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stringlengths 57
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OOP/300 | Question: Given an array **people**. people[i] represents the weight of the i-th person, the number of boats is unlimited, and each boat can carry a maximum weight of **limit**. Each boat can carry up to two people at the same time, but the condition is that the sum of these people's weights is at most **limit**. Return the minimum number of boats required to carry all people;
Based on the above question, please create a class **MSS** in Python language with the attribute **people**; then create a class **SN_MSS**, inherit the **MSS** class, and add the attribute **limit**, as well as a public function **Minimum_ships** to return the minimum number of boats required to carry all people. | [
"assert candidate([1,2],3)==1",
"assert candidate([3,2,2,1],3)==3",
"assert candidate([3,5,3,4],5)==4"
] | def test_run(content1,content2):
return SN_MSS(content1,content2).Minimum_ships() | test_run | assert candidate([['class MSS', 'class SN_MSS(MSS)', 'super().__init__(people)', 'def Minimum_ships']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/301 | Question: In an n x n **grid**, we place some 1 x 1 x 1 cubes aligned with the **x**, **y**, **z** axes. Each value v = grid[i][j] represents **v** cubes stacked on the cell (i, j). Now, we look at the projections of these cubes on the **xy**, **yz**, and **zx** planes. A projection is like a shadow, mapping a three-dimensional shape onto a two-dimensional plane. When we look at the cube from the top, front, and side, we will see the shadow. Return the total area of all three projections;
Please create a class **TPD** based on the above question using Python, with the attribute **grid**; then create a class **SN_TPD**, inheriting from the **TPD** class, and add a public function **Total_projected** to return the total area of all the cubes' projections on the **xy**, **yz**, and **zx** planes. | [
"assert candidate([[1,2],[3,4]])==17",
"assert candidate([[2]])==5",
"assert candidate([[1,0],[0,2]])==8"
] | def test_run(content1):
return SN_TPD(content1).Total_projected() | test_run | assert candidate([['class TPD', 'class SN_TPD(TPD)', 'super().__init__(grid)', 'def Total_projected']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/302 | Question: On a grid of rows x cols, you start from the cell (rStart, cStart) facing east. The northwest corner of the grid is at the first row and the first column, and the southeast corner is at the last row and the last column. You need to walk in a clockwise spiral, visiting every position in this grid. Whenever you move beyond the boundary of the grid, you need to continue walking outside the grid (but you may return to the grid boundary later). Eventually, we have visited all the rows x cols spaces in the grid. Return the list of coordinates representing the grid positions in the order of visit;
Based on the above question, please create a class **CLT** in Python language with the property **rows**; then create another class **SN_CLT** that inherits the **CLT** class, and add three properties **cols**, **rStart** and **cStart**, as well as a public function **Coordinate_List** to return the list of coordinates representing the grid positions in the order of visit. | [
"assert candidate(1,4,0,0)==[[0,0],[0,1],[0,2],[0,3]]",
"assert candidate(5,6,1,4)==[[1,4],[1,5],[2,5],[2,4],[2,3],[1,3],[0,3],[0,4],[0,5],[3,5],[3,4],[3,3],[3,2],[2,2],[1,2],[0,2],[4,5],[4,4],[4,3],[4,2],[4,1],[3,1],[2,1],[1,1],[0,1],[4,0],[3,0],[2,0],[1,0],[0,0]]"
] | def test_run(content1,content2,content3,content4):
return SN_CLT(content1,content2,content3,content4).Coordinate_List() | test_run | assert candidate([['class CLT', 'class SN_CLT(CLT)', 'super().__init__(rows)', 'def Coordinate_List']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/303 | Question: Given a set of **n** people (numbered 1,2,...,n), we want to divide each person into two groups of any size. Each person may not like others, so they should not belong to the same group. Given the integer **n** and the array **dislikes**, where dislikes[i]=[a_i,b_i], it is not allowed to put the people numbered **a_i** and **b_i** into the same group. When all people can be divided into two groups in this way, return True; otherwise, return False;
Based on the above question, please create a class **GPG** in Python with the attribute **n**; then create a class **SN_GPG** that inherits from the **GPG** class, and add the attribute **dislikes**, as well as a public function **grouping** to determine whether each person can be divided into two groups of any size given the integer **n**and the array **dislikes**. If it is possible, return True; otherwise, return False. | [
"assert candidate(4,[[1,2],[1,3],[2,4]])==True",
"assert candidate(3,[[1,2],[1,3],[2,3]])==False",
"assert candidate(5,[[1,2],[2,3],[3,4],[4,5],[1,5]])==False"
] | def test_run(content1,content2):
return SN_GPG(content1,content2).grouping() | test_run | assert candidate([['class GPG', 'class SN_GPG(GPG)', 'super().__init__(n)', 'def grouping']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/304 | Question: You are given **k** identical eggs and you have access to a building with **n** floors from the 1st floor to the n-th floor. It is known that there exists a floor **f**, satisfying 0<=f<=n, any eggs dropped from a floor higher than **f** will break, and those dropped from the **f** floor or lower will not break. Each time, you can take an unbroken egg and drop it from any floor **x** (satisfying 1<=x<=n). If the egg breaks, you cannot use it again. If an egg does not break after being dropped, it can be reused in subsequent operations. Please calculate and return the minimum number of operations to determine the exact value of **f**.
Please create a class **NOS** in Python based on the above problem, with the attribute **k**. Then create a class **SN_NOS** that inherits from the **NOS** class, adds the attribute **n**, and a public function **number_operations** to calculate and return the minimum number of operations to determine the exact value of **f**. | [
"assert candidate(1,2)==2",
"assert candidate(2,6)==3",
"assert candidate(3,14)==4"
] | def test_run(content1,content2):
return SN_NOS(content1,content2).number_operations() | test_run | assert candidate([['class NOS', 'class SN_NOS(NOS)', 'super().__init__(k)', 'def number_operations']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/305 | Question: The width of a sequence is defined as the difference between the maximum and minimum elements in the sequence. Given an integer array **nums**, return the sum of the widths of all non-empty subsequences of **nums**. A subsequence is defined as an array obtained by deleting some (or not deleting) elements from an array without changing the order of the remaining elements.
Based on the above question, please create a class **SWS** in Python, which has the attribute **nums**; then create another class **SN_SWS** that inherits from the **SWS** class, and add a public function **Sum_widths** to return the sum of the widths of all non-empty subsequences of the integer array **nums**. | [
"assert candidate([2,1,3])==6",
"assert candidate([2])==0"
] | def test_run(content1):
return SN_SWS(content1).Sum_widths() | test_run | assert candidate([['class SWS', 'class SN_SWS(SWS)', 'super().__init__(nums)', 'def Sum_widths']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/306 | Question: We have a non-negative integer array **arr**. For each (continuous) subarray sub=[arr[i],arr[i+1],...,arr[j]] (i<=j), we perform a bitwise OR operation on each element in **sub**, obtaining the result arr[i]|arr[i+1]|...|arr[j]. Return the number of possible results. Multiple occurrences of the result are only counted once in the final answer;
Please create a class **FAR** with the property **arr** in Python language based on the above question; then create a class **SN_FAR** inheriting the **FAR** class, and add a public function **Final_Answer** to return the number of possible results. | [
"assert candidate([0])==1",
"assert candidate([1,1,2])==3",
"assert candidate([1,2,4])==6"
] | def test_run(content1):
return SN_FAR(content1).Final_Answer() | test_run | assert candidate([['class FAR', 'class SN_FAR(FAR)', 'super().__init__(arr)', 'def Final_Answer']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/307 | Question: Given a string **s** and an integer **k**. You can choose one from the first **k** letters of **s** and add it to the end of the string. Return the lexicographically smallest string after any number of moves applying the above steps;
Please create a class **SSG** with the attribute **s** in Python based on the above question; then create another class **SN_SSG** that inherits from the **SSG** class, and add the attribute **k**, as well as a public function **Smallest_string** to return the lexicographically smallest string after any number of moves applying the above steps. | [
"assert candidate(\"cba\",1)==\"acb\"",
"assert candidate(\"baaca\",3)==\"aaabc\""
] | def test_run(content1,content2):
return SN_SSG(content1,content2).Smallest_string() | test_run | assert candidate([['class SSG', 'class SN_SSG(SSG)', 'super().__init__(s)', 'def Smallest_string']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/308 | Question: Given a numerical array **digits** sorted in non-decreasing order. You can write numbers using digits[i] any number of times. For example, if digits = ['1','3','5'], we can write numbers like '13', '551', and '1351315'. Return the number of positive integers that can be generated that are less than or equal to a given integer **n**;
Please create a class **NDG** in Python based on the above question, with the property **digits**; then create a class **SN_NDG** that inherits the **NDG** class, and add the property **n**, as well as a public function **Non_decreasing** to return the number of positive integers that can be generated that are less than or equal to the given integer **n**. | [
"assert candidate([\"1\",\"3\",\"5\",\"7\"],100)==20",
"assert candidate([\"1\",\"4\",\"9\"],1000000000)==29523",
"assert candidate([\"7\"],8)==1"
] | def test_run(content1,content2):
return SN_NDG(content1,content2).Non_decreasing() | test_run | assert candidate([['class NDG', 'class SN_NDG(NDG)', 'super().__init__(digits)', 'def Non_decreasing']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/309 | Question: Given a string **s** of length **n**, where s[i] is:
1. **D** means decrease; 2. **I** means increase; A valid arrangement is a permutation **perm** of n+1 integers within the range [0, n], so that for all **i**:
1. If s[i] == 'D', then perm[i] > perm[i+1]; 2. If s[i] == 'I', then perm[i] < perm[i+1]. Return the number of valid arrangements **perm**;
Based on the above question, please create a class **EAT** in Python, with the attribute **s**; then create a class **SN_EAT** that inherits from the **EAT** class, and add a public function **Effective_arrangement** that returns the number of valid arrangements **perm**. | [
"assert candidate(\"DID\")==5",
"assert candidate(\"D\")==1"
] | def test_run(content1):
return SN_EAT(content1).Effective_arrangement() | test_run | assert candidate([['class EAT', 'class SN_EAT(EAT)', 'super().__init__(s)', 'def Effective_arrangement']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/310 | Question: Given an integer array **arr**, find the sum of min(b), where **b** ranges over each (continuous) subarray of **arr**.
