Flutter array data deduplication ultimate solution

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foreword

Handling deduplication of data is a common task in Flutter application development. This article will introduce various data deduplication methods in Flutter in detail, including different techniques such as using Set, fold method, where method, custom functions, and using third-party libraries. Each method will provide sample code and explanations to help you understand and apply the methods to meet different needs.

1. What is data deduplication?

Array deduplication refers to removing repeated elements from an array containing repeated elements to obtain a new array containing only unique elements. In the deduplicated array, each element is unique and there will be no duplication.

Usually, array deduplication is to simplify data, reduce repeated information or improve the efficiency of data processing. The deduplicated array can better meet the needs of data analysis, calculation, display, etc., and avoid unnecessary impact of repeated data on the results.

Array deduplication is very common in actual development, especially when processing data collections, statistical data, or data filtering. Deduplication can be applied to different types of data, including numbers, strings, objects, etc.

For example, suppose there is an integer array [1, 2, 2, 3, 4, 4, 5], after the deduplication operation on the array, the new array obtained is [1, 2, 3, 4, 5], where Duplicate elements 2 and 4 are removed, leaving only the unique value of each element.

All in all, array deduplication is to get a new array without duplicate elements by eliminating duplicate elements, so as to better process and utilize data.

2. Application Scenarios of Data Deduplication

Data deduplication plays an important role in many application scenarios. The following are some common data deduplication application scenarios:

1. Data cleaning and preprocessing: In data analysis and machine learning tasks, raw data may contain a large amount of duplicate data. When performing data cleaning and preprocessing, deduplication can reduce noise and double counting, and ensure data accuracy and consistency.
2. Database operation: In the process of database management and query, it is often necessary to perform deduplication operations on data. Deduplication can eliminate duplicate data records, improve database query efficiency and storage space utilization.
3. Data presentation and visualization: In data visualization and report generation, repeated data may lead to duplication of information and distortion of charts. Deduplication can ensure the accuracy and clarity of data presentation, making the final results more reliable and easy to understand.
4. Data statistics and analysis: Duplicate data can introduce bias and errors when statistics and analysis of data sets. Deduplication ensures data uniqueness to accurately calculate metrics, identify patterns, and make correct decisions.
5. Data exchange and integration: Deduplication is a critical step in data integration and data exchange. By removing duplicate data, data redundancy and repeated import can be avoided, and the efficiency of data integration and sharing can be improved.
6. Unique identifiers and indexes: When building unique identifiers or indexes, you need to ensure the uniqueness of the identifiers or indexes. Deduplication can help identify duplicate identifiers or indexes, avoiding conflicts and confusion.
7. User management and identification: In a user management system, it is crucial to ensure the uniqueness of each user. Deduplication can prevent repeated creation of user accounts and identify duplicate user information.

All in all, data deduplication is an essential step in various data processing and application scenarios. It can improve data accuracy, reduce data redundancy, improve data processing efficiency, and ensure the quality and reliability of final results.

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1. Use Set to deduplicate data

Set is an unordered, non-repeating collection. Data deduplication can be easily realized by using the characteristics of Set.

Sample code:

List<int> list = [1, 2, 2, 3, 4, 4, 5];
Set<int> uniqueSet = list.toSet();
List<int> uniqueList = uniqueSet.toList();
print(uniqueList); // [1, 2, 3, 4, 5]

2. Use the fold method to deduplicate data

The old method can perform cumulative calculations on the elements in the list, combined with the contains method to achieve data deduplication.

Sample code:

List<int> list = [1, 2, 2, 3, 4, 4, 5];
List<int> uniqueList = list.fold([], (List<int> acc, int curr) {
    
    
  if (!acc.contains(curr)) {
    
    
    acc.add(curr);
  }
  return acc;
});
print(uniqueList); // [1, 2, 3, 4, 5]

3. Use the where method to deduplicate data

The where method can filter the elements in the list according to the conditions, combined with the indexOf method to achieve data deduplication.

Sample code:

List<int> list = [1, 2, 2, 3, 4, 4, 5];
List<int> uniqueList = list.where((element) => list.indexOf(element) == list.lastIndexOf(element)).toList();
print(uniqueList); // [1, 3, 5]

4. Custom function for data deduplication

Custom functions can traverse data and remove duplicate elements according to specific needs.

Sample code:

List<int> list = [1, 2, 2, 3, 4, 4, 5];
List<int> uniqueList = removeDuplicates(list);
print(uniqueList); // [1, 2, 3, 4, 5]

List<int> removeDuplicates(List<int> list) {
    
    
  List<int> uniqueList = [];
  for (int i = 0; i < list.length; i++) {
    
    
    if (!uniqueList.contains(list[i])) {
    
    
      uniqueList.add(list[i]);
    }
  }
  return uniqueList;
}

5. Use a third-party library for data deduplication

In Flutter, there are many third-party libraries to choose from, such as collection, quiver, equitable, etc. These libraries provide more advanced data deduplication functions.

Sample code (using collection library):

import 'package:collection/collection.dart';

List<int> list = [1, 2, 2, 3, 4, 4, 5];
List<int> uniqueList = list.toSet().toList();
print(uniqueList); // [1, 2, 3, 4, 5]

6. Deduplication of complex data

Complex data deduplication, as shown in the following example, the list array contains a model type of data, this kind of data deduplication, due to the inconsistency of the type, the data cannot be deduplicated.
The solution is as follows:

  removal(List<RelevanceStoreDataList> list) {
    
    
    final uniqueList = list.map((e) => e.code).toSet();
    list.retainWhere((element) => uniqueList.remove(element.code));
    return list;
  }

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Summarize

The above methods provide multiple ways to implement data deduplication, and you can choose the method that suits you according to your actual needs. Each method has its advantages and disadvantages, and the choice is based on data volume and performance requirements. At the same time, you are also encouraged to write custom data deduplication functions according to actual needs to meet specific business logic.