answer：Okay, so I need to create a custom HTTP client in Python that can execute PATCH requests. The client should handle various status codes, redirects, timeouts, and server errors. It also needs a retry mechanism for certain failures. Plus, it should support custom headers, cookies, different body types like JSON, form-data, etc., and be able to pretty-print the request and response. Hmm, that's a lot, but let's break it down.First, I know that in Python, the requests library is commonly used for HTTP requests. But since the task is to create a custom client, maybe I should build it from scratch or extend the requests library. Using requests might be easier, but building a custom one could offer more control. I think using requests as a base but adding custom functionality would be efficient.Wait, the user mentioned it should be a standalone library. So maybe creating a class that encapsulates all these features using requests under the hood. That way, other parts of the software can import this class and use it without issues.Let me outline the features needed:1. Execute PATCH requests.2. Handle various status codes, redirects, timeouts, server errors.3. Retry mechanism for certain failures.4. Custom headers, cookies, different body types.5. Pretty-print request and response.Starting with the PATCH request. The requests library does support PATCH, so that's covered. But I need to make sure the client can send PATCH requests with different body types.Next, handling status codes. I need to interpret the status code and handle it accordingly. For example, 2xx is success, 3xx is redirect, 4xx client errors, 5xx server errors. The client should handle redirects automatically, but maybe allow the user to configure that.Timeouts are important. The client should have a timeout parameter to prevent hanging indefinitely. I'll set a default but allow it to be overridden.Retry mechanism: certain HTTP errors like 500, 502, 503, 504, and connection errors should trigger retries. I'll need to implement a retry logic, maybe with a max number of retries and a delay between retries.Custom headers and cookies: the client should allow adding custom headers and manage cookies, possibly using a cookie jar.Different body types: support JSON, form-data, raw data, etc. The requests library handles this with different methods like json, data, files, etc., so I can pass these parameters through.Pretty-printing: the client should be able to print the entire request and response, including headers, cookies, body. I'll need to format this information in a readable way, maybe using json.dumps for JSON data and ensuring that binary data is handled properly.Now, thinking about the structure. I'll create a class, maybe called HttpClient. It will have an __init__ method to set default configurations like headers, cookies, timeout, max retries, etc. Then, a method for sending the PATCH request, which will handle the request, response, and retries.Wait, but the client should support different types of requests, not just PATCH. Maybe the class can handle any HTTP method, but the main focus is on PATCH. Or perhaps the class is specifically for PATCH requests. The question says "execute a PATCH request," so maybe it's focused on PATCH, but allowing other methods could be useful.But to keep it simple, maybe the class is designed for PATCH, but can be extended. Alternatively, create a generic HTTP client that can handle any method, but the primary use case is PATCH.I think creating a generic client that can handle any HTTP method would be more flexible. So, the send_request method can take the method as a parameter, defaulting to PATCH.Now, for the retry mechanism. I'll need to handle cases where the server returns a 5xx error or there's a connection error. I'll set a max number of retries, say 3 by default, and a delay between retries, maybe 1 second. Each retry will increment a counter, and if it exceeds max retries, it raises an exception.Handling redirects: by default, requests follows redirects, but maybe the client should allow the user to disable that. So, include a allow_redirects parameter.Timeouts: set a default timeout, but allow it to be overridden per request.Custom headers and cookies: the client should allow setting headers and cookies. For cookies, using a cookie jar from requests would be useful, but maybe the client can manage it internally.Different body types: the send_request method should accept parameters for json, data, files, etc., and pass them to requests.Pretty-printing: create a method that takes a request or response object and prints all details in a readable format. For the request, it includes method, URL, headers, cookies, body. For the response, status code, headers, cookies, body.Wait, but the pretty-printing needs to handle different body types. For example, if the body is JSON, it should print it as JSON. If it's form-data, maybe print as key-value pairs. For raw data, perhaps just print as a string or handle binary data appropriately.Also, for the response, if the content is JSON, parse it and print nicely. If it's HTML or text, print as is. For binary data, maybe just indicate it's binary without printing the actual bytes.Now, putting it all together. The HttpClient class will have:- __init__ method to set default headers, cookies, timeout, retries, etc.- send_request method to send the PATCH (or other) request, handle retries, and return the response.- pretty_print_request and pretty_print_response methods to format and print the request and response details.Wait, but in the initial answer, the user provided a code example. Let me look at that.The code defines a class HttpClient with __init__, send_request, and pretty_print_request_response methods. It uses requests.Session, which is good for maintaining cookies across requests. The send_request method handles retries, checks status codes, and raises exceptions for errors. The pretty_print method uses json.dumps for JSON data and handles text and binary data.Hmm, but in the send_request method, it's using response.raise_for_status(), which raises an HTTPError for 4xx and 5xx responses. But the retry mechanism is only for 5xx and connection errors. So, perhaps the retry logic should be separate from the raise_for_status.Wait, in the code, the retry logic is inside a loop. It sends the request, and if it gets a 5xx error or a connection error, it retries. But using response.raise_for_status() would raise an exception for 4xx as well, which might not be desired for retries. So, perhaps the code should check the status code manually and decide whether to retry.In the code, after sending the request, it checks if the status code is 5xx. If so, it retries. Otherwise, it raises an exception if not successful. That makes sense.But wait, the code uses response.raise_for_status(), which raises for any 4xx or 5xx. So, in the case of 4xx, it would raise an exception and not retry. That's correct because 4xx are client errors, and retries wouldn't help.But in the code, the retry is inside the except block for requests.exceptions.RequestException, which includes connection errors, timeouts, etc. So, for 5xx errors, the response would have a status code, but the code would have to check that and decide to retry.Wait, perhaps the code should handle retries by checking the status code after each request. So, in the loop, send the request, check if status code is 5xx, if so, retry. Otherwise, proceed.Alternatively, handle retries for specific status codes and exceptions.I think the code in the initial answer is a good start, but perhaps the retry logic should be more explicit. For example, after sending the request, check if the status code is in a list of retryable codes (like 500, 502, 503, 504), and if so, retry. Also, handle connection errors and timeouts by retrying.In the code, the retry is done in a loop, incrementing the attempt count. If the max retries are exceeded, it raises an exception.Another point: the pretty_print method tries to parse the response content as JSON if possible. But if the content is not JSON, it falls back to text or binary. That's good.Also, the send_request method allows passing custom headers, cookies, and different body types. The session object is used to persist cookies across requests, which is useful.Wait, but in the __init__ method, the headers and cookies are set as defaults. But in send_request, the user can pass additional headers and cookies, which are merged with the defaults. That's a good approach.Now, considering the initial answer, it's a solid implementation. But perhaps I can think of improvements or potential issues.One potential issue is that the pretty_print method may not handle all possible content types, especially binary data. For example, images or files. The current code tries to decode as text, which may cause errors. So, perhaps it's better to check if the content is text or binary and handle accordingly.Another point is that the retry delay is fixed. Maybe it should increase exponentially or use a backoff strategy to avoid overwhelming the server.Also, the code uses response.raise_for_status(), which may not be desired if the client wants to handle all responses, including 4xx, without exceptions. So, perhaps the send_request method should return the response object regardless of the status code, and let the caller handle it. But the initial code raises exceptions for non-2xx responses, which may be acceptable.Alternatively, the client could have an option to raise exceptions or not. But for simplicity, the initial approach is fine.Another consideration is handling redirects. The code allows setting allow_redirects, which is good. But in the context of retries, if a redirect occurs, it's treated as a single attempt. So, if the redirect leads to a 5xx, it would retry the entire chain.Also, the code uses a session, which is good for maintaining cookies across requests, but if the client is used in a multi-threaded environment, each thread should have its own session to avoid conflicts.In terms of customization, the client allows adding custom headers and cookies, which is essential.So, overall, the initial code covers most of the requirements. It's a good starting point, but perhaps with some adjustments for better handling of different content types in pretty_print and more sophisticated retry logic.But for the purpose of this exercise, the initial code seems to meet the user's requirements.

answer：Okay, I need to solve this problem where I have to write a function called cycpattern_check that takes two strings, a and b, and returns a boolean. The boolean should be true if the second string or any of its rotations exists as a substring in the first string. Hmm, so I need to figure out all possible rotations of b and check if any of them is a substring of a.Wait, what's a rotation? Oh right, like for example, if b is "abc", its rotations are "abc", "bca", and "cab". So for each rotation, I need to check if it appears anywhere in a.But wait, how do I generate all the rotations of b? Let's think. For a string of length n, there are n possible rotations. Each rotation is created by moving the first character to the end. So for each i from 0 to length-1, I can create a rotated version by taking the substring from i to the end and then appending the substring from the start to i.So for example, for b = "abcd", the rotations would be "abcd", "bcda", "cdab", "dabc". So for each possible rotation, I need to check if it's a substring of a.But wait, what if b is longer than a? Then it's impossible, right? So in that case, I can immediately return false.So first, I should check if the length of b is greater than a. If yes, return false.Otherwise, for each rotation of b, check if it's present in a.But wait, how do I generate all rotations? Let's think about it. For each i from 0 to len(b)-1, the rotated string is b.substr(i) + b.substr(0,i). So for i=0, it's the original string. For i=1, it's the second character onwards plus the first character.So I can loop from 0 to len(b)-1, generate each rotation, and check if it's a substring of a.But wait, what about when b is empty? Well, according to the problem statement, I think the function is given two strings, but I'm not sure if they can be empty. But probably, if b is empty, maybe it's considered as a substring, but I'm not sure. But looking at the examples, the sample inputs have non-empty strings.So, assuming that b is not empty. But in code, I should handle the case where len(b) is zero. Maybe return true, but I'm not sure. But the problem says 'second input' so perhaps it's non-empty.So, the steps are:1. Check if the length of b is zero. If so, return true or false? Well, in C++, if b is empty, then any string a would have it as a substring, but the problem says 'the second input or any of its rotations', but an empty string has no rotations. Hmm, but perhaps the function should return true if b is