深海游弋的鱼 – 第 15 页 – 智障儿童欢乐多

Gitlab Flow实践

当前git是大部分开发团队的首选版本管理工具，一个好的流程规范可以让大家有效地合作，像流水线一样有条不紊地进行团队协作。

业界包含三种flow：

Git flow
Github flow
Gitlab flow

ubuntu 22.04 WARNING: [pool ***] server reached max_children, consider raising it

最近 WordPress 上传图片的时候，偶尔会发生失败，报错 503。以前比较少，最近越来越频繁，于是跟踪了一下服务器的日志，看到如下报错信息：

xxx.xxx.xxx.xxx - - [08/Aug/2023:14:50:36 +0800] "POST /wp-admin/async-upload.php HTTP/2.0" 503 417 "https://www.mobibrw.com/wp-admin/post.php?post=xxxx&action=edit&classic-editor" "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36"

xxx.xxx.xxx.xxx - - [08/Aug/2023:14:50:36 +0800] "POST /wp-admin/async-upload.php HTTP/2.0" 503 417 "https://www.mobibrw.com/wp-admin/post.php?post=xxxx&action=edit&classic-editor" "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36"

查看 PHP 的日志，却找不到任何有用的日志，只看到如下警告：

起初是百思不得其解，按理说应该有相关报错才对。

后来仔细思考了一下，才想明白，原来是并发数超过最大限制了，默认的并发数量是 5，这个绝对是不够的，并发超过限制是没有任何报错信息的，日志只会给出一个警告。

详细的解决方案如下：

If you encounter such an error in the php logs, then it is time to modify max_children. The php logs are usually located in /var/log/, and in my case they are in /var/log/php7.4-fpm.log

WARNING: [pool ********] server reached max_children setting (8), consider raising it

1	WARNING: [pool ********] server reached max_children setting (8), consider raising it

Search for the file where the max_children variable is located, in my case the file is www.conf and is located in the folder: /etc/php/7.4/fpm/pool.d/

Change the value pm.max_children = 8 to a larger one, 16 for example

$ sudo nano /etc/php/7.4/fpm/pool.d/www.conf

1	$ sudo nano /etc/php/7.4/fpm/pool.d/www.conf

save the .conf file and restart the web server:

$ sudo systemctl restart apache2

1	$ sudo systemctl restart apache2

or only the php-fpm service as follows:

$ sudo systemctl restart php7.4-fpm.service

1	$ sudo systemctl restart php7.4-fpm.service

Eventually you can check these logs, who knows, you may not even know you have such a problem!

** As I noticed, for HestiaCP (VestaCP) users max_children can be found in both the /etc/php/7.4/fpm/pool.d/www.conf file and the file /usr/local/hestia/php/etc/php-fpm.conf

** Attention, you must also have enough memory for this, otherwise the results are not as expected!

Check the memory used by each php-fpm service-child with the following command:

$ ps -ef | grep '[f]'pm
root      618    1  0 Dec17 ?        00:00:27 php-fpm: master process (/usr/local/hestia/php/etc/php-fpm.conf)
root     1692    1  0 01:11 ?        00:00:00 php-fpm: master process (/etc/php/7.4/fpm/php-fpm.conf)
matrix    3539 1692 14 01:30 ?        00:00:03 php-fpm: pool mydomain314159265.com
matrix    3542 1692 10 01:30 ?        00:00:01 php-fpm: pool mydomain314159265.com
matrix    3547 1692  0 01:30 ?        00:00:00 php-fpm: pool mydomain314159265.com
matrix    3548 1692 15 01:30 ?        00:00:00 php-fpm: pool mydomain314159265.com

$ ps -ef | grep '[f]'pm

root 618 1 0 Dec17 ? 00:00:27 php-fpm: master process (/usr/local/hestia/php/etc/php-fpm.conf)

root 1692 1 0 01:11 ? 00:00:00 php-fpm: master process (/etc/php/7.4/fpm/php-fpm.conf)

matrix 3539 1692 14 01:30 ? 00:00:03 php-fpm: pool mydomain314159265.com

matrix 3542 1692 10 01:30 ? 00:00:01 php-fpm: pool mydomain314159265.com

matrix 3547 1692 0 01:30 ? 00:00:00 php-fpm: pool mydomain314159265.com

matrix 3548 1692 15 01:30 ? 00:00:00 php-fpm: pool mydomain314159265.com

Then, to see the memory required for these processes, we need to add the rss parameter which is “Resident Set Size” or the physical memory. Note: Modify php-fpm7.4 to suit your version of PHP:

