Develop Reference

What I get an attribute error from plotly-dash in PYTHON?

Here You can see a Colab code. I basically try to run those codes but I get this error.
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-16-1b48c937269f> in <module>()
----> 1 macrodemos.ARMA()
3 frames
/usr/local/lib/python3.7/dist-packages/dash/_utils.py in __setitem__(self, key, val)
156
157 # pylint: disable=inconsistent-return-statements
--> 158 def first(self, *names):
159 for name in names:
160 value = self.get(name)
AttributeError: ('Read-only: can only be set in the Dash constructor or during init_app()', 'requests_pathname_prefix')
I have no idea about this actually and I am not an expert. Could you please explain the problem? and a solution if you have any. Thanks

It appears there is some issue with the latest version of the package.
Using the following version of the packages appears to work well.
Notebook with changes, for your convenience:
https://colab.research.google.com/drive/1WyPr2p2nXmrNhjqJXl7hKaHtOocP731S?usp=sharing
Explanation:
While installing the packages, simple use:
!pip install macrodemos --upgrade
!pip install -q dash==1.19.0
This will replace the version of dash used to an older one that works, Here is a screenshot for your reference:
Screenshot 1
I am a newbie and I appreciate your feedback about whether this is helpful or not.
Thanks in advance. :)

I was able to fix this error by following the recommendations in the error message pasted here for reference,
AttributeError: ('Read-only: can only be set in the Dash constructor or during init_app()', 'requests_pathname_prefix')
The solution is to only set the Dash config when you first initialize the app application instead of using app.config.update according to the new version of Dash.
So instead of something like this which is trying to update a read-only variable,
app.config.update({
'requests_pathname_prefix': '/dash/' # wrong, will cause read-only error
})
You could do,
app = dash.Dash(
:
requests_pathname_prefix='/dash/')
Which sets those variables when it originally was defined so there will be no read-only error.
This answer might not fully address the original poster's concerns because after looking at the Colab notebook, the library of concern is macrodemos which needs to be updated to be compatible with the newest version of Dash.

'tensorflow' has no attribute 'to_int32'

I am trying to implement CTC loss to audio files but I get the following error:
TensorFlow has no attribute 'to_int32'
I'm running tf.version 2.0.0.
I think it's with the version, I'm currently using, as we see the error is thrown in the package itself ' tensorflow_backend.py' code.
I have imported packages as "tensorflow.keras.class_name" with backend as K. Below is the screenshot.

You can cast the tensor in TensorFlow 2 as follows:
tf.cast(my_tensor, tf.int32)
You can read the documentation of the method in https://www.tensorflow.org/api_docs/python/tf/cast
You can also see that the to_int32 is deprecated and was used in TensorFlow 1
https://www.tensorflow.org/api_docs/python/tf/compat/v1/to_int32

After you make the import just write
tf.to_int=lambda x: tf.cast(x, tf.int32)
This is similar to writing the behavior of tf.to_int in everywhere in the code, so you don't have to manually edit a TF1.0 code

Error with obtaining license OpenCV project

I am trying to make a machine learning model with Python. However, I keep getting this error:
LSD = cv2.createLineSegmentDetector(_refine=cv2.LSD_REFINE_ADV, _quant=qError)
cv2.error: OpenCV(4.2.0) /Users/travis/build/skvark/opencv-python/opencv/modules/imgproc/src/lsd.cpp:143: error: (-213:The function/feature is not implemented) Implementation has been removed due original code license issues in function 'LineSegmentDetectorImpl'
My code is as follows:
_, vp, _, _, panoEdge, _, _ = panoEdgeDetection(img_ori,
qError=args.q_error,
refineIter=args.refine_iter)
panoEdge = (panoEdge > 0)
How can I fix this? Thanks to all. Satya

This seems to be happening due to the function LineSegmentDetectorImpl being deprecated in latest version. For example, if you are using this opencv-contrib-python==4.1.1.26 and opencv-python==4.1.1.26.
To solve it:
Downgrade to opencv-contrib-python==4.0.0.21 and opencv-python==4.0.0.21.
According to this question on Stakoverflow, to replace the missing LineSegmentDetectorImpl, install pylsd using pip install pylsd. For more details about how to use it with opencv, please check the documentation.
This should solve the problem.

