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gutenberg | Block Editor project for WordPress | Content Management System library

 by   WordPress JavaScript Version: v13.1.0-rc.1 License: Non-SPDX

 by   WordPress JavaScript Version: v13.1.0-rc.1 License: Non-SPDX

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kandi X-RAY | gutenberg Summary

gutenberg is a JavaScript library typically used in Telecommunications, Media, Media, Entertainment, Web Site, Content Management System, Wordpress applications. gutenberg has no bugs, it has no vulnerabilities and it has medium support. However gutenberg has a Non-SPDX License. You can install using 'npm i @wordpress/url' or download it from GitHub, npm.
Welcome to the development hub for the WordPress Gutenberg project!. "Gutenberg" is a codename for a whole new paradigm in WordPress site building and publishing, that aims to revolutionize the entire publishing experience as much as Gutenberg did the printed word. Right now, the project is in the second phase of a four-phase process that will touch every piece of WordPress -- Editing, Customization (which includes Full Site Editing, Block Patterns, Block Directory and Block based themes), Collaboration, and Multilingual -- and is focused on a new editing experience, the block editor. The block editor introduces a modular approach to pages and posts: each piece of content in the editor, from a paragraph to an image gallery to a headline, is its own block. And just like physical blocks, WordPress blocks can be added, arranged, and rearranged, allowing WordPress users to create media-rich pages in a visually intuitive way -- and without work-arounds like shortcodes or custom HTML. The block editor first became available in December 2018, and we're still hard at work refining the experience, creating more and better blocks, and laying the groundwork for the next three phases of work. The Gutenberg plugin gives you the latest version of the block editor so you can join us in testing bleeding-edge features, start playing with blocks, and maybe get inspired to build your own. Check out the Ways to keep up with Gutenberg & Full Site Editing (FSE).
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Support
Quality
Quality
Security
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kandi-support Support

  • gutenberg has a medium active ecosystem.
  • It has 7736 star(s) with 2889 fork(s). There are 337 watchers for this library.
  • There were 10 major release(s) in the last 12 months.
  • There are 4121 open issues and 14862 have been closed. On average issues are closed in 94 days. There are 807 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of gutenberg is v13.1.0-rc.1
gutenberg Support
Best in #Content Management System
Average in #Content Management System
gutenberg Support
Best in #Content Management System
Average in #Content Management System

quality kandi Quality

  • gutenberg has 0 bugs and 0 code smells.
gutenberg Quality
Best in #Content Management System
Average in #Content Management System
gutenberg Quality
Best in #Content Management System
Average in #Content Management System

securitySecurity

  • gutenberg has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • gutenberg code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
gutenberg Security
Best in #Content Management System
Average in #Content Management System
gutenberg Security
Best in #Content Management System
Average in #Content Management System

license License

  • gutenberg has a Non-SPDX License.
  • Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.
gutenberg License
Best in #Content Management System
Average in #Content Management System
gutenberg License
Best in #Content Management System
Average in #Content Management System

buildReuse

  • gutenberg releases are available to install and integrate.
  • Deployable package is available in npm.
  • Installation instructions are available. Examples and code snippets are not available.
  • It has 50410 lines of code, 1302 functions and 5613 files.
  • It has high code complexity. Code complexity directly impacts maintainability of the code.
gutenberg Reuse
Best in #Content Management System
Average in #Content Management System
gutenberg Reuse
Best in #Content Management System
Average in #Content Management System
Top functions reviewed by kandi - BETA

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

  • Initializes navigation .
    • Button Editor Constructor .
      • Instructs a table .
        • Creates a new gallery edit editor .
          • The View wrapping wrapper .
            • Selector for the graph .
              • Edit the cover editor
                • Returns a new registry for the store .
                  • Creates a new Colorette .
                    • Replace input with the editor .

                      Get all kandi verified functions for this library.

