* Adding a Quine in Python.
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* implement function to handle polynomial operations
* edit documentation
* fix type hint and linter errors
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* fix short variable name
* fix spelling
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* Added Readme file to document the hashing algorithm.
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* Adding ELFHash Algorithm
Adding a new Hash Algorithm.
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* For the better understanding of time taken.
In this change I have initialized a variable p with the value of (1e9+7) and then took the modulus of process time with it . This modification gives better time taken by the process . Firstly it was giving answer in the exponential now it gives in the integer form.
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* Description of DOuble hasing
* Fix sheebang
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* Added explanation and increased speed of the solution of problem 092
* updating DIRECTORY.md
* Added temporary fix to the failing of problem 104
* Reduced few seconds by minor improvements
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* quantum_teleportation.py
This code is for the #Hacktoberfest.
This file run the quantum teleportation circuit using Qiskit.
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* Update
Corrected some typos.
Add more comments for adding the gates.
Update the variable qc with quantum_circuit in the simulator and execute.
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* python return typehint solved.
* Fix long line
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* Updated info
Updated the readme section for sorts.
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* Added Manhattan distance algorithm, Fixes: #7776
* Forgot that isinstance can accept a tuple
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* Update manhattan_distance.py
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* Increased Readability Of Variables
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* added recursive dfs backtracking for count paths with doctests
* fixed doc testing
* added type hints
* redefined r as row, c as col
* fixed naming conventions, ran mypy, only tests that didn't pass were using List[], rathan list()
* added another doctest, as well as a explanation above
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* Update matrix/count_paths.py
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* Added cosine similarity
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* Resonant Frequency
* Resonant Frequency of LC Circuit
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* Updated resonant_frequency.py
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* Fixed doctest issues in resonant_frequency.py
* Algorithm for Electrical Impedance
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* Updated Algorithm for Electrical Impedance
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* Added Viterbi algorithm Fixes: #7465
Squashed commits
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* Added doctest for validators
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* Create recursive_approach_knapsack.py
Added a new naïve recursive approach to solve the knapsack problem.
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Updated
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* Update password_generator.py
1. Use secrets module instead of random for passwords as it gives a secure source of randomness
2. Add type annotations for functions
3. Replace ctbi (variable for the characters to be included) with a more meaningful and short name
4. Use integer division instead of obtaining the integer part of a division computing a floating point
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* Create centripetal_force.py
Centripetal force is the force acting on an object in curvilinear motion directed towards the axis of rotation or centre of curvature.
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* Create potential_energy.py
Finding the gravitational potential energy of an object with reference to the earth, by taking its mass and height above the ground as input
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* Cleanup the BFS
* Add both functions and timeit
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* Add performace results as comment
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* Create combination_sum_iv.py
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* Resolved PR Comments
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* minor change
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* Update maximum_subarray.py
1. Rectify documentation to indicate the correct output: function doesn't return the subarray, but rather returns a sum.
2. Make the function more Pythonic and optimal.
3. Make function annotation generic i.e. can accept any sequence.
4. Raise value error when the input sequence is empty.
* Update maximum_subarray.py
1. Use the conventions as mentioned in pep-0257.
2. Use negative infinity as the initial value for the current maximum and the answer.
* Update maximum_subarray.py
Avoid type conflict by returning the answer cast to an integer.
* Update other/maximum_subarray.py
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* Create fetch_amazon_product_data.py
This file provides a function which will take
a product name as input from the user,and fetch the necessary
information about that kind of products from Amazon like the product
title,link to that product,price of the product,the ratings of
the product and the discount available on the product
in the form of a csv file,this will help the users by improving searchability
and navigability and find the right product easily and in a short period of time,
it will also be beneficial for performing better analysis on products
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Modified function to return the data in the form of Pandas Dataframe,modified type hints and added a functionality to let the user determine if they need the data in a csv file
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* Implemented Swish Function
* Added more description and return hint in def
* Changed the name and added more descrition including test for sigmoid function
* Added * in front of links
* Adopt Python >= 3.8 assignment expressions using auto-walrus
* updating DIRECTORY.md
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