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Styleguide - Style guides for Google-originated open-source projects

Styleguide - Style guides for Google-originated open-source projects
Every major open-source project has its own style guide: a set of conventions (sometimes arbitrary) about how to write code for that project. It is much easier to understand a large codebase when all the code in it is in a consistent style. “Style” covers a lot of ground, from “use camelCase for variable names” to “never use global variables” to “never use exceptions.” This project holds the style guidelines we use for Google code. If you are modifying a project that originated at Google, you may be pointed to this page to see the style guides that apply to that project. Our C++ Style Guide, Objective-C Style Guide, Java Style Guide, Python Style Guide, Shell Style Guide, HTML/CSS Style Guide, JavaScript Style Guide, AngularJS Style Guide, Common Lisp Style Guide, and Vimscript Style Guide are now available. If your project requires that you create a new XML document format, our XML Document Format Style Guide may be helpful.

signalfuse/maestro-ng slafs/cookiecutter-saltstack-formula Lightning MDB (aka Lightning Database, LMDB) Symas LMDB is an extraordinarily fast, memory-efficient database we developed for the Symas OpenLDAP Project. With memory-mapped files, it has the read performance of a pure in-memory database while retaining the persistence of standard disk-based databases. In other words, it runs like a bat out of hell, performing several times faster than other DB engines — several orders of magnitude faster in many cases. No buffers or caches needed, no memory copies generated. And it’s only limited to the size of the virtual address space, not to the size of physical RAM. Bottom line, with only 32KB of object code, LMDB may seem tiny. Explore Capabilities How It Compares Here’s a quick comparison of other embedded key value stores. Support and Documentation Commercial support, porting and professional services and documentation. Learn More Commercial Support Symas offers fixed-price commercial support to those using LMDB in your applications. Porting and Professional Services Support Documentation

How was C made? Autotest Remote (Autoserv) — autotest 2015.2.27 documentation Autoserv is a framework for “automating machine control” Autoserv’s purpose is to control machines, it can: power cycleinstall kernelsmodify bootloader entriesrun arbitrary commandsrun Autotest Local (client) teststransfer files A machine can be: localremote (through ssh and conmux)virtual (through kvm) Control Files¶ In a way similar to Autotest, Autoserv uses control files. Here is an example control file that installs a .deb packaged kernel on a remote host controlled through ssh. remote_host= hosts.SSHHost("") print"uname -a").stdout kernel= deb_kernel.DEBKernel()kernel.get("/var/local/linux-2.6.22.deb") print kernel.get_version()print kernel.get_image_name()print kernel.get_initrd_name() kernel.install(remote_host) remote_host.reboot() print"uname -a").stdout Hosts¶ “Host” objects are the work horses of Autoserv control files. Main Host Methods¶ Here are the most commonly used Host methods. CmdResult Objects¶ Main types of Host¶ SSHHost¶ SiteHost¶

hangarunderground/hendrix versae/qbe Tasks — Celery 3.1.17 documentation Tasks are the building blocks of Celery applications. A task is a class that can be created out of any callable. It performs dual roles in that it defines both what happens when a task is called (sends a message), and what happens when a worker receives that message. Every task class has a unique name, and this name is referenced in messages so that the worker can find the right function to execute. A task message does not disappear until the message has been acknowledged by a worker. Ideally task functions should be idempotent, which means that the function will not cause unintented effects even if called multiple times with the same arguments. If your task is idempotent you can set the acks_late option to have the worker acknowledge the message after the task returns instead. In this chapter you will learn all about defining tasks, and this is the table of contents: Basics You can easily create a task from any callable by using the task() decorator: Names For example: Context Logging

Welcome to django-smartfields’s documentation! — django-smartfields 1.0.4 documentation