Implementing AWS Interaction

Length: 00:14:08

Lesson Summary:

The last unit that we need to implement before we can combine all of our modules into our final tool is the storage strategy for AWS S3.

Documentation For This Video

Installing boto3

To interface with AWS (S3 specifically), we’re going to use the wonderful boto3 package. We can install this to our virtualenv using pipenv:

(pgbackup-E7nj_BsO) $ pipenv install boto3

Configuring AWS Client

The boto3 package works off of the same configuration file that you can use with the official aws CLI. To get our configuration right, let’s leave our virtualenv and install the awscli package for our user. From there, we’ll use its configure command to set up our config file:

(pgbackup-E7nj_BsO) $ exit
$ mkdir ~/.aws
$ pip3.6 install --user awscli
$ aws configure
$ exec $SHELL

The exec $SHELL portion reload the shell to ensure that the configuration changes are picked up. Before moving on, make sure to reactivate our development virtualenv:

$ pipenv shell

Writing S3 test

Following the approach that we’ve been using, let’s write tests for our S3 interaction. To limit the explicit dependencies that we have, we’re going to have the following parameters to our storage.s3 function:

  • A client object that has an upload_fileobj method.
  • A boto3 client meets this requirement, but in testing, we can pass in a “mock” object that implements this method.
  • A file-like object (responds to read).
  • An S3 bucket name as a string.
  • The name of the file to create in S3.

We need an infile for all of our tests, so let’s extract a fixture for that also.

tests/ (partial)

import tempfile
import pytest

from pgbackup import storage

def infile():
    infile = tempfile.TemporaryFile('r+b')
    return infile

# Local storage tests...

def test_storing_file_on_s3(mocker, infile):
    Writes content from one readable to S3
    client = mocker.Mock()



Implementing S3 Strategy

Our test gives a little too much information about how we’re going to implement our storage.s3 function, but it should be pretty simple for us to implement now:

src/pgbackup/ (partial)

def s3(client, infile, bucket, name):
    client.upload_fileobj(infile, bucket, name)

Manually Testing S3 Integration

Like we did with our PostgreSQL interaction, let’s manually test uploading a file to S3 using our storage.s3 function. First, we’ll create an example.txt file, and then we’ll load into a Python REPL with our code loaded:

(pgbackup-E7nj_BsO) $ echo "UPLOADED" > example.txt
(pgbackup-E7nj_BsO) $ PYTHONPATH=./src python
>>> import boto3
>>> from pgbackup import storage
>>> client = boto3.client('s3')
>>> infile = open('example.txt', 'rb')
>>> storage.s3(client, infile, 'pyscripting-db-backups',

When we check our S3 console, we should see the file there.

Lastly, remove the example.txt file and then commit these changes:

(pgbackup-E7nj_BsO) $ rm example.txt
(pgbackup-E7nj_BsO) $ git add .
(pgbackup-E7nj_BsO) $ git commit -m 'Implement S3 interactions'

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