                      Get all kandi verified functions for this library.

                      gutenberg Key Features

                      The Block Editor project for WordPress and beyond. Plugin is available from the official repository.

                      How to remove strings that contain at least an uppercase letter in them from an ArrayList<String>?

                      copy iconCopydownload iconDownload
                      for (int i = 0; i < totalListOfWords.size(); i++) {
                          if(containsUpperCaseLetter(totalListOfWords.get(i))){
                              totalListOfWords.remove(i);
                              i--;
                          }
                      }
                      
                      for (Iterator<String> iter = totalListOfWords.iterator(); iter.hasNext();) {
                          if (containsUpperCaseLetter(iter.next())) {
                              iter.remove();
                          }
                      }
                      
                      totalListOfWords.removeIf(word -> containsUpperCaseLetter(word));
                      
                      for (int i = 0; i < totalListOfWords.size(); i++) {
                          if(containsUpperCaseLetter(totalListOfWords.get(i))){
                              totalListOfWords.remove(i);
                              i--;
                          }
                      }
                      
                      for (Iterator<String> iter = totalListOfWords.iterator(); iter.hasNext();) {
                          if (containsUpperCaseLetter(iter.next())) {
                              iter.remove();
                          }
                      }
                      
                      totalListOfWords.removeIf(word -> containsUpperCaseLetter(word));
                      
                      for (int i = 0; i < totalListOfWords.size(); i++) {
                          if(containsUpperCaseLetter(totalListOfWords.get(i))){
                              totalListOfWords.remove(i);
                              i--;
                          }
                      }
                      
                      for (Iterator<String> iter = totalListOfWords.iterator(); iter.hasNext();) {
                          if (containsUpperCaseLetter(iter.next())) {
                              iter.remove();
                          }
                      }
                      
                      totalListOfWords.removeIf(word -> containsUpperCaseLetter(word));
                      

                      Typescript React compiler issue with children props

                      copy iconCopydownload iconDownload
                      const path = require("path");
                      const defaultConfig = require("@wordpress/scripts/config/webpack.config");
                      
                      module.exports = {
                          ...defaultConfig,
                          entry: "./src/editor/index.ts",
                          output: {
                              ...defaultConfig.output,
                              filename: "index.js",
                              path: path.resolve(__dirname, "dist/editor"),
                          },
                      };
                      

                      Expose default gutenberg block styles in WordPress rest API

                      copy iconCopydownload iconDownload
                      div[class*="wp-container-"] .wp-block-button{
                          ...
                      }
                      
                      <!-- wp:buttons {"layout":{"type":"flex","justifyContent":"center"}} -->
                      <div class="wp-block-buttons"><!-- wp:button -->
                      <div class="wp-block-button"><a class="wp-block-button__link">Hello</a></div>
                      <!-- /wp:button --></div>
                      <!-- /wp:buttons -->
                      
                      div[class*="wp-container-"] .wp-block-button{
                          ...
                      }
                      
                      <!-- wp:buttons {"layout":{"type":"flex","justifyContent":"center"}} -->
                      <div class="wp-block-buttons"><!-- wp:button -->
                      <div class="wp-block-button"><a class="wp-block-button__link">Hello</a></div>
                      <!-- /wp:button --></div>
                      <!-- /wp:buttons -->
                      

                      PHP inserting string issue

                      copy iconCopydownload iconDownload
                      $after = preg_replace('/(<div.*?class=".*?(?<=[ "])wp-block-button(?=[ "]))(.*?")/', '$1 is-icon-pdf $2', $before);
                      

                      Pyspark, create RDD with line number and list of words in line

                      copy iconCopydownload iconDownload
                      RDD2=RDD.zipWithIndex().map(lambda x: (x[1], x[0].split()))
                      for element in RDD2.take(2):
                          print(element)
                      
                      from pyspark.sql import functions as sf
                      df = spark.createDataFrame(RDD2, schema="row_num: int, line: string") # convert to DataFrame
                      df2 = df.withColumn("words", sf.split(df.line,"\s+")).drop("line") # split on white spaces and drop the original line
                      df2.show(10)
                      

