^^^^
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/json/__init__.py", line 238, in dumps
**kw).encode(obj)
^^^^^^^^^^^
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/json/encoder.py", line 200, in encode
chunks = self.iterencode(o, _one_shot=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/nfs/staff-ssd/gaoni/miniconda3/envs/jax4/lib/python3.11/json/encoder.py", line 258, in iterencode
return _iterencode(o, 0)
^^^^^^^^^^^^^^^^^
ValueError: Out of range float values are not JSON compliant
``` | closed | 2023-03-28T15:55:19Z | 2023-11-14T22:47:53Z | https://github.com/aimhubio/aim/issues/2629 | [
"type / bug",
"help wanted",
"area / Web-UI",
"phase / shipped"
] | n-gao | 4 |
Johnserf-Seed/TikTokDownload | api | 334 | [Question] getXbogus 请问这个功能的逻辑是怎么实现的？ | 请问，在解析抖音资源的时候会call作者你部署的api 去 getXbogus，但是api的具体逻辑是什么呢？
| open | 2023-02-28T06:00:28Z | 2023-03-02T11:12:43Z | https://github.com/Johnserf-Seed/TikTokDownload/issues/334 | [
"需求建议(enhancement)"
] | CoffeeHi | 4 |
davidsandberg/facenet | computer-vision | 1,255 | i-JOiN | open | 2024-10-28T08:53:34Z | 2024-10-28T08:53:34Z | https://github.com/davidsandberg/facenet/issues/1255 | [] | orb-jaydee | 0 | |
tflearn/tflearn | data-science | 980 | Natural Language Processing tutorial | Just a question, when do you think the tutorial on Natural Language Processing will be out? | open | 2017-12-15T22:12:03Z | 2017-12-15T22:12:03Z | https://github.com/tflearn/tflearn/issues/980 | [] | matthewchung74 | 0 |
yihong0618/running_page | data-visualization | 485 | GarminCN -> Strava时区问题 | 同步GraminCN到Strava目前遇到了时区问题，同步到的时间-8小时，貌似不是北京时区
<img width="368" alt="image" src="https://github.com/yihong0618/running_page/assets/1930500/7cbd8bd7-c52a-4ab8-bda2-2077d08f8cc5">
<img width="1007" alt="image" src="https://github.com/yihong0618/running_page/assets/1930500/632009a8-b9ba-443b-a790-257863f1cebc">
| closed | 2023-09-07T11:05:36Z | 2023-09-08T08:10:09Z | https://github.com/yihong0618/running_page/issues/485 | [] | donghao526 | 11 |
ResidentMario/geoplot | matplotlib | 62 | MatplotlibDeprecationWarning | When using kdeplot function with matplotlib 3.0.0, it raise the following warnings, which I think should be considered in future version:
```python
/home/user/Documents/geoplottest/env/lib/python3.6/site-packages/matplotlib/__init__.py:846: MatplotlibDeprecationWarning:
The text.latex.unicode rcparam was deprecated in Matplotlib 2.2 and will be removed in 3.1.
"2.2", name=key, obj_type="rcparam", addendum=addendum)
/home/user/Documents/geoplottest/env/lib/python3.6/site-packages/matplotlib/__init__.py:855: MatplotlibDeprecationWarning:
examples.directory is deprecated; in the future, examples will be found relative to the 'datapath' directory.
"found relative to the 'datapath' directory.".format(key))
```
You can reproduce it with the following code:
```python
import geopandas as gpd
boroughs = gpd.read_file(gpd.datasets.get_path('nybb')).to_crs(epsg='4326')
collisions =gpd.read_file(
"https://github.com/ResidentMario/geoplot-data/raw/master/nyc-injurious-collisions.geojson")
