jackson-datatypes-collections | Jackson project that contains various collection | JSON Processing library

by FasterXML Java Version: 2.14.1 License: Apache-2.0

kandi X-RAY | jackson-datatypes-collections Summary

jackson-datatypes-collections is a Java library typically used in Utilities, JSON Processing, JPA applications. jackson-datatypes-collections has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub, Maven.

This is a multi-module umbrella project for various Jackson Datatype modules to support 3rd party Collection libraries.

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kandi-support Support

jackson-datatypes-collections has a low active ecosystem.
It has 65 star(s) with 46 fork(s). There are 11 watchers for this library.
There were 6 major release(s) in the last 6 months.
There are 14 open issues and 46 have been closed. On average issues are closed in 208 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of jackson-datatypes-collections is 2.14.1

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quality kandi Quality

jackson-datatypes-collections has 0 bugs and 0 code smells.

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security Security

jackson-datatypes-collections has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
jackson-datatypes-collections code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.

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license License

jackson-datatypes-collections is licensed under the Apache-2.0 License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.

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build Reuse

jackson-datatypes-collections releases are not available. You will need to build from source code and install.
Deployable package is available in Maven.
Build file is available. You can build the component from source.
Installation instructions, examples and code snippets are available.
jackson-datatypes-collections saves you 875126 person hours of effort in developing the same functionality from scratch.
It has 528262 lines of code, 1109 functions and 2614 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.

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Top functions reviewed by kandi - BETA

kandi has reviewed jackson-datatypes-collections and discovered the below as its top functions. This is intended to give you an instant insight into jackson-datatypes-collections implemented functionality, and help decide if they suit your requirements.

Find the appropriate ValueInstantiator for the given bean type

Creates an instance of the primitive type factory
Create a ValueInstantiator for the given type using the given factory

Serializes the CharIterable with the given type

Writes the contents of the CharIterable as an array

Serializes the map iterable with the type suffix

Serialize the fields

Starts the maven wrapper

Downloads a file from an URL

Deserialize a JSON value

Add the context

Finds the serializer for the given type

Serialize the value

Returns the actual serializer for this bean

Overrides default implementation

Creates a pure primitive instance factory for the given pair class

Serializes the CharIterable

Serialize the contents of the wrapped object

Gets the contextual value

Serialize the given ByteIterable with the type suffix

Serialize the array with the given type suffix

Returns the contextual serializer for the bean

Creates the contextual value handler

Get all kandi verified functions for this library.

jackson-datatypes-collections Key Features

Eclipse Collections datatype (for Eclipse Collections): jackson-datatype-eclipse-collections (since 2.10)

Guava datatype (for Guava library): jackson-datatype-guava

HPPC datatype (for High-Performance Primitive Collections): jackson-datatype-hppc

PCollections datatype (for Persistent Java Collections): jackson-datatype-pcollections

jackson-datatypes-collections Examples and Code Snippets

See all related Code Snippets

Community Discussions

Trending Discussions on JSON Processing

st_read path for shinyapp in R
How to write jsonb inside WHERE without JSON Processing Functions
Renumerating indexed JSON
How to get values from array of JSON in C#
SSIS Script Task Fails with NewtonSoft.Json
Is there an automated way to split a JSON(B) column into multiple columns in PostgreSQL?
Register Java Class in Flink Cluster
A simple way to parse XML with repeated element using Jackson
Shiny.io cannot deploy the application
How to deploy shiny app to shinyapps.io from drake plan

Trending Discussions on JSON Processing

QUESTION

st_read path for shinyapp in R

Asked 2021-Oct-03 at 00:33

Usually when st_read is used you put path in dsn, but in case of shiny if you put a full path inside dsn it will give an error as that file path does not exist on the server. So, now I put the shapefile in the www folder, but I don't know what path to put in dsn so that the app picks up the shapefile.

How can I fix this?

