public
/
cookiecutter-data-science
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge pull request #45 from adamkgoldfarb/patch-1 

Update doc to reflect AWS CLI rather than s3cmd
This commit is contained in:
Peter Bull 2016-08-14 18:21:53 -04:00 committed by GitHub
parent 2c08fd900b 438ef529a8
commit 59c2f0d2a4
1 changed files with 1 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
docs/docs/index.md
View File

@ -130,7 +130,7 @@ There are some opinions implicit in the project structure that have grown out of
Don't ever edit your raw data, especially not manually, and especially not in Excel. Don't overwrite your raw data. Don't save multiple versions of the raw data. Treat the data (and its format) as immutable. The code you write should move the raw data through a pipeline to your final analysis. You shouldn't have to run all of the steps every time you want to make a new figure (see [Analysis is a DAG](#analysis-is-a-dag)), but anyone should be able to reproduce the final products with only the code in `src` and the data in `data/raw`. Don't ever edit your raw data, especially not manually, and especially not in Excel. Don't overwrite your raw data. Don't save multiple versions of the raw data. Treat the data (and its format) as immutable. The code you write should move the raw data through a pipeline to your final analysis. You shouldn't have to run all of the steps every time you want to make a new figure (see [Analysis is a DAG](#analysis-is-a-dag)), but anyone should be able to reproduce the final products with only the code in `src` and the data in `data/raw`.
Also, if data is immutable, it doesn't need source control in the same way that code does. Therefore, ***by default, the data folder is included in the `.gitignore` file.*** If you have a small amount of data that rarely changes, you may want to include the data in the repository. Github currently warns if files are over 50MB and rejects files over 100MB. Some other options for storing/syncing large data include [AWS S3](https://aws.amazon.com/s3/) with a syncing tool (e.g., [`s3cmd`](http://s3tools.org/s3cmd)), [Git Large File Storage](https://git-lfs.github.com/), [Git Annex](https://git-annex.branchable.com/), and [dat](http://dat-data.com/). Currently by default, we ask for an S3 bucket and use `s3cmd` to sync data in the `data` folder with the server. Also, if data is immutable, it doesn't need source control in the same way that code does. Therefore, ***by default, the data folder is included in the `.gitignore` file.*** If you have a small amount of data that rarely changes, you may want to include the data in the repository. Github currently warns if files are over 50MB and rejects files over 100MB. Some other options for storing/syncing large data include [AWS S3](https://aws.amazon.com/s3/) with a syncing tool (e.g., [`s3cmd`](http://s3tools.org/s3cmd)), [Git Large File Storage](https://git-lfs.github.com/), [Git Annex](https://git-annex.branchable.com/), and [dat](http://dat-data.com/). Currently by default, we ask for an S3 bucket and use [AWS CLI](http://docs.aws.amazon.com/cli/latest/reference/s3/index.html) to sync data in the `data` folder with the server.
### Notebooks are for exploration and communication ### Notebooks are for exploration and communication