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混浊又暗下来 2025-02-20 21:11:33
public int Name{
   get; set;
}

这可以删除整个私有属性规范,并让您更快地创建属性。

值是语言关键字,您可以使用它来调节当您从属性返回该值时是否更改了值。

我建议您阅读有关物业如何工作的更多信息。

public int Name{
   get; set;
}

This removes the whole private property specification and lets you create properties faster.

Value is a language keyword, you can use it to condition whether the value is changed when you return it from the property.

I advice you to read more about how properties work.

用字符串使用什么而不是值?

混浊又暗下来 2025-02-20 07:03:20

使用更新

df.update(df.loc[df['b']== 3,['a']].replace(2,1))
df
Out[354]: 
     a  b
0  1.0  1
1  2.0  1
2  1.0  3
3  1.0  3
4  1.0  1

Do with update

df.update(df.loc[df['b']== 3,['a']].replace(2,1))
df
Out[354]: 
     a  b
0  1.0  1
1  2.0  1
2  1.0  3
3  1.0  3
4  1.0  1

过滤,更换和重新置于熊猫中的df柱

混浊又暗下来 2025-02-20 02:00:53

您可以使用 netadaddr :: mac 来自CPAN到分析的模块到分析和格式Mac地址方法:

#!/usr/bin/env perl
use warnings;
use strict;
use feature qw/say/;
use NetAddr::MAC;

my $macaddr = '4cf5.5b8b.f860';
my $mac = NetAddr::MAC->new($macaddr);
say $mac->as_ieee; # 4c:f5:5b:8b:f8:60

You can use the NetAddr::MAC module from CPAN to parse and format MAC addresses in many different ways:

#!/usr/bin/env perl
use warnings;
use strict;
use feature qw/say/;
use NetAddr::MAC;

my $macaddr = '4cf5.5b8b.f860';
my $mac = NetAddr::MAC->new($macaddr);
say $mac->as_ieee; # 4c:f5:5b:8b:f8:60

如何在Perl中转换MAC地址格式?

混浊又暗下来 2025-02-19 22:38:01

这些听起来像服务器配置,而不是NUXT本身。

例如,我在 ssr:false target:static in nuxt.config.js 中,我正在使用 ssr:false IIS 10

在应用程序的根文件夹中,我有一个 web.config 用于使用的 iis 的文件,其中包含一些标头,例如:

<?xml version="1.0" encoding="UTF-8"?>
<configuration>
    <system.webServer>
        <security>
          <requestFiltering removeServerHeader="true">
          </requestFiltering>
        </security>
        <httpProtocol>
            <customHeaders>
                <remove name="X-Powered-By" />
                <add name="X-Frame-Options" value="DENY" />
                <add name="Strict-Transport-Security" value="max-age=31536000" />
                <add name="Content-Security-Policy" value="default-src 'self'; script-src 'self'; style-src 'self' 'unsafe-inline';" />
            </customHeaders>
        </httpProtocol>
    </system.webServer>
</configuration>

side注意:我在使用 content-security-policy 时,该应用程序最终删除了该行; web.config 具有更多的配置

these sound like a server config rather than nuxt itself.

for example I had a nuxt built website with ssr: false and target: static in nuxt.config.js and I was deploying the site using IIS 10.

in the root folder of the app I had a web.config file for the IIS to use and it contained some of the headers like:

<?xml version="1.0" encoding="UTF-8"?>
<configuration>
    <system.webServer>
        <security>
          <requestFiltering removeServerHeader="true">
          </requestFiltering>
        </security>
        <httpProtocol>
            <customHeaders>
                <remove name="X-Powered-By" />
                <add name="X-Frame-Options" value="DENY" />
                <add name="Strict-Transport-Security" value="max-age=31536000" />
                <add name="Content-Security-Policy" value="default-src 'self'; script-src 'self'; style-src 'self' 'unsafe-inline';" />
            </customHeaders>
        </httpProtocol>
    </system.webServer>
</configuration>

side note: I had some issues in the app when using Content-Security-Policy so I ended up removing that line; and web.config had more configurations but shortened it here for readability

NUXT安全性:修复缺失的标题

混浊又暗下来 2025-02-19 19:44:20

您可以使用静态方法:

const chart = Chart.getChart(canvasId);
const data = chart.data.datasets[0].data;

You can use the static Chart.getChart method:

const chart = Chart.getChart(canvasId);
const data = chart.data.datasets[0].data;