Current function code in the app:

rocks_utm_sf = st_read(dsn = "D:/Sedimentary_Data_Analysis/www",layer = "Sed_UTM")

Below error in the log breaks the app

    021-10-02T19:05:08.733697+00:00 shinyapps[4783188]: Server version: 1.8.6.1
2021-10-02T19:05:08.733707+00:00 shinyapps[4783188]: R version: 4.0.2
2021-10-02T19:05:08.733705+00:00 shinyapps[4783188]: LANG: en_US.UTF-8
2021-10-02T19:05:08.725767+00:00 shinyapps[4783188]: Running on host: 52b53ce9aed0
2021-10-02T19:05:08.733716+00:00 shinyapps[4783188]: shiny version: 1.6.0
2021-10-02T19:05:08.733732+00:00 shinyapps[4783188]: httpuv version: 1.6.1
2021-10-02T19:05:08.931183+00:00 shinyapps[4783188]: Using jsonlite for JSON processing
2021-10-02T19:05:08.934357+00:00 shinyapps[4783188]: 
2021-10-02T19:05:08.733977+00:00 shinyapps[4783188]: Using pandoc: /opt/connect/ext/pandoc/2.11
2021-10-02T19:05:08.733739+00:00 shinyapps[4783188]: rmarkdown version: 2.9
2021-10-02T19:05:08.733790+00:00 shinyapps[4783188]: jsonlite version: 1.7.2
2021-10-02T19:05:08.934357+00:00 shinyapps[4783188]: Starting R with process ID: '26'
2021-10-02T19:05:08.733779+00:00 shinyapps[4783188]: knitr version: 1.33
2021-10-02T19:05:08.963216+00:00 shinyapps[4783188]: 
2021-10-02T19:05:08.733791+00:00 shinyapps[4783188]: RJSONIO version: (none)
2021-10-02T19:05:08.733797+00:00 shinyapps[4783188]: htmltools version: 0.5.1.1
2021-10-02T19:05:08.963841+00:00 shinyapps[4783188]:     box
2021-10-02T19:05:08.963217+00:00 shinyapps[4783188]: 
2021-10-02T19:05:08.963840+00:00 shinyapps[4783188]: The following object is masked from ‘package:graphics’:
2021-10-02T19:05:08.963840+00:00 shinyapps[4783188]: 
2021-10-02T19:05:08.963217+00:00 shinyapps[4783188]: Attaching package: ‘shinydashboard’
2021-10-02T19:05:08.963841+00:00 shinyapps[4783188]: 
2021-10-02T19:05:10.008023+00:00 shinyapps[4783188]: ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
2021-10-02T19:05:10.013142+00:00 shinyapps[4783188]: ✔ ggplot2 3.3.5     ✔ purrr   0.3.4
2021-10-02T19:05:10.013143+00:00 shinyapps[4783188]: ✔ tibble  3.1.3     ✔ dplyr   1.0.7
2021-10-02T19:05:10.013144+00:00 shinyapps[4783188]: ✔ tidyr   1.1.3     ✔ stringr 1.4.0
2021-10-02T19:05:10.194146+00:00 shinyapps[4783188]: ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
2021-10-02T19:05:10.194148+00:00 shinyapps[4783188]: ✖ dplyr::lag()    masks stats::lag()
2021-10-02T19:05:10.013144+00:00 shinyapps[4783188]: ✔ readr   2.0.0     ✔ forcats 0.5.1
2021-10-02T19:05:10.194148+00:00 shinyapps[4783188]: ✖ dplyr::filter() masks stats::filter()
2021-10-02T19:05:10.415161+00:00 shinyapps[4783188]: Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1
2021-10-02T19:05:10.464817+00:00 shinyapps[4783188]: Listening on http://127.0.0.1:44842
2021-10-02T19:05:10.464815+00:00 shinyapps[4783188]: 
2021-10-02T19:05:16.625537+00:00 shinyapps[4783188]: Warning: Error in : Cannot open "D:/Sedimentary_Data_Analysis/www"; The file doesn't seem to exist.
2021-10-02T19:05:16.630916+00:00 shinyapps[4783188]:   113: <Anonymous>

ANSWER

Answered 2021-Oct-03 at 00:33

Thanks to Guillaumme for his comment, so I was able to fix the problem by first moving the shiny app to a R project. Then in the app code write st_read as follows, and the app is able to pick up the shapefile when its published on shinyapps.io.

 sf_object = st_read(dsn = "www", layer = "Name")

Source https://stackoverflow.com/questions/69415642

QUESTION

How to get values from array of JSON in C#

Asked 2021-Jun-23 at 20:23

I am new to JSON processing by NewtonSoft on C#. I have the following JSON and trying to get all orderIds and orderNumbers. I tried the following code. But in both cases, I am getting can't access child items error. I also tried using JObject.Parse(json) and tried to get the two values, but got similar errors.

