A Performant Interactive Bottom Sheet with Fully Configurable Options

Bottom Sheet

A performant interactive bottom sheet with fully configurable options 🚀

Initially, this project was a cloned of react-native-scroll-bottom-sheet by @rgommezz ❤️. However, it is been fully re-written to add extra functionalities and simplify the approach.

Features

🌟 Modal presentation view, Bottom Sheet Modal.
Smooth interactions & snapping animations.
Support FlatList, SectionList, ScrollView & View scrolling interactions.
Support React Navigation Integration.
Compatible with Reanimated v1 & v2.
Compatible with Expo.
Written in TypeScript.

Installation

Version v1

Link to version 1 branch

This version is written with Reanimated v1

yarn add @gorhom/bottom-sheet
# or
npm install @gorhom/bottom-sheet

⚠️ You need to install react-native-reanimated & react-native-gesture-handler and follow their installation instructions.

Version v2 ( Alpha )

Link to version 2 branch

this version is written with Reanimated v2, although this version is still in alpha phase, yet it provides all version 1 functionalities with the huge performance boost, thanks to Reanimated v2 ❤️

yarn add @gorhom/bottom-sheet@2.0.0-alpha.0
# or
npm install @gorhom/bottom-sheet@2.0.0-alpha.0

⚠️ You need to install react-native-reanimated v2 & react-native-gesture-handler and follow their installation instructions.

Usage

import React, { useCallback, useMemo, useRef } from 'react';
import { View, StyleSheet } from 'react-native';
import BottomSheet from '@gorhom/bottom-sheet';

const App = () => {
  // hooks
  const bottomSheetRef = useRef<BottomSheet>(null);

  // variables
  const snapPoints = useMemo(() => ['25%', '50%', '90%'], []);

  // callbacks
  const handleSheetChanges = useCallback((index: number) => {
    console.log('handleSheetChanges', index);
  }, []);

  // renders
  return (
    <View style={styles.container}>
      <BottomSheet
        ref={bottomSheetRef}
        initialSnapIndex={1}
        snapPoints={snapPoints}
        onChange={handleSheetChanges}
      >
        {/* INSERT A SCROLLABLE HERE */}
      </BottomSheet>
    </View>
  );
};

const styles = StyleSheet.create({
  container: {
    flex: 1,
    padding: 24,
  },
});

export default App;

Props

`initialSnapIndex`

Initial snap index. You also could provide {-1} to initiate bottom sheet in closed state.

required: NO | type: number | default: 0

`snapPoints`

Points for the bottom sheet to snap to, points should be sorted from bottom to top. It accepts array of number, string or mix. String values should be a percentage.

required: YES | type: Array<string | number>
example: [100, ‘50%’, ‘90%’]

`topInset`

Top inset value helps to calculate percentage snap points values. usually comes from @react-navigation/stack hook useHeaderHeight or from react-native-safe-area-context hook useSafeArea.

required: NO | type: number | default: 0

`enabled`

To enable or disable user interaction with the sheet.

required: NO | type: boolean | default: true

`animationDuration`

Snapping animation duration.

required: NO | type: number | default: 500

`animationEasing`

Snapping animation easing function.

required: NO | type: Animated.EasingFunction | default: Easing.out(Easing.back(0.75))

`animatedPosition`

Animated value to be used as a callback for the position node internally.

required: NO | type: Animated.Value

`animatedPositionIndex`

Animated value to be used as a callback for the position index node internally.

required: NO | type: Animated.Value

`handleComponent`

Component to be placed as a sheet handle.

required: NO | type: React.FC<BottomSheetHandleProps>

`backgroundComponent`

Component to be placed as a background.

required: NO | type: React.FC

`onChange`

Callback when sheet position changed to a provided point.

required: NO | type: (index: number) => void

`children`

A scrollable node or normal view.

required: YES | type: () => React.ReactNode | React.ReactNode[] | React.ReactNode

Methods

`snapTo`

Snap to one of the provided points from snapPoints.

type: (index: number) => void

`expand`

Snap to the maximum provided point from snapPoints.

type: () => void

`collapse`

Snap to the minimum provided point from snapPoints.

type: () => void

`close`

Close the bottom sheet.

type: () => void

Hooks

`useBottomSheet`

The library provide useBottomSheet hook to provide the bottom sheet methods, anywhere inside the sheet content.

type: BottomSheetMethods

Scrollables

This library provides a pre-integrated views that utilise an internal functionalities with the bottom sheet to allow smooth interactions. These views i called them Scrollables and they are:

To Do

[x] Add Reanimated v2 support.
[ ] Add tablets support.
[ ] Add Bounce support.

FAQ

How this library differ from `reanimated-bottom-sheet` or `react-native-scroll-bottom-sheet`?

This library was built to provide the most native-like experience and could fit any use-case that developers wants it to be.

While both libraries providing similar experience, but they still missing the following:

reanimated-bottom-sheet

Seamless gesture interaction between the sheet and the content.

react-native-scroll-bottom-sheet

Extracting scrollable content to allow developers customize the sheet content, like integrate React Navigation as the sheet content.

Both libraries are great! and I have used both of them at my work ❤️

How can I integrate `React Navigation`?

here you go React Navigation Integration :)

Will this library support `Reanimated v2`?

Yes 🎉

Built With ❤️

Author

Mo Gorhom

Download Details:

Author: gorhom

Source Code: https://github.com/gorhom/react-native-bottom-sheet

#react #react-native #mobile-apps

What is GEEK

Buddha Community

A Performant Interactive Bottom Sheet with Fully Configurable Options

Robert E. Hilton

1650521873

How to Create the Custom Radio Buttons using only HTML & CSS

In this guide you’ll learn how to create the Custom Radio Buttons using only HTML & CSS.

