Not Found (HTTP 404) twitteR loop error - r

I am aiming to build a twitter network by constructing an igraph from twitter relationships.
After 10 iterations R gives me this error
Error in twInterfaceObj$doAPICall(paste("users", "show", sep = "/"), params = params, :
Not Found (HTTP 404).
# Grab latest tweets
tweets_galway <- searchTwitter('#galway', n=100)
# make into df
df <- do.call("rbind", lapply(tweets_galway, as.data.frame))
# extract users from galway hashtag tweets
galway_users = df$screenName
connectiondf=data.frame()
for( i in 1:100)
{
name<-getUser(galway_users[i])
following<-name$getFriends()
following <- twListToDF(following)
connect1=cbind(follower=galway_users[i],following=following$screenName)
follower<-name$getFollowers()
follower <- twListToDF(follower)
connect2=cbind(follower=follower$screenName,following=galway_users[i])
connection<-rbind(connect1,connect2)
connectiondf=rbind(connectiondf,connection)
print(i)
}
Why am I getting this error? Apologies if this is a silly query but I am new to R

Related

Page limit using rvest

I'm having an issue when using rvest to scrape 466 pages from a wiki. Each page represents a metric that I need further information about. I have the following code which loops through each link (loaded from a csv file) and extracts the information I need from a html table on each page.
Metrics <- read.csv("C:\\Users\\me\\Documents\\WebScraping\\LONMetrics.csv")
Metrics$Theme <- as.character(paste0(Metrics$Theme))
Metrics$Metric <- as.character(paste0(Metrics$Metric))
Metrics$URL <- as.character(paste0(Metrics$URL))
n = nrow(Metrics)
i = 1
while (i <= n) {
webPage <- read_html(Metrics$URL[i])
pageTable <- html_table(webpage)
Metrics$Definition[i] <- pageTable[[1]]$X2[1]
Metrics$Category[i] <- pageTable[[1]]$X2[2]
Metrics$Calculation[i] <- pageTable[[1]]$X2[3]
Metrics$UOM[i] <- pageTable[[1]]$X2[4]
Metrics$ExpectedTrend[i] <- pageTable[[1]]$X2[6]
Metrics$MinTech[i] <- pageTable[[1]]$X2[7]
i = i+1
}
The problem I'm having is that it stops returning data after 32 pages giving an error as:
Error in read_connection_(x, n) :
Evaluation error: Failure when receiving data from the peer
I'm wondering what the cause may be and how to get around this seeming limitation?
Thanks.
Rob

using GET in a loop

I am using the following code. I create a list of first names and then generate links to an API for each name and then try to capture the data from each link.
mydata$NameGenderURL2 <- paste ("https://gender-api.com/get?name=",mydata$firstname, "&key=suZrzhrNJRvrkWFXAG", sep="")
mynamegenderfunction <- function(x){
GET(url= mydata$NameGenderURL2[x])
this.raw.content <- genderdata$content
this.raw.content <- rawToChar(genderdata$content)
this.content <- fromJSON(this.raw.content)
name1[x] <- this.content$name
gender1[x] <- this.content$gender}
namelist <- mydata$firstname[1:100]
genderdata <- lapply(namelist, mynamegenderfunction)
Oddly enough I receive the following message:
>Error in curl::curl_fetch_memory(url, handle = handle) :
>Could not resolve host: NA`
I tried another API and got the same issue. Any suggestions?
Here is a data sample:
namesurl
https://api.genderize.io/?name=kaan
https://api.genderize.io/?name=Joan
https://api.genderize.io/?name=homeblitz
https://api.genderize.io/?name=Flatmax
https://api.genderize.io/?name=BRYAN
https://api.genderize.io/?name=James
https://api.genderize.io/?name=Dion
https://api.genderize.io/?name=Flintu
https://api.genderize.io/?name=Adriana
The output that I need is the gender for each link, which would be :Male/Female, Null

Unknown error on Facebook API through R.

