Chapter 2 Installation

Before we can do anything, we need to install the package. The package is currently located on my github page. If you have it installed devtools, please run install.packages(“devtools”).

devtools::install_github('fdrennan/biggr')

## Downloading GitHub repo fdrennan/biggr@master

## 
##   
   checking for file ‘/private/var/folders/1q/j1clv3hj53174q0d05p52fsw0000gn/T/RtmpcYNGzb/remotes21c3182b26d/fdrennan-biggr-4f34d44/DESCRIPTION’ ...
  
✔  checking for file ‘/private/var/folders/1q/j1clv3hj53174q0d05p52fsw0000gn/T/RtmpcYNGzb/remotes21c3182b26d/fdrennan-biggr-4f34d44/DESCRIPTION’
## 
  
─  preparing ‘biggr’:
## 
  
   checking DESCRIPTION meta-information ...
  
✔  checking DESCRIPTION meta-information
## 
  
─  checking for LF line-endings in source and make files and shell scripts
## 
  
─  checking for empty or unneeded directories
## 
  
─  building ‘biggr_1.2.0.tar.gz’
## 
  
   
## 

Once this is complete, we will use two packages. biggr and reticulate. For more on reticulate, visit Rstudio.

library(biggr)
library(reticulate)

Next use the install_python and choose an environment name to install the package. By default, R uses the virtual environment r_reticulate. You can use this environment or specify a different name. I will use a different name below. My understanding is that if you do not specify the environment, each time you load up R you will not have to specify which environment to use because R uses r_reticulate by default. *You can also use Conda by specifying method = conda. The insides of the function are directly below.

install_python

## function (method = "auto", conda = "auto", envname = "r_reticulate") 
## {
##     reticulate::py_install("scipy", method = method, conda = conda, 
##         envname = envname)
##     reticulate::py_install("awscli", method = method, conda = conda, 
##         envname = envname)
##     reticulate::py_install("boto3", method = method, conda = conda, 
##         envname = envname)
## }
## <bytecode: 0x7fce2c638150>
## <environment: namespace:biggr>

Here we create a virtual environment named biggr.

install_python(envname = 'biggr')

Next we go ahead and set which environment we want to use.

use_virtualenv('biggr')

Here we verify that we are in fact using the correct environment.

py_config()

## python:         /Users/digitalfirstmedia/.virtualenvs/biggr/bin/python
## libpython:      /System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/config/libpython2.7.dylib
## pythonhome:     /System/Library/Frameworks/Python.framework/Versions/2.7:/System/Library/Frameworks/Python.framework/Versions/2.7
## virtualenv:     /Users/digitalfirstmedia/.virtualenvs/biggr/bin/activate_this.py
## version:        2.7.10 (default, Aug 17 2018, 19:45:58)  [GCC 4.2.1 Compatible Apple LLVM 10.0.0 (clang-1000.0.42)]
## numpy:          /Users/digitalfirstmedia/.virtualenvs/biggr/lib/python2.7/site-packages/numpy
## numpy_version:  1.16.3
## scipy:          /Users/digitalfirstmedia/.virtualenvs/biggr/lib/python2.7/site-packages/scipy
## 
## python versions found: 
##  /Users/digitalfirstmedia/.virtualenvs/biggr/bin/python
##  /Users/digitalfirstmedia/.virtualenvs/r-reticulate/bin/python
##  /usr/bin/python
##  /usr/local/bin/python
##  /usr/local/bin/python3
##  /Users/digitalfirstmedia/.virtualenvs/biggr_env/bin/python
##  /Users/digitalfirstmedia/.virtualenvs/py3-virtualenv/bin/python
##  /Users/digitalfirstmedia/.virtualenvs/r_reticulate/bin/python
##  /Users/digitalfirstmedia/.virtualenvs/r-tensorflow/bin/python
##  /Users/digitalfirstmedia/.virtualenvs/venv/bin/python
##  /Users/digitalfirstmedia/.virtualenvs/voicecode/bin/python
##  /anaconda3/envs/r-tensorflow/bin/python
##  /Users/digitalfirstmedia/.talon/bin/python

2.1 Authentication with AWS

Next we set permissions. You need to go to the AWS console and create a user which has administrator access. This will set the environment variables for the underlying aws command line interface.

configure_aws(aws_access_key_id = "XXXXXXXXXX",
              aws_secret_access_key = "XXXXXXXXXX",
              default.region = "us-east-2")

Then finally we verify that the package is in fact working in talking to Python as well as AWS.

s3_list_buckets()

## # A tibble: 4 x 2
##   name             creation_date            
##   <chr>            <chr>                    
## 1 couch-dog-photos 2019-03-08 04:45:05+00:00
## 2 fdrennanunittest 2019-05-02 21:15:04+00:00
## 3 freddydbucket    2019-05-03 05:46:19+00:00
## 4 kerasmods        2019-01-29 20:47:11+00:00