data - command line tool for working with data, Data Packages and the DataHub
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README.md

Overview

"Data-cli" is an important part of the DataHub project. This is a command line tool, that helps you to manipulate your data (as git manipulates the code).

For example you have a set of data as a result of your work, let it be few data-files and a description. And you want to share it with your colleagues. With the "data-cli" you just need to:

cd data-folder
data init  # convert my data files into the data-package
> "Answer a few questions here, e.g. dataset name, files to include, etc"
data push  # upload the dataset onto a DataHub
> "As a result you'll got a link to share:
http://datahub.io/user-name/data-package-name

That's it! Your data is online. You can make your data unlisted or private, add some pretty graphics, and many more. Please read http://datahub.io/docs for details.

With data-cli you can also:

  • Get data from online sources
  • Get info about data files and datasets (local and remote)
  • Validate your data to ensure its quality
  • Initialize a new dataset (as a Data Package)

Usage examples:

Here we show examples of usage for common data commands. To see the full command documentation - click on the command name, or proceed to the help pages.

data login

You should login at the first use of data-cli:

$ data login
? Login with... Github
> Opening browser and waiting for you to authenticate online
> You are logged in!

data push

Upload a dataset or a separate file on the DataHub:

$ data push mydata.csv
? Please, confirm name for this dataset:
0-selfish-cougar-7 mydataset
? Please, confirm title for this dataset:
Mydataset Mydataset
  Uploading [******************************] 100% (0.0s left)
  your data is published!
🔗  https://datahub.io/myname/mydataset/v/1 (copied to clipboard)

Alternatively you can set name without interaction

$ data push mydata.csv --name=mydataset
  Uploading [******************************] 100% (0.0s left)
  your data is published!
🔗  https://datahub.io/myname/mydataset/v/1 (copied to clipboard)

Note: by default, findability flag for your dataset is set to --public. Use --unlisted flag if you want it to not appear in the search results.

data get

Get a dataset from the DataHub or GitHub:

$ data get http://datahub.io/core/gold-prices
Time elapsed: 1.72 s
Dataset/file is saved in "core/gold-prices"

data info

Shows info about the dataset (local or remote):

$ data info http://datahub.io/core/gold-prices
# Gold Prices (Monthly in USD)

Monthly gold prices since 1950 in USD (London market). Data is sourced from the Bundesbank.

## Data
    * [Bundesbank statistic ... [see more below]

## RESOURCES
┌───────────────────┬────────┬───────┬───────┐
│ Name              │ Format │ Size  │ Title │
├───────────────────┼────────┼───────┼───────┤
│ data_csv          │ csv    │ 16172 │       │
├───────────────────┼────────┼───────┼───────┤
│ data_json         │ json   │ 32956 │       │
├───────────────────┼────────┼───────┼───────┤
│ gold-prices_zip   │ zip    │ 17755 │       │
├───────────────────┼────────┼───────┼───────┤
│ data              │ csv    │ 16170 │       │
└───────────────────┴────────┴───────┴───────┘

## README
Monthly gold prices since 1950 in USD (London market). Data is sourced from the Bundesbank.
...

### Licence
...

data cat

Works similar as Unix cat command but works with remote resources and can convert tabular data into different formats:

$ data cat http://datahub.io/core/gold-prices/r/0.csv
┌──────────────────────────────────────┬──────────────────────────────────────┐
│ date                                 │ price                                │
├──────────────────────────────────────┼──────────────────────────────────────┤
│ 1950-02-01                           │ 34.730                               │
├──────────────────────────────────────┼──────────────────────────────────────┤
│ 1950-03-01                           │ 34.730                               │

...........

You can also convert tabular data into different formats (the source could be remote as well):

$ data cat prices.csv prices.md
> All done! Your data is saved in "prices.md"
user@pc:~/Downloads$ cat prices.md
| date       | price    |
| ---------- | -------- |
| 1950-02-01 | 34.730   |
| 1950-03-01 | 34.730   |

data init

Data-cli has an init command that will automatically generate Data Package metadata including scanning the current directory for data files and inferring [table schema] for tabular files:

$ data init
This process initializes a new datapackage.json file.
Once there is a datapackage.json file, you can still run `data init`
to update/extend it.
Press ^C at any time to quit.

? Enter Data Package name prices
? Enter Data Package title prices
? Do you want to add following file as a resource "prices.csv" - y/n? y
prices.csv is just added to resources
? Do you want to add following file as a resource "prices.xls" - y/n? y
prices.xls is just added to resources

? Going to write to /home/user/Downloads/datapackage.json:
{
  "name": "prices",
  "title": "prices",
  "resources": [
    {
      "path": "prices.csv",
      "name": "prices",
      "format": "csv",
....
    },
      "schema": {
        "fields": [
          {
            "name": "date",
            "type": "date",
            "format": "default"
          },
          {
........
    {
      "path": "prices.xls",
      "pathType": "local",
      "name": "prices",
      "format": "xls",
      "mediatype": "application/vnd.ms-excel",
      "encoding": "windows-1250"
    }
  ]
}


Is that OK - y/n? y
datapackage.json file is saved in /home/user/Downloads/datapackage.json

data validate

$ data validate path/to/correct/datapackage
> Your Data Package is valid!
$ data validate path/to/invalid-data
> Error! Validation has failed for "missing-column"
> Error! The column header names do not match the field names in the schema on line 2

data help

Also you can run "help" command in your terminal to see command docs:

$ data help
'General description'
$ data help push
> 'push command description'

# data help get
# data help init
# etc ...

Installation

npm install data-cli --global

After installation you can run data-cli by the name data:

data --version
> 0.8.9

If you're not using NPM you can install data-cli binaries following this instructions.

For developers

Build Status XO code style Issues

Configuration

Configuration is in ~/.config/datahub/config.json. In general, you should not need to edit this by hand. You can also override any variables in there using environment variables or on the command line by using the same name e.g.

$ data login --api https://api-testing.datahub.io

NB: you can set a custom location for the config.json config file using the DATAHUB_JSON environment variable e.g.:

export DATAHUB_JSON=~/.config/datahub/my-special-config.json

Environment

You need to have Node.js version >7.6

NOTE: if you're a developer, you need to set datahub=dev environment variable so your usage of the CLI isn't tracked in the analytics:

It is recommended that you set this up permanently, e.g., MacOS users need to edit ~/.bash_profile file - add this script in your ~/.bash_profile:

# The next line sets 'datahub' env var so data-cli doesn't send tracking data to Analytics
export datahub=dev

and then restart your terminal.

Install

$ npm install

Running tests

We use Ava for our tests. For running tests use:

$ [sudo] npm test

To run tests in watch mode:

$ [sudo] npm run watch:test

We also have tests for push command that publishes some of test datasets to DataHub. While Travis runs all tests on every commit, the push tests are run only on tagged commits. To run these tests locally you need to have credentials for 'test' user and use following command:

$ [sudo] npm test test/push/push.test.js

Lint

We use XO for checking our code for JS standard/convention/style:

# When you run tests, it first runs lint:
$ npm test

# To run lint separately:
$ npm run lint # shows errors only

# Fixing erros automatically:
$ xo --fix