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1. Top results related to what is better search algorithm for tagalog dictionary python or c

   • What is better in python, a Dictionary or Mysql?

     Top Answer

     Answered Oct 10, 2010 · 5 votes

     Generally speaking, if you want information from a database, ask the database for what you need. MySQL (and other database engines) are designed to retrieve data as efficiently as possible.

     Trying to write your own procedures for retrieving data is trying to outsmart the talented people who have already imbued MySQL with so much data processing power.

     This isn't to say it's never appropriate to load data into Python, but you should be sure that a database query isn't the right way to go first.

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     1/5

   • What is a better way to match multiple substrings in a string than to search for each substring in a loop?

     Top Answer

     Answered Apr 04, 2023 · 6 votes

     It's hard to suggest an optimal solution without seeing the actual data, but you can try these things:

     • Generate a single pattern matching all values. This way you would only need to search the string once (instead of once per value).
     • Skip escaping values unless they contain special characters (like '^' or '*').
     • Create the resulting list using a list comprehension instead of calling list.extend() repeatedly.

     # 'str' is a built-in function, so use another name insteadstring = 'A Test test string from which I want to match multiple substrings'values = ['test', 'test2', 'Multiple', 'ring', 'match']pattern = r'\b({})\b'.format('|'.join(map(re.escape, values)))-# unique matches, uppercasedmatches = set(map(str.upper, re.findall(pattern, string, regex.IGNORECASE)))-# arrange the results as they appear in `values`matched_values = [v for value in values if (v := value.upper()) in matches]print(matched_values) # ['TEST', 'MULTIPLE', 'MATCH']-

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     2/5

   • What is a better way to match multiple substrings in a string than to search for each substring in a loop?

     Top Answer

     Answered Apr 04, 2023 · 6 votes

     It's hard to suggest an optimal solution without seeing the actual data, but you can try these things:

     • Generate a single pattern matching all values. This way you would only need to search the string once (instead of once per value).
     • Skip escaping values unless they contain special characters (like '^' or '*').
     • Create the resulting list using a list comprehension instead of calling list.extend() repeatedly.

     # 'str' is a built-in function, so use another name insteadstring = 'A Test test string from which I want to match multiple substrings'values = ['test', 'test2', 'Multiple', 'ring', 'match']pattern = r'\b({})\b'.format('|'.join(map(re.escape, values)))-# unique matches, uppercasedmatches = set(map(str.upper, re.findall(pattern, string, regex.IGNORECASE)))-# arrange the results as they appear in `values`matched_values = [v for value in values if (v := value.upper()) in matches]print(matched_values) # ['TEST', 'MULTIPLE', 'MATCH']-

     Check all answers on Stack Overflow

     3/5

   • What is the purpose of a zip function (as in Python or C# 4.0)?

     Top Answer

     Answered Apr 10, 2024 · 15 votes

     Someone actually asked a question here fairly recently that I answered with the Zip extension method, so it's obviously important for some people. ;)

     Actually, it is a fairly important operation for mathematical algorithms - matrices, curve fitting, interpolation, pattern recognition, that sort of thing. Also very important in engineering applications like digital signal processing where much of what you do is combine multiple signals or apply linear transforms to them - both are based on the sample index, hence, zip it. Zipping two sequences is far, far faster than sorting and joining them based on some key, especially when you know in advance that the sequences have the same number of elements and are in the same order.

     I can't get into tight specifics here on account of my current employment, but speaking generally, this is also valuable for telemetry data - industrial, scientific, that sort of thing. Often you'll have time sequences of data coming from hundreds or thousands of points - parallel sources - and you need to aggregate, but horizontally, over devices, not over time. At the end, you want another time sequence, but with the sum or average or some other aggregate of all the individual points.

     It may sound like a simple sort/group/join in SQL Server (for example) but it's actually really hard to do efficiently this way. For one thing, the timestamps may not match exactly, but you don't care about differences of a few milliseconds, so you end up having to generate a surrogate key/row number and group on that - and of course, the surrogate row number is nothing more than the time index which you already had. Zipping is simple, fast, and infinitely parallelizable.

     I don't know if I'd call it foundational, but it it is important. I don't use the Reverse method very often either, but by the same token I'm glad I don't have to keep writing it myself on those rare occasions when I do find a need for it.

