Add discussion of .env usage per #18
- Add opinion about being careful before changing folder layout.
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@ -66,7 +66,9 @@ With this in mind, we've created a data science cookiecutter template for projec
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Starting a new project is as easy as running this command at the command line. No need to create a directory first, the cookiecutter will do it for you.
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Starting a new project is as easy as running this command at the command line. No need to create a directory first, the cookiecutter will do it for you.
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cookiecutter https://github.com/drivendata/cookiecutter-data-science
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```nohighlight
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cookiecutter https://github.com/drivendata/cookiecutter-data-science
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```
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### Example
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### Example
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@ -178,9 +180,42 @@ One effective approach to this is use [virtualenv](https://virtualenv.pypa.io/en
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If you have more complex requirements for recreating your environment, consider a virtual machine based approach such as [Docker](https://www.docker.com/) or [Vagrant](https://www.vagrantup.com/). Both of these tools use text-based formats (Dockerfile and Vagrantfile respectively) you can easily add to source control to describe how to create a virtual machine with the requirements you need.
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If you have more complex requirements for recreating your environment, consider a virtual machine based approach such as [Docker](https://www.docker.com/) or [Vagrant](https://www.vagrantup.com/). Both of these tools use text-based formats (Dockerfile and Vagrantfile respectively) you can easily add to source control to describe how to create a virtual machine with the requirements you need.
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### Keep secrets out of version control
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### Keep secrets and configuration out of version control
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You _really_ don't want to leak your AWS secret key or Postgres username and password on Github. Enough said, mostly — see the [Twelve Factor App](http://12factor.net/) principles on this point. We generally use a `.env` file that, thanks to the `.gitignore`, never makes it into the repository (secrets should be shared via other means with contributors). The `.env` file defines secrets as environment variables, and is read in automatically by a package like `dotenv` in Python.
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You _really_ don't want to leak your AWS secret key or Postgres username and password on Github. Enough said — see the [Twelve Factor App](http://12factor.net/config) principles on this point. Here's one way to do this:
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#### Store your secrets and config variables in a special file
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Create a `.env` file in the project root folder. Thanks to the `.gitignore`, this file should never get committed into the version control repository. Here's an example:
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```nohighlight
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# example .env file
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DATABASE_URL=postgres://username:password@localhost:5432/dbname
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AWS_ACCESS_KEY=myaccesskey
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AWS_SECRET_ACCESS_KEY=mysecretkey
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OTHER_VARIABLE=something
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```
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#### Use a package to load these variables automatically.
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If you look at the stub script in `src/data/make_dataset.py`, it uses a package called [python-dotenv](https://github.com/theskumar/python-dotenv) to load up all the entries in this file as environment variables so they are accessible with `os.environ.get`. Here's an example snippet adapted from the `python-dotenv` documentation:
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```python
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# src/data/dotenv_example.py
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from os.path import join, dirname
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from dotenv import load_dotenv
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dotenv_path = join(dirname(__file__), os.pardir, os.pardir, '.env') # up two levels to root folder
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load_dotenv(dotenv_path)
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database_url = os.environ.get("DATABASE_URL")
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other_variable = os.environ.get("OTHER_VARIABLE")
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```
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### Be conservative in changing the default folder structure
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To keep this structure broadly applicable for many different kinds of projects, we think the best approach is to be liberal in changing the folders around for _your_ project, but be conservative in changing the default structure for _all_ projects.
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We've created a <span class="label label-info">folder-layout</span> label specifically for issues proposing to add, subtract, rename, or move folders around. More generally, we've also created a <span class="label label-warning">needs-discussion</span> label for issues that should have some careful discussion and broad support before being implemented.
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## Contributing
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## Contributing
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