1628302560
Hide show div component in react js. In this tutorial, you will learn how to make hide show div component in react js app.
If you want to hide show div components in react js app. So, this example tutorial will guide you step by step on how to hide show div components in react js app.
Note that, in this example will create comp1, comp2, and hideshow components and then include it in app.js file of your react js app.
1677668905
Mocking library for TypeScript inspired by http://mockito.org/
mock
) (also abstract classes) #examplespy
) #examplewhen
) via:verify
)reset
, resetCalls
) #example, #examplecapture
) #example'Expected "convertNumberToString(strictEqual(3))" to be called 2 time(s). But has been called 1 time(s).'
)npm install ts-mockito --save-dev
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance from mock
let foo:Foo = instance(mockedFoo);
// Using instance in source code
foo.getBar(3);
foo.getBar(5);
// Explicit, readable verification
verify(mockedFoo.getBar(3)).called();
verify(mockedFoo.getBar(anything())).called();
// Creating mock
let mockedFoo:Foo = mock(Foo);
// stub method before execution
when(mockedFoo.getBar(3)).thenReturn('three');
// Getting instance
let foo:Foo = instance(mockedFoo);
// prints three
console.log(foo.getBar(3));
// prints null, because "getBar(999)" was not stubbed
console.log(foo.getBar(999));
// Creating mock
let mockedFoo:Foo = mock(Foo);
// stub getter before execution
when(mockedFoo.sampleGetter).thenReturn('three');
// Getting instance
let foo:Foo = instance(mockedFoo);
// prints three
console.log(foo.sampleGetter);
Syntax is the same as with getter values.
Please note, that stubbing properties that don't have getters only works if Proxy object is available (ES6).
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
foo.getBar(1);
foo.getBar(2);
foo.getBar(2);
foo.getBar(3);
// Call count verification
verify(mockedFoo.getBar(1)).once(); // was called with arg === 1 only once
verify(mockedFoo.getBar(2)).twice(); // was called with arg === 2 exactly two times
verify(mockedFoo.getBar(between(2, 3))).thrice(); // was called with arg between 2-3 exactly three times
verify(mockedFoo.getBar(anyNumber()).times(4); // was called with any number arg exactly four times
verify(mockedFoo.getBar(2)).atLeast(2); // was called with arg === 2 min two times
verify(mockedFoo.getBar(anything())).atMost(4); // was called with any argument max four times
verify(mockedFoo.getBar(4)).never(); // was never called with arg === 4
// Creating mock
let mockedFoo:Foo = mock(Foo);
let mockedBar:Bar = mock(Bar);
// Getting instance
let foo:Foo = instance(mockedFoo);
let bar:Bar = instance(mockedBar);
// Some calls
foo.getBar(1);
bar.getFoo(2);
// Call order verification
verify(mockedFoo.getBar(1)).calledBefore(mockedBar.getFoo(2)); // foo.getBar(1) has been called before bar.getFoo(2)
verify(mockedBar.getFoo(2)).calledAfter(mockedFoo.getBar(1)); // bar.getFoo(2) has been called before foo.getBar(1)
verify(mockedFoo.getBar(1)).calledBefore(mockedBar.getFoo(999999)); // throws error (mockedBar.getFoo(999999) has never been called)
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(10)).thenThrow(new Error('fatal error'));
let foo:Foo = instance(mockedFoo);
try {
foo.getBar(10);
} catch (error:Error) {
console.log(error.message); // 'fatal error'
}
You can also stub method with your own implementation
let mockedFoo:Foo = mock(Foo);
let foo:Foo = instance(mockedFoo);
when(mockedFoo.sumTwoNumbers(anyNumber(), anyNumber())).thenCall((arg1:number, arg2:number) => {
return arg1 * arg2;
});
// prints '50' because we've changed sum method implementation to multiply!
console.log(foo.sumTwoNumbers(5, 10));
You can also stub method to resolve / reject promise
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.fetchData("a")).thenResolve({id: "a", value: "Hello world"});
when(mockedFoo.fetchData("b")).thenReject(new Error("b does not exist"));
You can reset just mock call counter
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
foo.getBar(1);
foo.getBar(1);
verify(mockedFoo.getBar(1)).twice(); // getBar with arg "1" has been called twice
// Reset mock
resetCalls(mockedFoo);
// Call count verification
verify(mockedFoo.getBar(1)).never(); // has never been called after reset
You can also reset calls of multiple mocks at once resetCalls(firstMock, secondMock, thirdMock)
Or reset mock call counter with all stubs
// Creating mock
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(1)).thenReturn("one").