     One of the reasons it might not seem that useful to you now is that .NET/C# 3.5 does not have tuples. C# 4 does have tuples, and when you're working with tuples, zipping really is a fundamental operation because ordering is strictly enforced.

     Other Answers

     Answered Mar 12, 2010 · 14 votes

     A use case:

     >>> fields = ["id", "name", "location"]>>> values = ["13", "bill", "redmond"]>>> dict(zip(fields, values)){'location': 'redmond', 'id': '13', 'name': 'bill'}-

     Try doing this without zip...

     Other Answers

     Answered Mar 12, 2010 · 13 votes

     zip is useful if you'd like to iterate over multiple iterables simultaneously, which is a reasonably common scenario in Python.

     One real-world scenario where zip has come in handy for me is if you have an M by N array, and you want to look at columns instead of rows. For example:

     >>> five_by_two = ((0, 1), (1, 2), (2, 3), (3, 4), (4, 5))>>> two_by_five = tuple(zip(*five_by_two))>>> two_by_five((0, 1, 2, 3, 4), (1, 2, 3, 4, 5))-

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     4/5

   • Python: better to use dictionary or hashmap for common elements of array

     Top Answer

     Answered Mar 08, 2019 · 0 votes

     You should use a set:

     def common(first, second): return set(first) & set(second)-

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     5/5

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2. stackoverflow.com › questions › 19103785python - Efficient Dictionary Searching? - Stack Overflow

   stackoverflow.com › questions › 19103785

   • Cached

   Oct 1, 2013 · 10. data_dict.keys() returns an unsorted list of keys in the dictionary. Thus each time you check to see if a given key is in the dictionary, you're doing a linear search across the list of keys (an O (n) operation). The longer your list, the longer it takes to search for a given key. Contrast this to data_dict[keyStr].

   Usage example

   if key in data_dict:

   See more on stackoverflow

3. www.geeksforgeeks.org › lemmatization-vs-stemmingLemmatization vs. Stemming: A Deep Dive into NLP’s Text ...

   www.geeksforgeeks.org › lemmatization-vs-stemming

   • Cached

   2 days ago · Algorithms. Uses dictionaries and morphological analysis. Uses rule-based algorithms like Porter, Snowball, and Lancaster Stemmers. Accuracy. Produces more accurate and meaningful words. Less accurate, may produce non-meaningful stems. Output Example “Running” → “run”, “Better” → “good”.

4. Videos

   • 

     22:06

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     Python Tutorial #5: Dictionary | List of Dictionaries | INDEPTH Tutorial | Tagalog | Filipino

     May 17, 2020

     31.6K Views

   • 

     35:31

     youtube.com

     Dictionaries in python | Dictionaries Built-in functions | Python Tutorials for Beginners #lec67

     Jun 4, 2023

     77.5K Views

   • 

     13:09

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     Python Tutorial for Beginners (TAGALOG VERSION) - #1 (Introduction) What is Python?

     Apr 18, 2020

     4.4K Views

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5. www.geeksforgeeks.org › searching-algorithmsSearching Algorithms - GeeksforGeeks

   www.geeksforgeeks.org › searching-algorithms

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   • What Is Searching?
   • Searching Terminologies
   • Importance of Searching in DSA
   • Applications of Searching
   • Basics of Searching Algorithms
   • Searching Algorithms
   • Comparisons Between Different Searching Algorithms
   • Library Implementations of Searching Algorithms
   • Easy Problems on Searching
   • Medium Problems on Searching

   Searching is the fundamental process of locating a specific element or item within a collection of data. This collection of data can take various forms, such as arrays, lists, trees, or other structured representations. The primary objective of searching is to determine whether the desired element exists within the data, and if so, to identify its ...

   See full list on geeksforgeeks.org

   Target Element:

   In searching, there is always a specific target element or item that you want to find within the data collection. This target could be a value, a record, a key, or any other data entity of interest.

   Search Space:

   The search space refers to the entire collection of data within which you are looking for the target element. Depending on the data structure used, the search space may vary in size and organization.

   Complexity:

   Searching can have different levels of complexity depending on the data structure and the algorithm used. The complexity is often measured in terms of time and space requirements.

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   Efficiency:Efficient searching algorithms improve program performance.

   Data Retrieval: Quickly find and retrieve specific data from large datasets.

   Database Systems:Enables fast querying of databases.

   Problem Solving: Used in a wide range of problem-solving tasks.

