Monty  Boehm

Monty Boehm

1659671880

A Step By Step Guide to D3.js Chart Usage in Ijulia Notebooks

Workflow:

  • create dummy data to experiment with chart
  • write d3 chart as script that is loaded in index.html file
  • transform Javascript script to function:
    • in index.html file:
      • select canvas
      • set customized parameters
      • load data
    • in function:
      • set default parameters, create access functions
      • remove data loading
      • create inner function: based on selection and data
  • create Julia API:
    • save data to disk
    • alternatively: directly write data to Javascript code
    • TODO: print warning that data is written to disk
    • load data in Javascript
    • forward chart options to Javascript
    • call chart
    • return full Javascript code
    • TODO: include CSS somehow

Original article source at: https://github.com/cgroll/ijulia_d3_tutorial 

#julia #d3 

What is GEEK

Buddha Community

A Step By Step Guide to D3.js Chart Usage in Ijulia Notebooks

NBB: Ad-hoc CLJS Scripting on Node.js

Nbb

Not babashka. Node.js babashka!?

Ad-hoc CLJS scripting on Node.js.

Status

Experimental. Please report issues here.

Goals and features

Nbb's main goal is to make it easy to get started with ad hoc CLJS scripting on Node.js.

Additional goals and features are:

  • Fast startup without relying on a custom version of Node.js.
  • Small artifact (current size is around 1.2MB).
  • First class macros.
  • Support building small TUI apps using Reagent.
  • Complement babashka with libraries from the Node.js ecosystem.

Requirements

Nbb requires Node.js v12 or newer.

How does this tool work?

CLJS code is evaluated through SCI, the same interpreter that powers babashka. Because SCI works with advanced compilation, the bundle size, especially when combined with other dependencies, is smaller than what you get with self-hosted CLJS. That makes startup faster. The trade-off is that execution is less performant and that only a subset of CLJS is available (e.g. no deftype, yet).

Usage

Install nbb from NPM:

$ npm install nbb -g

Omit -g for a local install.

Try out an expression:

$ nbb -e '(+ 1 2 3)'
6

And then install some other NPM libraries to use in the script. E.g.:

$ npm install csv-parse shelljs zx

Create a script which uses the NPM libraries:

(ns script
  (:require ["csv-parse/lib/sync$default" :as csv-parse]
            ["fs" :as fs]
            ["path" :as path]
            ["shelljs$default" :as sh]
            ["term-size$default" :as term-size]
            ["zx$default" :as zx]
            ["zx$fs" :as zxfs]
            [nbb.core :refer [*file*]]))

(prn (path/resolve "."))

(prn (term-size))

(println (count (str (fs/readFileSync *file*))))

(prn (sh/ls "."))

(prn (csv-parse "foo,bar"))

(prn (zxfs/existsSync *file*))

(zx/$ #js ["ls"])

Call the script:

$ nbb script.cljs
"/private/tmp/test-script"
#js {:columns 216, :rows 47}
510
#js ["node_modules" "package-lock.json" "package.json" "script.cljs"]
#js [#js ["foo" "bar"]]
true
$ ls
node_modules
package-lock.json
package.json
script.cljs

Macros

Nbb has first class support for macros: you can define them right inside your .cljs file, like you are used to from JVM Clojure. Consider the plet macro to make working with promises more palatable:

(defmacro plet
  [bindings & body]
  (let [binding-pairs (reverse (partition 2 bindings))
        body (cons 'do body)]
    (reduce (fn [body [sym expr]]
              (let [expr (list '.resolve 'js/Promise expr)]
                (list '.then expr (list 'clojure.core/fn (vector sym)
                                        body))))
            body
            binding-pairs)))

Using this macro we can look async code more like sync code. Consider this puppeteer example:

(-> (.launch puppeteer)
      (.then (fn [browser]
               (-> (.newPage browser)
                   (.then (fn [page]
                            (-> (.goto page "https://clojure.org")
                                (.then #(.screenshot page #js{:path "screenshot.png"}))
                                (.catch #(js/console.log %))
                                (.then #(.close browser)))))))))

Using plet this becomes:

(plet [browser (.launch puppeteer)
       page (.newPage browser)
       _ (.goto page "https://clojure.org")
       _ (-> (.screenshot page #js{:path "screenshot.png"})
             (.catch #(js/console.log %)))]
      (.close browser))

See the puppeteer example for the full code.

