I'm getting the following error when importing StanzaLanguage from spacy_stanza:
ImportError Traceback (most recent call last)
in ()
4 import stanza
5 stanza.download('es')
----> 6 from spacy_stanza import StanzaLanguage
7
8
ImportError: cannot import name 'StanzaLanguage' from 'spacy_stanza' (/usr/local/lib/python3.7/dist-packages/spacy_stanza/init.py)
I think you've installed newest spacy-stanza but you're trying to use it with older spaCy:
As of v1.0.0 spacy-stanza is only compatible with spaCy v3.x. For spaCy v2, install v0.2.x
pip install "spacy-stanza<0.3.0"
Take a look what are the differences in Usage & Examples between them:
https://github.com/explosion/spacy-stanza vs https://github.com/explosion/spacy-stanza/tree/v0.2.x#-usage--examples
Related
Code is running properly in local windows machine but gives error while importing spacy.training in collab
what can be the problem?
from spacy.training import Example
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-1-ebc5aa3cff21> in <module>()
3 from spacy.util import minibatch, compounding
4 from pathlib import Path
----> 5 from spacy.training import Example
6 # TRAINING THE MODEL
7 with nlp.disable_pipes(*unaffected_pipes):
ModuleNotFoundError: No module named 'spacy.training'
I believe You have spacy 2 on your colab.
You need to import spacy with all the modules again on colab.
It is independent from Windows spacy.
You can check your version of spacy and update it using below instructions:
Run this command on your Jupyter cell:
!pip show spacy
OR
spacy.__version__
Once you check the version, you can update to a latest version by:
!pip install -U spacy
Once, you get spacy 3 your problem will be resolved.
Example was introduced in spacy version 3.
Link to Example :
https://spacy.io/api/example#_title
Make sure to Restart Runtime from the menu bar in colab.
The version info and issue are as given below. I want to know if pandas_ml is broken or am I doing something wrong. Why am I not able to import pandas_ml?
Basic info:
Versions of sklearn and pandas_ml and python are given below:
Python 3.8.2
scikit-learn 0.23.0
pandas-ml 0.6.1
Issue:
import pandas_ml as pdml
returns the following error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-47-79d5f9d2381c> in <module>
----> 1 import pandas_ml as pdml
2 #from pandas_ml import ModelFrame
3 #mf = pdml.ModelFrame(df.to_dict())
4 #mf.head()
d:\program files\python38\lib\site-packages\pandas_ml\__init__.py in <module>
1 #!/usr/bin/env python
2
----> 3 from pandas_ml.core import ModelFrame, ModelSeries # noqa
4 from pandas_ml.tools import info # noqa
5 from pandas_ml.version import version as __version__ # noqa
d:\program files\python38\lib\site-packages\pandas_ml\core\__init__.py in <module>
1 #!/usr/bin/env python
2
----> 3 from pandas_ml.core.frame import ModelFrame # noqa
4 from pandas_ml.core.series import ModelSeries # noqa
d:\program files\python38\lib\site-packages\pandas_ml\core\frame.py in <module>
8
9 import pandas_ml.imbaccessors as imbaccessors
---> 10 import pandas_ml.skaccessors as skaccessors
11 import pandas_ml.smaccessors as smaccessors
12 import pandas_ml.snsaccessors as snsaccessors
d:\program files\python38\lib\site-packages\pandas_ml\skaccessors\__init__.py in <module>
13 from pandas_ml.skaccessors.linear_model import LinearModelMethods # noqa
14 from pandas_ml.skaccessors.manifold import ManifoldMethods # noqa
---> 15 from pandas_ml.skaccessors.metrics import MetricsMethods # noqa
16 from pandas_ml.skaccessors.model_selection import ModelSelectionMethods # noqa
17 from pandas_ml.skaccessors.neighbors import NeighborsMethods # noqa
d:\program files\python38\lib\site-packages\pandas_ml\skaccessors\metrics.py in <module>
254 _true_pred_methods = (_classification_methods + _regression_methods
255 + _cluster_methods)
--> 256 _attach_methods(MetricsMethods, _wrap_target_pred_func, _true_pred_methods)
257
258
d:\program files\python38\lib\site-packages\pandas_ml\core\accessor.py in _attach_methods(cls, wrap_func, methods)
91
92 for method in methods:
---> 93 _f = getattr(module, method)
94 if hasattr(cls, method):
95 raise ValueError("{0} already has '{1}' method".format(cls, method))
AttributeError: module 'sklearn.metrics' has no attribute 'jaccard_similarity_score'
It seems it is indeed. Here is the situation:
Although the function jaccard_similarity_score is not shown in the available ones of sklearn.metrics in the documentation, it was still there under the hood (hence available) until v0.22.2 (source code) in addition to the jaccard_score one. But in the source code of the latest v0.23, it has been removed, and only jaccard_score remains.
This would imply that it could still be possible to use pandas-ml by simply downgrading scikit-learn to v.0.22.2. But unfortunately this will not work either, throwing a different error:
!pip install pandas-ml
# Successfully installed enum34-1.1.10 pandas-ml-0.6.1
import sklearn
sklearn.__version__
# '0.22.2.post1'
import pandas_ml as pdml
[...]
AttributeError: module 'sklearn.preprocessing' has no attribute 'Imputer'
I guess it would be possible to find a scikit-learn version that works with it by going back enough (the last commit in their Github repo was in March 2019), but not sure if it is worth the fuss. In any case, they do not even mention scikit-learn (let alone any specific version of it) in their requirements file, which does not seem as sound practice, and the whole project seems rather abandoned.
So after some time and effort on this, I got it working and realized that the concept of broken in Python is rather murky. It would depend upon the combination of libraries you are trying to use and their dependencies. The older releases are all available and can be used but sometimes, it can be a hit-and-trial process to find that correct combination of package versions which gets everything working.
The other thing that I learnt from this exercise is the importance of having a significant expertise in creating and managing the virtual environments when programming with python.
In my case, I got help from some friends with the hit-and-trial part and found that pandas_ml works on python 3.7. Given below is the pip freeze output which can be used to setup a reliable virtual environment for machine learning and deep learning work using libraries like pandas_ml and imbalanced-learn libraries and may include some other libraries which have not had a new release in the last few years.
To create a working environment with the right version of packages which would ensure that pandas_ml and imbalanced-learn libraries work, create an environment with the following configuration on Python 3.7.
backcall==0.1.0
colorama==0.4.3
cycler==0.10.0
decorator==4.4.2
enum34==1.1.10
imbalanced-learn==0.4.3
ipykernel==5.2.1
ipython==7.14.0
ipython-genutils==0.2.0
jedi==0.17.0
joblib==0.15.0
jupyter-client==6.1.3
jupyter-core==4.6.3
kiwisolver==1.2.0
matplotlib==3.2.1
numpy==1.15.4
pandas==0.24.2
pandas-ml==0.6.1
parso==0.7.0
pickleshare==0.7.5
prompt-toolkit==3.0.5
Pygments==2.6.1
pyparsing==2.4.7
python-dateutil==2.8.1
pytz==2020.1
pywin32==227
pyzmq==19.0.1
scikit-learn==0.20.0
scipy==1.3.3
six==1.14.0
threadpoolctl==2.0.0
tornado==6.0.4
traitlets==4.3.3
wcwidth==0.1.9
Hope this helps someone who is looking for the right combination of library versions to setup their machine and deep learning environment in python using pandas_ml and imbalanced-learn packages.
Hi I have been trying to install twython for Jupyter Notebook. I have proved through the python repl that it is universally installed throughout my laptop. But it still won't appear on Jupyter Notebook. Looking for help trying to figure out it is found in a spot that it can be found by my Anaconda 3 Jupyter Notebook.
Context: Homework assignment trying to mine twitter for tweets
Here is the errors I am receiving and I am running Mac OS
/Users/name/twitter/__init__.py:22: UserWarning: The twython library has not been installed. Some functionality from the twitter package will not be available.
"The twython library has not been installed. "
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-4-38297a1141e0> in <module>
----> 1 import twitter
2 import twython
3 #---------------------------------------------
4 # Define a Function to Login Twitter API
5 def oauth_login():
~/twitter/__init__.py in <module>
34
35
---> 36 from nltk.twitter.common import json2csv
ModuleNotFoundError: No module named 'nltk.twitter
Have you installed nltk package?
If not, do it:
pip3 install -U nltk
then run python3
inside python3 command line, run:
import nltk
nltk.download()
after the download, restart jupyter, and run your code again.
I am on windows using Anaconda with python 3.6, I have installed keras by:
conda install -c conda-forge keras
and whene i try this code
from keras.models import Graph
I get this error message:
ImportError Traceback (most recent call last)
<ipython-input-4-74d2d1fd7bad> in <module>()
----> 1 from keras.models import Graph
ImportError: cannot import name 'Graph'
This is not a Python issue. This is because the latest version of keras has removed Graph module from models. You can surely check the documentation.
If you check this Github issue (Why Keras remove graph model?), you can use the following line of code:
from .legacy.models import Graph
However, it is suggested to use functional API instead. Please check The Functional API
I use
apt-get install libboost-all-dev
But when I import boost with python3, I get some errors
In [1]: import boost
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-1-df3240a4d6cf> in <module>()
----> 1 import boost
/usr/lib/python3/dist-packages/boost/__init__.py in <module>()
7 sys.setdlopenflags(flags)
8 else:
----> 9 import mpi
10
ImportError: No module named 'mpi'
I try to use pip3 to install the module mpi, but it seems that there has no module named mpi.
By the way, boost works well in python2.7.
What should I do?