# AutoTrain Dataset for project: javascript-traing-1

## Dataset Description

This dataset has been automatically processed by AutoTrain for project javascript-traing-1.

### Languages

The BCP-47 code for the dataset's language is unk.

## Dataset Structure

### Data Instances

A sample from this dataset looks as follows:

```json
[
  {
    "target": "test/NavbarSpec.js",
    "feat_repo_name": "aabenoja/react-bootstrap",
    "text": "import React from 'react';\nimport ReactTestUtils from 'react/lib/ReactTestUtils';\nimport Navbar from '../src/Navbar';\nimport Nav from '../src/Nav';\n\ndescribe('Nav', function () {\n\n  it('Should create nav element', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar />\n    );\n    let nav = instance.getDOMNode();\n    assert.equal(nav.nodeName, 'NAV');\n    assert.ok(nav.className.match(/\\bnavbar\\b/));\n    assert.ok(nav.getAttribute('role'), 'navigation');\n  });\n\n  it('Should add fixedTop variation class', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar fixedTop />\n    );\n    assert.ok(ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'navbar-fixed-top'));\n  });\n\n  it('Should add fixedBottom variation class', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar fixedBottom />\n    );\n    assert.ok(ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'navbar-fixed-bottom'));\n  });\n\n  it('Should add staticTop variation class', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar staticTop />\n    );\n    assert.ok(ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'navbar-static-top'));\n  });\n\n  it('Should add inverse variation class', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar inverse />\n    );\n    assert.ok(ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'navbar-inverse'));\n  });\n\n  it('Should add fluid variation class', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar fluid />\n    );\n    assert.ok(ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'container-fluid'));\n  });\n\n  it('Should override role attribute', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar role=\"banner\"/>\n    );\n    assert.ok(instance.getDOMNode().getAttribute('role'), 'banner');\n  });\n\n  it('Should override node class', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar componentClass={'header'}/>\n    );\n    assert.ok(instance.getDOMNode().nodeName, 'HEADER');\n  });\n\n  it('Should add header with brand', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar brand=\"Brand\" />\n    );\n\n    let header = ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'navbar-header');\n\n    assert.ok(header);\n\n    let brand = ReactTestUtils.findRenderedDOMComponentWithClass(header, 'navbar-brand');\n\n    assert.ok(brand);\n    assert.equal(brand.getDOMNode().innerText, 'Brand');\n  });\n\n  it('Should add header with brand component', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar brand={<a>Brand</a>} />\n    );\n\n    let header = ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'navbar-header');\n\n    assert.ok(header);\n\n    let brand = ReactTestUtils.findRenderedDOMComponentWithClass(header, 'navbar-brand');\n\n    assert.ok(brand);\n    assert.equal(brand.getDOMNode().nodeName, 'A');\n    assert.equal(brand.getDOMNode().innerText, 'Brand');\n  });\n\n  it('Should pass navbar prop to navs', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar brand=\"Brand\">\n        <Nav />\n      </Navbar>\n    );\n\n    let nav = ReactTestUtils.findRenderedComponentWithType(instance, Nav);\n\n    assert.ok(nav.props.navbar);\n  });\n\n  it('Should pass nav prop to ul', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Nav />\n    );\n\n    let navNode = ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'nav').getDOMNode();\n    assert.ok(navNode);\n    assert.equal(navNode.nodeName, 'UL');\n    assert.equal(navNode.parentNode.nodeName, 'NAV');\n\n    instance.setProps({navbar: true});\n\n    navNode = ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'nav').getDOMNode();\n    assert.ok(navNode);\n    assert.equal(navNode.nodeName, 'UL');\n    assert.equal(navNode.parentNode.nodeName, 'DIV');\n  });\n\n  it('Should add header when toggleNavKey is 0', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar toggleNavKey={0}>\n        <Nav eventKey={0} />\n      </Navbar>\n    );\n\n    let header = ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'navbar-header');\n\n    assert.ok(header);\n  });\n\n  it('Should add header when toggleNavKey is 1', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar toggleNavKey={1}>\n        <Nav eventKey={1} />\n      </Navbar>\n    );\n\n    let header = ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'navbar-header');\n\n    assert.ok(header);\n  });\n\n  it('Should add header when toggleNavKey is string', function () {\n    let instance = ReactTestUtils.renderIntoDocument(\n      <Navbar toggleNavKey={'string'}>\n        <Nav eventKey={'string'} />\n      </Navbar>\n    );\n\n    let header = ReactTestUtils.findRenderedDOMComponentWithClass(instance, 'navbar-header');\n\n    assert.ok(header);\n  });\n});\n"
  },
  {
    "target": "node_modules/rc-slider/lib/common/Steps.js",
    "feat_repo_name": "maty21/statistisc",
    "text": "'use strict';\n\nObject.defineProperty(exports, \"__esModule\", {\n  value: true\n});\n\nvar _defineProperty2 = require('babel-runtime/helpers/defineProperty');\n\nvar _defineProperty3 = _interopRequireDefault(_defineProperty2);\n\nvar _react = require('react');\n\nvar _react2 = _interopRequireDefault(_react);\n\nvar _classnames = require('classnames');\n\nvar _classnames2 = _interopRequireDefault(_classnames);\n\nvar _warning = require('warning');\n\nvar _warning2 = _interopRequireDefault(_warning);\n\nfunction _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { \"default\": obj }; }\n\nvar calcPoints = function calcPoints(vertical, marks, dots, step, min, max) {\n  (0, _warning2[\"default\"])(dots ? step > 0 : true, '`Slider[step]` should be a positive number in order to make Slider[dots] work.');\n  var points = Object.keys(marks).map(parseFloat);\n  if (dots) {\n    for (var i = min; i <= max; i = i + step) {\n      if (points.indexOf(i) >= 0) continue;\n      points.push(i);\n    }\n  }\n  return points;\n};\n\nvar Steps = function Steps(_ref) {\n  var prefixCls = _ref.prefixCls,\n      vertical = _ref.vertical,\n      marks = _ref.marks,\n      dots = _ref.dots,\n      step = _ref.step,\n      included = _ref.included,\n      lowerBound = _ref.lowerBound,\n      upperBound = _ref.upperBound,\n      max = _ref.max,\n      min = _ref.min;\n\n  var range = max - min;\n  var elements = calcPoints(vertical, marks, dots, step, min, max).map(function (point) {\n    var _classNames;\n\n    var offset = Math.abs(point - min) / range * 100 + '%';\n    var style = vertical ? { bottom: offset } : { left: offset };\n\n    var isActived = !included && point === upperBound || included && point <= upperBound && point >= lowerBound;\n    var pointClassName = (0, _classnames2[\"default\"])((_classNames = {}, (0, _defineProperty3[\"default\"])(_classNames, prefixCls + '-dot', true), (0, _defineProperty3[\"default\"])(_classNames, prefixCls + '-dot-active', isActived), _classNames));\n\n    return _react2[\"default\"].createElement('span', { className: pointClassName, style: style, key: point });\n  });\n\n  return _react2[\"default\"].createElement(\n    'div',\n    { className: prefixCls + '-step' },\n    elements\n  );\n};\n\nexports[\"default\"] = Steps;\nmodule.exports = exports['default'];"
  }
]
```