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
console.log(foo.getBar(1)); // "one" - as defined in stub
console.log(foo.getBar(1)); // "one" - as defined in stub
verify(mockedFoo.getBar(1)).twice(); // getBar with arg "1" has been called twice
// Reset mock
reset(mockedFoo);
// Call count verification
verify(mockedFoo.getBar(1)).never(); // has never been called after reset
console.log(foo.getBar(1)); // null - previously added stub has been removed
You can also reset multiple mocks at once reset(firstMock, secondMock, thirdMock)
let mockedFoo:Foo = mock(Foo);
let foo:Foo = instance(mockedFoo);
// Call method
foo.sumTwoNumbers(1, 2);
// Check first arg captor values
const [firstArg, secondArg] = capture(mockedFoo.sumTwoNumbers).last();
console.log(firstArg); // prints 1
console.log(secondArg); // prints 2
You can also get other calls using first()
, second()
, byCallIndex(3)
and more...
You can set multiple returning values for same matching values
const mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(anyNumber())).thenReturn('one').thenReturn('two').thenReturn('three');
const foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(1)); // two
console.log(foo.getBar(1)); // three
console.log(foo.getBar(1)); // three - last defined behavior will be repeated infinitely
Another example with specific values
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(1)).thenReturn('one').thenReturn('another one');
when(mockedFoo.getBar(2)).thenReturn('two');
let foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(2)); // two
console.log(foo.getBar(1)); // another one
console.log(foo.getBar(1)); // another one - this is last defined behavior for arg '1' so it will be repeated
console.log(foo.getBar(2)); // two
console.log(foo.getBar(2)); // two - this is last defined behavior for arg '2' so it will be repeated
Short notation:
const mockedFoo:Foo = mock(Foo);
// You can specify return values as multiple thenReturn args
when(mockedFoo.getBar(anyNumber())).thenReturn('one', 'two', 'three');
const foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(1)); // two
console.log(foo.getBar(1)); // three
console.log(foo.getBar(1)); // three - last defined behavior will be repeated infinity
Possible errors:
const mockedFoo:Foo = mock(Foo);
// When multiple matchers, matches same result:
when(mockedFoo.getBar(anyNumber())).thenReturn('one');
when(mockedFoo.getBar(3)).thenReturn('one');
const foo:Foo = instance(mockedFoo);
foo.getBar(3); // MultipleMatchersMatchSameStubError will be thrown, two matchers match same method call
You can mock interfaces too, just instead of passing type to mock
function, set mock
function generic type Mocking interfaces requires Proxy
implementation
let mockedFoo:Foo = mock<FooInterface>(); // instead of mock(FooInterface)
const foo: SampleGeneric<FooInterface> = instance(mockedFoo);
You can mock abstract classes
const mockedFoo: SampleAbstractClass = mock(SampleAbstractClass);
const foo: SampleAbstractClass = instance(mockedFoo);
You can also mock generic classes, but note that generic type is just needed by mock type definition
const mockedFoo: SampleGeneric<SampleInterface> = mock(SampleGeneric);
const foo: SampleGeneric<SampleInterface> = instance(mockedFoo);
You can partially mock an existing instance:
const foo: Foo = new Foo();
const spiedFoo = spy(foo);
when(spiedFoo.getBar(3)).thenReturn('one');
console.log(foo.getBar(3)); // 'one'
console.log(foo.getBaz()); // call to a real method
You can spy on plain objects too:
const foo = { bar: () => 42 };
const spiedFoo = spy(foo);
foo.bar();
console.log(capture(spiedFoo.bar).last()); // [42]
Author: NagRock
Source Code: https://github.com/NagRock/ts-mockito
License: MIT license
1653465344
This PySpark SQL cheat sheet is your handy companion to Apache Spark DataFrames in Python and includes code samples.
You'll probably already know about Apache Spark, the fast, general and open-source engine for big data processing; It has built-in modules for streaming, SQL, machine learning and graph processing. Spark allows you to speed analytic applications up to 100 times faster compared to other technologies on the market today. Interfacing Spark with Python is easy with PySpark: this Spark Python API exposes the Spark programming model to Python.