{
  "orders": [{
      "orderId": 123,
      "orderNumber": "234",
      "billTo": {
        "name": "John1 Doe1",
        "Street": "1 one way"
      },
      "items": [{
        "orderItemId": 46429,
        "lineItemKey": "110",
        "sku": "Hammer",
        "name": "Small Hammer"
      }]
    },
    {
      "orderId": 567,
      "orderNumber": "789",
      "billTo": {
        "name": "John2 Doe2",
        "Street": "2 second way"
      },
      "items": [{
        "orderItemId": 76567,
        "lineItemKey": "213",
        "sku": "Tape",
        "name": "Electric Tape"
      }]
    },
    {
      "orderId": 223,
      "orderNumber": "334",
      "billTo": {
        "name": "John3 Doe4",
        "Street": "3 third way"
      },
      "items": [{
        "orderItemId": 87890,
        "lineItemKey": "890",
        "sku": "Box",
        "name": "Wooden box"
      }]
    }
  ]
}

  dynamic dynJson = JsonConvert.DeserializeObject(json);
foreach (var item in dynJson)
{
    //Console.WriteLine("{0} {1} \n", item["orders"].orderId, 
                        item["orders"].orderNumber);
    Console.WriteLine("{0} {1} \n", item["orders"]["orderId"], item["orders"] 
                       ["orderNumber"]);
}

ANSWER

Answered 2021-Jun-23 at 19:49

The for loop statement seems to be wrong since dynJson is an object and not an array. You need to loop through the dynJson.orders, like below.

dynamic dynJson = JsonConvert.DeserializeObject(data);
    foreach (var item in dynJson.orders)
    {
        //Console.WriteLine("{0} {1} \n", item["orders"].orderId, 
                            //item["orders"].orderNumber);
        Console.WriteLine("{0} {1} \n", item.orderId,
                           item.orderNumber);
    }
}

Above code will print out

123 234 
567 789 
223 334

Source https://stackoverflow.com/questions/68106071

QUESTION

Is there an automated way to split a JSON(B) column into multiple columns in PostgreSQL?

Asked 2020-Sep-07 at 16:54

So I have a PostgreSQL (TimescaleDB) table that looks like this:

╔════════════════════════════╦═══════╦═══════╗
║            tags            ║ time  ║ value ║
╠════════════════════════════╬═══════╬═══════╣
║ {"a": "test", "c": "test"} ║ 10:24 ║   123 ║
║ {"b": "test", "c": "test"} ║ 10:25 ║   110 ║
║ {"b": "test"}              ║ 10:26 ║   130 ║
╚════════════════════════════╩═══════╩═══════╝

And I would like to split the JSON(B) column into multiple columns like this:

╔════════╦════════╦════════╦═══════╦═══════╗
║   a    ║   b    ║   c    ║ time  ║ value ║
╠════════╬════════╬════════╬═══════╬═══════╣
║ "test" ║        ║ "test" ║ 10:24 ║   123 ║
║        ║ "test" ║ "test" ║ 10:25 ║   110 ║
║        ║ "test" ║        ║ 10:26 ║   130 ║
╚════════╩════════╩════════╩═══════╩═══════╝

I looked into the JSON Processing Functions and it seems that those require finding all the JSON(B) attributes and types. Is there a way to do this automatically?

ANSWER

Answered 2020-Sep-07 at 16:54

There is no way to make this dynamic. The number (and types) of all columns of a query must be known to the database when parsing the statement, long before it's actually executed.

If you always have the same structure you can create a type:

create type tag_type as (a text, b text, c text);

and then use jsonb_populate_record()

select (jsonb_populate_record(null::tag_type, tags)).*, time, value
from the_table;

Source https://stackoverflow.com/questions/63779087

QUESTION

Asked 2020-Aug-23 at 22:02

I am running my Fat Jar in Flink Cluster which reads Kafka and saves in Cassandra, the code is,

        final Properties prop = getProperties();
        final FlinkKafkaConsumer<String> flinkConsumer = new FlinkKafkaConsumer<>
                                             (kafkaTopicName, new SimpleStringSchema(), prop);
        flinkConsumer.setStartFromEarliest();

        final DataStream<String> stream = env.addSource(flinkConsumer);
        DataStream<Person> sensorStreaming = stream.flatMap(new FlatMapFunction<String, Person>() {
            @Override
            public void flatMap(String value, Collector<Person> out) throws Exception {
                try {
                    out.collect(objectMapper.readValue(value, Person.class));
                } catch (JsonProcessingException e) {
                    logger.error("Json Processing Exception", e);
                }
            }
        });
        savePersonDetails(sensorStreaming);
        env.execute();

and The Person POJO contains,

    @Column(name = "event_time")
    private Instant eventTime;