在图表上测试自动化。JS和Angular 14

混浊又暗下来 2025-02-18 04:08:27

在您尝试时,引用变量将外壳视为单个值。当您需要时未能引用是一个常见的初学者错误,但是当您想要时引用在shell上拆分whitespace上的值(并在结果中扩展通配符)也是错误的。也许还请参见

只要您的项目只是令牌,就可以将它们保存在字符串中。

output='a.txt b.txt c.txt d.txt'
for item in $output; do
   echo "$item"  # remember quotes here
done

不过,该变量不会给您任何东西。

for item in a.txt b.txt c.txt d.txt
do
    ...

或者,如果您想要的只是一一打印令牌,那么

printf '%s\n' a.txt b.txt c.txt d.txt

sh 中唯一的数据类型就是字符串。没有简单安全的方法来存储一系列需要在变量中引用的项目。 (如果您可以完全控制输入并知道您在做什么,请尝试 eval ;但是通常,这些条件中的一个或两个是不正确的。)

如上所述,如果您可以避免保存保存变量中的值,您可以使用您喜欢的任何引用!

for item in "an item" another \
    'yet one more (with "nested quotes" even, see?)'
do
    echo "$item"  # now the quotes are important!
done

bash和ksh等有数组,因此您可以做类似的事情

items=("an item" another 'yet one more (with "nested quotes" even, see?)')
printf '%s\n' "${items[@]}"

,但这在普通 sh 中不可用。

(对于它的价值,您也无法嵌套以尝试的方式引用。

input='['a.txt', '

创建一个由(引用) [>(未引用的) a.txt a.txt 的字符串与(引用)逗号和空间相邻。

In your attempt, quoting the variable forced the shell to regard it as a single value. Failing to quote when you need to is a common beginner error, but quoting when you want the shell to split a value on whitespace (and expand wildcards in the result) is also wrong. Perhaps see also When to wrap quotes around a shell variable?

As long as your items are just tokens, you can save them in a string.

output='a.txt b.txt c.txt d.txt'
for item in $output; do
   echo "$item"  # remember quotes here
done

In isolation, the variable doesn't buy you anything, though.

for item in a.txt b.txt c.txt d.txt
do
    ...

or, if all you want is to print the tokens one by one, simply

printf '%s\n' a.txt b.txt c.txt d.txt

The only data type in sh is a string. There is no simple and safe way to store a sequence of items which require quoting in a variable. (If you can completely control the input, and know what you are doing, try eval; but often, one or both of these conditions are not true.)

As suggested above, if you can avoid saving the values in a variable, you can use any quoting you like!

for item in "an item" another \
    'yet one more (with "nested quotes" even, see?)'
do
    echo "$item"  # now the quotes are important!
done

Bash and Ksh etc have arrays, so you can do things like

items=("an item" another 'yet one more (with "nested quotes" even, see?)')
printf '%s\n' "${items[@]}"

but this is not available in plain sh.

(For what it's worth, you also cannot nest quotes the way you tried to.

input='['a.txt', '

creates a string consisting of (quoted) [ immediately adjacent to (unquoted) a.txt imrediately adjacent to (quoted) comma and space. The shell will simply join together the adjacent strings into a single string after quote removal.)

外壳脚本以循环在字符串列表上

混浊又暗下来 2025-02-18 02:06:02

您可以尝试一下: -

import findspark
findspark.init()
import pyspark.sql.functions as F
from pyspark.sql import SparkSession
from itertools import combinations
import datetime

spark = SparkSession.builder.appName("Practice").master("local[*]").config("spark.executor.memory", "70g").config("spark.driver.memory", "50g").config("spark.memory.offHeap.enabled",True).config("spark.memory.offHeap.size","16g").getOrCreate()

df = spark.read.parquet('spark-big-data\parquet_small_example.parquet')
df = df.withColumn('fs_origin',df.request.Segments.getItem(0)['Origin'])
df = df.withColumn('fs_destination',df.request.Segments.getItem(0)['Destination'])
df = df.withColumn('fs_date',df.request.Segments.getItem(0)['FlightTime'])
df = df.withColumn('ss_origin',df.request.Segments.getItem(1)['Origin'])
df = df.withColumn('ss_destination',df.request.Segments.getItem(1)['Destination'])
df = df.withColumn('ss_date',df.request.Segments.getItem(1)['FlightTime'])
df = df.withColumn('full_date',F.concat_ws('-', df.year,df.month,df.day))
df = df.filter((df["fs_origin"] == 'TLV') & (df["fs_destination"] == 'NYC') & (df["ss_origin"] == 'NYC') & (df['ss_destination']=='TLV')).persist()

