Analysis of Ethereum Python source code

1. 1. In other words, if there is no certain foundation, and clear their own purpose. You are God, spend an hour to read the source code, it is meaningless. 2. Just like if you just memorize words and read the word list, but don't understand the meaning, it's also worthless. 3. You should know what you want to do. And then to find the right way is the normal way to solve the problem. 4. To answer your question alone is: from a few days, to a few months, or a few years, the specific number of days depends on what your own Python foundation wants to achieve. For example, if you are not familiar with Python, it may take several years for some people to fully understand the source code. Of course, if you read the python source code as a word, just take a look, that's another way to say. For Python is very familiar with, just need to quickly see how to achieve various functions, find the corresponding interface, study the corresponding implementation mechanism. The length of time is also different.

2.

The main features of this book are as follows:
a book that deeply analyzes the specific implementation of Python
the content is fresh, and uses the latest Python language version (25)
a large number of diagrams to vividly show the internal operation mechanism of Python
while introcing the principles, it leads readers to transform the python virtual machine
completely covering all the core topics of Python, Deeply reveal how Python and C / C + + interact

3. 1. In other words, if there is no certain foundation, and clear their own purpose
you are a god man. It is meaningless to spend an hour reading the source code
2. Just like if you just memorize words and read the word list, but don't understand the meaning, it's also worthless
3. You should be clear about what you want to do. And then to find the right way is the normal way to solve the problem
4. To answer your question alone is:
from a few days, to a few months, or a few years, the specific number of days depends on:
your own Python foundation
what you want to achieve

for example, if you are not familiar with Python, some people may need several years to fully understand the source code
of course, if you just take a look at the python source code as a word reading, that's another way to say

for those familiar with Python, you just need to quickly see how various functions are implemented, find the corresponding interface, and study the corresponding implementation mechanism. The length of time is also different.

4. browser = webdriver.Chrome(executable_ path=chrome_ Path) browser. Get (URL) ා this is the content of element in Chrome browser browser. Find_ elements_ by_ tag_ name(' td') # Get the content under TD in element!

5. You can download its source code from the official website of Python
https://www.python.org/downloads/source/

6. First of all, you need to find the location of the source code. You can use the following method: if you can run Python on the command line, you can use the following command to view the directory& gt;& gt;& gt; import string>& gt;& gt; string.__ file__&# 39;/ usr/lib/python2.7/string.pyc'& gt;& gt;& gt; String. Py in the corresponding directory is the source code of package, but some

7. Because Python is open source, it can be downloaded to the source code.

8. You can learn how Python calls the WebKit engine. What you said is not to encrypt with JS, but to dynamically load the page content with JS. You have to use a browser engine like WebKit to render.

9.

