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lfa:2022:lab01-programming-intro [2022/10/07 14:14]
pdmatei 		lfa:2022:lab01-programming-intro [2022/10/14 13:13] (current)
mihai.udubasa add solutions
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 ====== Programming introduction ====== ====== Programming introduction ======
 +
 +===== 1. Scala introduction =====
 +
 +**Exercise 1.1.** Write a function ​ ''​startStop''​ which retrieves the elements of a list from within bounds. Use patterns in your implementation. Define an object ''​Main''​ as shown below.
 +Any code within the object can be directly executed. (Hint: use a simply-recursive function)/
 +
 +<code scala>
 +object Main extends App {
 +def startStop[A] (l: List[A] ,start: Int, stop: Int): List[A] = ???
 +
 +println(startStop(List(1,​2,​3,​4,​5,​6),​1,​4))
 + // = List(2,​3,​4) ​
 +}
 +</​code> ​
 +
 +**Exercise 1.2.** Write a function which determines the number of occurrences of each character in a string. (Hint: use a tail-recursive function)
 +<code scala>
 +def countChars (s:String): Map[Char,​Int] = {
 +    def aux(l: List[Char], acc: Map[Char,​Int]):​ Map[Char,​Int] = ???
 +    ???
 +  }
 +</​code>​
 +
 +**Exercise 1.3** Write a function which takes a list of records first name, last name, CNP (encoded as tuples), and returns a list of the last names and ages of all females which are younger than the average of the entire list. E.g. ''​List( (“Mary”,​ “2030694123456”),​ (“Anne”,​“2121092123456”),​ (“Matei”,​ “5121202123456”),​ (“Maggie”,​ “2121078123456”) )''​ yields ''​List( (“Mary”,​28),​ (“Anne”,​30) )''​. Maggie was born in '78, whereas Mary, Anne and Matei were born in '94, '92 and 2002, respectively. (Hint: use combinations of **map** with **filter**)
 +
 +<code scala>
 +val example = List(("​Mary", ​ "​2030694123456"​),​ ("​Anne", ​ "​2121092123456"​),​ ("​Matei",​ "​5121202123456"​),​ ("​Maggie",​ "​2121078123456"​))
 +
 +def youngerThanAverage(l:​ List[(String,​String)]):​ List[(String,​Int)] = {
 +    def getAge(s:​String):​Int = ??? 
 +    // female gender = True
 +    def getGender(s:​String):​Boolean = ???
 +    ???
 +  }
 +</​code>​
 +
 +**Exercise 1.4** 
 +A labelled graph is encoded as a String text where **each line** is an edge ''<​from>​ <​label>​ <​to>''​
 +Example:
 +<​code>​
 +0 r 1
 +0 r 2
 +0 g 1
 +1 g 2 
 +1 b 3
 +1 r 4
 +4 g 1
 +3 b 2
 +2 r 2
 +2 g 3
 +</​code>​
 +
 +  * Suppose we encode streets as labelled graphs, where each label '​r',​ '​g'​ or '​b'​ denotes a street color. These colors can be any alphabetical character, not necessarily just rgb. 
 +  * Given a **start node** and a **sequence of colors**, find all the destination nodes that can be accessed by traversing streets in that particular color.
 +    * Example: Starting from 0, on the sequence ''​rrg'',​ the destination node are ''​1''​ (0 red to 1 red to 4 green to 1) and ''​3''​ (0 red to 2, red to 2, red to 3)
 +  * Hint: use **foldLeft** as well as **for expressions**.
 +
 +<code scala>
 +val example = """​0 r 1
 +                  |0 r 2
 +                  |0 g 1
 +                  |1 g 2
 +                  |1 b 3
 +                  |1 r 4
 +                  |4 g 1
 +                  |3 b 2
 +                  |2 r 2
 +                  |2 g 3"""​.stripMargin
 +           
 +type Streets = Map[(Int,​Char),​Set[Int]]
 +def readStreets(s:​ String): Streets = ???
 +
 +def findDestination(start:​ Int, colors: String, streets: Streets): Set[Int] = ???
 +</​code>​
 +
 +
 +
 +===== 2. Python introduction =====
  
 Python3 is a multi-paradigm language, that combines the **imperative** style with the **functional** style. It also supports Object-Oriented programming,​ albeit in a limited way.  Python3 is a multi-paradigm language, that combines the **imperative** style with the **functional** style. It also supports Object-Oriented programming,​ albeit in a limited way. 
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 ==== List traversal ==== ==== List traversal ====
  
-**Exercise ​1.1.** Write a function ''​f(l)''​ which determines the maximum of a list ''​l''​ of integers.+**Exercise ​2.1.** Write a function ''​f(l)''​ which determines the maximum of a list ''​l''​ of integers.
  