Why pylint returns `unsubscriptable-object` for numpy.ndarray.shape?

I just put together the following "minimum" repro case (minimum in quotes because I wanted to ensure pylint threw no other errors, warnings, hints, or suggestions - meaning there's a bit of boilerplate):
pylint_error.py:
"""
Docstring
"""
import numpy as np
def main():
"""
Main entrypoint
"""
test = np.array([1])
print(test.shape[0])
if __name__ == "__main__":
main()
When I run pylint on this code (pylint pylint_error.py) I get the following output:
$> pylint pylint_error.py
************* Module pylint_error
pylint_error.py:13:10: E1136: Value 'test.shape' is unsubscriptable (unsubscriptable-object)
------------------------------------------------------------------
Your code has been rated at 1.67/10 (previous run: 1.67/10, +0.00)
It claims that test.shape is not subscriptable, even though it quite clearly is. When I run the code it works just fine:
$> python pylint_error.py
1
So what's causing pylint to become confused, and how can I fix it?
Some additional notes:
If I declare test as np.arange(1) the error goes away
If I declare test as np.zeros(1), np.zeros((1)), np.ones(1), or np.ones((1)) the error does not go away
If I declare test as np.full((1), 1) the error goes away
Specifying the type (test: np.ndarray = np.array([1])) does not fix the error
Specifying a dtype (np.array([1], dtype=np.uint8)) does not fix the error
Taking a slice of test (test[:].shape) makes the error go away
My first instinct says that the inconsistent behavior with various NumPY methods (arange vs zeros vs full, etc) suggests it's just a bug in NumPY. However it's possible there's some underlying concept to NumPY that I'm misunderstanding. I'd like to be sure I'm not writing code with undefined behavior that's only working on accident.

I don't have enough reputation to comment, but it looks like this is an open issue: https://github.com/PyCQA/pylint/issues/3139
Until the issue is resolved on their end, I would just change the line to
print(test.shape[0]) # pylint: disable=E1136 # pylint/issues/3139
to my pylintrc file.

As of November 2019:
As mentioned by one of the users in the discussion on GitHub you could resolve the problem by downgrading both pylint and astroid, e.g. in requirements.txt
astroid>=2.0, <2.3
pylint>=2.3, <2.4
or
pip install astroid==2.2.5 & pip install pylint==2.3.1

This was finally fixed with the release of astroid 2.4.0 in May 2020.
https://github.com/PyCQA/pylint/issues/3139

DataFrame object has no attribute 'sample'

Simple code like this won't work anymore on my python shell:
import pandas as pd
df=pd.read_csv("K:/01. Personal/04. Models/10. Location/output.csv",index_col=None)
df.sample(3000)
The error I get is:
AttributeError: 'DataFrame' object has no attribute 'sample'
DataFrames definitely have a sample function, and this used to work.
I recently had some trouble installing and then uninstalling another distribution of python. I don't know if this could be related.
I've previously had a similar problem when trying to execute a script which had the same name as a module I was importing, this is not the case here, and pandas.read_csv is actually working.
What could cause this?

As given in the documentation of DataFrame.sample -
DataFrame.sample(n=None, frac=None, replace=False, weights=None, random_state=None, axis=None)
Returns a random sample of items from an axis of object.
New in version 0.16.1.
(Emphasis mine).
DataFrame.sample is added in 0.16.1 , you can either -
Upgrade your pandas version to latest, you can use pip for that, Example -
pip install pandas --upgrade
Or if you don't want to upgrade, and want to sample few rows from the dataframe, you can also use random.sample(), Example -
import random
num = 100 #number of samples
sampleddata = df.loc[random.sample(list(df.index),num)]