                      Calculate relative frequency of bigrams in PySpark

                      copy iconCopydownload iconDownload
                      from pyspark.sql import functions as F
                      from pyspark.sql import Window as W
                      
                      data = [(("project", "gutenberg"), 69,),
                              (("gutenberg", "ebook"), 14,),
                              (("ebook", "of"), 5,),
                              (("adventures", "of"), 6,),
                              (("by", "sir"), 12,),
                              (("conan", "doyle"), 1,),
                              (("changing", "all"), 2,),
                              (("all", "over"), 24,), ]
                      
                      df = spark.createDataFrame(data, ("pair", "count", ))
                      
                      ws = W.partitionBy(F.col("pair")._2).rowsBetween(W.unboundedPreceding, W.unboundedFollowing)
                      
                      (df.withColumn("relative_freq", F.col("count") / F.sum("count").over(ws))
                         .orderBy(F.col("count").desc())
                         .limit(3) # change here to select top 1000
                         .orderBy(F.desc(F.col("pair")._2), F.col("relative_freq").desc())
                      ).show()
                      
                      """
                      +--------------------+-----+-------------+
                      |                pair|count|relative_freq|
                      +--------------------+-----+-------------+
                      |         {all, over}|   24|          1.0|
                      |{project, gutenberg}|   69|          1.0|
                      |  {gutenberg, ebook}|   14|          1.0|
                      +--------------------+-----+-------------+
                      """
                      

                      How to get the image links from Gutenberg block gallery and add them as html data attributes to a button in wordpress

                      copy iconCopydownload iconDownload
                      if (has_block("gallery", get_the_content())) 
                      {
                        $post_blocks = parse_blocks(get_the_content());
                        foreach ($post_blocks as $post_block) 
                        {
                          if ("core/gallery" == $post_block["blockName"]) 
                          {
                            $ids = $post_block["attrs"]["ids"];
                          }
                        }
                      }
                      
                      <button class="gallery" 
                      <?php
                      for ($i = 0; $i < count($ids); $i++) {
                        $img_link = wp_get_attachment_image_url($ids[$i], "full");
                        echo "data-img-" . $i . " = " . $img_link . " ";
                      }
                      ?>
                      >
                      Light Box 
                      </button>
                      
                      if (has_block("gallery", get_the_content())) 
                      {
                        $post_blocks = parse_blocks(get_the_content());
                        foreach ($post_blocks as $post_block) 
                        {
                          if ("core/gallery" == $post_block["blockName"]) 
                          {
                            $ids = $post_block["attrs"]["ids"];
                          }
                        }
                      }
                      
                      <button class="gallery" 
                      <?php
                      for ($i = 0; $i < count($ids); $i++) {
                        $img_link = wp_get_attachment_image_url($ids[$i], "full");
                        echo "data-img-" . $i . " = " . $img_link . " ";
                      }
                      ?>
                      >
                      Light Box 
                      </button>
                      

                      Finding a list of words in a corpus using NLTK? Cannot find the frequency of words

                      copy iconCopydownload iconDownload
                      N()[source]
                      Return the total number of sample outcomes that have been recorded by this FreqDist. For the number of unique sample values (or bins) with counts greater than zero, use FreqDist.B().
                      Return type:    int
                      
                      freq(sample)[source]
                      Return the frequency of a given sample. The frequency of a sample is defined as the count of that sample divided by the total number of sample outcomes that have been recorded by this FreqDist. The count of a sample is defined as the number of times that sample outcome was recorded by this FreqDist. Frequencies are always real numbers in the range [0, 1].
                      