$ ps -C php-fpm7.4 -o rss=
81316
136872
138096
121728

$ ps -C php-fpm7.4 -o rss=

81316

136872

138096

121728

These numbers are in Kbytes , so we calculate an average of the displayed values and multiply by max_children, and we find approximately the memory needed only for php, but don’t forget, the server also needs memory for Apache, Nginx, mysql … maybe Varnish, HAproxy, Redish, etc. .. so, check these values carefully!

参考链接

Solved! WARNING: [pool ***] server reached max_children, consider raising it

ubuntu 22.04 Warning: apt-key is deprecated

在尝试安装 nvidia-docker 的时候（ubuntu 22.04系统Docker和Nvidia-docker的安装、测试，及运行GUI应用），执行如下命令增加 nvidia 源：

$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
   && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \
   && curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \

&& curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \

&& curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

系统发出如下警告：

Warning: apt-key is deprecated. Manage keyring files in trusted.gpg.d instead (see apt-key(8)).

1	Warning: apt-key is deprecated. Manage keyring files in trusted.gpg.d instead (see apt-key(8)).

经过分析，是脚本中的如下部分导致：

$ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo tee /etc/apt/trusted.gpg.d/nvidia-docker.gpg

1	$ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey \| sudo tee /etc/apt/trusted.gpg.d/nvidia-docker.gpg

解决方法为修改为使用如下脚本：

$ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg 

$ sudo chmod 644 /etc/apt/trusted.gpg.d/nvidia-docker.gpg

$ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg

$ sudo chmod 644 /etc/apt/trusted.gpg.d/nvidia-docker.gpg

完整修改后的脚本如下：

$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
   && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
   && sudo chmod 644 /etc/apt/trusted.gpg.d/nvidia-docker.gpg \
   && curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \

&& curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \

&& sudo chmod 644 /etc/apt/trusted.gpg.d/nvidia-docker.gpg \

&& curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

参考链接

Warning: apt-key is deprecated (SOLVED)

ubuntu 22.04系统Docker和Nvidia-docker的安装、测试，及运行GUI应用

快速搭建所需开发环境

Docker文档：https://docs.docker.com/，Docker安装指南： Install Docker Engine on Ubuntu

Dokcer安装

Uninstall old versions ~$ sudo apt-get remove docker docker-engine docker.io containerd runc ~$ sudo apt-get install curl Install using the repository ~$ curl https://get.docker.com | sh \ && sudo systemctl --now enable docker Verify that Docker Engine is installed correctly by running the hello-world image. ~$ sudo docker run hello-world

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Uninstall old versions

~$ sudo apt-get remove docker docker-engine docker.io containerd runc

~$ sudo apt-get install curl

Install using the repository

~$ curl https://get.docker.com | sh \
&& sudo systemctl --now enable docker

Verify that Docker Engine is installed correctly by running the hello-world image.
~$ sudo docker run hello-world

Docker测试

# 启动docker服务 $ sudo service docker start # Docker: hello-world $ sudo docker run hello-world

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# 启动docker服务
$ sudo service docker start

# Docker: hello-world
$ sudo docker run hello-world

其他Docker命令：

Usage: service docker {start|stop|restart|status} 查看镜像 $ sudo docker images 查看容器 $ sudo docker container ls -a

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Usage: service docker {start|stop|restart|status}

