CSC1018F: Regular Expressions Diving into Python Ch. 7 Number Systems

Lecture Outline Recap of OO Python [week 3] Regular Expressions Standard Verbose Number Systems Binary, decimal, hexadecimal

Recap of OO Python Object Orientation: Exceptions File Handling: Module importing Defining, initializing and instantiating Classes Class attributes Class methods Exceptions File Handling: Opening, reading, writing and closing

Intro to Regular Expressions Regular expressions are a powerful means for parsing text to identify complex patterns of characters Standard string methods (find, replace, split) can be insufficient in complex cases But regular expressions can be complicated and difficult to read so avoid them if string methods will do the job Read regular expressions from left to right Usage: Import re # regular expression functionality in re module Re.sub(regexpr, repstr, inputstr) # typical search & replace

Format of Regular Expressions Syntax: $ - end of string marker ^ - start of string marker \b - word boundary marker (to avoid backslash escapes use a raw string - r"stringcontents") ? - optional match to a single character (A|B|C) - indicates mutually exclusive options A, B and C Examples: re.sub(r"\bROAD$", "RD.", addr) addr: 60 BROAD ROAD  60 BROAD RD. re.search(r"^(a|b|c) -", question) question: a - how are you?  <SRE_Match object …>

Further Syntax P{n, m} syntax: More syntax: Examples: Deals with repeating patterns Read as pattern P appears at least n times but no more than m times More syntax: \d - any numeric digit \D - any character except a numeric digit + - 1 or more * - 0 or more ( ) - to indicate groups Examples: >>> phPat = re.compile(r"^(\d{3})\D*(\d{7})$") >>> phPat.search(“021 6504058”).groups() (‘021’, ‘6504058’)

Verbose Regular Expressions So far only compact regular expressions To aid readability we would like to include comments and spaces Use re.VERBOSE as the last arguments to re functions Whitespace is ignored Comments ( # commentstr) are ignored Example: pattern = """ ^ # beginning of string $ # end of string """

Case Study Counting 1-10 in roman numerals Additive and subtractive combination of I (=1), V(=5), X (=10) Can have at most 3 of a particular numeral in a row >>> roman = r"^(I?X|IV|V?I{0,3})$" >>> re.search(roman, "X") <_sre.SRE_Match object at 0x1e55be0> >>> re.search(roman, "VIII") <_sre.SRE_Match object at 0x1e55ba0> >>> re.search(roman, "") <_sre.SRE_Match object at 0x1e55ce0> >>> re.search(roman, "IIII") == None True

Number Systems Decimal (base 10) Binary (base 2) Hexadecimal (base 16) Digits (0-9) Each place represents a power of ten 172 = 2*100 + 7*101 + 1*102 = 172 Binary (base 2) Digits (0,1) Each place represents a power of two 10011 = 1*20 + 1*21 + 0* 22 + 0* 23 + 1* 24 = 19 Hexadecimal (base 16) Digits (0-9, A-F) A-F represent 10-15 Each place represents a power of sixteen E.g., F7A = 10*160 + 7* 161 + 15* 162 = 3962

Conversion Decimal to others Bin2Hex: Hex2Bin Hex is used because: Repeatedly divide number by base and populate places from right to left with the remainder E.g. Dec2Bin: 50 / 2 [% = 0] = 25 / 2 [% = 1] = 12 / 2 [% = 0] = 6 / 2 [% = 0] = 3 / 2 [% = 1] = 1 / 2 [% = 1] = 0 [110010] Bin2Hex: Collect binary digits into groups of four and convert E.g., 111000011111 = 1110 0001 1111 = E1F Hex2Bin Hexadecimal digits convert into groups of four binary digits E.g., A7C = 1010 0111 1100 = 101001111100 Hex is used because: It is easy to convert to and from binary Offers a more compact representation

Revision Exercise Create a function which will take a date string in any one of the following formats: dd/mm/yyyy or dd/mm/yy Other separators (e.g., ‘\’, ‘ ‘, ‘-’) are also allowed Single figure entries may have the form x or 0x, e.g. 3/4/5 or 03/04/05 dd month yy or yyyy where month may be written in full (December) or abbreviated (Dec. or Dec) And return it in the format: dd month(in full) yyyy, e.g. 13 March 2006 Implement this using regular expressions and also implement range checking on dates