df.count()

res =[]

for date in range(10):
    df_date = df.filter((df['fs_date']=='2021-02-'+str(date)+'T00:00:00') & (df['ss_date']=='2021-02-16'+'T00:00:00'))

    if df_date.count()==0:
        res.append(0)
        
    else:
        df_date = df_date.sort(F.unix_timestamp("full_date", "yyyy-M-d").desc())
        latest_day = df_date.collect()[0]['full_date']

        df_date = df_date.filter(df_date['full_date']==latest_day)
        df_date = df_date.withColumn("exploded_data", F.explode("response.results"))
        df_date = df_date.withColumn(
                    "price",
                    F.col("exploded_data").getItem('PriceInfo').getItem('Price') # either get by name or by index e.g. getItem(0) etc
                )

        res.append(df_date.sort(df_date.price.asc()).collect()[0]['price'])
    
df.unpersist()
spark.catalog.clearCache()

Can you try this:-

import findspark
findspark.init()
import pyspark.sql.functions as F
from pyspark.sql import SparkSession
from itertools import combinations
import datetime

spark = SparkSession.builder.appName("Practice").master("local[*]").config("spark.executor.memory", "70g").config("spark.driver.memory", "50g").config("spark.memory.offHeap.enabled",True).config("spark.memory.offHeap.size","16g").getOrCreate()

df = spark.read.parquet('spark-big-data\parquet_small_example.parquet')
df = df.withColumn('fs_origin',df.request.Segments.getItem(0)['Origin'])
df = df.withColumn('fs_destination',df.request.Segments.getItem(0)['Destination'])
df = df.withColumn('fs_date',df.request.Segments.getItem(0)['FlightTime'])
df = df.withColumn('ss_origin',df.request.Segments.getItem(1)['Origin'])
df = df.withColumn('ss_destination',df.request.Segments.getItem(1)['Destination'])
df = df.withColumn('ss_date',df.request.Segments.getItem(1)['FlightTime'])
df = df.withColumn('full_date',F.concat_ws('-', df.year,df.month,df.day))
df = df.filter((df["fs_origin"] == 'TLV') & (df["fs_destination"] == 'NYC') & (df["ss_origin"] == 'NYC') & (df['ss_destination']=='TLV')).persist()

df.count()

res =[]

for date in range(10):
    df_date = df.filter((df['fs_date']=='2021-02-'+str(date)+'T00:00:00') & (df['ss_date']=='2021-02-16'+'T00:00:00'))

    if df_date.count()==0:
        res.append(0)
        
    else:
        df_date = df_date.sort(F.unix_timestamp("full_date", "yyyy-M-d").desc())
        latest_day = df_date.collect()[0]['full_date']

        df_date = df_date.filter(df_date['full_date']==latest_day)
        df_date = df_date.withColumn("exploded_data", F.explode("response.results"))
        df_date = df_date.withColumn(
                    "price",
                    F.col("exploded_data").getItem('PriceInfo').getItem('Price') # either get by name or by index e.g. getItem(0) etc
                )

        res.append(df_date.sort(df_date.price.asc()).collect()[0]['price'])
    
df.unpersist()
spark.catalog.clearCache()

火花数据帧内部循环每次都速度较慢

混浊又暗下来 2025-02-17 20:06:27

我设法通过删除和重新创建静态文件来解决它

I managed to solve it by deleting and recreating the static files

错误渲染页面:错误:无法加载脚本:/_next/static/chunks/pages/_error-2280fa386d040b66.js

混浊又暗下来 2025-02-17 08:20:59

第一个选项是创建类似类的全局变量:

// 'a' can also be placed here :)
class MyPage extends StatefulWidget {
  const MyPage({Key? key}) : super(key: key);

  @override
  State<MyPage> createState() => _MyPageState();
}

// this is a global variable. It has no colors. (see image)
double a = 20.0;
/*
  now, wherever you import the file containing the class 'MyPage',
  you can use this variable!
 */

class _MyPageState extends State<MyPage> {
  
  // this is a local variable. It has a purple color. (see image)
  double b = 10.0;
  