To create the custom radio buttons using only HTML & CSS. First, you need to create two Files one HTML File and another one is CSS File.

1: First, create an HTML file with the name of index.html

<!DOCTYPE html>
<html lang="en" dir="ltr">
  <head>
    <meta charset="utf-8">
    <title>Custom Radio Buttons | Codequs</title>
    <link rel="stylesheet" href="style.css">
  </head>
  <body>
    <div class="wrapper">
      <input type="radio" name="select" id="option-1" checked>
      <input type="radio" name="select" id="option-2">
      <label for="option-1" class="option option-1">
        <div class="dot"></div>
        <span>Student</span>
      </label>
      <label for="option-2" class="option option-2">
        <div class="dot"></div>
        <span>Teacher</span>
      </label>
    </div>
  </body>
</html>

2: Second, create a CSS file with the name of style.css

@import url('https://fonts.googleapis.com/css?family=Poppins:400,500,600,700&display=swap');
*{
  margin: 0;
  padding: 0;
  box-sizing: border-box;
  font-family: 'Poppins', sans-serif;
}
html,body{
  display: grid;
  height: 100%;
  place-items: center;
  background: #0069d9;
}
.wrapper{
  display: inline-flex;
  background: #fff;
  height: 100px;
  width: 400px;
  align-items: center;
  justify-content: space-evenly;
  border-radius: 5px;
  padding: 20px 15px;
  box-shadow: 5px 5px 30px rgba(0,0,0,0.2);
}
.wrapper .option{
  background: #fff;
  height: 100%;
  width: 100%;
  display: flex;
  align-items: center;
  justify-content: space-evenly;
  margin: 0 10px;
  border-radius: 5px;
  cursor: pointer;
  padding: 0 10px;
  border: 2px solid lightgrey;
  transition: all 0.3s ease;
}
.wrapper .option .dot{
  height: 20px;
  width: 20px;
  background: #d9d9d9;
  border-radius: 50%;
  position: relative;
}
.wrapper .option .dot::before{
  position: absolute;
  content: "";
  top: 4px;
  left: 4px;
  width: 12px;
  height: 12px;
  background: #0069d9;
  border-radius: 50%;
  opacity: 0;
  transform: scale(1.5);
  transition: all 0.3s ease;
}
input[type="radio"]{
  display: none;
}
#option-1:checked:checked ~ .option-1,
#option-2:checked:checked ~ .option-2{
  border-color: #0069d9;
  background: #0069d9;
}
#option-1:checked:checked ~ .option-1 .dot,
#option-2:checked:checked ~ .option-2 .dot{
  background: #fff;
}
#option-1:checked:checked ~ .option-1 .dot::before,
#option-2:checked:checked ~ .option-2 .dot::before{
  opacity: 1;
  transform: scale(1);
}
.wrapper .option span{
  font-size: 20px;
  color: #808080;
}
#option-1:checked:checked ~ .option-1 span,
#option-2:checked:checked ~ .option-2 span{
  color: #fff;
}

Now you’ve successfully created Custom Radio Buttons using only HTML & CSS.

Spring Framework

1647998803

Rate Limit Auto-configure for Spring Cloud Netflix Zuul

Overview

Module to enable rate limit per service in Netflix Zuul.

There are five built-in rate limit approaches:

Authenticated User
- Uses the authenticated username or 'anonymous'
Request Origin
- Uses the user origin request
URL
- Uses the request path of the downstream service
URL Pattern
- Uses the request Ant path pattern to the downstream service
ROLE
- Uses the authenticated user roles
Request method
- Uses the HTTP request method
Request header
- Uses the HTTP request header
Global configuration per service:
- This one does not validate the request Origin, Authenticated User or URI
- To use this approach just don’t set param 'type'

Note	It is possible to combine Authenticated User, Request Origin, URL, ROLE and Request Method just adding multiple values to the list

Usage

Note	If you are using Spring Boot version `1.5.x` you MUST use Spring Cloud Zuul RateLimit version `1.7.x`. Please take a look at the Maven Central and pick the latest artifact in this version line.

Add the dependency on pom.xml

<dependency>
    <groupId>com.marcosbarbero.cloud</groupId>
    <artifactId>spring-cloud-zuul-ratelimit</artifactId>
    <version>${latest-version}</version>
</dependency>

Add the following dependency accordingly to the chosen data storage:

Redis

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>

Consul

<dependency>
   <groupId>org.springframework.cloud</groupId>
   <artifactId>spring-cloud-starter-consul</artifactId>
</dependency>

Spring Data JPA

<dependency>
   <groupId>org.springframework.boot</groupId>
   <artifactId>spring-boot-starter-data-jpa</artifactId>
</dependency>

This implementation also requires a database table, bellow here you can find a sample script:

CREATE TABLE rate (
  rate_key VARCHAR(255) NOT NULL,
  remaining BIGINT,
  remaining_quota BIGINT,
  reset BIGINT,
  expiration TIMESTAMP,
  PRIMARY KEY(rate_key)
);

Bucket4j JCache

<dependency>
     <groupId>com.github.vladimir-bukhtoyarov</groupId>
     <artifactId>bucket4j-core</artifactId>
</dependency>
<dependency>
     <groupId>com.github.vladimir-bukhtoyarov</groupId>
     <artifactId>bucket4j-jcache</artifactId>
</dependency>
<dependency>
     <groupId>javax.cache</groupId>
     <artifactId>cache-api</artifactId>
</dependency>

Bucket4j Hazelcast (depends on Bucket4j JCache)

<dependency>
     <groupId>com.github.vladimir-bukhtoyarov</groupId>
     <artifactId>bucket4j-hazelcast</artifactId>
</dependency>
<dependency>
     <groupId>com.hazelcast</groupId>
     <artifactId>hazelcast</artifactId>
</dependency>

