1.3. A Quick Tour — Buildbot 0.9.12 documentation 1.3.1. Goal This tutorial will expand on the First Run tutorial by taking a quick tour around some of the features of buildbot that are hinted at in the comments in the sample configuration. As a part of this tutorial, we will make buildbot do a few actual builds. This section will teach you how to: make simple configuration changes and activate themdeal with configuration errorsforce buildsenable and control the IRC botenable ssh debuggingadd a ‘try’ scheduler 1.3.2. Let’s start simple by looking at where you would customize the buildbot’s project name and URL. We continue where we left off in the First Run tutorial. Open a new terminal, and first enter the same sandbox you created before (where $EDITOR is your editor of choice like vim, gedit, or emacs): cd ~/tmp/bb-master source sandbox/bin/activate $EDITOR master/master.cfg Now, look for the section marked PROJECT IDENTITY which reads: After making a change go into the terminal and type: 1.3.3. This creates a Python SyntaxError. 1.3.4. Note
10 bad habits to break if you want to become a great developer Pursuing a career as a developer is a wise choice: The US Bureau of Labor and Statistics predicts software developer jobs will grow 17% between 2014 and 2024—much faster than the average rate of other professions. Meanwhile, front end developers, full stack developers, mobile developers, and back end developers are all currently in the top 10 hardest to fill tech jobs, according to data from job search site Indeed.com. However, a number of common mistakes arise for those who are new to the field that could make your entry to a successful career more difficult. 1. This is "the worst thing a developer can do," according to Karen Panetta, IEEE fellow and associate dean of the school of engineering at Tufts University. Further, many customers do not know the details of how something should work. SEE: How to become a developer: 7 tips from the pros 2. It's incorrect for developers to assume that "if the software compiles, it works," Panetta said. 3. 4. 5. 6. 7. 8. 9. 10. Also see
Continuous Integration - Full Stack Python Continuous integration automates the building, testing and deploying of applications. Software projects, whether created by a single individual or entire teams, typically use continuous integration as a hub to ensure important steps such as unit testing are automated rather than manual processes. Why is continuous integration important? When continuous integration (CI) is established as a step in a software project's development process it can dramatically reduce deployment times by minimizing steps that require human intervention. Automated testing Another major advantage with CI is that testing can be an automated step in the deployment process. The automated testing on checked in source code can be thought of like the bumper guards in bowling that prevent code quality from going too far off track. Continuous integration example The following picture represents a high level perspective on how continuous integration and deployment can work. Open source CI projects Jenkins CI resources
1. Getting Started — Python Developer's Guide CPython provides several compilation flags which help with debugging various things. While all of the known flags can be found in the Misc/SpecialBuilds.txt file, the most critical one is the Py_DEBUG flag which creates what is known as a “pydebug” build. This flag turns on various extra sanity checks which help catch common issues. The use of the flag is so common that turning on the flag is a basic compile option. You should always develop under a pydebug build of CPython (the only instance of when you shouldn’t is if you are taking performance measurements). Even when working only on pure Python code the pydebug build provides several useful checks that one should not skip. 1.1.3.1. The core CPython interpreter only needs a C compiler to be built; if you get compile errors with a C89 or C99-compliant compiler, please open a bug report. For UNIX based systems, we try to use system libraries whenever available. On Fedora, Red Hat Enterprise Linux and other yum based systems: and make: .
What's in a transport layer? Microservices are small programs, each with a specific and narrow scope, that are glued together to produce what appears from the outside to be one coherent web application. This architectural style is used in contrast with a traditional "monolith" where every component and sub-routine of the application is bundled into one codebase and not separated by a network boundary. In recent years microservices have enjoyed increased popularity, concurrent with (but not necessarily requiring the use of) enabling new technologies such as Amazon Web Services and Docker. In this article, we will take a look at the "what" and "why" of microservices and at gRPC, an open source framework released by Google, which is a tool organizations are increasingly reaching for in their migration towards microservices. Why Use Microservices? To understand the general history and structure of microservices emerging as an architectural pattern, this Martin Fowler article is a good and fairly comprehensive read.
Developer’s Guide — Python Developer's Guide This guide is a comprehensive resource for contributing to Python – for both new and experienced contributors. It is maintained by the same community that maintains Python. We welcome your contributions to Python! Quick Reference Here are the basic steps needed to get set up and contribute a patch. Install and set up Git and other dependencies (see the Get Setup page for detailed information).Fork the CPython repository to your GitHub account and get the source code using:git clone Python, on UNIX and Mac OS use:. Note First time contributors will need to sign the Contributor Licensing Agreement (CLA) as described in the Licensing section of this guide. Status of Python branches (1) The exact date of Python 2.7 end-of-life has not been decided yet. Status: Dates in italic are scheduled and can be adjusted. By default, the end-of-life is scheduled 5 years after the first release. See also Security branches. Proposing changes to Python itself
The evolution of data center networks I asked Dinesh Dutt, chief scientist at Cumulus Networks and author of BGP in the Datacenter, to discuss how data centers have changed in recent years, new tools and techniques for network engineers, and what the future may hold for data center networking. Here are some highlights. How have data centers evolved over the past few years? Modern data centers have come a long way from when I first began working on them in 2007. Pioneers such as Google and Amazon started a trend that many others now try to emulate. First, more people are embracing the Clos network topology and routing as the fundamental rubric of the modern data center. Second, automation is more ubiquitously embraced as a mandatory requirement rather than a nice to have. Third, disaggregated solutions or white box switching, where the hardware and software are acquired separately from different vendors, is steadily gaining ground. What are some of the traditional approaches to troubleshooting networks?
What is Python and Why Python What is Python? Python is an agile programming language. There, I said it, so now everyone can stop using terms like scripting and interpreted or high-level that either have negative connotations or don't really get across why Python is so great. Just say Python is an agile programming language. Ward Cunningham and I came up with the idea of calling Python an agile language during an evening get-together on March 14th, 2003 with Brian Ingerson. Here's the working list for what I'm calling agile programming languages. excellent for beginners, yet superb for experts highly scalable, suitable for large projects as well as small ones rapid development portable, cross-platform embeddable easily extensible object-oriented you can get the job done simple yet elegant stable and mature powerful standard libs wealth of 3rd party packages And don't forget that with Python, programming is fun again! Why Python? Eric Raymond explains Why Python?
The Microcontainer Manifesto and the Right Tool for the Job | Oracle Developers Blog Containers have grown dramatically in popularity over the last few years. They have been used to replace both package managers and config management. Unfortunately, while the standard build process for containers is ideal for developers, but the resulting container images make operators' jobs more difficult. Related content While building cloud services here at Oracle, we identified a number of services that could benefit from containers, but we ensure their stability and security. Problems Resulting from Docker Build Many of the problems arise from the practice of putting an entire linux into the container image. 1. The standard method for building images for the longest time started with `FROM debian/jesse`, which resulted in large images that necessitated layers just to be manageable. 2. The practice of putting an entire linux user space into the application deployment artifact means that a compromise of the application gives other potential avenues of attack for privilege escalation.