### Dataset Fields

The dataset has the following fields (also called "features"):

```json
{
  "target": "Value(dtype='string', id=None)",
  "feat_repo_name": "Value(dtype='string', id=None)",
  "text": "Value(dtype='string', id=None)"
}
```

### Dataset Splits

This dataset is split into a train and validation split. The split sizes are as follow:

| Split name   | Num samples         |
| ------------ | ------------------- |
| train        | 80000 |
| valid        | 20000 |

task_categories:summarization region:us
{"task_categories": ["summarization"]}
TAGS
#task_categories-summarization #region-us 

AutoTrain Dataset for project: javascript-traing-1
==================================================


Dataset Description
-------------------


This dataset has been automatically processed by AutoTrain for project javascript-traing-1.


### Languages


The BCP-47 code for the dataset's language is unk.


Dataset Structure
-----------------


### Data Instances


A sample from this dataset looks as follows:


### Dataset Fields


The dataset has the following fields (also called "features"):


### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow:




### Languages


The BCP-47 code for the dataset's language is unk.


Dataset Structure
----------------- ### Data Instances


A sample from this dataset looks as follows: ### Dataset Fields


The dataset has the following fields (also called "features"): ### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow:
TAGS
#task_categories-summarization #region-us 
 ### Languages


The BCP-47 code for the dataset's language is unk.


Dataset Structure
----------------- ### Data Instances


A sample from this dataset looks as follows: ### Dataset Fields


The dataset has the following fields (also called "features"): ### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow:
passage: TAGS
#task_categories-summarization #region-us 
### Languages


The BCP-47 code for the dataset's language is unk.


Dataset Structure
-----------------### Data Instances


A sample from this dataset looks as follows:### Dataset Fields


The dataset has the following fields (also called "features"):### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow: