boto

windows 10 webrtc 下载与编译以及遇到的问题

只愿长相守 提交于 2020-11-01 13:46:50
下载: 1、由于webrtc 源码在 墙外,所以需要科学上网(自行解决)。当然现在webrtc 有国内的镜像地址:https://webrtc.org.cn/mirror 内附编译下载教程自行查阅(下载后只包含M79 和最新的master 分支),由于个人项目需要M72 版本,所以需要科学上网。 2、需要在windows 上安装git(version 2.23.0.windows.1),然后配置环境变量,后续需要在 “命令提示符” 中使用 3、下载depot_tools git clone https://chromium.googlesource.com/chromium/tools/depot_tools.git 下载depot-tools之后解压,把解压目录设置到环境变量里面 (PATH) 环境变量中添加下面两项 DEPOT_TOOLS_WIN_TOOL_WIN_TOOLCHAIN = 0 4、下载WebRTC源码 创建文件夹 $mkdir webrtc_wins $cd webrtc_src 获取源码 $fetch --nohooks webrtc $gclient sync 将分支定位到m72 $cd src $git checkout -b m72 refs/remotes/branch-heads/72 $gclient sync 编译 1、编译前需要配置一下环境

如何设置Ansible AWS的动态清单

≯℡__Kan透↙ 提交于 2020-10-27 17:53:31
当您将Ansible与AWS结合使用时,维护清单文件将是一项繁重的任务,因为AWS经常更改IP,自动缩放实例等。但是,有一个简单的解决方案就是ansible动态清单。它基本上是一个Python脚本,当您运行ansible命令时会进行API调用以获取实例信息。这将为您提供动态清单详细信息,这些信息可以用来方便管理AWS基础架构。 设置Ansible AWS动态清单 1.使用pip安装boto库。如果您尚未安装pip,则可以按照此文档进行安装–> 安装python pip pip install boto 2.将清单脚本下载到/ etc / ansible目录。 Wget https://raw.github.com/ansible/ansible/devel/contrib/inventory/ec2.py 3.使文件可执行。 chmod + x ec2.py 4.将ec2.ini文件下载到/ etc / ansible目录。 https://raw.githubusercontent.com/ansible/ansible/devel/contrib/inventory/ec2.ini ec2.ini文件具有默认的AWS配置,可通过ec2.py文件读取。因此,请注释掉并配置必要的参数,以免查询时间过长。这样的例子就是“ regions”参数。默认情况下,该值为“ all”

How to get all messages in Amazon SQS queue using boto library in Python?

江枫思渺然 提交于 2020-08-22 04:20:13
问题 I'm working on an application whose workflow is managed by passing messages in SQS, using boto. My SQS queue is growing gradually, and I have no way to check how many elements it is supposed to contain. Now I have a daemon that periodically polls the queue, and checks if i have a fixed-size set of elements. For example, consider the following "queue": q = ["msg1_comp1", "msg2_comp1", "msg1_comp2", "msg3_comp1", "msg2_comp2"] Now I want to check if I have "msg1_comp1", "msg2_comp1" and "msg3

在AWS上部署、监控和扩展机器学习模型

和自甴很熟 提交于 2020-08-15 13:16:05
作者|Aparna Dhinakaran 编译|Flin 来源|towardsdatascience 部署健壮的、可扩展的机器学习解决方案仍然是一个非常复杂的过程,需要大量的人力参与,并做出很多努力。因此,新产品和服务需要很长时间才能上市,或者在原型状态下就被放弃,从而降低了行业内的对它的兴趣。那么,我们如何才能促进将机器学习模型投入生产的过程呢? Cortex是一个将机器学习模型部署为生产网络服务的开源平台。它利用强大的AWS生态系统,根据需要部署、监视和扩展与框架无关的模型。其主要特点概括如下: 框架无关:Cortex支持任何python代码;与其他python脚本一样,TensorFlow、PyTorch、scikit-learn、XGBoost都是由该库支持的。 自动缩放:Cortex自动缩放你的api,以处理生产负载。 CPU / GPU支持:使用AWS IaaS作为底层基础架构,Cortex可以在CPU或GPU环境下运行。 Spot实例:Cortex支持EC2 Spot实例来降低成本。 滚动更新:Cortex对模型应用任何更新,没有任何停机时间。 日志流:Cortex使用类似docker的语法将部署模型中的日志保存下来,并将其流式传输到CLI。 预测监测:Cortex监测网络指标并跟踪预测。 最小配置:Cortex部署配置被定义为一个简单的YAML文件。 在本文中

