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Utility package to help managing configuration files stored in S3-like services.

Project description

# s3conf

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Utility package to help managing configuration files stored in S3-like services. Needs python 3 to work.

# Installation

`python pip install s3conf `

# Usage

## Configuration

This package provides a command line client s3conf that helps us to manipulate enviroment variables. It assumes the environemnt variable S3CONF is available and points to a file in a S3-like bucket. Eg.:

`bash export S3CONF=s3://mybucket/myfile.env `

The client will search for authentication variables, if they are provided. The following example shows the allowed variables.

`bash AWS_ACCESS_KEY_ID=***access_key*** AWS_SECRET_ACCESS_KEY=***secret_access_key*** AWS_S3_REGION_NAME=***region_name*** AWS_S3_ENDPOINT_URL=***endpoint_url*** `

If these variables are not provided, the usual boto3 credentials resolution process is used. These variables are particularly useful for non-aws blob storage services compatible with S3, such as DigitalOcean Spaces.

If these variables are not defined, the client fallsback to a config file stored in ~/.s3conf/config.ini, if it is available. A convenient way to edit this file is using the client itself:

`bash s3conf -e `

This will open your default file editor, much like as how crontab -e works. The config file should have the following structure:

` [default] S3CONF=s3://mybucket/myfile.env AWS_ACCESS_KEY_ID=***access_key*** AWS_SECRET_ACCESS_KEY=***secret_access_key*** AWS_S3_REGION_NAME=***region_name*** AWS_S3_ENDPOINT_URL=***endpoint_url*** `

Eniroment variables have precedence over variables defined in the config file.

If you create a section other than the default section in the ini file, you can use it passing it as an argument.

` [my_section] S3CONF=s3://mybucket/myfile.env AWS_ACCESS_KEY_ID=***access_key*** AWS_SECRET_ACCESS_KEY=***secret_access_key*** AWS_S3_REGION_NAME=***region_name*** AWS_S3_ENDPOINT_URL=***endpoint_url*** `

`bash s3conf my_section env `

## Environment File

Once credentials are in place, geting the data from the file defined in S3CONF is fairly simple.

`bash $ s3conf env ENV_VAR_1=some_data_1 ENV_VAR_2=some_data_2 ENV_VAR_3=some_data_3 `

It should parse the environment file and output its values to be used with export, for instance.

`bash $ export $(s3conf env) `

Since editing the environment file is also common, the client provides a convenient way to do so:

`bash s3conf env -e `

This will download the environment file in a temporary file, open your default file editor (much like as crontab -e works) and upload the file back to the blob storage service if any edits were made (you can edit an arbitrary file if you also pass the -f path_to_file to the client).

## Mapping Files

Besides setting evironment variables, we sometimes need to grab some configuration files. To do so, the client provides very convenient way to store and download these files.

If we define a variable named S3CONF_MAP inside the file defined in S3CONF, we can tell the client to download the files as defined in the former variable. One example of this mapping would be the following:

`bash S3CONF_MAP=s3://my_bucket/config.file:/app/config/my.file;s3://my_bucket/etc/app_config_folder/:/etc/app_config_folder/; `

This variable would map a single file config.file from our s3-like service to our local file my.file and the whole subfolder structure from s3://my_bucket/etc/app_config_folder/ would be replicated in /etc/app_config_folder/. Since s3-like services have no concept of folder, it is *VERY IMPORTANT* to add the *trailing slash* to the S3 path when it is a folder so that the client knows it has to traverse the directory structure.

To instruct the client to map the files in the S3CONF_MAP when reading from the file in S3CONF simply pass the -m flag:

`bash s3conf env -m `

## Using With Docker

The most straight forward way to use this client with docker is to create an in your image that sets the environment variables and map all needed files:

`bash #!/usr/bin/env bash set -e export $(s3conf env -m) exec "$@" `

And use it when running your container (assuming your entrypoint is in /app/ and *is executable*)

`bash docker run --entrypoint `/app/` my_image my_command `

### Even Better With Phusion Baseimage

A great base image that solves many challenges of working with docker is the Phusion Base Image, that can be found in <>. It manages environment variables by creating files in the /etc/container_environment folder with the environement variable name and with its contents as the environement variables themselves (a full description of this process can be found in <>).

The client has a feature that automatically creates these files based on the file read from the S3-like service. To do so, it is enough to run it with the –phusion flag. Therefore, if we wanted to map files and dump them in the Phusion format, we would run our client in the following way:

`bash s3conf env -m --phusion `

The Phusion container also defines how to run scripts at container startup (an alternative for the, defined in <>). Since the environment configuration is something we would like to run at the container startup quite often, it makes a lot of sense to add a script that runs the former command when creating the container. Luckly, I have already prepared an image based on Phusion Baseimage that has python 3.6 installed (python 3 is a requirement for the client) and has it all alredy configured. It can be found in [sbneto/phusion-python:3.6-env]( To have a fully configured container based on this image, you just have to define your credentials and the S3CONF variable, prepare a bucket with your configuration files, and you are good to go (following [Phusion’s way to run one-shot commands](

`bash docker run --rm -e S3CONF=s3://my-bucket/my.env -e AWS_ACCESS_KEY_ID=***access_key*** -e AWS_SECRET_ACCESS_KEY=***secret_access_key*** sbneto/phusion-python:3.6-env /sbin/my_init -- echo "hello world" `

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