计算机作业代写，工程师论文代写范文，北美cs代写
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CS assignment代写是什么？为什么要挑选计算机作业代写？
CS全称为ComputerScience，CSassignment代写可理解为留学生编程作业代写，归于计算机科学的范畴。计算机科学是一门复杂且归纳的学科，其间既包括计算机理论知识，又涵盖了数据及算法的编程与使用。咱们常说的CS作业主要指留学生需求完结的一系列编程作业的写作。
由于CS作业的归纳性，留学生想要完结质量较高的编程作业的写作，需求一起具备较高的英文修改才能、计算机编程才能以及必定的数学计算水平。再加上海外学校的高标准与严要求，很多留学生难以顺利完结导师安置的CS作业。在这样的两层压力下，留学生不得不寻觅计算机作业代写的协助。
CSassignment代写的流程与常见问题解析
在找到适宜的计算机作业代写组织前，咱们有必要了解CSassignment代写的基本流程以及代写过程中可能呈现的一些常见问题。下面，小编以LondonerEssay代写为例，为大家剖析CSassignment代写的详细流程。
代写范文
When working on this quiz, recall the rules stated on the Academic Integrity Contract that you signed. You can download the q2helper project folder (available for Friday, on the Weekly Schedule link) in which to write your Regular Expressions and write/test/debug your code. Submit your completed files for repattern1a.txt, repattern1b.txt, repattern2a.txt, repattern4a.txt, repattern4b.txt, and your q2solution.py module online by Friday, 11:30pm. I will post my solutions to Piazza reachable via the Solutionslink on Sundaymorning. For parts 1a, 1b, and 2a, use a text editor (I suggest using Eclipse’s) to write and submit a one line file. The line should start with the ^ character and end (on the same line) with the $ character. The contents of that one line should be exactly what you typed-in/tested in the online Regular Expression checker. 1a. (4 pts) Write a regular expression pattern that matches familial relationships involving a mother, father, son, daughter, and the words Great, grand, and Step. To simplify the problem, we will use just the first letters (case is important) of these words with no spaces between them. The symbol GGgs means “great great grandson.” Legal: Should Match : m, gf, Ggm, GGgf, Ss, SGgs, Illegal: Should Not Match: mf, Gm, SSm, GSm, See bscq2W20.txt for other legal/illegal combinations. Put your answer in repattern1.txt. 1b. (2 pts) Write a regular expression pattern that matches the same strings described in part 1a. But in addition for this pattern, ensure capture group 1 (also named step) is the S or None; group 2 (also named great) is some number of Gs or None; group 3 (also named grand) is the g or None; group 4 (also named basic) is the m, f, d, or s. For example, if we execute m = re.match(the-pattern, 'GGgf’) then m.groups() returns (None, 'GG', 'g', 'f'); and m.groupdict() returns {'step': None, 'great': 'GG', 'grand': 'g', 'basic': 'f'}. There should be no other numbered capture groups. Hint (?:...) creates a parenthesized regular expression that is not numbered as a group. You can write one regular expression for both 1a and 1b, or you can write a simpler one for 1a (just use parentheses for grouping and ignore capture groups) and then update it for 1b by including only the necessary groups. Put your answer in repattern1b.txt. 2. (2 pts) Recall that parameter specifications in function definitions come in two flavors: name-only parameters and default-argument parameters, with the ability to preface at most one name-only parameter by a * (for this problem, we will not allow ** written before a name-only parameter, although such parameters are legal in Python). All parameters are separated by commas. To simplify this problem, let’s use n to abbreviate a name-only parameter and d to abbreviate a default-argument parameter. Write a regular-expression pattern that matches legal orders of these parameter lists in a function definition. The general rule you should model is: a parameter list can (a) be empty, (b) contain one n, *n, or d, (c) can contain a sequence of ns and ds with at most one *n in the sequence (front, middle, or rear). These rules are a simplification of real Python, but are complex enough for this problem. Legal: Should Match : n; d; *n; n,d,n,d; n,d,*n,d,d; *n,d,d,n,d; n,n,*n Illegal: Should Not Match: n,,d; nd; *n,*n; n,*nd; n,d*n,d; *n,d,d,*n Put your answer in repattern2.txt. 3. (7 pts) EBNF allows us to name rules and then build complex descriptions whose right-hand sides use these names. But Regular Expression (RE) patterns are not named, so they cannot contain the names of other patterns. It would be useful to have named REs and use their names in other REs. In this problem, we will represent named RE patterns by using a dict (whose keys are the names and whose associated values are RE patterns that can contain names), and then repeatedly replace the names by their RE patterns, to produce complicated RE patterns that contains no names. Define a function named expand_re that takes one dict as an argument, representing various names and their associated RE patterns; expand_re returns None, but mutates the dict by repeatedly replacing each name by its pattern, in all the other patterns. The names in patterns will always appear between #s. For example, if p is the dict {’digit’: r’[0-9]’, ’integer’: r’[+-]?