mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-23 21:11:08 +00:00
Rewrite build_directory_md.py (#1076)
* Rewrite build_directory_md.py * Regenerate DIRECTORY.md
This commit is contained in:
Christian Clauss
GitHub
parent
3b63857b65
commit
a0817bdcf0
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@ -19,5 +19,5 @@ script:
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--ignore=machine_learning/random_forest_classification/random_forest_classification.py
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--ignore=machine_learning/random_forest_regression/random_forest_regression.py
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after_success:
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- python scripts/build_directory_md.py
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- scripts/build_directory_md.py > DIRECTORY.md
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- cat DIRECTORY.md
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23
DIRECTORY.md
23
DIRECTORY.md
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@ -1,5 +1,6 @@
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## Arithmetic Analysis
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* [bisection](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/bisection.py)
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* [in static equilibrium](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/in_static_equilibrium.py)
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* [intersection](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/intersection.py)
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* [lu decomposition](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/lu_decomposition.py)
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* [newton method](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_method.py)
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@ -42,7 +43,6 @@
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* [burrows wheeler](https://github.com/TheAlgorithms/Python/blob/master/compression/burrows_wheeler.py)
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* [huffman](https://github.com/TheAlgorithms/Python/blob/master/compression/huffman.py)
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* [peak signal to noise ratio](https://github.com/TheAlgorithms/Python/blob/master/compression/peak_signal_to_noise_ratio.py)
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* Image Data
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## Conversions
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* [decimal to binary](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_binary.py)
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* [decimal to hexadecimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_hexadecimal.py)
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@ -62,9 +62,9 @@
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* [double hash](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/double_hash.py)
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* [hash table](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/hash_table.py)
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* [hash table with linked list](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/hash_table_with_linked_list.py)
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* [quadratic probing](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/quadratic_probing.py)
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* Number Theory
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* [prime numbers](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/number_theory/prime_numbers.py)
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* [quadratic probing](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/quadratic_probing.py)
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* Heap
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* [heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/heap.py)
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* Linked List
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@ -87,6 +87,7 @@
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* Trie
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* [trie](https://github.com/TheAlgorithms/Python/blob/master/data_structures/trie/trie.py)
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## Digital Image Processing
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* [change contrast](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/change_contrast.py)
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* Edge Detection
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* [canny](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/edge_detection/canny.py)
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* Filters
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@ -94,7 +95,6 @@
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* [gaussian filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/gaussian_filter.py)
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* [median filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/median_filter.py)
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* [sobel filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/sobel_filter.py)
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* Image Data
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## Divide And Conquer
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* [closest pair of points](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/closest_pair_of_points.py)
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* [max subarray sum](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/max_subarray_sum.py)
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@ -167,24 +167,22 @@
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* [lib](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra_python/src/lib.py)
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* [tests](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra_python/src/tests.py)
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## Machine Learning
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* [NaiveBayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/NaiveBayes.ipynb)
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* [decision tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
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* [gradient descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
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* [k means clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
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* [knn sklearn](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/knn_sklearn.py)
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* [linear regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/linear_regression.py)
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* [logistic regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/logistic_regression.py)
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* [NaiveBayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/NaiveBayes.ipynb)
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* [perceptron](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/perceptron.py)
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* [reuters one vs rest classifier](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/reuters_one_vs_rest_classifier.ipynb)
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* [scoring functions](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/scoring_functions.py)
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* Random Forest Classification
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* [random forest classification](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_classification/random_forest_classification.py)
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* [random forest classifier](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_classification/random_forest_classifier.ipynb)
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* [Social Network Ads](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_classification/Social_Network_Ads.csv)
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* Random Forest Regression