# Plot the data.
import geoplot.crs as gcrs
import geoplot as gplt
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(10,5))
ax2 = plt.subplot(122, projection=gcrs.AlbersEqualArea(central_latitude=40.7128,
central_longitude=-74.0059))
gplt.kdeplot(collisions, projection=gcrs.AlbersEqualArea(), shade=True,
clip=boroughs.geometry, shade_lowest=False, ax=ax2)
gplt.polyplot(boroughs, projection=gcrs.AlbersEqualArea(), ax=ax2)
plt.title("Collisions")
plt.savefig("nyc-collision-factors.png", bbox_inches='tight', pad_inches=0.1)
```
| closed | 2018-10-24T18:17:35Z | 2018-11-18T05:56:40Z | https://github.com/ResidentMario/geoplot/issues/62 | [] | enadeau | 2 |
miguelgrinberg/flasky | flask | 516 | ImportError: cannot import name 'current_app' from partially initialized module 'flask' (most likely due to a circular import) | I can't find the problem where make it a circular import | closed | 2021-06-20T14:38:32Z | 2023-08-03T15:57:05Z | https://github.com/miguelgrinberg/flasky/issues/516 | [] | Yuluer | 3 |
AirtestProject/Airtest | automation | 487 | Airtest IDE corrupts Script code, If Windows 10 is not responding and a restart is needed. | **Describe the bug**
Airtest IDE corrupts Script code, If Windows 10 is not responding and a restart is needed.
**To Reproduce**
Steps to reproduce the behavior:
1. Wait for Windows 10 to crash while airtest project is on
2. When Windows 10 is unresponsive, force restart PC
3. Encounter error when airtest project is reopened
**Expected behavior**
1. Project shouldn't be corrupted
**Screenshots**
Error Screenshot :
Expected Result :
**python version:** `python3.7`
**airtest version:** `1.0.27`
**Smartphone (please complete the following information):**
- Device: Pocophone F1
- OS: Android
| closed | 2019-08-07T02:43:47Z | 2019-08-09T03:32:26Z | https://github.com/AirtestProject/Airtest/issues/487 | [] | phantomsom | 1 |
mage-ai/mage-ai | data-science | 5,040 | [BUG] SalesForce integration problem with datatypes | ### Mage version
v0.9.68
### Describe the bug
1. When creating a integration pipeline between S3 and SalesForce the upload to SalesForce fails due to datatypes of certain columns being different in Mage and in SalesForce.
More precisely BillingAddress has a string/object dtype in Mage but Address dtype in SF and pipeline fails if data contains this column. Also YearStarted has string/object dtype in Mage, but Text(4) in SF and pipeline also fails if data contains this column.
Another SF dtype that is incompatible is Currency(18, 0).
```
raise Exception(message)
Exception: 2024-05-07T07:57:04 Salesforce process failed with error The incomming schema is incompatable with your Account object. {"error": "The incomming schema is incompatable with your Account object", "errors": [" File \"/usr/local/lib/python3.10/site-packages/mage_integrations/destinations/salesforce/__init__.py\", line 37, in <module>
destination.process(sys.stdin.buffer)
", " File \"/usr/local/lib/python3.10/site-packages/mage_integrations/destinations/base.py\", line 364, in process
errors=traceback.format_stack(),
"], "message": "Traceback (most recent call last):
File \"/usr/local/lib/python3.10/site-packages/mage_integrations/destinations/salesforce/target_salesforce/sinks.py\", line 74, in _validate_schema_against_object
validate_schema_field(
File \"/usr/local/lib/python3.10/site-packages/mage_integrations/destinations/salesforce/target_salesforce/utils/validation.py\", line 41, in validate_schema_field
raise InvalidStreamSchema(
mage_integrations.destinations.salesforce.target_salesforce.utils.exceptions.InvalidStreamSchema: BillingAddress is not updatable for your Account Object, invalid for upsert action