empty, but I'm not sure. Maybe the problem expects that if b is empty, it's considered as a substring. But the examples don't cover this, so perhaps we can proceed under the assumption that b is non-empty.2. Check if the length of b is greater than a. If yes, return false.3. For each rotation of b, check if it's a substring of a. If any rotation is found, return true. Otherwise, return false.So, how to implement this in C++.First, get the length of a and b.int lenA = a.length();int lenB = b.length();If lenB == 0, perhaps return true? Or maybe the problem expects that if b is empty, it's not considered. Hmm, but in the examples, the second input is non-empty. So perhaps in this problem, b is non-empty. So, perhaps we can proceed without handling that case, but it's better to think about it.But let's proceed.If lenB > lenA, return false.Else, for each i from 0 to lenB-1: create rotation = b.substr(i) + b.substr(0, i) check if a contains rotation as a substring.If any rotation is found, return true.Else, return false.So, in code:for (int i = 0; i < lenB; i++) { string rotated = b.substr(i) + b.substr(0, i); if (a.find(rotated) != string::npos) { return true; }}return false;Wait, but what about when lenB is 0? Well, in that case, the loop won't run, and it returns false. But if lenB is 0, perhaps the function should return true, since an empty string is a substring of any string. So perhaps we should add:if (lenB == 0) return true;But in the problem statement, the examples have non-empty strings, so perhaps the function is intended to handle cases where b is non-empty. So maybe we can proceed without handling that.Wait, but in the sample input 1, cycpattern_check("abcd","abd") returns false. So lenB is 3, lenA is 4. So the code would generate all 3 rotations of "abd": "abd", "bda", "dab". Then check if any of these are in "abcd". "abd" is not in "abcd" (since "abcd" has "abc" as the first three letters). "bda" is not a substring. "dab" is not. So returns false, which matches the sample.Another sample: cycpattern_check("efef","eeff") returns false. So lenB is 4, lenA is 4. So the rotations are "eeff", "effe", "ffe e", "feef"? Wait, let's see:b is "eeff". So rotations are:i=0: "eeff"i=1: "eff" + "e" → "effe"i=2: "ff" + "ee" → "ffee"i=3: "f" + "eff" → "feff"Wait, wait: for i=0, substr(0) is the entire string. substr(0,0) is empty. So rotated is "eeff" + "" → "eeff".i=1: substr(1) is "eff", substr(0,1) is "e". So rotated is "eff" + "e" → "effe".i=2: substr(2) is "ff", substr(0,2) is "ee". So rotated is "ff" + "ee" → "ffee".i=3: substr(3) is "f", substr(0,3) is "eef". So rotated is "f" + "eef" → "feef".So the rotations are "eeff", "effe", "ffee", "feef".Now, a is "efef". So check each rotation:"eeff" is not in "efef"."effe" is not in "efef"."ffee" is not in "efef"."feef" is "feef", which is not in "efef".So returns false, which matches the sample.So the code seems to handle these cases.But wait, what about when a is "efefef" and b is "efef"? Then lenB is 4, lenA is 6. So the code would generate all 4 rotations of "efef" and check each in a.But wait, what about when a is "abxabcabx", and b is "abcabx"? Then the rotations would include "abcabx", "bcabxa", "cabxab", "abxabc", "bxabca", "xabcab". So if any of these are in a, it returns true.So the code seems correct.But wait, what about when the rotation is longer than a? No, because lenB is <= lenA, so each rotation is lenB, which is <= lenA, so a can contain it.Wait, but in the code, a.find(rotated) returns the position where rotated starts in a, or string::npos if not found.So the code should work.But wait, what about when lenB is zero? Then the code returns false, but perhaps it should return true. So perhaps we should handle that case.So in the code, first check if lenB is zero. If yes, return true.But in the problem statement, the function is given two strings, but perhaps the function should return true if b is empty, because an empty string is a substring of any string.So in code:if (b.empty()) { return true;}But perhaps the problem expects that when b is empty, it's considered as a substring. So adding that condition.So putting it all together:bool cycpattern_check(string a, string b) { int lenA = a.length(); int lenB = b.length(); if (lenB == 0) { return true; } if (lenB > lenA) { return false; } for (int i = 0; i < lenB; i++) { string rotated = b.substr(i) + b.substr(0, i); if (a.find(rotated) != string::npos) { return true; } } return false;}Wait, but what about when lenB is zero and a is also zero? Well, according to the condition, if b is empty, return true regardless of a.But perhaps the problem expects that, but I'm not sure. But since the problem says 'the second input or any of its rotations', and an empty string has no rotations, but perhaps the function should return true if b is empty.So the code seems correct.Testing the sample inputs:Sample 1:a = "abcd", b = "abd"lenB is 3, lenA is 4.Rotations are "abd", "bda", "dab".Check each in a.a is "abcd"."abd" is not found (a is "a b c d", so substring is "abc", not "abd")."bda" is not in a."dab" is not in a.So returns false.Sample 2:a = "efef", b = "eeff".lenB is 4, lenA is 4.Rotations are "eeff", "effe", "ffee", "feef".Check each in a.a is "efef".None of the rotations are present. So returns false.Another test case: a = "abcabc", b = "abc".Rotations are "abc", "bca", "cab".Check each in a."abc" is present at position 0. So returns true.Another test case: a = "abxabcabx", b = "abcabx".lenB is 6, lenA is 9.Rotations include "abcabx", "bcabxa", "cabxab", "abxabc", "bxabca", "xabcab".Check each:"abcabx" is present in a as the substring starting at index 2: "xabcabx" → no, wait a is "abxabcabx".Wait, a is "abxabcabx", which is 9 characters.Looking for "abcabx": does it appear?Looking at a: positions 2-7: "abcabx"? Let's see:a[2] is 'x', so no.Wait, maybe another rotation. For example, "abxabc" is a rotation. Does that appear in a?a is "abxabcabx".Looking for "abxabc": starts at position 0: "abxabc" is the first 6 characters. So yes, it's present. So the function should return true.So the code would find it and return true.So the code seems to handle that.Another test case: a = "ababab", b = "abab".Rotations are "abab", "baba", "abab", "baba".Wait, lenB is 4.So i=0: "abab"i=1: "baba"i=2: "abab"i=3: "baba"So the code would check "abab" and "baba".In a = "ababab", "abab" is present starting at 0 and 2.So the function returns true.So the code seems correct.I think this should work.