查看镜像
$ sudo docker images

查看容器
$ sudo docker container ls -a

Tips：Docker中一般Crtl+C退出，传送门：停止、删除所有的 docker 容器和镜像。

Nvidia-docker安装

查看nvidia版本

$ nvidia-smi Thu Nov 26 10:34:37 2020 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 450.80.02 Driver Version: 450.80.02 CUDA Version: 11.0 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 GeForce RTX 2060 Off | 00000000:01:00.0 On | N/A | | 0% 37C P8 9W / 190W | 301MiB / 5931MiB | 2% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | 0 N/A N/A 942 G /usr/lib/xorg/Xorg 35MiB | | 0 N/A N/A 2278 G /usr/lib/xorg/Xorg 96MiB | | 0 N/A N/A 2404 G /usr/bin/gnome-shell 150MiB | | 0 N/A N/A 4051 G /usr/lib/firefox/firefox 3MiB | +-----------------------------------------------------------------------------+

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$ nvidia-smi
Thu Nov 26 10:34:37 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.80.02    Driver Version: 450.80.02    CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce RTX 2060    Off  | 00000000:01:00.0  On |                  N/A |
|  0%   37C    P8     9W / 190W |    301MiB /  5931MiB |      2%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A       942      G   /usr/lib/xorg/Xorg                 35MiB |
|    0   N/A  N/A      2278      G   /usr/lib/xorg/Xorg                 96MiB |
|    0   N/A  N/A      2404      G   /usr/bin/gnome-shell              150MiB |
|    0   N/A  N/A      4051      G   /usr/lib/firefox/firefox            3MiB |
+-----------------------------------------------------------------------------+

参考链接：官网 installation guide
Github：NVIDIA/nvidia-docker

# $ distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \ && curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \ && curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | \ sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \ sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list $ sudo apt-get update $ sudo apt-get install -y nvidia-container-toolkit $ sudo nvidia-ctk runtime configure --runtime=docker $ sudo systemctl restart docker $ docker pull nvidia/cudagl:11.0-base # 测试 $ docker run --rm --gpus all nvidia/cudagl:11.0-base nvidia-smi Thu Nov 26 02:30:34 2020 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 450.80.02 Driver Version: 450.80.02 CUDA Version: 11.0 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 GeForce RTX 2060 Off | 00000000:01:00.0 On | N/A | | 0% 37C P8 10W / 190W | 307MiB / 5931MiB | 13% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| +-----------------------------------------------------------------------------+

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#
$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
      && curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
      && curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | \
            sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
            sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list

$ sudo apt-get update

$ sudo apt-get install -y nvidia-container-toolkit

$ sudo nvidia-ctk runtime configure --runtime=docker

$ sudo systemctl restart docker

$ docker pull nvidia/cudagl:11.0-base

# 测试
$ docker run --rm --gpus all nvidia/cudagl:11.0-base nvidia-smi

Thu Nov 26 02:30:34 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.80.02    Driver Version: 450.80.02    CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce RTX 2060    Off  | 00000000:01:00.0  On |                  N/A |
|  0%   37C    P8    10W / 190W |    307MiB /  5931MiB |     13%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
+-----------------------------------------------------------------------------+

测试

$ sudo docker run --runtime=nvidia --rm nvidia/cudagl:11.0-base nvidia-smi

1

$ sudo docker run --runtime=nvidia --rm nvidia/cudagl:11.0-base nvidia-smi

Docker 容器 GUI

$ sudo apt-get install x11-xserver-utils # 关闭权限控制，允许其他X客户端绘制 $ xhost + access control disabled, clients can connect from any host $ docker run -e DISPLAY=$DISPLAY -e GDK_SCALE -e GDK_DPI_SCAL -v /tmp/.X11-unix:/tmp/.X11-unix --rm -it container-name-or-id

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$ sudo apt-get install x11-xserver-utils

# 关闭权限控制，允许其他X客户端绘制
$ xhost +
access control disabled, clients can connect from any host

$ docker run -e DISPLAY=$DISPLAY -e GDK_SCALE -e GDK_DPI_SCAL -v /tmp/.X11-unix:/tmp/.X11-unix --rm -it container-name-or-id

