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QUESTION
i am trying to import PyML in colab and it tell me " No module named 'PyML' " i need to import it to use datafunc and. I check this question Python ImportError: cannot import name datafunc [PyML] , but it depend on import PyML. can any one help me to solve this or tell me onther way to do what datafunc do?
...ANSWER
Answered 2021-May-07 at 16:31one way is:
- clone the github:
!git clone https://github.com/gf712/PyML.git
verify that you have respective folder now.
QUESTION
I am currently doing some work where cupy
is involved. Overall, it makes my code run faster, since it is running everything on my GPU. Now, if a user does not have cupy
installed, but he does have numpy
, I would like to make the necessary adjustment. Currently, I am importing them like: import numpy as np; import cupy as cp
. I can make the check discussed here to test if cupy
is not installed, so that's not a problem. But I wouldn't like to put conditionals everywhere or change cp
to np
, since that would complicate things if cupy
is indeed installed and I'd like to use that instead. So, I tested out the following (which in theory would solve my issue):
ANSWER
Answered 2021-Apr-26 at 00:54To have another alias for a numpy import, why not just assign it?
QUESTION
I have multiple images (numpy arrays) whose data values correspond to N different classes. Each image does not necessarily contain examples of each class. For example, there might be a total of 12 different classes (0:11), however, one image might only contain classes 1:9.
I would like to plot each image such that the color assigned to each class is the same across all images.
I've looked into several answers: here the accepted and popular answers didn't work across multiple images. here seems like it could work but I would really like to use a color map (from matplotlib import cm
) so as not to manually set colors. I would also like a means to create an appropriate colorbar containing all classes.
The code I've tried is below:
...ANSWER
Answered 2021-Apr-22 at 23:19Looks like cm.get_cmap
needs to be adjusted to handle all the possible categories/classes in the images. The below code works:
QUESTION
I implemented BPSO as a feature selection approach using the pyswarms library. I followed this tutorial.
Is there a way to limit the maximum number of features? If not, are there other particle swarm (or genetic/simulated annealing) python-implementations that have this functionality?
...ANSWER
Answered 2021-Mar-16 at 11:36An easy way is to introduce a penalty for using any number of features. The in the following code a objective i defined
QUESTION
Thanks for looking into this, I have a python program for which I need to have process_tweet
and build_freqs
for some NLP task, nltk
is installed already and utils
wasn't so I installed it via pip install utils
but the above mentioned two modules apparently weren't installed, the error I got is standard one here,
ANSWER
Answered 2020-Dec-20 at 02:36QUESTION
I am working in a Google Colab notebook. There is one particular, computationally intensive piece of code that I'm doing using Cython in the same notebook. Within this piece of code, I want to call a function (defined in another cell in the same notebook, in Python).
Now, that function is heavily integrated with the rest of my pure Python code and rewriting and redefining things for Cython would not be possible.
My question is: How do I call that function written in Python, from another cell that is getting compiled in Cython?
Link I have already looked at: Call python file with python imports from C using cython
...ANSWER
Answered 2020-Dec-18 at 14:33Normally, you would put the whole functionality into a module and import it in the %%cython
-cell.
Another less clean (but in case of a notebook probably acceptable) way would be to import from __main__
, e.g.:
QUESTION
Excuse me. I am a noob I saw Python import csv to list Pandas #2
if I have this csv
...ANSWER
Answered 2020-Dec-17 at 14:56Try:
df.to_dict(orient='records')
QUESTION
I have built a docker image using a Dockerfile that does the following:
...ANSWER
Answered 2020-Dec-15 at 19:33There are a couple of things you can do to improve this.
The simplest is to run the application outside of Docker. You mention that you have a working Python virtual environment. A design goal of Docker is that programs in containers can't generally access files on the host, so if your application is all about reading and writing host files, Docker may not be a good fit.
Your file paths inside the container are fairly long, and this is bloating your -v
mount options. You don't need an /opt/data/projects/project
prefix; it's very typical just to use short paths like /app
or /data
.
You're also installing your application into a Python virtual environment, but inside a Docker image, which provides its own isolation. As you're seeing in your docker run
command and elsewhere, the mechanics of activating a virtual environment in Docker are a little hairy. It's also not necessary; just skip the virtual environment setup altogether. (You can also directly run /opt/venv/bin/python
and it knows it "belongs to" a virtual environment, without explicitly activating it.)
Finally, in your setup.py
file, you can use a setuptools
entry_points
declaration to provide a script that runs your named module.
That can reduce your Dockerfile to more or less
QUESTION
I am trying to build a python wheel on a complex program, and I have issues with imports. So I managed to reproduce it on a elementary example. The program works fine when directly called, but does not works when trying to import it from an installed wheel.
Here is my example structure :
...ANSWER
Answered 2020-Nov-30 at 17:12You are getting a ModuleNotFoundError
because the interpreter is searching for a global module named tata
, and not looking in the current directory. You are also repeating this behavior, in your first code block.
In the following snippet you are running main.py
as python path/to/main.py
QUESTION
Sorry, I'm a noob. I have a csv file like this
...ANSWER
Answered 2020-Dec-07 at 09:57You are using this:
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