                      tabulate(*args, **kwargs)[source]
                      Tabulate the given samples from the frequency distribution (cumulative), displaying the most frequent sample first. If an integer parameter is supplied, stop after this many samples have been plotted.
                      Parameters: samples (list) – The samples to plot (default is all samples)
                      
                      import urllib.request
                      import nltk
                      nltk.download("punkt")
                      
                      target_url0 = 'http://www.gutenberg.org/files/135/135-0.txt'
                      book_raw = urllib.request.urlopen(target_url0).read().decode('utf-8')
                      word_tokens = nltk.word_tokenize(book_raw)
                      
                      character_list = ['Myriel','Bishop','Baptistine','Magloire','Cravatte','Valjean','Gervais','Fantine','Tholomyès','Blachevelle','Dahlia','Fameuil','Favourite','Listolier','Zéphine','Cosette','Thénardier','Éponine','Azelma','Javert','Fauchelevent','Bamatabois','Champmathieu','Brevet','Simplice','Chenildieu','Cochepaille','Innocente','Reverend','Ascension','Crucifixion','Gavroche','Magnon','Gillenormand','Marius','Colonel','Mabeuf','Enjolras','Combeferre','Prouvaire','Feuilly','Courfeyrac','Bahorel','Lesgle','Joly','Grantaire','Patron-Minette','Brujon','Toussaint'] 
                      fdist_mis = nltk.FreqDist(word_tokens)
                      
                      .
                      >>> fdist_mis["Myriel"]
                      28
                      >>> fdist_mis["Bishop"]
                      260
                      
                      N()[source]
                      Return the total number of sample outcomes that have been recorded by this FreqDist. For the number of unique sample values (or bins) with counts greater than zero, use FreqDist.B().
                      Return type:    int
                      
                      freq(sample)[source]
                      Return the frequency of a given sample. The frequency of a sample is defined as the count of that sample divided by the total number of sample outcomes that have been recorded by this FreqDist. The count of a sample is defined as the number of times that sample outcome was recorded by this FreqDist. Frequencies are always real numbers in the range [0, 1].
                      
                      tabulate(*args, **kwargs)[source]
                      Tabulate the given samples from the frequency distribution (cumulative), displaying the most frequent sample first. If an integer parameter is supplied, stop after this many samples have been plotted.
                      Parameters: samples (list) – The samples to plot (default is all samples)
                      
                      import urllib.request
                      import nltk
                      nltk.download("punkt")
                      
                      target_url0 = 'http://www.gutenberg.org/files/135/135-0.txt'
                      book_raw = urllib.request.urlopen(target_url0).read().decode('utf-8')
                      word_tokens = nltk.word_tokenize(book_raw)
                      
                      character_list = ['Myriel','Bishop','Baptistine','Magloire','Cravatte','Valjean','Gervais','Fantine','Tholomyès','Blachevelle','Dahlia','Fameuil','Favourite','Listolier','Zéphine','Cosette','Thénardier','Éponine','Azelma','Javert','Fauchelevent','Bamatabois','Champmathieu','Brevet','Simplice','Chenildieu','Cochepaille','Innocente','Reverend','Ascension','Crucifixion','Gavroche','Magnon','Gillenormand','Marius','Colonel','Mabeuf','Enjolras','Combeferre','Prouvaire','Feuilly','Courfeyrac','Bahorel','Lesgle','Joly','Grantaire','Patron-Minette','Brujon','Toussaint'] 
                      fdist_mis = nltk.FreqDist(word_tokens)
                      
                      .
                      >>> fdist_mis["Myriel"]
                      28
                      >>> fdist_mis["Bishop"]
                      260
                      
                      N()[source]
                      Return the total number of sample outcomes that have been recorded by this FreqDist. For the number of unique sample values (or bins) with counts greater than zero, use FreqDist.B().
                      Return type:    int
                      
                      freq(sample)[source]
                      Return the frequency of a given sample. The frequency of a sample is defined as the count of that sample divided by the total number of sample outcomes that have been recorded by this FreqDist. The count of a sample is defined as the number of times that sample outcome was recorded by this FreqDist. Frequencies are always real numbers in the range [0, 1].
                      