```
2. Disable column type check doesn't work. I have toggled it on and I still get the error.
3. I have 2 columns in the dataset (country and city). These columns are missing in the Account object in SF. I turned on Automatically add new fields option but I receive an error when running the pipeline
```
raise Exception(message)
Exception: 2024-05-07T08:57:45 Salesforce process failed with error The incomming schema is incompatable with your Account object. {"error": "The incomming schema is incompatable with your Account object", "errors": [" File \"/usr/local/lib/python3.10/site-packages/mage_integrations/destinations/salesforce/__init__.py\", line 37, in <module>
destination.process(sys.stdin.buffer)
", " File \"/usr/local/lib/python3.10/site-packages/mage_integrations/destinations/base.py\", line 364, in process
errors=traceback.format_stack(),
"], "message": "Traceback (most recent call last):
File \"/usr/local/lib/python3.10/site-packages/mage_integrations/destinations/salesforce/target_salesforce/sinks.py\", line 74, in _validate_schema_against_object
validate_schema_field(
File \"/usr/local/lib/python3.10/site-packages/mage_integrations/destinations/salesforce/target_salesforce/utils/validation.py\", line 37, in validate_schema_field
raise InvalidStreamSchema(f\"{field_name} does not exist in your {stream_name} Object\")
mage_integrations.destinations.salesforce.target_salesforce.utils.exceptions.InvalidStreamSchema: Country does not exist in your Account Object
```
These are the fields in my Account Object
### To reproduce
This is the dataset to reproduce the problem[Account_Lead.csv](https://github.com/mage-ai/mage-ai/files/15232587/Account_Lead.csv)
I import it from S3 but I guess it doesn't matter what is the source.
these are the Select Stream options:
Select all columns except ```_s3_last_modified```
For destination select SalesForce and activate Automatically add new fields and Disable column type check
### Expected behavior
Expected to upload the data, and add the columns that are missing.
### Screenshots
_No response_
### Operating system
-OS: Windows 11
-Browser: Brave Version 1.65.114 Chromium: 124.0.6367.60
### Additional context
_No response_ | open | 2024-05-07T09:06:14Z | 2024-05-08T12:29:16Z | https://github.com/mage-ai/mage-ai/issues/5040 | [
"bug"
] | diatco | 1 |
ryfeus/lambda-packs | numpy | 8 | Python 3? | Any chance of a massive update to run with Python 3.6? I would be willing to help if you could teach me how you built the python 2 versions. | closed | 2017-08-29T17:10:02Z | 2019-05-26T06:24:44Z | https://github.com/ryfeus/lambda-packs/issues/8 | [
"help wanted"
] | MichaelMartinez | 9 |
aminalaee/sqladmin | sqlalchemy | 412 | Using `wtforms.fields.FieldList` in `form_overrides` raises `TypeError` | ### Checklist
- [X] The bug is reproducible against the latest release or `master`.
- [X] There are no similar issues or pull requests to fix it yet.
### Describe the bug
I am using FastAPI with SQLModel as my ORM. I have a model where one of the fields is a list of strings. In my postgresql database this is stored in an ARRAY column. I would like to render this field as a list of `StringField`s. However, when attempting to do so via the `ModelView.form_overrides` attribute, I get a `TypeError`.
### Steps to reproduce the bug
Here is a truncated version of my code:
```python
# models.py
class Brand(SQLModel, table=True):
__tablename__ = 'brands'
id: Optional[int] = Field(default=None, primary_key=True)
name: str = Field(max_length=255)
features: Optional[List[str]] = Field(
sa_column=Column(postgresql.ARRAY(String(length=255))),
default=None
)
```
```python
# admin.py
class BrandAdmin(ModelView, model=models.Brand):
form_overrides = {
'features': FieldList(StringField())
}
```
### Expected behavior
I would expect the form to render the `features` field as a list of text input boxes.
### Actual behavior
When visiting the edit view, the code throws a `TypeError`. I believe this is because `issubclass` does not consider `wtforms.fields.FieldList` to be ta class, which it definitely is. The traceback is listed below.