I'm trying to download all the posts from a facebook page through RFacebook, but when the page has an high number of posts (over 400 or so), the script stops, returning the error
"Error in callAPI(url = url, token = token) : An unknown error has occurred." at the line where I call the getPage.
library(Rfacebook)
library(stringr)
load("fb_oauth")
token=fb_oauth
page<-getPage("bicocca", token, n = 100000, since = NULL, until = NULL, feed = TRUE)
noSpaceMsg<-str_replace_all(page$message, "[\r\n]" , "")
output<-as.data.frame(cbind(page$from_name,page$id, noSpaceMsg, page$created_time, page$type, page$link, page$likes_count, page$comments_count, page$shares_count))
colnames(output)<-c("username","msgid", "message", "created_time", "type", "link", "likes", "comments", "shares")
write.csv(output, "bicocca.csv", row.names=FALSE)
Where is the problem? How can I fix it?
It seems to be a problem with the API, not with the R package. When I try to do the query in the Graph API Explorer here, I get an error too. No idea why.
One way around this is to query month by month, wrapping the getPage function in a try command:
page <- 'bicocca'
dates <- seq(as.Date("2010/10/01"), as.Date("2015/04/20"), by="month")
n <- length(dates)-1
df <- list()
for (i in 1:n){
cat(as.character(dates[i]), " ")
try(df[[i]] <- getPage(page, token, since=dates[i], until=dates[i+1]))
cat("\n")
}
df <- do.call(rbind, df)
This will not give you all the posts, but probably most of them.

Scripting userTimeline from twitteR package to data mine from a list of users in Twitter, accounting for missing users in a list

I am attempting to compile a corpus of the usertimelines of a specific sub-set of Twitter users. My problem is that in the existing code (given below), when a user's account has been suspended or deleted, the code breaks, giving the provided output & error (below).
## ORIGINAL ##
for (user in users){
# Download user's timeline from Twitter
tweets <- userTimeline(user)
# Extract tweets
tweets <- unlist( lapply(tweets, function(t) t$getText() ) )
# Save tweets to file
write.csv(tweets, file=paste(user, ".csv", sep=""), row.names=F)
#Sys.sleep(sleepTime)
}
[1] "Not Found"
Error in twInterfaceObj$doAPICall(cmd, params, method,
...) : Error: Not Found
My question is, how can I keep the script running, saving some sort of null result for the 'missing' (deleted/inactive) accounts?
I am using the twitteR package in R: ftp://cran.r-project.org/pub/R/web/packages/twitteR/twitteR.pdf
#EDIT#
# Extract tweets
# Pause for 60 sec
sleepTime = 60
for (user in users)
{
# tell the loop to skip a user if their account is protected
# or some other error occurs
result <- try(userTimeline(user), silent = TRUE);
if(class(result) == "try-error") next;
# Download user's timeline from Twitter
tweets <- userTimeline(user)
# Extract tweets
tweets <- unlist( lapply(tweets, function(t) t$getText() ) )
# Save tweets to file
write.csv(tweets, file=paste(user, ".csv", sep=""), row.names=F)
# Tell the loop to pause for 60s between iterations to avoid exceeding the Twitter API request limit
print('Sleeping for 60 seconds...')
Sys.sleep(sleepTime);
}
#
# Now inspect tweets to see the user's timeline data
You can catch the exception. see ?try or ?tryCatch. For example:
tweets <- try(userTimeline(user),silent=TRUE)
if(inherits(tweets ,'try-error'))
return(NULL)
else{
## process normally here
}