There is codec required to store Instant as below for Cassandra side,

final Cluster cluster = ClusterManager.getCluster(cassandraIpAddress);
cluster.getConfiguration().getCodecRegistry().register(InstantCodec.instance);

When i run standalone works fine, but when i run local cluster throws me an error as below,

Caused by: com.datastax.driver.core.exceptions.CodecNotFoundException: Codec not found for requested operation: [timestamp <-> java.time.Instant]
    at com.datastax.driver.core.CodecRegistry.notFound(CodecRegistry.java:679)
    at com.datastax.driver.core.CodecRegistry.createCodec(CodecRegistry.java:526)
    at com.datastax.driver.core.CodecRegistry.findCodec(CodecRegistry.java:506)
    at com.datastax.driver.core.CodecRegistry.access$200(CodecRegistry.java:140)
    at com.datastax.driver.core.CodecRegistry$TypeCodecCacheLoader.load(CodecRegistry.java:211)
    at com.datastax.driver.core.CodecRegistry$TypeCodecCacheLoader.load(CodecRegistry.java:208)

I read the below document for registering,

https://ci.apache.org/projects/flink/flink-docs-release-1.11/dev/custom_serializers.html

but InstantCodec is 3rd party one. How can i register it?

ANSWER

Answered 2020-Aug-23 at 22:02

I solved the problem, there was LocalDateTime which was emitting from and when i was converting with same type, there was above error. I changed the type into java.util Date type then it worked.

Source https://stackoverflow.com/questions/63494496

QUESTION

Shiny.io cannot deploy the application

Asked 2020-Jul-28 at 21:34

I was trying to create an interactive map with the Shiny web application, however, after I published it to my shiny.io account, clicking the URL will only yield: shiny.io application page

An error has occurred!

An error has occurred. Check your logs or contact the app author for clarification.

Can you help me with it? Thanks!

Here are the logs of the application:

