Jonathanliu92251.github.io

study memo

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Project maintained by Jonathanliu92251 Hosted on GitHub Pages — Theme by mattgraham

Date: 2018-05-18

chapter 1. General

data + processing.

data: basic data type, + data structure: - sequences: “fix-length”? collections of objects accessed by numeric position string, tuple, list
- mappings: access by key objects - sets. simple collections of unique objects with no additonal kind of access - exceptions. simple data objects & events that control the execution of programs statements( try, except, finally, raise), - files.

General Notes:

• Python is case sensitive
• Python makes use of indentation
• Filename only letters, digits and “_”, suffix “.py”
• Spaces are used sparingly in expressions.
• Spaces are never used between a function name and the ()’s that surround the arguments.

Print

print([object, …], [sep=’ ’], [end=’n’], [file=sys.stdout])

print( "This is an error message", file=sys.stderr )
- PDF w/ ReportLab
- Error mesage / logs, w/ logging library
- Debugging messages, w/ logging library

Questions

1 基本数据类型 ?
2 数据结构 ?

chapter 2. Data Type

Numeric Types and Operators

Integer: 32 bit-long, ± 2 billion
Binary, Octal and Hexadecimal: 0bnnn, 0nnn 0x Long Integers nnnL int(), long() Floating-Point Numbers 64 bit-long, double-precision: 6.25E-2 Complex Numbers nnnJ: (2+3j)*(4+5j)

Numeric Conversion:

• int(x)
• float(x)
• long(x)
• complex(real, image)

Built-in Math Functions:

• 绝对值 abs(n)
• 指数 pow(x,y,z) xy modulo z
• 取整 round(n, digits)
• 转为字符串 hex(n), oct(n), bin(n), str(obj), repr(obj)
• 字串转为整数 int(str, base)
• max(), min(), any(), all(), sum()

chapter 6. ADVANCED EXPRESSIONS

modules:

• import math
  • sin cos tan asin acos atan sinh cosh tanh
  • exp sqrt pow log hypot
  • pi e
  • ceil floor fabx fmod frexp
• import random
  • choice(seqs) random(max) rangerange((a,b), step)
  • randint([a,b]) uniform([a,b))

Bit Manipulation Operators

• ‘~’, ‘&’, ‘^’, ‘

  ’, ‘«’ and ‘»’.

Chapter 7. Variables

1. Naming:

• Names that begin with ‘_’ are typically private to a module or class.
• Names that begin with ‘__’ are part of the way the Python interpreter is built.
• In Python, every variable is a simple reference to an underlying object.

2. How to debug in MicrosoftCode ?

• Python Experimental
• F10 - StepOver

chapter 8 Truth and Logic

8.1 Truth and Logic

• Python represents truth and falsity in a variety of ways.
  • False. Also:
    • 0,
    • the special value None,
    • zero-length strings “”,
    • zero-length lists [],
    • zero-length tuples
    • (), empty mappings {} are all treated as False.
  • True. Anything else that is not equivalent to False.
  • bool(object)
  • operator: AND OR

8.2 Comparisons

- > < >= <= == !=

average = count != 0 and sum/count
if count ! =0 :
    average = count
else
    count = sum / count     Exact equality between floating-point numbers is a dangerous concept. abs(a-b)<0.0001

8.3 If - elif - else

if d1+d2 == 2 or d1+d2 == 12:
    print "field win" 
elif d1+d2==4 or d1+d2==9 or d1+d2==10 or d1+d2==11:
    print "field loses" 
else
    pass

average = sum/count if count != 0 else None

assert condition , expression

Chapter 9. Loop

for s in iterable :
    statements
    continue;
    break;

while expression:
    suite

Chapter 10. Functions

• argument, variable

    def functionName ( parameter<,....>):
    suite
    return [values]
  

• Default Values for Parameters

    def report( spin, count=1 ):
        suite
  

• Providing Argument Values by Keyword

    test1 = averageDice( samples=200 )
    test2 = averageDice( 300 )
  

• Returning Multiple Values

    def rollDice():
    return ( 1 + random.randrange(6), 1 + random.randrange(6) )  #tuple
  

• DocString & Help(obj)
  • ””” “””
• Ordinary / Procedure / Factory / Generator Functions
  • Python treats same for function and precedure
  • Call By Value and Call By Reference
  • The Python rules also mean that, in general, all variable updates must be done explicitly via an assignment statement. This makes variable changes perfectly clear.
• Command-Line Interaction / Script Mode / Hacking Mode
  • debug console
  • BUT how to F5

Chapter 12. SEQUENCES: STRINGS, TUPLES AND LISTS

• Sequence:
  • A sequence is a container of objects which are kept in a specific order.
  • We can identify the individual objects in a sequence by their position or index.
  • Positions are numbered from zero in Python;
  • “vector” or “array”, called in other programming lanaguage sometimes
• Type:
  • str: A container of single-byte ASCII , or multi-byte Unicode characters.
  • bytes. A container of binary data.
  • tuple. A container of anything, with a fixed number of elements.
  • list. A container of anything, with a dynamic number of elements. (mutable)
• Note:
  • there is no separate character data type. A character is simply a string of length one.
  • This relieves programmers from the C or Java burden of remembering which quotes to use for single characters as distinct from multi-character string.
  • It also eliminates any problems when dealing with Unicode multi-byte characters.