Since v0.0.36, nbb includes promesa which is a library to deal with promises. The above plet macro is similar to promesa.core/let.

Startup time

$ time nbb -e '(+ 1 2 3)'
6
nbb -e '(+ 1 2 3)'   0.17s  user 0.02s system 109% cpu 0.168 total

The baseline startup time for a script is about 170ms seconds on my laptop. When invoked via npx this adds another 300ms or so, so for faster startup, either use a globally installed nbb or use $(npm bin)/nbb script.cljs to bypass npx.

Dependencies

NPM dependencies

Nbb does not depend on any NPM dependencies. All NPM libraries loaded by a script are resolved relative to that script. When using the Reagent module, React is resolved in the same way as any other NPM library.

Classpath

To load .cljs files from local paths or dependencies, you can use the --classpath argument. The current dir is added to the classpath automatically. So if there is a file foo/bar.cljs relative to your current dir, then you can load it via (:require [foo.bar :as fb]). Note that nbb uses the same naming conventions for namespaces and directories as other Clojure tools: foo-bar in the namespace name becomes foo_bar in the directory name.

To load dependencies from the Clojure ecosystem, you can use the Clojure CLI or babashka to download them and produce a classpath:

$ classpath="$(clojure -A:nbb -Spath -Sdeps '{:aliases {:nbb {:replace-deps {com.github.seancorfield/honeysql {:git/tag "v2.0.0-rc5" :git/sha "01c3a55"}}}}}')"

and then feed it to the --classpath argument:

$ nbb --classpath "$classpath" -e "(require '[honey.sql :as sql]) (sql/format {:select :foo :from :bar :where [:= :baz 2]})"
["SELECT foo FROM bar WHERE baz = ?" 2]

Currently nbb only reads from directories, not jar files, so you are encouraged to use git libs. Support for .jar files will be added later.

Current file

The name of the file that is currently being executed is available via nbb.core/*file* or on the metadata of vars:

(ns foo
  (:require [nbb.core :refer [*file*]]))

(prn *file*) ;; "/private/tmp/foo.cljs"

(defn f [])
(prn (:file (meta #'f))) ;; "/private/tmp/foo.cljs"

Reagent

Nbb includes reagent.core which will be lazily loaded when required. You can use this together with ink to create a TUI application:

$ npm install ink

ink-demo.cljs:

(ns ink-demo
  (:require ["ink" :refer [render Text]]
            [reagent.core :as r]))

(defonce state (r/atom 0))

(doseq [n (range 1 11)]
  (js/setTimeout #(swap! state inc) (* n 500)))

(defn hello []
  [:> Text {:color "green"} "Hello, world! " @state])

(render (r/as-element [hello]))

Promesa

Working with callbacks and promises can become tedious. Since nbb v0.0.36 the promesa.core namespace is included with the let and do! macros. An example:

(ns prom
  (:require [promesa.core :as p]))

(defn sleep [ms]
  (js/Promise.
   (fn [resolve _]
     (js/setTimeout resolve ms))))

(defn do-stuff
  []
  (p/do!
   (println "Doing stuff which takes a while")
   (sleep 1000)
   1))

(p/let [a (do-stuff)
        b (inc a)
        c (do-stuff)
        d (+ b c)]
  (prn d))
$ nbb prom.cljs
Doing stuff which takes a while
Doing stuff which takes a while
3

Also see API docs.

Js-interop

Since nbb v0.0.75 applied-science/js-interop is available:

(ns example
  (:require [applied-science.js-interop :as j]))

(def o (j/lit {:a 1 :b 2 :c {:d 1}}))

(prn (j/select-keys o [:a :b])) ;; #js {:a 1, :b 2}
(prn (j/get-in o [:c :d])) ;; 1

Most of this library is supported in nbb, except the following:

  • destructuring using :syms
  • property access using .-x notation. In nbb, you must use keywords.

See the example of what is currently supported.