Bucket4j Infinispan (depends on Bucket4j JCache)

<dependency>
     <groupId>com.github.vladimir-bukhtoyarov</groupId>
     <artifactId>bucket4j-infinispan</artifactId>
</dependency>
<dependency>
     <groupId>org.infinispan</groupId>
     <artifactId>infinispan-core</artifactId>
</dependency>

Bucket4j Ignite (depends on Bucket4j JCache)

<dependency>
     <groupId>com.github.vladimir-bukhtoyarov</groupId>
     <artifactId>bucket4j-ignite</artifactId>
</dependency>
<dependency>
     <groupId>org.apache.ignite</groupId>
     <artifactId>ignite-core</artifactId>
</dependency>

Sample YAML configuration

zuul:
  ratelimit:
    key-prefix: your-prefix
    enabled: true
    repository: REDIS
    behind-proxy: true
    add-response-headers: true
    deny-request:
      response-status-code: 404 #default value is 403 (FORBIDDEN)
      origins:
        - 200.187.10.25
        - somedomain.com
    default-policy-list: #optional - will apply unless specific policy exists
      - limit: 10 #optional - request number limit per refresh interval window
        quota: 1000 #optional - request time limit per refresh interval window (in seconds)
        refresh-interval: 60 #default value (in seconds)
        type: #optional
          - user
          - origin
          - url
          - http_method
    policy-list:
      myServiceId:
        - limit: 10 #optional - request number limit per refresh interval window
          quota: 1000 #optional - request time limit per refresh interval window (in seconds)
          refresh-interval: 60 #default value (in seconds)
          type: #optional
            - user
            - origin
            - url
        - type: #optional value for each type
            - user=anonymous
            - origin=somemachine.com
            - url=/api #url prefix
            - role=user
            - http_method=get #case insensitive
            - http_header=customHeader
        - type:
            - url_pattern=/api/*/payment

Sample Properties configuration

zuul.ratelimit.enabled=true
zuul.ratelimit.key-prefix=your-prefix
zuul.ratelimit.repository=REDIS
zuul.ratelimit.behind-proxy=true
zuul.ratelimit.add-response-headers=true

zuul.ratelimit.deny-request.response-status-code=404
zuul.ratelimit.deny-request.origins[0]=200.187.10.25
zuul.ratelimit.deny-request.origins[1]=somedomain.com

zuul.ratelimit.default-policy-list[0].limit=10
zuul.ratelimit.default-policy-list[0].quota=1000
zuul.ratelimit.default-policy-list[0].refresh-interval=60

# Adding multiple rate limit type
zuul.ratelimit.default-policy-list[0].type[0]=user
zuul.ratelimit.default-policy-list[0].type[1]=origin
zuul.ratelimit.default-policy-list[0].type[2]=url
zuul.ratelimit.default-policy-list[0].type[3]=http_method

# Adding the first rate limit policy to "myServiceId"
zuul.ratelimit.policy-list.myServiceId[0].limit=10
zuul.ratelimit.policy-list.myServiceId[0].quota=1000
zuul.ratelimit.policy-list.myServiceId[0].refresh-interval=60
zuul.ratelimit.policy-list.myServiceId[0].type[0]=user
zuul.ratelimit.policy-list.myServiceId[0].type[1]=origin
zuul.ratelimit.policy-list.myServiceId[0].type[2]=url

# Adding the second rate limit policy to "myServiceId"
zuul.ratelimit.policy-list.myServiceId[1].type[0]=user=anonymous
zuul.ratelimit.policy-list.myServiceId[1].type[1]=origin=somemachine.com
zuul.ratelimit.policy-list.myServiceId[1].type[2]=url_pattern=/api/*/payment
zuul.ratelimit.policy-list.myServiceId[1].type[3]=role=user
zuul.ratelimit.policy-list.myServiceId[1].type[4]=http_method=get
zuul.ratelimit.policy-list.myServiceId[1].type[5]=http_header=customHeader

Both 'quota' and 'refresh-interval', can be expressed with Spring Boot’s duration formats:

A regular long representation (using seconds as the default unit)

The standard ISO-8601 format used by java.time.Duration (e.g. PT30M means 30 minutes)

A more readable format where the value and the unit are coupled (e.g. 10s means 10 seconds)

Available implementations

There are eight implementations provided:

Implementation	Data Storage
ConsulRateLimiter	Consul
RedisRateLimiter	Redis
SpringDataRateLimiter	Spring Data
Bucket4jJCacheRateLimiter	Bucket4j
Bucket4jHazelcastRateLimiter
Bucket4jIgniteRateLimiter
Bucket4jInfinispanRateLimiter

Bucket4j implementations require the relevant bean with @Qualifier("RateLimit"):

JCache - javax.cache.Cache

Hazelcast - com.hazelcast.map.IMap

Ignite - org.apache.ignite.IgniteCache

Infinispan - org.infinispan.functional.ReadWriteMap

Common application properties

Property namespace: zuul.ratelimit

Property name	Values	Default Value
enabled	true/false	false
behind-proxy	true/false	false
response-headers	NONE, STANDARD, VERBOSE	VERBOSE
key-prefix	String	${spring.application.name:rate-limit-application}
repository	CONSUL, REDIS, JPA, BUCKET4J_JCACHE, BUCKET4J_HAZELCAST, BUCKET4J_INFINISPAN, BUCKET4J_IGNITE	-
deny-request	DenyRequest	-
default-policy-list	List of Policy	-
policy-list	Map of Lists of Policy	-
postFilterOrder	int	FilterConstants.SEND_RESPONSE_FILTER_ORDER - 10
preFilterOrder	int	FilterConstants.FORM_BODY_WRAPPER_FILTER_ORDER

