| Morning | |||
| 08:20 | Check-in | ||
| 09:00 | Opening | ||
| 09:10 |
The practical guide to use of ACE in python environment and architecture design slides |
戒空(姜继忠) | ... |
| 09:40 |
base Python build DaoCloud slides video |
颜开 | What is DaoCloud? Why we use python to build it? DaoCloud s Python technology stack. How to use various Python technologies API Celery Docker Client Docker Compose Python helps DaoCloud do rapid iterations |
| 10:25 |
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 |
| 11:10 | Intermission | ||
| 11:20 |
Let's talk about something fun slides |
沈崴 | ... |
| 11:35 |
? slides |
孔令开 | ... |
| 12:05 |
Facebook and Python slides |
Jianming Wu (吴建明) | ... |
| Noon | |||
| 12:10 | Lunch + Photo | ||
| Afternoon | |||
| 13:30 |
用 jieba 处理中文以及台湾的 Py 社团 slides presentations |
亮亮 | Share some experiences in using Pinkoi. How to use jieba, and how to improve the Elasticsearch user experiences when searching for Chinese commodities, how to find correlation between commodities using word2vec, how to do recommendation. Introduce the Python communities in Taiwan. |
| 14:00 |
Let python software be lightning fast slides |
刘国强 (Bruce Liu) | the practical guide to python performance tuning... |
| 14:30 |
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 |
| 15:00 |
Python&GUI slides |
陈海波 | basic introduction to Python&GUI Why GUI Different technology paths to choose from Compilation and packaging on different platforms How to draw interface? The imagination powered by GUI How to make your first desktop software? |
| 15:30 | Intermission | ||
| 15:40 |
A way to execute code remotely slides |
许智翔(shell909090) | short 10 mins speech, introducing a tip to execute any code remotely |
| 16:15 |
the toolbox for data of python slides |
肖凯 | introduction to the new data analysis tools in the python community, including numpy/scipy/pandas/sklearn/theano and etc, their positions in the data processing workflow, and comparison to other tools |
| 16:35 |
TheConsortium: a state based automation tool for data center management slides |
徐洲 | TheConsortium is a configuration management tool built on top of tornado, etcd and arangodb. Its plugins can interact with the backend of the data centers, such as database, switchers, balancers and puppet, providing a unified entry point for managing various components in a data center. |
| 17:00 |
Graphic Python -- quick construction of robotic system slides |
王立奇 | 1. Flagship of product; Python robot NAO, toolkit based on NI LabVIEW 2. Python modules used by LabVIEW, how to write robotic apps 3. How to add python modules to the toolkit |
| Lighting Talks | |||
| 17:20 |
py + gi - efficient C library integration slides |
Derek 呆 | Normally to use c libraries in Python, you need to do a binding and let python runtime communicate with target C libraries. This approach is error-prone and hard for maintenance. By using gobject introspection together with type information, we can optimize the power of Python + C! |
| 17:30 |
Build data storage with Luiti slides |
陈大伟 | When the magnitude of data is large enough that you need to use Hadoop, a easy to use and efficient offline task management framework become necessary. Luiti started from this demand. It is based on Luigi module open sourced from Spotify, and it can be used like Flask or RoR frameworks to build up data storage quickly. Please visit http://luiti.github.io/index.html |
| 17:40 | Intermission | ||
| Canceled Talks | |||
| (ー`´ー) |
... |
Pythoneer | ... |