若遇到X Error时，添加参数：--ipc=host 或 --env="QT_X11_NO_MITSHM=1"，参考链接：
How to fix X Error: BadAccess, BadDrawable, BadShmSeg while running graphical application using Docker?
Docker: gazebo: cannot connect to X server
若遇到 libGL error: No matching fbConfigs or visuals found libGL error... ，参考链接：
使用docker时出现libGL error: No matching fbConfigs or visuals found libGL error: failed to load driver...
已成功测试上述链接中的 pull image 方式
使用nvidia-smi查看nvidia driver和cuda版本，根据 nvidia/cudagl ，选择合适的TAG

$ sudo apt-get install x11-xserver-utils $ nvidia-smi $ docker pull nvidia/cudagl:11.0-base # 关闭权限控制，允许其他X客户端绘制 $ xhost + access control disabled, clients can connect from any host $ sudo docker run --rm --runtime=nvidia -it -e DISPLAY=$DISPLAY -e GDK_SCALE -e GDK_DPI_SCAL -v /tmp/.X11-unix:/tmp/.X11-unix nvidia/cudagl:11.0-base $ apt-get update $ apt-get install mesa-utils $ glxgears

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$ sudo apt-get install x11-xserver-utils

$ nvidia-smi

$ docker pull nvidia/cudagl:11.0-base

# 关闭权限控制，允许其他X客户端绘制
$ xhost +
access control disabled, clients can connect from any host

$ sudo docker run --rm --runtime=nvidia -it -e DISPLAY=$DISPLAY -e GDK_SCALE -e GDK_DPI_SCAL -v /tmp/.X11-unix:/tmp/.X11-unix nvidia/cudagl:11.0-base

$ apt-get update

$ apt-get install mesa-utils

$ glxgears

创建新的长期镜像：

$ sudo apt-get install x11-xserver-utils

$ nvidia-smi

$ docker pull nvidia/cudagl:10.2-base

# 关闭权限控制，允许其他X客户端绘制
$ xhost +
access control disabled, clients can connect from any host

$ sudo docker run -it --name isaac --runtime=nvidia -it -e DISPLAY=$DISPLAY -e GDK_SCALE -e GDK_DPI_SCAL -v /tmp/.X11-unix:/tmp/.X11-unix -v /data/isaac:/data/isaac nvidia/cudagl:10.2-base

$ apt-get update

$ apt-get install mesa-utils

$ glxgears

$ exit

$ sudo docker ps -a

$ sudo docker start isaac

$ sudo docker attach isaac

$ sudo apt-get install x11-xserver-utils

$ nvidia-smi

$ docker pull nvidia/cudagl:10.2-base

# 关闭权限控制，允许其他X客户端绘制

$ xhost +

access control disabled, clients can connect from any host

$ sudo docker run -it --name isaac --runtime=nvidia -it -e DISPLAY=$DISPLAY -e GDK_SCALE -e GDK_DPI_SCAL -v /tmp/.X11-unix:/tmp/.X11-unix -v /data/isaac:/data/isaac nvidia/cudagl:10.2-base

$ apt-get update

$ apt-get install mesa-utils

$ glxgears

$ exit

$ sudo docker ps -a

$ sudo docker start isaac

$ sudo docker attach isaac

如果遇到如下报错：

Nvidia-container-cli: initialization error: load library failed: libnvidia-ml.so.1: cannot open shared object file: no such file or directory

1	Nvidia-container-cli: initialization error: load library failed: libnvidia-ml.so.1: cannot open shared object file: no such file or directory

上述报错目前没有找到很好的解决方法，应该是某个安装包意外修改了系统配置，导致出现问题，重装系统可以顺利解决此问题。

参考链接

Isaac教程--基于Elbrus立体视觉 VSLAM 的定位

基于Elbrus立体视觉 VSLAM 的定位

继续阅读Isaac教程--基于Elbrus立体视觉 VSLAM 的定位

使用 dart extension

如何使用

dart extension 的使用场景是无法修改原类的时候，通过扩展的方式来增加原类的方法，也可以增加 getter，setters，and operators。

比如

int.parse('42')

1	int.parse('42')

如果 String 有 pareseInt 方法，我们可以这样写

'42'.parseInt()

1	'42'.parseInt()

为了达到这个目标，需要写一个 Extension

extension NumberParsing on String {
  int parseInt() {
    return int.parse(this);
  }
  // ···
}

extension NumberParsing on String {

int parseInt() {

return int.parse(this);

}

// ···

}

然后就可以使用了。

// Import a library that contains an extension on String.
import 'string_apis.dart';
// ···
print('42'.padLeft(5)); // Use a String method.
print('42'.parseInt()); // Use an extension method.

