Python Major Troubleshooting [41-60]
Recommended Article : 【Python】 Python Table of Contents
41. ImportError: cannot import name ‘mnist.data_utils’
⑴ Problem Situation:
from mnist.data_utils import load_data
...
MNIST_data = h5py.File("mnist/MNISTdata.hdf5", 'r')
⑵ Solution 1: Download MNIST data and execute the code as follows:
MNIST_data = h5py.File("./MNISTdata.hdf5", 'r')
X_train = np.float32(MNIST_data['x_train'][:])
y_train = np.int32(np.array(MNIST_data['y_train'][:, 0])).reshape(-1, 1)
X_test = np.float32(MNIST_data['x_test'][:])
y_test = np.int32(np.array(MNIST_data['y_test'][:, 0])).reshape(-1, 1)
MNIST_data.close()
⑶ Solution 2: Use tensorflow.keras.datasets.mnist.load_data().
import tensorflow as tf
(Xtr, Ytr), (Xte, Yte) = tf.keras.datasets.mnist.load_data()
42. TypeError: can’t multiply sequence by non-int of type ‘float’
⑴ (grammar) Cause 1. Attempting to multiply a float value in a situation where only integers can be multiplied.
### case 1. (Good)
names = ("John ", "Jane ")
print(names * 2)
# ('John ', 'Jane ', 'John ', 'Jane ')
### case 2. (Bad)
names = ("John ", "Jane ")
print(names * 2.0)
# TypeError: can't multiply sequence by non-int of type 'float'
### case 3. (Good)
names = ("John ", "Jane ")
print(names * int(2.0))
# ('John ', 'Jane ', 'John ', 'Jane ')
⑵ (grammar) Cause 2. As Space Ranger gets updated, it generates tissue_positions.csv instead of tissue_positions_list.csv, and this new file includes an improper header (see below). Errors occur when viewing an AnnData object, which has been loaded using scanpy.read_visium without updating to reflect this change, through scanpy.pl.spatial.
# tissue_positions_list.csv (Previous)
ACGCCTGACACGCGCT-1,1,0,0,256,1780
TACCGATCCAACACTT-1,1,1,1,268,1760
...
# tissue_positions.csv (Newest)
barcode,in_tissue,array_row,array_col,pxl_row_in_fullres,pxl_col_in_fullres
ACGCCTGACACGCGCT-1,1,0,0,256,1780
TACCGATCCAACACTT-1,1,1,1,268,1760
① (grammar) Solution: Rename
tissue_positions.csvtotissue_positions_list.csvand remove the header, just like in the previous version.
43. UnicodeDecodeError: ‘utf-8’ codec can’t decode byte 0xdf in position 991: invalid continuation byte
⑴ Problem Situation: Issue arises from using data = pandas.read_csv('example.csv', index_col=0).
① It is suspected that characters like α, β within the .csv file are causing the problem.
⑵ Solution: Use data = pandas.read_csv('example.csv', index_col=0, encoding='ISO-8859-1').
44. Server Connection Error: A connection to the Jupyter server could not be established. JupyterLab will continue trying to reconnect. Check your network connection or Jupyter server configuration.
⑴ Problem Situation: The same issue occurs in both Jupyter Lab and Jupyter Notebook.
⑵ Solution 1: It might be a broken pipe issue, in which case follow the solution provided here.
① Broken pipe issues may be related to network configuration due to national security policies.
② Measures like using VPN can prevent broken pipe issues for users.
⑶ Solution 2: If execution takes a long time, there could be intentional disconnection by the server due to unresponsiveness. In such cases, periodic pressing of Enter in the terminal or Anaconda prompt where jupyter notebook / jupyter lab was launched can resolve unresponsiveness and connection errors.
45. No module named ‘google.protobuf’
⑴ Problem Situation:
⑵ Solution: Install with conda install protobuf.
46. error: OpenCV(4.6.0) /io/opencv/modules/imgproc/src/color.cpp:182: error: (-215:Assertion failed) !_src.empty() in function ‘cvtColor’
⑴ Problem Situation: This error occurs when trying to read an image file using OpenCV, but the image file doesn’t exist.
47. RuntimeError: CUDA error: out of memory
⑴ Problem Situation: Occurs when GPU usage exceeds its limit.
⑵ Solution: Modify the command to use a specific GPU, e.g., change from python app.py to a command that specifies GPU usage like CUDA_VISIBLE_DEVICES=1 python app.py.