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* [Position Salaries](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_regression/Position_Salaries.csv)
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* [random forest regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_regression/random_forest_regression.ipynb)
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* [random forest regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_regression/random_forest_regression.py)
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* [reuters one vs rest classifier](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/reuters_one_vs_rest_classifier.ipynb)
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* [scoring functions](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/scoring_functions.py)
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## Maths
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* [3n+1](https://github.com/TheAlgorithms/Python/blob/master/maths/3n+1.py)
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* [abs](https://github.com/TheAlgorithms/Python/blob/master/maths/abs.py)
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@ -203,11 +201,15 @@
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* [find lcm](https://github.com/TheAlgorithms/Python/blob/master/maths/find_lcm.py)
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* [find max](https://github.com/TheAlgorithms/Python/blob/master/maths/find_max.py)
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* [find min](https://github.com/TheAlgorithms/Python/blob/master/maths/find_min.py)
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* [gaussian](https://github.com/TheAlgorithms/Python/blob/master/maths/gaussian.py)
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* [greater common divisor](https://github.com/TheAlgorithms/Python/blob/master/maths/greater_common_divisor.py)
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* [is square free](https://github.com/TheAlgorithms/Python/blob/master/maths/is_square_free.py)
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* [lucas series](https://github.com/TheAlgorithms/Python/blob/master/maths/lucas_series.py)
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* [mobius function](https://github.com/TheAlgorithms/Python/blob/master/maths/mobius_function.py)
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* [modular exponential](https://github.com/TheAlgorithms/Python/blob/master/maths/modular_exponential.py)
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* [newton raphson](https://github.com/TheAlgorithms/Python/blob/master/maths/newton_raphson.py)
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* [prime check](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_check.py)
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* [prime factors](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_factors.py)
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* [segmented sieve](https://github.com/TheAlgorithms/Python/blob/master/maths/segmented_sieve.py)
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* [sieve of eratosthenes](https://github.com/TheAlgorithms/Python/blob/master/maths/sieve_of_eratosthenes.py)
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* [simpson rule](https://github.com/TheAlgorithms/Python/blob/master/maths/simpson_rule.py)
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@ -219,6 +221,8 @@
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* [rotate matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/rotate_matrix.py)
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* [searching in sorted matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/searching_in_sorted_matrix.py)
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* [spiral print](https://github.com/TheAlgorithms/Python/blob/master/matrix/spiral_print.py)
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* Tests
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* [test matrix operation](https://github.com/TheAlgorithms/Python/blob/master/matrix/tests/test_matrix_operation.py)
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## Networking Flow
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* [ford fulkerson](https://github.com/TheAlgorithms/Python/blob/master/networking_flow/ford_fulkerson.py)
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* [minimum cut](https://github.com/TheAlgorithms/Python/blob/master/networking_flow/minimum_cut.py)
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@ -228,6 +232,7 @@
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* [fully connected neural network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/fully_connected_neural_network.ipynb)
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* [perceptron](https://github.com/TheAlgorithms/Python/blob/master/neural_network/perceptron.py)
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## Other
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* [Food wastage analysis from 1961-2013 (FAO)](https://github.com/TheAlgorithms/Python/blob/master/other/Food%20wastage%20analysis%20from%201961-2013%20(FAO).ipynb)
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* [anagrams](https://github.com/TheAlgorithms/Python/blob/master/other/anagrams.py)
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* [binary exponentiation](https://github.com/TheAlgorithms/Python/blob/master/other/binary_exponentiation.py)
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* [binary exponentiation 2](https://github.com/TheAlgorithms/Python/blob/master/other/binary_exponentiation_2.py)
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@ -235,7 +240,6 @@
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* [euclidean gcd](https://github.com/TheAlgorithms/Python/blob/master/other/euclidean_gcd.py)
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* [finding primes](https://github.com/TheAlgorithms/Python/blob/master/other/finding_primes.py)
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* [fischer yates shuffle](https://github.com/TheAlgorithms/Python/blob/master/other/fischer_yates_shuffle.py)
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* [Food wastage analysis from 1961-2013 (FAO)](https://github.com/TheAlgorithms/Python/blob/master/other/Food%20wastage%20analysis%20from%201961-2013%20(FAO).ipynb)
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* [frequency finder](https://github.com/TheAlgorithms/Python/blob/master/other/frequency_finder.py)
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* [game of life](https://github.com/TheAlgorithms/Python/blob/master/other/game_of_life.py)
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* [linear congruential generator](https://github.com/TheAlgorithms/Python/blob/master/other/linear_congruential_generator.py)
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@ -247,7 +251,6 @@
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* [tower of hanoi](https://github.com/TheAlgorithms/Python/blob/master/other/tower_of_hanoi.py)
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* [two sum](https://github.com/TheAlgorithms/Python/blob/master/other/two_sum.py)
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* [word patterns](https://github.com/TheAlgorithms/Python/blob/master/other/word_patterns.py)
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* [words](https://github.com/TheAlgorithms/Python/blob/master/other/words)
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## Project Euler
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* Problem 01
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* [sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_01/sol1.py)
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96
scripts/build_directory_md.py
Normal file → Executable file
96
scripts/build_directory_md.py
Normal file → Executable file
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@ -1,71 +1,45 @@
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"""
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This is a simple script that will scan through the current directory
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and generate the corresponding DIRECTORY.md file, can also specify
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files or folders to be ignored.
