diff --git a/.devcontainer/Dockerfile b/.devcontainer/Dockerfile new file mode 100644 index 000000000..b5a5347c6 --- /dev/null +++ b/.devcontainer/Dockerfile @@ -0,0 +1,8 @@ +# https://github.com/microsoft/vscode-dev-containers/blob/main/containers/python-3/README.md +ARG VARIANT=3.11-bookworm +FROM mcr.microsoft.com/vscode/devcontainers/python:${VARIANT} +COPY requirements.txt /tmp/pip-tmp/ +RUN python3 -m pip install --upgrade pip \ + && python3 -m pip install --no-cache-dir install -r /tmp/pip-tmp/requirements.txt \ + && pipx install pre-commit ruff \ + && pre-commit install diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json new file mode 100644 index 000000000..c5a855b25 --- /dev/null +++ b/.devcontainer/devcontainer.json @@ -0,0 +1,42 @@ +{ + "name": "Python 3", + "build": { + "dockerfile": "Dockerfile", + "context": "..", + "args": { + // Update 'VARIANT' to pick a Python version: 3, 3.10, 3.9, 3.8, 3.7, 3.6 + // Append -bullseye or -buster to pin to an OS version. + // Use -bullseye variants on local on arm64/Apple Silicon. + "VARIANT": "3.11-bookworm", + } + }, + + // Configure tool-specific properties. + "customizations": { + // Configure properties specific to VS Code. + "vscode": { + // Set *default* container specific settings.json values on container create. + "settings": { + "python.defaultInterpreterPath": "/usr/local/bin/python", + "python.linting.enabled": true, + "python.formatting.blackPath": "/usr/local/py-utils/bin/black", + "python.linting.mypyPath": "/usr/local/py-utils/bin/mypy" + }, + + // Add the IDs of extensions you want installed when the container is created. + "extensions": [ + "ms-python.python", + "ms-python.vscode-pylance" + ] + } + }, + + // Use 'forwardPorts' to make a list of ports inside the container available locally. + // "forwardPorts": [], + + // Use 'postCreateCommand' to run commands after the container is created. + // "postCreateCommand": "pip3 install --user -r requirements.txt", + + // Comment out to connect as root instead. More info: https://aka.ms/vscode-remote/containers/non-root. + "remoteUser": "vscode" +} diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 1d92d2ff3..b08139561 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -16,12 +16,12 @@ repos: - id: auto-walrus - repo: https://github.com/astral-sh/ruff-pre-commit - rev: v0.0.275 + rev: v0.0.284 hooks: - id: ruff - repo: https://github.com/psf/black - rev: 23.3.0 + rev: 23.7.0 hooks: - id: black @@ -33,7 +33,7 @@ repos: - tomli - repo: https://github.com/tox-dev/pyproject-fmt - rev: "0.12.1" + rev: "0.13.1" hooks: - id: pyproject-fmt @@ -51,7 +51,7 @@ repos: - id: validate-pyproject - repo: https://github.com/pre-commit/mirrors-mypy - rev: v1.4.1 + rev: v1.5.0 hooks: - id: mypy args: diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 618cca868..4a1bb6527 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -25,6 +25,8 @@ We appreciate any contribution, from fixing a grammar mistake in a comment to im Your contribution will be tested by our [automated testing on GitHub Actions](https://github.com/TheAlgorithms/Python/actions) to save time and mental energy. After you have submitted your pull request, you should see the GitHub Actions tests start to run at the bottom of your submission page. If those tests fail, then click on the ___details___ button try to read through the GitHub Actions output to understand the failure. If you do not understand, please leave a comment on your submission page and a community member will try to help. +If you are interested in resolving an [open issue](https://github.com/TheAlgorithms/Python/issues), simply make a pull request with your proposed fix. __We do not assign issues in this repo__ so please do not ask for permission to work on an issue. + Please help us keep our issue list small by adding `Fixes #{$ISSUE_NUMBER}` to the description of pull requests that resolve open issues. For example, if your pull request fixes issue #10, then please add the following to its description: ``` diff --git a/DIRECTORY.md b/DIRECTORY.md index d25d665ef..be5fa3584 100644 --- a/DIRECTORY.md +++ b/DIRECTORY.md @@ -74,6 +74,7 @@ * [Game Of Life](cellular_automata/game_of_life.py) * [Nagel Schrekenberg](cellular_automata/nagel_schrekenberg.py) * [One Dimensional](cellular_automata/one_dimensional.py) + * [Wa Tor](cellular_automata/wa_tor.py) ## Ciphers * [A1Z26](ciphers/a1z26.py) @@ -236,8 +237,8 @@ * [Double Ended Queue](data_structures/queue/double_ended_queue.py) * [Linked Queue](data_structures/queue/linked_queue.py) * [Priority Queue Using List](data_structures/queue/priority_queue_using_list.py) + * [Queue By List](data_structures/queue/queue_by_list.py) * [Queue By Two Stacks](data_structures/queue/queue_by_two_stacks.py) - * [Queue On List](data_structures/queue/queue_on_list.py) * [Queue On Pseudo Stack](data_structures/queue/queue_on_pseudo_stack.py) * Stacks * [Balanced Parentheses](data_structures/stacks/balanced_parentheses.py) @@ -293,7 +294,7 @@ * [Inversions](divide_and_conquer/inversions.py) * [Kth Order Statistic](divide_and_conquer/kth_order_statistic.py) * [Max Difference Pair](divide_and_conquer/max_difference_pair.py) - * [Max Subarray Sum](divide_and_conquer/max_subarray_sum.py) + * [Max Subarray](divide_and_conquer/max_subarray.py) * [Mergesort](divide_and_conquer/mergesort.py) * [Peak](divide_and_conquer/peak.py) * [Power](divide_and_conquer/power.py) @@ -324,8 +325,7 @@ * [Matrix Chain Order](dynamic_programming/matrix_chain_order.py) * [Max Non Adjacent Sum](dynamic_programming/max_non_adjacent_sum.py) * [Max Product Subarray](dynamic_programming/max_product_subarray.py) - * [Max Sub Array](dynamic_programming/max_sub_array.py) - * [Max Sum Contiguous Subsequence](dynamic_programming/max_sum_contiguous_subsequence.py) + * [Max Subarray Sum](dynamic_programming/max_subarray_sum.py) * [Min Distance Up Bottom](dynamic_programming/min_distance_up_bottom.py) * [Minimum Coin Change](dynamic_programming/minimum_coin_change.py) * [Minimum Cost Path](dynamic_programming/minimum_cost_path.py) @@ -336,9 +336,11 @@ * [Minimum Tickets Cost](dynamic_programming/minimum_tickets_cost.py) * [Optimal Binary Search Tree](dynamic_programming/optimal_binary_search_tree.py) * [Palindrome Partitioning](dynamic_programming/palindrome_partitioning.py) + * [Regex Match](dynamic_programming/regex_match.py) * [Rod Cutting](dynamic_programming/rod_cutting.py) * [Subset Generation](dynamic_programming/subset_generation.py) * [Sum Of Subset](dynamic_programming/sum_of_subset.py) + * [Tribonacci](dynamic_programming/tribonacci.py) * [Viterbi](dynamic_programming/viterbi.py) * [Word Break](dynamic_programming/word_break.py) @@ -512,7 +514,7 @@ * Lstm * [Lstm Prediction](machine_learning/lstm/lstm_prediction.py) * [Multilayer Perceptron Classifier](machine_learning/multilayer_perceptron_classifier.py) - * [Polymonial Regression](machine_learning/polymonial_regression.py) + * [Polynomial Regression](machine_learning/polynomial_regression.py) * [Scoring Functions](machine_learning/scoring_functions.py) * [Self Organizing Map](machine_learning/self_organizing_map.py) * [Sequential Minimum Optimization](machine_learning/sequential_minimum_optimization.py) @@ -571,9 +573,7 @@ * [Fermat Little Theorem](maths/fermat_little_theorem.py) * [Fibonacci](maths/fibonacci.py) * [Find Max](maths/find_max.py) - * [Find Max Recursion](maths/find_max_recursion.py) * [Find Min](maths/find_min.py) - * [Find Min Recursion](maths/find_min_recursion.py) * [Floor](maths/floor.py) * [Gamma](maths/gamma.py) * [Gamma Recursive](maths/gamma_recursive.py) @@ -586,17 +586,16 @@ * [Hardy Ramanujanalgo](maths/hardy_ramanujanalgo.py) * [Hexagonal Number](maths/hexagonal_number.py) * [Integration By Simpson Approx](maths/integration_by_simpson_approx.py) + * [Interquartile Range](maths/interquartile_range.py) * [Is Int Palindrome](maths/is_int_palindrome.py) * [Is Ip V4 Address Valid](maths/is_ip_v4_address_valid.py) * [Is Square Free](maths/is_square_free.py) * [Jaccard Similarity](maths/jaccard_similarity.py) * [Juggler Sequence](maths/juggler_sequence.py) - * [Kadanes](maths/kadanes.py) * [Karatsuba](maths/karatsuba.py) * [Krishnamurthy Number](maths/krishnamurthy_number.py) * [Kth Lexicographic Permutation](maths/kth_lexicographic_permutation.py) * [Largest Of Very Large Numbers](maths/largest_of_very_large_numbers.py) - * [Largest Subarray Sum](maths/largest_subarray_sum.py) * [Least Common Multiple](maths/least_common_multiple.py) * [Line Length](maths/line_length.py) * [Liouville Lambda](maths/liouville_lambda.py) @@ -712,7 +711,6 @@ * [Exponential Linear Unit](neural_network/activation_functions/exponential_linear_unit.py) * [Back Propagation Neural Network](neural_network/back_propagation_neural_network.py) * [Convolution Neural Network](neural_network/convolution_neural_network.py) - * [Input Data](neural_network/input_data.py) * [Perceptron](neural_network/perceptron.py) * [Simple Neural Network](neural_network/simple_neural_network.py) @@ -733,7 +731,6 @@ * [Linear Congruential Generator](other/linear_congruential_generator.py) * [Lru Cache](other/lru_cache.py) * [Magicdiamondpattern](other/magicdiamondpattern.py) - * [Maximum Subarray](other/maximum_subarray.py) * [Maximum Subsequence](other/maximum_subsequence.py) * [Nested Brackets](other/nested_brackets.py) * [Number Container System](other/number_container_system.py) @@ -744,7 +741,9 @@ * [Tower Of Hanoi](other/tower_of_hanoi.py) ## Physics + * [Altitude Pressure](physics/altitude_pressure.py) * [Archimedes Principle](physics/archimedes_principle.py) + * [Basic Orbital Capture](physics/basic_orbital_capture.py) * [Casimir Effect](physics/casimir_effect.py) * [Centripetal Force](physics/centripetal_force.py) * [Grahams Law](physics/grahams_law.py) @@ -1066,7 +1065,6 @@ * [Q Fourier Transform](quantum/q_fourier_transform.py) * [Q Full Adder](quantum/q_full_adder.py) * [Quantum Entanglement](quantum/quantum_entanglement.py) - * [Quantum Random](quantum/quantum_random.py) * [Quantum Teleportation](quantum/quantum_teleportation.py) * [Ripple Adder Classic](quantum/ripple_adder_classic.py) * [Single Qubit Measure](quantum/single_qubit_measure.py) @@ -1172,6 +1170,7 @@ * [Is Pangram](strings/is_pangram.py) * [Is Spain National Id](strings/is_spain_national_id.py) * [Is Srilankan Phone Number](strings/is_srilankan_phone_number.py) + * [Is Valid Email Address](strings/is_valid_email_address.py) * [Jaro Winkler](strings/jaro_winkler.py) * [Join](strings/join.py) * [Knuth Morris Pratt](strings/knuth_morris_pratt.py) diff --git a/README.md b/README.md index bf6e0ed3c..d8eba4e01 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,7 @@ Contributions Welcome - + Discord chat @@ -42,7 +42,7 @@ Read through our [Contribution Guidelines](CONTRIBUTING.md) before you contribut ## Community Channels -We are on [Discord](https://discord.gg/c7MnfGFGa6) and [Gitter](https://gitter.im/TheAlgorithms/community)! Community channels are a great way for you to ask questions and get help. Please join us! +We are on [Discord](https://the-algorithms.com/discord) and [Gitter](https://gitter.im/TheAlgorithms/community)! Community channels are a great way for you to ask questions and get help. Please join us! ## List of Algorithms diff --git a/arithmetic_analysis/newton_raphson.py b/arithmetic_analysis/newton_raphson.py index aee2f07e5..1b90ad417 100644 --- a/arithmetic_analysis/newton_raphson.py +++ b/arithmetic_analysis/newton_raphson.py @@ -25,9 +25,11 @@ def newton_raphson( """ x = a while True: - x = Decimal(x) - (Decimal(eval(func)) / Decimal(eval(str(diff(func))))) + x = Decimal(x) - ( + Decimal(eval(func)) / Decimal(eval(str(diff(func)))) # noqa: S307 + ) # This number dictates the accuracy of the answer - if abs(eval(func)) < precision: + if abs(eval(func)) < precision: # noqa: S307 return float(x) diff --git a/cellular_automata/game_of_life.py b/cellular_automata/game_of_life.py index 3382af7b5..d691a2b73 100644 --- a/cellular_automata/game_of_life.py +++ b/cellular_automata/game_of_life.py @@ -10,7 +10,7 @@ Python: - 3.5 Usage: - - $python3 game_o_life + - $python3 game_of_life Game-Of-Life Rules: @@ -52,7 +52,8 @@ def seed(canvas: list[list[bool]]) -> None: def run(canvas: list[list[bool]]) -> list[list[bool]]: - """This function runs the rules of game through all points, and changes their + """ + This function runs the rules of game through all points, and changes their status accordingly.(in the same canvas) @Args: -- @@ -60,7 +61,7 @@ def run(canvas: list[list[bool]]) -> list[list[bool]]: @returns: -- - None + canvas of population after one step """ current_canvas = np.array(canvas) next_gen_canvas = np.array(create_canvas(current_canvas.shape[0])) @@ -70,10 +71,7 @@ def run(canvas: list[list[bool]]) -> list[list[bool]]: pt, current_canvas[r - 1 : r + 2, c - 1 : c + 2] ) - current_canvas = next_gen_canvas - del next_gen_canvas # cleaning memory as we move on. - return_canvas: list[list[bool]] = current_canvas.tolist() - return return_canvas + return next_gen_canvas.tolist() def __judge_point(pt: bool, neighbours: list[list[bool]]) -> bool: @@ -98,7 +96,7 @@ def __judge_point(pt: bool, neighbours: list[list[bool]]) -> bool: if pt: if alive < 2: state = False - elif alive == 2 or alive == 3: + elif alive in {2, 3}: state = True elif alive > 3: state = False diff --git a/cellular_automata/wa_tor.py b/cellular_automata/wa_tor.py new file mode 100644 index 000000000..e423d1595 --- /dev/null +++ b/cellular_automata/wa_tor.py @@ -0,0 +1,550 @@ +""" +Wa-Tor algorithm (1984) + +@ https://en.wikipedia.org/wiki/Wa-Tor +@ https://beltoforion.de/en/wator/ +@ https://beltoforion.de/en/wator/images/wator_medium.webm + +This solution aims to completely remove any systematic approach +to the Wa-Tor planet, and utilise fully random methods. + +The constants are a working set that allows the Wa-Tor planet +to result in one of the three possible results. +""" + +from collections.abc import Callable +from random import randint, shuffle +from time import sleep +from typing import Literal + +WIDTH = 50 # Width of the Wa-Tor planet +HEIGHT = 50 # Height of the Wa-Tor planet + +PREY_INITIAL_COUNT = 30 # The initial number of prey entities +PREY_REPRODUCTION_TIME = 5 # The chronons before reproducing + +PREDATOR_INITIAL_COUNT = 50 # The initial number of predator entities +# The initial energy value of predator entities +PREDATOR_INITIAL_ENERGY_VALUE = 15 +# The energy value provided when consuming prey +PREDATOR_FOOD_VALUE = 5 +PREDATOR_REPRODUCTION_TIME = 20 # The chronons before reproducing + +MAX_ENTITIES = 500 # The max number of organisms on the board +# The number of entities to delete from the unbalanced side +DELETE_UNBALANCED_ENTITIES = 50 + + +class Entity: + """ + Represents an entity (either prey or predator). + + >>> e = Entity(True, coords=(0, 0)) + >>> e.prey + True + >>> e.coords + (0, 0) + >>> e.alive + True + """ + + def __init__(self, prey: bool, coords: tuple[int, int]) -> None: + self.prey = prey + # The (row, col) pos of the entity + self.coords = coords + + self.remaining_reproduction_time = ( + PREY_REPRODUCTION_TIME if prey else PREDATOR_REPRODUCTION_TIME + ) + self.energy_value = None if prey is True else PREDATOR_INITIAL_ENERGY_VALUE + self.alive = True + + def reset_reproduction_time(self) -> None: + """ + >>> e = Entity(True, coords=(0, 0)) + >>> e.reset_reproduction_time() + >>> e.remaining_reproduction_time == PREY_REPRODUCTION_TIME + True + >>> e = Entity(False, coords=(0, 0)) + >>> e.reset_reproduction_time() + >>> e.remaining_reproduction_time == PREDATOR_REPRODUCTION_TIME + True + """ + self.remaining_reproduction_time = ( + PREY_REPRODUCTION_TIME if self.prey is True else PREDATOR_REPRODUCTION_TIME + ) + + def __repr__(self) -> str: + """ + >>> Entity(prey=True, coords=(1, 1)) + Entity(prey=True, coords=(1, 1), remaining_reproduction_time=5) + >>> Entity(prey=False, coords=(2, 1)) # doctest: +NORMALIZE_WHITESPACE + Entity(prey=False, coords=(2, 1), + remaining_reproduction_time=20, energy_value=15) + """ + repr_ = ( + f"Entity(prey={self.prey}, coords={self.coords}, " + f"remaining_reproduction_time={self.remaining_reproduction_time}" + ) + if self.energy_value