in <module> main()的问题(暂时没有解决办法)

7、python基础:错误和异常 文章目录前言一、句法错误二、异常三、处理异常四、触发异常五、异常链python官方文档链接python官方标准库链接 前言 余生平,怎一个懒字了得。 一、句法错误 句法错误又称解析错误,是学习 Python 时最常见的错误: >>> while True print('Hello world') File "<stdin>", line 1 while True print('Hello world') ^ SyntaxErro 阅读详情
AI摘要

此篇博客讲述了在尝试使用Python的pip命令时遇到'KeyError: None'的问题,通过在脚本中添加from pip import main并解析了出现的警告和解决方法,重点在于理解pip的旧脚本模式和正确调用方式。

Traceback (most recent call last):
  File "C:\Users\a-xiaobodou\OneDrive - Microsoft\Projects\Python\weatherapp\weatherapp.py", line 96, in <module>
    main()
  File "C:\Users\a-xiaobodou\OneDrive - Microsoft\Projects\Python\weatherapp\weatherapp.py", line 41, in main
    city_name = citys[sht.range("city_name").value]
KeyError: None

Process finished with exit code 1

在if __main__="__main__"的上面增加一个语句:from pip import main

结果出现是

WARNING: pip is being invoked by an old script wrapper. This will fail in a future version of pip.
Please see https://github.com/pypa/pip/issues/5599 for advice on fixing the underlying issue.
To avoid this problem you can invoke Python with '-m pip' instead of running pip directly.

Usage:   
  weatherapp.py <command> [options]

Commands:
  install                     Install packages.
  download                    Download packages.
  uninstall                   Uninstall packages.
  freeze                      Output installed packages in requirements format.
  list                        List installed packages.
  show                        Show information about installed packages.
  check                       Verify installed packages have compatible dependencies.
  config                      Manage local and global configuration.
  search                      Search PyPI for packages.
  cache                       Inspect and manage pip's wheel cache.
  index                       Inspect information available from package indexes.
  wheel                       Build wheels from your requirements.
  hash                        Compute hashes of package archives.
  completion                  A helper command used for command completion.
  debug                       Show information useful for debugging.
  help                        Show help for commands.

General Options:
  -h, --help                  Show help.
  --debug                     Let unhandled exceptions propagate outside the
                              main subroutine, instead of logging them to
                              stderr.
  --isolated                  Run pip in an isolated mode, ignoring
                              environment variables and user configuration.
  --require-virtualenv        Allow pip to only run in a virtual environment;
                              exit with an error otherwise.
  -v, --verbose               Give more output. Option is additive, and can be
                              used up to 3 times.
  -V, --version               Show version and exit.
  -q, --quiet                 Give less output. Option is additive, and can be
                              used up to 3 times (corresponding to WARNING,
                              ERROR, and CRITICAL logging levels).
  --log <path>                Path to a verbose appending log.
  --no-input                  Disable prompting for input.
  --proxy <proxy>             Specify a proxy in the form
                              [user:passwd@]proxy.server:port.
  --retries <retries>         Maximum number of retries each connection should
                              attempt (default 5 times).
  --timeout <sec>             Set the socket timeout (default 15 seconds).
  --exists-action <action>    Default action when a path already exists:
                              (s)witch, (i)gnore, (w)ipe, (b)ackup, (a)bort.
  --trusted-host <hostname>   Mark this host or host:port pair as trusted,
                              even though it does not have valid or any HTTPS.
  --cert <path>               Path to PEM-encoded CA certificate bundle. If
                              provided, overrides the default. See 'SSL
                              Certificate Verification' in pip documentation
                              for more information.
  --client-cert <path>        Path to SSL client certificate, a single file
                              containing the private key and the certificate
                              in PEM format.
  --cache-dir <dir>           Store the cache data in <dir>.
  --no-cache-dir              Disable the cache.
  --disable-pip-version-check
                              Don't periodically check PyPI to determine
                              whether a new version of pip is available for
                              download. Implied with --no-index.
  --no-color                  Suppress colored output.
  --no-python-version-warning
                              Silence deprecation warnings for upcoming
                              unsupported Pythons.
  --use-feature <feature>     Enable new functionality, that may be backward
                              incompatible.
  --use-deprecated <feature>  Enable deprecated functionality, that will be
                              removed in the future.