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   Searching algorithms have numerous applications across various fields. Here are some common applications: 1. Information Retrieval: Search engines like Google, Bing, and Yahoo use sophisticated searching algorithms to retrieve relevant information from vast amounts of data on the web. 2. Database Systems:Searching is fundamental in database systems...

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   Introduction to Searching – Data Structure and Algorithm Tutorial

   Importance of searching in Data Structure

   What is the purpose of the search algorithm?

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   Linear Search

   Sentinel Linear Search

   Binary Search

   Meta Binary Search | One-Sided Binary Search

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   Linear Search vs Binary Search

   Interpolation search vs Binary search

   Why is Binary Search preferred over Ternary Search?

   Is Sentinel Linear Search better than normal Linear Search?

   See full list on geeksforgeeks.org

   Binary Search functions in C++ STL (binary_search, lower_bound and upper_bound)

   Arrays.binarySearch() in Java with examples | Set 1

   Arrays.binarySearch() in Java with examples | Set 2 (Search in subarray)

   Collections.binarySearch() in Java with Examples

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   Find the largest three elements in an array

   Find the Missing Number

   Find the first repeating element in an array of integers

   Find the missing and repeating number

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   Find all triplets with zero sum

   Find the element before which all the elements are smaller than it, and after which all are greater

   Find the largest pair sum in an unsorted array

   K’th Smallest/Largest Element in Unsorted Array

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6. medium.com › analytics-vidhya › search-algorithms-inSearch Algorithms in Python, Explained | by Paul ... - Medium

   medium.com › analytics-vidhya › search-algorithms-in

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   Apr 11, 2021 · Binary search is a great algorithm that can solve even the largest searches in a small amount of time. Hash tables are used for instant access to data. Hash tables are the same as dictionaries in ...

   • Author: Paul Torres

7. stackabuse.com › search-algorithms-in-pythonSearch Algorithms in Python - Stack Abuse

   stackabuse.com › search-algorithms-in-python

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   Oct 23, 2023 · The binary search algorithm can be written either recursively or iteratively. Recursion is generally slower in Python because it requires the allocation of new stack frames. Since a good search algorithm should be as fast and accurate as possible, let's consider the iterative implementation of binary search:

8. www.freecodecamp.org › news › search-algorithmsSearch Algorithms Explained with Examples in Java, Python ...

   www.freecodecamp.org › news › search-algorithms

   • Cached

   Dec 13, 2019 · Steps. Jump the array 2^i elements at a time searching for the condition Array[2^(i-1)] < valueWanted < Array[2^i] . If 2^i is greater than the lenght of array, then set the upper bound to the length of the array. Do a binary search between Array[2^(i-1)] and Array[2^i] // C++ program to find an element x in a.

9. People also ask

   Is Python a good programming language for implementing search algorithms?

   • Python is highly readable and efficient when compared to older programming languages like Java, Fortran, C, C++ etc. One key advantage of using Python for implementing search algorithms is that you don't have to worry about casting or explicit typing.

   Search Algorithms in Python - Stack Abuse

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   What is a search algorithm in Computer Science?

   • Searching algorithms are essential tools in computer science used to locate specific items within a collection of data. These algorithms are designed to efficiently navigate through data structures to find the desired information, making them fundamental in various applications such as databases, web search engines, and more. What is Searching?

   Searching Algorithms - GeeksforGeeks

   www.geeksforgeeks.org/searching-algorithms/

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   What are the advantages of using Python for implementing search algorithms?

   • One key advantage of using Python for implementing search algorithms is that you don't have to worry about casting or explicit typing. In Python, most of the search algorithms we discussed will work just as well if we're searching for a String.

   Search Algorithms in Python - Stack Abuse

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   What is linear search in Python?

   • Linear search is one of the simplest searching algorithms and the easiest to understand. We can think of it as a ramped-up version of our own implementation of Python's in operator. The algorithm consists of iterating over an array and returning the index of the first occurrence of an item once it is found: if numbers[i] == element: return i

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10. github.com › crlwingen › TagalogStemmerPythonTagalog Words Stemmer using Python - GitHub

    github.com › crlwingen › TagalogStemmerPython

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    Tagalog Words Stemmer is a program that processes Tagalog words by removing all of its affixes and returns the root of the words. Sample Output: Input: "Patuloy pa din sila sa paghahanap ng posibleng gamot sa malubhang sakit ng dinaramdam ng kanyang ina."