Examples

See the examples directory for small examples.

Also check out these projects built with nbb:

API

See API documentation.

Migrating to shadow-cljs

See this gist on how to convert an nbb script or project to shadow-cljs.

Build

Prequisites:

  • babashka >= 0.4.0
  • Clojure CLI >= 1.10.3.933
  • Node.js 16.5.0 (lower version may work, but this is the one I used to build)

To build:

  • Clone and cd into this repo
  • bb release

Run bb tasks for more project-related tasks.

Download Details:
Author: borkdude
Download Link: Download The Source Code
Official Website: https://github.com/borkdude/nbb 
License: EPL-1.0

#node #javascript

John  Smith

John Smith

1657107416

Find the Best Restaurant Mobile App Development Company in Abu Dhbai

The era of mobile app development has completely changed the scenario for businesses in regions like Abu Dhabi. Restaurants and food delivery businesses are experiencing huge benefits via smart business applications. The invention and development of the food ordering app have helped all-scale businesses reach new customers and boost sales and profit. 

As a result, many business owners are searching for the best restaurant mobile app development company in Abu Dhabi. If you are also searching for the same, this article is helpful for you. It will let you know the step-by-step process to hire the right team of restaurant mobile app developers. 

Step-by-Step Process to Find the Best Restaurant App Development Company

Searching for the top mobile app development company in Abu Dhabi? Don't know the best way to search for professionals? Don't panic! Here is the step-by-step process to hire the best professionals. 

#Step 1 – Know the Company's Culture

Knowing the organization's culture is very crucial before finalizing a food ordering app development company in Abu Dhabi. An organization's personality is shaped by its common beliefs, goals, practices, or company culture. So, digging into the company culture reveals the core beliefs of the organization, its objectives, and its development team. 

Now, you might be wondering, how will you identify the company's culture? Well, you can take reference from the following sources – 

  • Social media posts 
  • App development process
  • About us Page
  • Client testimonials

#Step 2 - Refer to Clients' Reviews

Another best way to choose the On-demand app development firm for your restaurant business is to refer to the clients' reviews. Reviews are frequently available on the organization's website with a tag of "Reviews" or "Testimonials." It's important to read the reviews as they will help you determine how happy customers are with the company's app development process. 

You can also assess a company's abilities through reviews and customer testimonials. They can let you know if the mobile app developers create a valuable app or not. 

#Step 3 – Analyze the App Development Process

Regardless of the company's size or scope, adhering to the restaurant delivery app development process will ensure the success of your business application. Knowing the processes an app developer follows in designing and producing a top-notch app will help you know the working process. Organizations follow different app development approaches, so getting well-versed in the process is essential before finalizing any mobile app development company. 

#Step 4 – Consider Previous Experience

Besides considering other factors, considering the previous experience of the developers is a must. You can obtain a broad sense of the developer's capacity to assist you in creating a unique mobile application for a restaurant business.

You can also find out if the developers' have contributed to the creation of other successful applications or not. It will help you know the working capacity of a particular developer or organization. Prior experience is essential to evaluating their work. For instance, whether they haven't previously produced an app similar to yours or not. 

#Step 5 – Check for Their Technical Support

As you expect a working and successful restaurant mobile app for your business, checking on this factor is a must. A well-established organization is nothing without a good technical support team. So, ensure whatever restaurant mobile app development company you choose they must be well-equipped with a team of dedicated developers, designers, and testers. 

Strong tech support from your mobile app developers will help you identify new bugs and fix them bugs on time. All this will ensure the application's success. 

#Step 6 – Analyze Design Standards

Besides focusing on an organization's development, testing, and technical support, you should check the design standards. An appealing design is crucial in attracting new users and keeping the existing ones stick to your services. So, spend some time analyzing the design standards of an organization. Now, you might be wondering, how will you do it? Simple! By looking at the organization's portfolio. 

Whether hiring an iPhone app development company or any other, these steps apply to all. So, don't miss these steps. 

#Step 7 – Know Their Location

Finally, the last yet very crucial factor that will not only help you finalize the right person for your restaurant mobile app development but will also decide the mobile app development cost. So, you have to choose the location of the developers wisely, as it is a crucial factor in defining the cost. 

Summing Up!!!

Restaurant mobile applications have taken the food industry to heights none have ever considered. As a result, the demand for restaurant mobile app development companies has risen greatly, which is why businesses find it difficult to finalize the right person. But, we hope that after referring to this article, it will now be easier to hire dedicated developers under the desired budget. So, begin the hiring process now and get a well-craft food ordering app in hand. 

Dylan  Iqbal

Dylan Iqbal

1561523460

Matplotlib Cheat Sheet: Plotting in Python

This Matplotlib cheat sheet introduces you to the basics that you need to plot your data with Python and includes code samples.

Data visualization and storytelling with your data are essential skills that every data scientist needs to communicate insights gained from analyses effectively to any audience out there. 

For most beginners, the first package that they use to get in touch with data visualization and storytelling is, naturally, Matplotlib: it is a Python 2D plotting library that enables users to make publication-quality figures. But, what might be even more convincing is the fact that other packages, such as Pandas, intend to build more plotting integration with Matplotlib as time goes on.

However, what might slow down beginners is the fact that this package is pretty extensive. There is so much that you can do with it and it might be hard to still keep a structure when you're learning how to work with Matplotlib.   

DataCamp has created a Matplotlib cheat sheet for those who might already know how to use the package to their advantage to make beautiful plots in Python, but that still want to keep a one-page reference handy. Of course, for those who don't know how to work with Matplotlib, this might be the extra push be convinced and to finally get started with data visualization in Python. 

You'll see that this cheat sheet presents you with the six basic steps that you can go through to make beautiful plots. 

Check out the infographic by clicking on the button below:

Python Matplotlib cheat sheet

With this handy reference, you'll familiarize yourself in no time with the basics of Matplotlib: you'll learn how you can prepare your data, create a new plot, use some basic plotting routines to your advantage, add customizations to your plots, and save, show and close the plots that you make.

What might have looked difficult before will definitely be more clear once you start using this cheat sheet! Use it in combination with the Matplotlib Gallery, the documentation.

Matplotlib 

Matplotlib is a Python 2D plotting library which produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms.

Prepare the Data 

1D Data 

>>> import numpy as np
>>> x = np.linspace(0, 10, 100)
>>> y = np.cos(x)
>>> z = np.sin(x)

2D Data or Images 

>>> data = 2 * np.random.random((10, 10))
>>> data2 = 3 * np.random.random((10, 10))
>>> Y, X = np.mgrid[-3:3:100j, -3:3:100j]
>>> U = 1 X** 2 + Y
>>> V = 1 + X Y**2
>>> from matplotlib.cbook import get_sample_data
>>> img = np.load(get_sample_data('axes_grid/bivariate_normal.npy'))

Create Plot

>>> import matplotlib.pyplot as plt

Figure 

>>> fig = plt.figure()
>>> fig2 = plt.figure(figsize=plt.figaspect(2.0))

Axes 

>>> fig.add_axes()
>>> ax1 = fig.add_subplot(221) #row-col-num
>>> ax3 = fig.add_subplot(212)
>>> fig3, axes = plt.subplots(nrows=2,ncols=2)
>>> fig4, axes2 = plt.subplots(ncols=3)

Save Plot 

>>> plt.savefig('foo.png') #Save figures
>>> plt.savefig('foo.png',  transparent=True) #Save transparent figures

Show Plot

>>> plt.show()

Plotting Routines 

1D Data 

>>> fig, ax = plt.subplots()
>>> lines = ax.plot(x,y) #Draw points with lines or markers connecting them
>>> ax.scatter(x,y) #Draw unconnected points, scaled or colored
>>> axes[0,0].bar([1,2,3],[3,4,5]) #Plot vertical rectangles (constant width)
>>> axes[1,0].barh([0.5,1,2.5],[0,1,2]) #Plot horiontal rectangles (constant height)
>>> axes[1,1].axhline(0.45) #Draw a horizontal line across axes
>>> axes[0,1].axvline(0.65) #Draw a vertical line across axes
>>> ax.fill(x,y,color='blue') #Draw filled polygons
>>> ax.fill_between(x,y,color='yellow') #Fill between y values and 0