is not None: + repr_ += f", energy_value={self.energy_value}" + return f"{repr_})" + + +class WaTor: + """ + Represents the main Wa-Tor algorithm. + + :attr time_passed: A function that is called every time + time passes (a chronon) in order to visually display + the new Wa-Tor planet. The time_passed function can block + using time.sleep to slow the algorithm progression. + + >>> wt = WaTor(10, 15) + >>> wt.width + 10 + >>> wt.height + 15 + >>> len(wt.planet) + 15 + >>> len(wt.planet[0]) + 10 + >>> len(wt.get_entities()) == PREDATOR_INITIAL_COUNT + PREY_INITIAL_COUNT + True + """ + + time_passed: Callable[["WaTor", int], None] | None + + def __init__(self, width: int, height: int) -> None: + self.width = width + self.height = height + self.time_passed = None + + self.planet: list[list[Entity | None]] = [[None] * width for _ in range(height)] + + # Populate planet with predators and prey randomly + for _ in range(PREY_INITIAL_COUNT): + self.add_entity(prey=True) + for _ in range(PREDATOR_INITIAL_COUNT): + self.add_entity(prey=False) + self.set_planet(self.planet) + + def set_planet(self, planet: list[list[Entity | None]]) -> None: + """ + Ease of access for testing + + >>> wt = WaTor(WIDTH, HEIGHT) + >>> planet = [ + ... [None, None, None], + ... [None, Entity(True, coords=(1, 1)), None] + ... ] + >>> wt.set_planet(planet) + >>> wt.planet == planet + True + >>> wt.width + 3 + >>> wt.height + 2 + """ + self.planet = planet + self.width = len(planet[0]) + self.height = len(planet) + + def add_entity(self, prey: bool) -> None: + """ + Adds an entity, making sure the entity does + not override another entity + + >>> wt = WaTor(WIDTH, HEIGHT) + >>> wt.set_planet([[None, None], [None, None]]) + >>> wt.add_entity(True) + >>> len(wt.get_entities()) + 1 + >>> wt.add_entity(False) + >>> len(wt.get_entities()) + 2 + """ + while True: + row, col = randint(0, self.height - 1), randint(0, self.width - 1) + if self.planet[row][col] is None: + self.planet[row][col] = Entity(prey=prey, coords=(row, col)) + return + + def get_entities(self) -> list[Entity]: + """ + Returns a list of all the entities within the planet. + + >>> wt = WaTor(WIDTH, HEIGHT) + >>> len(wt.get_entities()) == PREDATOR_INITIAL_COUNT + PREY_INITIAL_COUNT + True + """ + return [entity for column in self.planet for entity in column if entity] + + def balance_predators_and_prey(self) -> None: + """ + Balances predators and preys so that prey + can not dominate the predators, blocking up + space for them to reproduce. + + >>> wt = WaTor(WIDTH, HEIGHT) + >>> for i in range(2000): + ... row, col = i // HEIGHT, i % WIDTH + ... wt.planet[row][col] = Entity(True, coords=(row, col)) + >>> entities = len(wt.get_entities()) + >>> wt.balance_predators_and_prey() + >>> len(wt.get_entities()) == entities + False + """ + entities = self.get_entities() + shuffle(entities) + + if len(entities) >= MAX_ENTITIES - MAX_ENTITIES / 10: + prey = [entity for entity in entities if entity.prey] + predators = [entity for entity in entities if not entity.prey] + + prey_count, predator_count = len(prey), len(predators) + + entities_to_purge = ( + prey[:DELETE_UNBALANCED_ENTITIES] + if prey_count > predator_count + else predators[:DELETE_UNBALANCED_ENTITIES] + ) + for entity in entities_to_purge: + self.planet[entity.coords[0]][entity.coords[1]] = None + + def get_surrounding_prey(self, entity: Entity) -> list[Entity]: + """ + Returns all the prey entities around (N, S, E, W) a predator entity. + + Subtly different to the try_to_move_to_unoccupied square. + + >>> wt = WaTor(WIDTH, HEIGHT) + >>> wt.set_planet([ + ... [None, Entity(True, (0, 1)), None], + ... [None, Entity(False, (1, 1)), None], + ... [None, Entity(True, (2, 1)), None]]) + >>> wt.get_surrounding_prey( + ... Entity(False, (1, 1))) # doctest: +NORMALIZE_WHITESPACE + [Entity(prey=True, coords=(0, 1), remaining_reproduction_time=5), + Entity(prey=True, coords=(2, 1), remaining_reproduction_time=5)] + >>> wt.set_planet([[Entity(False, (0, 0))]]) + >>> wt.get_surrounding_prey(Entity(False, (0, 0))) + [] + >>> wt.set_planet([ + ... [Entity(True, (0, 0)), Entity(False, (1, 0)), Entity(False, (2, 0))], + ... [None, Entity(False, (1, 1)), Entity(True, (2, 1))], + ... [None, None, None]]) + >>> wt.get_surrounding_prey(Entity(False, (1, 0))) + [Entity(prey=True, coords=(0, 0), remaining_reproduction_time=5)] + """ + row, col = entity.coords + adjacent: list[tuple[int, int]] = [ + (row - 1, col), # North + (row + 1, col), # South + (row, col - 1), # West + (row, col + 1), # East + ] + + return [ + ent + for r, c in adjacent + if 0 <= r < self.height + and 0 <= c < self.width + and (ent := self.planet[r][c]) is not None + and ent.prey + ] + + def move_and_reproduce( + self, entity: Entity, direction_orders: list[Literal["N", "E", "S", "W"]] + ) -> None: + """ + Attempts to move to an unoccupied neighbouring square + in either of the four directions (North, South, East, West). + If the move was successful and the remaining_reproduction time is + equal to 0, then a new prey or predator can also be created + in the previous square. + + :param direction_orders: Ordered list (like priority queue) depicting + order to attempt to move. Removes any systematic + approach of checking neighbouring squares. + + >>> planet = [ + ... [None, None, None], + ... [None, Entity(True, coords=(1, 1)), None], + ... [None, None, None] + ... ] + >>> wt = WaTor(WIDTH, HEIGHT) + >>> wt.set_planet(planet) + >>> wt.move_and_reproduce(Entity(True, coords=(1, 1)), direction_orders=["N"]) + >>> wt.planet # doctest: +NORMALIZE_WHITESPACE + [[None, Entity(prey=True, coords=(0, 1), remaining_reproduction_time=4), None], + [None, None, None], + [None, None, None]] + >>> wt.planet[0][0] = Entity(True, coords=(0, 0)) + >>> wt.move_and_reproduce(Entity(True, coords=(0, 1)), + ... direction_orders=["N", "W", "E", "S"]) + >>> wt.planet # doctest: +NORMALIZE_WHITESPACE + [[Entity(prey=True, coords=(0, 0), remaining_reproduction_time=5), None, + Entity(prey=True, coords=(0, 2), remaining_reproduction_time=4)], + [None, None, None], + [None, None, None]] + >>> wt.planet[0][1] = wt.planet[0][2] + >>> wt.planet[0][2] = None + >>> wt.move_and_reproduce(Entity(True, coords=(0, 1)), + ... direction_orders=["N", "W", "S", "E"]) + >>> wt.planet # doctest: +NORMALIZE_WHITESPACE + [[Entity(prey=True, coords=(0, 0), remaining_reproduction_time=5), None, None], + [None, Entity(prey=True, coords=(1, 1), remaining_reproduction_time=4), None], + [None, None, None]] + + >>> wt = WaTor(WIDTH, HEIGHT) + >>> reproducable_entity = Entity(False, coords=(0, 1)) + >>> reproducable_entity.remaining_reproduction_time = 0 + >>> wt.planet = [[None, reproducable_entity]] + >>> wt.move_and_reproduce(reproducable_entity, + ... direction_orders=["N", "W", "S", "E"]) + >>> wt.planet # doctest: +NORMALIZE_WHITESPACE + [[Entity(prey=False, coords=(0, 0), + remaining_reproduction_time=20, energy_value=15), + Entity(prey=False, coords=(0, 1), remaining_reproduction_time=20, + energy_value=15)]] + """ + row, col = coords = entity.coords + + adjacent_squares: dict[Literal["N", "E", "S", "W"], tuple[int, int]] = { + "N": (row - 1, col), # North + "S": (row + 1, col), # South + "W": (row, col - 1), # West + "E": (row, col + 1), # East + } + # Weight adjacent locations + adjacent: list[tuple[int, int]] = [] + for order in direction_orders: + adjacent.append(adjacent_squares[order]) + + for r, c in adjacent: + if ( + 0 <= r < self.height + and 0 <= c < self.width + and self.planet[r][c] is None + ): + # Move entity to empty adjacent square + self.planet[r][c] = entity + self.planet[row][col] = None + entity.coords = (r, c) + break + + # (2.) See if it possible to reproduce in previous square + if coords != entity.coords and entity.remaining_reproduction_time <= 0: + # Check if the entities on the planet is less than the max limit + if len(self.get_entities()) < MAX_ENTITIES: + # Reproduce in previous square + self.planet[row][col] = Entity(prey=entity.prey, coords=coords) + entity.reset_reproduction_time() + else: + entity.remaining_reproduction_time -= 1 + + def perform_prey_actions( + self, entity: Entity, direction_orders: list[Literal["N", "E", "S", "W"]] + ) -> None: + """ + Performs the actions for a prey entity + + For prey the rules are: + 1. At each chronon, a prey moves randomly to one of the adjacent unoccupied + squares. If there are no free squares, no movement takes place. + 2. Once a prey has survived a certain number of chronons it may reproduce. + This is done as it moves to a neighbouring square, + leaving behind a new prey in its old position. + Its reproduction time is also reset to zero. + + >>> wt = WaTor(WIDTH, HEIGHT) + >>> reproducable_entity = Entity(True, coords=(0, 1)) + >>> reproducable_entity.remaining_reproduction_time = 0 + >>> wt.planet = [[None, reproducable_entity]] + >>> wt.perform_prey_actions(reproducable_entity, + ... direction_orders=["N", "W", "S", "E"]) + >>> wt.planet # doctest: +NORMALIZE_WHITESPACE + [[Entity(prey=True, coords=(0, 0), remaining_reproduction_time=5), + Entity(prey=True, coords=(0, 1), remaining_reproduction_time=5)]] + """ + self.move_and_reproduce(entity, direction_orders) + + def perform_predator_actions( + self, + entity: Entity, + occupied_by_prey_coords: tuple[int, int] | None, + direction_orders: list[Literal["N", "E", "S", "W"]], + ) -> None: + """ + Performs the actions for a predator entity + + :param occupied_by_prey_coords: Move to this location if there is prey there + + For predators the rules are: + 1. At each chronon, a predator moves randomly to an adjacent square occupied + by a prey. If there is none, the predator moves to a random adjacent + unoccupied square. If there are no free squares, no movement takes place. + 2. At each chronon, each predator is deprived of a unit of energy. + 3. Upon reaching zero energy, a predator dies. + 4. If a predator moves to a square occupied by a prey, + it eats the prey and earns a certain amount of energy. + 5. Once a predator has survived a certain number of chronons + it may reproduce in exactly the same way as the prey. + + >>> wt = WaTor(WIDTH, HEIGHT) + >>> wt.set_planet([[Entity(True, coords=(0, 0)), Entity(False, coords=(0, 1))]]) + >>> wt.perform_predator_actions(Entity(False, coords=(0, 1)), (0, 0), []) + >>> wt.planet # doctest: +NORMALIZE_WHITESPACE + [[Entity(prey=False, coords=(0, 0), + remaining_reproduction_time=20, energy_value=19), None]] + """ + assert entity.energy_value is not None # [type checking] + + # (3.) If the entity has 0 energy, it will die + if entity.energy_value == 0: + self.planet[entity.coords[0]][entity.coords[1]] = None + return + + # (1.) Move to entity if possible + if occupied_by_prey_coords is not None: + # Kill the prey + prey = self.planet[occupied_by_prey_coords[0]][occupied_by_prey_coords[1]] + assert prey is not None + prey.alive = False + + # Move onto prey + self.planet[occupied_by_prey_coords[0]][occupied_by_prey_coords[1]] = entity + self.planet[entity.coords[0]][entity.coords[1]] = None + + entity.coords = occupied_by_prey_coords + # (4.) Eats the prey and earns energy + entity.energy_value += PREDATOR_FOOD_VALUE + else: + # (5.) If it has survived the certain number of chronons it will also + # reproduce in this function + self.move_and_reproduce(entity, direction_orders) + + # (2.) Each chronon, the predator is deprived of a unit of energy + entity.energy_value -= 1 + + def run(self, *, iteration_count: int) -> None: + """ + Emulate time passing by looping iteration_count times + + >>> wt = WaTor(WIDTH, HEIGHT) + >>> wt.run(iteration_count=PREDATOR_INITIAL_ENERGY_VALUE - 1) + >>> len(list(filter(lambda entity: entity.prey is False, + ... wt.get_entities()))) >= PREDATOR_INITIAL_COUNT + True + """ + for iter_num in range(iteration_count): + # Generate list of all entities in order to randomly + # pop an entity at a time to simulate true randomness + # This removes the systematic approach of iterating + # through each entity width by height + all_entities = self.get_entities() + + for __ in range(len(all_entities)): + entity = all_entities.pop(randint(0, len(all_entities) - 1)) + if entity.alive is False: + continue + + directions: list[Literal["N", "E", "S", "W"]] = ["N", "E", "S", "W"] + shuffle(directions) # Randomly shuffle directions + + if entity.prey: + self.perform_prey_actions(entity, directions) + else: + # Create list of surrounding prey + surrounding_prey = self.get_surrounding_prey(entity) + surrounding_prey_coords = None + + if surrounding_prey: + # Again, randomly shuffle directions + shuffle(surrounding_prey) + surrounding_prey_coords = surrounding_prey[0].coords + + self.perform_predator_actions( + entity, surrounding_prey_coords, directions + ) + + # Balance out the predators and prey + self.balance_predators_and_prey() + + if self.time_passed is not None: + # Call time_passed function for Wa-Tor planet + # visualisation in a terminal or a graph. + self.time_passed(self, iter_num) + + +def visualise(wt: WaTor, iter_number: int, *, colour: bool = True) -> None: + """ + Visually displays the Wa-Tor planet using + an ascii code in terminal to clear and re-print + the Wa-Tor planet at intervals. + + Uses ascii colour codes to colourfully display + the predators and prey. + + (0x60f197) Prey = # + (0xfffff) Predator = x + + >>> wt = WaTor(30, 30) + >>> wt.set_planet([ + ... [Entity(True, coords=(0, 0)), Entity(False, coords=(0, 1)), None], + ... [Entity(False, coords=(1, 0)), None, Entity(False, coords=(1, 2))], + ... [None, Entity(True, coords=(2, 1)), None] + ... ]) + >>> visualise(wt, 0, colour=False) # doctest: +NORMALIZE_WHITESPACE + # x . + x . x + . # . + + Iteration: 0 | Prey count: 2 | Predator count: 3 | + """ + if colour: + __import__("os").system("") + print("\x1b[0;0H\x1b[2J\x1b[?25l") + + reprint = "\x1b[0;0H" if colour else "" + ansi_colour_end = "\x1b[0m " if colour else " " + + planet = wt.planet + output = "" + + # Iterate over every entity in the planet + for row in planet: + for entity in row: + if entity is None: + output += " . " + else: + if colour is True: + output += ( + "\x1b[38;2;96;241;151m" + if entity.prey + else "\x1b[38;2;255;255;15m" + ) + output += f" {'#' if entity.prey else 'x'}{ansi_colour_end}" + + output += "\n" + + entities = wt.get_entities() + prey_count = sum(entity.prey for entity in entities) + + print( + f"{output}\n Iteration: {iter_number} | Prey count: {prey_count} | " + f"Predator count: {len(entities) - prey_count} | {reprint}" + ) + # Block the thread to be able to visualise seeing the algorithm + sleep(0.05) + + +if __name__ == "__main__": + import doctest + + doctest.testmod() + + wt = WaTor(WIDTH, HEIGHT) + wt.time_passed = visualise + wt.run(iteration_count=100_000) diff --git a/ciphers/diffie_hellman.py b/ciphers/diffie_hellman.py index cd40a6b9c..aec7fb3ea 100644 --- a/ciphers/diffie_hellman.py +++ b/ciphers/diffie_hellman.py @@ -10,13 +10,13 @@ primes = { 5: { "prime": int( "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1" - + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD" - + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245" - + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED" - + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D" - + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F" - + "83655D23DCA3AD961C62F356208552BB9ED529077096966D" - + "670C354E4ABC9804F1746C08CA237327FFFFFFFFFFFFFFFF", + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD" + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245" + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED" + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D" + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F" + "83655D23DCA3AD961C62F356208552BB9ED529077096966D" + "670C354E4ABC9804F1746C08CA237327FFFFFFFFFFFFFFFF", base=16, ), "generator": 2, @@ -25,16 +25,16 @@ primes = { 14: { "prime": int( "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1" - + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD" - + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245" - + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED" - + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D" - + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F" - + "83655D23DCA3AD961C62F356208552BB9ED529077096966D" - + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B" - + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9" - + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510" - + "15728E5A8AACAA68FFFFFFFFFFFFFFFF", + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD" + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245" + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED" + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D" + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F" + "83655D23DCA3AD961C62F356208552BB9ED529077096966D" + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B" + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9" + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510" + "15728E5A8AACAA68FFFFFFFFFFFFFFFF", base=16, ), "generator": 2, @@ -43,21 +43,21 @@ primes = { 15: { "prime": int( "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1" - + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD" - + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245" - + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED" - + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D" - + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F" - + "83655D23DCA3AD961C62F356208552BB9ED529077096966D" - + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B" - + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9" - + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510" - + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64" - + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7" - + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B" - + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C" - + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31" - + "43DB5BFCE0FD108E4B82D120A93AD2CAFFFFFFFFFFFFFFFF", + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD" + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245" + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED" + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D" + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F" + "83655D23DCA3AD961C62F356208552BB9ED529077096966D" + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B" + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9" + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510" + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64" + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7" + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B" + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C" + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31" + "43DB5BFCE0FD108E4B82D120A93AD2CAFFFFFFFFFFFFFFFF", base=16, ), "generator": 2, @@ -66,27 +66,27 @@ primes = { 16: { "prime": int( "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1" - + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD" - + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245" - + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED" - + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D" - + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F" - + "83655D23DCA3AD961C62F356208552BB9ED529077096966D" - + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B" - + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9" - + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510" - + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64" - + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7" - + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B" - + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C" - + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31" - + "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7" - + "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA" - + "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6" - + "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED" - + "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9" - + "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934063199" - + "FFFFFFFFFFFFFFFF", + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD" + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245" + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED" + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D" + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F" + "83655D23DCA3AD961C62F356208552BB9ED529077096966D" + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B" + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9" + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510" + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64" + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7" + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B" + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C" + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31" + "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7" + "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA" + "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6" + "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED" + "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9" + "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934063199" + "FFFFFFFFFFFFFFFF", base=16, ), "generator": 2, @@ -95,33 +95,33 @@ primes = { 17: { "prime": int( "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD129024E08" - + "8A67CC74020BBEA63B139B22514A08798E3404DDEF9519B3CD3A431B" - + "302B0A6DF25F14374FE1356D6D51C245E485B576625E7EC6F44C42E9" - + "A637ED6B0BFF5CB6F406B7EDEE386BFB5A899FA5AE9F24117C4B1FE6" - + "49286651ECE45B3DC2007CB8A163BF0598DA48361C55D39A69163FA8" - + "FD24CF5F83655D23DCA3AD961C62F356208552BB9ED529077096966D" - + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3BE39E772C" - + "180E86039B2783A2EC07A28FB5C55DF06F4C52C9DE2BCBF695581718" - + "3995497CEA956AE515D2261898FA051015728E5A8AAAC42DAD33170D" - + "04507A33A85521ABDF1CBA64ECFB850458DBEF0A8AEA71575D060C7D" - + "B3970F85A6E1E4C7ABF5AE8CDB0933D71E8C94E04A25619DCEE3D226" - + "1AD2EE6BF12FFA06D98A0864D87602733EC86A64521F2B18177B200C" - + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB3143DB5BFC" - + "E0FD108E4B82D120A92108011A723C12A787E6D788719A10BDBA5B26" - + "99C327186AF4E23C1A946834B6150BDA2583E9CA2AD44CE8DBBBC2DB" - + "04DE8EF92E8EFC141FBECAA6287C59474E6BC05D99B2964FA090C3A2" - + "233BA186515BE7ED1F612970CEE2D7AFB81BDD762170481CD0069127" - + "D5B05AA993B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492" - + "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BDF8FF9406" - + "AD9E530EE5DB382F413001AEB06A53ED9027D831179727B0865A8918" - + "DA3EDBEBCF9B14ED44CE6CBACED4BB1BDB7F1447E6CC254B33205151" - + "2BD7AF426FB8F401378CD2BF5983CA01C64B92ECF032EA15D1721D03" - + "F482D7CE6E74FEF6D55E702F46980C82B5A84031900B1C9E59E7C97F" - + "BEC7E8F323A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA" - + "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE32806A1D58B" - + "B7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55CDA56C9EC2EF29632" - + "387FE8D76E3C0468043E8F663F4860EE12BF2D5B0B7474D6E694F91E" - + "6DCC4024FFFFFFFFFFFFFFFF", + "8A67CC74020BBEA63B139B22514A08798E3404DDEF9519B3CD3A431B" + "302B0A6DF25F14374FE1356D6D51C245E485B576625E7EC6F44C42E9" + "A637ED6B0BFF5CB6F406B7EDEE386BFB5A899FA5AE9F24117C4B1FE6" + "49286651ECE45B3DC2007CB8A163BF0598DA48361C55D39A69163FA8" + "FD24CF5F83655D23DCA3AD961C62F356208552BB9ED529077096966D" + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3BE39E772C" + "180E86039B2783A2EC07A28FB5C55DF06F4C52C9DE2BCBF695581718" + "3995497CEA956AE515D2261898FA051015728E5A8AAAC42DAD33170D" + "04507A33A85521ABDF1CBA64ECFB850458DBEF0A8AEA71575D060C7D" + "B3970F85A6E1E4C7ABF5AE8CDB0933D71E8C94E04A25619DCEE3D226" + "1AD2EE6BF12FFA06D98A0864D87602733EC86A64521F2B18177B200C" + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB3143DB5BFC" + "E0FD108E4B82D120A92108011A723C12A787E6D788719A10BDBA5B26" + "99C327186AF4E23C1A946834B6150BDA2583E9CA2AD44CE8DBBBC2DB" + "04DE8EF92E8EFC141FBECAA6287C59474E6BC05D99B2964FA090C3A2" + "233BA186515BE7ED1F612970CEE2D7AFB81BDD762170481CD0069127" + "D5B05AA993B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492" + "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BDF8FF9406" + "AD9E530EE5DB382F413001AEB06A53ED9027D831179727B0865A8918" + "DA3EDBEBCF9B14ED44CE6CBACED4BB1BDB7F1447E6CC254B33205151" + "2BD7AF426FB8F401378CD2BF5983CA01C64B92ECF032EA15D1721D03" + "F482D7CE6E74FEF6D55E702F46980C82B5A84031900B1C9E59E7C97F" + "BEC7E8F323A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA" + "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE32806A1D58B" + "B7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55CDA56C9EC2EF29632" + "387FE8D76E3C0468043E8F663F4860EE12BF2D5B0B7474D6E694F91E" + "6DCC4024FFFFFFFFFFFFFFFF", base=16, ), "generator": 2, @@ -130,48 +130,48 @@ primes = { 18: { "prime": int( "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1" - + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD" - + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245" - + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED" - + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D" - + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F" - + "83655D23DCA3AD961C62F356208552BB9ED529077096966D" - + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B" - + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9" - + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510" - + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64" - + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7" - + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B" - + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C" - + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31" - + "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7" - + "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA" - + "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6" - + "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED" - + "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9" - + "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492" - + "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BD" - + "F8FF9406AD9E530EE5DB382F413001AEB06A53ED9027D831" - + "179727B0865A8918DA3EDBEBCF9B14ED44CE6CBACED4BB1B" - + "DB7F1447E6CC254B332051512BD7AF426FB8F401378CD2BF" - + "5983CA01C64B92ECF032EA15D1721D03F482D7CE6E74FEF6" - + "D55E702F46980C82B5A84031900B1C9E59E7C97FBEC7E8F3" - + "23A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA" - + "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE328" - + "06A1D58BB7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55C" - + "DA56C9EC2EF29632387FE8D76E3C0468043E8F663F4860EE" - + "12BF2D5B0B7474D6E694F91E6DBE115974A3926F12FEE5E4" - + "38777CB6A932DF8CD8BEC4D073B931BA3BC832B68D9DD300" - + "741FA7BF8AFC47ED2576F6936BA424663AAB639C5AE4F568" - + "3423B4742BF1C978238F16CBE39D652DE3FDB8BEFC848AD9" - + "22222E04A4037C0713EB57A81A23F0C73473FC646CEA306B" - + "4BCBC8862F8385DDFA9D4B7FA2C087E879683303ED5BDD3A" - + "062B3CF5B3A278A66D2A13F83F44F82DDF310EE074AB6A36" - + "4597E899A0255DC164F31CC50846851DF9AB48195DED7EA1" - + "B1D510BD7EE74D73FAF36BC31ECFA268359046F4EB879F92" - + "4009438B481C6CD7889A002ED5EE382BC9190DA6FC026E47" - + "9558E4475677E9AA9E3050E2765694DFC81F56E880B96E71" - + "60C980DD98EDD3DFFFFFFFFFFFFFFFFF", + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD" + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245" + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED" + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D" + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F" + "83655D23DCA3AD961C62F356208552BB9ED529077096966D" + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B" + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9" + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510" + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64" + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7" + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B" + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C" + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31" + "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7" + "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA" + "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6" + "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED" + "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9" + "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492" + "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BD" + "F8FF9406AD9E530EE5DB382F413001AEB06A53ED9027D831" + "179727B0865A8918DA3EDBEBCF9B14ED44CE6CBACED4BB1B" + "DB7F1447E6CC254B332051512BD7AF426FB8F401378CD2BF" + "5983CA01C64B92ECF032EA15D1721D03F482D7CE6E74FEF6" + "D55E702F46980C82B5A84031900B1C9E59E7C97FBEC7E8F3" + "23A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA" + "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE328" + "06A1D58BB7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55C" + "DA56C9EC2EF29632387FE8D76E3C0468043E8F663F4860EE" + "12BF2D5B0B7474D6E694F91E6DBE115974A3926F12FEE5E4" + "38777CB6A932DF8CD8BEC4D073B931BA3BC832B68D9DD300" + "741FA7BF8AFC47ED2576F6936BA424663AAB639C5AE4F568" + "3423B4742BF1C978238F16CBE39D652DE3FDB8BEFC848AD9" + "22222E04A4037C0713EB57A81A23F0C73473FC646CEA306B" + "4BCBC8862F8385DDFA9D4B7FA2C087E879683303ED5BDD3A" + "062B3CF5B3A278A66D2A13F83F44F82DDF310EE074AB6A36" + "4597E899A0255DC164F31CC50846851DF9AB48195DED7EA1" + "B1D510BD7EE74D73FAF36BC31ECFA268359046F4EB879F92" + "4009438B481C6CD7889A002ED5EE382BC9190DA6FC026E47" + "9558E4475677E9AA9E3050E2765694DFC81F56E880B96E71" + "60C980DD98EDD3DFFFFFFFFFFFFFFFFF", base=16, ), "generator": 2, diff --git a/compression/burrows_wheeler.py b/compression/burrows_wheeler.py index 0916b8a65..52bb045d9 100644 --- a/compression/burrows_wheeler.py +++ b/compression/burrows_wheeler.py @@ -150,7 +150,7 @@ def reverse_bwt(bwt_string: str, idx_original_string: int) -> str: raise ValueError("The parameter idx_original_string must not be lower than 0.") if idx_original_string >= len(bwt_string): raise ValueError( - "The parameter idx_original_string must be lower than" " len(bwt_string)." + "The parameter idx_original_string must be lower than len(bwt_string)." ) ordered_rotations = [""] * len(bwt_string) diff --git a/conversions/length_conversion.py b/conversions/length_conversion.py index d8f395152..07fa93a19 100644 --- a/conversions/length_conversion.py +++ b/conversions/length_conversion.py @@ -22,9 +22,13 @@ REFERENCES : -> Wikipedia reference: https://en.wikipedia.org/wiki/Millimeter """ -from collections import namedtuple +from typing import NamedTuple + + +class FromTo(NamedTuple): + from_factor: float + to_factor: float -from_to = namedtuple("from_to", "from_ to") TYPE_CONVERSION = { "millimeter": "mm", @@ -40,14 +44,14 @@ TYPE_CONVERSION = { } METRIC_CONVERSION = { - "mm": from_to(0.001, 1000), - "cm": from_to(0.01, 100), - "m": from_to(1, 1), - "km": from_to(1000, 0.001), - "in": from_to(0.0254, 39.3701), - "ft": from_to(0.3048, 3.28084), - "yd": from_to(0.9144, 1.09361), - "mi": from_to(1609.34, 0.000621371), + "mm": FromTo(0.001, 1000), + "cm": FromTo(0.01, 100), + "m": FromTo(1, 1), + "km": FromTo(1000, 0.001), + "in": FromTo(0.0254, 39.3701), + "ft": FromTo(0.3048, 3.28084), + "yd": FromTo(0.9144, 1.09361), + "mi": FromTo(1609.34, 0.000621371), } @@ -115,7 +119,11 @@ def length_conversion(value: float, from_type: str, to_type: str) -> float: f"Conversion abbreviations are: {', '.join(METRIC_CONVERSION)}" ) raise ValueError(msg) - return value * METRIC_CONVERSION[new_from].from_ * METRIC_CONVERSION[new_to].to + return ( + value + * METRIC_CONVERSION[new_from].from_factor + * METRIC_CONVERSION[new_to].to_factor + ) if __name__ == "__main__": diff --git a/conversions/pressure_conversions.py b/conversions/pressure_conversions.py index e0cd18d23..fe78b1382 100644 --- a/conversions/pressure_conversions.py +++ b/conversions/pressure_conversions.py @@ -19,19 +19,23 @@ REFERENCES : -> https://www.unitconverters.net/pressure-converter.html """ -from collections import