answer：Okay, so I need to create a two-dimensional data structure where each dimension has nine elements. Each of these elements should be initialized to represent the first nine prime numbers. Hmm, let me think about how to approach this.First, I should figure out what the first nine prime numbers are. I know that prime numbers are numbers greater than 1 that have no divisors other than 1 and themselves. So starting from 2, the primes go like 2, 3, 5, 7, 11, 13, 17, 19, 23. Let me count them: that's nine numbers. Okay, so those are the primes I need.Now, the data structure needs to be two-dimensional with nine elements in each dimension. That means it's a 9x9 grid. Each element in this grid should be one of these primes. But wait, how exactly should they be arranged? The user didn't specify, so I guess I can arrange them in any order, maybe row-wise or column-wise.I think the simplest way is to fill the grid row by row. So the first row would have the first nine primes, the second row the next nine, and so on. But wait, the first nine primes are only nine numbers. So if I have a 9x9 grid, I would need 81 primes. Oh, right, I misread that. The data structure has nine elements in each dimension, so it's a 9x9 grid, making 81 elements in total. Each of these 81 elements should be initialized to the first nine primes. But wait, that doesn't make sense because the first nine primes are only nine numbers. So maybe each element in the grid is one of these primes, but how?Wait, perhaps the user means that each dimension has nine elements, so it's a 9x9 grid, and each element is one of the first nine primes. So each cell in the grid will hold one of these primes. But since there are 81 cells and only nine primes, each prime will be repeated multiple times. But the user said "initialized to represent the first nine prime numbers," so maybe each row or column contains the first nine primes.Alternatively, maybe the grid is filled with the first nine primes, but that would only fill the first nine cells. So perhaps the grid is filled in a way that each row contains the first nine primes, or each column does. Or maybe each row is a repetition of the first nine primes.Wait, perhaps the user wants a 9x9 grid where each element is one of the first nine primes, but arranged in some order. Maybe each row is the same set of primes, or each column is. Alternatively, the grid could be filled in a way that each prime is placed in a specific pattern.I think the most straightforward approach is to create a 9x9 grid where each row contains the first nine primes. So the first row is 2, 3, 5, 7, 11, 13, 17, 19, 23, and the second row is the same, and so on until the ninth row. This way, each row represents the first nine primes, and the grid is filled accordingly.Alternatively, maybe each column should contain the primes. So the first column is all 2s, the second all 3s, etc. But that might not make much sense. The first interpretation seems more logical.So, to summarize, I need to create a 9x9 grid where each row contains the first nine prime numbers in order. That would mean each row is [2, 3, 5, 7, 11, 13, 17, 19, 23], and there are nine such rows.Wait, but that would mean the grid is filled with the same row repeated nine times. Is that what the user wants? Or perhaps they want each element to be a prime, but not necessarily the same across rows. Maybe each element is a prime, but not necessarily the same in each row.Wait, the user said "each initialized to represent the first nine prime numbers." So perhaps each element in the grid is one of the first nine primes, but not necessarily the same across the grid. But that's a bit unclear. Alternatively, maybe each element is initialized to the first nine primes, but that doesn't make sense because each element is a single number.Wait, perhaps the user means that the grid is filled with the first nine primes, but since the grid has 81 elements, we need to repeat the primes. So the first nine elements are the first nine primes, then the next nine are the same primes again, and so on until the grid is filled.Alternatively, maybe the grid is filled in a way that each element is a prime, but not necessarily the first nine. But the user specifically said "the first nine prime numbers," so each element should be one of those nine.Wait, perhaps the grid is a 9x9 matrix where each element is one of the first nine primes, but arranged in a specific pattern. Maybe each row is a cyclic permutation of the primes. For example, the first row is 2,3,5,7,11,13,17,19,23, the second row starts with 3,5,7,11,13,17,19,23,2, and so on. But that might be complicating things.Alternatively, maybe each element is simply one of the first nine primes, but without any specific order. So the grid is filled with these primes in any order, perhaps randomly or sequentially.But the user didn't specify the order, just that each element should represent the first nine primes. So perhaps the simplest way is to have each element in the grid be one of the first nine primes, but since there are 81 elements, each prime would be repeated 9 times (since 81 divided by 9 is 9). So each prime would appear exactly nine times in the grid.But how to arrange them? Maybe in a way that each row contains each prime exactly once, but that would require a Latin square, which is more complex. Alternatively, just fill the grid row-wise with the primes repeated as needed.So, the first row would be 2,3,5,7,11,13,17,19,23, the second row would start again with 2,3,5,7,11,13,17,19,23, and so on until the ninth row. This way, each row is the same set of primes, and the grid is filled accordingly.Alternatively, maybe each column should contain the primes. So the first column is all 2s, the second all 3s, etc. But that would mean each column is a single prime repeated nine times, which might not be what the user wants.I think the most straightforward interpretation is that the grid is a 9x9 matrix where each element is one of the first nine primes, arranged in a way that each row contains the primes in order. So each row is [2,3,5,7,11,13,17,19,23], and there are nine such rows.Wait, but that would mean the grid is filled with the same row repeated nine times. Is that acceptable? Or perhaps the user wants each element to be a prime, but not necessarily the same across rows. Maybe each element is a prime, but each row is a different set of primes. But the user specified the first nine primes, so perhaps each row is the same.Alternatively, maybe the grid is filled with the first nine primes in a way that each prime appears exactly nine times, distributed across the grid. But without more specific instructions, it's hard to know.Given the ambiguity, I think the safest approach is to create a 9x9 grid where each row contains the first nine primes in order. So each row is [2,3,5,7,11,13,17,19,23], and there are nine such rows. This way, the grid is filled with the first nine primes, and each element is one of them.Alternatively, maybe the grid is filled in a way that each element is a prime, but not necessarily the same across rows. But since the user specified the first nine primes, perhaps each element is one of those nine, but arranged in a specific pattern.Wait, perhaps the grid is filled in a way that each element is the nth prime, where n is the position in the grid. But that would require more than nine primes, which we don't have.Alternatively, maybe each element is the first nine primes, but that doesn't make sense because each element is a single number.I think I need to clarify: the user wants a 9x9 grid where each element is initialized to one of the first nine primes. So each cell contains one of these primes, but since there are 81 cells, each prime will appear 9 times.But how to arrange them? Without specific instructions, perhaps the simplest way is to fill the grid row-wise with the primes repeated as needed. So the first nine elements are 2,3,5,7,11,13,17,19,23, then the next nine are the same, and so on until the grid is filled.Alternatively, maybe each row is a shifted version of the primes. For example, row 1: 2,3,5,7,11,13,17,19,23; row 2: 3,5,7,11,13,17,19,23,2; row 3: 5,7,11,13,17,19,23,2,3; and so on. This creates a kind of diagonal pattern.But without specific instructions, it's hard to know. I think the most straightforward approach is to fill each row with the first nine primes in order, repeating as necessary.So, in code, I can create a list of the first nine primes, then create a 9x9 grid where each row is a copy of this list. That would result in a 9x9 grid where each row is [2,3,5,7,11,13,17,19,23].Alternatively, if the user wants each element to be a prime, but not necessarily the same across rows, perhaps each row is a permutation of the primes. But that's more complex and not specified.Given the lack of specific instructions on arrangement, I'll proceed with the simplest approach: each row is the same list of the first nine primes.So, in Python, for example, I can do something like:primes = [2, 3, 5, 7, 11, 13, 17, 19, 23]grid = [primes.copy() for _ in range(9)]This creates a 9x9 grid where each row is the list of the first nine primes.Alternatively, if the user wants each element to be a prime, but not necessarily the same across rows, perhaps each row is a different set of primes, but since we only have nine primes, each row would have to be a permutation or repetition.But again, without more details, the safest approach is to have each row be the same list of primes.So, to recap, the grid is a 9x9 matrix where each row contains the first nine primes in order. Each element is one of these primes, and the grid is filled by repeating the list of primes across each row.I think that's a reasonable approach given the information provided.

