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

   • 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.

     Check all answers on Stack Overflow

     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 MATLAB good for? Why is it so used by universities? When is it better than Python?

     Top Answer

     Answered Jun 23, 2012 · 77 votes

     Adam is only partially right. Many, if not most, mathematicians will never touch it. If there is a computer tool used at all, it's going to be something like Mathematica or Maple. Engineering departments, on the other hand, often rely on it and there are definitely useful things for some applied mathematicians. It's also used heavily in industry in some areas.

     Something you have to realize about MATLAB is that it started off as a wrapper on Fortran libraries for linear algebra. For a long time, it had an attitude that "all the world is an array of doubles (floats)". As a language, it has grown very organically, and there are some flaws that are very much baked in, if you look at it just as a programming language.

     However, if you look at it as an environment for doing certain types of research in, it has some real strengths. It's about as good as it gets for doing floating point linear algebra. The notation is simple and powerful, the implementation fast and trusted. It is very good at generating plots and other interactive tasks. There are a large number of `toolboxes' with good code for particular tasks, that are affordable. There is a large community of users that share numerical codes (Python + NumPy has nothing in the same league, at least yet)

     Python, warts and all, is a much better programming language (as are many others). However, it's a decade or so behind in terms of the tools.

     The key point is that the majority of people who use MATLAB are not programmers really, and don't want to be.

     It's a lousy choice for a general programming language; it's quirky, slow for many tasks (you need to vectorize things to get efficient codes), and not easy to integrate with the outside world. On the other hand, for the things it is good at, it is very very good. Very few things compare. There's a company with reasonable support and who knows how many man-years put into it. This can matter in industry.

     Strictly looking at your Python vs. MATLAB comparison, they are mostly different tools for different jobs. In the areas where they do overlap a bit, it's hard to say what the better route to go is (depends a lot on what you're trying to do). But mostly Python isn't all that good at MATLAB's core strengths, and vice versa.

     Other Answers

     Answered Oct 22, 2012 · 38 votes

     Most of answers do not get the point.

     There is ONE reason matlab is so good and so widely used:

     EXTREMELY FAST CODING

     I am a computer vision phD student and have been using matlab for 4 years, before my phD I was using different languages including C++, java, php, python... Most of the computer vision researchers are using exclusively matlab.

     1) Researchers need fast prototyping

     In research environment, we have (hopefully) often new ideas, and we want to test them really quick to see if it's worth keeping on in that direction. And most often only a tiny sub-part of what we code will be useful.

     Matlab is often slower at execution time, but we don't care much. Because we don't know in advance what method is going to be successful, we have to try many things, so our bottle neck is programming time, because our code will most often run a few times to get the results to publish, and that's all.

     So let's see how matlab can help.

     2) Everything I need is already there

     Matlab has really a lot of functions that I need, so that I don't have to reinvent them all the time:

     change the index of a matrix to 2d coordinate: ind2sub extract all patches of an image: im2col; compute a histogram of an image: hist(Im(:)); find the unique elements in a list unique(list); add a vector to all vectors of a matrix bsxfun(@plus,M,V); convolution on n-dimensional arrays convn(A); calculate the computation time of a sub part of the code: tic; %%code; toc; graphical interface to crop an image: imcrop(im);

     The list could be very long... And they are very easy to find by using the help.

     The closest to that is python...But It's just a pain in python, I have to go to google each time to look for the name of the function I need, and then I need to add packages, and the packages are not compatible one with another, the format of the matrix change, the convolution function only handle doubles but does not make an error when I give it char, just give a wrong output... no

     3) IDE

     An example: I launch a script. It produces an error because of a matrix. I can still execute code with the command line. I visualize it doing: imagesc(matrix). I see that the last line of the matrix is weird. I fix the bug. All variables are still set. I select the remaining of the code, press F9 to execute the selection, and everything goes on. Debuging becomes fast, thanks to that.

     Matlab underlines some of my errors before execution. So I can quickly see the problems. It proposes some way to make my code faster.

     There is an awesome profiler included in the IDE. KCahcegrind is such a pain to use compared to that.

     python's IDEs are awefull. python without ipython is not usable. I never manage to debug, using ipython.

     +autocompletion, help for function arguments,...

     4) Concise code

     To normalize all the columns of a matrix ( which I need all the time), I do: bsxfun(@times,A,1./sqrt(sum(A.^2)))

     To remove from a matrix all colums with small sum:

     A(:,sum(A)<e)=[]

     To do the computation on the GPU:

     gpuX = gpuarray(X); %%% code normally and everything is done on GPU-

     To paralize my code:

     parfor n=1:100%%% code normally and everything is multi-threaded-

     What language can beat that?