                      tabulate(*args, **kwargs)[source]
                      Tabulate the given samples from the frequency distribution (cumulative), displaying the most frequent sample first. If an integer parameter is supplied, stop after this many samples have been plotted.
                      Parameters: samples (list) – The samples to plot (default is all samples)
                      
                      import urllib.request
                      import nltk
                      nltk.download("punkt")
                      
                      target_url0 = 'http://www.gutenberg.org/files/135/135-0.txt'
                      book_raw = urllib.request.urlopen(target_url0).read().decode('utf-8')
                      word_tokens = nltk.word_tokenize(book_raw)
                      
                      character_list = ['Myriel','Bishop','Baptistine','Magloire','Cravatte','Valjean','Gervais','Fantine','Tholomyès','Blachevelle','Dahlia','Fameuil','Favourite','Listolier','Zéphine','Cosette','Thénardier','Éponine','Azelma','Javert','Fauchelevent','Bamatabois','Champmathieu','Brevet','Simplice','Chenildieu','Cochepaille','Innocente','Reverend','Ascension','Crucifixion','Gavroche','Magnon','Gillenormand','Marius','Colonel','Mabeuf','Enjolras','Combeferre','Prouvaire','Feuilly','Courfeyrac','Bahorel','Lesgle','Joly','Grantaire','Patron-Minette','Brujon','Toussaint'] 
                      fdist_mis = nltk.FreqDist(word_tokens)
                      
                      .
                      >>> fdist_mis["Myriel"]
                      28
                      >>> fdist_mis["Bishop"]
                      260
                      

                      Pyspark operations on text, counting words, unique words, most common words

                      copy iconCopydownload iconDownload
                      from pyspark.sql import SparkSession
                      import pyspark.sql.functions as F
                      
                      spark = SparkSession.builder.getOrCreate()
                      df = spark.read.text("mobydick")
                      df = df.filter(F.col("value") != "")  # Remove empty rows
                      
                      word_counts = (
                          df.withColumn("word", F.explode(F.split(F.col("value"), "\s+")))
                          .withColumn("word", F.regexp_replace("word", "[^\w]", ""))
                          .groupBy("word")
                          .count()
                          .sort("count", ascending=False)
                      )
                      
                      # Top 10
                      word_counts.show(10)
                      
                      # All words count
                      word_counts.agg(F.sum("count").alias("count_all_words")).show()
                      
                      # Whale count
                      word_counts.filter(F.col("word").rlike("(?i)whale")).agg(
                          F.sum("count").alias("whale_count")
                      ).show()
                      
                      # Unique count
                      print("Unique words: ", word_counts.count())
                      
                      +----+-----+                                                                    
                      |word|count|
                      +----+-----+
                      |the |13701|
                      |of  |6551 |
                      |and |5992 |
                      |to  |4513 |
                      |a   |4491 |
                      |in  |3905 |
                      |that|2865 |
                      |his |2462 |
                      |it  |2089 |
                      |I   |1942 |
                      +----+-----+
                      
                      +---------------+
                      |count_all_words|
                      +---------------+
                      |212469         |
                      +---------------+
                      
                      +-----------+
                      |whale_count|
                      +-----------+
                      |1687       |
                      +-----------+
                      
                      Unique words:  21837
                      
                      from pyspark.sql import SparkSession
                      import pyspark.sql.functions as F
                      
                      spark = SparkSession.builder.getOrCreate()
                      df = spark.read.text("mobydick")
                      df = df.filter(F.col("value") != "")  # Remove empty rows
                      
                      word_counts = (
                          df.withColumn("word", F.explode(F.split(F.col("value"), "\s+")))
                          .withColumn("word", F.regexp_replace("word", "[^\w]", ""))
                          .groupBy("word")
                          .count()
                          .sort("count", ascending=False)
                      )
                      