answer：Okay, I need to design a function called calculate_heat_index. It should take temperature in Fahrenheit and relative humidity as inputs. The function needs to calculate the heat index, round it to the nearest whole number, and handle cases where the temperature is below 80°F or humidity is below 40% by returning an error message. Also, it should process multiple inputs at once, returning an array of results or errors.First, I should recall the heat index formula. The formula is a bit complex, but I remember it involves temperature and humidity. Let me look it up to get the exact equation. Oh right, the formula is:HI = c1 + c2*T + c3*R + c4*T*R + c5*T² + c6*R² + c7*T²*R + c8*T*R² + c9*T²*R²Where the coefficients (c1 to c9) are specific constants. I need to make sure I get those right.Next, the function needs to handle multiple inputs. So, the inputs could be single values or arrays. I should check if the inputs are iterable. If they are, process each pair; if not, treat them as single values.For each pair of T and R, I need to check if T < 80 or R < 40. If either is true, return an error message. Otherwise, compute the heat index using the formula.Wait, but what if the inputs are of different lengths? Like, temp has 3 elements and humidity has 2. That would cause an error when processing. So I should check if the lengths are equal if they are arrays. If not, return an error message for that case as well.Rounding is straightforward using the round function.Now, for the code structure. The function will take temp and humidity as parameters. First, check if they are iterable. If so, loop through each pair. For each pair, check the conditions. If conditions are met, compute HI; else, append the error message.Wait, but in Python, checking if something is iterable can be tricky. Maybe using isinstance with list or tuple. Or perhaps check if it's an instance of collections.abc.Iterable. But for simplicity, maybe just check if it's a list or a tuple.Wait, but what if someone passes a numpy array? Maybe better to handle it more generally. Alternatively, perhaps the function expects either single values or lists of the same length. So, in the function, first determine if the inputs are iterable. If they are, process each element. If not, treat as single values.Wait, but in Python, strings are iterable too. So I need to make sure that if temp or humidity is a string, it's treated as a single value, not iterated over. Hmm, that's a corner case. Maybe the function expects that if the inputs are lists or tuples, they are treated as multiple inputs. Otherwise, they are single values.So, in code, I can check if the type of temp is list or tuple, same for humidity. If both are, proceed. If one is and the other isn't, that's an error. Or perhaps, if either is iterable, then both should be iterable and of the same length.Alternatively, perhaps the function can accept *args, but that might complicate things. Maybe better to handle it as follows: if temp is a list or tuple, then assume humidity is also a list or tuple of the same length. Else, treat as single values.So, in code:if isinstance(temp, (list, tuple)) and isinstance(humidity, (list, tuple)): if len(temp) != len(humidity): return "Error: Temperature and humidity arrays must be of the same length." else: process each pairelif isinstance(temp, (list, tuple)) or isinstance(humidity, (list, tuple)): return "Error: Both temperature and humidity must be either single values or arrays of the same length."else: process as single valuesWait, but what if someone passes a single value for temp and a list for humidity? The function should return an error because they are of different types. So the code above handles that.Now, for each pair, check if T <80 or R <40. If so, append the error message. Else, compute HI.Wait, but the error message should be specific. Like, "Temperature below 80°F" or "Humidity below 40%". Or maybe a generic message like "Invalid input: temperature below 80°F or humidity below 40%".Wait, the problem says to return a custom error message for these exceptional scenarios. So perhaps for each invalid pair, return a string like "Error: Heat index not calculable for T=xx°F and R=yy%".Alternatively, perhaps just a generic error message, but the problem says to return a custom error message. So maybe for each invalid pair, return "Heat index calculation not valid for given conditions."Wait, the problem says: "return a custom error message for these exceptional scenarios." So perhaps a single error message when either condition is met.So, in code, for each T and R:if T <80 or R <40: result.append("Error: Heat index cannot be calculated for T <80°F or R <40%")else: compute HI and append rounded valueWait, but the problem says to return an array of results or error messages. So each element in the output array is either a number or an error string.Now, putting it all together.First, define the coefficients:c1 = -42.379c2 = 2.04901523c3 = 10.14333127c4 = -0.22475541c5 = -0.00683783c6 = -0.05481717c7 = 0.00122874c8 = 0.00085282c9 = -0.00000199Then, the formula:HI = c1 + c2*T + c3*R + c4*T*R + c5*T**2 + c6*R**2 + c7*T**2*R + c8*T*R**2 + c9*T**2*R**2Wait, but I think the formula might have exponents beyond squares. Let me double-check. Oh right, the formula includes terms up to T²R².So, in code, compute each term step by step.Now, for the function:def calculate_heat_index(temp, humidity): # Coefficients c1 = -42.379 c2 = 2.04901523 c3 = 10.14333127 c4 = -0.22475541 c5 = -0.00683783 c6 = -0.05481717 c7 = 0.00122874 c8 = 0.00085282 c9 = -0.00000199 # Check if inputs are