Please create a class **IAY** in Python language based on the above question, with the attribute **arr**; then create a class **SN_IAY** that inherits from the **IAY** class, and add a public function **Integer_array** to return the sum of min(b). | [
"assert candidate([3,1,2,4])==17",
"assert candidate([11,81,94,43,3])==444"
] | def test_run(content1):
return SN_IAY(content1).Integer_array() | test_run | assert candidate([['class IAY', 'class SN_IAY(IAY)', 'super().__init__(arr)', 'def Integer_array']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/311 | Question: Given an integer array **nums** and an integer **k**. For each index **i** (0<=i<nums.length), change nums[i] to nums[i]+k or nums[i]-k. The score of **nums** is the difference between the maximum and minimum elements in **nums**. After changing the value corresponding to each index, return the minimum score of **nums**;
Based on the above question, please use Python to create a class **MSE** with the attribute **nums**; then create another class **SN_MSE** that inherits from the **MSE** class, and add the attribute **k**, as well as a public function **Minimum_score** that returns the minimum score of **nums**. | [
"assert candidate([1],0)==0",
"assert candidate([0,10],2)==6",
"assert candidate([1,3,6],3)==3"
] | def test_run(content1,content2):
return SN_MSE(content1,content2).Minimum_score() | test_run | assert candidate([['class MSE', 'class SN_MSE(MSE)', 'super().__init__(nums)', 'def Minimum_score']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/312 | Question: Given an integer array **nums**, please sort this array in ascending order;
Based on the above question, please create a class **AOR** using Python language, with the attribute **nums**; then create another class **SN_AOR** that inherits from the **AOR** class, and add a public function **ascend_order** to sort the integer array **nums** in ascending order. | [
"assert candidate([5,2,3,1])==[1,2,3,5]",
"assert candidate([5,1,1,2,0,0])==[0,0,1,1,2,5]"
] | def test_run(content1):
return SN_AOR(content1).ascend_order() | test_run | assert candidate([['class AOR', 'class SN_AOR(AOR)', 'super().__init__(nums)', 'def ascend_order']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/313 | Question: Two players play the roles of a cat and a mouse respectively, and they play a game on an undirected graph, taking turns to move. The form of the graph is: graph[a] is a list, consisting of all nodes **b** that satisfy that **ab** is an edge in the graph. The **mouse** starts from node 1 and moves first; the **cat** starts from node 2 and moves second. There is a **hole** at node 0. In each player's move, they must move along an edge connected to their current position in the graph. For example, if the mouse is at node 1, it must move to any node in graph[1]. In addition, the cat cannot move into the hole (node 0). Then, the game ends when one of the following three situations occurs: If the cat and the mouse appear at the same node, the cat wins. If the mouse reaches the hole, the mouse wins. If a position is repeated (that is, the player's position and the order of movement are the same as the last action), the game is a draw. Given a graph, and assuming that both players participate in the game in their best state: if the mouse wins, return 1; if the cat wins, return 2; if it is a draw, return 0;
Based on the above question, please create a class called **CGS** in Python language with the attribute **graph**; then create a class called **SN_CGS** that inherits from the **CGS** class, and add a public function called **Cat_games** to return the final game result. | [
"assert candidate([[2,5],[3],[0,4,5],[1,4,5],[2,3],[0,2,3]])==0",
"assert candidate([[1,3],[0],[3],[0,2]])==1"
] | def test_run(content1):
return SN_CGS(content1).Cat_games() | test_run | assert candidate([['class CGS', 'class SN_CGS(CGS)', 'super().__init__(graph)', 'def Cat_games']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/314 | Question: Given a deck of cards, each card has an integer written on it. At this point, you need to select a number **X**, so that we can divide the deck into one or more groups according to the following rules: each group has **X** cards. All the cards in the group have the same integer written on them. Return True only when the selectable **X** is greater than or equal to 2, otherwise return False;
Based on the above question, please use Python language to create a class **SIR** with the attribute **deck**; then create a class **SN_SIR** that inherits the **SIR** class, and add a public function **Same_integer** to determine whether the selectable **X** is greater than or equal to 2. If it is, return True, otherwise, return False. | [
"assert candidate([1,2,3,4,4,3,2,1])==True",
"assert candidate([1,1,1,2,2,2,3,3])==False"
] | def test_run(content1):
return SN_SIR(content1).Same_integer() | test_run | assert candidate([['class SIR', 'class SN_SIR(SIR)', 'super().__init__(deck)', 'def Same_integer']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/315 | Question: Given an array **nums**, divide it into two consecutive sub-arrays **left** and **right** so that:
1. Each element in **left** is less than or equal to each element in **right**. 2. Both **left** and **right** are non-empty. 3. The length of **left** should be as small as possible. After completing such grouping, return the length of **left**;
Please create a class **PLH** in Python language based on the above question, with the attribute **nums**; then create another class **SN_PLH** that inherits the **PLH** class, and add a public function **Packet_Length** to divide the array **nums** into two consecutive sub-arrays **left** and **right**, and then return the length of **left** after grouping. | [
"assert candidate([5,0,3,8,6])==3",
"assert candidate([1,1,1,0,6,12])==4"
] | def test_run(content1):
return SN_PLH(content1).Packet_Length() | test_run | assert candidate([['class PLH', 'class SN_PLH(PLH)', 'super().__init__(nums)', 'def Packet_Length']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/316 | Question: Given two string arrays **words1** and **words2**. Now, if every letter in **b** appears in **a**, including the repeated letters, then we say that string **b** is a subset of string **a**. If for every word **b** in **words2**, **b** is a subset of **a**, then we say that the word **a** in **words1** is a universal word. Return all the universal words in **words1** in the form of an array;
Based on the above question, create a class **CWS** using Python language, with the property **words1**; then create a class **SN_CWS**, inheriting from the **CWS** class, and add the property **words2**, as well as a public function **Common_Words** to return all the universal words in **words1** in the form of an array. | [
"assert candidate([\"amazon\",\"apple\",\"facebook\",\"google\",\"leetcode\"],[\"e\",\"o\"])==[\"facebook\",\"google\",\"leetcode\"]",
"assert candidate([\"amazon\",\"apple\",\"facebook\",\"google\",\"leetcode\"],[\"l\",\"e\"])==[\"apple\",\"google\",\"leetcode\"]",
"assert candidate([\"amazon\",\"apple\",\"facebook\",\"google\",\"leetcode\"],[\"e\",\"oo\"])==[\"facebook\",\"google\"]",
"assert candidate([\"amazon\",\"apple\",\"facebook\",\"google\",\"leetcode\"],[\"lo\",\"eo\"])==[\"google\",\"leetcode\"]",
"assert candidate([\"amazon\",\"apple\",\"facebook\",\"google\",\"leetcode\"],[\"ec\",\"oc\",\"ceo\"])==[\"facebook\",\"leetcode\"]"
] | def test_run(content1,content2):
return SN_CWS(content1,content2).Common_Words() | test_run | assert candidate([['class CWS', 'class SN_CWS(CWS)', 'super().__init__(words1)', 'def Common_Words']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/317 | Question: Given a circular integer array **nums** of length **n**, return the maximum possible sum of non-empty subarrays in **nums**.
Please create a class **CAY** in Python based on the above question, with the attribute **nums**. Then create another class **SN_CAY**, inheriting from the **CAY** class, and add a public function **Circular_array** to return the maximum possible sum of non-empty subarrays in the circular integer array **nums** of length **n**. | [
"assert candidate([1,-2,3,-2])==3",
"assert candidate([5,-3,5])==10",
"assert candidate([3,-2,2,-3])==3"
] | def test_run(content1):
return SN_CAY(content1).Circular_array() | test_run | assert candidate([['class CAY', 'class SN_CAY(CAY)', 'super().__init__(nums)', 'def Circular_array']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/318 | Question: You have **n** different songs in your music player. During your journey, you plan to listen to **goal** songs (not necessarily different, i.e., song repetition is allowed). You will create a playlist according to the following rules:
1. Each song is played at least once. 2. A song can only be played again after other **k** songs have been played. Given **n**, **goal**, and **k**, return the number of playlists that can meet the requirements.
Based on the above question, please create a class **PAL** in Python with the attribute **n**; then create another class **SN_PAL**, inheriting from the **PAL** class, and add two attributes **goal** and **k**, as well as a public function **PlayList** that returns the number of playlists that can meet the requirements. | [
"assert candidate(3,3,1)==6",
"assert candidate(2,3,0)==6",
"assert candidate(2,3,1)==2"
] | def test_run(content1,content2,content3):
return SN_PAL(content1,content2,content3).PlayList() | test_run | assert candidate([['class PAL', 'class SN_PAL(PAL)', 'super().__init__(n)', 'def PlayList']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/319 | Question: A parenthesis string is valid only if one of the following conditions is met:
1. It is an empty string; 2. It can be written as AB (A connected with B), where both A and B are valid strings; 3. It can be written as (A), where A is a valid string. Given a parenthesis string **s**, in each operation, you can insert a parenthesis at any position in the string to make the result string **s** valid. The task is to return the minimum number of parentheses that must be added to make the string **s** valid.
Based on the above question, please create a class **MPS** in Python, which has an attribute **s**. Then create another class **SN_MPS**, which inherits from the **MPS** class, and add a public function **Minimum_parentheses** that returns the minimum number of parentheses that must be added to make the result string **s** valid. | [
"assert candidate(\"())\")==1",
"assert candidate(\"(((\")==3"
] | def test_run(content1):
return SN_MPS(content1).Minimum_parentheses() | test_run | assert candidate([['class MPS', 'class SN_MPS(MPS)', 'super().__init__(s)', 'def Minimum_parentheses']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/320 | Question: Given a non-negative integer array **nums**, half of the integers in **nums** are odd, and half are even. Sort the array so that when nums[i] is odd, **i** is also odd; when nums[i] is even, **i** is also even. You can return any array that meets the above conditions as the answer;
Based on the above question, please use Python to create a class **ASG** with the attribute **nums**; then create a class **SN_ASG** that inherits from the **ASG** class, and add a public function **Array_sorting** that returns an array that meets the conditions as the answer. | [
"assert candidate([4,2,5,7])==[4,5,2,7]",
"assert candidate([2,3])==[2,3]"
] | def test_run(content1):
return SN_ASG(content1).Array_sorting() | test_run | assert candidate([['class ASG', 'class SN_ASG(ASG)', 'super().__init__(nums)', 'def Array_sorting']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/321 | Question: Given an integer array **arr**, and an integer **target** as the target value, return the number of tuples **i**, **j**, **k** that satisfy i<j<k and arr[i]+arr[j]+arr[k]==target;
Please create a class **NTS** in Python language based on the above question, with **arr** as an attribute; then create another class **SN_NTS**, inheriting from the **NTS** class, and add the attribute **target**, as well as a public function **Number_tuples** to return the number of tuples **i**, **j**, **k** that satisfy i<j<k and arr[i]+arr[j]+arr[k]==target. | [
"assert candidate([1,1,2,2,3,3,4,4,5,5],8)==20",
"assert candidate([1,1,2,2,2,2],5)==12"
] | def test_run(content1,content2):
return SN_NTS(content1,content2).Number_tuples() | test_run | assert candidate([['class NTS', 'class SN_NTS(NTS)', 'super().__init__(arr)', 'def Number_tuples']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/322 | Question: Given a binary string **s**, you can flip any 0 to 1 or flip 1 to 0. Return the minimum number of flips to make **s** monotonically increasing;
Please create a class **FTM** in Python based on the above question, with the attribute **s**. Then create another class **SN_FTM** that inherits from the **FTM** class, and add a public function **Flip_Times** to return the minimum number of flips to make the binary string **s** monotonically increasing. | [
"assert candidate(\"00110\")==1",
"assert candidate(\"010110\")==2",
"assert candidate(\"00011000\")==2"
] | def test_run(content1):
return SN_FTM(content1).Flip_Times() | test_run | assert candidate([['class FTM', 'class SN_FTM(FTM)', 'super().__init__(s)', 'def Flip_Times']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/323 | Question: Given an array **arr** composed of 0s and 1s, divide the array into three non-empty parts so that all these parts represent the same binary value. If it can be done, please return any [i, j], where i+1<j, so that:
1. arr[0], arr[1], ..., arr[i] is the first part; 2. arr[i+1], arr[i+2], ..., arr[j-1] is the second part; 3. arr[j], arr[j+1], ..., arr[arr.length-1] is the third part. These three parts represent the same binary value. If it cannot be done, return [-1, -1];
Based on the above question, please create a class **BVE** in Python with the attribute **arr**; then create a class **SN_BVE** that inherits the **BVE** class, and add a public function **Binary_values** that returns any [i, j], or [-1, -1] if not possible. | [
"assert candidate([1,0,1,0,1])==[0,3]",
"assert candidate([1,1,0,1,1])==[-1,-1]",
"assert candidate([1,1,0,0,1])==[0,2]"
] | def test_run(content1):
return SN_BVE(content1).Binary_values() | test_run | assert candidate([['class BVE', 'class SN_BVE(BVE)', 'super().__init__(arr)', 'def Binary_values']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/324 | Question: Given a binary array **nums** and an integer **goal**, please count and return how many non-empty subarrays have a sum equal to **goal**.