Deny Request properties

Property name	Values	Default Value
origins	list of origins to have the access denied	-
response-status-code	the http status code to be returned on a denied request	403 (FORBIDDEN)

Policy properties:

Property name	Values	Default Value
limit	number of requests	-
quota	time of requests	-
refresh-interval	seconds	60
type	[ORIGIN, USER, URL, URL_PATTERN, ROLE, HTTP_METHOD, HTTP_HEADER]	[]
breakOnMatch	true/false	false

Further Customization

This section details how to add custom implementations

Key Generator

If the application needs to control the key strategy beyond the options offered by the type property then it can be done just by creating a custom RateLimitKeyGenerator bean[1] implementation adding further qualifiers or something entirely different:

  @Bean
  public RateLimitKeyGenerator ratelimitKeyGenerator(RateLimitProperties properties, RateLimitUtils rateLimitUtils) {
      return new DefaultRateLimitKeyGenerator(properties, rateLimitUtils) {
          @Override
          public String key(HttpServletRequest request, Route route, RateLimitProperties.Policy policy) {
              return super.key(request, route, policy) + ":" + request.getMethod();
          }
      };
  }

Error Handling

This framework uses 3rd party applications to control the rate limit access and these libraries are out of control of this framework. If one of the 3rd party applications fails, the framework will handle this failure in the DefaultRateLimiterErrorHandler class which will log the error upon failure.

If there is a need to handle the errors differently, it can be achieved by defining a custom RateLimiterErrorHandler bean[2], e.g:

  @Bean
  public RateLimiterErrorHandler rateLimitErrorHandler() {
    return new DefaultRateLimiterErrorHandler() {
        @Override
        public void handleSaveError(String key, Exception e) {
            // custom code
        }

        @Override
        public void handleFetchError(String key, Exception e) {
            // custom code
        }

        @Override
        public void handleError(String msg, Exception e) {
            // custom code
        }
    }
  }

Event Handling

If the application needs to be notified when a rate limit access was exceeded then it can be done by listening to RateLimitExceededEvent event:

    @EventListener
    public void observe(RateLimitExceededEvent event) {
        // custom code
    }

Contributing

Spring Cloud Zuul Rate Limit is released under the non-restrictive Apache 2.0 license, and follows a very standard Github development process, using Github tracker for issues and merging pull requests into master. If you want to contribute even something trivial please do not hesitate, but follow the guidelines below.

Download Details:
Author: marcosbarbero
Source Code: https://github.com/marcosbarbero/spring-cloud-zuul-ratelimit
License: Apache-2.0 License

#spring #spring-boot #java

React Native Dev

1652543820

Background Fetch for React Native Apps

react-native-background-fetch

Background Fetch is a very simple plugin which attempts to awaken an app in the background about every 15 minutes, providing a short period of background running-time. This plugin will execute your provided callbackFn whenever a background-fetch event occurs.

There is no way to increase the rate which a fetch-event occurs and this plugin sets the rate to the most frequent possible — you will never receive an event faster than 15 minutes. The operating-system will automatically throttle the rate the background-fetch events occur based upon usage patterns. Eg: if user hasn't turned on their phone for a long period of time, fetch events will occur less frequently or if an iOS user disables background refresh they may not happen at all.

:new: Background Fetch now provides a scheduleTask method for scheduling arbitrary "one-shot" or periodic tasks.

iOS

There is no way to increase the rate which a fetch-event occurs and this plugin sets the rate to the most frequent possible — you will never receive an event faster than 15 minutes. The operating-system will automatically throttle the rate the background-fetch events occur based upon usage patterns. Eg: if user hasn't turned on their phone for a long period of time, fetch events will occur less frequently.
scheduleTask seems only to fire when the device is plugged into power.
⚠️ When your app is terminated, iOS no longer fires events — There is no such thing as stopOnTerminate: false for iOS.
iOS can take days before Apple's machine-learning algorithm settles in and begins regularly firing events. Do not sit staring at your logs waiting for an event to fire. If your simulated events work, that's all you need to know that everything is correctly configured.
If the user doesn't open your iOS app for long periods of time, iOS will stop firing events.

Android

The Android plugin provides a HeadlessJS implementation allowing you to continue handling events even after app-termination (see @config enableHeadless)

Installing the plugin

⚠️ If you have a previous version of react-native-background-fetch < 2.7.0 installed into react-native >= 0.60, you should first unlink your previous version as react-native link is no longer required.

$ react-native unlink react-native-background-fetch

With `yarn`

$ yarn add react-native-background-fetch

With `npm`

$ npm install --save react-native-background-fetch

Setup Guides

iOS Setup

`react-native >= 0.60`

Auto-linking Setup

Android Setup

`react-native >= 0.60`

Auto-linking Setup

Example

ℹ️ This repo contains its own Example App. See /example

import React from 'react';
import {
  SafeAreaView,
  StyleSheet,
  ScrollView,
  View,
  Text,
  FlatList,
  StatusBar,
} from 'react-native';

import {
  Header,
  Colors
} from 'react-native/Libraries/NewAppScreen';

import BackgroundFetch from "react-native-background-fetch";

class App extends React.Component {
  constructor(props) {
    super(props);
    this.state = {
      events: []
    };
  }

  componentDidMount() {
    // Initialize BackgroundFetch ONLY ONCE when component mounts.
    this.initBackgroundFetch();
  }

  async initBackgroundFetch() {
    // BackgroundFetch event handler.
    const onEvent = async (taskId) => {
      console.log('[BackgroundFetch] task: ', taskId);
      // Do your background work...
      await this.addEvent(taskId);
      // IMPORTANT:  You must signal to the OS that your task is complete.
      BackgroundFetch.finish(taskId);
    }