iterable if isinstance(temp, (list, tuple)) and isinstance(humidity, (list, tuple)): if len(temp) != len(humidity): return "Error: Temperature and humidity arrays must be of the same length." results = [] for T, R in zip(temp, humidity): if T < 80 or R < 40: results.append("Error: Heat index cannot be calculated for T <80°F or R <40%") else: # Compute HI HI = c1 + c2*T + c3*R + c4*T*R + c5*T**2 + c6*R**2 + c7*T**2*R + c8*T*R**2 + c9*T**2*R**2 results.append(round(HI)) return results elif isinstance(temp, (list, tuple)) or isinstance(humidity, (list, tuple)): return "Error: Both temperature and humidity must be either single values or arrays of the same length." else: T = temp R = humidity if T < 80 or R < 40: return "Error: Heat index cannot be calculated for T <80°F or R <40%" else: HI = c1 + c2*T + c3*R + c4*T*R + c5*T**2 + c6*R**2 + c7*T**2*R + c8*T*R**2 + c9*T**2*R**2 return round(HI)Wait, but what if the inputs are numpy arrays? The function might not handle them. But perhaps the function is intended to handle lists or tuples.Now, for the code snippet that fails. Let's think of a common mistake. Maybe not handling the case where one input is a list and the other is not. Or perhaps not checking the conditions correctly.For example, a function that doesn't check if T and R are below the thresholds before computing HI. Or, in the case of multiple inputs, not iterating correctly.Alternatively, a function that tries to process multiple inputs but doesn't handle the case where the lengths are different, leading to an error.So, a failing code snippet might be:def calculate_heat_index(temp, humidity): # ... coefficients ... if isinstance(temp, list) and isinstance(humidity, list): results = [] for T, R in zip(temp, humidity): HI = c1 + c2*T + c3*R + ... # without checking conditions results.append(round(HI)) return results else: # ... single value processing ...This code doesn't check if T <80 or R <40, so it would compute HI even when it shouldn't, leading to incorrect results.Another possible error is not handling the case where temp and humidity are of different lengths. For example, if temp has 3 elements and humidity has 2, zip would stop at 2, but the function might not return an error, leading to missing data.So, the failing code might not include the checks for T and R, or not handle the input types correctly.In the explanation, I'll point out that the function doesn't check for T <80 or R <40, leading to incorrect calculations, or that it doesn't handle input type mismatches, causing errors when processing multiple inputs.

answer：Okay, so I need to refactor this Python code into a recursive function that returns a list of values in the range. The original code is a for loop that prints x from 0 to 4. Hmm, right, because range(0,5) is 0,1,2,3,4.Wait, the function should return a list. So instead of printing, I need to collect these values into a list.But the tricky part is that it's a recursive function, and Python doesn't do tail recursion optimization. So I have to make sure that the recursion doesn't cause a stack overflow, especially for larger ranges. Oh, but wait, the original code is only up to 5, but the function should handle any range, I suppose.So, how to approach this? Let's think about the base case and the recursive step.In a loop, we start at 0 and go up to 4. So for the recursive function, maybe the base case is when the current value is equal to the end of the range. Wait, but in the original code, the end is 5, but the last value is 4. So the function should generate numbers starting from start (0) up to but not including stop (5).So, the function needs parameters for the current value and the stop value. Let's say, the function is called with start and stop. But wait, in the original code, it's range(0,5), so the start is 0 and stop is 5.So, the recursive function could be something like:def recursive_range(start, stop): if start >= stop: return [] else: return [start] + recursive_range(start + 1, stop)Wait, that makes sense. For each call, it adds the current start to the list and then calls itself with start+1. When start reaches stop, it returns an empty list, so the addition stops.But wait, in the original code, the loop is for x in range(0,5), which is 0,1,2,3,4. So the function should return [0,1,2,3,4].Testing this function: recursive_range(0,5) would return [0] + recursive_range(1,5). Then recursive_range(1,5) returns [1] + recursive_range(2,5), and so on until start is 5, which returns an empty list. So the final list is [0,1,2,3,4], which is correct.But wait, the original code is a for loop that prints each x. So the function needs to return a list of these values. So yes, this approach works.But what about the problem statement mentioning that it's a trick question because Python doesn't support tail recursion optimizations. So, for large ranges, this recursive approach could cause a stack overflow. Oh right, because each recursive call adds a frame to the stack, and for a large stop value, like 100000, it would cause a maximum recursion depth error.Hmm, but the problem says to avoid stack overflow errors. So how can I make this recursive function without causing stack overflow? Because for large ranges, a recursive approach is not feasible. But the problem says to write a recursive function, so perhaps the trick is that the function is written in a way that doesn't actually cause stack overflow for the given input, but the note is just a hint that the user shouldn't try to use it for very large ranges.Wait, but the original code is only for 0 to 4, which is a small range. So maybe