                      # Top 10
                      word_counts.show(10)
                      
                      # All words count
                      word_counts.agg(F.sum("count").alias("count_all_words")).show()
                      
                      # Whale count
                      word_counts.filter(F.col("word").rlike("(?i)whale")).agg(
                          F.sum("count").alias("whale_count")
                      ).show()
                      
                      # Unique count
                      print("Unique words: ", word_counts.count())
                      
                      +----+-----+                                                                    
                      |word|count|
                      +----+-----+
                      |the |13701|
                      |of  |6551 |
                      |and |5992 |
                      |to  |4513 |
                      |a   |4491 |
                      |in  |3905 |
                      |that|2865 |
                      |his |2462 |
                      |it  |2089 |
                      |I   |1942 |
                      +----+-----+
                      
                      +---------------+
                      |count_all_words|
                      +---------------+
                      |212469         |
                      +---------------+
                      
                      +-----------+
                      |whale_count|
                      +-----------+
                      |1687       |
                      +-----------+
                      
                      Unique words:  21837
                      

                      I'm new to JavaFX, trying to use buttons to run a text analyzer

                      copy iconCopydownload iconDownload
                      Caused by: java.lang.NullPointerException: Children: child node is null: parent = HBox@4f9175a0
                        . . .
                        at Text_Processor.<init>(Text_Processor.java:24)
                      
                      Button button, button2, button3;
                      HBox hbox = new HBox(button, button2, button3);
                      
                      HBox hbox = new HBox();
                      
                      hbox.getChildren().addAll(button, button2, button3);
                      
                      Button fetchButton = new Button("Click First to Fetch The Raven Text"); 
                      fetchButton.setOnAction(e -> fetch());
                      
                      . . .
                      
                      private void fetch() {
                          // perform the fetch task.
                      }
                      
                      Caused by: java.lang.NullPointerException: Children: child node is null: parent = HBox@4f9175a0
                        . . .
                        at Text_Processor.<init>(Text_Processor.java:24)
                      
                      Button button, button2, button3;
                      HBox hbox = new HBox(button, button2, button3);
                      
                      HBox hbox = new HBox();
                      
                      hbox.getChildren().addAll(button, button2, button3);
                      
                      Button fetchButton = new Button("Click First to Fetch The Raven Text"); 
                      fetchButton.setOnAction(e -> fetch());
                      
                      . . .
                      
                      private void fetch() {
                          // perform the fetch task.
                      }
                      
                      Caused by: java.lang.NullPointerException: Children: child node is null: parent = HBox@4f9175a0
                        . . .
                        at Text_Processor.<init>(Text_Processor.java:24)
                      
                      Button button, button2, button3;
                      HBox hbox = new HBox(button, button2, button3);
                      
                      HBox hbox = new HBox();
                      
                      hbox.getChildren().addAll(button, button2, button3);
                      
                      Button fetchButton = new Button("Click First to Fetch The Raven Text"); 
                      fetchButton.setOnAction(e -> fetch());
                      
                      . . .
                      
                      private void fetch() {
                          // perform the fetch task.
                      }
                      
                      Caused by: java.lang.NullPointerException: Children: child node is null: parent = HBox@4f9175a0
                        . . .
                        at Text_Processor.<init>(Text_Processor.java:24)
                      
                      Button button, button2, button3;
                      HBox hbox = new HBox(button, button2, button3);
                      
                      HBox hbox = new HBox();
                      
                      hbox.getChildren().addAll(button, button2, button3);
                      
                      Button fetchButton = new Button("Click First to Fetch The Raven Text"); 
                      fetchButton.setOnAction(e -> fetch());
                      
                      . . .
                      
                      private void fetch() {
                          // perform the fetch task.
                      }
                      
                      Caused by: java.lang.NullPointerException: Children: child node is null: parent = HBox@4f9175a0
                        . . .
                        at Text_Processor.<init>(Text_Processor.java:24)
                      
                      Button button, button2, button3;
                      HBox hbox = new HBox(button, button2, button3);
                      