2020-07-28T20:32:42.887039+00:00 shinyapps[2621249]: jsonlite version: 1.6.1
2020-07-28T20:32:42.887039+00:00 shinyapps[2621249]: RJSONIO version: (none)
2020-07-28T20:32:42.887050+00:00 shinyapps[2621249]: htmltools version: 0.5.0
2020-07-28T20:32:42.887235+00:00 shinyapps[2621249]: Using pandoc: /opt/connect/ext/pandoc2
2020-07-28T20:32:43.039412+00:00 shinyapps[2621249]: 
2020-07-28T20:32:43.039413+00:00 shinyapps[2621249]: Starting R with process ID: '58'
2020-07-28T20:32:43.106062+00:00 shinyapps[2621249]: Listening on http://127.0.0.1:36754
2020-07-28T20:32:43.106061+00:00 shinyapps[2621249]: 
2020-07-28T20:32:43.035592+00:00 shinyapps[2621249]: Using jsonlite for JSON processing
2020-07-28T20:32:43.299242+00:00 shinyapps[2621249]: Warning: Error in plotlyOutput: could not find function "plotlyOutput"
2020-07-28T20:32:43.304719+00:00 shinyapps[2621249]:    99: div
2020-07-28T20:32:43.304717+00:00 shinyapps[2621249]:   100: dots_list
2020-07-28T20:32:43.304719+00:00 shinyapps[2621249]:    98: tabPanel
2020-07-28T20:53:57.079846+00:00 shinyapps[2621249]: Running on host: 220810008dc5
2020-07-28T20:53:57.085768+00:00 shinyapps[2621249]: Server version: 1.8.4-11
2020-07-28T20:53:57.085785+00:00 shinyapps[2621249]: LANG: en_US.UTF-8
2020-07-28T20:53:57.085827+00:00 shinyapps[2621249]: R version: 4.0.0
2020-07-28T20:53:57.085867+00:00 shinyapps[2621249]: shiny version: 1.5.0
2020-07-28T20:53:57.085869+00:00 shinyapps[2621249]: httpuv version: 1.5.4
2020-07-28T20:53:57.085881+00:00 shinyapps[2621249]: rmarkdown version: (none)
2020-07-28T20:53:57.085882+00:00 shinyapps[2621249]: knitr version: (none)
2020-07-28T20:53:57.085895+00:00 shinyapps[2621249]: jsonlite version: 1.6.1
2020-07-28T20:53:57.085909+00:00 shinyapps[2621249]: RJSONIO version: (none)
2020-07-28T20:53:57.085959+00:00 shinyapps[2621249]: htmltools version: 0.5.0
2020-07-28T20:53:57.086171+00:00 shinyapps[2621249]: Using pandoc: /opt/connect/ext/pandoc2
2020-07-28T20:53:57.244930+00:00 shinyapps[2621249]: Using jsonlite for JSON processing
2020-07-28T20:53:57.248899+00:00 shinyapps[2621249]: 
2020-07-28T20:53:57.248900+00:00 shinyapps[2621249]: Starting R with process ID: '24'
2020-07-28T20:53:57.319981+00:00 shinyapps[2621249]: 
2020-07-28T20:53:57.319982+00:00 shinyapps[2621249]: Listening on http://127.0.0.1:44567
2020-07-28T20:56:14.943220+00:00 shinyapps[2621249]: Running on host: 220810008dc5
2020-07-28T20:56:14.950036+00:00 shinyapps[2621249]: Server version: 1.8.4-11
2020-07-28T20:56:14.950099+00:00 shinyapps[2621249]: httpuv version: 1.5.4
2020-07-28T20:56:14.950046+00:00 shinyapps[2621249]: LANG: en_US.UTF-8
2020-07-28T20:56:14.950063+00:00 shinyapps[2621249]: R version: 4.0.0
2020-07-28T20:56:14.950165+00:00 shinyapps[2621249]: knitr version: (none)
2020-07-28T20:56:14.950089+00:00 shinyapps[2621249]: shiny version: 1.5.0
2020-07-28T20:56:14.950105+00:00 shinyapps[2621249]: rmarkdown version: (none)
2020-07-28T20:56:14.950182+00:00 shinyapps[2621249]: jsonlite version: 1.6.1
2020-07-28T20:56:14.950410+00:00 shinyapps[2621249]: Using pandoc: /opt/connect/ext/pandoc2
2020-07-28T20:56:15.113622+00:00 shinyapps[2621249]: Using jsonlite for JSON processing
2020-07-28T20:56:14.950182+00:00 shinyapps[2621249]: RJSONIO version: (none)
2020-07-28T20:56:14.950183+00:00 shinyapps[2621249]: htmltools version: 0.5.0
2020-07-28T20:56:15.118668+00:00 shinyapps[2621249]: Starting R with process ID: '73'
2020-07-28T20:56:15.118666+00:00 shinyapps[2621249]: 
2020-07-28T20:56:15.192554+00:00 shinyapps[2621249]: 
2020-07-28T20:56:15.192556+00:00 shinyapps[2621249]: Listening on http://127.0.0.1:37222
2020-07-28T20:56:15.320813+00:00 shinyapps[2621249]: Warning: Error in plotlyOutput: could not find function "plotlyOutput"
2020-07-28T20:56:15.326689+00:00 shinyapps[2621249]:   100: dots_list
2020-07-28T20:56:15.326691+00:00 shinyapps[2621249]:    99: div
2020-07-28T20:56:15.326692+00:00 shinyapps[2621249]:    98: tabPanel

It worked perfectly in RStudio with the following ui.R and Server.R:

library(shiny)
library(leaflet)

shinyUI(fluidPage(
    
    titlePanel("JHU COVID-19 Modeling Visualization Map"),
    
    sidebarLayout(
        sidebarPanel(
            checkboxGroupInput("statesInput", "Choose the State(s)", 
                               c("AL", "MO", "AK", "MT", "AZ", "NE", 
                                 "AR", "NV", "CA", "NH", "CO", "NJ", 
                                 "CT", "NM", "DE", "NY", "DC", "NC", 
                                 "FL", "ND", "GA", "OH", "HI", "OK", 
                                 "ID", "OR", "IL", "PA", "IN", "RI", 
                                 "IA", "SC", "KS", "SD", "KY", "TN", 
                                 "LA", "TX", "ME", "UT", "MD", "VT", 
                                 "MA", "VA", "MI", "WA", "MN", "WV", 
                                 "MS", "WI", "WY"),
                               inline = TRUE),
                                                                       
            submitButton("Submit"),
                ), 

        mainPanel(
            tabsetPanel(type = "tabs", 
                        tabPanel("County Level", plotlyOutput("countyPolygonMap")), 
                        tabPanel("State Level", leafletOutput("statePolygonMap"))
            )
        )
)))