### Debugging material
```bash
nebula-api-1 | Traceback (most recent call last):
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/uvicorn/protocols/http/httptools_impl.py", line 372, in run_asgi
nebula-api-1 | result = await app(self.scope, self.receive, self.send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/uvicorn/middleware/proxy_headers.py", line 75, in __call__
nebula-api-1 | return await self.app(scope, receive, send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/uvicorn/middleware/message_logger.py", line 82, in __call__
nebula-api-1 | raise exc from None
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/uvicorn/middleware/message_logger.py", line 78, in __call__
nebula-api-1 | await self.app(scope, inner_receive, inner_send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/fastapi/applications.py", line 269, in __call__
nebula-api-1 | await super().__call__(scope, receive, send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/applications.py", line 124, in __call__
nebula-api-1 | await self.middleware_stack(scope, receive, send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/middleware/errors.py", line 184, in __call__
nebula-api-1 | raise exc
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/middleware/errors.py", line 162, in __call__
nebula-api-1 | await self.app(scope, receive, _send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/middleware/cors.py", line 84, in __call__
nebula-api-1 | await self.app(scope, receive, send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/exceptions.py", line 93, in __call__
nebula-api-1 | raise exc
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/exceptions.py", line 82, in __call__
nebula-api-1 | await self.app(scope, receive, sender)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/fastapi/middleware/asyncexitstack.py", line 21, in __call__
nebula-api-1 | raise e
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/fastapi/middleware/asyncexitstack.py", line 18, in __call__
nebula-api-1 | await self.app(scope, receive, send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/routing.py", line 670, in __call__
nebula-api-1 | await route.handle(scope, receive, send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/routing.py", line 418, in handle
nebula-api-1 | await self.app(scope, receive, send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/applications.py", line 124, in __call__
nebula-api-1 | await self.middleware_stack(scope, receive, send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/middleware/errors.py", line 184, in __call__
nebula-api-1 | raise exc
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/middleware/errors.py", line 162, in __call__
nebula-api-1 | await self.app(scope, receive, _send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/exceptions.py", line 93, in __call__
nebula-api-1 | raise exc
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/exceptions.py", line 82, in __call__
nebula-api-1 | await self.app(scope, receive, sender)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/routing.py", line 670, in __call__
nebula-api-1 | await route.handle(scope, receive, send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/routing.py", line 266, in handle
nebula-api-1 | await self.app(scope, receive, send)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/starlette/routing.py", line 65, in app
nebula-api-1 | response = await func(request)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/sqladmin/authentication.py", line 56, in wrapper_decorator
nebula-api-1 | return await func(*args, **kwargs)
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/sqladmin/application.py", line 465, in edit
nebula-api-1 | Form = await model_view.scaffold_form()
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/sqladmin/models.py", line 1005, in scaffold_form
nebula-api-1 | return await get_model_form(
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/sqladmin/forms.py", line 536, in get_model_form
nebula-api-1 | field = await converter.convert(
nebula-api-1 | File "/nebula/lib/python3.8/site-packages/sqladmin/forms.py", line 287, in convert
nebula-api-1 | assert issubclass(override, Field)
nebula-api-1 | TypeError: issubclass() arg 1 must be a class
```
### Environment
- `python:3.8-slim` docker container running on MacOS Monterrey 12.2.1
- Python 3.8
- sqladmin version 0.8.0
- sqlmodel version 0.0.8
- fastapi version 0.78.0
### Additional context
I believe this is either a bug or an unsupported feature. If this feature is unsupported, I did not see it mentioned anywhere in the documentation. I'll be happy to provide any additional required information.