  @override
  Widget build(BuildContext context) {
    return Container();
  }
}

​然后,在此文件中定义您的变量, double A = 10.0; ,然后在其他飞镖文件中您可以像以前一样导入并使用变量:您可以使用此信息:在其他文件中使用:导入:'globals.dart'作为Globals; ,然后在您的文件中您可以使用: globals.a = 20.0; setState(()= &gt; {}); 。不要忘记上面的 setstate :)

First option is to create a global variable inside the class like this:

// 'a' can also be placed here :)
class MyPage extends StatefulWidget {
  const MyPage({Key? key}) : super(key: key);

  @override
  State<MyPage> createState() => _MyPageState();
}

// this is a global variable. It has no colors. (see image)
double a = 20.0;
/*
  now, wherever you import the file containing the class 'MyPage',
  you can use this variable!
 */

class _MyPageState extends State<MyPage> {
  
  // this is a local variable. It has a purple color. (see image)
  double b = 10.0;
  
  @override
  Widget build(BuildContext context) {
    return Container();
  }
}

picture showing the colors

Second option is to create a dart file, let's call it globals.dart. Then, in this file define your variables, double a = 10.0; And then in your other dart files you can either import it as before and use the variables or you can use this: in your other files use: import: 'globals.dart' as globals; and then in your file you can use: globals.a = 20.0; inside a setState(()=>{});. Don't forget to setState above as well :)

如何从函数内部更新变量?

混浊又暗下来 2025-02-16 23:10:19

数据实际上是每行词典列表。您可以从每一行构建一个数据框。然后将名称包含在列中,该列可以转换为列表,爆炸,然后在此操作 value_counts

df = pd.DataFrame({'col1': [ [{'name': 'John'}, {'name': 'Mark'}, {'name': 'Susan'}, {'name': 'Mr.Bean'}, {'name': 'The Smiths'}], \
[{'name': 'Mark'}, {'name': 'Barbara'}, {'name': 'Poly'}, {'name': 'John'}, {'name': 'Nick'}] ] })

print(df)

output:

                                                col1
0  [{'name': 'John'}, {'name': 'Mark'}, {'name': ...
1  [{'name': 'Mark'}, {'name': 'Barbara'}, {'name...

value_count:

df.apply(lambda x: pd.DataFrame(x['col1']).squeeze().to_list(), axis=1).explode().value_counts()

output:oumptice:output:output:

John          2
Mark          2
Susan         1
Mr.Bean       1
The Smiths    1
Barbara       1
Poly          1
Nick          1

The data is actually a list of dictionaries on each line. You can build a dataframe from each row. Then the names are contained in a column which can be converted to a list, exploded and then perform a value_counts on that:

df = pd.DataFrame({'col1': [ [{'name': 'John'}, {'name': 'Mark'}, {'name': 'Susan'}, {'name': 'Mr.Bean'}, {'name': 'The Smiths'}], \
[{'name': 'Mark'}, {'name': 'Barbara'}, {'name': 'Poly'}, {'name': 'John'}, {'name': 'Nick'}] ] })

print(df)

Output:

                                                col1
0  [{'name': 'John'}, {'name': 'Mark'}, {'name': ...
1  [{'name': 'Mark'}, {'name': 'Barbara'}, {'name...

value_count :

df.apply(lambda x: pd.DataFrame(x['col1']).squeeze().to_list(), axis=1).explode().value_counts()

Output :

John          2
Mark          2
Susan         1
Mr.Bean       1
The Smiths    1
Barbara       1
Poly          1
Nick          1

熊猫:是否有一种方法可以计算给定列中包含单词值的给定列中值的发生数量?

混浊又暗下来 2025-02-16 08:38:49

在Java 8之前,

我们可以使用 arrays.toString(array)打印一个维数组和 arrays.deeptostring(array)用于多维数组。

Java 8

现在我们可以选择 stream lambda 打印数组。

打印一维数组:

public static void main(String[] args) {
    int[] intArray = new int[] {1, 2, 3, 4, 5};
    String[] strArray = new String[] {"John", "Mary", "Bob"};

    //Prior to Java 8
    System.out.println(Arrays.toString(intArray));
    System.out.println(Arrays.toString(strArray));

    // In Java 8 we have lambda expressions
    Arrays.stream(intArray).forEach(System.out::println);
    Arrays.stream(strArray).forEach(System.out::println);
}