library(shiny)
library(leaflet)
library(magrittr)
library(rgdal)

shinyServer(function(input, output) {
    library(rjson)
    library(plotly)
    library(dplyr)
    
    statepolygonZip <- download.file("https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip", 
                                     destfile = "cb_2018_us_state_500k.zip");
    unzip("cb_2018_us_state_500k.zip");
    statePolygonData <- readOGR("cb_2018_us_state_500k.shp", layer = "cb_2018_us_state_500k", 
                                GDAL1_integer64_policy = TRUE);
    ## obtaning the state shape file data provided by cencus.gov 
    ## for more categories of region shape file: 
    ## https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html
    
    
    output$countyPolygonMap <- renderPlotly({
        url <- 'https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json'
        countyGeo <- rjson::fromJSON(file=url)
        ## Obtaining the geographical file for all U.S. counties
        url2<- "https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv"
        df <- read.csv(url2, colClasses=c(fips="character"))
        names(df)[2] = "unemployment"
        ## obtaining the unemployment rate data 
        url3 <- "https://storage.googleapis.com/kagglesdsdata/datasets%2F579969%2F1374720%2Fus_county.csv?GoogleAccessId=gcp-kaggle-com@kaggle-161607.iam.gserviceaccount.com&Expires=1596139521&Signature=easqHBFZ757D%2F7LVyDM%2BF%2FIMU6l2OEY6giqVvIC0l0tSSe%2Fohq6NC%2FLFKbsIV6FdFALmPUqG9vATbg0cuRVVwGQMsoUOjlW%2BZLhTVluxbYh1dDE1MTFzWRpzlSH18ejIwqa61F0ARJ%2Bpq6ryIfJuE7wQQ1rOCEpaVB9m%2FP7QaZm2gBJeHYLXJXcvO8w1p0sEnqRsGAesg2Fgj%2Bv8unPGNtDJekEWuNbl1K9k7CAaZWjG2QQ94LB9tAPvfKqykDWDD7w6yN3YFkcfu7kUmjs0CybnMD6IP%2FM5hvJXuUTIie0MOMTWt5bIua4qcTHxIxR5l918y1H17JA2HHrnKLVY%2BA%3D%3D"
        county <- read.csv(url3)
        county$nfips <- sprintf("%05d",county$fips)

        countyPolygonMap <- plot_ly() %>% add_trace(
            type="choroplethmapbox",
            geojson=countyGeo,
            locations=county$nfips,
            z=~county$population,
            colorscale="Viridis",
            zmin=200,
            zmax=1100000,
            marker=list(line=list(width=0),opacity=0.5)
        ) %>% layout(
            mapbox=list(
                style="carto-positron",
                zoom =2,
                center=list(lon= -95.71, lat=37.09))
        );
        countyPolygonMap;
        ## generating the interactive plotly map
    })
    
    output$statePolygonMap <-renderLeaflet ({
        statesAbbr <- subset(statePolygonData, input$statesInput %in% statePolygonData$STUSPS);
        ## subsetting the shape file with the selected states
        
        leaflet(statesAbbr) %>%
            addPolygons(color = "#444444", weight = 1, smoothFactor = 0.5,
                        opacity = 1.0, fillOpacity = 0.5,
                        fillColor = ~colorQuantile("YlOrRd", ALAND)(ALAND),
                        highlightOptions = highlightOptions
                        (color = "white", weight = 2,bringToFront = TRUE))
    })
    ## producing the map with polygon boundary on the state level
})

ANSWER

Answered 2020-Jul-28 at 21:15

I am thinking you mean shinyapps.io. To get to the logs:

Click on the dashboard view (the left-side panel).
Click on the name of your app (a hyperlink)
Click on the logs button at the top of the screen

Source https://stackoverflow.com/questions/63142711

QUESTION

How to deploy shiny app to shinyapps.io from drake plan

Asked 2020-Jul-16 at 18:20

This is a follow-on question from closing the loop on passing the app and data to a Shiny deployment function:

How to use shiny app as a target in drake

I would like to deploy a Shiny app directly from a drake plan as below.

library(drake)
library(shiny)

plan <- drake_plan(
  cars_data = mtcars,
  deployment = custom_deployment_function(file_in("app.R"), cars_data)
)

custom_shiny_deployment <- function(file, data_input) {

    rsconnect::deployApp(
    appFiles = file,
    appName = "cars",
    forceUpdate = TRUE
  )
}