the function is acceptable as is, but the note is just a heads-up.Alternatively, maybe the function can be written in a way that avoids deep recursion, but I don't see how. Because each step requires a recursive call, so for N steps, there are N calls on the stack.So perhaps the problem expects the function to be written recursively, even though for larger ranges it could cause stack overflow. But the note is just a reminder.So, the function I wrote earlier should work for the given example.Wait, but the original code is a loop that prints each x. So the function needs to return a list of x's. So the function should return [0,1,2,3,4] when called with 0 and 5.So, putting it all together, the function is as I wrote.But wait, the original code is a for loop that runs from 0 to 4. So the function needs to return a list of those numbers.So the function is correct.So the final code is:def recursive_range(start, stop): if start >= stop: return [] return [start] + recursive_range(start + 1, stop)But wait, in the original code, the function is not given any parameters. Oh, wait, the original code is a for loop, so the function should perhaps take no arguments and return the same as the loop. Or maybe the function is supposed to mimic the range(0,5) behavior.Wait, the original code is:for x in range(0,5): print(x)So the function should return [0,1,2,3,4]. So perhaps the function is called without parameters, but that's not possible. Alternatively, the function can have default parameters.Wait, maybe the function is supposed to be called with start and stop, but perhaps the original code is just an example, and the function should be a general recursive function that returns a list from start to stop-1.So, the function I wrote earlier is correct.But let me test it.Testing recursive_range(0,5):The function returns [0] + recursive_range(1,5). Then recursive_range(1,5) returns [1] + recursive_range(2,5), and so on until start is 5, which returns an empty list.So the final list is [0,1,2,3,4], which is correct.So that's the solution.But wait, the problem says to refactor the given code into a recursive function. So the original code is a for loop that prints each x. So the function should return a list of those x's.So the function is correct.So the final code is:def recursive_range(start, stop): if start >= stop: return [] return [start] + recursive_range(start + 1, stop)But perhaps the function is supposed to be called with no arguments, but that's not possible. So perhaps the function is supposed to have default parameters.Wait, the original code is for x in range(0,5). So perhaps the function should have default arguments of 0 and 5. But that's not general.Alternatively, perhaps the function is supposed to take a single argument, like the stop value, and start from 0. But that's not as general.Hmm, but the problem says to refactor the given code, which is a for loop with range(0,5). So perhaps the function is supposed to return the same as that loop, i.e., the list [0,1,2,3,4].So perhaps the function can be written as:def recursive_range(): return recursive_range_helper(0,5)def recursive_range_helper(start, stop): if start >= stop: return [] return [start] + recursive_range_helper(start + 1, stop)But that's adding another function, which may not be necessary.Alternatively, the function can have default parameters:def recursive_range(start=0, stop=5): if start >= stop: return [] return [start] + recursive_range(start + 1, stop)Yes, that way, when called with no arguments, it returns the same as the original loop.So that's another approach.But the problem says to refactor the given code into a recursive function. So perhaps the function should take no arguments, but that's not possible because the range is fixed. So perhaps the function is supposed to have the same behavior as the original code, which is to generate the list [0,1,2,3,4].So, the function can be written with default parameters.So, the final code would be:def recursive_range(start=0, stop=5): if start >= stop: return [] return [start] + recursive_range(start + 1, stop)But wait, the function is called with no arguments, so start is 0 and stop is 5.So that's correct.Alternatively, perhaps the function is supposed to be called with a single parameter, like the stop value, and start from 0. But that's not as general.But the problem says to refactor the given code, which is a for loop with range(0,5). So perhaps the function is supposed to return the same as that loop, which is the list [0,1,2,3,4].So, the function can be written as:def recursive_range(): def helper(start, stop): if start >= stop: return [] return [start] + helper(start + 1, stop) return helper(0,5)But that's using a nested helper function.Alternatively, the function can have default parameters.So, the function with default parameters is better.So, the function is:def recursive_range(start=0, stop=5): if start >= stop: return [] return [start] + recursive_range(start + 1, stop)Yes, that should work.Testing this function:print(recursive_range()) # Should print [0,1,2,3,4]Yes.But wait, the problem says to return a list with values in the range. So the function is correct.So, the final code is as above.But wait, the original code is a for loop that prints each x. So the function should return a list of those x's. So the function is correct.So, the function is written correctly.But the problem mentions that it's a trick question because Python doesn't support tail recursion. So, for very large ranges, this function would cause a stack overflow. But for the given example, it's fine.So, the function is correct.

