Utility package to help managing configuration files stored in S3-like services.
Utility package to help managing configuration files stored in S3-like services. Needs python3.
`python pip install s3conf `
## Quick Start
This package provides a command line client s3conf that helps us to manipulate enviroment variables. It looks for a configuration variable named S3CONF that should point to a file in a S3-like bucket. Eg.:
`bash export S3CONF=s3://mybucket/myfile.env `
If you have a aws-cli working, this should already be enough to get you started.
### S3 Credentials
In addition to the S3CONF environment variable, the client will also search for these authentication variables if they are provided:
`bash S3CONF_ACCESS_KEY_ID=***access_key*** S3CONF_SECRET_ACCESS_KEY=***secret_access_key*** S3CONF_S3_REGION_NAME=***region_name*** S3CONF_S3_ENDPOINT_URL=***endpoint_url*** `
These variables map to their AWS_ counterpart used for regular Boto3 configuration. The client also searchs for the regular AWS_ variables, but their S3CONF_* version take precedence. They are particularly useful when using non-aws blob storage services that are compatible with S3, such as DigitalOcean Spaces, without messing your AWS credentials.
## Project Environments Configuration
The recommended way to manage environment variables for a project is to create a .s3conf/config file in the project folder. This file should have the S3CONF variable for each existing evironemnt in the project. Since the credentials to access the bucket are not included in the file, it should be safe to commit this file together with project code.
To facilitate creating an environemt for a project, we can use the client command init. For example, issuing the command
`bash s3conf init dev s3://my-dev-bucket/myfile.env `
in the folder /usr/sbneto/project will create the file /usr/sbneto/project/.s3conf/config if it does not exist and add the following lines to it:
`ini [dev] S3CONF=s3://my-dev-bucket/myfile.env `
This file is an INI file as described in Pyhton’s [ConfigParser](https://docs.python.org/3/library/configparser.html). Each section of this file is considered a new environment in the project. More variables can be manually defined in each section (per section S3 credentials, for example).
When the section is provided to the client, the variables in the .s3conf/config associated section take precedence over the environment ones:
`bash s3conf env dev `
is equivalent to
`bash S3CONF=s3://my-dev-bucket/myfile.env s3conf env `
### Editing Your Environemnts Config File
A convenient way to edit the Configuration File is to use the following command:
`bash s3conf -e `
This will open your default file editor, much like as how crontab -e works. If no configuration folder is found in the current directory path, you can use the -c flag to create it in the current folder ./.s3conf/config:
`bash s3conf -ec `
## Retrieving the Environment File
Once credentials are in place, we want to get the data from the file defined in the S3CONF environment variable. This can be achieved with the following command:
`bash $ s3conf env ENV_VAR_1=some_data_1 ENV_VAR_2=some_data_2 ENV_VAR_3=some_data_3 `
If you are using the S3CONF value from a particular section in your config, you should pass it as well:
`bash $ s3conf env dev ENV_VAR_1=some_data_1 ENV_VAR_2=some_data_2 ENV_VAR_3=some_data_3 `
### Setting the Environment
The output can be used to set the environment with export:
`bash $ export $(s3conf env dev) `
## Editing Your Environment File
The client provides a convenient way to manipulate the environemnt file referenced by S3CONF variable:
`bash s3conf env -e `
This will download the environment file from the S3-like storage to a temporary file, open your default file editor for manual editing (much like as crontab -e works) and upload the file back to the blob storage service if any edits were made.
## Setting/Unsetting a singe Environment Variable
You can set a single environemnt variable for a environment file pointed in a section in the following way:
`bash s3conf set dev ENV_VAR_1=some_data_1 `
You can remove this environment variable from your file in a similar way:
`bash s3conf unset dev ENV_VAR_1 `
## Mapping Files
Besides setting evironment variables, we sometimes need to grab some configuration files. To do so, the client provides convenient way to store and download these files.
If we define a variable named S3CONF_MAP inside the environemnt file referenced by 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 entrypoint.sh 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/entrypoint.sh and *is executable*)
`bash docker run --entrypoint `/app/entrypoint.sh` 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 <https://github.com/phusion/baseimage-docker>. 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 <https://github.com/phusion/baseimage-docker#environment_variables>).
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 entrypoint.sh, defined in <https://github.com/phusion/baseimage-docker#running_startup_scripts>). 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](https://hub.docker.com/r/sbneto/phusion-python/). 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](https://github.com/phusion/baseimage-docker#oneshot))
`bash docker run --rm -e S3CONF=s3://my-bucket/my.env -e S3CONF_ACCESS_KEY_ID=***access_key*** -e S3CONF_SECRET_ACCESS_KEY=***secret_access_key*** sbneto/phusion-python:3.6-env /sbin/my_init -- echo "hello world" `
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