Saved as "app.R" in project working directory (the app works outside of drake if data_input <- mtcars) :

shinyApp(
  ui = fluidPage(
    selectInput("variable", "Variable:",
                c("Cylinders" = "cyl",
                  "Transmission" = "am")),
    tableOutput("data")
  ),
  server = function(input, output) {
    output$data <- renderTable({
      data_input[, c("mpg", input$variable), drop = FALSE]
    }, rownames = TRUE)
  }
)

Logs from shinyapps.io shows "cars_data" from drake is not being passed to the Shiny server "data_input" in the custom_deployment_function environment:

2020-07-14T20:12:57.418989+00:00 shinyapps[2569696]: htmltools version: 0.5.0
2020-07-14T20:12:57.419186+00:00 shinyapps[2569696]: Using pandoc: /opt/connect/ext/pandoc2
2020-07-14T20:12:57.589960+00:00 shinyapps[2569696]: Using jsonlite for JSON processing
2020-07-14T20:12:57.593223+00:00 shinyapps[2569696]: 
2020-07-14T20:12:57.593224+00:00 shinyapps[2569696]: Starting R with process ID: '25'
2020-07-14T20:12:57.628389+00:00 shinyapps[2569696]: 
2020-07-14T20:12:57.628390+00:00 shinyapps[2569696]: Listening on http://127.0.0.1:38608
2020-07-14T20:13:14.686424+00:00 shinyapps[2569696]: Running on host: e89f96d02b6e
2020-07-14T20:13:14.691423+00:00 shinyapps[2569696]: Server version: 1.8.4-11
2020-07-14T20:13:14.691436+00:00 shinyapps[2569696]: LANG: en_US.UTF-8
2020-07-14T20:13:14.691436+00:00 shinyapps[2569696]: R version: 4.0.0
2020-07-14T20:13:14.691437+00:00 shinyapps[2569696]: shiny version: 1.5.0
2020-07-14T20:13:14.691467+00:00 shinyapps[2569696]: rmarkdown version: (none)
2020-07-14T20:13:14.691648+00:00 shinyapps[2569696]: Using pandoc: /opt/connect/ext/pandoc2
2020-07-14T20:13:14.691475+00:00 shinyapps[2569696]: knitr version: (none)
2020-07-14T20:13:14.857243+00:00 shinyapps[2569696]: Using jsonlite for JSON processing
2020-07-14T20:13:14.691443+00:00 shinyapps[2569696]: httpuv version: 1.5.4
2020-07-14T20:13:14.895595+00:00 shinyapps[2569696]: 
2020-07-14T20:13:14.691480+00:00 shinyapps[2569696]: jsonlite version: 1.7.0
2020-07-14T20:13:14.860404+00:00 shinyapps[2569696]: 
2020-07-14T20:13:14.860404+00:00 shinyapps[2569696]: Starting R with process ID: '41'
2020-07-14T20:13:14.895596+00:00 shinyapps[2569696]: Listening on http://127.0.0.1:42022
2020-07-14T20:13:14.691496+00:00 shinyapps[2569696]: RJSONIO version: (none)
2020-07-14T20:13:14.691506+00:00 shinyapps[2569696]: htmltools version: 0.5.0
2020-07-14T20:15:57.441648+00:00 shinyapps[2569696]: Running on host: a2e664ad9837
2020-07-14T20:15:57.447236+00:00 shinyapps[2569696]: Server version: 1.8.4-11
2020-07-14T20:15:57.447326+00:00 shinyapps[2569696]: R version: 4.0.0
2020-07-14T20:15:57.447337+00:00 shinyapps[2569696]: knitr version: (none)
2020-07-14T20:15:57.447337+00:00 shinyapps[2569696]: rmarkdown version: (none)
2020-07-14T20:15:57.447327+00:00 shinyapps[2569696]: shiny version: 1.5.0
2020-07-14T20:15:57.447260+00:00 shinyapps[2569696]: LANG: en_US.UTF-8
2020-07-14T20:15:57.447337+00:00 shinyapps[2569696]: httpuv version: 1.5.4
2020-07-14T20:15:57.447338+00:00 shinyapps[2569696]: jsonlite version: 1.7.0
2020-07-14T20:15:57.447338+00:00 shinyapps[2569696]: RJSONIO version: (none)
2020-07-14T20:15:57.667089+00:00 shinyapps[2569696]: 
2020-07-14T20:15:57.447494+00:00 shinyapps[2569696]: Using pandoc: /opt/connect/ext/pandoc2
2020-07-14T20:15:57.630039+00:00 shinyapps[2569696]: Starting R with process ID: '24'
2020-07-14T20:15:57.626886+00:00 shinyapps[2569696]: Using jsonlite for JSON processing
2020-07-14T20:15:57.447347+00:00 shinyapps[2569696]: htmltools version: 0.5.0
2020-07-14T20:15:57.630037+00:00 shinyapps[2569696]: 
2020-07-14T20:15:57.667090+00:00 shinyapps[2569696]: Listening on http://127.0.0.1:40107
2020-07-14T20:16:14.758082+00:00 shinyapps[2569696]: Warning: Error in renderTable: object 'data_input' not found
2020-07-14T20:16:14.772348+00:00 shinyapps[2569696]:   108: renderTable [/srv/connect/apps/cars/app.R#13]
2020-07-14T20:16:14.772349+00:00 shinyapps[2569696]:   107: func
2020-07-14T20:16:14.772350+00:00 shinyapps[2569696]:    94: origRenderFunc
2020-07-14T20:16:14.772350+00:00 shinyapps[2569696]:    93: output$data
2020-07-14T20:16:14.772350+00:00 shinyapps[2569696]:    13: runApp
2020-07-14T20:16:14.772351+00:00 shinyapps[2569696]:    12: fn
2020-07-14T20:16:14.772351+00:00 shinyapps[2569696]:     7: connect$retry
2020-07-14T20:16:14.772352+00:00 shinyapps[2569696]:     6: eval
2020-07-14T20:16:14.772352+00:00 shinyapps[2569696]:     5: eval