2D Data 

>>> fig, ax = plt.subplots()
>>> im = ax.imshow(img, #Colormapped or RGB arrays
      cmap= 'gist_earth', 
      interpolation= 'nearest',
      vmin=-2,
      vmax=2)
>>> axes2[0].pcolor(data2) #Pseudocolor plot of 2D array
>>> axes2[0].pcolormesh(data) #Pseudocolor plot of 2D array
>>> CS = plt.contour(Y,X,U) #Plot contours
>>> axes2[2].contourf(data1) #Plot filled contours
>>> axes2[2]= ax.clabel(CS) #Label a contour plot

Vector Fields 

>>> axes[0,1].arrow(0,0,0.5,0.5) #Add an arrow to the axes
>>> axes[1,1].quiver(y,z) #Plot a 2D field of arrows
>>> axes[0,1].streamplot(X,Y,U,V) #Plot a 2D field of arrows

Data Distributions 

>>> ax1.hist(y) #Plot a histogram
>>> ax3.boxplot(y) #Make a box and whisker plot
>>> ax3.violinplot(z)  #Make a violin plot

Plot Anatomy & Workflow 

Plot Anatomy 

 y-axis      

                           x-axis 

Workflow 

The basic steps to creating plots with matplotlib are:

1 Prepare Data
2 Create Plot
3 Plot
4 Customized Plot
5 Save Plot
6 Show Plot

>>> import matplotlib.pyplot as plt
>>> x = [1,2,3,4]  #Step 1
>>> y = [10,20,25,30] 
>>> fig = plt.figure() #Step 2
>>> ax = fig.add_subplot(111) #Step 3
>>> ax.plot(x, y, color= 'lightblue', linewidth=3)  #Step 3, 4
>>> ax.scatter([2,4,6],
          [5,15,25],
          color= 'darkgreen',
          marker= '^' )
>>> ax.set_xlim(1, 6.5)
>>> plt.savefig('foo.png' ) #Step 5
>>> plt.show() #Step 6

Close and Clear 

>>> plt.cla()  #Clear an axis
>>> plt.clf(). #Clear the entire figure
>>> plt.close(). #Close a window

Plotting Customize Plot 

Colors, Color Bars & Color Maps 

>>> plt.plot(x, x, x, x**2, x, x** 3)
>>> ax.plot(x, y, alpha = 0.4)
>>> ax.plot(x, y, c= 'k')
>>> fig.colorbar(im, orientation= 'horizontal')
>>> im = ax.imshow(img,
            cmap= 'seismic' )

Markers 

>>> fig, ax = plt.subplots()
>>> ax.scatter(x,y,marker= ".")
>>> ax.plot(x,y,marker= "o")

Linestyles 

>>> plt.plot(x,y,linewidth=4.0)
>>> plt.plot(x,y,ls= 'solid') 
>>> plt.plot(x,y,ls= '--') 
>>> plt.plot(x,y,'--' ,x**2,y**2,'-.' ) 
>>> plt.setp(lines,color= 'r',linewidth=4.0)

Text & Annotations 

>>> ax.text(1,
           -2.1, 
           'Example Graph', 
            style= 'italic' )
>>> ax.annotate("Sine", 
xy=(8, 0),
xycoords= 'data', 
xytext=(10.5, 0),
textcoords= 'data', 
arrowprops=dict(arrowstyle= "->", 
connectionstyle="arc3"),)

Mathtext 

>>> plt.title(r '$sigma_i=15$', fontsize=20)

Limits, Legends and Layouts 

Limits & Autoscaling 

>>> ax.margins(x=0.0,y=0.1) #Add padding to a plot
>>> ax.axis('equal')  #Set the aspect ratio of the plot to 1
>>> ax.set(xlim=[0,10.5],ylim=[-1.5,1.5])  #Set limits for x-and y-axis
>>> ax.set_xlim(0,10.5) #Set limits for x-axis

Legends 

>>> ax.set(title= 'An Example Axes',  #Set a title and x-and y-axis labels
            ylabel= 'Y-Axis', 
            xlabel= 'X-Axis')
>>> ax.legend(loc= 'best')  #No overlapping plot elements