#digit##digit#*’} then after calling expand_re(p), p is now the dict {'integer': '[+-]?(?:[0-9])(?:[0-9])*', 'digit': '[0-9]'}. Notice that digit remains the same, but each #digit# in integer has been replaced by its associated pattern and put inside a pair of parentheses prefaced by ?:. Hint: For every rule in the dictionary, substitute (see the sub function in re) all occurrences of its key (as a pattern, in the form #key#) by its associated value (always putting the value inside parentheses), in every rule in the dictionary. The order in which names are replaced by patterns is not important. Hint: I used re.compile for the #key# pattern (here no ^ or $ anchors!), and my function was 4 lines long (this number is not a requirement). The q2solution.py module contains the example above and two more complicated ones (and in comments, the dicts that result when all the RE patterns are substituted for their names). These examples are tested in the bscq2W21.txt file as well. 4. (10 pts) In the review notes, examine the descriptions of name-only and default-argument parameters as well as positional and named arguments. You will write a function that takes a correctly written parameter list (from a function definition) and a correctly written argument list (from a function call) and implement the algorithm that matches the parameter/argument matching rules of Python. This function returns all the bindings for the parameters or raises an AssertionError if any of the binding rules are violated (e,g.: parameter fails to bind to argument or binds to more than one). To aid in this algorithm, you will first write two regular expressions for helping to decode a parameter/argument. This is a hard problem; I do not expect everyone to finish all the parts; the last parts are worth less than the early parts. 4a. (3 pts) Write a regular expression pattern that matches a single argument: an optional name and equal sign followed by an integer (for simplicity, we will assume here that all arguments are integers). Python names start with an alphabetic or underscore character, and continue with any alphabetic, numeric, or underscore characters. Integers have an optional sign followed by some non-zero number of digits. Allow no spaces in the text. Matches should have two named groups: name and value. For example, if we execute m = re.match(the-pattern,'x=-2’) then m.groupdict() returns {'name': 'x', 'value': '-2'}. 4b. (1 pts) Write a regular expression pattern that matches a single parameter: an optional * followed by a name (assume no spaces are between them) optionally followed by an equal sign and an integer (for simplicity, we will assume here that all default arguments are integers). Python names start with an alphabetic or underscore character, and continue with any alphabetic, numeric, or underscore characters. Allow no spaces in the text. Matches should have three named groups: star (might be '*’ or None), name, and value. For example, if we execute m = re.match(the-pattern,'x=-2’) then m.groupdict() returns {'star': None, 'name': 'x', 'value': '-2'}. This pattern is actually very similar to the one you wrote in part 4a, which is why it is worth only 1 point. 4c. (6 pts) Now write the match_param_args function to take two strings as arguments, the first representing a legal list of parameters (from a function definition) and the second representing a legal list of arguments (from a function call). This function returns a dict with all the bindings for the parameters or raises an AssertionError if any of the binding rules are violated. I strongly suggest that you write (conditional) print statements in this function to supply a trace of your function so that you can see how it is processing the arguments and better debug it. See my example at the end of this problem. You can leave the tracing code in, delete it, or just comment it out when you submit your module for grading. Note that as the processing gets more complicated, the points go down, because I expect fewer students to correctly write that code. You don’t have to follow my hints, but I expect that you will find them useful. Hint 1: Split the parameter string and then create a list of match objects, with each parameter matched against the above-specified regular
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