namedtuple +from typing import NamedTuple + + +class FromTo(NamedTuple): + from_factor: float + to_factor: float -from_to = namedtuple("from_to", "from_ to") PRESSURE_CONVERSION = { - "atm": from_to(1, 1), - "pascal": from_to(0.0000098, 101325), - "bar": from_to(0.986923, 1.01325), - "kilopascal": from_to(0.00986923, 101.325), - "megapascal": from_to(9.86923, 0.101325), - "psi": from_to(0.068046, 14.6959), - "inHg": from_to(0.0334211, 29.9213), - "torr": from_to(0.00131579, 760), + "atm": FromTo(1, 1), + "pascal": FromTo(0.0000098, 101325), + "bar": FromTo(0.986923, 1.01325), + "kilopascal": FromTo(0.00986923, 101.325), + "megapascal": FromTo(9.86923, 0.101325), + "psi": FromTo(0.068046, 14.6959), + "inHg": FromTo(0.0334211, 29.9213), + "torr": FromTo(0.00131579, 760), } @@ -71,7 +75,9 @@ def pressure_conversion(value: float, from_type: str, to_type: str) -> float: + ", ".join(PRESSURE_CONVERSION) ) return ( - value * PRESSURE_CONVERSION[from_type].from_ * PRESSURE_CONVERSION[to_type].to + value + * PRESSURE_CONVERSION[from_type].from_factor + * PRESSURE_CONVERSION[to_type].to_factor ) diff --git a/conversions/volume_conversions.py b/conversions/volume_conversions.py index 44d290091..cb2403805 100644 --- a/conversions/volume_conversions.py +++ b/conversions/volume_conversions.py @@ -18,35 +18,39 @@ REFERENCES : -> Wikipedia reference: https://en.wikipedia.org/wiki/Cup_(unit) """ -from collections import namedtuple +from typing import NamedTuple + + +class FromTo(NamedTuple): + from_factor: float + to_factor: float -from_to = namedtuple("from_to", "from_ to") METRIC_CONVERSION = { - "cubicmeter": from_to(1, 1), - "litre": from_to(0.001, 1000), - "kilolitre": from_to(1, 1), - "gallon": from_to(0.00454, 264.172), - "cubicyard": from_to(0.76455, 1.30795), - "cubicfoot": from_to(0.028, 35.3147), - "cup": from_to(0.000236588, 4226.75), + "cubic meter": FromTo(1, 1), + "litre": FromTo(0.001, 1000), + "kilolitre": FromTo(1, 1), + "gallon": FromTo(0.00454, 264.172), + "cubic yard": FromTo(0.76455, 1.30795), + "cubic foot": FromTo(0.028, 35.3147), + "cup": FromTo(0.000236588, 4226.75), } def volume_conversion(value: float, from_type: str, to_type: str) -> float: """ Conversion between volume units. - >>> volume_conversion(4, "cubicmeter", "litre") + >>> volume_conversion(4, "cubic meter", "litre") 4000 >>> volume_conversion(1, "litre", "gallon") 0.264172 - >>> volume_conversion(1, "kilolitre", "cubicmeter") + >>> volume_conversion(1, "kilolitre", "cubic meter") 1 - >>> volume_conversion(3, "gallon", "cubicyard") + >>> volume_conversion(3, "gallon", "cubic yard") 0.017814279 - >>> volume_conversion(2, "cubicyard", "litre") + >>> volume_conversion(2, "cubic yard", "litre") 1529.1 - >>> volume_conversion(4, "cubicfoot", "cup") + >>> volume_conversion(4, "cubic foot", "cup") 473.396 >>> volume_conversion(1, "cup", "kilolitre") 0.000236588 @@ -54,7 +58,7 @@ def volume_conversion(value: float, from_type: str, to_type: str) -> float: Traceback (most recent call last): ... ValueError: Invalid 'from_type' value: 'wrongUnit' Supported values are: - cubicmeter, litre, kilolitre, gallon, cubicyard, cubicfoot, cup + cubic meter, litre, kilolitre, gallon, cubic yard, cubic foot, cup """ if from_type not in METRIC_CONVERSION: raise ValueError( @@ -66,7 +70,11 @@ def volume_conversion(value: float, from_type: str, to_type: str) -> float: f"Invalid 'to_type' value: {to_type!r}. Supported values are:\n" + ", ".join(METRIC_CONVERSION) ) - return value * METRIC_CONVERSION[from_type].from_ * METRIC_CONVERSION[to_type].to + return ( + value + * METRIC_CONVERSION[from_type].from_factor + * METRIC_CONVERSION[to_type].to_factor + ) if __name__ == "__main__": diff --git a/data_structures/binary_tree/binary_tree_traversals.py b/data_structures/binary_tree/binary_tree_traversals.py index 71a895e76..2afb7604f 100644 --- a/data_structures/binary_tree/binary_tree_traversals.py +++ b/data_structures/binary_tree/binary_tree_traversals.py @@ -58,6 +58,19 @@ def inorder(root: Node | None) -> list[int]: return [*inorder(root.left), root.data, *inorder(root.right)] if root else [] +def reverse_inorder(root: Node | None) -> list[int]: + """ + Reverse in-order traversal visits right subtree, root node, left subtree. + >>> reverse_inorder(make_tree()) + [3, 1, 5, 2, 4] + """ + return ( + [*reverse_inorder(root.right), root.data, *reverse_inorder(root.left)] + if root + else [] + ) + + def height(root: Node | None) -> int: """ Recursive function for calculating the height of the binary tree. @@ -161,15 +174,12 @@ def zigzag(root: Node | None) -> Sequence[Node | None] | list[Any]: def main() -> None: # Main function for testing. - """ - Create binary tree. - """ + # Create binary tree. root = make_tree() - """ - All Traversals of the binary are as follows: - """ + # All Traversals of the binary are as follows: print(f"In-order Traversal: {inorder(root)}") + print(f"Reverse In-order Traversal: {reverse_inorder(root)}") print(f"Pre-order Traversal: {preorder(root)}") print(f"Post-order Traversal: {postorder(root)}", "\n") diff --git a/data_structures/binary_tree/distribute_coins.py b/data_structures/binary_tree/distribute_coins.py index ea02afc2c..5712604cb 100644 --- a/data_structures/binary_tree/distribute_coins.py +++ b/data_structures/binary_tree/distribute_coins.py @@ -39,8 +39,8 @@ Space: O(1) from __future__ import annotations -from collections import namedtuple from dataclasses import dataclass +from typing import NamedTuple @dataclass @@ -50,7 +50,9 @@ class TreeNode: right: TreeNode | None = None -CoinsDistribResult = namedtuple("CoinsDistribResult", "moves excess") +class CoinsDistribResult(NamedTuple): + moves: int + excess: int def distribute_coins(root: TreeNode | None) -> int: @@ -79,7 +81,7 @@ def distribute_coins(root: TreeNode | None) -> int: # Validation def count_nodes(node: TreeNode | None) -> int: """ - >>> count_nodes(None): + >>> count_nodes(None) 0 """ if node is None: @@ -89,7 +91,7 @@ def distribute_coins(root: TreeNode | None) -> int: def count_coins(node: TreeNode | None) -> int: """ - >>> count_coins(None): + >>> count_coins(None) 0 """ if node is None: diff --git a/data_structures/binary_tree/red_black_tree.py b/data_structures/binary_tree/red_black_tree.py index 3ebc8d639..4ebe0e927 100644 --- a/data_structures/binary_tree/red_black_tree.py +++ b/data_structures/binary_tree/red_black_tree.py @@ -152,7 +152,7 @@ class RedBlackTree: self.grandparent.color = 1 self.grandparent._insert_repair() - def remove(self, label: int) -> RedBlackTree: + def remove(self, label: int) -> RedBlackTree: # noqa: PLR0912 """Remove label from this tree.""" if self.label == label: if self.left and self.right: diff --git a/data_structures/binary_tree/segment_tree.py b/data_structures/binary_tree/segment_tree.py index b05803869..5f822407d 100644 --- a/data_structures/binary_tree/segment_tree.py +++ b/data_structures/binary_tree/segment_tree.py @@ -7,7 +7,8 @@ class SegmentTree: self.st = [0] * ( 4 * self.N ) # approximate the overall size of segment tree with array N - self.build(1, 0, self.N - 1) + if self.N: + self.build(1, 0, self.N - 1) def left(self, idx): return idx * 2 diff --git a/data_structures/queue/double_ended_queue.py b/data_structures/queue/double_ended_queue.py index 2472371b4..44dc863b9 100644 --- a/data_structures/queue/double_ended_queue.py +++ b/data_structures/queue/double_ended_queue.py @@ -54,7 +54,7 @@ class Deque: the current node of the iteration. """ - __slots__ = "_cur" + __slots__ = ("_cur",) def __init__(self, cur: Deque._Node | None) -> None: self._cur = cur diff --git a/data_structures/queue/queue_by_list.py b/data_structures/queue/queue_by_list.py new file mode 100644 index 000000000..4b05be9fd --- /dev/null +++ b/data_structures/queue/queue_by_list.py @@ -0,0 +1,141 @@ +"""Queue represented by a Python list""" + +from collections.abc import Iterable +from typing import Generic, TypeVar + +_T = TypeVar("_T") + + +class QueueByList(Generic[_T]): + def __init__(self, iterable: Iterable[_T] | None = None) -> None: + """ + >>> QueueByList() + Queue(()) + >>> QueueByList([10, 20, 30]) + Queue((10, 20, 30)) + >>> QueueByList((i**2 for i in range(1, 4))) + Queue((1, 4, 9)) + """ + self.entries: list[_T] = list(iterable or []) + + def __len__(self) -> int: + """ + >>> len(QueueByList()) + 0 + >>> from string import ascii_lowercase + >>> len(QueueByList(ascii_lowercase)) + 26 + >>> queue = QueueByList() + >>> for i in range(1, 11): + ... queue.put(i) + >>> len(queue) + 10 + >>> for i in range(2): + ... queue.get() + 1 + 2 + >>> len(queue) + 8 + """ + + return len(self.entries) + + def __repr__(self) -> str: + """ + >>> queue = QueueByList() + >>> queue + Queue(()) + >>> str(queue) + 'Queue(())' + >>> queue.put(10) + >>> queue + Queue((10,)) + >>> queue.put(20) + >>> queue.put(30) + >>> queue + Queue((10, 20, 30)) + """ + + return f"Queue({tuple(self.entries)})" + + def put(self, item: _T) -> None: + """Put `item` to the Queue + + >>> queue = QueueByList() + >>> queue.put(10) + >>> queue.put(20) + >>> len(queue) + 2 + >>> queue + Queue((10, 20)) + """ + + self.entries.append(item) + + def get(self) -> _T: + """ + Get `item` from the Queue + + >>> queue = QueueByList((10, 20, 30)) + >>> queue.get() + 10 + >>> queue.put(40) + >>> queue.get() + 20 + >>> queue.get() + 30 + >>> len(queue) + 1 + >>> queue.get() + 40 + >>> queue.get() + Traceback (most recent call last): + ... + IndexError: Queue is empty + """ + + if not self.entries: + raise IndexError("Queue is empty") + return self.entries.pop(0) + + def rotate(self, rotation: int) -> None: + """Rotate the items of the Queue `rotation` times + + >>> queue = QueueByList([10, 20, 30, 40]) + >>> queue + Queue((10, 20, 30, 40)) + >>> queue.rotate(1) + >>> queue + Queue((20, 30, 40, 10)) + >>> queue.rotate(2) + >>> queue + Queue((40, 10, 20, 30)) + """ + + put = self.entries.append + get = self.entries.pop + + for _ in range(rotation): + put(get(0)) + + def get_front(self) -> _T: + """Get the front item from the Queue + + >>> queue = QueueByList((10, 20, 30)) + >>> queue.get_front() + 10 + >>> queue + Queue((10, 20, 30)) + >>> queue.get() + 10 + >>> queue.get_front() + 20 + """ + + return self.entries[0] + + +if __name__ == "__main__": + from doctest import testmod + + testmod() diff --git a/data_structures/queue/queue_on_list.py b/data_structures/queue/queue_on_list.py deleted file mode 100644 index 71fca6b2f..000000000 --- a/data_structures/queue/queue_on_list.py +++ /dev/null @@ -1,52 +0,0 @@ -"""Queue represented by a Python list""" - - -class Queue: - def __init__(self): - self.entries = [] - self.length = 0 - self.front = 0 - - def __str__(self): - printed = "<" + str(self.entries)[1:-1] + ">" - return printed - - """Enqueues {@code item} - @param item - item to enqueue""" - - def put(self, item): - self.entries.append(item) - self.length = self.length + 1 - - """Dequeues {@code item} - @requirement: |self.length| > 0 - @return dequeued - item that was dequeued""" - - def get(self): - self.length = self.length - 1 - dequeued = self.entries[self.front] - # self.front-=1 - # self.entries = self.entries[self.front:] - self.entries = self.entries[1:] - return dequeued - - """Rotates the queue {@code rotation} times - @param rotation - number of times to rotate queue""" - - def rotate(self, rotation): - for _ in range(rotation): - self.put(self.get()) - - """Enqueues {@code item} - @return item at front of self.entries""" - - def get_front(self): - return self.entries[0] - - """Returns the length of this.entries""" - - def size(self): - return self.length diff --git a/data_structures/stacks/infix_to_postfix_conversion.py b/data_structures/stacks/infix_to_postfix_conversion.py index 901744309..e69706193 100644 --- a/data_structures/stacks/infix_to_postfix_conversion.py +++ b/data_structures/stacks/infix_to_postfix_conversion.py @@ -4,9 +4,26 @@ https://en.wikipedia.org/wiki/Reverse_Polish_notation https://en.wikipedia.org/wiki/Shunting-yard_algorithm """ +from typing import Literal + from .balanced_parentheses import balanced_parentheses from .stack import Stack +PRECEDENCES: dict[str, int] = { + "+": 1, + "-": 1, + "*": 2, + "/": 2, + "^": 3, +} +ASSOCIATIVITIES: dict[str, Literal["LR", "RL"]] = { + "+": "LR", + "-": "LR", + "*": "LR", + "/": "LR", + "^": "RL", +} + def precedence(char: str) -> int: """ @@ -14,7 +31,15 @@ def precedence(char: str) -> int: order of operation. https://en.wikipedia.org/wiki/Order_of_operations """ - return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(char, -1) + return PRECEDENCES.get(char, -1) + + +def associativity(char: str) -> Literal["LR", "RL"]: + """ + Return the associativity of the operator `char`. + https://en.wikipedia.org/wiki/Operator_associativity + """ + return ASSOCIATIVITIES[char] def infix_to_postfix(expression_str: str) -> str: @@ -35,6 +60,8 @@ def infix_to_postfix(expression_str: str) -> str: 'a b c * + d e * f + g * +' >>> infix_to_postfix("x^y/(5*z)+2") 'x y ^ 5 z * / 2 +' + >>> infix_to_postfix("2^3^2") + '2 3 2 ^ ^' """ if not balanced_parentheses(expression_str): raise ValueError("Mismatched parentheses") @@ -50,9 +77,26 @@ def infix_to_postfix(expression_str: str) -> str: postfix.append(stack.pop()) stack.pop() else: - while not stack.is_empty() and precedence(char) <= precedence(stack.peek()): + while True: + if stack.is_empty(): + stack.push(char) + break + + char_precedence = precedence(char) + tos_precedence = precedence(stack.peek()) + + if char_precedence > tos_precedence: + stack.push(char) + break + if char_precedence < tos_precedence: + postfix.append(stack.pop()) + continue + # Precedences are equal + if associativity(char) == "RL": + stack.push(char) + break postfix.append(stack.pop()) - stack.push(char) + while not stack.is_empty(): postfix.append(stack.pop()) return " ".join(postfix) diff --git a/data_structures/trie/radix_tree.py b/data_structures/trie/radix_tree.py index 66890346e..fadc50cb4 100644 --- a/data_structures/trie/radix_tree.py +++ b/data_structures/trie/radix_tree.py @@ -54,10 +54,17 @@ class RadixNode: word (str): word to insert >>> RadixNode("myprefix").insert("mystring") + + >>> root = RadixNode() + >>> root.insert_many(['myprefix', 'myprefixA', 'myprefixAA']) + >>> root.print_tree() + - myprefix (leaf) + -- A (leaf) + --- A (leaf) """ # Case 1: If the word is the prefix of the node # Solution: We set the current node as leaf - if self.prefix == word: + if self.prefix == word and not self.is_leaf: self.is_leaf = True # Case 2: The node has no edges that have a prefix to the word @@ -156,7 +163,7 @@ class RadixNode: del self.nodes[word[0]] # We merge the current node with its only child if len(self.nodes) == 1 and not self.is_leaf: - merging_node = list(self.nodes.values())[0] + merging_node = next(iter(self.nodes.values())) self.is_leaf = merging_node.is_leaf self.prefix += merging_node.prefix self.nodes = merging_node.nodes @@ -165,7 +172,7 @@ class RadixNode: incoming_node.is_leaf = False # If there is 1 edge, we merge it with its child else: - merging_node = list(incoming_node.nodes.values())[0] + merging_node = next(iter(incoming_node.nodes.values())) incoming_node.is_leaf = merging_node.is_leaf incoming_node.prefix += merging_node.prefix incoming_node.nodes = merging_node.nodes diff --git a/digital_image_processing/dithering/burkes.py b/digital_image_processing/dithering/burkes.py index 0804104ab..35aedc16d 100644 --- a/digital_image_processing/dithering/burkes.py +++ b/digital_image_processing/dithering/burkes.py @@ -39,9 +39,18 @@ class Burkes: def get_greyscale(cls, blue: int, green: int, red: int) -> float: """ >>> Burkes.get_greyscale(3, 4, 5) - 3.753 + 4.185 + >>> Burkes.get_greyscale(0, 0, 0) + 0.0 + >>> Burkes.get_greyscale(255, 255, 255) + 255.0 """ - return 0.114 * blue + 0.587 * green + 0.2126 * red + """ + Formula from https://en.wikipedia.org/wiki/HSL_and_HSV + cf Lightness section, and Fig 13c. + We use the first of four possible. + """ + return 0.114 * blue + 0.587 * green + 0.299 * red def process(self) -> None: for y in range(self.height): @@ -49,10 +58,10 @@ class Burkes: greyscale = int(self.get_greyscale(*self.input_img[y][x])) if self.threshold > greyscale + self.error_table[y][x]: self.output_img[y][x] = (0, 0, 0) - current_error = greyscale + self.error_table[x][y] + current_error = greyscale + self.error_table[y][x] else: self.output_img[y][x] = (255, 255, 255) - current_error = greyscale + self.error_table[x][y] - 255 + current_error = greyscale + self.error_table[y][x] - 255 """ Burkes error propagation (`*` is current pixel): diff --git a/divide_and_conquer/convex_hull.py b/divide_and_conquer/convex_hull.py index 1ad933417..1d1bf301d 100644 --- a/divide_and_conquer/convex_hull.py +++ b/divide_and_conquer/convex_hull.py @@ -266,7 +266,7 @@ def convex_hull_bf(points: list[Point]) -> list[Point]: points_left_of_ij = points_right_of_ij = False ij_part_of_convex_hull = True for k in range(n): - if k != i and k != j: + if k not in {i, j}: det_k = _det(points[i], points[j], points[k]) if det_k > 0: diff --git a/divide_and_conquer/max_subarray.py b/divide_and_conquer/max_subarray.py new file mode 100644 index 000000000..851ef621a --- /dev/null +++ b/divide_and_conquer/max_subarray.py @@ -0,0 +1,112 @@ +""" +The maximum subarray problem is the task of finding the continuous subarray that has the +maximum sum within a given array of numbers. For example, given the array +[-2, 1, -3, 4, -1, 2, 1, -5, 4], the contiguous subarray with the maximum sum is +[4, -1, 2, 1], which has a sum of 6. + +This divide-and-conquer algorithm finds the maximum subarray in O(n log n) time. +""" +from __future__ import annotations + +import time +from collections.abc import Sequence +from random import randint + +from matplotlib import pyplot as plt + + +def max_subarray( + arr: Sequence[float], low: int, high: int +) -> tuple[int | None, int | None, float]: + """ + Solves the maximum subarray problem using divide and conquer. + :param arr: the given array of numbers + :param low: the start index + :param high: the end index + :return: the start index of the maximum subarray, the end index of the + maximum subarray, and the maximum subarray sum + + >>> nums = [-2, 1, -3, 4, -1, 2, 1, -5, 4] + >>> max_subarray(nums, 0, len(nums) - 1) + (3, 6, 6) + >>> nums = [2, 8, 9] + >>> max_subarray(nums, 0, len(nums) - 1) + (0, 2, 19) + >>> nums = [0, 0] + >>> max_subarray(nums, 0, len(nums) - 1) + (0, 0, 0) + >>> nums = [-1.0, 0.0, 1.0] + >>> max_subarray(nums, 0, len(nums) - 1) + (2, 2, 1.0) + >>> nums = [-2, -3, -1, -4, -6] + >>> max_subarray(nums, 0, len(nums) - 1) + (2, 2, -1) + >>> max_subarray([], 0, 0) + (None, None, 0) + """ + if not arr: + return None, None, 0 + if low == high: + return low, high, arr[low] + + mid = (low + high) // 2 + left_low, left_high, left_sum = max_subarray(arr, low, mid) + right_low, right_high, right_sum = max_subarray(arr, mid + 1, high) + cross_left, cross_right, cross_sum = max_cross_sum(arr, low, mid, high) + if left_sum >= right_sum and left_sum >= cross_sum: + return left_low, left_high, left_sum + elif right_sum >= left_sum and right_sum >= cross_sum: + return right_low, right_high, right_sum + return cross_left, cross_right, cross_sum + + +def max_cross_sum( + arr: Sequence[float], low: int, mid: int, high: int +) -> tuple[int, int, float]: + left_sum, max_left = float("-inf"), -1 + right_sum, max_right = float("-inf"), -1 + + summ: int | float = 0 + for i in range(mid, low - 1, -1): + summ += arr[i] + if summ > left_sum: + left_sum = summ + max_left = i + + summ = 0 + for i in range(mid + 1, high + 1): + summ += arr[i] + if summ > right_sum: + right_sum = summ + max_right = i + + return max_left, max_right, (left_sum + right_sum) + + +def time_max_subarray(input_size: int) -> float: + arr = [randint(1, input_size) for _ in range(input_size)] + start = time.time() + max_subarray(arr, 0, input_size - 1) + end = time.time() + return end - start + + +def plot_runtimes() -> None: + input_sizes = [10, 100, 1000, 10000, 50000, 100000, 200000, 300000, 400000, 500000] + runtimes = [time_max_subarray(input_size) for input_size in input_sizes] + print("No of Inputs\t\tTime Taken") + for input_size, runtime in zip(input_sizes, runtimes): + print(input_size, "\t\t", runtime) + plt.plot(input_sizes, runtimes) + plt.xlabel("Number of Inputs") + plt.ylabel("Time taken in seconds") + plt.show() + + +if __name__ == "__main__": + """ + A random simulation of this algorithm. + """ + from doctest import testmod + + testmod() diff --git a/divide_and_conquer/max_subarray_sum.py b/divide_and_conquer/max_subarray_sum.py deleted file mode 100644 index f23e81719..000000000 --- a/divide_and_conquer/max_subarray_sum.py +++ /dev/null @@ -1,78 +0,0 @@ -""" -Given a array of length n, max_subarray_sum() finds -the maximum of sum of contiguous sub-array using divide and conquer method. - -Time complexity : O(n log n) - -Ref : INTRODUCTION TO ALGORITHMS THIRD EDITION -(section : 4, sub-section : 4.1, page : 70) - -""" - - -def max_sum_from_start(array): - """This function finds the maximum contiguous sum of array from 0 index - - Parameters : - array (list[int]) : given array - - Returns : - max_sum (int) : maximum contiguous sum of array from 0 index - - """ - array_sum = 0 - max_sum = float("-inf") - for num in array: - array_sum += num - if array_sum > max_sum: - max_sum = array_sum - return max_sum - - -def max_cross_array_sum(array, left, mid, right): - """This function finds the maximum contiguous sum of left and right arrays - - Parameters : - array, left, mid, right (list[int], int, int, int) - - Returns : - (int) : maximum of sum of contiguous sum of left and right arrays - - """ - - max_sum_of_left = max_sum_from_start(array[left : mid + 1][::-1]) - max_sum_of_right = max_sum_from_start(array[mid + 1 : right + 1]) - return max_sum_of_left + max_sum_of_right - - -def max_subarray_sum(array, left, right): - """Maximum contiguous sub-array sum, using divide and conquer method - - Parameters : - array, left, right (list[int], int, int) : - given array, current left index and current right index - - Returns : - int : maximum of sum of contiguous sub-array - - """ - - # base case: array has only one element - if left == right: - return array[right] - - # Recursion - mid = (left + right) // 2 - left_half_sum = max_subarray_sum(array, left, mid) - right_half_sum = max_subarray_sum(array, mid + 1, right) - cross_sum = max_cross_array_sum(array, left, mid, right) - return max(left_half_sum, right_half_sum, cross_sum) - - -if __name__ == "__main__": - array = [-2, -5, 6, -2, -3, 1, 5, -6] - array_length = len(array) - print( - "Maximum sum of contiguous subarray:", - max_subarray_sum(array, 0, array_length - 1), - ) diff --git a/dynamic_programming/max_sub_array.py b/dynamic_programming/max_sub_array.py deleted file mode 100644 index 07717fba4..000000000 --- a/dynamic_programming/max_sub_array.py +++ /dev/null @@ -1,93 +0,0 @@ -""" -author : Mayank Kumar Jha (mk9440) -""" -from __future__ import annotations - - -def find_max_sub_array(a, low, high): - if low == high: - return low, high, a[low] - else: - mid = (low + high) // 2 - left_low, left_high, left_sum = find_max_sub_array(a, low, mid) - right_low, right_high, right_sum = find_max_sub_array(a, mid + 1, high) - cross_left, cross_right, cross_sum = find_max_cross_sum(a, low, mid, high) - if left_sum >= right_sum and left_sum >= cross_sum: - return left_low, left_high, left_sum - elif right_sum >= left_sum and right_sum >= cross_sum: - return right_low, right_high, right_sum - else: - return cross_left, cross_right, cross_sum - - -def find_max_cross_sum(a, low, mid, high): - left_sum, max_left = -999999999, -1 - right_sum, max_right = -999999999, -1 - summ = 0 - for i in range(mid, low - 1, -1): - summ += a[i] - if summ > left_sum: - left_sum = summ - max_left = i - summ = 0 - for i in range(mid + 1, high + 1): - summ += a[i] - if summ > right_sum: - right_sum = summ - max_right = i - return max_left, max_right, (left_sum + right_sum) - - -def max_sub_array(nums: list[int]) -> int: - """ - Finds the contiguous subarray which has the largest sum and return its sum. - - >>> max_sub_array([-2, 1, -3, 4, -1, 2, 1, -5, 4]) - 6 - - An empty (sub)array has sum 0. - >>> max_sub_array([]) - 0 - - If all elements are negative, the largest subarray would be the empty array, - having the sum 0. - >>> max_sub_array([-1, -2, -3]) - 0 - >>> max_sub_array([5, -2, -3]) - 5 - >>> max_sub_array([31, -41, 59, 26, -53, 58, 97, -93, -23, 84]) - 187 - """ - best = 0 - current = 0 - for i in nums: - current += i - current = max(current, 0) - best = max(best, current) - return best - - -if __name__ == "__main__": - """ - A random simulation of this algorithm. - """ - import time - from random import randint - - from matplotlib import pyplot as plt - - inputs = [10, 100, 1000, 10000, 50000, 100000, 200000, 300000, 400000, 500000] - tim = [] - for i in inputs: - li = [randint(1, i) for j in range(i)] - strt = time.time() - (find_max_sub_array(li, 0, len(li) - 1)) - end = time.time() - tim.append(end - strt) - print("No of Inputs Time Taken") - for i in range(len(inputs)): - print(inputs[i], "\t\t", tim[i]) - plt.plot(inputs, tim) - plt.xlabel("Number of Inputs") - plt.ylabel("Time taken in seconds ") - plt.show() diff --git a/dynamic_programming/max_subarray_sum.py b/dynamic_programming/max_subarray_sum.py new file mode 100644 index 000000000..c76943472 --- /dev/null +++ b/dynamic_programming/max_subarray_sum.py @@ -0,0 +1,60 @@ +""" +The maximum subarray sum problem is the task of finding the maximum sum that can be +obtained from a contiguous subarray within a given array of numbers. For example, given +the array [-2, 1, -3, 4, -1, 2, 1, -5, 4], the contiguous subarray with the maximum sum +is [4, -1, 2, 1], so the maximum subarray sum is 6. + +Kadane's algorithm is a simple dynamic programming algorithm that solves the maximum +subarray sum problem in O(n) time and O(1) space. + +Reference: https://en.wikipedia.org/wiki/Maximum_subarray_problem +""" +from collections.abc import Sequence + + +def max_subarray_sum( + arr: Sequence[float], allow_empty_subarrays: bool = False +) -> float: + """ + Solves the maximum subarray sum problem using Kadane's algorithm. + :param arr: the given array of numbers + :param allow_empty_subarrays: if True, then the algorithm considers empty subarrays + + >>> max_subarray_sum([2, 8, 9]) + 19 + >>> max_subarray_sum([0, 0]) + 0 + >>> max_subarray_sum([-1.0, 0.0, 1.0]) + 1.0 + >>> max_subarray_sum([1, 2, 3, 4, -2]) + 10 + >>> max_subarray_sum([-2, 1, -3, 4, -1, 2, 1, -5, 4]) + 6 + >>> max_subarray_sum([2, 3, -9, 8, -2]) + 8 + >>> max_subarray_sum([-2, -3, -1, -4, -6]) + -1 + >>> max_subarray_sum([-2, -3, -1, -4, -6], allow_empty_subarrays=True) + 0 + >>> max_subarray_sum([]) + 0 + """ + if not arr: + return 0 + + max_sum = 0 if allow_empty_subarrays else float("-inf") + curr_sum = 0.0 + for num in arr: + curr_sum = max(0 if allow_empty_subarrays else num, curr_sum + num) + max_sum = max(max_sum, curr_sum) + + return max_sum + + +if __name__ == "__main__": + from doctest import testmod + + testmod() + + nums = [-2, 1, -3, 4, -1, 2, 1, -5, 4] + print(f"{max_subarray_sum(nums) = }") diff --git a/dynamic_programming/max_sum_contiguous_subsequence.py b/dynamic_programming/max_sum_contiguous_subsequence.py deleted file mode 100644 index bac592370..000000000 --- a/dynamic_programming/max_sum_contiguous_subsequence.py +++ /dev/null @@ -1,20 +0,0 @@ -def max_subarray_sum(nums: list) -> int: - """ - >>> max_subarray_sum([6 , 9, -1, 3, -7, -5, 10]) - 17 - """ - if not nums: - return 0 - n = len(nums) - - res, s, s_pre = nums[0], nums[0], nums[0] - for i in range(1, n): - s = max(nums[i], s_pre + nums[i]) - s_pre = s - res = max(res, s) - return res - - -if __name__ == "__main__": - nums = [6, 9, -1, 3, -7, -5, 10] - print(max_subarray_sum(nums)) diff --git a/dynamic_programming/regex_match.py b/dynamic_programming/regex_match.py new file mode 100644 index 000000000..200a88283 --- /dev/null +++ b/dynamic_programming/regex_match.py @@ -0,0 +1,97 @@ +""" +Regex matching check if a text matches pattern or not. +Pattern: + '.' Matches any single character. + '*' Matches zero or more of the preceding element. +More info: + https://medium.com/trick-the-interviwer/regular-expression-matching-9972eb74c03 +""" + + +def recursive_match(text: str, pattern: str) -> bool: + """ + Recursive matching algorithm. + + Time complexity: O(2 ^ (|text| + |pattern|)) + Space complexity: Recursion depth is O(|text| + |pattern|). + + :param text: Text to match. + :param pattern: Pattern to match. + :return: True if text matches pattern, False otherwise. + + >>> recursive_match('abc', 'a.c') + True + >>> recursive_match('abc', 'af*.c') + True + >>> recursive_match('abc', 'a.c*') + True + >>> recursive_match('abc', 'a.c*d') + False + >>> recursive_match('aa', '.*') + True + """ + if not pattern: + return not text + + if not text: + return pattern[-1] == "*" and recursive_match(text, pattern[:-2]) + + if text[-1] == pattern[-1] or pattern[-1] == ".": + return recursive_match(text[:-1], pattern[:-1]) + + if pattern[-1] == "*": + return recursive_match(text[:-1], pattern) or recursive_match( + text, pattern[:-2] + ) + + return False + + +def dp_match(text: str, pattern: str) -> bool: + """ + Dynamic programming matching algorithm. + + Time complexity: O(|text| * |pattern|) + Space complexity: O(|text| * |pattern|) + + :param text: Text to match. + :param pattern: Pattern to match. + :return: True if text matches pattern, False otherwise. + + >>> dp_match('abc', 'a.c') + True + >>> dp_match('abc', 'af*.c') + True + >>> dp_match('abc', 'a.c*') + True + >>> dp_match('abc', 'a.c*d') + False + >>> dp_match('aa', '.*') + True + """ + m = len(text) + n = len(pattern) + dp = [[False for _ in range(n + 1)] for _ in range(m + 1)] + dp[0][0] = True + + for j in range(1, n + 1): + dp[0][j] = pattern[j - 1] == "*" and dp[0][j - 2] + + for i in range(1, m + 1): + for j in range(1, n + 1): + if pattern[j - 1] in {".", text[i - 1]}: + dp[i][j] = dp[i - 1][j - 1] + elif pattern[j - 1] == "*": + dp[i][j] = dp[i][j - 2] + if pattern[j - 2] in {".", text[i - 1]}: + dp[i][j] |= dp[i - 1][j] + else: + dp[i][j] = False + + return dp[m][n] + + +if __name__ == "__main__": + import doctest + + doctest.testmod() diff --git a/dynamic_programming/tribonacci.py b/dynamic_programming/tribonacci.py new file mode 100644 index 000000000..58e15da91 --- /dev/null +++ b/dynamic_programming/tribonacci.py @@ -0,0 +1,24 @@ +# Tribonacci sequence using Dynamic Programming + + +def tribonacci(num: int) -> list[int]: + """ + Given a number, return first n Tribonacci Numbers. + >>> tribonacci(5) + [0, 0, 1, 1, 2] + >>> tribonacci(8) + [0, 0, 1, 1, 2, 4, 7, 13] + """ + dp = [0] * num + dp[2] = 1 + + for i in range(3, num): + dp[i] = dp[i - 1] + dp[i - 2] + dp[i - 3] + + return dp + + +if __name__ == "__main__": + import doctest + + doctest.testmod() diff --git a/electronics/electric_power.py b/electronics/electric_power.py index e59795601..8b92e320a 100644 --- a/electronics/electric_power.py +++ b/electronics/electric_power.py @@ -1,7 +1,12 @@ # https://en.m.wikipedia.org/wiki/Electric_power from __future__ import annotations -from collections import namedtuple +from typing import NamedTuple + + +class Result(NamedTuple): + name: str + value: float def electric_power(voltage: float, current: float, power: float) -> tuple: @@ -10,11 +15,11 @@ def electric_power(voltage: float, current: float, power: float) -> tuple: fundamental value of electrical system. examples are below: >>> electric_power(voltage=0, current=2, power=5) - result(name='voltage', value=2.5) + Result(name='voltage', value=2.5) >>> electric_power(voltage=2, current=2, power=0) - result(name='power', value=4.0) + Result(name='power', value=4.0) >>> electric_power(voltage=-2, current=3, power=0) - result(name='power', value=6.0) + Result(name='power', value=6.0) >>> electric_power(voltage=2, current=4, power=2) Traceback (most recent call last): ... @@ -28,9 +33,8 @@ def electric_power(voltage: float, current: float, power: float) -> tuple: ... ValueError: Power cannot be negative in any electrical/electronics system >>> electric_power(voltage=2.2, current=2.2, power=0) - result(name='power', value=4.84) + Result(name='power', value=4.84) """ - result = namedtuple("result", "name value") if (voltage, current, power).count(0) != 1: raise ValueError("Only one argument must be 0") elif power < 0: @@ -38,11 +42,11 @@ def electric_power(voltage: float, current: float, power: float) -> tuple: "Power cannot be negative in any electrical/electronics system" ) elif voltage == 0: - return result("voltage", power / current) + return Result("voltage", power / current) elif current == 0: - return result("current", power / voltage) + return Result("current", power / voltage) elif power == 0: - return result("power", float(round(abs(voltage * current), 2))) + return Result("power", float(round(abs(voltage * current), 2))) else: raise ValueError("Exactly one argument must be 0") diff --git a/fractals/sierpinski_triangle.py b/fractals/sierpinski_triangle.py index c28ec00b2..45f7ab84c 100644 --- a/fractals/sierpinski_triangle.py +++ b/fractals/sierpinski_triangle.py @@ -82,3 +82,4 @@ if __name__ == "__main__": vertices = [(-175, -125), (0, 175), (175, -125)] # vertices of triangle triangle(vertices[0], vertices[1], vertices[2], int(sys.argv[1])) + turtle.Screen().exitonclick() diff --git a/graphs/bi_directional_dijkstra.py b/graphs/bi_directional_dijkstra.py index a4489026b..529a235db 100644 --- a/graphs/bi_directional_dijkstra.py +++ b/graphs/bi_directional_dijkstra.py @@ -26,8 +26,8 @@ def pass_and_relaxation( cst_bwd: dict, queue: PriorityQueue, parent: dict, - shortest_distance: float | int, -) -> float | int: + shortest_distance: float, +) -> float: for nxt, d in graph[v]: if nxt in visited_forward: continue diff --git a/graphs/directed_and_undirected_(weighted)_graph.py b/graphs/directed_and_undirected_(weighted)_graph.py index b29485031..8ca645fda 100644 --- a/graphs/directed_and_undirected_(weighted)_graph.py +++ b/graphs/directed_and_undirected_(weighted)_graph.py @@ -39,7 +39,7 @@ class DirectedGraph: stack = [] visited = [] if s == -2: - s = list(self.graph)[0] + s = next(iter(self.graph)) stack.append(s) visited.append(s) ss = s @@ -87,7 +87,7 @@ class DirectedGraph: d = deque() visited = [] if s == -2: - s = list(self.graph)[0] + s = next(iter(self.graph)) d.append(s) visited.append(s) while d: @@ -114,7 +114,7 @@ class DirectedGraph: stack = [] visited = [] if s == -2: - s = list(self.graph)[0] + s = next(iter(self.graph)) stack.append(s) visited.append(s) ss = s @@ -146,7 +146,7 @@ class DirectedGraph: def cycle_nodes(self): stack = [] visited = [] - s = list(self.graph)[0] + s = next(iter(self.graph)) stack.append(s) visited.append(s) parent = -2 @@ -199,7 +199,7 @@ class DirectedGraph: def has_cycle(self): stack = [] visited = [] - s = list(self.graph)[0] + s = next(iter(self.graph)) stack.append(s) visited.append(s) parent = -2 @@ -305,7 +305,7 @@ class Graph: stack = [] visited = [] if s == -2: - s = list(self.graph)[0] + s = next(iter(self.graph)) stack.append(s) visited.append(s) ss = s @@ -353,7 +353,7 @@ class Graph: d = deque() visited = [] if s == -2: - s = list(self.graph)[0] + s = next(iter(self.graph)) d.append(s) visited.append(s) while d: @@ -371,7 +371,7 @@ class Graph: def cycle_nodes(self): stack = [] visited = [] - s = list(self.graph)[0] + s = next(iter(self.graph)) stack.append(s) visited.append(s) parent = -2 @@ -424,7 +424,7 @@ class Graph: def has_cycle(self): stack = [] visited = [] - s = list(self.graph)[0] + s = next(iter(self.graph)) stack.append(s) visited.append(s) parent = -2 diff --git a/graphs/edmonds_karp_multiple_source_and_sink.py b/graphs/edmonds_karp_multiple_source_and_sink.py index d06108041..5c774f4b8 100644 --- a/graphs/edmonds_karp_multiple_source_and_sink.py +++ b/graphs/edmonds_karp_multiple_source_and_sink.py @@ -113,7 +113,7 @@ class PushRelabelExecutor(MaximumFlowAlgorithmExecutor): vertices_list = [ i for i in range(self.verticies_count) - if i != self.source_index and i != self.sink_index + if i not in {self.source_index, self.sink_index} ] # move through list diff --git a/graphs/eulerian_path_and_circuit_for_undirected_graph.py b/graphs/eulerian_path_and_circuit_for_undirected_graph.py index 6c43c5d3e..6b4ea8e21 100644 --- a/graphs/eulerian_path_and_circuit_for_undirected_graph.py +++ b/graphs/eulerian_path_and_circuit_for_undirected_graph.py @@ -20,7 +20,7 @@ def check_circuit_or_path(graph, max_node): odd_degree_nodes = 0 odd_node = -1 for i in range(max_node): - if i not in graph.keys(): + if i not in graph: continue if len(graph[i]) % 2 == 1: odd_degree_nodes += 1 diff --git a/linear_algebra/src/polynom_for_points.py b/linear_algebra/src/polynom_for_points.py index f5e3db0cb..a9a9a8117 100644 --- a/linear_algebra/src/polynom_for_points.py +++ b/linear_algebra/src/polynom_for_points.py @@ -43,62 +43,43 @@ def points_to_polynomial(coordinates: list[list[int]]) -> str: x = len(coordinates) - count_of_line = 0 - matrix: list[list[float]] = [] # put the x and x to the power values in a matrix - while count_of_line < x: - count_in_line = 0 - a = coordinates[count_of_line][0] - count_line: list[float] = [] - while count_in_line < x: - count_line.append(a ** (x - (count_in_line + 1))) - count_in_line += 1 - matrix.append(count_line) - count_of_line += 1 + matrix: list[list[float]] = [ + [ + coordinates[count_of_line][0] ** (x - (count_in_line + 1)) + for count_in_line in range(x) + ] + for count_of_line in range(x) + ] - count_of_line = 0 # put the y values into a vector - vector: list[float] = [] - while count_of_line < x: - vector.append(coordinates[count_of_line][1]) - count_of_line += 1 + vector: list[float] = [coordinates[count_of_line][1] for count_of_line in range(x)] - count = 0 - - while count < x: - zahlen = 0 - while zahlen < x: - if count == zahlen: - zahlen += 1 - if zahlen == x: - break - bruch = matrix[zahlen][count] / matrix[count][count] + for count in range(x): + for number in range(x): + if count == number: + continue + fraction = matrix[number][count] / matrix[count][count] for counting_columns, item in enumerate(matrix[count]): # manipulating all the values in the matrix - matrix[zahlen][counting_columns] -= item * bruch + matrix[number][counting_columns] -= item * fraction # manipulating the values in the vector - vector[zahlen] -= vector[count] * bruch - zahlen += 1 - count += 1 + vector[number] -= vector[count] * fraction - count = 0 # make solutions - solution: list[str] = [] - while count < x: - solution.append(str(vector[count] / matrix[count][count])) - count += 1 + solution: list[str] = [ + str(vector[count] / matrix[count][count]) for count in range(x) + ] - count = 0 solved = "f(x)=" - while count < x: + for count in range(x): remove_e: list[str] = solution[count].split("E") if len(remove_e) > 1: solution[count] = f"{remove_e[0]}*10^{remove_e[1]}" solved += f"x^{x - (count + 1)}*{solution[count]}" if count + 1 != x: solved += "+" - count += 1 return solved diff --git a/linear_programming/simplex.py b/linear_programming/simplex.py index a2e354651..314bcd327 100644 --- a/linear_programming/simplex.py +++ b/linear_programming/simplex.py @@ -4,7 +4,7 @@ tabular form with - `>=`, `<=`, and `=` constraints and - each variable `x1, x2, ...>= 0`. -See https://gist.github.com/imengus/f9619a568f8da5bc74eaf20169a24d98 for how to +See https://gist.github.com/imengus/f9619a568f7da5bc74eaf20169a24d98 for how to convert linear programs to simplex tableaus, and the steps taken in the simplex algorithm. @@ -29,33 +29,44 @@ class Tableau: Traceback (most recent call last): ... ValueError: RHS must be > 0 - """ - def __init__(self, tableau: np.ndarray, n_vars: int, n_art_vars: int) -> None: + >>> Tableau(np.array([[-1,-1,0,0,1],[1,3,1,0,4],[3,1,0,1,4.]]), -2, 2) + Traceback (most recent call last): + ... + ValueError: number of (artificial) variables must be a natural number + """ + # Max iteration number to prevent cycling + maxiter = 100 + def __init__(self, tableau: np.ndarray, n_vars: int, n_artificial_vars: int) -> None: if tableau.dtype != 'float64': raise TypeError('Tableau must have type float64') # Check if RHS is negative - if np.any(tableau[:, -1], where=tableau[:, -1] < 0): + if not (tableau[:, -1] >= 0).all(): raise ValueError("RHS must be > 0") + if n_vars < 2 or n_artificial_vars < 0: + raise ValueError( + "number of (artificial) variables must be a natural number" + ) + self.tableau = tableau self.n_rows, n_cols = tableau.shape # Number of decision variables x1, x2, x3... - self.n_vars, self.n_art_vars = n_vars, n_art_vars + self.n_vars, self.n_artificial_vars = n_vars, n_artificial_vars # 2 if there are >= or == constraints (nonstandard), 1 otherwise (std) - self.n_stages = (self.n_art_vars > 0) + 1 + self.n_stages = (self.n_artificial_vars > 0) + 1 # Number of slack variables added to make inequalities into equalities - self.n_slack = n_cols - self.n_vars - self.n_art_vars - 1 + self.n_slack = n_cols - self.n_vars - self.n_artificial_vars - 1 # Objectives for each stage self.objectives = ["max"] # In two stage simplex, first minimise then maximise - if self.n_art_vars: + if self.n_artificial_vars: self.objectives.append("min") self.col_titles = self.generate_col_titles() @@ -166,8 +177,8 @@ class Tableau: ... [2, 1, 0, -1, 0, 1, 2] ... ]), 2, 2).change_stage().tolist() ... # doctest: +NORMALIZE_WHITESPACE - [[2.0, 1.0, 0.0, 0.0, 0.0], - [1.0, 2.0, -1.0, 0.0, 2.0], + [[2.0, 1.0, 0.0, 0.0, 0.0], + [1.0, 2.0, -1.0, 0.0, 2.0], [2.0, 1.0, 0.0, -1.0, 2.0]] """ # Objective of original objective row remains @@ -177,7 +188,7 @@ class Tableau: return self.tableau # Slice containing ids for artificial columns - s = slice(-self.n_art_vars - 1, -1) + s = slice(-self.n_artificial_vars - 1, -1) # Delete the artificial variable columns self.tableau = np.delete(self.tableau, s, axis=1) @@ -187,7 +198,7 @@ class Tableau: self.n_stages = 1 self.n_rows -= 1 - self.n_art_vars = 0 + self.n_artificial_vars = 0 self.stop_iter = False return self.tableau @@ -271,7 +282,7 @@ class Tableau: {'P': 132.0, 'x1': 12.000... 'x2': 5.999...} """ # Stop simplex algorithm from cycling. - for _ in range(100): + for _ in range(Tableau.maxiter): # Completion of each stage removes an objective. If both stages # are complete, then no objectives are left if not self.objectives: @@ -302,16 +313,16 @@ class Tableau: output_dict = {"P": abs(self.tableau[0, -1])} for i in range(self.n_vars): - # Gives ids of nonzero entries in the ith column + # Gives indices of nonzero entries in the ith column nonzero = np.nonzero(self.tableau[:, i]) n_nonzero = len(nonzero[0]) - # First entry in the nonzero ids + # First entry in the nonzero indices nonzero_rowidx = nonzero[0][0] nonzero_val = self.tableau[nonzero_rowidx, i] # If there is only one nonzero value in column, which is one - if n_nonzero == nonzero_val == 1: + if n_nonzero == 1 and nonzero_val == 1: rhs_val = self.tableau[nonzero_rowidx, -1] output_dict[self.col_titles[i]] = rhs_val return output_dict diff --git a/machine_learning/forecasting/ex_data.csv b/machine_learning/forecasting/ex_data.csv index 1c429e649..e6e73c4a1 100644 --- a/machine_learning/forecasting/ex_data.csv +++ b/machine_learning/forecasting/ex_data.csv @@ -1,4 +1,4 @@ -total_user,total_events,days +total_users,total_events,days 18231,0.0,1 22621,1.0,2 15675,0.0,3 diff --git a/machine_learning/forecasting/run.py b/machine_learning/forecasting/run.py index 0909b76d8..64e719daa 100644 --- a/machine_learning/forecasting/run.py +++ b/machine_learning/forecasting/run.py @@ -1,6 +1,6 @@ """ this is code for forecasting -but i modified it and used it for safety checker of data +but I modified it and used it for safety checker of data for ex: you have an online shop and for some reason some data are missing (the amount of data that u expected are not supposed to be) then we can use it @@ -11,6 +11,8 @@ missing (the amount of data that u expected are not supposed to be) u can just adjust it for ur own purpose """ +from warnings import simplefilter + import numpy as np import pandas as pd from sklearn.preprocessing import Normalizer @@ -45,8 +47,10 @@ def sarimax_predictor(train_user: list, train_match: list, test_match: list) -> >>> sarimax_predictor([4,2,6,8], [3,1,2,4], [2]) 6.6666671111109626 """ + # Suppress the User Warning raised by SARIMAX due to insufficient observations + simplefilter("ignore", UserWarning) order = (1, 2, 1) - seasonal_order = (1, 1, 0, 7) + seasonal_order = (1, 1, 1, 7) model = SARIMAX( train_user, exog=train_match, order=order, seasonal_order=seasonal_order ) @@ -102,6 +106,10 @@ def data_safety_checker(list_vote: list, actual_result: float) -> bool: """ safe = 0 not_safe = 0 + + if not isinstance(actual_result, float): + raise TypeError("Actual result should be float. Value passed is a list") + for i in list_vote: if i > actual_result: safe = not_safe + 1 @@ -114,16 +122,11 @@ def data_safety_checker(list_vote: list, actual_result: float) -> bool: if __name__ == "__main__": - # data_input_df = pd.read_csv("ex_data.csv", header=None) - data_input = [[18231, 0.0, 1], [22621, 1.0, 2], [15675, 0.0, 3], [23583, 1.0, 4]] - data_input_df = pd.DataFrame( - data_input, columns=["total_user", "total_even", "days"] - ) - """ data column = total user in a day, how much online event held in one day, what day is that(sunday-saturday) """ + data_input_df = pd.read_csv("ex_data.csv") # start normalization normalize_df = Normalizer().fit_transform(data_input_df.values) @@ -138,23 +141,23 @@ if __name__ == "__main__": x_test = x[len(x) - 1 :] # for linear regression & sarimax - trn_date = total_date[: len(total_date) - 1] - trn_user = total_user[: len(total_user) - 1] - trn_match = total_match[: len(total_match) - 1] + train_date = total_date[: len(total_date) - 1] + train_user = total_user[: len(total_user) - 1] + train_match = total_match[: len(total_match) - 1] - tst_date = total_date[len(total_date) - 1 :] - tst_user = total_user[len(total_user) - 1 :] - tst_match = total_match[len(total_match) - 1 :] + test_date = total_date[len(total_date) - 1 :] + test_user = total_user[len(total_user) - 1 :] + test_match = total_match[len(total_match) - 1 :] # voting system with forecasting res_vote = [ linear_regression_prediction( - trn_date, trn_user, trn_match, tst_date, tst_match + train_date, train_user, train_match, test_date, test_match ), - sarimax_predictor(trn_user, trn_match, tst_match), - support_vector_regressor(x_train, x_test, trn_user), + sarimax_predictor(train_user, train_match, test_match), + support_vector_regressor(x_train, x_test, train_user), ] # check the safety of today's data - not_str = "" if data_safety_checker(res_vote, tst_user) else "not " - print("Today's data is {not_str}safe.") + not_str = "" if data_safety_checker(res_vote, test_user[0]) else "not " + print(f"Today's data is {not_str}safe.") diff --git a/machine_learning/polymonial_regression.py b/machine_learning/polymonial_regression.py deleted file mode 100644 index 487fb8145..000000000 --- a/machine_learning/polymonial_regression.py +++ /dev/null @@ -1,44 +0,0 @@ -import pandas as pd -from matplotlib import pyplot as plt -from sklearn.linear_model import LinearRegression - -# Splitting the dataset into the Training set and Test set -from sklearn.model_selection import train_test_split - -# Fitting Polynomial Regression to the dataset -from sklearn.preprocessing import PolynomialFeatures - -# Importing the dataset -dataset = pd.read_csv( - "https://s3.us-west-2.amazonaws.com/public.gamelab.fun/dataset/" - "position_salaries.csv" -) -X = dataset.iloc[:, 1:2].values -y = dataset.iloc[:, 2].values - - -X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0) - - -poly_reg = PolynomialFeatures(degree=4) -X_poly = poly_reg.fit_transform(X) -pol_reg = LinearRegression() -pol_reg.fit(X_poly, y) - - -# Visualizing the Polymonial Regression results -def viz_polymonial(): - plt.scatter(X, y, color="red") - plt.plot(X, pol_reg.predict(poly_reg.fit_transform(X)), color="blue") - plt.title("Truth or Bluff (Linear Regression)") - plt.xlabel("Position level") - plt.ylabel("Salary") - plt.show() - - -if __name__ == "__main__": - viz_polymonial() - - # Predicting a new result with Polymonial Regression - pol_reg.predict(poly_reg.fit_transform([[5.5]])) - # output should be 132148.43750003 diff --git a/machine_learning/polynomial_regression.py b/machine_learning/polynomial_regression.py new file