Practical Introduction to Web Scraping in R

Useful introduction.

Ten random useful things in R that you might not know about

Useful tips.

Play with the cyphr package

The cyphr package seems to provide a good choice for small research group that shares sensitive data over internet (e.g., DropBox). I did some simple experiment myself and made sure it can actually serve my purpose.

I did my experiment on two computers (using openssl): I created the test data on my Linux workstation running Manjaro then I tried to access the data on a Windows 7 laptop.

For creating the data (Linux workstation):

library(cyphr)

# Create the test data
data_dir <- file.path("~/Dropbox/temp_files", "data")
dir.create(data_dir)
dir(data_dir)

# Encrypt the test data
cyphr::data_admin_init(data_dir)

key <- cyphr::data_key(data_dir)

filename <- file.path(data_dir, "iris.rds")
cyphr::encrypt(saveRDS(iris, filename), key)
dir(data_dir)

# Cannot read the data without decrypting it first
readRDS(filename)

# Read the decrypted version of the data
head(cyphr::decrypt(readRDS(filename), key))

For accessing the data (Windows laptop):

library(cyphr)

key <- data_key("C:/Users/Ssong/Dropbox/temp_files/data", path_user = "C:/Users/Ssong/.ssh")

# Make data access request
data_request_access("C:/Users/Ssong/Dropbox/temp_files/data", 
path_user = "C:/Users/Ssong/.ssh")

On Windows 7,  the system cannot locate the public located in "~/.ssh", which is pretty dumb.

Going back to the Linux workstation to approve the data access request:

# Review the request and approve (to share with other users)
req <- data_admin_list_requests(data_dir)
data_admin_authorise(data_dir, yes = TRUE)
data_admin_list_keys(data_dir)

Now I can access the data on my Windows laptop:

key <- data_key("C:/Users/Ssong/Dropbox/temp_files/data", path_user = "C:/Users/Ssong/.ssh")

d <- decrypt( readRDS( "C:/Users/Ssong/Dropbox/temp_files/data/iris.rds"), key)

‘Meta’ machine learning packages in R

Instead of using multiple packages for different machine learning tasks, it is now possible to use one of those meta packages to do (almost) all of them.

Finally, an IDE that does both Python and R well

Useful information here.

How GPL makes me leave R for Python

Informative post, especially David's response.

The new 4.19 kernel is causing trouble

A "kworker" process is hogging my CPU. I have to go back to 4.18 kernel to resolve this issue.

UPDATE (01/24/2019)

The solution is amazingly simple. Follow this post:

1. Install perf;
2. sudo perf record -g -a sleep 10
3. sudo perf report

Scrolling down the records, it looks like the problem is related to my USB hub. Unplug the hub and the problem goes away. 

Good tmap examples

I learned a lot from this.

How to increase graph resolution in Rmarkdown and more

Very useful information here.