     And of course, I rarely need to make loops, everything is included in functions, which make the code way easier to read, and no headache with indices. So I can focus, on what I want to program, not how to program it.

     5) Plotting tools

     Matlab is famous for its plotting tools. They are very helpful.

     Python's plotting tools have much less features. But there is one thing super annoying. You can plot figures only once per script??? if I have along script I cannot display stuffs at each step ---> useless.

     6) Documentation

     Everything is very quick to access, everything is crystal clear, function names are well chosen. With python, I always need to google stuff, look in forums or stackoverflow.... complete time hog.

     PS: Finally, what I hate with matlab: its price

     Other Answers

     Answered Oct 10, 2008 · 34 votes

     I've been using matlab for many years in my research. It's great for linear algebra and has a large set of well-written toolboxes. The most recent versions are starting to push it into being closer to a general-purpose language (better optimizers, a much better object model, richer scoping rules, etc.).

     This past summer, I had a job where I used Python + numpy instead of Matlab. I enjoyed the change of pace. It's a "real" language (and all that entails), and it has some great numeric features like broadcasting arrays. I also really like the ipython environment.

     Here are some things that I prefer about Matlab:

     If I didn't have such a large existing codebase, I'd seriously consider switching to Python + numpy.

     Check all answers on Stack Overflow

     3/5

   • what is the order of looping (for loop) in python dictionary

     Top Answer

     Answered Jun 16, 2017 · 7 votes

     Python dictionaries don't have an order. However, you can specify an order by using the sorted(domains) function. By default, it sorts using the key.

     for key in sorted(domains): print key-

     will produce

     dehunoskus

     If you want to order based on values, you can use something like sorted(domains.items(), key = lambda(k, v): (v, k)).

     Check all answers on Stack Overflow

     4/5

   • What is the best algorithm for sorting a list with very large numbers in python

     Top Answer

     Answered Sep 29, 2017 · 2 votes

     Short answer: An integer list with less than 500000 item will have a negligible performance difference with sorting small numbers versus sorting large numbers. An integer list in the millions of items will have a vastly different sort times based on the integer ranges in the list.

     A quick set of benchmarks:

     list1 = A list of N integers of range 0-100000list2 = Another list of N integers of range 0-10**50

     sorting using list.sort() Running with Python 3.5.2.

     When N is 5000, sort times for both lists is 0.0 seconds

     When N is 50000, sort times are .014 and .016 seconds (negligible difference)

     When N is 500000, sort times are are .17 and .23 seconds (50% delta, but still a negligible difference).

     When N is 5000000, sort times are are 2.1 and 3.6 seconds (71% delta, noticable difference)

     Conclusion: if your list size is less than 500K integers, the sort times are rather negligible regardless of the integer range. The op's code implies N is less than 10K.

     Once you get into the lists of "millions of integers", we starter to see wider swings in perf especially with different python interpreters.

     def createRandomNumber(number_of_digits): x = 0 number_of_digits = int(number_of_digits) for i in range(number_of_digits): x = x*10 + int(10 * random.random()) return xdef createRandomNumberList(max_digits, count): l = [] for i in range(count): l.append(createRandomNumber(random.random()*max_digits+1)) return llist1 = createRandomNumberList(5, 50000)list2 = createRandomNumberList(50, 50000)print("sorting list1")start1 = time.time()list1.sort()end1 = time.time()print("sorting list2")start2 = time.time()list2.sort()end2 = time.time()print("time to sort list1: ", end1-start1)print("time to sort list2: ", end2-start2)

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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. github.com › topics › tagalog-dictionarytagalog-dictionary · GitHub Topics · GitHub

   github.com › topics › tagalog-dictionary

   • Cached

   Feb 19, 2023 · To associate your repository with the tagalog-dictionary topic, visit your repo's landing page and select "manage topics." GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.

4. People also ask

   How do I associate my repository with a Tagalog topic?

   • To associate your repository with the tagalog topic, visit your repo's landing page and select "manage topics." GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.

   tagalog · GitHub Topics · GitHub

   github.com/topics/tagalog

   See all results for this question

   What is the best first search algorithm?

   • Depending on the quality and type of heuristic function, the best-first search algorithm can behave as both the DFS ( depth-first search algorithm) and BFS ( breadth-first search algorithm ). It can also switch between them and is more efficient than BFS and DFS.

   The Best-First Search Algorithm in Python - Finxter

   blog.finxter.com/the-best-first-search-algorithm-in-python/

   See all results for this question

   Which stemming algorithms are available in Python?

   • Python implementations of the Porter, Porter2, Paice-Husk, and Lovins stemming algorithms for English are available in the stemming package It seems that they use different algorithms. I will try it, thanks!

