(Google http://source.android.com/source)
Build a compilation environment
1. Initial language compilation environment
The source code size is about 6 GB. It takes about 25 GB to complete a compilation, and my hard drive is 50 GB.
2. Create a Linux
I have updated a lot of things. Please go to the official website to check details. This article is outdated.
After a long time
I have read many articles on the Internet.
Finally, the source code of the ginger pie is compiled successfully.
To sum
In the morning on the computer to synchronize the android source code (using repo sync), the prompt "a new version of Repo is available", so downloaded the latest repo (curl https://dl-ssl.google.com/dl/googlesource/git-repo/repo> repo)
Execute
Fourth chapter source code download and compileAndroid source code contains something: an app embedded in android : photos, calculators, calendars, albums, dialer and other source code;Android SDK With various tools: such as:adb, emulator mksdcard
To download the source code, you first need to install the following software: Curl and Git-core 1.1 Install Curl:Execute in Terminal: $sudo apt-get Install Curl 1.2 installation Git-core1.2. 1 Create a new bin file in the user directory to execute
First step to install the. Net Core EnvironmentInstall dotnet Environment See the official website Https://www.microsoft.com/net/core.Select the appropriate system version to install. After the installation is completed, enter the command to view
Blog "android source code download-using Git clone to implement a single folder download" introduced the use of Git clone method to download Android single folder source code, this article has four years of history, during which Google's source code
1. $sudo pip install-v pyv8Error:pip unicodedecodeerror ' ASCII ' codec can ' t decode byte 0xe2 in position ordinal No in range (128)2. Update the PIP versionUninstall Python-pip (version:1.5), latest Pip 6.0.7Remove your system wide installation
This shows the process of compiling the TensorFlow from the source code.The original tutorial https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/get_started/os_setup.md# on GitHub Installing-from-sourcesFirst, install the Build
According to the "Dig" development needs, choose Nodejs to implement asynchronous Io, in order to resolve the server card is not able to process the subsequent HTTP requests. Look at the structure of the flower petal video lectures, just decided to
Upgrade Python version#pythoncentOS6.8 installed in the default version 2.6, because I install to the back of the error Python version is lower, so you can first upgrade the Python version to 2.7;Enter directly at the command line: #wget https://www.
It relies on LXC (Linux Container) to get a configured Linux image from the network, and it is very easy to run its own applications in an isolated system. Also because its underlying core is a LXC, you need to run a small LXC in VirtualBox under
1. Update the PIP version#安装curl https://bootstrap.pypa.io/get-pip.py -o get-pip.pypython3 setup.py install pip install -U pip2. Use Pip to install the VIRTUALENV Virtual Environment tool to create a development environment:pip3.5 install
Http://spring.io/blog/2015/02/11/better-application-events-in-spring-framework-4-2Better application Events in Spring Framework 4.2 ENGINEERING STÉPHANE NICOLL February one, COMMENTSApplication events is available since the very beginning of the
(0) Jane saidcurrently hasnand thenvmThese two tools can be upgraded to node, the following is a brief introduction to the use of both. (1) nInstallation is simple:$ sudo npm install-g nAnother way to get the source code installation:$ git clone
This article describes how to build a localized Docker image warehouse on the POWER8 server, which involves mirroring production, Docker Registry service startup, and so on. I want to be able to provide reference for the students who build Docker
Objective
After installing tools such as Python and pip,setuptools, you can create a virualenv virtual environment, a virtual machine-like tool that lets you run multiple versions of the Python program on the same computer, without affecting each
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