Overview:

• Literal Values:
  • string uses quotes: “string”
  • tuple uses ‘()’: (1,’b’,3.1)
  • list uses ‘[]’: [1,’b’,3.1]
• Operations:
  • ‘+’ concatenate
  • ‘*’ repeat sequence
  • ‘[ ]’ select elements from a sequence
• Built-in Functions:
  • len(sized_col lection)
  • max(iterable_collection)
  • min(iterable_collection)
  • sum(iterable_collection, [init=0])
  • any(iterable_col lection)
  • all(iterable_col lection)
  • enumerate(iterable_col lection)
  • sorted(sequence, [key=None], [reverse=False])
  • reversed(sequence)
• Comparisons:
  • ‘<’, ‘<=’, ‘>’, ‘<=’, ‘==’, ‘!=’
  • ‘in’, ‘not in’
• Methods:
  • The string and list classes have method functions that operate on the object’s value. ‘”abc”.upper()’
  • The exact dictionary of methods is unique to each class of sequences.

• Statements:

  The tuple and list: eg. assignment, for, exists

• Modules:

chapter 13. STRINGS

msg = "A very long" \
"message, which didn't fit on" \
"one line."

“日本” is made up of Unicode characters ‘U+65e5’ and ‘U+672c’. In Python, we write this string as ‘u’\u65e5\u672c’’.

r= "die 1 shows %i, and die 2 shows %i" % ( d1, d2 )

• WHY immutable STRING ?
  • Python’s storage management makes this use of immutable string the simplest and most efficient.
• WHY bother with tuple, Since a list does everything a tuple does and is mutable ?
  • Immutable tuple objects are more efficient than variable-length list objects for some operations.
  • When it is no longer referenced, the normal Python garbage collection will release the storage for the tuple
  • Most importantly, a tuple can be reliably hashed to a single value. This makes it a usable key for a mapping.
• Wouldn’t it be “more efficient” to allow mutable string s?
  • There are a number of axes for efficiency: the two most common are time and memory use.
  • A mutable string could use less memory. However, this is only true in the benign special case where we are only replacing or shrinking the string within a fixed-size buffer.
  • it must switch to dynamic memory allocation, if he string expands beyond the size of the buffer.
  • Python simply uses dynamic memory allocation from the start.
  • Processing a mutable string could use less time, if fixed-length small buffer required text-intensive applications we may want to avoid creating separate string objects.
  • Instead, we may want to create a single string object – the input buffer – and work with slices of that buffer.
    That’s Python does, and we get flexibility and simplicity.

Chapter 14. TUPLES

• Latin suffix for multiples: double, triple, quadruple, quintuple.
• a tuple has a fixed and known number of elements, N-cordinal ARRAY but immutable.

• The elements of a tuple do not have to be the same type.

    xy= (2, 3)   #  xy A 2-tuple with integers.
    	personal= ('Hannah',14,5*12+6)  # ersonal A 3-tuple with a string and two integers
    	singleton= ("hello",)
  

• singleton. A 1-tuple with a string. The trailing ‘,’ assures that his is a tuple, not an expression.

    >>> x, y = (1, 2) 
    >>> for i in ( 1,3,5,7,9, 12,14,16,18, 19,21,23,25,27, 30,32,34,36 ):
    	>>>    s += i
  

• divmod(x, y ) -> ( div, mod)

    >>> q,r = divmod(355,113) 
    	>>> (q,r)
    3, 16 # Chapter 15. LISTS
  

• A list is a container for variable length sequence of Python objects

• A list is mutable, items within the list can be changed, added or removed.

  myList = [ 2, 3, 4, 9, 10, 11, 12 ] history = [ ]

  »> i = range(10) »> del i[0], i[2], i[4], i[6] »> for i, t in enumerate( a ): … print “index”,i,”value”,t »> for i in [2,3,5,7,11,13,17,19]: … s += i »> print “total”,s
• Functions
  • append(obj)
  • insert(index,obj)
  • pop(index=-1)
  • remove(value)
  • index(value)
  • count(value)