Now, it's time to tackle the Spark SQL module, which is meant for structured data processing, and the DataFrame API, which is not only available in Python, but also in Scala, Java, and R.
Without further ado, here's the cheat sheet:
This PySpark SQL cheat sheet covers the basics of working with the Apache Spark DataFrames in Python: from initializing the SparkSession to creating DataFrames, inspecting the data, handling duplicate values, querying, adding, updating or removing columns, grouping, filtering or sorting data. You'll also see that this cheat sheet also on how to run SQL Queries programmatically, how to save your data to parquet and JSON files, and how to stop your SparkSession.
Spark SGlL is Apache Spark's module for working with structured data.
A SparkSession can be used create DataFrame, register DataFrame as tables, execute SGL over tables, cache tables, and read parquet files.
>>> from pyspark.sql import SparkSession
>>> spark a SparkSession \
.builder\
.appName("Python Spark SQL basic example") \
.config("spark.some.config.option", "some-value") \
.getOrCreate()
>>> from pyspark.sql.types import*
Infer Schema
>>> sc = spark.sparkContext
>>> lines = sc.textFile(''people.txt'')
>>> parts = lines.map(lambda l: l.split(","))
>>> people = parts.map(lambda p: Row(nameap[0],ageaint(p[l])))
>>> peopledf = spark.createDataFrame(people)
Specify Schema
>>> people = parts.map(lambda p: Row(name=p[0],
age=int(p[1].strip())))
>>> schemaString = "name age"
>>> fields = [StructField(field_name, StringType(), True) for field_name in schemaString.split()]
>>> schema = StructType(fields)
>>> spark.createDataFrame(people, schema).show()
From Spark Data Sources
JSON
>>> df = spark.read.json("customer.json")
>>> df.show()
>>> df2 = spark.read.load("people.json", format="json")
Parquet files
>>> df3 = spark.read.load("users.parquet")
TXT files
>>> df4 = spark.read.text("people.txt")
#Filter entries of age, only keep those records of which the values are >24
>>> df.filter(df["age"]>24).show()
>>> df = df.dropDuplicates()
>>> from pyspark.sql import functions as F
Select
>>> df.select("firstName").show() #Show all entries in firstName column
>>> df.select("firstName","lastName") \
.show()
>>> df.select("firstName", #Show all entries in firstName, age and type
"age",
explode("phoneNumber") \
.alias("contactInfo")) \
.select("contactInfo.type",
"firstName",
"age") \
.show()
>>> df.select(df["firstName"],df["age"]+ 1) #Show all entries in firstName and age, .show() add 1 to the entries of age
>>> df.select(df['age'] > 24).show() #Show all entries where age >24
When
>>> df.select("firstName", #Show firstName and 0 or 1 depending on age >30
F.when(df.age > 30, 1) \
.otherwise(0)) \
.show()
>>> df[df.firstName.isin("Jane","Boris")] #Show firstName if in the given options
.collect()
Like
>>> df.select("firstName", #Show firstName, and lastName is TRUE if lastName is like Smith
df.lastName.like("Smith")) \
.show()
Startswith - Endswith
>>> df.select("firstName", #Show firstName, and TRUE if lastName starts with Sm
df.lastName \
.startswith("Sm")) \
.show()
>>> df.select(df.lastName.endswith("th"))\ #Show last names ending in th
.show()
Substring
>>> df.select(df.firstName.substr(1, 3) \ #Return substrings of firstName
.alias("name")) \
.collect()
Between
>>> df.select(df.age.between(22, 24)) \ #Show age: values are TRUE if between 22 and 24
.show()
Adding Columns
>>> df = df.withColumn('city',df.address.city) \
.withColumn('postalCode',df.address.postalCode) \
.withColumn('state',df.address.state) \
.withColumn('streetAddress',df.address.streetAddress) \
.withColumn('telePhoneNumber', explode(df.phoneNumber.number)) \
.withColumn('telePhoneType', explode(df.phoneNumber.type))
Updating Columns
>>> df = df.withColumnRenamed('telePhoneNumber', 'phoneNumber')
Removing Columns
>>> df = df.drop("address", "phoneNumber")
>>> df = df.drop(df.address).drop(df.phoneNumber)
>>> df.na.fill(50).show() #Replace null values
>>> df.na.drop().show() #Return new df omitting rows with null values
>>> df.na \ #Return new df replacing one value with another
.replace(10, 20) \
.show()
>>> df.groupBy("age")\ #Group by age, count the members in the groups
.count() \
.show()
>>> peopledf.sort(peopledf.age.desc()).collect()
>>> df.sort("age", ascending=False).collect()
>>> df.orderBy(["age","city"],ascending=[0,1])\
.collect()
>>> df.repartition(10)\ #df with 10 partitions
.rdd \
.getNumPartitions()
>>> df.coalesce(1).rdd.getNumPartitions() #df with 1 partition
Registering DataFrames as Views
>>> peopledf.createGlobalTempView("people")
>>> df.createTempView("customer")
>>> df.createOrReplaceTempView("customer")
Query Views
>>> df5 = spark.sql("SELECT * FROM customer").show()