// Import a library that contains an extension on String.

import 'string_apis.dart';

// ···

print('42'.padLeft(5)); // Use a String method.

print('42'.parseInt()); // Use an extension method.

处理冲突

注意到前面加的 NumberParsing 了吗？这个是为 extension 起的名字。起名字的作用是有冲突的时候可以方便的控制显隐。比如 NumberParsing2 也定义了 parseInt 方法与 NumberParsing 的 parseInt 冲突，如果只想要 NumberParsing 的 parseInt，只需要把 NumberParsing2 隐藏就好了。

// Defines the String extension method parseInt().
import 'string_apis.dart';

// Also defines parseInt(), but hiding NumberParsing2
// hides that extension method.
import 'string_apis_2.dart' hide NumberParsing2;

// ···
// Uses the parseInt() defined in 'string_apis.dart'.
print('42'.parseInt());

// Defines the String extension method parseInt().

import 'string_apis.dart';

// Also defines parseInt(), but hiding NumberParsing2

// hides that extension method.

import 'string_apis_2.dart' hide NumberParsing2;

// ···

// Uses the parseInt() defined in 'string_apis.dart'.

print('42'.parseInt());

或者可以给 NumberParsing2 经起个别名

import 'string_apis.dart';
import 'string_apis_2.dart' as rad;

print(NumberParsing('42').parseInt());

// Use the ParseNumbers extension from string_apis_3.dart.
print(rad.NumberParsing('42').parseInt());

// Only string_apis_3.dart has parseNum().
print('42'.parseNum());

import 'string_apis.dart';

import 'string_apis_2.dart' as rad;

print(NumberParsing('42').parseInt());

// Use the ParseNumbers extension from string_apis_3.dart.

print(rad.NumberParsing('42').parseInt());

// Only string_apis_3.dart has parseNum().

print('42'.parseNum());

泛型 extension

可以只给 int 类型的 list 加 sum 方法，其它类型的 list 不能使用 sum。

// Import a library that contains an extension on String.
import 'string_apis.dart';
// ···
print('42'.padLeft(5)); // Use a String method.
print('42'.parseInt()); // Use an extension method.

// Import a library that contains an extension on String.

import 'string_apis.dart';

// ···

print('42'.padLeft(5)); // Use a String method.

print('42'.parseInt()); // Use an extension method.

["1", "2", "3"].sum();  //Error: The method 'sum' isn't defined for the class 'List<String>'

[1,2,3].sum(); // ok, output 6

["1", "2", "3"].sum(); //Error: The method 'sum' isn't defined for the class 'List<String>'

[1,2,3].sum(); // ok, output 6

要注意的问题

dart extension 不可以用于 dynamic 类型

dynamic d = '2';
print(d.parseInt()); // Runtime exception: NoSuchMethodError

1 2	dynamic d = '2'; print(d.parseInt()); // Runtime exception: NoSuchMethodError

dart extension 权限很大，这也意味着，很可能被过度使用。所以在使用的时候一定要再三权衡，一定要可读性，可维护性优先。

上面的代码是比较简单的，但是如果类型比较复杂，不明确指定类型，类似如下的形式，也是可能会报错的：

class Provider {

 late final d;

 Provider() {
    this.d = '';
    this.d.parseInt(); // Runtime exception: NoSuchMethodError
  }

}

class Provider {

late final d;