Please create a class **NSY** in Python based on the above question, with the attribute **nums**. Then create another class **SN_NSY**, inheriting from the **NSY** class, and add the attribute **goal**, as well as a public function **Non_subarray** to count and return how many non-empty subarrays have a sum equal to the integer **goal**. | [
"assert candidate([1,0,1,0,1],2)==4",
"assert candidate([0,0,0,0,0],0)==15"
] | def test_run(content1,content2):
return SN_NSY(content1,content2).Non_subarray() | test_run | assert candidate([['class NSY', 'class SN_NSY(NSY)', 'super().__init__(nums)', 'def Non_subarray']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/325 | Question: Given a square integer array **matrix** of size n x n, find and return the minimum sum of a descending path through the **matrix**;
Based on the above question, create a class **DPH** in Python with the attribute **matrix**. Then create another class **SN_DPH** that inherits from the **DPH** class, and add a public function **descent_path** to return the minimum sum of a descending path through the integer array **matrix**. | [
"assert candidate([[2,1,3],[6,5,4],[7,8,9]])==13",
"assert candidate([[-19,57],[-40,-5]])==-59"
] | def test_run(content1):
return SN_DPH(content1).descent_path() | test_run | assert candidate([['class DPH', 'class SN_DPH(DPH)', 'super().__init__(matrix)', 'def descent_path']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/326 | Question: An array **nums** of length **n** is considered a beautiful array if it meets the following conditions:
1. **nums** is a permutation of the integers in the range [1, n].
2. For every 0 <= i < j < n, there is no index **k** (i < k < j) such that 2*nums[k] == nums[i] + nums[j].
Given an integer **n**, return a beautiful array of length **n**.
Based on the above question, create a class **BAR** in Python with an attribute **n**. Then create another class **SN_BAR** that inherits from the **BAR** class, and add a public function **Beautiful_array** that returns a beautiful array of length **n**. | [
"assert candidate(4)==[2,1,4,3]",
"assert candidate(5)==[3,1,2,5,4]"
] | def test_run(content1):
return SN_BAR(content1).Beautiful_array() | test_run | assert candidate([['class BAR', 'class SN_BAR(BAR)', 'super().__init__(n)', 'def Beautiful_array']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/327 | Question: Given a binary matrix **grid** of size n x n, where 1 represents land and 0 represents water. An island is a maximum group formed by 1s connected on all four sides, i.e., it will not be connected to any other 1s not in the group. There are exactly two islands in the grid. You can turn any number of 0s into 1s to connect the two islands into one. Return the minimum number of 0s that must be flipped.
Based on the above question, create a class **FNE** in Python, which has the attribute **grid**. Then create another class **SN_FNE** that inherits from the **FNE** class, and add a public function **Flip_Number** that returns the minimum number of 0s that must be flipped. | [
"assert candidate([[0,1],[1,0]])==1",
"assert candidate([[0,1,0],[0,0,0],[0,0,1]])==2",
"assert candidate([[1,1,1,1,1],[1,0,0,0,1],[1,0,1,0,1],[1,0,0,0,1],[1,1,1,1,1]])==1"
] | def test_run(content1):
return SN_FNE(content1).Flip_Number() | test_run | assert candidate([['class FNE', 'class SN_FNE(FNE)', 'super().__init__(grid)', 'def Flip_Number']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/328 | Question: Given a log array **logs**. Each log is a string separated by spaces, with the first word being an identifier mixed with letters and numbers. There are two different types of logs:
1. Letter logs: Apart from the identifier, all words are composed of lowercase letters; 2. Number logs: Apart from the identifier, all words are composed of numbers; Please re-sort the logs according to the following rules:
1. All letter logs are ranked before number logs. 2. When the content of the letter logs is different, ignore the identifier and sort according to the alphabetical order of the content; when the content is the same, sort by the identifier. 3. The number logs should retain their original relative order. Return the final order of the logs;
Based on the above question, please create a class **FOR** in Python language with the property **logs**; then create a class **SN_FOR** that inherits the **FOR** class, and add a public function **Final_order** to return the final order of the logs. | [
"assert candidate([\"dig1 8 1 5 1\",\"let1 art can\",\"dig2 3 6\",\"let2 own kit dig\",\"let3 art zero\"])==[\"let1 art can\",\"let3 art zero\",\"let2 own kit dig\",\"dig1 8 1 5 1\",\"dig2 3 6\"]",
"assert candidate([\"a1 9 2 3 1\",\"g1 act car\",\"zo4 4 7\",\"ab1 off key dog\",\"a8 act zoo\"])==[\"g1 act car\",\"a8 act zoo\",\"ab1 off key dog\",\"a1 9 2 3 1\",\"zo4 4 7\"]"
] | def test_run(content1):
return SN_FOR(content1).Final_order() | test_run | assert candidate([['class FOR', 'class SN_FOR(FOR)', 'super().__init__(logs)', 'def Final_order']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/329 | Question: Given a set of points **drop** on the xy-plane, determine the minimum area of the rectangle formed by these points, where the sides of the rectangle are parallel to the x-axis and y-axis. If no rectangle can be formed, return 0;
Based on the above question, please create a class **MAR** in Python language with the property **drop**; then create a class **SN_MAR** that inherits from the **MAR** class, and add a public function **Minimum_Area** that returns the minimum area of the rectangle formed. If no rectangle can be formed, return 0. | [
"assert candidate([[1,1],[1,3],[3,1],[3,3],[2,2]])==4",
"assert candidate([[1,1],[1,3],[3,1],[3,3],[4,1],[4,3]])==2"
] | def test_run(content1):
return SN_MAR(content1).Minimum_Area() | test_run | assert candidate([['class MAR', 'class SN_MAR(MAR)', 'super().__init__(drop)', 'def Minimum_Area']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/330 | Question: Given a string **s**, calculate the number of different non-empty sub-sequences of **s**;
Based on the above question, please create a class **ESU** in Python language with the attribute **s**. Then create another class **SN_ESU** that inherits from the **ESU** class, and add a public function **empty_subsequence** to return the number of different non-empty sub-sequences of the string **s**. | [
"assert candidate(\"abc\")==7",
"assert candidate(\"aba\")==6",
"assert candidate(\"aaa\")==3"
] | def test_run(content1):
return SN_ESU(content1).empty_subsequence() | test_run | assert candidate([['class ESU', 'class SN_ESU(ESU)', 'super().__init__(s)', 'def empty_subsequence']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/331 | Question: Given an integer array **nums**. Each **move** operation will choose any index **i** that satisfies 0<=i<nums.length, and increase **nums[i]** by 1. Return the minimum number of operations required to make each value in **nums** unique;
Please create a class **MOT** with the attribute **nums** in Python based on the above question. Then create a class **SN_MOT** that inherits from the **MOT** class, and add a public function **Minimum_operations** to return the minimum number of operations required to make each value in the integer array **nums** unique. | [
"assert candidate([1,2,2])==1",
"assert candidate([3,2,1,2,1,7])==6"
] | def test_run(content1):
return SN_MOT(content1).Minimum_operations() | test_run | assert candidate([['class MOT', 'class SN_MOT(MOT)', 'super().__init__(nums)', 'def Minimum_operations']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/332 | Question: Given two sequences **pushed** and **popped**, each with unique values, return True if they could be the result of a sequence of **push** and **pop** operations on an initially empty stack; otherwise, return False.
Based on the above question, create a class **ISK** in Python language with the attribute **pushed**; then create another class **SN_ISK** that inherits from the **ISK** class, and add the attribute **popped**, as well as a public function **Initial_stack** that returns the corresponding result. | [
"assert candidate([1,2,3,4,5],[4,5,3,2,1])==True",
"assert candidate([1,2,3,4,5],[4,3,5,1,2])==False"
] | def test_run(content1,content2):
return SN_ISK(content1,content2).Initial_stack() | test_run | assert candidate([['class ISK', 'class SN_ISK(ISK)', 'super().__init__(pushed)', 'def Initial_stack']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/333 | Question: There are **n** stones placed on some integer coordinates in a two-dimensional plane. Each coordinate can have at most one stone. If a stone has other stones on the same row or column, it can be removed. Given an array of length **n**, **stones**, where stones[i] = [x_i, y_i] represents the position of the i-th stone, return the maximum number of stones that can be removed;
Please create a class **RSN** in Python based on the above problem, with the attribute **stones**. Then create a class **SN_RSN** that inherits the **RSN** class, and add a public function **Removed_stones** to return the maximum number of stones that can be removed. | [
"assert candidate([[0,0],[0,1],[1,0],[1,2],[2,1],[2,2]])==5",
"assert candidate([[0,0],[0,2],[1,1],[2,0],[2,2]])==3",
"assert candidate([[0,0]])==0"
] | def test_run(content1):
return SN_RSN(content1).Removed_stones() | test_run | assert candidate([['class RSN', 'class SN_RSN(RSN)', 'super().__init__(stones)', 'def Removed_stones']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/334 | Question: Your initial energy is **power**, and your initial score is 0. You only have one pack of **tokens**. Where tokens[i] is the value of the i-th token (index starts from 0). There are two possible ways to use the tokens as follows:
1. If you have at least token[i] points of energy, you can flip the i-th token face up, lose token[i] points of energy, and gain 1 point. 2. If we have at least 1 point, we can flip the i-th token face down, gain token[i] points of energy, and lose 1 point. Each token can only be used once, the order of use is not limited, and it is not necessary to use all tokens. After using any number of tokens, return the maximum score we can get;
Please create a class **INY** in Python based on the above question, with the attribute **tokens**; then create a class **SN_INY** that inherits the **INY** class, and add the attribute **power**, as well as a public function **Initial_energy** that returns the maximum score that can be obtained. | [
"assert candidate([100],50)==0",
"assert candidate([100,200],150)==1",
"assert candidate([100,200,300,400],200)==2"
] | def test_run(content1,content2):
return SN_INY(content1,content2).Initial_energy() | test_run | assert candidate([['class INY', 'class SN_INY(INY)', 'super().__init__(tokens)', 'def Initial_energy']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/335 | Question: Given an array composed of 4 digits, return the maximum time that can be set in accordance with the 24-hour system. The 24-hour format is **HH:MM**, where HH is between 00 and 23, and MM is between 00 and 59. The smallest 24-hour system time is 00:00, and the largest is 23:59. Starting from 00:00 (midnight), the longer it passes, the greater the time. Return the answer in the format of **HH:MM** with a string length of 5. If the valid time cannot be determined, return an empty string;
Based on the above question, please create a class named **ETM** in Python, which has an attribute **arr**; then create a class **SN_ETM** that inherits from the **ETM** class, and add a public function **effective_time** that returns the maximum time that can be set in accordance with the 24-hour system. If the valid time cannot be determined, return an empty string. | [
"assert candidate([1,2,3,4])==\"23:41\"",
"assert candidate([5,5,5,5])==\"\"",
"assert candidate([0,0,0,0])==\"00:00\"",
"assert candidate([0,0,1,0])==\"10:00\""
] | def test_run(content1):
return SN_ETM(content1).effective_time() | test_run | assert candidate([['class ETM', 'class SN_ETM(ETM)', 'super().__init__(arr)', 'def effective_time']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/336 | Question: Given a non-empty array **nums** composed of different positive integers, consider the following graph:
1. There are nums.length nodes, marked from nums[0] to nums[nums.length-1]; 2. There is an edge between nums[i] and nums[j] only when nums[i] and nums[j] share a common factor greater than 1. Return the size of the largest connected component in the graph;
Based on the above question, please create a class **CCN** in Python language with the attribute **nums**; then create a class **SN_CCN** that inherits from the **CCN** class, and add a public function **Connected_components** to return the size of the largest connected component in the graph. | [
"assert candidate([4,6,15,35])==4",
"assert candidate([20,50,9,63])==2",
"assert candidate([2,3,6,7,4,12,21,39])==8"
] | def test_run(content1):
return SN_CCN(content1).Connected_components() | test_run | assert candidate([['class CCN', 'class SN_CCN(CCN)', 'super().__init__(nums)', 'def Connected_components']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/337 | Question: Given an integer array **arr** of even length, return True if **arr** can be rearranged to satisfy for each 0<=i<len(arr)/2, arr[2*i+1]=2*arr[2*i]; otherwise, return False.