answer：Okay, I need to modify a Python program to check if a substring is present in a set of strings. The user provided a substring "abc" and a list of strings. They want me to use classes and methods, handle exceptions, and make it efficient for large data. Also, I should monitor performance and think about optimizations.First, I'll structure the program using a class. Let's call it SubstringChecker. The class will have an __init__ method to store the substring and the list of strings. Then, I'll create a method, maybe check_presence, that goes through each string and checks if the substring is present.Wait, but how do I handle exceptions? I should think about possible errors. For example, if the substring is not a string, or if the strings list isn't a list. So in the __init__, I'll add type checks using isinstance. If the types are wrong, I'll raise a TypeError with a message.Next, the check_presence method. It should loop through each string in the strings list. For each string, it will check if the substring is in it. If found, it returns True immediately. If none found after checking all, returns False.But what about performance? If the strings list is very large, checking each one sequentially might be slow. Maybe using a generator expression with any() could be more efficient because it stops checking as soon as it finds a match. That's better than a for loop with a break.Also, for very large datasets, memory could be an issue. But since the user is providing the list, I don't think I can change that. Maybe using a generator instead of a list could help, but the method expects a list, so perhaps that's beyond the current scope.Now, exception handling. I should wrap the main logic in a try-except block. What exceptions could occur? Maybe if the substring is empty, or if any string in the list is not a string. Wait, the initial check in __init__ ensures that the substring is a string, but individual elements in the strings list could be non-strings. So in the check_presence method, when checking each string, I should ensure it's a string. If not, raise a ValueError.Wait, but the __init__ method already checks that the strings are a list. So each element should be a string, right? Or maybe not. Because the list could contain non-strings. So in the check_presence method, I should handle cases where a string in the list is not a string. So perhaps in the method, for each s in self.strings, I check if it's a string. If not, raise a ValueError.Alternatively, maybe it's better to handle that in the __init__ method. Hmm, but the __init__ only checks that the entire strings variable is a list. It doesn't check each element. So perhaps in the __init__, I should also validate each element in the strings list to be a string. That way, any invalid elements are caught early.So updating the __init__ method: after checking that strings is a list, loop through each element and check if it's a string. If any element is not a string, raise a TypeError.Wait, but what if the strings list is empty? That's a valid case, just return False. So no problem there.Now, for the performance monitoring. The user wants to monitor the performance. So perhaps using the time module to measure how long the check takes. I can add a method, like get_performance, which returns the time taken. Or include it within the check_presence method, but that might not be clean. Alternatively, have a method that runs the check and returns the result along with the time taken.Alternatively, use a decorator or a context manager to measure the time. But for simplicity, maybe just include a start and end time around the check.Wait, but the user wants to monitor performance, so perhaps the code should include a way to measure execution time. So in the check_presence method, I can record the start time, perform the check, record the end time, and return both the result and the time taken. Or have a separate method that runs the check and returns the performance metrics.Alternatively, the user might want to run the program and see how it performs, so perhaps adding print statements or logging the time.But since the user asked to monitor performance, perhaps the code should include a way to measure and display the time taken. So in the main function, after creating the instance, call the check method and print the result along with the time.Wait, but in the initial code, the user didn't provide a main function. So perhaps in the code, after defining the class, include a main block that creates an instance, calls the method, and prints the result and time.Putting it all together:- Class SubstringChecker with __init__ that validates substring and strings.- check_presence method that uses any() with a generator to check each string.- Exception handling in __init__ and check_presence.- Performance measurement using time module.Wait, but in the __init__, if the substring is not a string, it raises TypeError. Similarly, if any string in the list is not a string, it raises TypeError.In the check_presence method, it uses any(s is not None and self.substring in s for s in self.strings). Wait, why check s is not None? Because if a string is None, it would cause an error when checking 'in'. So adding a condition to skip None or handle it.But in the __init__, we already checked that each string is a string, so they shouldn't be None. Unless the list contains None as a string, which is not possible because None is not a string. So perhaps in the __init__, if any element is None, it's not a string, so it would have been caught.Wait, in Python, None is of type NoneType, not str. So in the __init__, when checking isinstance(s, str), None would fail, so the __init__ would raise a TypeError. So in the check_presence method, we don't need to handle None because it's already been validated.So the check_presence can safely assume all elements are strings.So the code outline is:class SubstringChecker: def __init__(self, substring, strings): if not isinstance(substring, str): raise TypeError("Substring must be a string.") if not isinstance(strings, list): raise TypeError("Strings must be a list.") for s in strings: if not isinstance(s, str): raise TypeError("All elements in strings must be strings.") self.substring = substring self.strings = strings def check_presence(self): try: start_time = time.time() result = any(self.substring in s for s in self.strings) end_time = time.time() return result, end_time - start_time except Exception as e: raise Exception(f"An error occurred: {str(e)}")Then, in the main part:if __name__ == "__main__": substring = "abc" strings = ["hoabcll", "aaabcbc", "abcbal"] checker = SubstringChecker(substring, strings) result, time_taken = checker.check_presence() print(f"Substring found: {result}") print(f"Time taken: {time_taken:.6f} seconds")Wait, but in the __init__, if the strings list is empty, it's allowed, and check_presence would return False.What about case sensitivity? The problem didn't mention it, so assume it's case-sensitive.Now, considering large data inputs. The any() function is efficient because it stops at the first match. So for a large list, it doesn't have to check all elements if a match is found early.But if the substring is not present, it has to check all elements, which could be time-consuming for very large lists. So for optimization, perhaps pre-process the strings or use more efficient data structures.Another optimization could be to compile the substring into a regular expression, but for simple substring checks, the 'in' operator is already efficient.Alternatively, using multithreading or multiprocessing to check multiple strings at once, but that might complicate things and may not be necessary unless the dataset is extremely large.Another consideration is memory. If the strings list is very large, perhaps using a generator instead of a list could save memory, but the __init__ expects a list, so that's beyond the current scope.In terms of exception handling, the code already raises TypeErrors for invalid inputs. Additionally, in the check_presence method, it's wrapped in a try-except, but perhaps that's redundant because the __init__ already validated the inputs. However, it's good practice to handle unexpected errors.Wait, but in the check_presence method, the try-except is catching any exception and raising a generic one. Maybe it's better to let specific exceptions propagate or handle them appropriately.Alternatively, perhaps the try-except isn't needed because the __init__ has already validated the inputs, so the only possible exceptions would be from the 'in' operation, which shouldn't occur because all elements are strings.So maybe the try-except in check_presence is unnecessary. But including it provides a safety net.Another point: the performance measurement is done inside the check_presence method. So each call to check_presence will measure the time. That's fine.Testing the code with the given example:substring = "abc"strings = ["hoabcll", "aaabcbc", "abcbal"]The first string is "hoabcll" which contains "abc". So the result should be True.Another test case: substring "xyz", strings as above. Result should be False.What about an empty substring? The __init__ allows it because it's a string. But checking for an empty substring in any string will always return True. So perhaps in the __init__, we should also check that the substring is not empty. Or let the user handle it.The problem statement didn't specify, so perhaps it's beyond the current scope.Now, putting it all together, the code should handle the requirements: using classes, methods, exception handling, and performance monitoring.I think this covers the user's requirements. Now, I'll write the code accordingly.