   What is the best stemming method in Python? - Stack Overflow

   stackoverflow.com/questions/24647400/what-is-the-best-stemming-method-in-python

   See all results for this question

   How to use exponential search algorithm in Python?

   • The Python implementation of the exponential search algorithm is: return 0 index = 1 while index < len (numbers) and numbers[index] <= val: index = index * 2 return BinarySearch( arr[: min (index, len (numbers))], val) If we use the function to find the value of: print (index) The algorithm works by:

   Search Algorithms in Python - Stack Abuse

   stackabuse.com/search-algorithms-in-python/

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

   stackabuse.com › search-algorithms-in-python

   • Cached

   • Introduction
   • Membership Operators
   • Linear Search
   • Binary Search
   • Jump Search
   • Fibonacci Search
   • Exponential Search
   • Interpolation Search
   • Why Use Python For Searching?
   • Conclusion

   Searching for data stored in different data structures is a crucial part of pretty much every single application. There are many different algorithms available to utilize when searching, and each has different implementations and relies on different data structures to get the job done. Being able to choose a specific algorithm for a given task is a...

   See full list on stackabuse.com

   Algorithms develop and become optimized over time as a result of constant evolution and the need to find the most efficient solutions for underlying problems in different domains. Almost every programming language has its own implementation of a basic search algorithm, usually as a function that returns a Boolean value of True or Falsewhen an item ...

   See full list on stackabuse.com

   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 inoperator. The algorithm consists of iterating over an array and returning the index of the first occurrence of an item once it is found: So if we use the function to compute: Upon...

   See full list on stackabuse.com

   The binary search follows a divide-and-conquermethodology. It is faster than linear search but requires that the array be sorted before the algorithm is executed. Assuming that we're searching for a value val in a sorted array, the algorithm compares val to the value of the middle element of the array, which we'll call mid: 1. If midis the element ...

   See full list on stackabuse.com

   Jump Search is similar to binary search in that it works on a sorted array, and uses a similar divide-and-conquerapproach to search through it. It can be classified as an improvement of the linear search algorithm since it depends on a linear search to perform the actual comparison when searching for a value. Given a sorted array, instead of search...

   See full list on stackabuse.com

   Fibonacci search is another divide-and-conquer algorithm which bears similarities to both binary search and jump search. It gets its name because it uses Fibonacci numbersto calculate the block size or search range in each step. The algorithm works with three Fibonacci numbers at a time. Let's call the three numbers fibM, fibM_minus_1, and fibM_min...

   See full list on stackabuse.com

   Exponential search is another search algorithm that can be implemented quite simply in Python, compared to jump search and Fibonacci search which are both a bit complex. It is also known by the names galloping search, doubling search, and Struzik search. Exponential search depends on binary search to perform the final comparison of values. The algo...

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   Interpolation searchis another divide-and-conquer algorithm, similar to binary search. Unlike binary search, it does not always begin searching in the middle. Interpolation search calculates the probable position of the element we are searching for using the formula: Where the variables are: 1. numbers- our input array 2. val- the element we are se...

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   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. In Python, most of the search algorithms we discussed will work just as well if we're searching fo...

   See full list on stackabuse.com

   There are many possible ways to search for an element within a collection. In this article, we attempted to discuss a few search algorithms and their implementations in Python. Choosing which algorithm to use is based on the data you have to search through; your input array, which we've called numbersin all our implementations. 1. If you want to se...

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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. Videos

   • 

     22:06

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

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8. blog.finxter.com › the-best-first-search-algorithmThe Best-First Search Algorithm in Python - Finxter

   blog.finxter.com › the-best-first-search-algorithm

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   Dec 4, 2021 · The best-first search algorithm starts the graph traversal by marking the start vertex as visited, i.e. putting it in the dictionary and placing it into the priority queue of candidate vertices. We will use the term explored, which is synonymous with terms expanded or extended in other literature.

9. github.com › topics › tagalogtagalog · GitHub Topics · GitHub

   github.com › topics › tagalog

   • Cached

   Add this topic to your repo. To associate your repository with the tagalog topic, visit your repo's landing page and select "manage topics." GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.

10. towardsdatascience.com › a-complete-guide-toA Complete Guide to Dictionaries in Python | by Philip ...

    towardsdatascience.com › a-complete-guide-to

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    Apr 19, 2022 · What are Dictionaries. After Lists, Sets and Tuples, dictionaries are the next inbuilt data structure that comes ready in Python. They are commonly used in programming and lays the foundation for more advanced structures and functionality in Python within many different libraries. They take the form similar to an actual dictionary where you ...