Please create a class **RSF** with the attribute **arr** in Python based on the above question. Then create another class **SN_RSF** that inherits from the **RSF** class, and add a public function **Reorganization_satisfaction** that returns the corresponding result. | [
"assert candidate([3,1,3,6])==False",
"assert candidate([2,1,2,6])==False",
"assert candidate([4,-2,2,-4])==True"
] | def test_run(content1):
return SN_RSF(content1).Reorganization_satisfaction() | test_run | assert candidate([['class RSF', 'class SN_RSF(RSF)', 'super().__init__(arr)', 'def Reorganization_satisfaction']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/338 | Question: Given an array **strs** composed of **n** strings, where each string is of equal length. Select a deletion index sequence, for each string in **strs**, delete the character at each corresponding index. Suppose, we have chosen a set of deletion indices **answer**, then after performing the deletion operation, the elements of the final array are arranged in lexicographical order (strs[0]<=strs[1]<=strs[2]...<=strs[n-1]), then please return the smallest possible value of answer.length;
Based on the above question, please create a class **MPL** in Python language with the attribute **strs**; then create a class **SN_MPL** that inherits the **MPL** class, and add a public function **Minimum_possible** to return the smallest possible value of answer.length. | [
"assert candidate([\"ca\",\"bb\",\"ac\"])==1",
"assert candidate([\"xc\",\"yb\",\"za\"])==0",
"assert candidate([\"zyx\",\"wvu\",\"tsr\"])==3"
] | def test_run(content1):
return SN_MPL(content1).Minimum_possible() | test_run | assert candidate([['class MPL', 'class SN_MPL(MPL)', 'super().__init__(strs)', 'def Minimum_possible']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/339 | Question: You are installing a billboard and want it to be as high as possible. This billboard will have two steel brackets, one on each side. The height of each steel bracket must be equal. You have a pile of **rods** that can be welded together. For example, if the lengths of the rods are 1, 2, and 3, they can be welded together to form a bracket of length 6. Return the maximum possible installation height of the billboard. If the billboard cannot be installed, please return 0;
Please create a class called **IBD** in Python based on the above problem, with the attribute **rods**; then create a class **SN_IBD** that inherits from the **IBD** class, and add a public function **Install_billboards** that returns the maximum possible installation height of the billboard. If the billboard cannot be installed, please return 0. | [
"assert candidate([1,2,3,6])==6",
"assert candidate([1,2,3,4,5,6])==10",
"assert candidate([1,2])==0"
] | def test_run(content1):
return SN_IBD(content1).Install_billboards() | test_run | assert candidate([['class IBD', 'class SN_IBD(IBD)', 'super().__init__(rods)', 'def Install_billboards']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/340 | Question: In an nxn grid composed of 1x1 squares, each 1x1 square is made up of '/', '\' or a space. These characters divide the square into some regions with common edges. Given the grid represented as an array of strings, return the number of regions;
Please create a class **NAS** in Python based on the above question, with the attribute **grid**; then create a class **SN_NAS** that inherits from the **NAS** class, and add a public function **Number_areas** that returns the number of regions. | [
"assert candidate([\" /\",\"/ \"])==2",
"assert candidate([\" /\",\" \"])==1",
"assert candidate([\"/\\\",\"\\/\"])==5"
] | def test_run(content1):
return SN_NAS(content1).Number_areas() | test_run | assert candidate([['class NAS', 'class SN_NAS(NAS)', 'super().__init__(grid)', 'def Number_areas']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/341 | Question: Given an array of **strs** composed of **n** lowercase letter strings, where each string is of equal length. Select a deletion index sequence, and for each string in **strs**, delete the character at each corresponding index. For example, if strs = ["abcdef", "uvwxyz"], and the deletion index sequence is {0,2,3}, the result after deletion would be ["bef", "vyz"]. Suppose we have chosen a set of deletion indices **answer**, then after performing the deletion operation, each element in the row of the final array is sorted in dictionary order (i.e., (strs[0][0]<=strs[0][1]<=...<=strs[0][strs[0].length-1]) and (strs[1][0]<=strs[1][1]<=...<=strs[1][strs[1].length-1]), and so on). Please return the smallest possible value of answer.length;
Based on the above question, please create a class **MSI** in Python language with the property **strs**; then create a class **SN_MSI** that inherits from the **MSI** class, and add a public function **Minimum_spossible** that returns the smallest possible value of answer.length. | [
"assert candidate([\"babca\",\"bbazb\"])==3",
"assert candidate([\"edcba\"])==4",
"assert candidate([\"ghi\",\"def\",\"abc\"])==0"
] | def test_run(content1):
return SN_MSI(content1).Minimum_spossible() | test_run | assert candidate([['class MSI', 'class SN_MSI(MSI)', 'super().__init__(strs)', 'def Minimum_spossible']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/342 | Question: Given an integer array **A**, a slope is a tuple (i, j), where i < j and A[i] <= A[j]. The width of such a slope is j-i. Find the maximum width of the slope in **A**, if it does not exist, return 0.
Please create a class **WSP** in Python language based on the above question, with the attribute **A**. Then create another class **SN_WSP**, inheriting from the **WSP** class, and add a public function **Width_slope** to find the maximum width of the slope in **A**, if it does not exist, return 0. | [
"assert candidate([6,0,8,2,1,5])==4",
"assert candidate([9,8,1,0,1,9,4,0,4,1])==7"
] | def test_run(content1):
return SN_WSP(content1).Width_slope() | test_run | assert candidate([['class WSP', 'class SN_WSP(WSP)', 'super().__init__(A)', 'def Width_slope']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/343 | Question: Given a set of points **drop** on the **xy** plane, determine the minimum area of any rectangle formed by these points, where the sides of the rectangle are not necessarily parallel to the x-axis and y-axis. If there are no rectangles, return 0;
Based on the above question, please create a class **ARE** in Python language with the property **drop**; then create a class **SN_ARE** that inherits from the **ARE** class, and add a public function **Any_rectangle** to return the minimum area of any rectangle formed. If there are no rectangles, return 0. | [
"assert candidate([[1,2],[2,1],[1,0],[0,1]])==2.00000",
"assert candidate([[0,1],[2,1],[1,1],[1,0],[2,0]])==1.00000",
"assert candidate([[0,3],[1,2],[3,1],[1,3],[2,1]])==0",
"assert candidate([[3,1],[1,1],[0,1],[2,1],[3,3],[3,2],[0,2],[2,3]])==2.00000"
] | def test_run(content1):
return SN_ARE(content1).Any_rectangle() | test_run | assert candidate([['class ARE', 'class SN_ARE(ARE)', 'super().__init__(drop)', 'def Any_rectangle']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/344 | Question: Given a positive integer **x**, we will write an expression of the form x(op1)x(op2)x(op3)x..., where each operator op1, op2, ... can be one of addition, subtraction, multiplication, or division (+, -, *, or /). For example, for x=3, we can write the expression 3*3/3+3-3, which equals 3. When writing such expressions, we need to follow these conventions:
1. The division operator (/) returns a rational number; 2. There are no parentheses anywhere; 3. We use the usual order of operations: multiplication and division occur before addition and subtraction; 4. The unary negation operator (-) is not allowed. For example, **x-x** is a valid expression because it only uses subtraction, but **-x+x** is not because it uses the negation operator. We want to write an expression that equals a given **target** value and uses the fewest operators. Return the minimum number of operators used.
Based on the above question, please create a class **MNOOT** in Python with the attribute **x**; then create a class **SN_MNOOT** that inherits from the **MNOOT** class, and add a target attribute and a public function **minimum_operators** that returns the minimum number of operators used. | [
"assert candidate(3,19)==5",
"assert candidate(5,501)==8",
"assert candidate(100,100000000)==3"
] | def test_run(content1,content2):
return SN_MNOOT(content1,content2).minimum_operators==5() | test_run | assert candidate([['class MNOOT', 'class SN_MNOOT(MNOOT)', 'super().__init__(x)', 'def minimum_operators']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/345 | Question: Return all non-negative integers of length **n** such that the absolute difference between the digits in every two consecutive positions is **k**;
Please create a class **NIG** in Python language based on the above question, with the attribute **n**. Then create a class **SN_NIG** that inherits from the **NIG** class, and add the attribute **k**, as well as a public function **nonnegative_integer** to return the result of the above question. | [
"assert candidate(3,7)==[181,292,707,818,929]",
"assert candidate(2,1)==[10,12,21,23,32,34,43,45,54,56,65,67,76,78,87,89,98]",
"assert candidate(2,0)==[11,22,33,44,55,66,77,88,99]",
"assert candidate(2,2)==[13,20,24,31,35,42,46,53,57,64,68,75,79,86,97]"
] | def test_run(content1,content2):
return SN_NIG(content1,content2).nonnegative_integer() | test_run | assert candidate([['class NIG', 'class SN_NIG(NIG)', 'super().__init__(n)', 'def nonnegative_integer']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/346 | Question: Given an integer array **arr**, please sort the array using pancake flipping. The execution process of a pancake flip is as follows:
1. Choose an integer **k**, where 1<=k<=arr.length; 2. Reverse the sub-array arr[0...k-1] (index starts from 0); Return the sequence of **k** values corresponding to the pancake flipping operations that can sort **arr** in the form of an array. Any valid answer that sorts the array and the number of flips is within the range of 10*arr.length will be judged as correct;
Based on the above question, please create a class **PFG** in Python language with the property **arr**; then create a class **SN_PFG** that inherits the **PFG** class, and add a public function **Pancake_flipping** to return the sequence of **k** values corresponding to the pancake flipping operations that can sort the integer array **arr** in the form of an array. | [
"assert candidate([3,2,4,1])==[4,2,4,3]",
"assert candidate([1,2,3])==[]"
] | def test_run(content1):
return SN_PFG(content1).Pancake_flipping() | test_run | assert candidate([['class PFG', 'class SN_PFG(PFG)', 'super().__init__(arr)', 'def Pancake_flipping']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/347 | Question: Given three integers **x**, **y**, and **bound**, return a list of all powerful integers that are less than or equal to **bound**;
Based on the above question, please create a class **SIG** in Python with the attribute **x**; then create a class **SN_SIG** that inherits from the **SIG** class, and add two attributes **y** and **bound**, as well as a public function **Strong_integer** to return a list of all powerful integers that are less than or equal to **bound**. | [
"assert candidate(2,3,10)==[2,3,4,5,7,9,10]",
"assert candidate(3,5,15)==[2,4,6,8,10,14]"
] | def test_run(content1,content2,content3):
return SN_SIG(content1,content2,content3).Strong_integer() | test_run | assert candidate([['class SIG', 'class SN_SIG(SIG)', 'super().__init__(x)', 'def Strong_integer']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/348 | Question: Given two strings **s** and **t**, each string represents a non-negative rational number, return True only when they represent the same number;
Based on the above question, please create a class **SNR** in Python with the attribute **s**; then create another class **SN_SNR** inheriting from the **SNR** class, adding the attribute **t**, as well as a public function **Same_number** to return the result of the above question. | [
"assert candidate(\"0.(52)\",\"0.5(25)\")==True",
"assert candidate(\"0.1666(6)\",\"0.166(66)\")==True",
"assert candidate(\"0.9(9)\",\"1.\")==True"
] | def test_run(content1,content2):
return SN_SNR(content1,content2).() | test_run | assert candidate([['class SNR', 'class SN_SNR(SNR)', 'super().__init__(s)', 'def Same_number']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/349 | Question: Given an array **points**, where points[i] = [x_i, y_i] represents a point on the X-Y plane, and an integer **k**, return the **k** points closest to the origin (0,0);
Based on the above question, create a class **NOG** in Python, with the attribute **points**; then create a class **SN_NOG** that inherits from the **NOG** class, and add the attribute **k**, as well as a public function **Nearest_origin** to return the **k** points closest to the origin (0,0). | [
"assert candidate([[1,3],[-2,2]],1)==[[-2,2]]",
"assert candidate([[3,3],[5,-1],[-2,4]],2)==[[3,3],[-2,4]]"
] | def test_run(content1,content2):
return SN_NOG(content1,content2).Nearest_origin() | test_run | assert candidate([['class NOG', 'class SN_NOG(NOG)', 'super().__init__(points)', 'def Nearest_origin']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/350 | Question: Given an integer array **nums** and an integer **k**, return the number of (continuous, non-empty) sub-arrays whose sum of elements can be divided by **k**.