Provider() {

this.d = '';

this.d.parseInt(); // Runtime exception: NoSuchMethodError

}

参考链接

智能硬件Nvidia Jetson Nano B01

产品参数

GPU	128-core Maxwell
CPU	Quad-core ARM A57 @ 1.43 GHz
内存	4 GB 64-bit LPDDR4 25.6 GB/s
存储	micro SD 卡
视频编码	4K @ 30 \| 4x 1080p @ 30 \| 9x 720p @ 30 (H.264/H.265)
视频解码	4K @ 60 \| 2x 4K @ 30 \| 8x 1080p @ 30 \| 18x 720p @ 30 (H.264/H.265)
摄像头	2x MIPI CSI-2 D-PHY lanes
联网	千兆以太网，M.2 Key E 接口外扩 (可外接： AC8265 双模网卡 )
显示	HDMI 和 DP 显示接口
USB	4x USB 3.0，USB 2.0 Micro-B
扩展接口	GPIO，I2C，I2S，SPI，UART
其他	260-pin 连接器

Jetson Nano系统安装

1、JetPack介绍

JetPack SDK包括最新的Linux驱动程序包(L4T)，带有Linux操作系统和CUDA-X加速库，以及用于深度学习、计算机视觉、加速计算和多媒体的API。它还包括用于主机和开发人员套件的示例、文档和开发人员工具，并支持更高级别的SDK，例如用于流式视频分析的DeepStream和用于机器人的Isaac。

2、JetPack 4.4

JetPack 目前最新版本是4.4，支持Vulkan 1.2、TensorRT 7.1.3 、cuDNN 8.0、CUDA 10.2 等。

3、下载和安装

下载 Jetson Nano镜像，镜像中包含提供引导加载程序、Ubuntu18.04、必要的固件、NVIDIA驱动程序、示例文件系统等。
使用 Etcher 或者 Raspberry Pi Imager 将镜像烧录到SD卡（建议至少32G）中。

设置VNC服务

1.执行更新

$ sudo apt-get update

1	$ sudo apt-get update

2.安装vino服务端

这个vino服务端我使用的镜像文件是安装好了的，但是古早版的镜像文件可能没有，所以可以执行下代码看看是否有安装。

$ sudo apt-get install vino

1	$ sudo apt-get install vino

3.开启VNC 服务

$ sudo ln -s ../vino-server.service /usr/lib/systemd/user/graphical-session.target.wants

1	$ sudo ln -s ../vino-server.service /usr/lib/systemd/user/graphical-session.target.wants

4.配置VNC服务

$ gsettings set org.gnome.Vino prompt-enabled false

$ gsettings set org.gnome.Vino require-encryption false

$ gsettings set org.gnome.Vino prompt-enabled false

$ gsettings set org.gnome.Vino require-encryption false

设置开机自启动

1.创建VNC自动启动文件

创建文件夹，然后创建一个自动启动文件

$ mkdir -p ~/.config/autostart

$ sudo gedit ~/.config/autostart/vino-server.desktop

$ mkdir -p ~/.config/autostart

$ sudo gedit ~/.config/autostart/vino-server.desktop

2.添加以下内容到vino-server.desktop文件中

[Desktop Entry]
 
Type=Application
 
Name=Vino VNC server
 
Exec=/usr/lib/vino/vino-server
 
NoDisplay=true

[Desktop Entry]

Type=Application

Name=Vino VNC server

Exec=/usr/lib/vino/vino-server

NoDisplay=true

这个时候，虽说是自动启动了，但是只有进入桌面后才自动启动服务，所以需要取消登录密码，启动就进入桌面。

参考链接

解决 Only fullscreen opaque activities can request orientation

这段时间把App的targetSDKVersion升级到了27，昨晚上线之后今早看到后台一堆崩溃，全是 Android 8.0 的设备，因为手头设备有限，测试的时候只测了Android 8.1的设备，没想到还有一个这个坑埋在这里，记录一下处理办法。

问题分析

当targetSDKVersion为26或者27时，在 Android 8.0 的设备上，一些设置了windowIsTranslucent标志，将背景设为透明，同事将屏幕方向锁定的Activity，会崩溃并抛出这个异常:

Caused by: java.lang.IllegalStateException: Only fullscreen opaque activities can request orientation
       at android.app.Activity.onCreate(Activity.java:1007)
       at android.support.v4.app.SupportActivity.onCreate(SupportActivity.java:66)
       at android.support.v4.app.FragmentActivity.onCreate(FragmentActivity.java:321)
       at android.support.v7.app.AppCompatActivity.onCreate(AppCompatActivity.java:84)
       at ...