Ticks 

>>> ax.xaxis.set(ticks=range(1,5),  #Manually set x-ticks
             ticklabels=[3,100, 12,"foo" ])
>>> ax.tick_params(axis= 'y', #Make y-ticks longer and go in and out
             direction= 'inout', 
              length=10)

Subplot Spacing 

>>> fig3.subplots_adjust(wspace=0.5,   #Adjust the spacing between subplots
             hspace=0.3,
             left=0.125,
             right=0.9,
             top=0.9,
             bottom=0.1)
>>> fig.tight_layout() #Fit subplot(s) in to the figure area

Axis Spines 

>>> ax1.spines[ 'top'].set_visible(False) #Make the top axis line for a plot invisible
>>> ax1.spines['bottom' ].set_position(( 'outward',10))  #Move the bottom axis line outward

Have this Cheat Sheet at your fingertips

Original article source at https://www.datacamp.com

#matplotlib #cheatsheet #python

Leonard  Paucek

Leonard Paucek

1656280800

Jump to Local IDE Code Directly From Browser React Component

React Dev Inspector

Jump to local IDE code directly from browser React component by just a simple click

This package allows users to jump to local IDE code directly from browser React component by just a simple click, which is similar to Chrome inspector but more advanced.

View Demo View Github

Preview

press hotkey (ctrl⌃ + shift⇧ + commmand⌘ + c), then click the HTML element you wish to inspect.

screen record gif (8M size):

Jump to local IDE code directly from browser React component by just a simple click

Installation

npm i -D react-dev-inspector

Usage

Users need to add React component and apply webpack config before connecting your React project with 'react-dev-inspector'.

Note: You should NOT use this package, and React component, webpack config in production mode


 

1. Add Inspector React Component

import React from 'react'
import { Inspector, InspectParams } from 'react-dev-inspector'

const InspectorWrapper = process.env.NODE_ENV === 'development'
  ? Inspector
  : React.Fragment

export const Layout = () => {
  // ...

  return (
     {}}
      onClickElement={(params: InspectParams) => {}}
    >
     
       ...
     
    
  )
}


 

2. Set up Inspector Config

You should add:

  • an inspector babel plugin, to inject source code location info
    • react-dev-inspector/plugins/babel
  • an server api middleware, to open local IDE
    • import { launchEditorMiddleware } from 'react-dev-inspector/plugins/webpack'

to your current project development config.

Such as add babel plugin into your .babelrc or webpack babel-loader config,
add api middleware into your webpack-dev-server config or other server setup.


 

There are some example ways to set up, please pick the one fit your project best.

In common cases, if you're using webpack, you can see #raw-webpack-config,

If your project happen to use vite / nextjs / create-react-app and so on, you can also try out our integrated plugins / examples with

raw webpack config

Example:

// .babelrc.js
module.exports = {
  plugins: [
    /**
     * react-dev-inspector plugin, options docs see:
     * https://github.com/zthxxx/react-dev-inspector#inspector-babel-plugin-options
     */
    'react-dev-inspector/plugins/babel',
  ],
}
// webpack.config.ts
import type { Configuration } from 'webpack'
import { launchEditorMiddleware } from 'react-dev-inspector/plugins/webpack'

const config: Configuration = {
  /**
   * [server side] webpack dev server side middleware for launch IDE app
   */
  devServer: {
    before: (app) => {
      app.use(launchEditorMiddleware)
    },
  },
}


 

usage with Vite2

example project see: https://github.com/zthxxx/react-dev-inspector/tree/master/examples/vite2

example vite.config.ts:

import { defineConfig } from 'vite'
import { inspectorServer } from 'react-dev-inspector/plugins/vite'

export default defineConfig({
  plugins: [
    inspectorServer(),
  ],
})


 

usage with Next.js

use Next.js Custom Server + Customizing Babel Config

example project see: https://github.com/zthxxx/react-dev-inspector/tree/master/examples/nextjs

in server.js, example:

...

