Although I have more than 8-year programming experience, I first write Python code only a year ago. However, despite the really short-term experience, now Python is definitely one of my most favorite programming languages. I use Python in many different purposes such as research, private projects, part-time job, and competitive programming.
My usage scenes of Python is really wide-ranging, right? Actually, the theme of PyCon JP 2015 was Possibilities of Python, and everyone agrees with its possibilities. Also, the conference schedule clearly illustrates possibilities of Python; we can see a wide variety of talks: hardware-related (robotics, FPGA), web development, data science and machine learning.
Due to too much conference contents, summarizing them one-by-one is hard for me. So, I just list some GitHub repositories based on my stars during the conference:
- getsentry / sentry
- Keynote talk focused on Python technologies around error/crash reporting.
- Highly practical and interesting keynote.
- JukkaL / mypy
- python / typeshed
- Talk about Python 3.x and type hints (from 3.5).
- I still use Python 2.7, but this talk made me want to use 3.x.
- google / protobuf
- grpc / grpc
- Talk about gRPC and Kubernetes by Googler.
- Good introduction to modern infrastructure, including concepts of containers.
- mocobeta / janome
- Japanese morphological analyzer in Python.
- Easy to follow the talk about how Japanese morphological analyzer works.
- renyuanL / pythonTurtleInChinese
- Translate Python code into Chinese like for i in 範囲(100): ("範囲" means "range" in English)
- Thought-provoking talk on programming education.
- c-bata / pandas-validator
- blaze / dask
- fabric / fabric
- mitsuhiko / click
- airtoxin / pysqldf
Of course, there were many other interesting talks. In particular, presentations about tweet analysis, semantic web, pandas internals and ad science were good because these topics were very close to my current interests.
Since I am working on data science and machine learning research, one of the most impressive things is that several talks mentioned pandas, Python data analysis library. I have realized how pandas (and IPython notebooks) are important tools for data scientists.
PyCon JP 2015 was really stimulating, and this was great opportunity to see possibilities of Python. I like to learn more about Python and use this language and related tools more effectively. And, importantly, I will use Python 3.x starting today :)
Support (Thank you!)
- Apache Hivemall in PySpark
- Feeding User-Item Interactions to Python-Based Streaming Recommendation Engine via Faust
- Apache Hivemall at #ODSCEurope, #RecSys2018, and #MbedConnect
Author: Takuya Kitazawa
Takuya Kitazawa is a product developer, minimalistic traveler, ultralight hiker & runner, and craft beer enthusiast. Throughout my career, I have practically worked as a full-stack software engineer, OSS developer, technical evangelist, sales engineer, data scientist, machine learning engineer, and product manager. See my "now" page for more about what I am doing lately.
Opinions are my own and do not represent the views of organizations I am/was belonging to.