>>> peopledf2 = spark.sql("SELECT * FROM global_temp.people")\
.show()
>>> df.dtypes #Return df column names and data types
>>> df.show() #Display the content of df
>>> df.head() #Return first n rows
>>> df.first() #Return first row
>>> df.take(2) #Return the first n rows >>> df.schema Return the schema of df
>>> df.describe().show() #Compute summary statistics >>> df.columns Return the columns of df
>>> df.count() #Count the number of rows in df
>>> df.distinct().count() #Count the number of distinct rows in df
>>> df.printSchema() #Print the schema of df
>>> df.explain() #Print the (logical and physical) plans
Data Structures
>>> rdd1 = df.rdd #Convert df into an RDD
>>> df.toJSON().first() #Convert df into a RDD of string
>>> df.toPandas() #Return the contents of df as Pandas DataFrame
Write & Save to Files
>>> df.select("firstName", "city")\
.write \
.save("nameAndCity.parquet")
>>> df.select("firstName", "age") \
.write \
.save("namesAndAges.json",format="json")
>>> spark.stop()
Have this Cheat Sheet at your fingertips
Original article source at https://www.datacamp.com
#pyspark #cheatsheet #spark #dataframes #python #bigdata
1598839687
If you are undertaking a mobile app development for your start-up or enterprise, you are likely wondering whether to use React Native. As a popular development framework, React Native helps you to develop near-native mobile apps. However, you are probably also wondering how close you can get to a native app by using React Native. How native is React Native?
In the article, we discuss the similarities between native mobile development and development using React Native. We also touch upon where they differ and how to bridge the gaps. Read on.
Let’s briefly set the context first. We will briefly touch upon what React Native is and how it differs from earlier hybrid frameworks.
React Native is a popular JavaScript framework that Facebook has created. You can use this open-source framework to code natively rendering Android and iOS mobile apps. You can use it to develop web apps too.
Facebook has developed React Native based on React, its JavaScript library. The first release of React Native came in March 2015. At the time of writing this article, the latest stable release of React Native is 0.62.0, and it was released in March 2020.
Although relatively new, React Native has acquired a high degree of popularity. The “Stack Overflow Developer Survey 2019” report identifies it as the 8th most loved framework. Facebook, Walmart, and Bloomberg are some of the top companies that use React Native.
The popularity of React Native comes from its advantages. Some of its advantages are as follows:
Are you wondering whether React Native is just another of those hybrid frameworks like Ionic or Cordova? It’s not! React Native is fundamentally different from these earlier hybrid frameworks.
React Native is very close to native. Consider the following aspects as described on the React Native website:
Due to these factors, React Native offers many more advantages compared to those earlier hybrid frameworks. We now review them.
#android app #frontend #ios app #mobile app development #benefits of react native #is react native good for mobile app development #native vs #pros and cons of react native #react mobile development #react native development #react native experience #react native framework #react native ios vs android #react native pros and cons #react native vs android #react native vs native #react native vs native performance #react vs native #why react native #why use react native
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1632537859
Not babashka. Node.js babashka!?
Ad-hoc CLJS scripting on Node.js.
Experimental. Please report issues here.
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:
Nbb requires Node.js v12 or newer.
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).
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
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
.
$ 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
.
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.
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.
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"
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]))
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.
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:
:syms
.-x
notation. In nbb, you must use keywords.See the example of what is currently supported.
See the examples directory for small examples.
Also check out these projects built with nbb:
See API documentation.
See this gist on how to convert an nbb script or project to shadow-cljs.
Prequisites:
To build:
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