mode 100644 index 000000000..5bafea96f --- /dev/null +++ b/machine_learning/polynomial_regression.py @@ -0,0 +1,213 @@ +""" +Polynomial regression is a type of regression analysis that models the relationship +between a predictor x and the response y as an mth-degree polynomial: + +y = β₀ + β₁x + β₂x² + ... + βₘxᵐ + ε + +By treating x, x², ..., xᵐ as distinct variables, we see that polynomial regression is a +special case of multiple linear regression. Therefore, we can use ordinary least squares +(OLS) estimation to estimate the vector of model parameters β = (β₀, β₁, β₂, ..., βₘ) +for polynomial regression: + +β = (XᵀX)⁻¹Xᵀy = X⁺y + +where X is the design matrix, y is the response vector, and X⁺ denotes the Moore–Penrose +pseudoinverse of X. In the case of polynomial regression, the design matrix is + + |1 x₁ x₁² ⋯ x₁ᵐ| +X = |1 x₂ x₂² ⋯ x₂ᵐ| + |⋮ ⋮ ⋮ ⋱ ⋮ | + |1 xₙ xₙ² ⋯ xₙᵐ| + +In OLS estimation, inverting XᵀX to compute X⁺ can be very numerically unstable. This +implementation sidesteps this need to invert XᵀX by computing X⁺ using singular value +decomposition (SVD): + +β = VΣ⁺Uᵀy + +where UΣVᵀ is an SVD of X. + +References: + - https://en.wikipedia.org/wiki/Polynomial_regression + - https://en.wikipedia.org/wiki/Moore%E2%80%93Penrose_inverse + - https://en.wikipedia.org/wiki/Numerical_methods_for_linear_least_squares + - https://en.wikipedia.org/wiki/Singular_value_decomposition +""" + +import matplotlib.pyplot as plt +import numpy as np + + +class PolynomialRegression: + __slots__ = "degree", "params" + + def __init__(self, degree: int) -> None: + """ + @raises ValueError: if the polynomial degree is negative + """ + if degree < 0: + raise ValueError("Polynomial degree must be non-negative") + + self.degree = degree + self.params = None + + @staticmethod + def _design_matrix(data: np.ndarray, degree: int) -> np.ndarray: + """ + Constructs a polynomial regression design matrix for the given input data. For + input data x = (x₁, x₂, ..., xₙ) and polynomial degree m, the design matrix is + the Vandermonde matrix + + |1 x₁ x₁² ⋯ x₁ᵐ| + X = |1 x₂ x₂² ⋯ x₂ᵐ| + |⋮ ⋮ ⋮ ⋱ ⋮ | + |1 xₙ xₙ² ⋯ xₙᵐ| + + Reference: https://en.wikipedia.org/wiki/Vandermonde_matrix + + @param data: the input predictor values x, either for model fitting or for + prediction + @param degree: the polynomial degree m + @returns: the Vandermonde matrix X (see above) + @raises ValueError: if input data is not N x 1 + + >>> x = np.array([0, 1, 2]) + >>> PolynomialRegression._design_matrix(x, degree=0) + array([[1], + [1], + [1]]) + >>> PolynomialRegression._design_matrix(x, degree=1) + array([[1, 0], + [1, 1], + [1, 2]]) + >>> PolynomialRegression._design_matrix(x, degree=2) + array([[1, 0, 0], + [1, 1, 1], + [1, 2, 4]]) + >>> PolynomialRegression._design_matrix(x, degree=3) + array([[1, 0, 0, 0], + [1, 1, 1, 1], + [1, 2, 4, 8]]) + >>> PolynomialRegression._design_matrix(np.array([[0, 0], [0 , 0]]), degree=3) + Traceback (most recent call last): + ... + ValueError: Data must have dimensions N x 1 + """ + rows, *remaining = data.shape + if remaining: + raise ValueError("Data must have dimensions N x 1") + + return np.vander(data, N=degree + 1, increasing=True) + + def fit(self, x_train: np.ndarray, y_train: np.ndarray) -> None: + """ + Computes the polynomial regression model parameters using ordinary least squares + (OLS) estimation: + + β = (XᵀX)⁻¹Xᵀy = X⁺y + + where X⁺ denotes the Moore–Penrose pseudoinverse of the design matrix X. This + function computes X⁺ using singular value decomposition (SVD). + + References: + - https://en.wikipedia.org/wiki/Moore%E2%80%93Penrose_inverse + - https://en.wikipedia.org/wiki/Singular_value_decomposition + - https://en.wikipedia.org/wiki/Multicollinearity + + @param x_train: the predictor values x for model fitting + @param y_train: the response values y for model fitting + @raises ArithmeticError: if X isn't full rank, then XᵀX is singular and β + doesn't exist + + >>> x = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) + >>> y = x**3 - 2 * x**2 + 3 * x - 5 + >>> poly_reg = PolynomialRegression(degree=3) + >>> poly_reg.fit(x, y) + >>> poly_reg.params + array([-5., 3., -2., 1.]) + >>> poly_reg = PolynomialRegression(degree=20) + >>> poly_reg.fit(x, y) + Traceback (most recent call last): + ... + ArithmeticError: Design matrix is not full rank, can't compute coefficients + + Make sure errors don't grow too large: + >>> coefs = np.array([-250, 50, -2, 36, 20, -12, 10, 2, -1, -15, 1]) + >>> y = PolynomialRegression._design_matrix(x, len(coefs) - 1) @ coefs + >>> poly_reg = PolynomialRegression(degree=len(coefs) - 1) + >>> poly_reg.fit(x, y) + >>> np.allclose(poly_reg.params, coefs, atol=10e-3) + True + """ + X = PolynomialRegression._design_matrix(x_train, self.degree) # noqa: N806 + _, cols = X.shape + if np.linalg.matrix_rank(X) < cols: + raise ArithmeticError( + "Design matrix is not full rank, can't compute coefficients" + ) + + # np.linalg.pinv() computes the Moore–Penrose pseudoinverse using SVD + self.params = np.linalg.pinv(X) @ y_train + + def predict(self, data: np.ndarray) -> np.ndarray: + """ + Computes the predicted response values y for the given input data by + constructing the design matrix X and evaluating y = Xβ. + + @param data: the predictor values x for prediction + @returns: the predicted response values y = Xβ + @raises ArithmeticError: if this function is called before the model + parameters are fit + + >>> x = np.array([0, 1, 2, 3, 4]) + >>> y = x**3 - 2 * x**2 + 3 * x - 5 + >>> poly_reg = PolynomialRegression(degree=3) + >>> poly_reg.fit(x, y) + >>> poly_reg.predict(np.array([-1])) + array([-11.]) + >>> poly_reg.predict(np.array([-2])) + array([-27.]) + >>> poly_reg.predict(np.array([6])) + array([157.]) + >>> PolynomialRegression(degree=3).predict(x) + Traceback (most recent call last): + ... + ArithmeticError: Predictor hasn't been fit yet + """ + if self.params is None: + raise ArithmeticError("Predictor hasn't been fit yet") + + return PolynomialRegression._design_matrix(data, self.degree) @ self.params + + +def main() -> None: + """ + Fit a polynomial regression model to predict fuel efficiency using seaborn's mpg + dataset + + >>> pass # Placeholder, function is only for demo purposes + """ + import seaborn as sns + + mpg_data = sns.load_dataset("mpg") + + poly_reg = PolynomialRegression(degree=2) + poly_reg.fit(mpg_data.weight, mpg_data.mpg) + + weight_sorted = np.sort(mpg_data.weight) + predictions = poly_reg.predict(weight_sorted) + + plt.scatter(mpg_data.weight, mpg_data.mpg, color="gray", alpha=0.5) + plt.plot(weight_sorted, predictions, color="red", linewidth=3) + plt.title("Predicting Fuel Efficiency Using Polynomial Regression") + plt.xlabel("Weight (lbs)") + plt.ylabel("Fuel Efficiency (mpg)") + plt.show() + + +if __name__ == "__main__": + import doctest + + doctest.testmod() + + main() diff --git a/maths/area_under_curve.py b/maths/area_under_curve.py index b557b2029..0da6546b2 100644 --- a/maths/area_under_curve.py +++ b/maths/area_under_curve.py @@ -7,9 +7,9 @@ from collections.abc import Callable def trapezoidal_area( - fnc: Callable[[int | float], int | float], - x_start: int | float, - x_end: int | float, + fnc: Callable[[float], float], + x_start: float, + x_end: float, steps: int = 100, ) -> float: """ diff --git a/maths/collatz_sequence.py b/maths/collatz_sequence.py index 4f3aa5582..b47017146 100644 --- a/maths/collatz_sequence.py +++ b/maths/collatz_sequence.py @@ -57,7 +57,7 @@ def collatz_sequence(n: int) -> Generator[int, None, None]: def main(): - n = 43 + n = int(input("Your number: ")) sequence = tuple(collatz_sequence(n)) print(sequence) print(f"Collatz sequence from {n} took {len(sequence)} steps.") diff --git a/maths/decimal_to_fraction.py b/maths/decimal_to_fraction.py index 9462bafe0..2aa8e3c3d 100644 --- a/maths/decimal_to_fraction.py +++ b/maths/decimal_to_fraction.py @@ -1,4 +1,4 @@ -def decimal_to_fraction(decimal: int | float | str) -> tuple[int, int]: +def decimal_to_fraction(decimal: float | str) -> tuple[int, int]: """ Return a decimal number in its simplest fraction form >>> decimal_to_fraction(2) diff --git a/maths/factorial.py b/maths/factorial.py index bbf0efc01..18cacdef9 100644 --- a/maths/factorial.py +++ b/maths/factorial.py @@ -55,7 +55,7 @@ def factorial_recursive(n: int) -> int: raise ValueError("factorial() only accepts integral values") if n < 0: raise ValueError("factorial() not defined for negative values") - return 1 if n == 0 or n == 1 else n * factorial(n - 1) + return 1 if n in {0, 1} else n * factorial(n - 1) if __name__ == "__main__": diff --git a/maths/find_max.py b/maths/find_max.py index 684fbe816..729a80ab4 100644 --- a/maths/find_max.py +++ b/maths/find_max.py @@ -1,23 +1,23 @@ from __future__ import annotations -def find_max(nums: list[int | float]) -> int | float: +def find_max_iterative(nums: list[int | float]) -> int | float: """ >>> for nums in ([3, 2, 1], [-3, -2, -1], [3, -3, 0], [3.0, 3.1, 2.9]): - ... find_max(nums) == max(nums) + ... find_max_iterative(nums) == max(nums) True True True True - >>> find_max([2, 4, 9, 7, 19, 94, 5]) + >>> find_max_iterative([2, 4, 9, 7, 19, 94, 5]) 94 - >>> find_max([]) + >>> find_max_iterative([]) Traceback (most recent call last): ... - ValueError: find_max() arg is an empty sequence + ValueError: find_max_iterative() arg is an empty sequence """ if len(nums) == 0: - raise ValueError("find_max() arg is an empty sequence") + raise ValueError("find_max_iterative() arg is an empty sequence") max_num = nums[0] for x in nums: if x > max_num: @@ -25,6 +25,59 @@ def find_max(nums: list[int | float]) -> int | float: return max_num +# Divide and Conquer algorithm +def find_max_recursive(nums: list[int | float], left: int, right: int) -> int | float: + """ + find max value in list + :param nums: contains elements + :param left: index of first element + :param right: index of last element + :return: max in nums + + >>> for nums in ([3, 2, 1], [-3, -2, -1], [3, -3, 0], [3.0, 3.1, 2.9]): + ... find_max_recursive(nums, 0, len(nums) - 1) == max(nums) + True + True + True + True + >>> nums = [1, 3, 5, 7, 9, 2, 4, 6, 8, 10] + >>> find_max_recursive(nums, 0, len(nums) - 1) == max(nums) + True + >>> find_max_recursive([], 0, 0) + Traceback (most recent call last): + ... + ValueError: find_max_recursive() arg is an empty sequence + >>> find_max_recursive(nums, 0, len(nums)) == max(nums) + Traceback (most recent call last): + ... + IndexError: list index out of range + >>> find_max_recursive(nums, -len(nums), -1) == max(nums) + True + >>> find_max_recursive(nums, -len(nums) - 1, -1) == max(nums) + Traceback (most recent call last): + ... + IndexError: list index out of range + """ + if len(nums) == 0: + raise ValueError("find_max_recursive() arg is an empty sequence") + if ( + left >= len(nums) + or left < -len(nums) + or right >= len(nums) + or right < -len(nums) + ): + raise IndexError("list index out of range") + if left == right: + return nums[left] + mid = (left + right) >> 1 # the middle + left_max = find_max_recursive(nums, left, mid) # find max in range[left, mid] + right_max = find_max_recursive( + nums, mid + 1, right + ) # find max in range[mid + 1, right] + + return left_max if left_max >= right_max else right_max + + if __name__ == "__main__": import doctest diff --git a/maths/find_max_recursion.py b/maths/find_max_recursion.py deleted file mode 100644 index 629932e08..000000000 --- a/maths/find_max_recursion.py +++ /dev/null @@ -1,58 +0,0 @@ -from __future__ import annotations - - -# Divide and Conquer algorithm -def find_max(nums: list[int | float], left: int, right: int) -> int | float: - """ - find max value in list - :param nums: contains elements - :param left: index of first element - :param right: index of last element - :return: max in nums - - >>> for nums in ([3, 2, 1], [-3, -2, -1], [3, -3, 0], [3.0, 3.1, 2.9]): - ... find_max(nums, 0, len(nums) - 1) == max(nums) - True - True - True - True - >>> nums = [1, 3, 5, 7, 9, 2, 4, 6, 8, 10] - >>> find_max(nums, 0, len(nums) - 1) == max(nums) - True - >>> find_max([], 0, 0) - Traceback (most recent call last): - ... - ValueError: find_max() arg is an empty sequence - >>> find_max(nums, 0, len(nums)) == max(nums) - Traceback (most recent call last): - ... - IndexError: list index out of range - >>> find_max(nums, -len(nums), -1) == max(nums) - True - >>> find_max(nums, -len(nums) - 1, -1) == max(nums) - Traceback (most recent call last): - ... - IndexError: list index out of range - """ - if len(nums) == 0: - raise ValueError("find_max() arg is an empty sequence") - if ( - left >= len(nums) - or left < -len(nums) - or right >= len(nums) - or right < -len(nums) - ): - raise IndexError("list index out of range") - if left == right: - return nums[left] - mid = (left + right) >> 1 # the middle - left_max = find_max(nums, left, mid) # find max in range[left, mid] - right_max = find_max(nums, mid + 1, right) # find max in range[mid + 1, right] - - return left_max if left_max >= right_max else right_max - - -if __name__ == "__main__": - import doctest - - doctest.testmod(verbose=True) diff --git a/maths/find_min.py b/maths/find_min.py index 2eac087c6..762562e36 100644 --- a/maths/find_min.py +++ b/maths/find_min.py @@ -1,33 +1,86 @@ from __future__ import annotations -def find_min(nums: list[int | float]) -> int | float: +def find_min_iterative(nums: list[int | float]) -> int | float: """ Find Minimum Number in a List :param nums: contains elements :return: min number in list >>> for nums in ([3, 2, 1], [-3, -2, -1], [3, -3, 0], [3.0, 3.1, 2.9]): - ... find_min(nums) == min(nums) + ... find_min_iterative(nums) == min(nums) True True True True - >>> find_min([0, 1, 2, 3, 4, 5, -3, 24, -56]) + >>> find_min_iterative([0, 1, 2, 3, 4, 5, -3, 24, -56]) -56 - >>> find_min([]) + >>> find_min_iterative([]) Traceback (most recent call last): ... - ValueError: find_min() arg is an empty sequence + ValueError: find_min_iterative() arg is an empty sequence """ if len(nums) == 0: - raise ValueError("find_min() arg is an empty sequence") + raise ValueError("find_min_iterative() arg is an empty sequence") min_num = nums[0] for num in nums: min_num = min(min_num, num) return min_num +# Divide and Conquer algorithm +def find_min_recursive(nums: list[int | float], left: int, right: int) -> int | float: + """ + find min value in list + :param nums: contains elements + :param left: index of first element + :param right: index of last element + :return: min in nums + + >>> for nums in ([3, 2, 1], [-3, -2, -1], [3, -3, 0], [3.0, 3.1, 2.9]): + ... find_min_recursive(nums, 0, len(nums) - 1) == min(nums) + True + True + True + True + >>> nums = [1, 3, 5, 7, 9, 2, 4, 6, 8, 10] + >>> find_min_recursive(nums, 0, len(nums) - 1) == min(nums) + True + >>> find_min_recursive([], 0, 0) + Traceback (most recent call last): + ... + ValueError: find_min_recursive() arg is an empty sequence + >>> find_min_recursive(nums, 0, len(nums)) == min(nums) + Traceback (most recent call last): + ... + IndexError: list index out of range + >>> find_min_recursive(nums, -len(nums), -1) == min(nums) + True + >>> find_min_recursive(nums, -len(nums) - 1, -1) == min(nums) + Traceback (most recent call last): + ... + IndexError: list index out of range + """ + if len(nums) == 0: + raise ValueError("find_min_recursive() arg is an empty sequence") + if ( + left >= len(nums) + or left < -len(nums) + or right >= len(nums) + or right < -len(nums) + ): + raise IndexError("list index out of range") + if left == right: + return nums[left] + mid = (left + right) >> 1 # the middle + left_min = find_min_recursive(nums, left, mid) # find min in range[left, mid] + right_min = find_min_recursive( + nums, mid + 1, right + ) # find min in range[mid + 1, right] + + return left_min if left_min <= right_min else right_min + + if __name__ == "__main__": import doctest diff --git a/maths/find_min_recursion.py b/maths/find_min_recursion.py deleted file mode 100644 index 4d11015ef..000000000 --- a/maths/find_min_recursion.py +++ /dev/null @@ -1,58 +0,0 @@ -from __future__ import annotations - - -# Divide and Conquer algorithm -def find_min(nums: list[int | float], left: int, right: int) -> int | float: - """ - find