Does anyone have an example on how to properly integrate banana-rdf into a project?
Based on the example on how to use a SPARQL engine, I have tried to set up something for my project, but I get an error that I don't know how to resolve.
import java.net.URL
import org.w3.banana.jena.JenaModule
import org.w3.banana.{SparqlHttpModule, SparqlOpsModule, RDFOpsModule, RDFModule}
object SparqlService extends RDFModule with RDFOpsModule with SparqlOpsModule
with SparqlHttpModule with JenaModule
import SparqlService._
import SparqlService.sparqlOps
import SparqlService.sparqlOps._
import SparqlService.sparqlHttp.sparqlEngineSyntax._
import SparqlService.ops._
val endpoint = new URL("http://dbpedia.org/sparql/")
val query = parseSelect("""
PREFIX ont: <http://dbpedia.org/ontology/>
SELECT DISTINCT ?language WHERE {
?language a ont:ProgrammingLanguage .
?language ont:influencedBy ?other .
?other ont:influencedBy ?language .
} LIMIT 100
""").get
val answers: Rdf#Solutions = endpoint.executeSelect(query).get
val languages: Iterator[Rdf#URI] = answers.iterator map { row =>
row("language").get.as[Rdf#URI].get
}
println(languages.to[List])
Unfortunately, I get the following error and I don't get why.
Error:(27, 26) could not find implicit value for parameter fromPG:
org.w3.banana.binder.FromPG[org.w3.banana.jena.Jena,com.hp.hpl.jena.graph.Node_URI]
row("language").get.as[Rdf#URI].get
Any idea?
Related
I cannot get any NSE Symbol data from the AlphaVantage, they return always empty array.
Query:
https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY&symbol=NSE:TITAN&apikey=Q134IXR7RVWU5AQL&outputsize=full&interval=1min
Response:
{}
A month back the same query was returning data.
Looks something has changed on the AlphaVantage server end recently.
Your help is much appreciated in advance!
Try this
import pandas as pd
import json
import requests
import datetime
from pandas import DataFrame
from datetime import datetime as dt
from alpha_vantage.timeseries import TimeSeries
stock_ticker = 'SPY'
api_key = 'Q134IXR7RVWU5AQL'
ts = TimeSeries (key=api_key, output_format = "pandas")
data_daily, meta_data = ts.get_intraday(symbol=stock_ticker, interval ='1min', outputsize ='full')
print(data_daily)
The output for me looks like this
When running the following command I get the error
I am running the code on Databricks Platform, but the code is written using Pandas
TypeError: 'DataFrame' object does not support item assignment
Can someone let me know if the error is related to spark / databricks platform not supporting the code?
import numpy as np
import pandas as pd
def matchSchema(df):
df['active'] = df['active'].astype('boolean')
df['price'] = df['counts']/100
df.drop('counts', axis=1, inplace=True)
return df,df.head(3)
(dataset, sample) = matchSchema(df)
print(dataset)
print(sample)
The error is:
TypeError: 'DataFrame' object does not support item assignment
bool is used instead of boolean as a dtype...
df['active'] = df['active'].astype('bool')
I am using Gatling 3. I have a csv feeder with just one column titled accountIds. I need to pass this in the body of my POST request as JSON. I have tried a lot of different syntax but nothing seems to be working. I can also not print what is actually being sent in the body. It works if I remove the "$accountIds" and use an actual value instead. Below is my code:
val searchFeeder = csv("C://data/accountids.csv").random
val scn1 = scenario("Scenario 1")
.feed(searchFeeder)
.exec(http("Search")
.post("/v3/accounts/")
.body(StringBody("""{"accountIds": "${accountIds}"}""")).asJson)
setUp(scn1.inject(atOnceUsers(10)).protocols(httpConf))
Have you enabled trace level in logback.xml to see the details of post request?
Also, can you confirm if location you have mentioned "C://data/accountids.csv" is the right one. Generally, data folder resides in project location and within project you can access the data file as:
val searchFeeder = csv("data/stack.csv").random
I just created sample script and enabled logging.I am able to see that accountId is getting passed:
package basicpackage
import io.gatling.core.Predef._
import io.gatling.http.Predef._
import io.gatling.core.scenario.Simulation
class StackFeeder extends Simulation {
val httpConf=http.baseUrl("http://example.com")
val searchFeeder = csv("data/stack.csv").random
val scn1 = scenario("Scenario 1")
.feed(searchFeeder)
.exec(http("Search")
.post("/v3/accounts/")
.body(StringBody("""{"accountIds": "${accountIds}"}""")).asJson)
setUp(scn1.inject(atOnceUsers(1)).protocols(httpConf))
csv file location
I have written this code in Matlab to link weka with matlab so that i can implement Genetic Algorithm
enter code here
import java.util.*
import java.util.Enumeration
import java.lang.String
import weka.classifiers.*
import weka.classifiers.Evaluation
import weka.classifiers.trees.J48
import java.io.FileReader
import weka.core.Instances
import weka.core.Utils
import weka.core.Attribute
import java.lang.System
javaaddpath('C:\Users\sagnik\Documents\MATLAB\GA\weka.jar');
clear all
clc
v1 = java.lang.String('-t');
v2 = java.lang.String('C:\Users\sagnik\Documents\MATLAB\GA\generateTrainDiv.csv');
v3 = java.lang.String('-T');
v4 = java.lang.String('C:\Users\sagnik\Documents\MATLAB\GA\generateTestDiv.csv');
prm = cat(1,v1,v2,v3,v4);
classifier = javaObject('weka.classifiers.functions.MultilayerPerceptron');
weka.classifiers.Evaluation.evaluateModel(classifier,prm);
But this is giving error in the last line as:
Java exception occurred:
java.lang.Exception:
Weka exception: Can't open file null.
at weka.classifiers.Evaluation.evaluateModel(Evaluation.java:1080)
Please somenone help me,how to fix this! How is the filename 'null' here..I have already provided the 2 filenames..
I want to write a piece of code that looks like following :
var wordItr = Source.fromFile("myfile").getWords
while (wordItr.hasNext) {
val word = wordItr.next
process(word)
}
Reason behind this logic is "myfile" file is really big (around 10GB) and has no line breaks and writing a code like above really helps.
Can you please suggest how to code wordItr
Source.fromFile("myfile").getLines.flatMap(_.split(" "))
or
import java.io.File
import java.util.Scanner
var wordItr = new Scanner(new File("myFile")).useDelimiter(" ")