Caused by: java.lang.IllegalStateException: Only fullscreen opaque activities can request orientation

at android.app.Activity.onCreate(Activity.java:1007)

at android.support.v4.app.SupportActivity.onCreate(SupportActivity.java:66)

at android.support.v4.app.FragmentActivity.onCreate(FragmentActivity.java:321)

at android.support.v7.app.AppCompatActivity.onCreate(AppCompatActivity.java:84)

at ...

这个问题网上有很多讨论以及解决方法，问题的原因出自这里

if (ActivityInfo.isFixedOrientation(requestedOrientation) && !fullscreen 
	&& appInfo.targetSdkVersion >= O) {
	throw new IllegalStateException("Only fullscreen activities can request orientation");
}

if (ActivityInfo.isFixedOrientation(requestedOrientation) && !fullscreen

&& appInfo.targetSdkVersion >= O) {

throw new IllegalStateException("Only fullscreen activities can request orientation");

}

这里做了当屏幕方向锁定了并且不为全屏并且 App 的targetSdkVersion 大于 Android O的话，就会抛出这个异常。

是否为全屏的判定如下:

public static boolean isTranslucentOrFloating(TypedArray attributes) {
	final boolean isTranslucent = attributes.getBoolean(
		com.android.internal.R.styleable.Window_windowIsTranslucent, false);
	final boolean isSwipeToDismiss = 
        !attributes.hasValue(com.android.internal.R.styleable.Window_windowIsTranslucent) 
		&& attributes.getBoolean(com.android.internal.R.styleable.Window_windowSwipeToDismiss, false);
	final boolean isFloating = 
        attributes.getBoolean(com.android.internal.R.styleable.Window_windowIsFloating, false);
	return isFloating || isTranslucent || isSwipeToDismiss;
}

public static boolean isTranslucentOrFloating(TypedArray attributes) {

final boolean isTranslucent = attributes.getBoolean(

com.android.internal.R.styleable.Window_windowIsTranslucent, false);

final boolean isSwipeToDismiss =

!attributes.hasValue(com.android.internal.R.styleable.Window_windowIsTranslucent)

&& attributes.getBoolean(com.android.internal.R.styleable.Window_windowSwipeToDismiss, false);

final boolean isFloating =

attributes.getBoolean(com.android.internal.R.styleable.Window_windowIsFloating, false);

return isFloating || isTranslucent || isSwipeToDismiss;

}

手头的 Android 8.1 的机器并没有触发这个问题，是因为这个问题在 8.1 里已经修复了。

解决方案

解决方法有如下几种:

降级targetSDKVersion到26以下~~(废话！！)~~
移除mainfest文件里的screenOrientation属性
取消Activity主题里的windowIsTranslucent属性或者windowSwipeToDismiss属性或者windowIsFloating属性（根据你设置了什么属性来具体分析）
（推荐）移除manifest文件里的screenOrientation属性，并在Activity的onCreate方法里设置屏幕方向

if (Build.VERSION.SDK_INT != Build.VERSION_CODES.O) {
	setRequestedOrientation(ActivityInfo.SCREEN_ORIENTATION_PORTRAIT);
}

if (Build.VERSION.SDK_INT != Build.VERSION_CODES.O) {

setRequestedOrientation(ActivityInfo.SCREEN_ORIENTATION_PORTRAIT);

}

参考链接

解决 Only fullscreen opaque activities can request orientation

Android 12 SplashScreen API以及Jetpack兼容库

前言

1、什么是Android的冷启动时间？

冷启动时间是指点击桌面LOGO那一刻起到启动页面的Activity调用onCreate()之前的时间段。

2、冷启动的时间段内发生了什么？

在一个Activity打开时，如果Application还没有启动，系统会创建一个进程，进程的创建和初始化会消耗一些时间，在这个时间中，WindowManager会先加载APP的主题样式里的窗口背景(windowBackground)作为预览元素，然后才会真正的加载布局，如果这个时间过长，会给用户造成一种错觉：APP卡顿不流畅