const {
  queryParserMiddleware,
  launchEditorMiddleware,
} = require('react-dev-inspector/plugins/webpack')

app.prepare().then(() => {
  createServer((req, res) => {
    /**
     * middlewares, from top to bottom
     */
    const middlewares = [
      /**
       * react-dev-inspector configuration two middlewares for nextjs
       */
      queryParserMiddleware,
      launchEditorMiddleware,

      /** Next.js default app handle */
        (req, res) => handle(req, res),
    ]

    const middlewarePipeline = middlewares.reduceRight(
      (next, middleware) => (
        () => { middleware(req, res, next) }
      ),
      () => {},
    )

    middlewarePipeline()

  }).listen(PORT, (err) => {
    if (err) throw err
    console.debug(`> Ready on http://localhost:${PORT}`)
  })
})

in package.json, example:

  "scripts": {
-    "dev": "next dev",
+    "dev": "node server.js",
    "build": "next build"
  }

in .babelrc.js, example:

module.exports = {
  plugins: [
    /**
     * react-dev-inspector plugin, options docs see:
     * https://github.com/zthxxx/react-dev-inspector#inspector-babel-plugin-options
     */
    'react-dev-inspector/plugins/babel',
  ],
}


 

usage with create-react-app

cra + react-app-rewired + customize-cra example config-overrides.js:

example project see: https://github.com/zthxxx/react-dev-inspector/tree/master/examples/cra

const { ReactInspectorPlugin } = require('react-dev-inspector/plugins/webpack')
const {
  addBabelPlugin,
  addWebpackPlugin,
} = require('customize-cra')

module.exports = override(
  addBabelPlugin([
    'react-dev-inspector/plugins/babel',
    // plugin options docs see:
    // https://github.com/zthxxx/react-dev-inspector#inspector-babel-plugin-options
    {
      excludes: [
        /xxxx-want-to-ignore/,
      ],
    },
  ]),
  addWebpackPlugin(
    new ReactInspectorPlugin(),
  ),
)


 

usage with Umi3

example project see: https://github.com/zthxxx/react-dev-inspector/tree/master/examples/umi3

Example .umirc.dev.ts:

// https://umijs.org/config/
import { defineConfig } from 'umi'

export default defineConfig({
  plugins: [
    'react-dev-inspector/plugins/umi/react-inspector',
  ],
  inspectorConfig: {
    // babel plugin options docs see:
    // https://github.com/zthxxx/react-dev-inspector#inspector-babel-plugin-options
    excludes: [],
  },
})


 

usage with Umi2

Example .umirc.dev.js:

import { launchEditorMiddleware } from 'react-dev-inspector/plugins/webpack'

export default {
  // ...
  extraBabelPlugins: [
    // plugin options docs see:
    // https://github.com/zthxxx/react-dev-inspector#inspector-babel-plugin-options
    'react-dev-inspector/plugins/babel',
  ],

  /**
   * And you need to set `false` to `dll` in `umi-plugin-react`,
   * becase these is a umi2 bug that `dll` cannot work with `devServer.before`
   *
   * https://github.com/umijs/umi/issues/2599
   * https://github.com/umijs/umi/issues/2161
   */
  chainWebpack(config, { webpack }) {
    const originBefore = config.toConfig().devServer

    config.devServer.before((app, server, compiler) => {
      
      app.use(launchEditorMiddleware)
      
      originBefore?.before?.(app, server, compiler)
    })

    return config  
  },
}

usage with Ice.js

Example build.json:

// https://ice.work/docs/guide/basic/build
{
  "plugins": [
    "react-dev-inspector/plugins/ice",
  ]
}


 

Examples Project Code


 

Configuration

Component Props

checkout TS definition under react-dev-inspector/es/Inspector.d.ts.