    // Timeout callback is executed when your Task has exceeded its allowed running-time.
    // You must stop what you're doing immediately BackgroundFetch.finish(taskId)
    const onTimeout = async (taskId) => {
      console.warn('[BackgroundFetch] TIMEOUT task: ', taskId);
      BackgroundFetch.finish(taskId);
    }

    // Initialize BackgroundFetch only once when component mounts.
    let status = await BackgroundFetch.configure({minimumFetchInterval: 15}, onEvent, onTimeout);

    console.log('[BackgroundFetch] configure status: ', status);
  }

  // Add a BackgroundFetch event to <FlatList>
  addEvent(taskId) {
    // Simulate a possibly long-running asynchronous task with a Promise.
    return new Promise((resolve, reject) => {
      this.setState(state => ({
        events: [...state.events, {
          taskId: taskId,
          timestamp: (new Date()).toString()
        }]
      }));
      resolve();
    });
  }

  render() {
    return (
      <>
        <StatusBar barStyle="dark-content" />
        <SafeAreaView>
          <ScrollView
            contentInsetAdjustmentBehavior="automatic"
            style={styles.scrollView}>
            <Header />

            <View style={styles.body}>
              <View style={styles.sectionContainer}>
                <Text style={styles.sectionTitle}>BackgroundFetch Demo</Text>
              </View>
            </View>
          </ScrollView>
          <View style={styles.sectionContainer}>
            <FlatList
              data={this.state.events}
              renderItem={({item}) => (<Text>[{item.taskId}]: {item.timestamp}</Text>)}
              keyExtractor={item => item.timestamp}
            />
          </View>
        </SafeAreaView>
      </>
    );
  }
}

const styles = StyleSheet.create({
  scrollView: {
    backgroundColor: Colors.lighter,
  },
  body: {
    backgroundColor: Colors.white,
  },
  sectionContainer: {
    marginTop: 32,
    paddingHorizontal: 24,
  },
  sectionTitle: {
    fontSize: 24,
    fontWeight: '600',
    color: Colors.black,
  },
  sectionDescription: {
    marginTop: 8,
    fontSize: 18,
    fontWeight: '400',
    color: Colors.dark,
  },
});

export default App;

Executing Custom Tasks

In addition to the default background-fetch task defined by BackgroundFetch.configure, you may also execute your own arbitrary "oneshot" or periodic tasks (iOS requires additional Setup Instructions). However, all events will be fired into the Callback provided to BackgroundFetch#configure:

⚠️ iOS:

scheduleTask on iOS seems only to run when the device is plugged into power.
scheduleTask on iOS are designed for low-priority tasks, such as purging cache files — they tend to be unreliable for mission-critical tasks. scheduleTask will never run as frequently as you want.
The default fetch event is much more reliable and fires far more often.
scheduleTask on iOS stop when the user terminates the app. There is no such thing as stopOnTerminate: false for iOS.

// Step 1:  Configure BackgroundFetch as usual.
let status = await BackgroundFetch.configure({
  minimumFetchInterval: 15
}, async (taskId) => {  // <-- Event callback
  // This is the fetch-event callback.
  console.log("[BackgroundFetch] taskId: ", taskId);

  // Use a switch statement to route task-handling.
  switch (taskId) {
    case 'com.foo.customtask':
      print("Received custom task");
      break;
    default:
      print("Default fetch task");
  }
  // Finish, providing received taskId.
  BackgroundFetch.finish(taskId);
}, async (taskId) => {  // <-- Task timeout callback
  // This task has exceeded its allowed running-time.
  // You must stop what you're doing and immediately .finish(taskId)
  BackgroundFetch.finish(taskId);
});

// Step 2:  Schedule a custom "oneshot" task "com.foo.customtask" to execute 5000ms from now.
BackgroundFetch.scheduleTask({
  taskId: "com.foo.customtask",
  forceAlarmManager: true,
  delay: 5000  // <-- milliseconds
});

API Documentation

Config

Common Options

`@param {Integer} minimumFetchInterval [15]`

The minimum interval in minutes to execute background fetch events. Defaults to 15 minutes. Note: Background-fetch events will never occur at a frequency higher than every 15 minutes. Apple uses a secret algorithm to adjust the frequency of fetch events, presumably based upon usage patterns of the app. Fetch events can occur less often than your configured minimumFetchInterval.

`@param {Integer} delay (milliseconds)`

ℹ️ Valid only for BackgroundFetch.scheduleTask. The minimum number of milliseconds in future that task should execute.

`@param {Boolean} periodic [false]`

ℹ️ Valid only for BackgroundFetch.scheduleTask. Defaults to false. Set true to execute the task repeatedly. When false, the task will execute just once.

Android Options

`@config {Boolean} stopOnTerminate [true]`

Set false to continue background-fetch events after user terminates the app. Default to true.

`@config {Boolean} startOnBoot [false]`

Set true to initiate background-fetch events when the device is rebooted. Defaults to false.

❗ NOTE: startOnBoot requires stopOnTerminate: false.

`@config {Boolean} forceAlarmManager [false]`

By default, the plugin will use Android's JobScheduler when possible. The JobScheduler API prioritizes for battery-life, throttling task-execution based upon device usage and battery level.

Configuring forceAlarmManager: true will bypass JobScheduler to use Android's older AlarmManager API, resulting in more accurate task-execution at the cost of higher battery usage.

let status = await BackgroundFetch.configure({
  minimumFetchInterval: 15,
  forceAlarmManager: true
}, async (taskId) => {  // <-- Event callback
  console.log("[BackgroundFetch] taskId: ", taskId);
  BackgroundFetch.finish(taskId);
}, async (taskId) => {  // <-- Task timeout callback
  // This task has exceeded its allowed running-time.
  // You must stop what you're doing and immediately .finish(taskId)
  BackgroundFetch.finish(taskId);
});
.
.
.
// And with with #scheduleTask
BackgroundFetch.scheduleTask({
  taskId: 'com.foo.customtask',
  delay: 5000,       // milliseconds
  forceAlarmManager: true,
  periodic: false
});

`@config {Boolean} enableHeadless [false]`

Set true to enable React Native's Headless JS mechanism, for handling fetch events after app termination.