Process finished with exit code 0

Python报错:Traceback ():File 路径, line 12, in <module>,AttributeError以及NameError的原因及解决方法 本文主要讲解Python引入包,报错:AttributeError的原因及解决方法。日期:2023年5月10日作者:任聪聪。 阅读详情

相关推荐

股票行情接口,最全的接入方法

股票行情接口一般有两种,一种是WebSocket,一种是http,通过WebSocket可以获取逐笔的股票tick数据,实时并且高效;通过http接口可以获取股票行情接口中的股票历史数据;WebSocket是一种高效的双向通信协议,它允许数据的实时推送,避免了不断的轮询请求。其次,WebSocket允许您订阅特定的数据源或股票数据产品,只接收您感兴趣的信息,提高了数据的效率和可用性。通过接入股票行情数据的HTTP接口,您可以将数据导入到自己的分析工具或系统中,进行更深入的数据分析、模型构建和决策支持。

apifinance的博客 3423

Python模块(Module)

一个Python Module(模块),是一个文件,包含了Python对象定义和Python语句(definitions and statements)。文件名就是模块名加上后缀.py,在模块内部,模块名存储在全局变量__name__中,是一个string,可以直接在module中通过__name__引用到module name。 module是为了重复使用一些对象,比如类,函数,而将这些对象...

weixin_30764883的博客 452

UUVsimulator仿真

pub -r 10 /cmd_vel geometry_msgs/Twist控制运动没有反应。通过键盘控制运动,接收不到/cmd_vel消息。

Fatal__的博客 4606

chatgpt赋能python:Python报错InModule详解

当Python解释器试图导入一个模块,但却无法找到该模块时,就会引发In Module错误。你尝试导入一个不存在的模块你尝试导入模块的路径有误例如,如果你在你的Python代码中使用这是因为Python无法找到mathx这个模块。本文由chatgpt生成,文章没有在chatgpt生成的基础上进行任何的修改。以上只是chatgpt能力的冰山一角。作为通用的Aigc大模型,只是展现它原本的实力。对于颠覆工作方式的ChatGPT,应该选择拥抱而不是抗拒,未来属于“会用”AI的人。

vacvefito的博客 4705

抓包网络调试工具 reqable抓包教程

如果CA根证书未安装成功,网络图标是黄色,点击盾牌图标可以进入CA根证书安装界面,详细步骤请阅读。在API调试中,获取流量是第一步也是最基本的操作,这里讲解下如何使用Reqable获取流量,通俗地讲就是抓包。我们可以选择一个图片请求,双击打开详情面板,能够看到该请求的详细信息。如果系统代理未设置,网络图标是黄色,点击网络图标可以自动设置系统代理。此域名的结构树,可以查看该域名下所有请求的目录结构,点击选择可以查看该请求的详情。首先,需要启用Reqable的调试功能,点击最右上角的。打开浏览器,输入地址。

代码简单说 Vue、JAVA、PHP、Node.js 熟练运用,接口、架构、性能全搞定。 2557

基于YOLOv10的微小目标检测,多头检测器提升小目标检测精度

引入多头检测器助力YOLOv10,暴力提升小目标检测性能

①答疑群聊服务;②YOLO大模型知识问答系统;③计算机视觉论文生成智能体; 2569

PyCharm中“can't find '__main__' module in”问题的解决办法

一起来学Python PyCharm中“can’t find ‘main’ module in”问题的解决办法 Python语言,很久就想学习了,可总是下不了决心,现在宅在家,终于是可以学习下了。 一切顺利地下载安装了Python3.7,使用IDLE写了个“Hello World”,觉得这个工具也挺不错了,有空搜索了下网上Python大伽,发现很多人都在介绍使用PyCharm,饶有兴趣地看了PyC...