I'm not actually 100% if `wtforms.fields.FieldList` will actually work for my use case, but it doesn't seem that my use case is related to this error. | closed | 2023-01-18T00:04:52Z | 2024-08-23T07:14:41Z | https://github.com/aminalaee/sqladmin/issues/412 | [] | FFX01 | 9 |
man-group/arctic | pandas | 157 | preserve the NaN | when I run the following code
store.initialize_library('test_lib')
lib = store['test_lib']
lib.write('tmp1', pd.Series(['test', nan]))
and then read back:
lib.read('tmp1')
nan will be converted to 'nan' in the store. of course there is a choice to preserve NaN instead of forcing it to be a string, just wonder if there is a way to turn on/off the option.
| closed | 2016-06-26T05:24:17Z | 2018-11-05T13:02:26Z | https://github.com/man-group/arctic/issues/157 | [] | luli11 | 3 |
vanna-ai/vanna | data-visualization | 797 | Database Support | Does Vanna.ai support DM (Dameng) Database? | closed | 2025-03-10T05:12:59Z | 2025-03-10T13:33:27Z | https://github.com/vanna-ai/vanna/issues/797 | [] | junwei0001 | 0 |
explosion/spaCy | machine-learning | 13,701 | reference to obsolete thinc backend linalg | ```
ml/parser_model.pyx
line8: from thinc.backends.linalg cimport Vec, VecVec
```
https://github.com/explosion/thinc/pull/742
was obsoleted a couple of years ago, which is causing some downstream issues:
```
File "/usr/lib/python3.12/site-packages/auralis/models/xttsv2/config/tokenizer.py", line 12, in <module>
from spacy.lang.ar import Arabic
File "/usr/lib/python3.12/site-packages/spacy/__init__.py", line 13, in <module>
from . import pipeline # noqa: F401
^^^^^^^^^^^^^^^^^^^^^^
File "/usr/lib/python3.12/site-packages/spacy/pipeline/__init__.py", line 2, in <module>
from .dep_parser import DependencyParser
File "spacy/pipeline/dep_parser.pyx", line 1, in init spacy.pipeline.dep_parser
File "spacy/pipeline/transition_parser.pyx", line 1, in init spacy.pipeline.transition_parser
File "/usr/lib/python3.12/site-packages/spacy/ml/__init__.py", line 2, in <module>
from .models import * # noqa: F401, F403
^^^^^^^^^^^^^^^^^^^^^
File "/usr/lib/python3.12/site-packages/spacy/ml/models/__init__.py", line 3, in <module>
from .parser import * # noqa
^^^^^^^^^^^^^^^^^^^^^
File "/usr/lib/python3.12/site-packages/spacy/ml/models/parser.py", line 11, in <module>
from ..tb_framework import TransitionModel
File "/usr/lib/python3.12/site-packages/spacy/ml/tb_framework.py", line 4, in <module>
from .parser_model import ParserStepModel
File "spacy/ml/parser_model.pyx", line 1, in init spacy.ml.parser_model
ModuleNotFoundError: No module named 'thinc.backends.linalg'
```
## Your Environment
Arch linux
Name: spacy
Version: 3.8.2
Summary: Industrial-strength Natural Language Processing (NLP) in Python
Home-page: https://spacy.io
Author: Explosion
Author-email: contact@explosion.ai
License: MIT
Location: /usr/lib/python3.12/site-packages
Requires: catalogue, cymem, jinja2, langcodes, murmurhash, numpy, packaging, preshed, pydantic, requests, setuptools, spacy-legacy, spacy-loggers, srsly, thinc, tqdm, typer, wasabi, weasel
Required-by: auralis
* Operating System: Arch Linux
* Python Version Used: 3.12.7
* spaCy Version Used: 3.8.2 binary from pypi
* Environment Information:
| closed | 2024-11-30T19:27:58Z | 2025-01-11T00:03:05Z | https://github.com/explosion/spaCy/issues/13701 | [] | envolution | 2 |
huggingface/transformers | pytorch | 36,002 | Mismatch Between Image Tokens and Features in LLaVA Model Fine-Tuning | **Model: llava-hf/llava-1.5-7b-hf**
**Issue Description**
When I try to generate a response using the fine-tuned model, I encounter the following error:
ValueError: Image features and image tokens do not match: tokens: 575, features: 576
This error occurs during the generate() call, indicating a mismatch between the number of image tokens and image features.