📂 index.js (MUST BE IN index.js):

import BackgroundFetch from "react-native-background-fetch";

let MyHeadlessTask = async (event) => {
  // Get task id from event {}:
  let taskId = event.taskId;
  let isTimeout = event.timeout;  // <-- true when your background-time has expired.
  if (isTimeout) {
    // This task has exceeded its allowed running-time.
    // You must stop what you're doing immediately finish(taskId)
    console.log('[BackgroundFetch] Headless TIMEOUT:', taskId);
    BackgroundFetch.finish(taskId);
    return;
  }
  console.log('[BackgroundFetch HeadlessTask] start: ', taskId);

  // Perform an example HTTP request.
  // Important:  await asychronous tasks when using HeadlessJS.
  let response = await fetch('https://reactnative.dev/movies.json');
  let responseJson = await response.json();
  console.log('[BackgroundFetch HeadlessTask] response: ', responseJson);

  // Required:  Signal to native code that your task is complete.
  // If you don't do this, your app could be terminated and/or assigned
  // battery-blame for consuming too much time in background.
  BackgroundFetch.finish(taskId);
}

// Register your BackgroundFetch HeadlessTask
BackgroundFetch.registerHeadlessTask(MyHeadlessTask);

`@config {integer} requiredNetworkType [BackgroundFetch.NETWORK_TYPE_NONE]`

Set basic description of the kind of network your job requires.

If your job doesn't need a network connection, you don't need to use this option as the default value is BackgroundFetch.NETWORK_TYPE_NONE.

NetworkType	Description
`BackgroundFetch.NETWORK_TYPE_NONE`	This job doesn't care about network constraints, either any or none.
`BackgroundFetch.NETWORK_TYPE_ANY`	This job requires network connectivity.
`BackgroundFetch.NETWORK_TYPE_CELLULAR`	This job requires network connectivity that is a cellular network.
`BackgroundFetch.NETWORK_TYPE_UNMETERED`	This job requires network connectivity that is unmetered. Most WiFi networks are unmetered, as in "you can upload as much as you like".
`BackgroundFetch.NETWORK_TYPE_NOT_ROAMING`	This job requires network connectivity that is not roaming (being outside the country of origin)

`@config {Boolean} requiresBatteryNotLow [false]`

Specify that to run this job, the device's battery level must not be low.

This defaults to false. If true, the job will only run when the battery level is not low, which is generally the point where the user is given a "low battery" warning.

`@config {Boolean} requiresStorageNotLow [false]`

Specify that to run this job, the device's available storage must not be low.

This defaults to false. If true, the job will only run when the device is not in a low storage state, which is generally the point where the user is given a "low storage" warning.

`@config {Boolean} requiresCharging [false]`

Specify that to run this job, the device must be charging (or be a non-battery-powered device connected to permanent power, such as Android TV devices). This defaults to false.

`@config {Boolean} requiresDeviceIdle [false]`

When set true, ensure that this job will not run if the device is in active use.

The default state is false: that is, the for the job to be runnable even when someone is interacting with the device.

This state is a loose definition provided by the system. In general, it means that the device is not currently being used interactively, and has not been in use for some time. As such, it is a good time to perform resource heavy jobs. Bear in mind that battery usage will still be attributed to your application, and shown to the user in battery stats.

Methods

Method Name	Arguments	Returns	Notes
`configure`	`{FetchConfig}`, `callbackFn`, `timeoutFn`	`Promise<BackgroundFetchStatus>`	Configures the plugin's `callbackFn` and `timeoutFn`. This callback will fire each time a background-fetch event occurs in addition to events from `#scheduleTask`. The `timeoutFn` will be called when the OS reports your task is nearing the end of its allowed background-time.
`scheduleTask`	`{TaskConfig}`	`Promise<boolean>`	Executes a custom task. The task will be executed in the same `Callback` function provided to `#configure`.
`status`	`callbackFn`	`Promise<BackgroundFetchStatus>`	Your callback will be executed with the current `status (Integer)` `0: Restricted`, `1: Denied`, `2: Available`. These constants are defined as `BackgroundFetch.STATUS_RESTRICTED`, `BackgroundFetch.STATUS_DENIED`, `BackgroundFetch.STATUS_AVAILABLE` (NOTE: Android will always return `STATUS_AVAILABLE`)
`finish`	`String taskId`	`Void`	You MUST call this method in your `callbackFn` provided to `#configure` in order to signal to the OS that your task is complete. iOS provides only 30s of background-time for a fetch-event -- if you exceed this 30s, iOS will kill your app.
`start`	`none`	`Promise<BackgroundFetchStatus>`	Start the background-fetch API. Your `callbackFn` provided to `#configure` will be executed each time a background-fetch event occurs. NOTE the `#configure` method automatically calls `#start`. You do not have to call this method after you `#configure` the plugin
`stop`	`[taskId:String]`	`Promise<boolean>`	Stop the background-fetch API and all `#scheduleTask` from firing events. Your `callbackFn` provided to `#configure` will no longer be executed. If you provide an optional `taskId`, only that `#scheduleTask` will be stopped.