ydr888的博客 5873

向华为学习——解读158页 华为敏捷园区网技术解决方案【附全文阅读】

华为敏捷园区网解决方案通过策略随行和体验随身技术,满足移动办公场景下的网络需求。该方案采用敏捷交换机和防火墙自动执行策略配置,实现用户身份认证与业务策略的无缝衔接,且策略配置与IP地址解耦,简化了管理流程。相比传统技术,该方案有效解决了用户分级、QoS保障、无线接入等关键问题,确保用户在移动过程中获得一致的网络体验。

cdfunlove的博客 379

go: cannot find main module, but found .git/config in

在项目启动的时候特别是go build的时候就出现一个问题提示go: cannot find main module, but found .git/config in这个时候也是查看相关的文档发现问题,最初是以为没有.git/config这个文件也是查看发现并不是,因为这个文件夹是隐藏的所以需要在控制台输出 我们发现是有这个文件的,后面也是查阅文档发现是go的配置问题 我们需要把GO111MODULE配置为off关闭他set GO111MODULE=off这是window系统,macOS是export

qq_40896095的博客 6926

PointNet++改进策略目录

后续我将如何使用文章中创新点加入的PointNet++中代码实现部分进行更新。

u012901740的博客 2196

Open Lovable 网站克隆AI工具超详细实战教程(含环境配置、排错与代码修改)

本教程面向有一定计算机基础的新手用户,提供一份全面、深入的 Open Lovable 使用指南。从开发环境搭建、API密钥获取、项目部署到网站克隆、代码下载、本地运行与二次开发,涵盖全流程细节与常见问题解决方案。通过本教程,新手可掌握如何利用AI驱动的Open Lovable工具,将任意目标网站智能复刻为结构清晰、可编辑的现代前端项目(React/Vite),实现快速原型开发与技术学习。

hy行者勇哥的博客 4960

关于pycharm软件报错“can‘t find‘_main_‘module in”修改解释器配置的问题

首次安装运行pycharm时,容易出现图一所示的报错信息。 图一 “can’t find’main’module in”报错界面 查询资料发现,是因为“edit configuration”中设置错误,报错设置条件如图二,“script path”只选择了项目路径,而没有选中“.py”结尾的项目文件。 注:具体的“edit configuration”参见之前文章: 关于pycharm软件edit configurations及解释器配置的问题 图二 原始configuration设置参数 重新修改

跳动的喵尾巴 2088

国产上位机软件突围:适配统信UOS/麒麟OS的跨平台开发技术与实践(2026年信创实战指南)

(航天科技集团CTO):“在信创战场上,1ms的延迟意味着1个卫星的控制失效。2026年,C#/.NET MAUI不是选择,而是我们守护卫星的‘生命线’。

这里只有干货:从 Modbus 通信到 MES 对接,从 YOLO 训练到工控机部署,带你搞定工业软件开发全流程。 409

【Python】解决 can‘t find ‘__main__‘ module in ‘wm‘

当直接运行包的时侯(python wm),wm 不是作为一包来运行,因此包的路径 wm 没有被加入 sys.path 路径中。在__ini__.py 中定义一个 main() 函数,在__main__.py 中调用它,实现入口,最后调用了 wm.main() 函数,此时执行了。.py 的当前路径 wm 加入 sys.path 中,然后在这个路径下面寻找 wm 这个模块。早点的 python 版本,如果要想将一个文件夹作为包(package)来使用,当前文件夹下必须要有。像当前的 3 的版本,不用。

2025 热爱与开始 4157

IMSL CNL 7.0.0 (x86-64)Crack

IMSL CNL 7.0.0 (x86-64)Crack intel的算法库破解文件,这是C++版本的破解文件

数学建模模型总结

这是本人在两年内准备参加数学建模竞赛搜集到的模型资料,已经经过了本人的筛选和整理,希望能够对准备参加数学建模竞赛的学弟学妹们提供一些帮助!

can't find '__main__' module in ''

can't find '__main__' module in '' 使用sublime text运行python报错:can't find '__main__' module in ''。 其实问题很简单,只是因为没有将文件保存在本地,所以python运行会报错。 转载于:https://www.cnblogs.com/qmjy/p/11360104.html...

