Andrew Clancy nite

## debounce.R
# from https://gist.github.com/jcheng5/6141ea7066e62cafb31c
# Returns a reactive that debounces the given expression by the given time in
# milliseconds.
#
# This is not a true debounce in that it will not prevent \code{expr} from being
# called many times (in fact it may be called more times than usual), but
# rather, the reactive invalidation signal that is produced by expr is debounced
# instead. This means that this function should be used when \code{expr} is
# cheap but the things it will trigger (outputs and reactives that use
# \code{expr}) are expensive.

## curry.py
def curry(func):
    def f(*args):
        outerArgs = args
        next = lambda *args : f(*args, *outerArgs)
        next.value = lambda: func(args)
        return next
    return f

add = curry(sum)

## kvp.js
/**
 * Serialise input as key-value pair string, eg. for human-readable logs.
 *
 * @param {any} body
 * @param {number} nest
 * @param {string} delimiter
 * @param {string} arrayDelimiter
 * @param {boolean} nested
 * @returns {string}
 */

## grid-selection.directive.ts
import {Directive, EventEmitter, Output} from '@angular/core';
import {AgGridNg2} from 'ag-grid-angular';
import {GridApi} from 'ag-grid';

/***
 * Range selection directive which selects & highlights rows for any selected cell
 * (ctrl+click for multiple ranges) and emits a 'rangeSelectionRowsChanged' with a
 * rows property of selected rows.
 *
 * NOTE: this only currently supports client-side grids.

## plotly_crossfilter.py
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import plotly.graph_objs as go
from dash.dependencies import Output, Input, State
import dash_table_experiments as dt
from plotly.graph_objs.layout import Margin

app = dash.Dash(static_folder='static')

## js.ipynb

      
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                / js.ipynb
            
            
              Last active
              April 1, 2019 21:40
            
              
                Jupyter Notebook with client-side javascript interactive data visualisation in d3 & Plotly plots, plus a http fetch
              
          
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## index.html
<html>
  <head>
  	<meta name="viewport" content="width=device-width" />
  	<title>ParticleSlider</title>
  </head>
  <body id="particle-slider">
      <div class="slides">
        <div id="first-slide" class="slide"
        style="width: 100%; height 100%"
  data-noise="100"

## AgGridWrapper.tsx
import {ColDef, ColGroupDef, ColumnApi, GridApi} from 'ag-grid-community';
import {AgGridReact} from 'ag-grid-react';
import {AgGridReactProps} from 'ag-grid-react/lib/agGridReact';
import {functions, isEqual, omit} from 'lodash';
import log from 'loglevel';
import React, {useState} from 'react';
import useDeepCompareEffect from 'use-deep-compare-effect'

const gridStateChangeEvents = ['model', 'displayedColumnsChanged'];

## toObservable.ts
import { Observable } from 'rxjs';
import { computed, IValueDidChange } from 'mobx';
import isNil from 'lodash/isNil';
import omit from 'lodash/omit';
import { IEqualsComparer } from 'mobx/lib/internal';

interface ToObservableOptions<T> {
    initial?: boolean;
    equals?: IEqualsComparer<T>;
}

## pivot.ts
function pivot(meltedData, pivotCols: string[], varName: string, valueName: string) {
    const groups = {};

    for (const d of meltedData) {
        const key = pivotCols.map((k) => d[k]).join('|');
        const group = groups[key];
        groups[key] = {
            ...(group ? group : fromPairs(pivotCols.map((k) => [k, d[k]]))),
            [d[varName]]: d[valueName],
        };
	# from https://gist.github.com/jcheng5/6141ea7066e62cafb31c
	# Returns a reactive that debounces the given expression by the given time in
	# milliseconds.
	#
	# This is not a true debounce in that it will not prevent \code{expr} from being
	# called many times (in fact it may be called more times than usual), but
	# rather, the reactive invalidation signal that is produced by expr is debounced
	# instead. This means that this function should be used when \code{expr} is
	# cheap but the things it will trigger (outputs and reactives that use
	# \code{expr}) are expensive.
	def curry(func):
	def f(*args):
	outerArgs = args
	next = lambda args : f(args, *outerArgs)
	next.value = lambda: func(args)
	return next
	return f

	add = curry(sum)
	/**
	* Serialise input as key-value pair string, eg. for human-readable logs.
	*
	* @param {any} body
	* @param {number} nest
	* @param {string} delimiter
	* @param {string} arrayDelimiter
	* @param {boolean} nested
	* @returns {string}
	*/
	import {Directive, EventEmitter, Output} from '@angular/core';
	import {AgGridNg2} from 'ag-grid-angular';
	import {GridApi} from 'ag-grid';

	/***
	* Range selection directive which selects & highlights rows for any selected cell
	* (ctrl+click for multiple ranges) and emits a 'rangeSelectionRowsChanged' with a
	* rows property of selected rows.
	*
	* NOTE: this only currently supports client-side grids.
	import dash
	import dash_core_components as dcc
	import dash_html_components as html
	import pandas as pd
	import plotly.graph_objs as go
	from dash.dependencies import Output, Input, State
	import dash_table_experiments as dt
	from plotly.graph_objs.layout import Margin

	app = dash.Dash(static_folder='static')
	<html>
	<head>
	<meta name="viewport" content="width=device-width" />
	<title>ParticleSlider</title>
	</head>
	<body id="particle-slider">
	<div class="slides">
	<div id="first-slide" class="slide"
	style="width: 100%; height 100%"
	data-noise="100"
	import {ColDef, ColGroupDef, ColumnApi, GridApi} from 'ag-grid-community';
	import {AgGridReact} from 'ag-grid-react';
	import {AgGridReactProps} from 'ag-grid-react/lib/agGridReact';
	import {functions, isEqual, omit} from 'lodash';
	import log from 'loglevel';
	import React, {useState} from 'react';
	import useDeepCompareEffect from 'use-deep-compare-effect'

	const gridStateChangeEvents = ['model', 'displayedColumnsChanged'];
	import { Observable } from 'rxjs';
	import { computed, IValueDidChange } from 'mobx';
	import isNil from 'lodash/isNil';
	import omit from 'lodash/omit';
	import { IEqualsComparer } from 'mobx/lib/internal';

	interface ToObservableOptions<T> {
	initial?: boolean;
	equals?: IEqualsComparer<T>;
	}
	function pivot(meltedData, pivotCols: string[], varName: string, valueName: string) {
	const groups = {};

	for (const d of meltedData) {
	const key = pivotCols.map((k) => d[k]).join('\|');
	const group = groups[key];
	groups[key] = {
	...(group ? group : fromPairs(pivotCols.map((k) => [k, d[k]]))),
	[d[varName]]: d[valueName],
	};