I am trying to setup a cluster for load balancing. I am using the Java Graph API. In the documentation there is this code:
final OrientGraphFactory factory = new OrientGraphFactory("remote:localhost/demo");
factory.setConnectionStrategy(OStorageRemote.CONNECTION_STRATEGY.ROUND_ROBIN_CONNECT);
OrientGraphNoTx graph = factory.getNoTx();
I copied and pasted the code exactly like this and I get this compilation error
"incompatible types: CONNECTION_STRATEGY cannot be converted to
String"
The only relevant import I have is:
import com.orientechnologies.orient.client.remote.OStorageRemote;
Can you please help?
Has anyone tried this?
Thanks.
You could use
OStorageRemote.CONNECTION_STRATEGY.ROUND_ROBIN_CONNECT.toString()
Hope it helps
Related
I have run a meta-analysis in metafor and created a forest plot.
I then tried to save this, using ggsave, as below:
ggsave("../Desktop/ASPD_META_ANALYSIS_LAPTOP/CVR.png")
But I get the error:
Error in grDevices::dev.off() : QuartzBitmap_Output - unable to open
file '../Desktop/ASPD_META_ANALYSIS_LAPTOP/CVR.png'
Can someone please advise? I need a high res version of this image.
Try using
ggsave("./Desktop/ASPD_META_ANALYSIS_LAPTOP/CVR.png")
with just one point . before /Desktop
The error occur when running gridsearchcv using catboostclassifier and bootstrap_type='Bayesian'. Any idea what that error means?
I had similar issue while training my data with CatBoostClassifier. I had set the "subsample" parameter to "0.5". After removing this parameter, it worked for me.
More details at: enter link description here
Hope this is useful.
I was trying to play around with Spacy's Dependency Parser to extract Aspect for Aspect Based Sentiment Analysis.
I followed this link: https://remicnrd.github.io/Aspect-based-sentiment-analysis/
When I tried the following piece of the code on my data, I got an Error message.
import spacy
nlp = spacy.load('en')
dataset.review = dataset.review.str.lower()
aspect_terms = []
for review in nlp.pipe(dataset.review):
chunks = [(chunk.root.text) for chunk in review.noun_chunks if chunk.root.pos_ == 'NOUN']
aspect_terms.append(' '.join(chunks))
dataset['aspect_terms'] = aspect_terms
dataset.head(10)
The Error message was:
TypeError: object of type 'NoneType' has no len()
The Error was in this line:
for review in nlp.pipe(dataset.review):
Could someone please help me understand the issue here and how to resolve this. Thanks.
Writing the solution here incase it helps someone in future.
I was getting the Error because I had some empty rows for the column review.
I re-ran the code after removing the empty rows/rows with NaN values for the column reviews and it works fine :)
I am referring TensorFlow speciliazation from Coursera where a certain piece of code works absolutely fine in Google Colab, whereas when I try to run it locally on PyCharm, it gives following error:
Failed to find data adapter that can handle input
Any suggestions?
Can you tell me the code where the error occurred?
It should be available in logs under your PyCharm console.
Looking at your comments, it seems that the model is expecting an array while you provided a list.
I was facing the same issue. Turns out it was a in the form of a list. I had to convert the fields into a numpy array like:
training_padded = np.array(training_padded)
training_labels = np.array(training_labels)
testing_padded = np.array(testing_padded)
testing_labels = np.array(testing_labels)
thats it!
Try it out and let me know if it works.
I am trying to programmatically retrieve information from a database(BRENDA) using Zeep.
The following is the code.
import zeep
import hashlib
wsdl = "https://www.brenda-enzymes.org/soap/brenda.wsdl"
password = hashlib.sha256("xx".encode('utf-8')).hexdigest()
parameters = "xxx," + password + ",ecNumber*{}#organism*{}#".format("2.7.1.2", "Homo sapiens")
client = zeep.Client(wsdl=wsdl)
print(client)
km_string = client.getKmValue(parameters)
However, I get the following error
AttributeError: 'Client' object has no attribute 'getKmValue'
Could someone help me with this?
The above code works fine while using SOAPpy library in python 2. However, I couldn't successfully install SOAPpy in python 3, therefore I tried Zeep.
The sample code that shows SOAP implementation is available here
We fixed the webservice. It should work, now. Please have a look at the SOAP documentation on our website.
not the resolution but some hints.
1) with zeep you need to put .service between client and the name of the method. the correct syntax is client.service.getKmValue(parameters) (take a look at documentation)
anyway for zeep, getKmValue doesn't exists (but it exists on the wsdl schema and SoapUi see it).
you can also try py-suds,
but for some reason i obtain a 403 calling the wsdl.
from suds.client import Client
import hashlib
client = Client("https://www.brenda-enzymes.org/soap/brenda.wsdl")