[Chennaipy] ChennaiPy - 25-04-2020

[selvi dct]

Hi,

Please find the MIM.

Start by the - Vijay

Rangaraj : 15:20 - 15:33
-------------------------
Newbies to the python.
Notes :
- Python is an interpreter language
- Interpreter executes line by line
Problem :
- Rolling the dice to get random numbers
- Using import random module, to generate random numbers
- Complexity here is have more dices and many faces for dice
- To resolve this we can using list to hold faces for the dice
- To select only the faces in the list, we can use the function from random
is random.choice() giving the list as argument.
- Use print to check the selection
- To give wait period for the program to print the output, using import
time module.
Function: time.sleep(1) # here it will sleep for 1 sec
- Represent the output in traditional dice way using the below:
chr(rolled_value)  # convert the integer into unicode value, make sure to
have unicode value to be saved in the dice to show the values in dice format
# suggestion : range(9856, 9856+6) to save the
- Reference : https://en.wikipedia.org/wiki/Dice



Dr M.Muralidharan : 15:35 - 15:51
----------------------------------
Multithreading in Python
Notes :
- Python is involed in most of applications.
- One of the most popular language
- In all the domains, we have the modules and packages
Multithreading :
- Process :
- is the program execution
- each process has its only own data struction called PCB
- heavy weight
- can have child process created using fork
- Thread :
- light weight
- sub set of the process
- all the threads can be run at the same time to increase the efficiency
- Modules available
- Thread - spawn, manage, sync threads # deprecated
- Threading - higher level, improved sync modules
- Queue
- Locking Mechanism
- Locking and releasing is used for syncronisation purpose
- Explained with examples for each Module listed above
- Advantages :
- better use of resources
- Disadvantages :
- complexity increases
- debug issues
- dead locks can occur
- sync is cpu and memory intense
- Applications :
- web servers and browsers
- games
- text editors and IDE



Jitin Joseph : 15:53 - 16:15
------------------------------
Webscraping in Python
Notes :
- is a technique to fetch data and information from websites
- extracting data from web pages
- web crawling can be achieved by webscraping
Scrapy :
- Usages :
- e-commerce price comparision
- machine learning
- Rules :
- its legal based on the usage
- needs to check the terms and conditions
- check robot.txt
- should not crawl at disruptive rate
- General Steps :
- get the url
- validate the rules
- write code to scarp the code
- Challenges :
- throttle limit
- authentication required
- ip ban
- broken html or bad code
- Tools :
- Beautiful soup 4
- Scrapy
- Example demoed
- Architecture diagram of scrapy
Questions :
- when a URL Prompt for Captcha, do they try to limit bot login ? and will
OCR can over come it ? # Ans : Need to check the rules
- does robot.txt applies to all websites ? # Ans : Yes most of the websites
will have it
- is there any other page or method to identify the dsiallowed url ? # Ans
: Only robots.txt



Narendra Sridharan : 16:15 - 16:30
-----------------------------------
Surprising fact of Programming in Python
Notes :
- Newbie encounter surprises about python
Jupyter :
- Using Jupyter from anaconda
- Export .pyinb into .py
- Export into ppt also
Surprises :
- syntatic sugars
- not brackets only indentation
- no semicolons
- for loops are completly different
- negative indexing
- no switch case
- multiple assignments
- functional programming - lambdas, genertors
- concurrent programming - co-routines
- async programming
- aspect object programming -
Questions :
- negative indexing
- for last part of the filenames from path
- os.path.basename() # get the basename
- a=[0,1,2,3,4]
 a[-1]=4



Vijay : 16:30 - 16:48
----------------------
Threads, Locking and The GIL
Notes :
- Deeper into the locking
- GIL
Demo :
- For Threads
- have two threads running to increment a variable
- changed from 100, 1000, 10000
- after 100000, the incrementer counter values gets corrupted
- Why
- less the < 10000 the values are not getting corrupted
- Dis-assemble
- did.dis(function)
- to details the assembly language code
- explaination of the assemble steps
- load the attr
- inplace_add
- store_attr
- Able to see the race conditions
- which is causing the corruptions
- To resolve this we can use Locks
- Lessons Learnt
- when using multi thread, we should use locks for value changes
- GIL
- As interpreter only one thread can be executed
- When thread relases the GIL :
- when the blocking system call is invoked
- when more than 10000 instructions
Questions :
- pre-empted is under control of OS
- dis is used to get python byte code generators



Abhishek Mishra : 16:48 - 17:00
--------------------------------
PyConIndia
- Open online this year 2020
- https://in.pycon.org/cfp/2020/proposals/
- Date : 2-5th October
- CFP - submit the talks
- https://pyconindia.zulipchat.com/login/ # suggestion and chat


Conclusion and Thanks by Vijay.

-- 
Regards,
Selvi....
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