                      HBox hbox = new HBox();
                      
                      hbox.getChildren().addAll(button, button2, button3);
                      
                      Button fetchButton = new Button("Click First to Fetch The Raven Text"); 
                      fetchButton.setOnAction(e -> fetch());
                      
                      . . .
                      
                      private void fetch() {
                          // perform the fetch task.
                      }
                      

                      Community Discussions

                      Trending Discussions on gutenberg
                      • How to remove strings that contain at least an uppercase letter in them from an ArrayList&lt;String&gt;?
                      • Typescript React compiler issue with children props
                      • Gutenberg NPM doesn't do any changes
                      • Expose default gutenberg block styles in WordPress rest API
                      • PHP inserting string issue
                      • Pyspark, create RDD with line number and list of words in line
                      • Calculate relative frequency of bigrams in PySpark
                      • How to get the image links from Gutenberg block gallery and add them as html data attributes to a button in wordpress
                      • problem with extension intercepting downloads
                      • Finding a list of words in a corpus using NLTK? Cannot find the frequency of words
                      Trending Discussions on gutenberg

                      QUESTION

                      How to remove strings that contain at least an uppercase letter in them from an ArrayList&lt;String&gt;?

                      Asked 2022-Mar-23 at 07:26

                      So, I have an ArrayList called totalListOfWords. It contains a mixed of words from which has both lower and upper case letters in it. I want to remove all the words that contain upper case letter in them. Below is what I have.

                      I have a helper method called containsUpperCaseLetter. It basically checks whether a string contain an upper case letter in it.

                      Then I loop through my totalListOfWords using for loop and check each word in the list whether it contains an upper case letter. If so, I try to remove it. But it only remove some words. May be I am choosing the wrong type? Help please.

                      public class TextProcessor() {
                         ArrayList<String> totalListOfWords = new ArrayList<String>();
                         
                         totalListOfWords.add("The");
                         totalListOfWords.add("Project");
                         totalListOfWords.add("Gutenberg");
                         totalListOfWords.add("eBook");
                         totalListOfWords.add("of");
                         totalListOfWords.add("Pride");
                         totalListOfWords.add("and");
                         totalListOfWords.add("Prejudice");
                         totalListOfWords.add("by");
                         totalListOfWords.add("Jane");
                         totalListOfWords.add("Austen");
                      
                         public void processText() {
                            for (int i = 0; i < totalListOfWords.size(); i++) {
                               if(containsUpperCaseLetter(totalListOfWords.get(i))){
                                  totalListOfWords.remove(i);
                               }
                            }
                            System.out.println(totalListOfWords);  
                         }   
                      
                         public boolean containsUpperCaseLetter(String s){
                            for(int i = 0; i < s.length(); i++){
                                if(Character.isUpperCase(s.charAt(i))){
                                    return true;
                                }
                            }
                            return false;
                         }
                      
                         public static void main(String[] args) {
                            TextProcessor t1 = new TextProcessor();
                            t1.processTextAtURL(url1);
                         }
                      }
                      

                      ANSWER

                      Answered 2022-Mar-23 at 04:33

                      When you remove the element at index i, the next element is now at i instead of i+1. You would have to decrement i so it checks the same index again:

                      for (int i = 0; i < totalListOfWords.size(); i++) {
                          if(containsUpperCaseLetter(totalListOfWords.get(i))){
                              totalListOfWords.remove(i);
                              i--;
                          }
                      }
                      

                      Or you can use an iterator instead:

                      for (Iterator<String> iter = totalListOfWords.iterator(); iter.hasNext();) {
                          if (containsUpperCaseLetter(iter.next())) {
                              iter.remove();
                          }
                      }
                      

                      Or you can skip the whole loop altogether:

                      totalListOfWords.removeIf(word -> containsUpperCaseLetter(word));
                      

                      Source https://stackoverflow.com/questions/71581852

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