Please create a class **SET** in Python language based on the above question, which has the attribute **nums**. Then create another class **SN_SET**, inheriting from the **SET** class, and add the attribute **k**, as well as a public function **Sum_Elements** to return the number of (continuous, non-empty) sub-arrays in the integer array **nums** whose sum of elements can be divided by **k**. | [
"assert candidate([4,5,0,-2,-3,1],5)==7",
"assert candidate([5],9)==0"
] | def test_run(content1,content2):
return SN_SET(content1,content2).Sum_Elements() | test_run | assert candidate([['class SET', 'class SN_SET(SET)', 'super().__init__(nums)', 'def Sum_Elements']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/351 | Question: Given an integer array **A**, you can start from a certain index and make a certain number of jumps. During your jumping process, the 1-th, 3-th, 5-th... jumps are called odd jumps, while the 2-th, 4-th, 6-th... jumps are called even jumps. You can jump from index **i** to index **j** (where **i < j**) in the following ways:
1. During an odd jump (e.g., the 1-th, 3-th, 5-th... jumps), you will jump to index **j** such that A[i] <= A[j], and A[j] is the smallest possible value. If there are multiple such indexes **j**, you can only jump to the smallest index **j** that meets the requirement.
2. During an even jump (e.g., the 2-th, 4-th, 6-th... jumps), you will jump to index **j** such that A[i] >= A[j], and A[j] is the largest possible value. If there are multiple such indexes **j**, you can only jump to the smallest index **j** that meets the requirement. (For some indexes **i**, it may not be possible to make a jump that meets the requirement.)
3. If you can reach the end of the array (index A.length-1) by making a certain number of jumps (possibly 0 or more) starting from a certain index, then that index is considered a good starting index. Return the number of good starting indexes.
Please create a class **SID** in Python language based on the above question, with the attribute **A**. Then create another class **SN_SID** that inherits the **SID** class, and add a public function **start_index** that returns the number of good starting indexes. | [
"assert candidate([10,13,12,14,15])==2",
"assert candidate([2,3,1,1,4])==3",
"assert candidate([5,1,3,4,2])==3"
] | def test_run(content1):
return SN_SID(content1).start_index() | test_run | assert candidate([['class SID', 'class SN_SID(SID)', 'super().__init__(A)', 'def start_index']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/352 | Question: Given an integer array **arr**, return the length of the maximum **turbulence subarray** in **arr**. A subarray is a **turbulence subarray** if the comparison sign flips between each pair of adjacent elements in the subarray;
Based on the above question, create a class **MTL** in Python, which has the attribute **arr**; then create another class **SN_MTL** that inherits from the **MTL** class, and add a public function **Maximum_turbulence** that returns the length of the maximum **turbulence subarray** in **arr**. | [
"assert candidate([9,4,2,10,7,8,8,1,9])==5",
"assert candidate([4,8,12,16])==2",
"assert candidate([100])==1"
] | def test_run(content1):
return SN_MTL(content1).Maximum_turbulence() | test_run | assert candidate([['class MTL', 'class SN_MTL(MTL)', 'super().__init__(arr)', 'def Maximum_turbulence']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/353 | Question: On a two-dimensional grid **grid**, there are 4 types of squares:
**1** represents the starting square, and there is only one starting square; **2** represents the ending square, and there is only one ending square; **0** represents the empty square that we can walk through; **-1** represents the obstacle that we cannot cross. Return the number of different paths from the starting square to the ending square when walking in four directions (up, down, left, and right);
Based on the above question, please create a class **DPS** using Python language, with the attribute **grid**; then create a class **SN_DPS** that inherits the **DPS** class, and add a public function **Different_paths** to return the result of the above question. | [
"assert candidate([[1,0,0,0],[0,0,0,0],[0,0,2,-1]])==2",
"assert candidate([[1,0,0,0],[0,0,0,0],[0,0,0,2]])==4",
"assert candidate([[0,1],[2,0]])==0"
] | def test_run(content1):
return SN_DPS(content1).Different_paths() | test_run | assert candidate([['class DPS', 'class SN_DPS(DPS)', 'super().__init__(grid)', 'def Different_paths']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/354 | Question: Given an integer array **nums**, return the number of bitwise AND triplets. A bitwise AND triplet is a triplet made up of indices (i, j, k) that satisfy all of the following conditions:
1. 0<=i<nums.length; 2. 0<=j<nums.length; 3. 0<=k<nums.length; 4. nums[i]&nums[j]&nums[k]==0, where & represents the bitwise AND operator;
Based on the above question, create a class **BTT** using Python language, with the attribute **nums**; then create a class **SN_BTT** that inherits from the **BTT** class, and add a public function **Bitwise_triplet** that returns the number of bitwise AND triplets. | [
"assert candidate([2,1,3])==12",
"assert candidate([0,0,0])==27"
] | def test_run(content1):
return SN_BTT(content1).Bitwise_triplet() | test_run | assert candidate([['class BTT', 'class SN_BTT(BTT)', 'super().__init__(nums)', 'def Bitwise_triplet']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/355 | Question: Given two integers a and b, return any string s that satisfies the following conditions:
1. The length of s is a+b, and it contains exactly a occurrences of the letter 'a' and b occurrences of the letter 'b'.
2. The substring 'aaa' does not appear in s.
3. The substring 'bbb' does not appear in s.
Please create a class **ASG** in Python that has an attribute **a**. Then create a class **SN_ASG** that inherits from **ASG** and adds an attribute **b**, as well as a public function **Any_string** that returns the result of the above problem. | [
"assert candidate(1,2)==\"abb\"",
"assert candidate(4,1)==\"aabaa\""
] | def test_run(content1,content2):
return SN_ASG(content1,content2).Any_string() | test_run | assert candidate([['class ASG', 'class SN_ASG(ASG)', 'super().__init__(a)', 'def Any_string']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/356 | Question: Given two lists composed of some closed intervals, **firstList** and **secondList**, where firstList[i]=[start_i,end_i] and secondList[j]=[start_j,end_j]. Each interval list is pairwise disjoint and already sorted. Return the intersection of these two interval lists;
Based on the above question, please create a class **ILT** in Python language with the property **firstList**; then create another class **SN_ILT**, inheriting from the **ILT** class, and add the property **secondList**, as well as a public function **Interval_List** to return the intersection of the above two interval lists. | [
"assert candidate([[0,2],[5,10],[13,23],[24,25]],[[1,5],[8,12],[15,24],[25,26]])==[[1,2],[5,5],[8,10],[15,23],[24,24],[25,25]]",
"assert candidate([[1,3],[5,9]],[])==[]",
"assert candidate([],[[4,8],[10,12]])==[]",
"assert candidate([[1,7]],[[3,10]])==[[3,7]]"
] | def test_run(content1,content2):
return SN_ILT(content1,content2).Interval_List() | test_run | assert candidate([['class ILT', 'class SN_ILT(ILT)', 'super().__init__(firstList)', 'def Interval_List']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/357 | Question: Given an array composed of string equations that represent the relationships between variables, each string equation equations[i] has a length of 4 and takes one of two different forms: **a==b** or **a!=b**. Here, a and b are lowercase letters (not necessarily different), representing single-letter variable names. Return True only when integers can be assigned to variable names to satisfy all given equations, otherwise return False;
Based on the above question, please create a class **SVE** in Python language with the attribute **equations**; then create another class **SN_SVE** that inherits from the **SVE** class, and add a public function **Single_variable** that returns the result of the above question. | [
"assert candidate([\"a==b\",\"b!=a\"])==False",
"assert candidate([\"b==a\",\"a==b\"])==True",
"assert candidate([\"a==b\",\"b==c\",\"a==c\"])==True",
"assert candidate([\"a==b\",\"b!=c\",\"c==a\"])==False",
"assert candidate([\"c==c\",\"b==d\",\"x!=z\"])==True"
] | def test_run(content1):
return SN_SVE(content1).Single_variable() | test_run | assert candidate([['class SVE', 'class SN_SVE(SVE)', 'super().__init__(equations)', 'def Single_variable']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/358 | Question: On a broken calculator displaying the number **startValue**, we can perform the following two operations:
1. Double: Multiply the number on the display by 2; 2. Decrement: Subtract 1 from the number on the display. Given two integers, **startValue** and **target**, return the minimum number of operations required to display the number **target**.
Based on the above question, please create a class **MOS** in Python, with the attribute **startValue**. Then create another class **SN_MOS**, inheriting from the **MOS** class, and add the attribute **target**, as well as a public function **Minimum_operands** that returns the minimum number of operations required to display the number **target**. | [
"assert candidate(2,3)==2",
"assert candidate(5,8)==2",
"assert candidate(3,10)==3"
] | def test_run(content1,content2):
return SN_MOS(content1,content2).Minimum_operands() | test_run | assert candidate([['class MOS', 'class SN_MOS(MOS)', 'super().__init__(startValue)', 'def Minimum_operands']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/359 | Question: Given a positive integer array **nums** and an integer **k**, return the number of good sub-arrays in nums. If the number of different integers in a sub-array of nums is exactly **k**, then this continuous, not necessarily different sub-array of **nums** is called a good sub-array;
Based on the above question, create a class **GAR** in Python language with the attribute **nums**; then create a class **SN_GAR**, inheriting from the **GAR** class, and add the attribute **k**, as well as a public function **Good_array** to return the number of good sub-arrays in **nums**. | [
"assert candidate([1,2,1,2,3],2)==7",
"assert candidate([1,2,1,3,4],3)==3"
] | def test_run(content1,content2):
return SN_GAR(content1,content2).Good_array() | test_run | assert candidate([['class GAR', 'class SN_GAR(GAR)', 'super().__init__(nums)', 'def Good_array']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/360 | Question: In the given m x n grid **grid**, each cell can have one of the following three values:
1. Value 0 represents an empty cell.
2. Value 1 represents a fresh orange.
3. Value 2 represents a rotten orange.
Every minute, a rotten orange will make any fresh orange in the four adjacent directions rot. Return the minimum number of minutes required to make all the oranges rotten. If it is impossible, return -1.
Please create a class **MME** in Python based on the above question, with a **grid** attribute. Then create a class **SN_MME** that inherits from the **MME** class and add a public function **Min_Minutes** to return the result of the above question. | [
"assert candidate([[2,1,1],[1,1,0],[0,1,1]])==4",
"assert candidate([[2,1,1],[0,1,1],[1,0,1]])==-1",
"assert candidate([[0,2]])==0"
] | def test_run(content1):
return SN_MME(content1).Min_Minutes() | test_run | assert candidate([['class MME', 'class SN_MME(MME)', 'super().__init__(grid)', 'def Min_Minutes']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/361 | Question: Given a binary array **nums** and an integer **k**, return the minimum number of k-bit flips required for the array to have no zeros. If it's not possible, return -1. A k-bit flip means choosing a subarray of length **k** from nums, and simultaneously changing every 0 in the subarray to 1, and every 1 in the subarray to 0;
Based on the above question, create a class **MFI** in Python, which has the attribute **nums**. Then create another class **SN_MFI**, inheriting from the **MFI** class, and add the attribute **K**, as well as a public function **Min_Flip** that returns the result of the above problem. | [
"assert candidate([0,1,0],1)==2",
"assert candidate([1,1,0],2)==-1",
"assert candidate([0,0,0,1,0,1,1,0],3)==3"
] | def test_run(content1,content2):
return SN_MFI(content1,content2).Min_Flip() | test_run | assert candidate([['class MFI', 'class SN_MFI(MFI)', 'super().__init__(nums)', 'def Min_Flip']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/362 | Question: Given a non-negative integer array **A**, if the sum of every pair of adjacent elements is a perfect square, then this array is called a square array. Return the number of square arrangements of **A**.