**Steps I’ve Taken:**
- Image Preprocessing:
- I resized the input image to dimensions that are multiples of the patch_size (14 for LLaVA models).
- The image is resized to 518x336, which is a multiple of 14.
**Processor Configuration:**
- I manually set the patch_size and vision_feature_select_strategy in the processor to match the model's configuration.
- I verified that the processor's configuration is correct.
**Debugging Inputs:**
- I printed the inputs (input_ids, pixel_values, etc.) to ensure they are correctly formatted.
- The inputs are moved to the GPU for processing.
**Model Loading:**
The model and processor are loaded from the fine-tuned directory, and the model is moved to the GPU.
Code Snippet
Here’s the relevant part of my code:
`
```
#Load the processor and model
processor1 = LlavaProcessor.from_pretrained(model_path)
new_model_v1 = LlavaForConditionalGeneration.from_pretrained(model_path).to("cuda:0")
#Resize the image
patch_size = new_model_v1.config.vision_config.patch_size
shortest_edge = processor1.image_processor.size.get("shortest_edge", 336)
original_width, original_height = raw_image.size
scale_factor = shortest_edge / min(original_width, original_height)
new_width = int(original_width * scale_factor)
new_height = int(original_height * scale_factor)
new_width = (new_width // patch_size) * patch_size
new_height = (new_height // patch_size) * patch_size
raw_image = raw_image.resize((new_width, new_height)) # Resized to multiples of patch_size
#Process inputs
inputs = processor1(images=raw_image, text=prompt, return_tensors='pt')
inputs = {k: v.to("cuda:0") for k, v in inputs.items()}
#Generate response
output = new_model_v1.generate(
input_ids=inputs["input_ids"],
pixel_values=inputs["pixel_values"],
max_new_tokens=200,
do_sample=False
)
```
**Questions:**
- Why is there a mismatch between the number of image tokens (575) and image features (576)?
- Is there a mistake in my image preprocessing or model configuration that could cause this issue?
- How can I ensure that the number of image tokens matches the number of image features?
- Are there any additional steps I need to take to align the image tokens and features correctly?
**Additional Information**
- I have tried the Hugging Face transformers library both version 4.48.2 and 4.48.2.
- The fine-tuned model is saved in Google Drive, and I’m loading it in a new Colab session.
- The base model is llava-hf/llava-1.5-7b-hf.
<img width="885" alt="Image" src="https://github.com/user-attachments/assets/444c2286-629d-4385-85df-6c485a27f076" />
<img width="418" alt="Image" src="https://github.com/user-attachments/assets/3a24ce8b-09ae-4a36-b54f-3de0946619b8" /> | closed | 2025-02-01T12:15:54Z | 2025-02-21T09:01:48Z | https://github.com/huggingface/transformers/issues/36002 | [] | Md-Nasif03 | 6 |
assafelovic/gpt-researcher | automation | 1,148 | Front | **Describe the bug**
Download button disappeared!
"""
voyageai.error.RateLimitError: You have not yet added your payment method in the billing page and will have reduced rate limits of 3 RPM and 10K TPM. Please add your payment method in the billing page (https://dash.voyageai.com/billing/payment-methods) to unlock our standard rate limits (https://docs.voyageai.com/docs/rate-limits). Even with payment methods entered, the free tokens (200M tokens for Voyage series 3) will still apply. See our pricing docs (https://docs.voyageai.com/docs/pricing) for the free tokens for your model.
gpt-researcher-1 | INFO: connection closed"""
| closed | 2025-02-13T14:43:14Z | 2025-02-19T18:17:13Z | https://github.com/assafelovic/gpt-researcher/issues/1148 | [] | moghadas76 | 3 |
robotframework/robotframework | automation | 4,382 | Executing RobotFramework from PyInstaller generated exe gives error that log.html can't be found | Python version: Python 3.10.5
RF version: Robot Framework 5.0.1 (Python 3.10.5 on win32)
PyInstaller Version: 5.1
OS: Windows 10, build 19044.1766
I'm trying to package RobotFramework into an executable with PyInstaller. We have a packaged script which calls the robot file using robot.run('test.robot'). Robot file is not packaged in the executable.