Chapter 0 Python source code analysis -- compiling Python
0.1 Python overall architecture
0.2 Python source code organization
0.3 Python compiled in Windows
0.4 Python compiled in UNIX / Linux
0.5 Python source code modification
0.6 path to Python
0.7 some notes
Part 1 Python built-in object
Chapter 1 Python object preliminary exploration
1.1 p Objects in ython
1.1.1 the cornerstone of object mechanism pyobject
1.1.2 fixed length objects and variable length objects
1.2 type objects
1.2.1 object creation
1.2.2 object behavior
1.2.3 type types
1.3 polymorphism of Python objects
1.4 reference count
1.5 classification of Python objects
Chapter 2 integer objects in Python
2.1 initial recognition of PY Object object
2.2 creation and maintenance of pyobject object
2.2.1 three ways of object creation
2.2.2 small integer object
2.2.3 large integer object
2.2.4 add and delete
2.2.5 initialization of small integer object pool
2.3 hack pyobject
Chapter 3 string object in Python
3.1 pystringobject and pystring object_ Type
3.2 create the pstringobject
3.3 inter mechanism of string object
3.4 character buffer pool
3.5 efficiency related problems of pstringobject
3.6 hack pstringobject
list object in Python Chapter 4
4.1 pylistobject object
4.2 pylistobject creation and maintenance
4.2.1 create object
4.2.2 set element
4.2.3 Enter element
4.2.4 delete element
4.3 pylistobject object buffer pool
4.4 hack pylistobject
dict object in Python in Chapter 5
5.1 hash table overview
5.2 pyditobject
5.2.1 entry of associated container
5.2.2 implementation of associated container
5.3 creation and maintenance of pyditobject
5.3.1 pyditobject creation
5.3.2 pyditobject Element search
5.3.3 insert and delete
5.3.4 operation example
5.4 pydictobjet object buffer pool
5.5 hack pydictobjet
Chapter 6 the simplest Python simulation - small Python
6.1 small Python
6.2 object mechanism
6.3 explanation process
6.4 interactive environment
Part 2 Python virtual machine
Chapter 7 Python compilation results - cod E object and PyC file
7.1 Python program execution process
7.2 Python compiler compilation results pycodeobject object
7.2.1 pycodeobject and PyC file
7.2.2 pycodeobject in Python source code
7.2.3 PyC file
7.2.4 accessing pycodeobject in Python
7.3 PyC file generation
7.3.1 specific process of creating PyC file
7.3 2 write a pycodeobject to PyC file
7.3.3, Multiple pycodeobjects
7.4 bytecodes of Python
7.5 parsing PyC files
Chapter 8 Python virtual machine framework
execution environment in 8.1 Python virtual machine
pyframeobject in 8.1.1 Python source code
dynamic memory space in 8.1.2 pyframeobject
8.1.3 accessing pyframeobject in Python
8.2 name Scope and namespace
8.2.1 basic structure of Python program: Mole
8.2.2 constraints and namespace
8.2.3 scope and namespace
8.3 running framework of Python virtual machine
8.4 exploration of Python runtime environment 9.3 other general expressions
9.3.1 symbol search
9.3.2 numerical operation
9.3.3 information output
Chapter 10 control flow in Python virtual machine
10.1 if control flow in Python virtual machine
10.1.1 research object -- if_ Control. Py
10.1.2 comparison operation
10.1.3 instruction jump
10.2 for loop control flow in Python virtual machine
10.2.1 research object for_ Control. Py
10.2.2 initialization of loop control structure
10.2.3 iterative control
10.2.4 termination of iteration
10.3 while loop control structure in Python virtual machine
10.3.1 research object - while_ Control. Py
10.3.2 loop termination
10.3.3 loop normal operation
10.3.4 loop process change instruction continue
10.3.5 loop process change instruction break
10.4 exception control flow in Python virtual machine
10.4.1 exception mechanism in Python
10.4.2 exception control semantic structure in Python
Chapter 11 function mechanism in Python virtual machine
11.1 pyfunctionobject object
11.2 nonparametric function call
11.2.1 function object creation
11.2.2 function call
11.3 function execution namespace
11.4 function parameter implementation
11.4.1 parameter category
11.4.2 positional parameter transfer
11.4.3 positional parameter access
11.4.4 default value of positional parameter
11.4.5 extended positional parameter And extended key parameter
11.5 function local variable access
11.6 nested function Closure and decorator
11.6.1 the cornerstone of closure implementation
11.6.2 closure implementation
11.6.3 decorator
Chapter 12 class mechanism in Python virtual machine
12.1 object model in Python
12.1.1 relationship between objects
12.1.2 and
12.2 from type object to class object
12.2.1 processing base class and type information
12.2.2 processing base class list
12.2.3 Filling TP_ Dict
12.3 user defined class
12.3.1 create class object
12.4 from class object to instance object
12.5 access attributes in instance object
12.5.1 instance object__ dict__
12.5.2 on descriptors
12.5.3 function transformation
12.5.4 call of nonparametric function
12.5.5 call of parametric function
12.5.6 bound method and unbound method
12.6 ever-changing descriptors
Part 3 Python advanced topics
Chapter 13 Python runtime environment initialization
13.1 thread environment initialization
13.1.1 thread model Review
13.1 . 2 initialize thread environment
13.2 initialize system mole
13.2.1 create__ builtin__ Mole
13.2.2 create sys mole
13.2.3 create__ main__ Mole
13.2.4 set the search path of site-specific mole
13.3 activate Python virtual machine
13.3.1 interactive operation mode
13.3.2 script file operation mode
13.3.3 start virtual machine
13.3.4 namespace
Chapter 14 dynamic loading mechanism of Python mole
14.1 import Prelude
14.2 black box detection of import mechanism in Python
14.2.1 Standard import
14.2.2 nested import
14.2.3 import package
14.2.4 from and import
14.2.5 symbol renaming
14.2.6 symbol destruction and overloading
14.3 implementation of import mechanism
14.3.1 parsing the tree structure of mole / package
14.3.2 loading mole / pakcage
14.3.3 from and import
14.4 import operation in Python
14.4.1 import mole < br />14.4.2 import package
14.4.3 from & import
14.4.4 import & As
14.4.5 reload
14.4.6 built in mole: imp
14.5 mole related namespace problems
Chapter 15 Python multithreading mechanism
15.1 Gil and thread scheling
15.2 see Python thread
15.3 Python thread creation
15.3.1 multithreading environment
15.3.2 thread creation
15.4 Python thread scheling
15.4.1 standard scheling
15 4.2 blocking scheling
15.5 destruction of Python sub threads
15.6 user level mutex and synchronization of Python threads
15.6.1 user level mutex and synchronization
15.6.2 lock object
15.7 advanced thread library overview of thread
15.7.1 threading mole
thread synchronization tool of 15.7.2 threading
thread in 15.7.3 threading
Chapter 16 memory management of Python Mechanism
16.1 memory management architecture
16.2 small memory pool
16.2.1 block
16.2.2 pool
16.2.3 arena
16.2.4 memory pool
16.3 circular reference garbage collection
16.3.1 reference count and garbage collection
16.3.2 three color mark model
16.4 garbage collection in Python
16.4.1 collectable object list
16.4.2 generation garbage collection Garbage collection
16.4.3 mark clear method in Python
16.4.4 garbage collection panorama
16.4.5 GC mole in Python
16.4.6 summary

10. Python encourages open source, and it's OK to encrypt. For example, you can package win desktop software into exe. But now most of the software is based on BS, customers only see the data display, which is often said to be the front end. Logic is handled in the service, and users can't see it.