ba9284的博客 1918

蓝牙模块HM-10手册

蓝牙模块HM-10手册,该手册对蓝牙模块HM-10进行了详细的介绍和使用方法以及一些AT指令。

Python can't find '__main__' module in ''

第一次用Sublime Text, 一运行就运行出现这个错误 C:\Python27\python.exe: can't find '__main__' module in ''   *如果你没有保存一个文件就build,有可能出来以下的错误:

njxw1108的专栏 1万+

深度学习工具包 DeepLearningToolbox

深度学习工具包Deprecation notice.-----This toolbox is outdated and no longer maintained.There are much better tools available for deep learning than this toolbox, e.g. [Theano](http://deeplearning.net/software/theano/), [torch](http://torch.ch/) or [tensorflow](http://www.tensorflow.org/)I would suggest you use one of the tools mentioned above rather than use this toolbox.Best, Rasmus.DeepLearnToolbox================A Matlab toolbox for Deep Learning.Deep Learning is a new subfield of machine learning that focuses on learning deep hierarchical models of data.It is inspired by the human brain's apparent deep (layered, hierarchical) architecture.A good overview of the theory of Deep Learning theory is[Learning Deep Architectures for AI](http://www.iro.umontreal.ca/~bengioy/papers/ftml_book.pdf)For a more informal introduction, see the following videos by Geoffrey Hinton and Andrew Ng.* [The Next Generation of Neural Networks](http://www.youtube.com/watch?v=AyzOUbkUf3M) (Hinton, 2007)* [Recent Developments in Deep Learning](http://www.youtube.com/watch?v=VdIURAu1-aU) (Hinton, 2010)* [Unsupervised Feature Learning and Deep Learning](http://www.youtube.com/watch?v=ZmNOAtZIgIk) (Ng, 2011)If you use this toolbox in your research please cite [Prediction as a candidate for learning deep hierarchical models of data](http://www2.imm.dtu.dk/pubdb/views/publication_details.php?id=6284)```@MASTERSTHESIS\{IMM2012-06284, author = "R. B. Palm", title = "Prediction as a candidate for learning deep hierarchical models of data", year = "2012",}```Contact: rasmusbergpalm at gmail dot comDirectories included in the toolbox-----------------------------------`NN/` - A library for Feedforward Backpropagation Neural Networks`CNN/` - A library for Convolutional Neural Networks`DBN/` - A library for Deep Belief Networks`SAE/` - A library for Stacked Auto-Encoders`CAE/` - A library for Convolutional Auto-Encoders`util/` - Utility functions used by the libraries`data/` - Data used by the examples`tests/` - unit tests to verify toolbox is workingFor references on each library check REFS.mdSetup-----1. Download.2. addpath(genpath('DeepLearnToolbox'));Example: Deep Belief Network---------------------```matlabfunction test_example_DBNload mnist_uint8;train_x = double(train_x) / 255;test_x = double(test_x) / 255;train_y = double(train_y);test_y = double(test_y);%% ex1 train a 100 hidden unit RBM and visualize its weightsrand('state',0)dbn.sizes = [100];opts.numepochs = 1;opts.batchsize = 100;opts.momentum = 0;opts.alpha = 1;dbn = dbnsetup(dbn, train_x, opts);dbn = dbntrain(dbn, train_x, opts);figure; visualize(dbn.rbm{1}.W'); % Visualize the RBM weights%% ex2 train a 100-100 hidden unit DBN and use its weights to initialize a NNrand('state',0)%train dbndbn.sizes = [100 100];opts.numepochs = 1;opts.batchsize = 100;opts.momentum = 0;opts.alpha = 1;dbn = dbnsetup(dbn, train_x, opts);dbn = dbntrain(dbn, train_x, opts);%unfold dbn to nnnn = dbnunfoldtonn(dbn, 10);nn.activation_function = 'sigm';%train nnopts.numepochs = 1;opts.batchsize = 100;nn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.10, 'Too big error');```Example: Stacked Auto-Encoders---------------------```matlabfunction test_example_SAEload mnist_uint8;train_x = double(train_x)/255;test_x = double(test_x)/255;train_y = double(train_y);test_y = double(test_y);%% ex1 train a 100 hidden unit SDAE and use it to initialize a FFNN% Setup and train a stacked denoising autoencoder (SDAE)rand('state',0)sae = saesetup([784 100]);sae.ae{1}.activation_function = 'sigm';sae.ae{1}.learningRate = 1;sae.ae{1}.inputZeroMaskedFraction = 0.5;opts.numepochs = 1;opts.batchsize = 100;sae = saetrain(sae, train_x, opts);visualize(sae.ae{1}.W{1}(:,2:end)')% Use the SDAE to initialize a FFNNnn = nnsetup([784 100 10]);nn.activation_function = 'sigm';nn.learningRate = 1;nn.W{1} = sae.ae{1}.W{1};% Train the FFNNopts.numepochs = 1;opts.batchsize = 100;nn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.16, 'Too big error');```Example: Convolutional Neural Nets---------------------```matlabfunction test_example_CNNload mnist_uint8;train_x = double(reshape(train_x',28,28,60000))/255;test_x = double(reshape(test_x',28,28,10000))/255;train_y = double(train_y');test_y = double(test_y');%% ex1 Train a 6c-2s-12c-2s Convolutional neural network %will run 1 epoch in about 200 second and get around 11% error. %With 100 epochs you'll get around 1.2% errorrand('state',0)cnn.layers = { struct('type', 'i') %input layer struct('type', 'c', 'outputmaps', 6, 'kernelsize', 5) %convolution layer struct('type', 's', 'scale', 2) %sub sampling layer struct('type', 'c', 'outputmaps', 12, 'kernelsize', 5) %convolution layer struct('type', 's', 'scale', 2) %subsampling layer};cnn = cnnsetup(cnn, train_x, train_y);opts.alpha = 1;opts.batchsize = 50;opts.numepochs = 1;cnn = cnntrain(cnn, train_x, train_y, opts);[er, bad] = cnntest(cnn, test_x, test_y);%plot mean squared errorfigure; plot(cnn.rL);assert(er<0.12, 'Too big error');```Example: Neural Networks---------------------```matlabfunction test_example_NNload mnist_uint8;train_x = double(train_x) / 255;test_x = double(test_x) / 255;train_y = double(train_y);test_y = double(test_y);% normalize[train_x, mu, sigma] = zscore(train_x);test_x = normalize(test_x, mu, sigma);%% ex1 vanilla neural netrand('state',0)nn = nnsetup([784 100 10]);opts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samples[nn, L] = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.08, 'Too big error');%% ex2 neural net with L2 weight decayrand('state',0)nn = nnsetup([784 100 10]);nn.weightPenaltyL2 = 1e-4; % L2 weight decayopts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex3 neural net with dropoutrand('state',0)nn = nnsetup([784 100 10]);nn.dropoutFraction = 0.5; % Dropout fraction opts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex4 neural net with sigmoid activation functionrand('state',0)nn = nnsetup([784 100 10]);nn.activation_function = 'sigm'; % Sigmoid activation functionnn.learningRate = 1; % Sigm require a lower learning rateopts.numepochs = 1; % Number of full sweeps through dataopts.batchsize = 100; % Take a mean gradient step over this many samplesnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex5 plotting functionalityrand('state',0)nn = nnsetup([784 20 10]);opts.numepochs = 5; % Number of full sweeps through datann.output = 'softmax'; % use softmax outputopts.batchsize = 1000; % Take a mean gradient step over this many samplesopts.plot = 1; % enable plottingnn = nntrain(nn, train_x, train_y, opts);[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');%% ex6 neural net with sigmoid activation and plotting of validation and training error% split training data into training and validation datavx = train_x(1:10000,:);tx = train_x(10001:end,:);vy = train_y(1:10000,:);ty = train_y(10001:end,:);rand('state',0)nn = nnsetup([784 20 10]); nn.output = 'softmax'; % use softmax outputopts.numepochs = 5; % Number of full sweeps through dataopts.batchsize = 1000; % Take a mean gradient step over this many samplesopts.plot = 1; % enable plottingnn = nntrain(nn, tx, ty, opts, vx, vy); % nntrain takes validation set as last two arguments (optionally)[er, bad] = nntest(nn, test_x, test_y);assert(er < 0.1, 'Too big error');```[![Bitdeli Badge](https://d2weczhvl823v0.cloudfront.net/rasmusbergpalm/deeplearntoolbox/trend.png)](https://bitdeli.com/free "Bitdeli Badge")