When the executable is run, I get this output and error:
```
PS C:\Users\Name\PythonProjects\output> .\main.exe
==============================================================================
Test
==============================================================================
test .func
test | PASS |
------------------------------------------------------------------------------
Test | PASS |
1 test, 1 passed, 0 failed
==============================================================================
Output: C:\Users\Name\PythonProjects\output\output.xml
[ ERROR ] Unexpected error: FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\Name\\AppData\\Local\\Temp\\_MEI144002\\robot\\htmldata\\rebot\\log.html'
Traceback (most recent call last):
File "robot\utils\application.py", line 81, in _execute
File "robot\run.py", line 456, in main
File "robot\reporting\resultwriter.py", line 63, in write_results
File "robot\reporting\resultwriter.py", line 77, in _write_log
File "robot\reporting\resultwriter.
py", line 84, in _write
File "robot\reporting\logreportwriters.py", line 43, in write
File "robot\reporting\logreportwriters.py", line 36, in _write_file
File "robot\htmldata\htmlfilewriter.py", line 33, in write
File "robot\htmldata\template.py", line 27, in __iter__
FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\Name\\AppData\\Local\\Temp\\_MEI144002\\robot\\htmldata\\rebot\\log.html'
```
Steps to reproduce:
1. Open attached zip files, which contain my exe but also files to generate it again
2. [Project_Files.zip](https://github.com/robotframework/robotframework/files/8986821/Project_Files.zip)
3. Use PyInstaller command to generate own exe (modify abs paths as necessary)
4. `python -m PyInstaller --noconfirm --onefile --console --add-data "C:/Users/Name/PythonProjects/test.py;." "C:/Users/Name/PythonProjects/main.py"`
5. Place 'test.robot' into folder with generated 'main.exe'
6. Execute 'main.exe' (either clicking or calling 'main.exe' from Power Shell)
7. See test passes, but that it cannot generate log files correctly due to above error.
Also, I'll show preview of each file:
main.py:
```
import robot
import robot.libraries.BuiltIn
import robot.libraries.Reserved
import robot.libraries.Easter
robot.run("test.robot")
# Command line arg doesn't work either:
# robot.run("test.robot", outputdir='C:\\Users\\Name\\PythonProjects\\output', log='C:\\Users\\Name\\PythonProjects\\output\\log2.html')
```
test.py:
```
from robot.api import logger
def func():
logger.console("func test.")
```
test.robot:
```
*** Settings ***
Library test.py
*** Test Case ***
test
func
```
| closed | 2022-06-26T14:43:42Z | 2023-01-24T06:19:22Z | https://github.com/robotframework/robotframework/issues/4382 | [] | evmehok | 7 |
jofpin/trape | flask | 248 | NGROK NOT WORKING | Can anyone like fork this repo and fix the ngrok issue ,like include another tunnel like pagekite, localxpose and more _ | open | 2020-06-13T11:30:49Z | 2020-08-05T06:32:49Z | https://github.com/jofpin/trape/issues/248 | [] | Forbesgriffin | 7 |
HIT-SCIR/ltp | nlp | 453 | 1 | 1 | closed | 2020-12-14T10:42:11Z | 2020-12-14T10:44:17Z | https://github.com/HIT-SCIR/ltp/issues/453 | [] | glacierck | 0 |
run-llama/rags | streamlit | 53 | "Update Agent" creates an error and deletes the Agent | After creating an agent and navigating to "RAG Config" for the purpose of selecting the checkbox labeled "Include Summarization (only works for GPT-4)" an error is produced and the Agent is deleted after clicking "Update Agent".
Error:
| closed | 2023-12-05T21:49:49Z | 2023-12-07T18:29:04Z | https://github.com/run-llama/rags/issues/53 | [] | sorcery-ai | 3 |
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