Please create a **SAT** class based on the above question, with the attribute **A**; then create a **SN_SAT** class, inheriting the **SAT** class, and add a public **Square_arrangement** function to return the number of square arrangements of A. | [
"assert candidate([1,17,8])==2",
"assert candidate([2,2,2])==1"
] | def test_run(content1):
return SN_SAT(content1).Square_arrangement() | test_run | assert candidate([['class SAT', 'class SN_SAT(SAT)', 'super().__init__(A)', 'def Square_arrangement']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/363 | Question: There are **n** piles of stones arranged in a row, with stones[i] stones in the i-th pile. Each move requires merging **k** consecutive piles of stones into one pile, and the cost of this move is the total number of stones in these **k** piles. Return the lowest cost to merge all the stones into one pile. If it is impossible to merge into one pile, return -1;
Based on the above question, create a class **SMG** using Python language, with the attribute **stones**; then create a class **SN_SMG** that inherits the **SMG** class, and add the attribute **K**, as well as a public function **Stone_Merge** that returns the result of the above question. | [
"assert candidate([3,2,4,1],2)==20",
"assert candidate([3,2,4,1],3)==-1",
"assert candidate([3,5,1,2,6],3)==25"
] | def test_run(content1,content2):
return SN_SMG(content1,content2).Stone_Merge() | test_run | assert candidate([['class SMG', 'class SN_SMG(SMG)', 'super().__init__(stones)', 'def Stone_Merge']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/364 | Question: In a row of dominoes, tops[i] and bottoms[i] represent the top and bottom halves of the i-th domino respectively. (A domino is formed by two numbers from 1 to 6 arranged in columns - each half of the tile has a number.) We can rotate the i-th domino so that the values of tops[i] and bottoms[i] are swapped. Return the minimum number of rotations that can make all values in **tops** or all values in **bottoms** the same. If it is impossible, return -1;
Based on the above question, please create a class **DMS** in Python with the attribute **tops**; then create another class **SN_DMS** that inherits from the **DMS** class, and add the attribute **bottoms**, as well as a public function **Dominoes** to return the result of the above question. | [
"assert candidate([2,1,2,4,2,2],[5,2,6,2,3,2])==2",
"assert candidate([3,5,1,2,3],[3,6,3,3,4])==-1"
] | def test_run(content1,content2):
return SN_DMS(content1,content2).Dominoes() | test_run | assert candidate([['class DMS', 'class SN_DMS(DMS)', 'super().__init__(tops)', 'def Dominoes']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/365 | Question: In the song list, the duration of the i-th song is time[i] seconds. Return the number of song pairs whose total duration (in seconds) can be divided by 60;
Based on the above question, please create a class **TDN** in Python, with the attribute **time**; then create another class **SN_TDN**, inheriting from the **TDN** class, and add a public function **Total_duration** to return the number of song pairs whose total duration (in seconds) can be divided by 60. | [
"assert candidate([30,20,150,100,40])==3",
"assert candidate([60,60,60])==3"
] | def test_run(content1):
return SN_TDN(content1).Total_duration() | test_run | assert candidate([['class TDN', 'class SN_TDN(TDN)', 'super().__init__(time)', 'def Total_duration']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/366 | Question: The packages on the **conveyor belt** must be transported from one port to another within **days**. The weight of the i-th package on the conveyor belt is weights[i]. Every day, we load packages onto the conveyor belt in the order of the given weights. The weight we load will not exceed the maximum carrying weight of the ship. Return the minimum carrying capacity of the ship that can deliver all the packages on the conveyor belt within **days**;
Based on the above question, please use Python to create a class **MCG** with the attribute **weights**; then create a class **SN_MCG** that inherits from the **MCG** class, and add the attribute **days**, as well as a public function **Minimum_carrying** to return the minimum carrying capacity of the ship that can deliver all the packages on the conveyor belt within **days**. | [
"assert candidate([1,2,3,4,5,6,7,8,9,10],5)==15",
"assert candidate([3,2,2,4,1,4],3)==6",
"assert candidate([1,2,3,1,1],4)==3"
] | def test_run(content1,content2):
return SN_MCG(content1,content2).Minimum_carrying() | test_run | assert candidate([['class MCG', 'class SN_MCG(MCG)', 'super().__init__(weights)', 'def Minimum_carrying']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/367 | Question: Given a positive integer **n**, return the number of positive integers within the range [1, n] that have at least one repeating digit;
Based on the above question, please create a class called **RNS** in Python, with an attribute **n**. Then create another class **SN_RNS** that inherits from the **RNS** class, and add a public function **Repeating_numbers** that returns the result of the above question. | [
"assert candidate(20)==1",
"assert candidate(100)==10",
"assert candidate(1000)==262"
] | def test_run(content1):
return SN_RNS(content1).Repeating_numbers() | test_run | assert candidate([['class RNS', 'class SN_RNS(RNS)', 'super().__init__(n)', 'def Repeating_numbers']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/368 | Question: Given a positive integer array **values**, where values[i] represents the rating of the i-th sightseeing spot, and the distance between two spots i and j is j-i. The score of a sightseeing combination of a pair of spots (i<j) is values[i]+values[j]+i-j, which is the sum of the ratings of the spots minus the distance between them. Return the highest score that a pair of sightseeing spots can achieve;
Based on the above question, please create a class **SCT** in Python language with the attribute **values**; then create a class **SN_SCT** that inherits the **SCT** class, and add a public function **Sightseeing_combination** that returns the highest score that a pair of sightseeing spots can achieve. | [
"assert candidate([8,1,5,2,6])==11",
"assert candidate([1,2])==2"
] | def test_run(content1):
return SN_SCT(content1).Sightseeing_combination() | test_run | assert candidate([['class SCT', 'class SN_SCT(SCT)', 'super().__init__(values)', 'def Sightseeing_combination']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/369 | Question: Given a positive integer **k**, you need to find the length of the smallest positive integer **n** that can be divided by **k** and only contains the digit 1. Return the length of **n**. If there is no such **n**, return -1;
Based on the above question, please create a class **MIR** in Python with the attribute **k**; then create a class **SN_MIR** that inherits the **MIR** class, and add a public function **Minimum_integer** to return the result of the above question. | [
"assert candidate(1)==1",
"assert candidate(2)==-1",
"assert candidate(3)==3"
] | def test_run(content1):
return SN_MIR(content1).Minimum_integer() | test_run | assert candidate([['class MIR', 'class SN_MIR(MIR)', 'super().__init__(k)', 'def Minimum_integer']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/370 | Question: Given a binary string **s** and a positive integer **n**, return True if the binary representation of every integer in the range [1, n] is a substring of **s**, otherwise return False;
Please create a class **ETG** in Python language based on the above question, with the attribute **s**. Then create a class **SN_ETG** that inherits from the **ETG** class, add the attribute **n**, and a public function **Each_integer** that returns the result of the above question. | [
"assert candidate(\"0110\",3)==True",
"assert candidate(\"0110\",4)==False"
] | def test_run(content1,content2):
return SN_ETG(content1,content2).Each_integer() | test_run | assert candidate([['class ETG', 'class SN_ETG(ETG)', 'super().__init__(s)', 'def Each_integer']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/371 | Question: Given an integer **n**, return its negative binary (base-2) representation in the form of a binary string;
Based on the above question, create a class **NGY** in Python language with the attribute **n**; then create a class **SN_NGY** that inherits from the **NGY** class, and add a public function **negabinary** to return the negative binary (base-2) representation of the integer **n** in the form of a binary string. | [
"assert candidate(2)==\"110\"",
"assert candidate(3)==\"111\"",
"assert candidate(4)==\"100\""
] | def test_run(content1):
return SN_NGY(content1).negabinary() | test_run | assert candidate([['class NGY', 'class SN_NGY(NGY)', 'super().__init__(n)', 'def negabinary']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/372 | Question: Given a linked list of length **n**, **head**. For each node in the list, find the value of the next larger node. That is, for each node, find the value of the first node next to it, the value of this node is strictly greater than its value. Return an integer array **answer**, where answer[i] is the value of the next larger node of the i-th node (starting from 1). If the i-th node does not have a next larger node, set answer[i]=0;
Based on the above question, please create a class **LNS** in Python, with the attribute **head**; then create a class **SN_LNS** that inherits the **LNS** class, and add a public function **Larger_nodes** to return the result of the above question. | [
"assert candidate([2,1,5])==[5,5,0]",
"assert candidate([2,7,4,3,5])==[7,0,5,5,0]"
] | def test_run(content1):
return SN_LNS(content1).Larger_nodes() | test_run | assert candidate([['class LNS', 'class SN_LNS(LNS)', 'super().__init__(head)', 'def Larger_nodes']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/373 | Question: Given a binary matrix grid of size m x n, where 0 represents an ocean cell and 1 represents a land cell. A move is defined as moving from one land cell to another adjacent (up, down, left, right) land cell or crossing the border of the **grid**. Return the number of land cells in the grid that cannot leave the grid border in any number of moves;
Please create a class **LCL** in Python based on the above question, with the attribute **grid**. Then create a class **SN_LCL** that inherits from the **LCL** class, and add a public function **Land_Cell** to return the number of land cells in the grid that cannot leave the grid border in any number of moves. | [
"assert candidate([[0,0,0,0],[1,0,1,0],[0,1,1,0],[0,0,0,0]])==3",
"assert candidate([[0,1,1,0],[0,0,1,0],[0,0,1,0],[0,0,0,0]])==0"
] | def test_run(content1):
return SN_LCL(content1).Land_Cell() | test_run | assert candidate([['class LCL', 'class SN_LCL(LCL)', 'super().__init__(grid)', 'def Land_Cell']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/374 | Question: Given a string array **queries** and a string representing a **pattern**, return a boolean array **answer**. Only when the query item queries[i] matches the pattern string pattern, answer[i] is True, otherwise it is False;
Based on the above question, please create a class **BAY** in Python with the property **queries**; then create a class **SN_BAY** that inherits from the **BAY** class, and add the property **pattern**, as well as a public function **boolean_array** that returns the above results. | [
"assert candidate([\"FooBar\",\"FooBarTest\",\"FootBall\",\"FrameBuffer\",\"ForceFeedBack\"],\"FB\")==[True,False,True,True,False]",
"assert candidate([\"FooBar\",\"FooBarTest\",\"FootBall\",\"FrameBuffer\",\"ForceFeedBack\"],\"FoBa\")==[True,False,True,False,False]",
"assert candidate([\"FooBar\",\"FooBarTest\",\"FootBall\",\"FrameBuffer\",\"ForceFeedBack\"],\"FoBaT\")==[False,True,False,False,False]"
] | def test_run(content1,content2):
return SN_BAY(content1,content2).boolean_array() | test_run | assert candidate([['class BAY', 'class SN_BAY(BAY)', 'super().__init__(queries)', 'def boolean_array']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/375 | Question: Given an integer array **nums**, return the length of the longest arithmetic subsequence in **nums**;
Based on the above question, create a class **LSQ** using Python language, with the attribute **nums**. Then create another class **SN_LSQ**, inheriting from the **LSQ** class, and add a public function **Longest_subsequence** to return the length of the longest arithmetic subsequence in the integer array **nums**. | [
"assert candidate([3,6,9,12])==4",
"assert candidate([9,4,7,2,10])==3",
"assert candidate([20,1,15,3,10,5,8])==4"
] | def test_run(content1):
return SN_LSQ(content1).Longest_subsequence() | test_run | assert candidate([['class LSQ', 'class SN_LSQ(LSQ)', 'super().__init__(nums)', 'def Longest_subsequence']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/376 | Question: The company plans to interview 2n people. Given an array **costs**, where costs[i]=[aCosti,bCosti]. The cost for the i-th person to fly to city **a** is **aCost_i**, and the cost to fly to city **b** is **bCost_i**. Return the minimum cost to fly each person to either city **a** or **b**, with the requirement that **n** people must arrive in each city;
Based on the above question, create a class **MCT** in Python language with the attribute **costs**; then create a class **SN_MCT** that inherits from the **MCT** class, and add a public function **Minimum_cost** to return the result of the above question. | [
"assert candidate([[10,20],[30,200],[400,50],[30,20]])==110",
"assert candidate([[259,770],[448,54],[926,667],[184,139],[840,118],[577,469]])==1859",
"assert candidate([[515,563],[451,713],[537,709],[343,819],[855,779],[457,60],[650,359],[631,42]])==3086"
] | def test_run(content1):
return SN_MCT(content1).Minimum_cost() | test_run | assert candidate([['class MCT', 'class SN_MCT(MCT)', 'super().__init__(costs)', 'def Minimum_cost']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/377 | Question: Given an integer array **nums** and two integers **firstLen** and **secondLen**, you are to find and return the maximum sum of elements in two non-overlapping subarrays, with lengths respectively as **firstLen** and **secondLen**;
Based on the above question, create a class **OSR** in Python with the attribute **nums**; then create another class **SN_OSR** that inherits from the **OSR** class, and add two attributes **firstLen** and **secondLen**, as well as a public function **overlapping_subarray** that returns the result of the above question. | [
"assert candidate([0,6,5,2,2,5,1,9,4],1,2)==20",
"assert candidate([3,8,1,3,2,1,8,9,0],3,2)==29",
"assert candidate([2,1,5,6,0,9,5,0,3,8],4,3)==31"
] | def test_run(content1,content2,content3):
return SN_OSR(content1,content2,content3).overlapping_subarray() | test_run | assert candidate([['class OSR', 'class SN_OSR(OSR)', 'super().__init__(nums)', 'def overlapping_subarray']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/378 | Question: Three stones are placed on the number line at positions **a**, **b**, and **c**. In each round, you can pick up a stone from one of the ends (either the largest or smallest position) and place it in any free position between the two ends. Formally, suppose the three stones are currently at positions **x**, **y**, and **z** with x<y<z. Then you can pick up a stone from position **x** or **z** and move it to an integer position **k**, where x<k<z and k!=y. The game ends when you can't make any more moves, i.e., when the positions of the stones are consecutive. What are the minimum and maximum number of moves you can make to end the game? Return the answer in the form of a 2-length array: answer=[minimum_moves,maximum_moves];
Based on the above question, please create a class **SMT** in Python with an attribute **a**; then create a class **SN_SMT** that inherits from the **SMT** class, and add two attributes **b** and **c**, as well as a public function **Stone_movement** that returns the result of the above question. | [
"assert candidate(1,2,5)==[1, 2]",
"assert candidate(4,3,2)==[0, 0]"
] | def test_run(content1,content2,content3):
return SN_SMT(content1,content2,content3).Stone_movement() | test_run | assert candidate([['class SMT', 'class SN_SMT(SMT)', 'super().__init__(a)', 'def Stone_movement']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/379 | Question: Write down the integers in **nums1** and **nums2** in the given order on two independent horizontal lines. Now, some lines can be drawn connecting the two numbers nums1[i] and nums2[j]. These lines need to satisfy the following conditions:
1. nums1[i] == nums2[j];
2. The drawn line does not intersect with any other lines (non-horizontal lines). Please note that the lines cannot intersect even at the endpoints: each number can only belong to one line. Draw lines in this way and return the maximum number of lines that can be drawn.