离线编译chromium 59.0.3071.104,方法适合任意版本

瘦欲@ 提交于 2020-08-11 04:59:08
离线编译chromium 59.0.3071.104,方法适合任意版本 离线编译任意版本chromium 准备 修改 运行&编译 可能出现的问题及解决 离线编译任意版本chromium 没错, **离线 **且 **任意版本 ** chromium。离线还是要下载必要的代码的,但是可以分步进行,极大的提高编译成功率。 准备 chromium在墙内的git地址可以直接访问 https://github.com/chromium/chromium, 但是稳定的tag限于73以后,73以前的tag代码可以从 https://chromium.googlesource.com/chromium/src/+refs 下载指定的版本。 我以59.0.3071.104为例,下载好tar包:chromium-59.0.3071.104.tar.xz,大小500多M,直接翻墙下载很稳定,或者直接下载 源码离线包 下载最新depot_tools 见 http://commondatastorage.googleapis.com/chrome-infra-docs/flat/depot_tools/docs/html/depot_tools_tutorial.html#_setting_up 安装vs2015社区版,注意必须是update3,设置好INCLUDE环境变量: C:\Program

How to check User Data status while launching the instance in aws

梦想的初衷 提交于 2020-07-16 16:51:31
问题 I am trying to launch aws instance with User Data. My User Data is a server installation process and i have to check whether the user data scripts are executed properly. Is there any option to check if the status of User data is completed ? I need to know the status since from that launched instance i am taking another image. As off now, i explicitly used time.sleep(90) for my process completion. Note: I am using Boto library. Any solution on this would be greatly appreciated! 回答1: UPDATE

AWS cloudformation: One big template file or many small ones?

本小妞迷上赌 提交于 2020-07-04 20:26:09
问题 I'm about to rewrite a lot of my aws deployment code to launch everything with cloudformation controlled by boto, instead of bringing up each element on its own with boto. Does anyone know if its "best practice" to use one giant template file, which kicks everything off together, or a lot of smaller ones? The advantage of one giant one seems to be that AWS handles all the dependancies for you so will bring things up slightly faster. The clear disadvantage is that it seems like a nightmare to

AWS cloudformation: One big template file or many small ones?

流过昼夜 提交于 2020-07-04 20:25:27
问题 I'm about to rewrite a lot of my aws deployment code to launch everything with cloudformation controlled by boto, instead of bringing up each element on its own with boto. Does anyone know if its "best practice" to use one giant template file, which kicks everything off together, or a lot of smaller ones? The advantage of one giant one seems to be that AWS handles all the dependancies for you so will bring things up slightly faster. The clear disadvantage is that it seems like a nightmare to

aws boto - how to create instance and return instance_id

这一生的挚爱 提交于 2020-06-29 11:28:20
问题 I want to create a python script where I can pass arguments/inputs to specify instance type and later attach an extra EBS (if needed). ec2 = boto3.resource('ec2','us-east-1') hddSize = input('Enter HDD Size if you want extra space ') instType = input('Enter the instance type ') def createInstance(): ec2.create_instances( ImageId=AMI, InstanceType = instType, SubnetId='subnet-31d3ad3', DisableApiTermination=True, SecurityGroupIds=['sg-sa4q36fc'], KeyName='key' ) return instanceID; ## I know

boto3 can't connect to S3 from Docker container running in AWS batch

a 夏天 提交于 2020-05-29 10:43:50
问题 I am attempting to launch a Docker container stored in ECR as an AWS batch job. The entrypoint python script of this container attempts to connect to S3 and download a file. I have attached a role with AmazonS3FullAccess to both the AWSBatchServiceRole in the compute environment and I have also attached a role with AmazonS3FullAccess to the compute resources. This is the following error that is being logged: botocore.exceptions.ConnectTimeoutError: Connect timeout on endpoint URL: "https://s3