Python의 가능성
삼성 SDS 개발자 Conference OpeniT 5회
대안언어 축제
두산중공업 Software센터
조 인 석
Contents
Speaker is..
Python?
Why Python?
Java vs Python
Data Science w/ Python
How can I learn Python?
How can I play w/ Python?
Q & A
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Table of Contents
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조 인 석 (Chris Cho)
• 세종대 컴퓨터 공학 전공
• 육군전산소 SW개발병 (2년)
• 현대정보기술 해외금융개발팀 (7개월)
• 삼성 SDS (7년 3개월)
– ENG. Methodology 팀 & SI Process 팀 (2년 1개월)
• 통합 개발 플랫폼 대내외 프로젝트 지원
– Framework 팀 & Delivery Platform 팀 (5년 2개월)
• 삼성생명 차세대 Anyframe Enterprise BTO 전담 지원 (2년)
• 삼성전자 Global MES 2.0 Anyframe Enterprise 전담 지원 (3년)
• 두산 중공업 (현, 1년 9개월)
– Software센터 SW 개발팀
• Power & Water plant를 위한 Industrial IoT 관련 SW 개발 담당
• 실무환경에 맞춘 Node.js 프로그래밍 공저 (2014, 혜지원)
• 파이썬 입문 집필 중 (예정, 2016, 혜지원)
• Facebook : https://www.facebook.com/insuk.chris.cho
Speaker is..
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Python?
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Why Python? (1/4)
2015 Programming Language Rankings by RedMonk
Reference: http://redmonk.com/sogrady/2015/01/14/language-rankings-1-15/
Popularity Rank on GitHub
Popula
rity
Rank o
n S
tack O
verf
low
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Why Python? (2/4)
Most Popular Coding Languages of 2015
The result is based on hundreds of thousands of data points we've collected by processing over 600,000+ coding tests and challenges by over 2,000+ employers
Reference: http://blog.codeeval.com/codeevalblog/2015#.VZDg-PntlBc
Why Python? (3/4)
You can find Python everywhere..
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Why Python? (4/4)
You can find Python everywhere..
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Java vs Python
Reference: http://www.javascriptstyle.com/java-vs-python
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Python IDE – Jupyter (iPython-notebook)
Using Web Browser
Explanation
(Comments)
Source Code
Execution Results
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Data volume is growing exponentially within companies. Most don't know how to harvest its value or how to even compute on it.
Growing mess of tools, databases, and products. New products increase integration headaches, instead of simplifying.
New hardware & architectures are tempting, but are avoided or sit idle because of software challenges.
Promises of the "Big Red Solve" button continue to disappoint. (If someone can give you this button, they are your competitor.)
Data Science w/ Python (1/5)
※ Slide : http://www.slideshare.net/misterwang/pydata-texas-2015-keynote※ 동영상 : https://www.youtube.com/watch?v=Pkwygl3cgmU
Data Science w/ Python (2/5)
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※ Slide : http://www.slideshare.net/misterwang/pydata-texas-2015-keynote※ 동영상 : https://www.youtube.com/watch?v=Pkwygl3cgmU
Data Science w/ Python (3/5)
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※ Slide : http://www.slideshare.net/misterwang/pydata-texas-2015-keynote※ 동영상 : https://www.youtube.com/watch?v=Pkwygl3cgmU
Data Science w/ Python (4/5)
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※ Slide : http://www.slideshare.net/misterwang/pydata-texas-2015-keynote※ 동영상 : https://www.youtube.com/watch?v=Pkwygl3cgmU
Data Science w/ Python (5/5)
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OpenOPC for Python (http://openopc.sourceforge.net/)- OpenOPC for Python is a free, open source OPC (OLE for Process Control) toolkit
designed for use with the popular Python programming language
MQTT Brocker - Mosquitto (http://mosquitto.org/)
- Mosquitto makes it suitable for "machine to machine" messaging such as with low power sensors or mobile devices such as phones, embedded computers or microcontrollers
MQTT Client – paho-mqtt (https://pypi.python.org/pypi/paho-mqtt)- This code provides a client class which enable applications to connect to an MQTT
broker to publish messages, and to subscribe to topics and receive published messages
NumPy (http://www.numpy.org/, http://en.wikipedia.org/wiki/NumPy)- an optimized python library for numerical analysis, specifically: large, multi-
dimensional arrays and matrices. Found in Introduction to Data Science Pandas (http://pandas.pydata.org/, http://en.wikipedia.org/wiki/Pandas_(software) )
- an optimized python library for data analysis including dataframes inspired by R. Found in Introduction to Data Science
SciKit-learn (http://scikit-learn.org/stable/, http://en.wikipedia.org/wiki/Scikit-learn)- machine learning library built on NumPy, SciPy, and matplotlib. Mentioned in
Introduction to Machine Learning H2O (http://h2o.ai/)
- H2O is for data scientists and application developers who need fast, in-memory scalable machine learning for smarter applications. H2O is an open source parallel processing engine for machine learning
Django (https://www.djangoproject.com/)- Django is a high-level Python Web framework that encourages rapid development
and clean, pragmatic design
Anaconda (http://continuum.io/downloads)- a python package manager with the intent of simplifying and maintaining compatibility
between library versions. Also useful for getting started with ipython notebooks
Data Gathering
Data Distribution
& Sharing
Data Learning
& Modeling
Visualization
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How can I learn Python? –www.edx.org
How can I learn Python? –www.microsoftvirtaulacademy.com
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How can I play w/ Python? –www.codecademy.com
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How can I play w/ Python? –www.hackerrank.com
Q & A