Please create a class called **MCT** in Python, which has the attribute **nums1**. Then create another class called **SN_MCT** that inherits from the **MCT** class, and add the attribute **nums2**, as well as a public function **max_connections** that returns the maximum number of lines that can be drawn. | [
"assert candidate([1,4,2],[1,2,4])==2",
"assert candidate([2,5,1,2,5],[10,5,2,1,5,2])==3",
"assert candidate([1,3,7,1,7,5],[1,9,2,5,1])==2"
] | def test_run(content1,content2):
return SN_MCT(content1,content2).max_connections() | test_run | assert candidate([['class MCT', 'class SN_MCT(MCT)', 'super().__init__(nums1)', 'def max_connections']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/380 | Question: In a 10^6x10^6 grid, the coordinates of each cell are (x,y). Now, starting from the source cell source=[sx,sy], the intention is to rush to the target cell target=[tx,ty]. The array blocked is a list of blocked cells, where each blocked[i]=[xi,yi] indicates that the cell with coordinates (xi,yi) is forbidden to pass. Each move can go to the cell adjacent in the four directions in the grid, as long as the cell is not on the given **blocked** list. Also, it is not allowed to go out of the grid. Only when it is possible to reach the target cell target from the source cell source through a series of moves, return True. Otherwise, return False;
Based on the above question, please create a class **SGD** in Python language with the attribute **blocked**; then create a class **SN_SGD**, inherit the **SGD** class, and add two attributes **source** and **target**, and a public function **Source_grid** to return the result of the above question. | [
"assert candidate([[0,1],[1,0]],[0,0],[0,2])==False",
"assert candidate([],[0,0],[999999,999999])==True"
] | def test_run(content1,content2,content3):
return SN_SGD(content1,content2,content3).Source_grid() | test_run | assert candidate([['class SGD', 'class SN_SGD(SGD)', 'super().__init__(blocked)', 'def Source_grid']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/381 | Question: You have a convex n-polygon, each vertex of which has an integer value. Given an integer array **values**, where values[i] is the value of the i-th vertex (i.e., in clockwise order). Assume the polygon is divided into n-2 triangles. For each triangle, the value of the triangle is the product of the vertex labels, and the score of the triangulation is the sum of the values of all n-2 triangles after the triangulation. Return the lowest score that can be obtained after the polygon is triangulated;
Based on the above question, please create a class **TGT** in Python, with the attribute **values**; then create a class **SN_TGT** that inherits from the **TGT** class, and add a public function **triangulation** that returns the lowest score that can be obtained after the polygon is triangulated. | [
"assert candidate([1,2,3])==6",
"assert candidate([3,7,4,5])==144",
"assert candidate([1,3,1,4,1,5])==13"
] | def test_run(content1):
return SN_TGT(content1).triangulation() | test_run | assert candidate([['class TGT', 'class SN_TGT(TGT)', 'super().__init__(values)', 'def triangulation']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/382 | Question: On an infinite plane, the robot initially stands at the point (0,0), facing north. Note:
1. North is the positive direction of the y-axis. 2. South is the negative direction of the y-axis. 3. East is the positive direction of the x-axis. 4. West is the negative direction of the x-axis. The robot can accept one of the following three instructions:
1. **G**: Go straight for 1 unit. 2. **L**: Turn left by 90 degrees. 3. **R**: Turn right by 90 degrees. The robot executes the **instructions** in order and repeats them indefinitely. Only when there is a loop in the plane that the robot can never leave, return True. Otherwise, return False;
Please create a class **EIT** in Python based on the above problem, with the property **instructions**; Then create a class **SN_EIT**, inheriting from the **EIT** class, and add a public function **Execute_instructions** to return the result of the above problem. | [
"assert candidate(\"GGLLGG\")==True",
"assert candidate(\"GG\")==False",
"assert candidate(\"GL\")==True"
] | def test_run(content1):
return SN_EIT(content1).Execute_instructions() | test_run | assert candidate([['class EIT', 'class SN_EIT(EIT)', 'super().__init__(instructions)', 'def Execute_instructions']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/383 | Question: There are **n** gardens, labeled from 1 to **n**. There is also an array **paths**, where paths[i] = [x_i, y_i] describes the bidirectional path from garden **x_i** to garden **y_i**. In each garden, you plan to plant one of four types of flowers. Moreover, each garden can have at most three paths leading in or out. You need to choose a type of flower for each garden so that the types of flowers in any two gardens connected by a path are different. Return any feasible solution as the answer **answer** in the form of an array, where answer[i] represents the type of flower planted in the (i+1)th garden. The types of flowers are represented by 1, 2, 3, and 4;
Based on the above question, create a class **PFS** in Python with the attribute **n**; then create a class **SN_PFS** that inherits from the **PFS** class, and add the attribute **paths**, as well as a public function **Planted_flowers** that returns the result of the above question. | [
"assert candidate(3,[[1,2],[2,3],[3,1]])==[1,2,3]",
"assert candidate(4,[[1,2],[3,4]])==[1,2,1,2]",
"assert candidate(4,[[1,2],[2,3],[3,4],[4,1],[1,3],[2,4]])==[1,2,3,4]"
] | def test_run(content1,content2):
return SN_PFS(content1,content2).Planted_flowers() | test_run | assert candidate([['class PFS', 'class SN_PFS(PFS)', 'super().__init__(n)', 'def Planted_flowers']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/384 | Question: Given an integer array **arr**, please divide this array into some (continuous) sub-arrays with a maximum length of **k**. After the division, all values in each sub-array will become the maximum value in that sub-array. Return the maximum sum of elements that can be obtained after the array is divided and transformed;
Based on the above question, create a class **STF** in Python language with the attribute **arr**; then create a class **SN_STF** that inherits the **STF** class, and add the attribute **k**, as well as a public function **Separation_transformation** that returns the maximum sum of elements that can be obtained after the array is divided and transformed. | [
"assert candidate([1,15,7,9,2,5,10],3)==84",
"assert candidate([1,4,1,5,7,3,6,1,9,9,3],4)==83",
"assert candidate([1],1)==4"
] | def test_run(content1,content2):
return SN_STF(content1,content2).Separation_transformation() | test_run | assert candidate([['class STF', 'class SN_STF(STF)', 'super().__init__(arr)', 'def Separation_transformation']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/385 | Question: Given a string **s**, consider all its repeated substrings: that is, the (continuous) substrings of **s** that appear 2 or more times in **s**. These appearances may overlap. Return any one of the possible longest repeated substrings. If **s** does not contain repeated substrings, then the answer is "";
Please create a class **RST** in Python language based on the above question, with the attribute **s**; then create another class **SN_RST** that inherits from the **RST** class, and add a public function **Repeated_substring** that returns the possible longest repeated substring. | [
"assert candidate(\"banana\")==\"ana\"",
"assert candidate(\"abcd\")==\"\""
] | def test_run(content1):
return SN_RST(content1).Repeated_substring() | test_run | assert candidate([['class RST', 'class SN_RST(RST)', 'super().__init__(s)', 'def Repeated_substring']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/386 | Question: Given a word array **words**, each word is composed of lowercase English letters. If we can add exactly one letter anywhere in **wordA** without changing the order of other characters to make it become **wordB**, then we consider **wordA** to be the predecessor of **wordB**. For example, **abc** is the predecessor of **abac**, while **cba** is not the predecessor of **bcad**. A word chain is a sequence composed of words [word_1, word_2, ..., word_k], k>=1, where **word1** is the predecessor of **word2**, **word2** is the predecessor of **word3**, and so on. A word is usually a word chain where k==1. Choose words from the given word list **words** to form a word chain, and return the longest possible length of the word chain;
Based on the above question, please create a class **FCA** in Python with the attribute **words**; then create another class **SN_FCA** that inherits from the **FCA** class, and add a public function **Form_chain** that returns the longest possible length of the word chain. | [
"assert candidate([\"a\",\"b\",\"ba\",\"bca\",\"bda\",\"bdca\"])==4",
"assert candidate([\"xbc\",\"pcxbcf\",\"xb\",\"cxbc\",\"pcxbc\"])==5",
"assert candidate([\"abcd\",\"dbqca\"])==1"
] | def test_run(content1):
return SN_FCA(content1).Form_chain() | test_run | assert candidate([['class FCA', 'class SN_FCA(FCA)', 'super().__init__(words)', 'def Form_chain']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/387 | Question: There is a pile of stones, represented by an integer array **stones**. Where stones[i] represents the weight of the i-th stone. Each round, select any two stones from it and crush them together. Suppose the weights of the stones are **x** and **y**, and x <= y. Then the possible results of crushing are as follows:
1. If x == y, then both stones will be completely crushed; 2. If x != y, then the stone with weight **x** will be completely crushed, and the new weight of the stone with weight **y** is y-x. In the end, at most one stone will be left. Return the minimum possible weight of this stone. If no stones are left, return 0;
Based on the above question, please create a class **MWG** in Python, with the property **stones**; then create a class **SN_MWG** that inherits from the **MWG** class, and add a public function **Minimum_weight** to return the result of the above question. | [
"assert candidate([2,7,4,1,8,1])==1",
"assert candidate([31,26,33,21,40])==5"
] | def test_run(content1):
return SN_MWG(content1).Minimum_weight() | test_run | assert candidate([['class MWG', 'class SN_MWG(MWG)', 'super().__init__(stones)', 'def Minimum_weight']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/388 | Question: Given a positive integer array **arr** (which may contain duplicate elements), please return the maximum arrangement that is lexicographically smaller than **arr** and can be obtained by one swap (swapping the positions of two numbers arr[i] and arr[j]). If such operation is not possible, please return the original array;
Based on the above question, create a class **OEH** in Python with the attribute **arr**. Then create another class **SN_OEH** that inherits from the **OEH** class, and add a public function **One_exchange** that returns the result of the above question. | [
"assert candidate([3,2,1])==[3,1,2]",
"assert candidate([1,1,5])==[1,1,5]",
"assert candidate([1,9,4,6,7])==[1,7,4,6,9]"
] | def test_run(content1):