输出为:

[1,2,3,4,5]
[约翰,玛丽,鲍勃]
1
2
3
4
5
约翰
玛丽
鲍勃

打印多维阵列
以防万一我们要打印多维数组,我们可以使用 arrays.deeptostring(array) as:

public static void main(String[] args) {
    int[][] int2DArray = new int[][] { {11, 12}, { 21, 22}, {31, 32, 33} };
    String[][] str2DArray = new String[][]{ {"John", "Bravo"} , {"Mary", "Lee"}, {"Bob", "Johnson"} };

    //Prior to Java 8
    System.out.println(Arrays.deepToString(int2DArray));
    System.out.println(Arrays.deepToString(str2DArray));

    // In Java 8 we have lambda expressions
    Arrays.stream(int2DArray).flatMapToInt(x -> Arrays.stream(x)).forEach(System.out::println);
    Arrays.stream(str2DArray).flatMap(x -> Arrays.stream(x)).forEach(System.out::println);
} 

现在要观察到的要点是方法 arrays.stream.stream(t [])< /code>,如果是 int [] 返回我们 stream&lt; int []&gt; ,然后方法 flatmaptoint()映射每个元素通过将提供的映射函数应用于每个元素而产生的映射流的内容。

输出是:

[[[11,12],[21,22],[31,32,33]]
[[John,Bravo],[Mary,Lee],[Bob,Johnson]]
11
12
21
22
31
32
33
约翰
Bravo
玛丽

鲍勃
约翰逊

Prior to Java 8

We could have used Arrays.toString(array) to print one dimensional array and Arrays.deepToString(array) for multi-dimensional arrays.

Java 8

Now we have got the option of Stream and lambda to print the array.

Printing One dimensional Array:

public static void main(String[] args) {
    int[] intArray = new int[] {1, 2, 3, 4, 5};
    String[] strArray = new String[] {"John", "Mary", "Bob"};

    //Prior to Java 8
    System.out.println(Arrays.toString(intArray));
    System.out.println(Arrays.toString(strArray));

    // In Java 8 we have lambda expressions
    Arrays.stream(intArray).forEach(System.out::println);
    Arrays.stream(strArray).forEach(System.out::println);
}

The output is:

[1, 2, 3, 4, 5]
[John, Mary, Bob]
1
2
3
4
5
John
Mary
Bob

Printing Multi-dimensional Array
Just in case we want to print multi-dimensional array we can use Arrays.deepToString(array) as:

public static void main(String[] args) {
    int[][] int2DArray = new int[][] { {11, 12}, { 21, 22}, {31, 32, 33} };
    String[][] str2DArray = new String[][]{ {"John", "Bravo"} , {"Mary", "Lee"}, {"Bob", "Johnson"} };

    //Prior to Java 8
    System.out.println(Arrays.deepToString(int2DArray));
    System.out.println(Arrays.deepToString(str2DArray));

    // In Java 8 we have lambda expressions
    Arrays.stream(int2DArray).flatMapToInt(x -> Arrays.stream(x)).forEach(System.out::println);
    Arrays.stream(str2DArray).flatMap(x -> Arrays.stream(x)).forEach(System.out::println);
} 

Now the point to observe is that the method Arrays.stream(T[]), which in case of int[] returns us Stream<int[]> and then method flatMapToInt() maps each element of stream with the contents of a mapped stream produced by applying the provided mapping function to each element.

The output is:

[[11, 12], [21, 22], [31, 32, 33]]
[[John, Bravo], [Mary, Lee], [Bob, Johnson]]
11
12
21
22
31
32
33
John
Bravo
Mary
Lee
Bob
Johnson

什么是打印Java数组的最简单方法?

混浊又暗下来 2025-02-15 21:18:19

用UID指定用户名是正确的,但是密码属性是PWD - 您缺少The TrafingD。这就是它所抱怨的。登录失败是临时的 - 它没有密码,但这是次要问题。您可能还会发现它对DSN -ODBC Favors Server = {server}; database = {database}不满意。通常,您还会还指定驱动程序,因此完整的ODBC连接字符串看起来像一个(假设您使用SQL Server):

driver = {sql Server}; server = Servername; database; database = db_name; uid = username ; pwd = password;

或,如果它是一个受信任的连接(使用与Windows登录相同的凭据)

driver = {sql Server}; server = servername; database; database = db_name; trusted connection; trust connection = yes; yes; <<<<<<< /code>