常见做法

将背景设置为APP Logo，市面上大部分APP都是这么做的

<style name="AppTheme" parent="BaseTheme">
    <item name="android:windowBackground">@drawable/window_splash_screen_content</item>
</style>

<item name="android:windowBackground">@drawable/window_splash_screen_content</item>

</style>

将背景设置为透明色，当点击桌面LOGO时并不会立即启动APP，而是在桌面停留一会(其实已经启动)

<style name="AppTheme" parent="BaseTheme">
    <item name="android:windowBackground">@android:color/transparent</item>
</style>

<item name="android:windowBackground">@android:color/transparent</item>

</style>

上面做法可以达到秒开效果，但属于掩耳盗铃。

Android 8.0

Google以前不推荐使用闪屏的使用，但是后来很多APP都在使用闪屏，Google希望让启动屏的制作更简单。

Android Oreo中提供了Splash Screen API，允许开发者把一个drawable资源设置为闪屏。

新建values-v26目录:

<resources>
    <style name="AppTheme" parent="BaseTheme">
        <item name="android:windowSplashscreenContent">@drawable/window_splash_screen_content</item>
    </style>
</resources>

<item name="android:windowSplashscreenContent">@drawable/window_splash_screen_content</item>

</style>

</resources>

通过windowSplashscreenContent设置的drawable资源将会覆盖在windowBackground顶部，在系统状态栏之下，如果不想受到System Bars限制，请使用全屏主题。

继续阅读Android 12 SplashScreen API以及Jetpack兼容库

Android中使用System.exit(0)退出后App又重新启动

System.exit(0)：终止当前正在运行的 Java 虚拟机。参数用作状态码；根据惯例，非 0 的状态码表示异常终止。

System.exit(0)正常终止程序，有时候在退出安卓应用会使用到。

使用这个方法如果前面存在没有finish()掉的Activity会重新启动，导致退出失败。

MainActivity代码：

直接启动第二个Activity：

@Override  
protected void onCreate(Bundle savedInstanceState) {  
    super.onCreate(savedInstanceState);  
    setContentView(R.layout.activity_main);  
    Intent intent=new Intent(MainActivity.this,NewActivity.class);  
    startActivity(intent);  
}

@Override

protected void onCreate(Bundle savedInstanceState) {

super.onCreate(savedInstanceState);

setContentView(R.layout.activity_main);

Intent intent=new Intent(MainActivity.this,NewActivity.class);

startActivity(intent);

}

NewActivity代码：

public class NewActivity extends Activity {  
@Override  
protected void onCreate(Bundle savedInstanceState) {  
    super.onCreate(savedInstanceState);  
    Button button=new Button(NewActivity.this);  
    button.setText("退出测试");  
    button.setOnClickListener(new View.OnClickListener() {  
        @Override  
        public void onClick(View view) {  
            System.exit(0);  
        }  
    });  
    setContentView(button);  
 }  
}

public class NewActivity extends Activity {

@Override

protected void onCreate(Bundle savedInstanceState) {

super.onCreate(savedInstanceState);

Button button=new Button(NewActivity.this);

button.setText("退出测试");

button.setOnClickListener(new View.OnClickListener() {

@Override

public void onClick(View view) {

System.exit(0);

}

});

setContentView(button);

}

此时点击button退出应用重启，修改MainActivity：启动新的Activity，finish存在MainAcitvity

@Override  
protected void onCreate(Bundle savedInstanceState) {  
    super.onCreate(savedInstanceState);  
    setContentView(R.layout.activity_main);  
    Intent intent=new Intent(MainActivity.this,NewActivity.class);  
    startActivity(intent);  
    this.finish();  
}

@Override

protected void onCreate(Bundle savedInstanceState) {

super.onCreate(savedInstanceState);

setContentView(R.layout.activity_main);

Intent intent=new Intent(MainActivity.this,NewActivity.class);

startActivity(intent);

this.finish();

}

总结：

因为应用栈中还存在别的activity没有finish，导致应用重新启动。

使用System.exit(0)时，确保任务栈中所有activity已经finish。

参考链接

Android中使用System.exit(0)退出后app又重新启动

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