Debugging

iOS

🆕 `BGTaskScheduler` API for iOS 13+

⚠️ At the time of writing, the new task simulator does not yet work in Simulator; Only real devices.
See Apple docs Starting and Terminating Tasks During Development
After running your app in XCode, Click the [||] button to initiate a Breakpoint.
In the console (lldb), paste the following command (Note: use cursor up/down keys to cycle through previously run commands):

e -l objc -- (void)[[BGTaskScheduler sharedScheduler] _simulateLaunchForTaskWithIdentifier:@"com.transistorsoft.fetch"]

Click the [ > ] button to continue. The task will execute and the Callback function provided to BackgroundFetch.configure will receive the event.

Simulating task-timeout events

Only the new BGTaskScheduler api supports simulated task-timeout events. To simulate a task-timeout, your fetchCallback must not call BackgroundFetch.finish(taskId):

let status = await BackgroundFetch.configure({
  minimumFetchInterval: 15
}, async (taskId) => {  // <-- Event callback.
  // This is the task callback.
  console.log("[BackgroundFetch] taskId", taskId);
  //BackgroundFetch.finish(taskId); // <-- Disable .finish(taskId) when simulating an iOS task timeout
}, async (taskId) => {  // <-- Event timeout callback
  // This task has exceeded its allowed running-time.
  // You must stop what you're doing and immediately .finish(taskId)
  print("[BackgroundFetch] TIMEOUT taskId:", taskId);
  BackgroundFetch.finish(taskId);
});

Now simulate an iOS task timeout as follows, in the same manner as simulating an event above:

e -l objc -- (void)[[BGTaskScheduler sharedScheduler] _simulateExpirationForTaskWithIdentifier:@"com.transistorsoft.fetch"]

Old `BackgroundFetch` API

Simulate background fetch events in XCode using Debug->Simulate Background Fetch
iOS can take some hours or even days to start a consistently scheduling background-fetch events since iOS schedules fetch events based upon the user's patterns of activity. If Simulate Background Fetch works, your can be sure that everything is working fine. You just need to wait.

Android

Observe plugin logs in $ adb logcat:

$ adb logcat *:S ReactNative:V ReactNativeJS:V TSBackgroundFetch:V

Simulate a background-fetch event on a device (insert <your.application.id>) (only works for sdk 21+:

$ adb shell cmd jobscheduler run -f <your.application.id> 999

For devices with sdk <21, simulate a "Headless JS" event with (insert <your.application.id>)

$ adb shell am broadcast -a <your.application.id>.event.BACKGROUND_FETCH

Download Details:
Author: transistorsoft
Source Code: https://github.com/transistorsoft/react-native-background-fetch
License: MIT license

#react #reactnative #mobileapp #javascript

Jamison Fisher

1644350700

Datacompy: Pandas and Spark DataFrame Comparison for Humans

DataComPy

DataComPy is a package to compare two Pandas DataFrames. Originally started to be something of a replacement for SAS's PROC COMPARE for Pandas DataFrames with some more functionality than just Pandas.DataFrame.equals(Pandas.DataFrame) (in that it prints out some stats, and lets you tweak how accurate matches have to be). Then extended to carry that functionality over to Spark Dataframes.

Quick Installation

pip install datacompy

Pandas Detail

DataComPy will try to join two dataframes either on a list of join columns, or on indexes. If the two dataframes have duplicates based on join values, the match process sorts by the remaining fields and joins based on that row number.

Column-wise comparisons attempt to match values even when dtypes don't match. So if, for example, you have a column with decimal.Decimal values in one dataframe and an identically-named column with float64 dtype in another, it will tell you that the dtypes are different but will still try to compare the values.

Basic Usage

from io import StringIO
import pandas as pd
import datacompy

data1 = """acct_id,dollar_amt,name,float_fld,date_fld
10000001234,123.45,George Maharis,14530.1555,2017-01-01
10000001235,0.45,Michael Bluth,1,2017-01-01
10000001236,1345,George Bluth,,2017-01-01
10000001237,123456,Bob Loblaw,345.12,2017-01-01
10000001239,1.05,Lucille Bluth,,2017-01-01
"""

data2 = """acct_id,dollar_amt,name,float_fld
10000001234,123.4,George Michael Bluth,14530.155
10000001235,0.45,Michael Bluth,
10000001236,1345,George Bluth,1
10000001237,123456,Robert Loblaw,345.12
10000001238,1.05,Loose Seal Bluth,111
"""

df1 = pd.read_csv(StringIO(data1))
df2 = pd.read_csv(StringIO(data2))

compare = datacompy.Compare(
    df1,
    df2,
    join_columns='acct_id',  #You can also specify a list of columns
    abs_tol=0, #Optional, defaults to 0
    rel_tol=0, #Optional, defaults to 0
    df1_name='Original', #Optional, defaults to 'df1'
    df2_name='New' #Optional, defaults to 'df2'
    )
compare.matches(ignore_extra_columns=False)
# False

# This method prints out a human-readable report summarizing and sampling differences
print(compare.report())

See docs for more detailed usage instructions and an example of the report output.

Things that are happening behind the scenes

You pass in two dataframes (df1, df2) to datacompy.Compare and a column to join on (or list of columns) to join_columns. By default the comparison needs to match values exactly, but you can pass in abs_tol and/or rel_tol to apply absolute and/or relative tolerances for numeric columns.
- You can pass in on_index=True instead of join_columns to join on the index instead.
The class validates that you passed dataframes, that they contain all of the columns in join_columns and have unique column names other than that. The class also lowercases all column names to disambiguate.
On initialization the class validates inputs, and runs the comparison.
Compare.matches() will return True if the dataframes match, False otherwise.
- You can pass in ignore_extra_columns=True to not return False just because there are non-overlapping column names (will still check on overlapping columns)
- NOTE: if you only want to validate whether a dataframe matches exactly or not, you should look at pandas.testing.assert_frame_equal. The main use case for datacompy is when you need to interpret the difference between two dataframes.
Compare also has some shortcuts like
- intersect_rows, df1_unq_rows, df2_unq_rows for getting intersection, just df1 and just df2 records (DataFrames)
- intersect_columns(), df1_unq_columns(), df2_unq_columns() for getting intersection, just df1 and just df2 columns (Sets)
You can turn on logging to see more detailed logs.