PropertyDescriptionTypeDefault
keysinspector hotkeys

supported keys see: https://github.com/jaywcjlove/hotkeys#supported-keys
string[]['control', 'shift', 'command', 'c']
disableLaunchEditordisable editor launching

(launch by default in dev Mode, but not in production mode)
booleanfalse
onHoverElementtriggered when mouse hover in inspector mode(params: InspectParams) => void-
onClickElementtriggered when mouse hover in inspector mode(params: InspectParams) => void-
// import type { InspectParams } from 'react-dev-inspector'

interface InspectParams {
  /** hover / click event target dom element */
  element: HTMLElement,
  /** nearest named react component fiber for dom element */
  fiber?: React.Fiber,
  /** source file line / column / path info for react component */
  codeInfo?: {
    lineNumber: string,
    columnNumber: string,
    /**
    * code source file relative path to dev-server cwd(current working directory)
    * need use with `react-dev-inspector/plugins/babel`
    */
    relativePath?: string,
    /**
    * code source file absolute path
    * just need use with `@babel/plugin-transform-react-jsx-source` which auto set by most framework
    */
    absolutePath?: string,
  },
  /** react component name for dom element */
  name?: string,
}


 

Inspector Babel Plugin Options

interface InspectorPluginOptions {
  /** override process.cwd() */
  cwd?: string,
  /** patterns to exclude matched files */
  excludes?: (string | RegExp)[],
}


 

Inspector Loader Props

// import type { ParserPlugin, ParserOptions } from '@babel/parser'
// import type { InspectorConfig } from 'react-dev-inspector/plugins/webpack'

interface InspectorConfig {
  /** patterns to exclude matched files */
  excludes?: (string | RegExp)[],
  /**
   * add extra plugins for babel parser
   * default is ['typescript', 'jsx', 'decorators-legacy', 'classProperties']
   */
  babelPlugins?: ParserPlugin[],
  /** extra babel parser options */
  babelOptions?: ParserOptions,
}


 

IDE / Editor config

This package uses react-dev-utils to launch your local IDE application, but, which one will be open?

In fact, it uses an environment variable named REACT_EDITOR to specify an IDE application, but if you do not set this variable, it will try to open a common IDE that you have open or installed once it is certified.

For example, if you want it always open VSCode when inspection clicked, set export REACT_EDITOR=code in your shell.


 

VSCode

install VSCode command line tools, see the official docs
install-vscode-cli

set env to shell, like .bashrc or .zshrc

export REACT_EDITOR=code


 

WebStorm

  • just set env with an absolute path to shell, like .bashrc or .zshrc (only MacOS)
export REACT_EDITOR='/Applications/WebStorm.app/Contents/MacOS/webstorm'

OR

install WebStorm command line tools
Jump to local IDE code directly from browser React component by just a simple click

then set env to shell, like .bashrc or .zshrc

export REACT_EDITOR=webstorm


 

Vim

Yes! you can also use vim if you want, just set env to shell

export REACT_EDITOR=vim


 

How It Works

Stage 1 - Compile Time

  • [babel plugin] inject source file path/line/column to JSX data attributes props

Stage 2 - Web React Runtime

[React component] Inspector Component in react, for listen hotkeys, and request api to dev-server for open IDE.

Specific, when you click a component DOM, the Inspector will try to obtain its source file info (path/line/column), then request launch-editor api (in stage 3) with absolute file path.

Stage 3 - Dev-server Side

[middleware] setup launchEditorMiddleware in webpack dev-server (or other dev-server), to open file in IDE according to the request params.

Only need in development mode,and you want to open IDE when click a component element.

Not need in prod mode, or you just want inspect dom without open IDE (set disableLaunchEditor={true} to Inspector component props)

Analysis of Theory


Author: zthxxx
Source code: https://github.com/zthxxx/react-dev-inspector
License: MIT license

#react-native #react 

Monty  Boehm

Monty Boehm

1659671880

A Step By Step Guide to D3.js Chart Usage in Ijulia Notebooks

Workflow:

  • create dummy data to experiment with chart
  • write d3 chart as script that is loaded in index.html file
  • transform Javascript script to function:
    • in index.html file:
      • select canvas
      • set customized parameters
      • load data
    • in function:
      • set default parameters, create access functions
      • remove data loading
      • create inner function: based on selection and data
  • create Julia API:
    • save data to disk
    • alternatively: directly write data to Javascript code
    • TODO: print warning that data is written to disk
    • load data in Javascript
    • forward chart options to Javascript
    • call chart
    • return full Javascript code
    • TODO: include CSS somehow

Original article source at: https://github.com/cgroll/ijulia_d3_tutorial 

#julia #d3