报错no main manifest attribute, in app.jar

在app.jar中没有主清单属性

qq_45900010的博客 1805

no main manifest attribute, in demo.jar的原因和解决办法

根据提示,很明显是说找不到main入口,为什么是这样呢,我们打开jar包,看看jar包里的文件就知道了。jar的main入口是在jar包下–>META-INF文件夹下的MANINFEST.MF文件里定义的,可用用记事本打开这个文件,linux系统,可以cat 查看这个文件里的内容;重新clean package之后,执行。在我们的pom文件里,添加如下插件即可。

hacker_Lees的博客 2909

sublime text报错解决方法:XXX\python.exe: can't find '__main__' module in ''

打开sublime text,运行一句简单打印“Hello”的语句,出现报错XXX\python.exe: can't find '__main__' module in '' 解决方法如下: 由于sublime text需要对程序进行保存后才能运行,所以使用sublime text时,先保存程序文件,再运行(windows编译程序快捷键:Ctrl+B)程序即可。 解决方法如下: 由...

lisayh的博客 5435

webpack 5 如何在模块中使用顶层 await 并用 import() 切断 async module 传播链

在 webpack 5 中,如果一个模块在顶层使用了 `await`(例如数据库连接需要在模块可用之前建立),这个模块就变成了 **async module**:普通模块是同步求值的,而 async module 是异步求值的。麻烦在于,用普通 `import` 引入 async module 的模块本身也会变成 async module,并沿模块图向上传播。本文以仓库中的 [top-level-

gitblog_01041的博客 1031

Python多线程报错:on <module ‘__main__‘ (built-in)>

python多线程填坑:报错 Attribute Error: Can’t get attribute ‘你的多线程处理函数’ on <module ‘main’ (built-in)> jupyter 使用多线程时 from multiprocessing import Pool def down_temp(data): print(i) ... pool=Pool() for data in range(10): pool.apply_async(func=down_temp,args=

weixin_39862968的博客 5532

vscode运行程序时报go: cannot find main module, but found Gopkg.lock

从git上clone代码到本地运行时,报如下错误 go: cannot find main module, but found Gopkg.lock in d:\go\src\appserver to create a module there, run: cd ..\.. && go mod init exit status 1 Process exiting with ...

haiziccc的专栏 1万+

python error can't find '__main__' module in

今天学习python 的时候,发现出现了can't find '__main__' module in 的错误 百度以后发现了问题所在,关键是要把configuration 里面的路径修改位.py后缀的 修改以后: 再次运行,错误解决。 ...

weixin_38968853的博客 1363

小白:关于处理“can't find '__main__' module in ”这个问题的详细处理方式!

1、新手学习,安装过程比较顺利。 2、开始翻书开始学习。 3、运行过程中。出现了这个这个问题,(/usr/local/bin/python3.6: can’t find ‘main’ module in ‘/Users/interno.8/PycharmProjects/test/’)。查阅了各种网上资料,发现各位大神都是简单叙述,后来经过多次尝试,问题解决了。作为小白还是详细记录一下以便...

weixin_43164535的博客 11万+

(转载)(已解决)sublime text 写程序build后提示can't find '__main__' module in ' '

平时顺手打开sublime text3 写一段小程序  ctrl + b 结果蹦出来can't find '__main__' module in ' '  ......  原来如此逗比的原因!问题描述:               在sublime text里写最简单的python语句hello world:                    print  ('hello world')  ...

zhangmoyan9527的博客 762
上一篇: 283 · 三数之中的最大值(LintCode,算法,入门)
下一篇: 13001. 月球上的体重
DXB2021
博客等级 码龄5年 307粉丝 289原创
评论 5
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符
 
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

个

红包个数最小为10个

元

红包金额最低5元

当前余额3.43元 前往充值 >
需支付:10.00元
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付元
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值