Spark Detail

DataComPy's SparkCompare class will join two dataframes either on a list of join columns. It has the capability to map column names that may be different in each dataframe, including in the join columns. You are responsible for creating the dataframes from any source which Spark can handle and specifying a unique join key. If there are duplicates in either dataframe by join key, the match process will remove the duplicates before joining (and tell you how many duplicates were found).

As with the Pandas-based Compare class, comparisons will be attempted even if dtypes don't match. Any schema differences will be reported in the output as well as in any mismatch reports, so that you can assess whether or not a type mismatch is a problem or not.

The main reasons why you would choose to use SparkCompare over Compare are that your data is too large to fit into memory, or you're comparing data that works well in a Spark environment, like partitioned Parquet, CSV, or JSON files, or Cerebro tables.

Performance Implications

Spark scales incredibly well, so you can use SparkCompare to compare billions of rows of data, provided you spin up a big enough cluster. Still, joining billions of rows of data is an inherently large task, so there are a couple of things you may want to take into consideration when getting into the cliched realm of "big data":

SparkCompare will compare all columns in common in the dataframes and report on the rest. If there are columns in the data that you don't care to compare, use a select statement/method on the dataframe(s) to filter those out. Particularly when reading from wide Parquet files, this can make a huge difference when the columns you don't care about don't have to be read into memory and included in the joined dataframe.
For large datasets, adding cache_intermediates=True to the SparkCompare call can help optimize performance by caching certain intermediate dataframes in memory, like the de-duped version of each input dataset, or the joined dataframe. Otherwise, Spark's lazy evaluation will recompute those each time it needs the data in a report or as you access instance attributes. This may be fine for smaller dataframes, but will be costly for larger ones. You do need to ensure that you have enough free cache memory before you do this, so this parameter is set to False by default.

Basic Usage

import datetime
import datacompy
from pyspark.sql import Row

# This example assumes you have a SparkSession named "spark" in your environment, as you
# do when running `pyspark` from the terminal or in a Databricks notebook (Spark v2.0 and higher)

data1 = [
    Row(acct_id=10000001234, dollar_amt=123.45, name='George Maharis', float_fld=14530.1555,
        date_fld=datetime.date(2017, 1, 1)),
    Row(acct_id=10000001235, dollar_amt=0.45, name='Michael Bluth', float_fld=1.0,
        date_fld=datetime.date(2017, 1, 1)),
    Row(acct_id=10000001236, dollar_amt=1345.0, name='George Bluth', float_fld=None,
        date_fld=datetime.date(2017, 1, 1)),
    Row(acct_id=10000001237, dollar_amt=123456.0, name='Bob Loblaw', float_fld=345.12,
        date_fld=datetime.date(2017, 1, 1)),
    Row(acct_id=10000001239, dollar_amt=1.05, name='Lucille Bluth', float_fld=None,
        date_fld=datetime.date(2017, 1, 1))
]

data2 = [
    Row(acct_id=10000001234, dollar_amt=123.4, name='George Michael Bluth', float_fld=14530.155),
    Row(acct_id=10000001235, dollar_amt=0.45, name='Michael Bluth', float_fld=None),
    Row(acct_id=10000001236, dollar_amt=1345.0, name='George Bluth', float_fld=1.0),
    Row(acct_id=10000001237, dollar_amt=123456.0, name='Robert Loblaw', float_fld=345.12),
    Row(acct_id=10000001238, dollar_amt=1.05, name='Loose Seal Bluth', float_fld=111.0)
]

base_df = spark.createDataFrame(data1)
compare_df = spark.createDataFrame(data2)

comparison = datacompy.SparkCompare(spark, base_df, compare_df, join_columns=['acct_id'])

# This prints out a human-readable report summarizing differences
comparison.report()

Using SparkCompare on EMR or standalone Spark

Set proxy variables
Create a virtual environment, if desired (virtualenv venv; source venv/bin/activate)
Pip install datacompy and requirements
Ensure your SPARK_HOME environment variable is set (this is probably /usr/lib/spark but may differ based on your installation)
Augment your PYTHONPATH environment variable with export PYTHONPATH=$SPARK_HOME/python/lib/py4j-0.10.4-src.zip:$SPARK_HOME/python:$PYTHONPATH (note that your version of py4j may differ depending on the version of Spark you're using)

Using SparkCompare on Databricks

Clone this repository locally
Create a datacompy egg by running python setup.py bdist_egg from the repo root directory.
From the Databricks front page, click the "Library" link under the "New" section.
On the New library page:

Change source to "Upload Python Egg or PyPi"
Under "Upload Egg", Library Name should be "datacompy"
Drag the egg file in datacompy/dist/ to the "Drop library egg here to upload" box
Click the "Create Library" button

5. Once the library has been created, from the library page (which you can find in your /Users/{login} workspace), you can choose clusters to attach the library to.

6. import datacompy in a notebook attached to the cluster that the library is attached to and enjoy!

Contributors

We welcome and appreciate your contributions! Before we can accept any contributions, we ask that you please be sure to sign the Contributor License Agreement (CLA).

This project adheres to the Open Source Code of Conduct. By participating, you are expected to honor this code.

Roadmap

Roadmap details can be found here

Download Details:
Author: capitalone
Source Code: https://github.com/capitalone/datacompy
License: Apache-2.0 License

#pandas #python #data-science

Alfie Kemp

1604817780