 <hidden The pythonic way> ​ <hidden The pythonic way> ​
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 </​hidden>​ </​hidden>​
  
-**Exercise ​1.2.** Modify the previous function to ''​f(l,​start,​stop)''​ and determine the maximum between positions ''​start''​ and ''​stop''​.+**Exercise ​2.2.** Modify the previous function to ''​f(l,​start,​stop)''​ and determine the maximum between positions ''​start''​ and ''​stop''​.
  
 <hidden The pythonic way> ​ <hidden The pythonic way> ​
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 ==== Slicing lists ==== ==== Slicing lists ====
  
-**Exercise ​1.3.** Find the **longest** sequence of positive integers from a list. E.g. for the list ''​[1,​3,​-1,​2,​0,​1,​5,​4,​-2,​4,​5,​-3,​0,​1,​2]''​ the answer is ''​[2,​0,​1,​5,​4]''​.+**Exercise ​2.3.** Find the **longest** sequence of positive integers from a list. E.g. for the list ''​[1,​3,​-1,​2,​0,​1,​5,​4,​-2,​4,​5,​-3,​0,​1,​2]''​ the answer is ''​[2,​0,​1,​5,​4]''​.
  
 <hidden The pythonic way> ​ <hidden The pythonic way> ​
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 </​hidden>​ </​hidden>​
  
-**Exercise ​1.4.** Write a pythonic function to check if a list is palindrome.+**Exercise ​2.4.** Write a pythonic function to check if a list is palindrome.
  
 ===== Other datatypes ===== ===== Other datatypes =====
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 </​code>  ​ </​code>  ​
  
-**Exercise ​1.5.** Write a function which determines (and returns) the **longest** sequence of consecutive integers from a list.+**Exercise ​2.5.** Write a function which determines (and returns) the **longest** sequence of consecutive integers from a list.
  
 ==== Dictionaries ==== ==== Dictionaries ====
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 <​code>​ <​code>​
 5 5
-0 X 1 +0 r 1 
-1 O 2  +0 r 2 
-1 X 3 +0 g 1 
-1 O 4 +1 g 2  
-4 X 1 +1 b 3 
-3 O 2+1 r 4 
 +4 g 1 
 +3 b 2 
 +2 r 2 
 +2 g 3
 </​code>​ </​code>​
  
-  * Suppose we encode streets as labelled graphs, where each label 'X' or 'O' denotes ​if a street ​is closed or open.  +  * Suppose we encode streets as labelled graphs, where each label 'r', 'g' or 'b' denotes a street ​color. These colors can be any alphabetical character, not necessarily just rgb.  
-  * Compute the set of accessible nodes from a given **source**, via open streets.+  * Given a **start node** and a **sequence of colors**, find all the destination nodes that can be accessed by traversing ​streets ​in that particular color. 
 +    * Example: Starting from 0, on the sequence ''​rrg'',​ the destination node are ''​1''​ (0 red to 1 red to 4 green to 1) and ''​3''​ (0 red to 2, red to 2, red to 3)
   * (Hint1: google //Python read lines// to see how to read from a file; also, google ''​split''​ in Python)   * (Hint1: google //Python read lines// to see how to read from a file; also, google ''​split''​ in Python)
   * (Hint2: you will need a dictionary to store, for each node and label l, the list of its l-successors)   * (Hint2: you will need a dictionary to store, for each node and label l, the list of its l-successors)
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   * ''​None'':​ represents the lack of a value (or an explicit None value); useful to mark functions which have no return value, or that a value may be purposefully missing (in combination with the ''​|''​ operator), and a None check may be necessary   * ''​None'':​ represents the lack of a value (or an explicit None value); useful to mark functions which have no return value, or that a value may be purposefully missing (in combination with the ''​|''​ operator), and a None check may be necessary
 full documentation of the python typing module: [[https://​docs.python.org/​3/​library/​typing.html]] full documentation of the python typing module: [[https://​docs.python.org/​3/​library/​typing.html]]
 +
 +
 +
 +===== Solutions =====
 +<note important>​
 +[[https://​github.com/​NethDR/​LFA-LAB1-solutions|click here for spoilers/​solutions]]
 +</​note>​