return SN_OEH(content1).One_exchange() | test_run | assert candidate([['class OEH', 'class SN_OEH(OEH)', 'super().__init__(arr)', 'def One_exchange']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/389 | Question: In a warehouse, there is a row of barcodes, where the i-th barcode is barcodes[i]. Please rearrange these barcodes so that no two adjacent barcodes are the same. You can return any answer that meets this requirement, and it is guaranteed that an answer exists;
Please create a class **ABD** in Python based on the above question, with the property **barcodes**; then create a class **SN_ABD** that inherits from the **ABD** class, and add a public function **Adjacent_barcodes** that returns the result of the above question. | [
"assert candidate([1,1,1,2,2,2])==[2,1,2,1,2,1]",
"assert candidate([1,1,1,1,2,2,3,3])==[1,3,1,3,2,1,2,1]"
] | def test_run(content1):
return SN_ABD(content1).Adjacent_barcodes() | test_run | assert candidate([['class ABD', 'class SN_ABD(ABD)', 'super().__init__(barcodes)', 'def Adjacent_barcodes']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/390 | Question: Given two strings of equal length, **s1** and **s2**, and another string, baseStr, where s1[i] and s2[i] are a pair of equivalent characters. For example, if s1 = **abc** and s2 = **cde**, then 'a' == 'c', 'b' == 'd', and 'c' == 'e'. Equivalent characters follow the general rules of any equivalence relation:
1. Reflexivity: 'a' == 'a'; 2. Symmetry: if 'a' == 'b', then 'b' == 'a'; 3. Transitivity: if 'a' == 'b' and 'b' == 'c', then 'a' == 'c'. Using the equivalence information of **s1** and **s2**, find and return the lexicographically smallest equivalent string of baseStr;
Based on the above question, please create a class **EST** in Python, with the attribute **s1**; then create another class **SN_EST**, inheriting from the **EST** class, and add two attributes **s2** and **baseStr**, as well as a public function **Equivalent_String** that returns the lexicographically smallest equivalent string of **baseStr**. | [
"assert candidate(\"parker\",\"morris\",\"parser\")==\"makkek\"",
"assert candidate(\"hello\",\"world\",\"hold\")==\"hdld\"",
"assert candidate(\"leetcode\",\"programs\",\"sourcecode\")==\"aauaaaaada\""
] | def test_run(content1,content2,content3):
return SN_EST(content1,content2,content3).Equivalent_String() | test_run | assert candidate([['class EST', 'class SN_EST(EST)', 'super().__init__(s1)', 'def Equivalent_String']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/391 | Question: Given an m x n matrix **matrix**, you can select any number of columns from it and flip each cell on it. (That is, after flipping, the value of the cell changes from 0 to 1, or from 1 to 0.) Return the maximum number of rows where all values in the row are equal after some flips;
Please create a class **MRW** with the property **matrix** in Python based on the above question; then create a class **SN_MRW** that inherits the **MRW** class, and add a public function **Maximum_rows** to return the result of the above question. | [
"assert candidate([[0,1],[1,1]])==1",
"assert candidate([[0,1],[1,0]])==2",
"assert candidate([[0,0,0],[0,0,1],[1,1,0]])==2"
] | def test_run(content1):
return SN_MRW(content1).Maximum_rows() | test_run | assert candidate([['class MRW', 'class SN_MRW(MRW)', 'super().__init__(matrix)', 'def Maximum_rows']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/392 | Question: Given two numbers **arr1** and **arr2** in base -2, return the result of their addition;
Please create a class named **ANS** in Python based on the above question, with the attribute **arr1**. Then create another class named **SN_ANS**, which inherits from the **ANS** class, and adds the attribute **arr2**, as well as a public function **Adding_Numbers** to return the result of adding the two numbers. | [
"assert candidate([1,1,1,1,1],[1,0,1])==[1,0,0,0,0]",
"assert candidate([0],[0])==[0]",
"assert candidate([0],[1])==[1]"
] | def test_run(content1,content2):
return SN_ANS(content1,content2).Adding_Numbers() | test_run | assert candidate([['class ANS', 'class SN_ANS(ANS)', 'super().__init__(arr1)', 'def Adding_Numbers']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/393 | Question: Given a **matrix** and a **target** value, return the number of non-empty submatrices whose sum of elements equals the target value;
Please create a class **ESI** in Python language based on the above question, with the attribute **matrix**; then create another class **SN_ESI**, inheriting from the **ESI** class, and add the attribute **target**, as well as a public function **empty_submatrix** to return the number of non-empty submatrices whose sum of elements equals the **target** value. | [
"assert candidate([[0,1,0],[1,1,1],[0,1,0]],0)==4",
"assert candidate([[1,-1],[-1,1]],0)==5",
"assert candidate([[904]],0)==0"
] | def test_run(content1,content2):
return SN_ESI(content1,content2).empty_submatrix() | test_run | assert candidate([['class ESI', 'class SN_ESI(ESI)', 'super().__init__(matrix)', 'def empty_submatrix']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/394 | Question: You have a set of movable type **tiles**, each of which is engraved with a letter tiles[i]. Return the number of non-empty letter sequences you can print;
Please create a class **LSQ** based on the above question, with the attribute **tiles** using Python language; then create another class **SN_LSQ**, inheriting from the **LSQ** class, and add a public function **letter_sequence** that returns the number of non-empty letter sequences that can be printed. | [
"assert candidate(\"AAB\")==8",
"assert candidate(\"AAABBC\")==188",
"assert candidate(\"V\")==1"
] | def test_run(content1):
return SN_LSQ(content1).letter_sequence() | test_run | assert candidate([['class LSQ', 'class SN_LSQ(LSQ)', 'super().__init__(tiles)', 'def letter_sequence']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/395 | Question: Return the subsequence of **s** with the smallest lexicographical order, which contains all distinct characters of **s** and only contains them once;
Based on the above question, create a class **SSU** in Python language with the attribute **s**. Then create another class **SN_SSU**, which inherits from the **SSU** class, and add a public function **smallest_subsequence** to return the result of the above question. | [
"assert candidate(\"bcabc\")==\"abc\"",
"assert candidate(\"cbacdcbc\")==\"acdb\""
] | def test_run(content1):
return SN_SSU(content1).smallest_subsequence() | test_run | assert candidate([['class SSU', 'class SN_SSU(SSU)', 'super().__init__(s)', 'def smallest_subsequence']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/396 | Question: We have a set of **n** items. Two integer arrays, **values** and **labels**, are given, where the value and label of the i-th element are values[i] and labels[i] respectively. Two more integers, **numWanted** and **useLimit**, are also given. We are to select a subset **s** from the **n** elements such that:
1. The size of subset **s** is less than or equal to numWanted. 2. There are at most useLimit items with the same label in **s**. The score of a subset is the sum of the values of the subset. The task is to return the maximum score of subset **s**;
Based on the above question, please create a class named **MSR** in Python, which has the attribute **values**. Then create another class **SN_MSR**, which inherits from the **MSR** class, and adds three attributes: **labels**, **numWanted**, and **useLimit**, as well as a public function **Maximum_score** that returns the maximum score of subset **s**. | [
"assert candidate([5,4,3,2,1],[1,1,2,2,3],3,1)==9",
"assert candidate([5,4,3,2,1],[1,3,3,3,2],3,2)==12",
"assert candidate([9,8,8,7,6],[0,0,0,1,1],3,1)==16"
] | def test_run(content1,content2,content3,content4):
return SN_MSR(content1,content2,content3,content4).Maximum_score() | test_run | assert candidate([['class MSR', 'class SN_MSR(MSR)', 'super().__init__(values)', 'def Maximum_score']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/397 | Question: Given an n x n binary matrix **grid**, return the length of the shortest unobstructed path in the matrix. If such a path does not exist, return -1;
Based on the above question, please create a **UPT** class in Python with a **grid** attribute; then create a **SN_UPT** class that inherits the **UPT** class, and add a public **Unobstructed_path** function to return the result of the above question. | [
"assert candidate([[0,1],[1,0]])==2",
"assert candidate([[0,0,0],[1,1,0],[1,1,0]])==4",
"assert candidate([[1,0,0],[1,1,0],[1,1,0]])==-1"
] | def test_run(content1):
return SN_UPT(content1).Unobstructed_path() | test_run | assert candidate([['class UPT', 'class SN_UPT(UPT)', 'super().__init__(grid)', 'def Unobstructed_path']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/398 | Question: Given two strings **str1** and **str2**, return the shortest string that has both **str1** and **str2** as subsequences;
Please create a class **SSI** in Python, which has the attribute **str1**. Then create another class **SN_SSI** that inherits from the **SSI** class, and add the attribute **str2**, as well as a public function **Shortest_string** to return the shortest string that has both **str1** and **str2** as subsequences. | [
"assert candidate(\"abac\",\"cab\")==\"cabac\"",
"assert candidate(\"aaaaaaaa\",\"aaaaaaaa\")==\"aaaaaaaa\""
] | def test_run(content1,content2):
return SN_SSI(content1,content2).Shortest_string() | test_run | assert candidate([['class SSI', 'class SN_SSI(SSI)', 'super().__init__(str1)', 'def Shortest_string']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |
OOP/399 | Question: Initially, there are **capacity** empty seats on the bus. The bus can only travel in one direction (that is, it is not allowed to turn around or change direction). Given the integer **capacity** and an array **trips**, trip[i] = [numPassengers_i, from_i, to_i] indicates that there are **numPassengers_i** passengers in the i-th trip, and their pick-up and drop-off locations are **from_i** and **to_i** respectively. These locations are the kilometers from the initial position of the car to the east. Return True only and only when you can pick up and drop off all passengers in all given trips, otherwise please return False;
Based on the above question, please create a class **PPG** using Python language, with the attribute **trips**; then create a class **SN_PPG** that inherits the **PPG** class, and add the attribute **capacity**, and a public function **Pick_passengers** that returns the result of the above question. | [
"assert candidate([[2,1,5],[3,3,7]],4)==False",
"assert candidate([[2,1,5],[3,3,7]],5)==True"
] | def test_run(content1,content2):
return SN_PPG(content1,content2).Pick_passengers() | test_run | assert candidate([['class PPG', 'class SN_PPG(PPG)', 'super().__init__(trips)', 'def Pick_passengers']]) == True | def matching_function(content):
def run_match(text):
for task in text:
if task not in str_content:
return False
return True
len_cont = len(content)
if len_cont==1 and run_match(content[0]) == True:
return True
elif (len_cont==2 and run_match(content[0]) == True) or (len_cont==2 and run_match(content[1]) == True):
return True
else:
return False |