| Morning | |||
| 08:30 | Check-in | ||
| 09:00 | Opening | ||
| 09:10 |
from virtualenv to Docker slides |
颜开 | The dependence hell of python The problems caused by dependence description Virtualenv as the current de facto standard, can help to a degree, but also cause other issues Other solutions, comparison Docker as a solution How to use Docker to resolve the dependence problems The mechanism of Docker, why it can solve the problems Other values that Docker brings to Python. Easier deployment, easier integration with third party packages, easier to use CPython, PyPy, Jpython. |
| 09:35 |
Flask app development with web IDE slides |
吴柯 | Flask becomes popular as a light-weight web framework. What are its pros and cons? The concept of web IDE, the issues of light-weight development. Introduce WebIDE from coding, how to use WebIDE to write a light-weight web app, how to deploy. |
| 09:55 |
? slides |
陈博 | ... |
| 10:30 | Intermission | ||
| 10:40 |
Industry analysis of python programmers as a profession based on Liepin's big data slides |
石晶+单艺 | 0. The technology and mathematical methods used in our data analysis for professional development 1. Distribution of professionals： the distribution of pythoners in different industries, geographies, and positions 2. Needs of enterprises： the demand of pythoners in the job market and how it changes 3. Professional development： the analysis of the career path of pythoners, how they move in different industries 4. Salary levels： the different salary levels of pythoners in different industries, geographies, positions, and age groups 5. Portrait of python professionals： the age, education background, majors of pythoners and the relation with positions and salary levels |
| 11:00 |
Effective python functional programming: techniques, tools and practices slides video |
丁来强 | Different from Object Oriented Programming, functional programming wins public attention by low side effect, high reusability, and easy to use. Python, although not a pure functional programming language, provides powerful support to do functional programming. This speech covers how the key features of functional programming is implemented in Python. It will touch on core grammar of Python(function, lambda, generator, iterator, decorator and so on) and standard library(functools, operators, itertools) , the core concepts in functional programming (pure function, persistent data, high order function, currying, TCO, trampoline, overloading, pattern matching, laziness streaming), tools (multipledispatch, pyrsistent, fn, PyToolz, ipython cluster, python-parallel), concurrent programming, and effective functional programming. |
| 11:30 |
Dive into Sentry slides |
徐涛 | Share some experiences of using Sentry. How Sentry is used in Douban, and Sentry migration, the internal mechanism of Sentry, and some complaints. |
| 12:00 |
Facebook and Python slides |
Rosie Li (李若思) | ... |
| Noon | |||
| 12:10 | Lunch + Photo | ||
| Afternoon | |||
| 13:00 |
Python Rules Hadoop slides |
阳曙光+苏铖 | How to resolve dependence, timing, and retries after failure in the big data task processing? The three open source scheduling system oozie, azkaban、luigi all have its pros and cons. But their main target is the developers, thus can be hard for non-developers. Using Python, we developed a visual, light-weight and easy to use big data task management system that can be used by analysts. |
| 13:30 |
pidl: python-powered microservices at Douban |
Guillaume Bouriez | Pythonic Interface Description Language。Moving to a microservice architecture solves many issues, but it is hard.Pidl, our in-house interface layer, allows to isolate services with only minimal changes in client and service code. A pidl service efficiently exports fully functional python modules, with functions, classes and methods. For the user, it is pure magic: the service is used as a normal python module but its code is never imported! |
| 14:00 |
The unit testing scenarios in python projects slides |
郑堃 | The various scenarios of unit testing in python projects, such as/ 1. Hello World examples 2. testing frameworks used in web frameworks such as Django 3. mocking network request, file read/write, database 4. other Mock or Fake 5. tools and libraries |
| 14:30 |
How to program secure software in python slides |
廖新喜 | Mainly touch on python secure programming, such as xss Command injection (the causes, and how to filter them), sql injection How code gets executed (eval，pickle.loads), how to avoid it, the security loophole caused by wrong wrap up of eval, file manipulation |
| 15:00 | Intermission | ||
| 15:10 |
The mechanism of python modules and best practices slides |
刘畅 | Life is short, I use Python. Two pains in the neck while using python, one is the encoding, the other importing. It will cover the mechanism of python's modules management, PYTHONPATH, sys.path, why py3 discard the import mechanism of py2, what is absolute import in py3, the best practice of python project directories. |
| 15:40 |
Python make more people fall in love with programming slides |
林攀 | How to let children get interested in programming? Python is the best choice! Python, as a dynamic language, is more suited for beginners. Python can help beginners focusing on the domain logics instead of getting distracted by grammar and types. It might be personal taste as which language is more elegant, but there is no much dispute that Python is the most easy to read language. |
| 16:10 |
... slides |
汪尊 | ... |
| 16:40 |
Big data analysis and visualization with Python slides video |
丁来强 | in big data processing, 70% of the time we are doing data preparation (loading/extraction/cleansing/conversion/classification/integration). After business analysis, a lot of time is needed to do data visualization. It will talk about how to do data ETL with Pandas, the new feature of Pandas(Query/removing of GIL), how to do data visualization with BokeH, how to use Blaze and Spark to do large scale distributed data processing |
| Lighting Talks | |||
| 17:10 |
How to program effectively slides |
王志利 | After writing a big program, you find it running very slowly. It is hard to locate where it gets wrong. How to solve this problem? |
| 17:20 |
How to do rapid android app development with QPython slides |
曲池峰 | using the PyConChina2015 app as an example, introduce how to use QPython to develop android APK The design of Android WebApp The introduction of QPython and WebApp QPython WeChat account/qpython |
| 17:40 |
The application of Python in mobile social platforms slides |
衷文闻 | touch on the following/ 1. mobile social platform and its architecture (brief introduction) 1) the architecture of the platform (internationalization) 2) components 2. the use of Python and its libraries in the platform 1) use of Python (pros and cons) 2) related libraries (PIL and etc.) 3) experience sharing |
| 17:45 |
Python and network sniffing slides |
余占勇 | Normally network sniffing uses tcpdump, wireshark. It is not convenient for real time analysis, and cannot modify the content of the package, and limited to http packages. Python can solve these. |
| 17:50 |
Auto deployment based on Fabric slides |
黄鑫 | Introduce the application of Fabric in enterprises. Regular task automation, interaction with shell, working with multiple source code repository, Jenkins and proxy, checking after deployment, spreadsheet report and structured data for analysis |
| Canceled Talks | |||
| (ー`´ー) |
Python and smart devices |
杜军 | We wrote most logics of lapsule in Python, including sso/api/portal and integration with node.js. Lapsule is a cloud based service that is used by smart speakers, such as content integration, OTA, statistics, support for mobile app development. We provide hardware core modules, cloud based content, app customization, in-house engineer support, turnkey solutions. |