CUDA_VISIBLE_DEVICES=1 python app.py
48. RuntimeError: CUDA error: no kernel image is available for execution on the device
⑴ Problem Situation: Occurs when PyTorch or torchvision version doesn’t match system conditions, such as CUDA version.
① For example, CUDA11 or more recent versions should be used for RTX3090.
② Related error log : The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_70. If you want to use the NVIDIA GeForce RTX 3090 GPU with PyTorch, please check the instruction.
⑵ Solution: Install the correct PyTorch and torchvision versions that match the system, as described here.
pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 -f https://download.pytorch.org/whl/torch_stable.html
49. ImportError: cannot import name ‘ctx’ from ‘dash’
⑴ Problem Situation:
⑵ Solution: Upgrade the dash package to version 2.9.3 (or later, as of the author’s reference).
50. AttributeError: ‘Flask’ object has no attribute ‘before_first_request’
⑴ Problem Situation:
⑵ Solution: Upgrade the dash package to version 2.9.3 (or later, as of the author’s reference).
51. ImportError: cannot import name ‘cached_property’ from ‘werkzeug’
⑴ Problem Situation:
pip uninstall Werkzeug
pip install Werkzeug==0.16.0
⑵ Solution: Downgrade Werkzeug to version 1.0 or earlier.
52. TypeError: expected str, bytes or os.PathLike object, not numpy.ndarray
⑴ Problem Situation: Issue occurs when using gseapy.enrichr with an array input.
⑵ Cause: You need to provide a list instead of a numpy.ndarray as input.
⑶ Solution: Use numpy.ndarray.tolist(ar) or ar.tolist() as input.
53. OSError: wkhtmltopdf exited with non-zero code 1. error: qt.qpa.screen: QXcbConnection: Could not connect to display Could not connect to any X display.
⑴ Problem Situation:
pdfkit.from_string(output_text, 'pdf_generated.pdf', configuration=config)
⑵ Solution: Refer to the discussion in this Stack Overflow thread.
# newly added
from pyvirtualdisplay import Display
display = Display()
display.start()
# previous
pdfkit.from_string(output_text, 'pdf_generated.pdf', configuration=config)
# newly added
display.stop()
54. FileNotFoundError: [Errno 2] No such file or directory: ‘Xvfb’
⑴ Solution 1: Install the Xvfb package (reference).
sudo apt-get install xvfb
pip install xvfbwrapper
⑵ Solution 2: Avoid using pyvirtualdisplay.
# before
...
from pyvirtualdisplay import Display
display = Display()
display.start()
pdfkit.from_string(output_text, 'my_pdf.pdf', configuration=config)
display.stop()
# after
...
pdfkit.from_string(output_text, 'my_pdf.pdf', configuration=config)
55. TypeError: import_optional_dependency() got an unexpected keyword argument ‘errors’
⑴ Solution: Upgrade pandas with pip install pandas --upgrade.
56. bash: java: command not found
⑴ Solution: Follow the steps outlined here.
sudo apt install default-jre
57. Error: LinkageError occurred while loading main class picard.cmdline.PicardCommandLine java.lang.UnsupportedClassVersionError: picard/cmdline/PicardCommandLine has been compiled by a more recent version of the Java Runtime (class file version 61.0), this version of the Java Runtime only recognizes class file versions up to 55.0
⑴ Problem Situation: Version mismatch between picard and Java Runtime.
⑵ Solution: Downgrade picard to a version compatible with the installed Java Runtime.
58. Assertion failure in +[NSUndoManager _endTopLevelGroupings], NSUndoManager.m:1117
⑴ Problem Situation: Potential thread-safety conflict when multiple Python threads attempt to access macOS GUI simultaneously.
⑵ Solution 1: Run in a Linux environment instead of a macOS environment.
⑶ Solution 2: Disable the interactive mode of the web server that may contribute to the problem.
import matplotlib
matplotlib.use('Agg')
59. ImportError: cannot import name ‘Int64Index’ from ‘pandas’
⑴ Solution: Reinstall pandas and xgboost (reference).
pip uninstall pandas
pip install pandas --upgrade
pip3 uninstall xgboost
pip3 install xgboost
60. E: Unable to locate package tree
⑴ Solution:
sudo apt-get install update
sudo apt-get install tree
Input : 2023-01-28 02:15
Modified : 2023-07-28 17:22