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"""
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#!/usr/bin/env python3
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import os
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from typing import Iterator
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URL_BASE = "https://github.com/TheAlgorithms/Python/blob/master"
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# Target URL (master)
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URL = "https://github.com/TheAlgorithms/Python/blob/master/"
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def good_filepaths(top_dir: str = ".") -> Iterator[str]:
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for dirpath, dirnames, filenames in os.walk(top_dir):
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dirnames[:] = [d for d in dirnames if d != "scripts" and d[0] not in "._"]
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for filename in filenames:
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if filename == "__init__.py":
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continue
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if os.path.splitext(filename)[1] in (".py", ".ipynb"):
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yield os.path.join(dirpath, filename).lstrip("./")
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def tree(d, ignores, ignores_ext):
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return _markdown(d, ignores, ignores_ext, 0)
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def _markdown(parent, ignores, ignores_ext, depth):
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out = ""
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dirs, files = [], []
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for i in os.listdir(parent):
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full = os.path.join(parent, i)
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name, ext = os.path.splitext(i)
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if i not in ignores and ext not in ignores_ext:
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if os.path.isfile(full):
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# generate list
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pre = parent.replace("./", "").replace(" ", "%20")
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# replace all spaces to safe URL
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child = i.replace(" ", "%20")
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files.append((pre, child, name))
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else:
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dirs.append(i)
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# Sort files
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files.sort(key=lambda e: e[2].lower())
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for f in files:
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pre, child, name = f
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out += " " * depth + "* [" + name.replace("_", " ") + "](" + URL + pre + "/" + child + ")\n"
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# Sort directories
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dirs.sort()
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for i in dirs:
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full = os.path.join(parent, i)
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i = i.replace("_", " ").title()
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if depth == 0:
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out += "## " + i + "\n"
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else:
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out += " " * depth + "* " + i + "\n"
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out += _markdown(full, ignores, ignores_ext, depth+1)
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return out
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def md_prefix(i):
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return f"{i * ' '}*" if i else "##"
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# Specific files or folders with the given names will be ignored
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ignores = [".vs",
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".gitignore",
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".git",
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"scripts",
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"__init__.py",
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"requirements.txt",
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".github"
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]
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# Files with given entensions will be ignored
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ignores_ext = [
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".md",
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".ipynb",
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".png",
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".jpg",
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".yml"
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]
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def print_path(old_path: str, new_path: str) -> str:
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old_parts = old_path.split(os.sep)
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for i, new_part in enumerate(new_path.split(os.sep)):
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if i + 1 > len(old_parts) or old_parts[i] != new_part:
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if new_part:
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print(f"{md_prefix(i)} {new_part.replace('_', ' ').title()}")
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return new_path
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def print_directory_md(top_dir: str = ".") -> None:
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old_path = ""
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for filepath in sorted(good_filepaths()):
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filepath, filename = os.path.split(filepath)
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if filepath != old_path:
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old_path = print_path(old_path, filepath)
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indent = (filepath.count(os.sep) + 1) if filepath else 0
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url = "/".join((URL_BASE, filepath, filename)).replace(" ", "%20")
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filename = os.path.splitext(filename.replace("_", " "))[0]
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print(f"{md_prefix(indent)} [{filename}]({url})")
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if __name__ == "__main__":
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with open("DIRECTORY.md", "w+") as f:
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f.write(tree(".", ignores, ignores_ext))
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print_directory_md(".")
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