List and description of all packages in CRAN from within R

I can get a list of all the available packages with the function:
ap <- available.packages()
But how can I also get a description of these packages from within R, so I can have a data.frame with two columns: package and description?
Edit of an almost ten-year old accepted answer. What you likely want is not to scrape (unless you want to practice scraping) but use an existing interface: tools::CRAN_package_db(). Example:
> db <- tools::CRAN_package_db()[, c("Package", "Description")]
> dim(db)
[1] 18978 2
>
The function brings (currently) 66 columns back of which the of interest here are a part.
I actually think you want "Package" and "Title" as the "Description" can run to several lines. So here is the former, just put "Description" in the final subset if you really want "Description":
R> ## from http://developer.r-project.org/CRAN/Scripts/depends.R and adapted
R>
R> require("tools")
R>
R> getPackagesWithTitle <- function() {
+ contrib.url(getOption("repos")["CRAN"], "source")
+ description <- sprintf("%s/web/packages/packages.rds",
+ getOption("repos")["CRAN"])
+ con <- if(substring(description, 1L, 7L) == "file://") {
+ file(description, "rb")
+ } else {
+ url(description, "rb")
+ }
+ on.exit(close(con))
+ db <- readRDS(gzcon(con))
+ rownames(db) <- NULL
+
+ db[, c("Package", "Title")]
+ }
R>
R>
R> head(getPackagesWithTitle()) # I shortened one Title here...
Package Title
[1,] "abc" "Tools for Approximate Bayesian Computation (ABC)"
[2,] "abcdeFBA" "ABCDE_FBA: A-Biologist-Can-Do-Everything of Flux ..."
[3,] "abd" "The Analysis of Biological Data"
[4,] "abind" "Combine multi-dimensional arrays"
[5,] "abn" "Data Modelling with Additive Bayesian Networks"
[6,] "AcceptanceSampling" "Creation and evaluation of Acceptance Sampling Plans"
R>
Dirk has provided an answer that is terrific and after finishing my solution and then seeing his I debated for some time posting my solution for fear of looking silly. But I decided to post it anyway for two reasons:
it is informative to beginning scrapers like myself
it took me a while to do and so why not :)
I approached this thinking I'd need to do some web scraping and choose crantastic as the site to scrape from. First I'll provide the code and then two scraping resources that have been very helpful to me as I learn:
library(RCurl)
library(XML)
URL <- "http://cran.r-project.org/web/checks/check_summary.html#summary_by_package"
packs <- na.omit(XML::readHTMLTable(doc = URL, which = 2, header = T,
strip.white = T, as.is = FALSE, sep = ",", na.strings = c("999",
"NA", " "))[, 1])
Trim <- function(x) {
gsub("^\\s+|\\s+$", "", x)
}
packs <- unique(Trim(packs))
u1 <- "http://crantastic.org/packages/"
len.samps <- 10 #for demo purpose; use:
#len.samps <- length(packs) # for all of them
URL2 <- paste0(u1, packs[seq_len(len.samps)])
scraper <- function(urls){ #function to grab description
doc <- htmlTreeParse(urls, useInternalNodes=TRUE)
nodes <- getNodeSet(doc, "//p")[[3]]
return(nodes)
}
info <- sapply(seq_along(URL2), function(i) try(scraper(URL2[i]), TRUE))
info2 <- sapply(info, function(x) { #replace errors with NA
if(class(x)[1] != "XMLInternalElementNode"){
NA
} else {
Trim(gsub("\\s+", " ", xmlValue(x)))
}
}
)
pack_n_desc <- data.frame(package=packs[seq_len(len.samps)],
description=info2) #make a dataframe of it all
Resources:
talkstats.com thread on web scraping (great beginner
examples)
w3schools.com site on html stuff (very
helpful)
I wanted to try to do this using a HTML scraper (rvest) as an exercise, since the available.packages() in OP doesn't contain the package Descriptions.
library('rvest')
url <- 'https://cloud.r-project.org/web/packages/available_packages_by_name.html'
webpage <- read_html(url)
data_html <- html_nodes(webpage,'tr td')
length(data_html)
P1 <- html_nodes(webpage,'td:nth-child(1)') %>% html_text(trim=TRUE) # XML: The Package Name
P2 <- html_nodes(webpage,'td:nth-child(2)') %>% html_text(trim=TRUE) # XML: The Description
P1 <- P1[lengths(P1) > 0 & P1 != ""] # Remove NULL and empty ("") items
length(P1); length(P2);
mdf <- data.frame(P1, P2, row.names=NULL)
colnames(mdf) <- c("PackageName", "Description")
# This is the problem! It lists large sets column-by-column,
# instead of row-by-row. Try with the full list to see what happens.
print(mdf, right=FALSE, row.names=FALSE)
# PackageName Description
# A3 Accurate, Adaptable, and Accessible Error Metrics for Predictive\nModels
# abbyyR Access to Abbyy Optical Character Recognition (OCR) API
# abc Tools for Approximate Bayesian Computation (ABC)
# abc.data Data Only: Tools for Approximate Bayesian Computation (ABC)
# ABC.RAP Array Based CpG Region Analysis Pipeline
# ABCanalysis Computed ABC Analysis
# For small sets we can use either:
# mdf[1:6,] #or# head(mdf, 6)
However, although working quite well for small array/dataframe list (subset), I ran into a display problem with the full list, where the data would be shown either column-by-column or unaligned. I would have been great to have this paged and properly formatted in a new window somehow. I tried using page, but I couldn't get it to work very well.
EDIT:
The recommended method is not the above, but rather using Dirk's suggestion (from the comments below):
db <- tools::CRAN_package_db()
colnames(db)
mdf <- data.frame(db[,1], db[,52])
colnames(mdf) <- c("Package", "Description")
print(mdf, right=FALSE, row.names=FALSE)
However, this still suffers from the display problem mentioned...

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