Day 2, R3 10:30–11:00
Networks in your infrastructure set the foundation for how your application can be deployed, maintained, and serviced. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In this talk, we'll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks.
Code examples, further recourses, and latest trends will be provided for audience with different level of needs depends on the scope of their network.
Slides: https://speakerdeck.com/ericchou/network-automation-with-python
Speaker: Eric Chou
Eric Chou is a seasoned technologist with over 20 years of experience. He is an ex-Amazonian, ex-Microsoftee, and other Fortune 500 companies. Eric is the author of the best selling "Mastering Python Networking" (by Packt Publishing) and a few other books. He shares his deep interest in technology through his books, classes, and blog. Eric is passionate about network automation, Python, and helping companies build better security postures.
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https://www.youtube.com/watch?v=cdJP1q8iUOU
Speaker: Jiwon Seo
Python becomes increasingly popular in the domain of big data analysis. Many big data frameworks such as Hadoop now support Python to some extent. PySociaLite is a new big data framework developed at Stanford. It is designed from beginning to be fully integrated into Python. In PySociaLite, SQL-like queries (called SociaLite) are directly embedded within Python code; the queries can access Python variables and functions, so there is full inter-operation between SociaLite and Python.
In this talk, I will give a brief overview of SociaLite, then mainly present the techniques for the integration of SociaLite into Python. SociaLite builds on top of well-known programming concepts -- tables and relational operations -- and it allows users to declare distributed tables to perform, for example, distributed join operations. For the integration of SociaLite into Python, we basically extend Jython interpreter to process embedded SociaLite queries. More specificaly, we use PyParsing to recognize SociaLite queries and re-write the queries into Java function calls. We also use lesser-known Python features, such as import hooks to process SociaLite queries within imported modules. To access Python functions within SociaLite, Jython interpreter instance (from which SociaLite queries are executed) is passed to SociaLite runtime system, and used to lookup and access Python functions. For the distributed execution, Python functions are serialized (as well as its PyCode object) and copied to cluster machines.
Time permitting, I will give a demo of PySociaLite; SociaLite queries will be executed interactively within (extended) Jython shell and demonstrate the inter-operation between SociaLite and Python.
About the speaker
Jiwon Seo is a PhD student in Stanford university, studying parallel query language for data analysis. He contributed to Python in various ways; for example, he implemented PEP 289 (Generator Expressions) and PEP 3102 (Keyword-Only Arguments).
He designed and implemented a parallel and distributed query language, called SociaLite. The SociaLite compiler generates efficient parallel/distributed code from user queries. SociaLite queries can be embedded in Python programs, allowing users to enjoy flexibility of Python and efficiency of SociaLite. More information is in http://seojiwon.github.io/socialite/
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https://www.youtube.com/watch?v=wxlq0HkE3zw
Speaker: Liang Bo Wang
Statistics is essential to data analysis, and many people choose R because of its great package diversity. With the advent of pandas, Python becomes one of the hottest language to do data analysis, and it will be more helpful if we can do statistics in Python as well.
In this talk, I will first introduce how to do statistics in Python using statsmodel and some related functions implemented in Numpy and Scipy.
Then I will introduces the communication from Python to R using rpy2, and give you advices or alternatives about when to use this approach or not.
About the speaker
呆呆電雞生,喜歡寫 R / Python,喜歡統計與生物資訊。目前為 Taiwan R Users Group 工作人員及 Taipei.py 常客。
Bioinfo / Stat / R / Python, master student of NTU BEBI. Co-organizer of Taiwan R Users Group and freq attendee of Taipei.py.
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https://www.youtube.com/watch?v=YzVvZ9HPrn8
Day 1, R0 14:50–15:35
Data For Social Good (D4SG)是從2015年發起的一個用資料做公益的計畫,協助了超過30個NGO及公部門單位,並獲得總統府黑客松前五強,及聯發科的「智在家鄉」第一名等殊榮。在30多個專案中涵蓋影像辨識、文字探勘及資料分析,Python是常用的程式語言之一。本次Talk將分享給Python初學者在哪些情境可以如何做資料分析、機器學習來解決社會人文相關題目。
Slides not uploaded by the speaker.
Speaker: Ning Chen
NA
Speaker: Andrew Li
I am currently working as a Data Engineer and Data Analyst, besides I am a cross-domain engineer.
I had experienced in various domains, such as genetic engineering, metabolic engineering, fermentation engineering, process engineering, solvent recycling engineering, composite materials engineering, and full stack developer.
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https://www.youtube.com/watch?v=GO-UF8zjBfc
Day 1, 13:05-13:35
Abstract
Cyber forensics is a field that deals with the investigation of digital crimes by analyzing, examining, identifying, and recovering digital evidence from electronic devices and producing them in the court of law. The talk begins with an introduction to digital forensics, the process of investigation, and the collection of evidence. Next, I will cover the various python modules and built-in functions required to build your first cyber forensic application. The modules covered in the discussion are pyscreenshot, Whoosh, PIL, hashlib, mutagen, pyPDF2, and pefile. Finally, I will demonstrate creating small cyber forensic applications using bulit-in modules and functions that are already to known to most of the Python programmers.
Slides not uploaded by the speaker.
HackMD: https://hackmd.io/@pycontw/2021/%2F%40pycontw%2FByfYqeKGt
Speaker: Gajendra Deshpande
Mr. Gajendra Deshpande holds a masters degree in Computer Science and Engineering and working as Assistant Professor at the Department of Computer Science and Engineering, KLS Gogte Institute of Technology, Belagavi, Karnataka, India. He has a teaching experience of 12 years and a Linux and Network Administration experience of one year. Under his mentor-ship teams have won Smart India Hackathon 2018 and Smart India Hackathon 2019. He is the Technical Director for Sestoauto Networks Pvt. Ltd. and Founder of Thingsvalley. His areas of Interest include Programming, Web Designing, Cyber Security, Artificial Intelligence, Machine Learning, Brain-Computer Interface, Internet of Things, and Virtual Reality. He has presented papers at NIT Goa, Scipy India 2017 IIT Bombay, JuliaCon 2018 London, Scipy India 2018 IIT Bombay, Scipy 2019 USA, and PyCon FR 2019, Bordeaux, France.
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https://www.youtube.com/watch?v=nQWOwItvlDo