从任何一个合适的开始,假设它有效,如果您想进行实验以查找最低限度的内容,则可以从一次消除一个键值对开始,直到它破裂为止。不过,我建议您使用长格式。

如果您的服务器使用SQL Server以外的其他方式,请通过搜索“ ODBC数据源管理”来查找驱动程序名称。这将为您提供适当的应用程序,您使用的驱动程序应在此处列出。

ODBC的好处是老化且非常稳定,但是它对您的设置方式往往很挑剔。好消息是,一旦正确设置,它将在几十年内就不会浮出水面。

Specifying the username with UID is correct, but the password attribute is PWD - you're missing the trailing D. That's what it complains of. The login failure is extemporaneous - it has no password, but that's a secondary problem. You'll likely also find that it's unhappy with DSN - ODBC favors Server={Server};Database={database}. Typically you'll also specify a driver so a full ODBC connection string would look like one of (assuming you're using Sql Server):

Driver={Sql Server};Server=servername;Database=db_name;Uid=username;Pwd=password;

or, if it's a trusted connection (using the same credentials as your windows login)

Driver={Sql Server};Server=servername;Database=db_name;Trusted Connection=Yes;

Start with whichever of those is appropriate and, assuming it works, if you want to then experiment to find what the base MINIMUM is, you can start by eliminating one key-value pair at a time until it breaks. As a bit of advice, though, I'd suggest using the long-form.

If your server is using other than SQL Server, look for the driver name by searching for "ODBC Data Source Administration". That will give you the appropriate application and the driver you're using should be listed there.

ODBC has the benefit of being old and very stable, but it tends to be fussy about how you set it up. The good news is that once set up properly, it'll behave for decades without a blip.

通过ODBCConnection连接时无效连接字符串属性

混浊又暗下来 2025-02-15 19:55:22

考虑您正在读取键盘输入(标准输入流),然后通常您要这样做:

Scanner scanner=new Scanner(System.in);

在此处,扫描仪构造函数接受 java.io.inputStream 参数 system.in 正在返回。

in 是系统类型 java.io.inputStream 类的公共静态成员变量。

Consider you are reading keyboard input(Standard input stream), then usually you do:

Scanner scanner=new Scanner(System.in);

Here, Scanner constructor is accepting java.io.InputStream parameter which System.in is returning.

in is public static member variable of System class of type java.io.InputStream.

输入流语法

混浊又暗下来 2025-02-15 19:04:51
  1. 确保您已将文件名给了该程序作为一个
    参数。

    由G ++编译后,您应该这样运行以下程序:

      ./程序filename.txt
     

    argv [1] 是第一个程序参数,在这种情况下
    “ filename.txt”。

  2. 确保在同一工作目录中启动该程序的任何内容

  3. 请确保文件程序具有足够的权限可以读取文件。可以通过 chmod

    更改。

  1. Make sure that you have given the filename to the program as an
    argument.

    After being compiled by g++, you should run the program like this:

    ./program filename.txt
    

    argv[1] is the first program argument, in this case
    "filename.txt".

  2. Make sure that whatever launches the program is in the same working directory

  3. Make sure that the file program has sufficient permissions to read the file. This can be changed with chmod.

可以使用C&#x2B;&#x2B;可以打开文件

混浊又暗下来 2025-02-15 11:23:11

为此,我们可以使用可计算的内线绑定与副作用(您可以完全删除Onchange),这是一个演示

 Slider(value: Binding(get: { noteLength }, 
     set: { 
        // willSet side-effect here       // << here !!
        noteLenght = $0
        // didSet side-effect here       // << here !!
     }), 
    in: 0.1...3.01, step: 0.1)
    .onChange(of: noteLength, perform:  { value in
        defaults.set(value, forKey: "noteLengthEx1")
        levelIndex = 4
    })

We can use computable in-inline binding with side-effect for this (and you can remove onChange at all), here is a demo

 Slider(value: Binding(get: { noteLength }, 
     set: { 
        // willSet side-effect here       // << here !!
        noteLenght = $0
        // didSet side-effect here       // << here !!
     }), 
    in: 0.1...3.01, step: 0.1)
    .onChange(of: noteLength, perform:  { value in
        defaults.set(value, forKey: "noteLengthEx1")
        levelIndex = 4
    })

当Swift中使用滑块时,有没有办法调用功能?

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