Apologies if this is trivial, but between drake and shiny, it is escaping me.

ANSWER

Answered 2020-Jul-16 at 18:20

Now that I see how you are deploying the app, I can say that this is expected behavior. Yes, your custom_shiny_deployment() has access to the data, but the deployed app does not because rsconnect::deployApp() does not ship objects from the calling environment. If you want the data to be available to the app, I recommend saving it (and tracking it with file_in() and file_out()) then passing it to the appFiles argument of deployApp() via custom_shiny_deployment().

EDIT

Your app.R can stay like it is.

app.R is the same as what you wrote.

library(shiny)

cars_data <- readRDS("cars_data.RDS")

shinyApp(
  ui = fluidPage(
    selectInput("variable", "Variable:",
                c("Cylinders" = "cyl",
                  "Transmission" = "am")),
    tableOutput("data")
  ),
  server = function(input, output) {
    output$data <- renderTable({
      cars_data[, c("mpg", input$variable), drop = FALSE]
    }, rownames = TRUE)
  } 
)

But from drake's side, you need something like file_in() and file_out() to ensure the correct targets run in the correct order and in response to changes to cars_data.RDS and app.R.

library(drake)

plan <- drake_plan(
  cars_data = mtcars,
  save_cars = saveRDS(cars_data, file_out("cars_data.RDS")),
  deployment = rsconnect::deployApp(
    appFiles = file_in("app.R", "cars_data.RDS"),
    appName = "cars",
    forceUpdate = TRUE
  )
)

make(plan)

If you really want appFiles to be NULL, drake still needs file_in() so it knows to depend on physical files.

plan <- drake_plan(
  cars_data = mtcars,
  save_cars = saveRDS(cars_data, file_out("cars_data.RDS")),
  deployment = deploy_app(file_in("cars_data.RDS", "app.R"))
)

deploy_app <- function(...) {
  rsconnect::deployApp(
    appFiles = NULL,
    appName = "cars",
    forceUpdate = TRUE
  )
}

Either way, I recommend checking the plan with plot() or vis_drake_graph() before you run it with make(). Both plans above show deployment downstream of the data file (with incoming arrows) which is exactly what we want.

plot(plan)

Without these file markers, there is a chance that drake will deploy the app before the data is ready to go.

disconnected_plan <- drake_plan(
  cars_data = mtcars,
  saveRDS(cars_data, "cars_data.RDS"),
  deployment =  rsconnect::deployApp(
    appFiles = NULL,
    appName = "cars",
    forceUpdate = TRUE
  )
)

plot(disconnected_plan)

Source https://stackoverflow.com/questions/62903543

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