min value in list - :param nums: contains elements - :param left: index of first element - :param right: index of last element - :return: min in nums - - >>> for nums in ([3, 2, 1], [-3, -2, -1], [3, -3, 0], [3.0, 3.1, 2.9]): - ... find_min(nums, 0, len(nums) - 1) == min(nums) - True - True - True - True - >>> nums = [1, 3, 5, 7, 9, 2, 4, 6, 8, 10] - >>> find_min(nums, 0, len(nums) - 1) == min(nums) - True - >>> find_min([], 0, 0) - Traceback (most recent call last): - ... - ValueError: find_min() arg is an empty sequence - >>> find_min(nums, 0, len(nums)) == min(nums) - Traceback (most recent call last): - ... - IndexError: list index out of range - >>> find_min(nums, -len(nums), -1) == min(nums) - True - >>> find_min(nums, -len(nums) - 1, -1) == min(nums) - Traceback (most recent call last): - ... - IndexError: list index out of range - """ - if len(nums) == 0: - raise ValueError("find_min() arg is an empty sequence") - if ( - left >= len(nums) - or left < -len(nums) - or right >= len(nums) - or right < -len(nums) - ): - raise IndexError("list index out of range") - if left == right: - return nums[left] - mid = (left + right) >> 1 # the middle - left_min = find_min(nums, left, mid) # find min in range[left, mid] - right_min = find_min(nums, mid + 1, right) # find min in range[mid + 1, right] - - return left_min if left_min <= right_min else right_min - - -if __name__ == "__main__": - import doctest - - doctest.testmod(verbose=True) diff --git a/maths/interquartile_range.py b/maths/interquartile_range.py new file mode 100644 index 000000000..d4d72e73e --- /dev/null +++ b/maths/interquartile_range.py @@ -0,0 +1,66 @@ +""" +An implementation of interquartile range (IQR) which is a measure of statistical +dispersion, which is the spread of the data. + +The function takes the list of numeric values as input and returns the IQR. + +Script inspired by this Wikipedia article: +https://en.wikipedia.org/wiki/Interquartile_range +""" +from __future__ import annotations + + +def find_median(nums: list[int | float]) -> float: + """ + This is the implementation of the median. + :param nums: The list of numeric nums + :return: Median of the list + >>> find_median(nums=([1, 2, 2, 3, 4])) + 2 + >>> find_median(nums=([1, 2, 2, 3, 4, 4])) + 2.5 + >>> find_median(nums=([-1, 2, 0, 3, 4, -4])) + 1.5 + >>> find_median(nums=([1.1, 2.2, 2, 3.3, 4.4, 4])) + 2.65 + """ + div, mod = divmod(len(nums), 2) + if mod: + return nums[div] + return (nums[div] + nums[(div) - 1]) / 2 + + +def interquartile_range(nums: list[int | float]) -> float: + """ + Return the interquartile range for a list of numeric values. + :param nums: The list of numeric values. + :return: interquartile range + + >>> interquartile_range(nums=[4, 1, 2, 3, 2]) + 2.0 + >>> interquartile_range(nums = [-2, -7, -10, 9, 8, 4, -67, 45]) + 17.0 + >>> interquartile_range(nums = [-2.1, -7.1, -10.1, 9.1, 8.1, 4.1, -67.1, 45.1]) + 17.2 + >>> interquartile_range(nums = [0, 0, 0, 0, 0]) + 0.0 + >>> interquartile_range(nums=[]) + Traceback (most recent call last): + ... + ValueError: The list is empty. Provide a non-empty list. + """ + if not nums: + raise ValueError("The list is empty. Provide a non-empty list.") + nums.sort() + length = len(nums) + div, mod = divmod(length, 2) + q1 = find_median(nums[:div]) + half_length = sum((div, mod)) + q3 = find_median(nums[half_length:length]) + return q3 - q1 + + +if __name__ == "__main__": + import doctest + + doctest.testmod() diff --git a/maths/kadanes.py b/maths/kadanes.py deleted file mode 100644 index c2ea53a6c..000000000 --- a/maths/kadanes.py +++ /dev/null @@ -1,63 +0,0 @@ -""" -Kadane's algorithm to get maximum subarray sum -https://medium.com/@rsinghal757/kadanes-algorithm-dynamic-programming-how-and-why-does-it-work-3fd8849ed73d -https://en.wikipedia.org/wiki/Maximum_subarray_problem -""" -test_data: tuple = ([-2, -8, -9], [2, 8, 9], [-1, 0, 1], [0, 0], []) - - -def negative_exist(arr: list) -> int: - """ - >>> negative_exist([-2,-8,-9]) - -2 - >>> [negative_exist(arr) for arr in test_data] - [-2, 0, 0, 0, 0] - """ - arr = arr or [0] - max_number = arr[0] - for i in arr: - if i >= 0: - return 0 - elif max_number <= i: - max_number = i - return max_number - - -def kadanes(arr: list) -> int: - """ - If negative_exist() returns 0 than this function will execute - else it will return the value return by negative_exist function - - For example: arr = [2, 3, -9, 8, -2] - Initially we set value of max_sum to 0 and max_till_element to 0 than when - max_sum is less than max_till particular element it will assign that value to - max_sum and when value of max_till_sum is less than 0 it will assign 0 to i - and after that whole process, return the max_sum - So the output for above arr is 8 - - >>> kadanes([2, 3, -9, 8, -2]) - 8 - >>> [kadanes(arr) for arr in test_data] - [-2, 19, 1, 0, 0] - """ - max_sum = negative_exist(arr) - if max_sum < 0: - return max_sum - - max_sum = 0 - max_till_element = 0 - - for i in arr: - max_till_element += i - max_sum = max(max_sum, max_till_element) - max_till_element = max(max_till_element, 0) - return max_sum - - -if __name__ == "__main__": - try: - print("Enter integer values sepatated by spaces") - arr = [int(x) for x in input().split()] - print(f"Maximum subarray sum of {arr} is {kadanes(arr)}") - except ValueError: - print("Please enter integer values.") diff --git a/maths/largest_subarray_sum.py b/maths/largest_subarray_sum.py deleted file mode 100644 index 90f92c712..000000000 --- a/maths/largest_subarray_sum.py +++ /dev/null @@ -1,21 +0,0 @@ -from sys import maxsize - - -def max_sub_array_sum(a: list, size: int = 0): - """ - >>> max_sub_array_sum([-13, -3, -25, -20, -3, -16, -23, -12, -5, -22, -15, -4, -7]) - -3 - """ - size = size or len(a) - max_so_far = -maxsize - 1 - max_ending_here = 0 - for i in range(0, size): - max_ending_here = max_ending_here + a[i] - max_so_far = max(max_so_far, max_ending_here) - max_ending_here = max(max_ending_here, 0) - return max_so_far - - -if __name__ == "__main__": - a = [-13, -3, -25, -20, 1, -16, -23, -12, -5, -22, -15, -4, -7] - print(("Maximum contiguous sum is", max_sub_array_sum(a, len(a)))) diff --git a/maths/line_length.py b/maths/line_length.py index b810f2d9a..ed2efc31e 100644 --- a/maths/line_length.py +++ b/maths/line_length.py @@ -5,9 +5,9 @@ from collections.abc import Callable def line_length( - fnc: Callable[[int | float], int | float], - x_start: int | float, - x_end: int | float, + fnc: Callable[[float], float], + x_start: float, + x_end: float, steps: int = 100, ) -> float: """ diff --git a/maths/numerical_integration.py b/maths/numerical_integration.py index f2d65f89e..4ac562644 100644 --- a/maths/numerical_integration.py +++ b/maths/numerical_integration.py @@ -7,9 +7,9 @@ from collections.abc import Callable def trapezoidal_area( - fnc: Callable[[int | float], int | float], - x_start: int | float, - x_end: int | float, + fnc: Callable[[float], float], + x_start: float, + x_end: float, steps: int = 100, ) -> float: """ diff --git a/maths/polynomials/single_indeterminate_operations.py b/maths/polynomials/single_indeterminate_operations.py index 8bafdb591..e31e6caa3 100644 --- a/maths/polynomials/single_indeterminate_operations.py +++ b/maths/polynomials/single_indeterminate_operations.py @@ -87,7 +87,7 @@ class Polynomial: return Polynomial(self.degree + polynomial_2.degree, coefficients) - def evaluate(self, substitution: int | float) -> int | float: + def evaluate(self, substitution: float) -> float: """ Evaluates the polynomial at x. >>> p = Polynomial(2, [1, 2, 3]) @@ -144,7 +144,7 @@ class Polynomial: coefficients[i] = self.coefficients[i + 1] * (i + 1) return Polynomial(self.degree - 1, coefficients) - def integral(self, constant: int | float = 0) -> Polynomial: + def integral(self, constant: float = 0) -> Polynomial: """ Returns the integral of the polynomial. >>> p = Polynomial(2, [1, 2, 3]) diff --git a/maths/primelib.py b/maths/primelib.py index 81d573706..28b5aee9d 100644 --- a/maths/primelib.py +++ b/maths/primelib.py @@ -154,7 +154,7 @@ def prime_factorization(number): quotient = number - if number == 0 or number == 1: + if number in {0, 1}: ans.append(number) # if 'number' not prime then builds the prime factorization of 'number' diff --git a/maths/series/geometric_series.py b/maths/series/geometric_series.py index 90c9fe77b..b8d6a8620 100644 --- a/maths/series/geometric_series.py +++ b/maths/series/geometric_series.py @@ -14,10 +14,10 @@ from __future__ import annotations def geometric_series( - nth_term: float | int, - start_term_a: float | int, - common_ratio_r: float | int, -) -> list[float | int]: + nth_term: float, + start_term_a: float, + common_ratio_r: float, +) -> list[float]: """ Pure Python implementation of Geometric Series algorithm @@ -48,7 +48,7 @@ def geometric_series( """ if not all((nth_term, start_term_a, common_ratio_r)): return [] - series: list[float | int] = [] + series: list[float] = [] power = 1 multiple = common_ratio_r for _ in range(int(nth_term)): diff --git a/maths/series/p_series.py b/maths/series/p_series.py index 34fa3f239..a091a6f3f 100644 --- a/maths/series/p_series.py +++ b/maths/series/p_series.py @@ -13,7 +13,7 @@ python3 p_series.py from __future__ import annotations -def p_series(nth_term: int | float | str, power: int | float | str) -> list[str]: +def p_series(nth_term: float | str, power: float | str) -> list[str]: """ Pure Python implementation of P-Series algorithm :return: The P-Series starting from 1 to last (nth) term diff --git a/maths/volume.py b/maths/volume.py index 1da4584c8..721974e68 100644 --- a/maths/volume.py +++ b/maths/volume.py @@ -8,7 +8,7 @@ from __future__ import annotations from math import pi, pow -def vol_cube(side_length: int | float) -> float: +def vol_cube(side_length: float) -> float: """ Calculate the Volume of a Cube. >>> vol_cube(1) diff --git a/matrix/matrix_class.py b/matrix/matrix_class.py index a73e8b92a..a5940a38e 100644 --- a/matrix/matrix_class.py +++ b/matrix/matrix_class.py @@ -141,7 +141,7 @@ class Matrix: @property def order(self) -> tuple[int, int]: - return (self.num_rows, self.num_columns) + return self.num_rows, self.num_columns @property def is_square(self) -> bool: @@ -315,7 +315,7 @@ class Matrix: ] ) - def __mul__(self, other: Matrix | int | float) -> Matrix: + def __mul__(self, other: Matrix | float) -> Matrix: if isinstance(other, (int, float)): return Matrix( [[int(element * other) for element in row] for row in self.rows] diff --git a/matrix/matrix_operation.py b/matrix/matrix_operation.py index f189f1898..d63e758f1 100644 --- a/matrix/matrix_operation.py +++ b/matrix/matrix_operation.py @@ -47,7 +47,7 @@ def subtract(matrix_a: list[list[int]], matrix_b: list[list[int]]) -> list[list[ raise TypeError("Expected a matrix, got int/list instead") -def scalar_multiply(matrix: list[list[int]], n: int | float) -> list[list[float]]: +def scalar_multiply(matrix: list[list[int]], n: float) -> list[list[float]]: """ >>> scalar_multiply([[1,2],[3,4]],5) [[5, 10], [15, 20]] @@ -189,9 +189,7 @@ def main() -> None: matrix_c = [[11, 12, 13, 14], [21, 22, 23, 24], [31, 32, 33, 34], [41, 42, 43, 44]] matrix_d = [[3, 0, 2], [2, 0, -2], [0, 1, 1]] print(f"Add Operation, {add(matrix_a, matrix_b) = } \n") - print( - f"Multiply Operation, {multiply(matrix_a, matrix_b) = } \n", - ) + print(f"Multiply Operation, {multiply(matrix_a, matrix_b) = } \n") print(f"Identity: {identity(5)}\n") print(f"Minor of {matrix_c} = {minor(matrix_c, 1, 2)} \n") print(f"Determinant of {matrix_b} = {determinant(matrix_b)} \n") diff --git a/matrix/searching_in_sorted_matrix.py b/matrix/searching_in_sorted_matrix.py index ddca3b1ce..f55cc71d6 100644 --- a/matrix/searching_in_sorted_matrix.py +++ b/matrix/searching_in_sorted_matrix.py @@ -1,9 +1,7 @@ from __future__ import annotations -def search_in_a_sorted_matrix( - mat: list[list[int]], m: int, n: int, key: int | float -) -> None: +def search_in_a_sorted_matrix(mat: list[list[int]], m: int, n: int, key: float) -> None: """ >>> search_in_a_sorted_matrix( ... [[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]], 3, 3, 5) diff --git a/matrix/sherman_morrison.py b/matrix/sherman_morrison.py index 256271e8a..b6e50f70f 100644 --- a/matrix/sherman_morrison.py +++ b/matrix/sherman_morrison.py @@ -22,7 +22,7 @@ class Matrix: """ self.row, self.column = row, column - self.array = [[default_value for c in range(column)] for r in range(row)] + self.array = [[default_value for _ in range(column)] for _ in range(row)] def __str__(self) -> str: """ @@ -54,15 +54,15 @@ class Matrix: def __repr__(self) -> str: return str(self) - def validate_indicies(self, loc: tuple[int, int]) -> bool: + def validate_indices(self, loc: tuple[int, int]) -> bool: """ Check if given indices are valid to pick element from matrix. Example: >>> a = Matrix(2, 6, 0) - >>> a.validate_indicies((2, 7)) + >>> a.validate_indices((2, 7)) False - >>> a.validate_indicies((0, 0)) + >>> a.validate_indices((0, 0)) True """ if not (isinstance(loc, (list, tuple)) and len(loc) == 2): @@ -81,7 +81,7 @@ class Matrix: >>> a[1, 0] 7 """ - assert self.validate_indicies(loc) + assert self.validate_indices(loc) return self.array[loc[0]][loc[1]] def __setitem__(self, loc: tuple[int, int], value: float) -> None: @@ -96,7 +96,7 @@ class Matrix: [ 1, 1, 1] [ 1, 1, 51] """ - assert self.validate_indicies(loc) + assert self.validate_indices(loc) self.array[loc[0]][loc[1]] = value def __add__(self, another: Matrix) -> Matrix: @@ -145,7 +145,7 @@ class Matrix: def __sub__(self, another: Matrix) -> Matrix: return self + (-another) - def __mul__(self, another: int | float | Matrix) -> Matrix: + def __mul__(self, another: float | Matrix) -> Matrix: """ Return self * another. @@ -233,7 +233,7 @@ class Matrix: v_t = v.transpose() numerator_factor = (v_t * self * u)[0, 0] + 1 if numerator_factor == 0: - return None # It's not invertable + return None # It's not invertible return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor)) diff --git a/neural_network/input_data.py b/neural_network/input_data.py.DEPRECATED.txt similarity index 99% rename from neural_network/input_data.py rename to neural_network/input_data.py.DEPRECATED.txt index 94c018ece..a58e64907 100644 --- a/neural_network/input_data.py +++ b/neural_network/input_data.py.DEPRECATED.txt @@ -263,9 +263,7 @@ def _maybe_download(filename, work_directory, source_url): return filepath -@deprecated( - None, "Please use alternatives such as:" " tensorflow_datasets.load('mnist')" -) +@deprecated(None, "Please use alternatives such as: tensorflow_datasets.load('mnist')") def read_data_sets( train_dir, fake_data=False, diff --git a/other/davisb_putnamb_logemannb_loveland.py b/other/davisb_putnamb_logemannb_loveland.py index a1bea5b39..f5fb103ba 100644 --- a/other/davisb_putnamb_logemannb_loveland.py +++ b/other/davisb_putnamb_logemannb_loveland.py @@ -253,7 +253,7 @@ def find_unit_clauses( unit_symbols = [] for clause in clauses: if len(clause) == 1: - unit_symbols.append(list(clause.literals.keys())[0]) + unit_symbols.append(next(iter(clause.literals.keys()))) else: f_count, n_count = 0, 0 for literal, value in clause.literals.items(): diff --git a/other/maximum_subarray.py b/other/maximum_subarray.py deleted file mode 100644 index 1c8c8cabc..000000000 --- a/other/maximum_subarray.py +++ /dev/null @@ -1,32 +0,0 @@ -from collections.abc import Sequence - - -def max_subarray_sum(nums: Sequence[int]) -> int: - """Return the maximum possible sum amongst all non - empty subarrays. - - Raises: - ValueError: when nums is empty. - - >>> max_subarray_sum([1,2,3,4,-2]) - 10 - >>> max_subarray_sum([-2,1,-3,4,-1,2,1,-5,4]) - 6 - """ - if not nums: - raise ValueError("Input sequence should not be empty") - - curr_max = ans = nums[0] - nums_len = len(nums) - - for i in range(1, nums_len): - num = nums[i] - curr_max = max(curr_max + num, num) - ans = max(curr_max, ans) - - return ans - - -if __name__ == "__main__": - n = int(input("Enter number of elements : ").strip()) - array = list(map(int, input("\nEnter the numbers : ").strip().split()))[:n] - print(max_subarray_sum(array)) diff --git a/other/number_container_system.py b/other/number_container_system.py index f547bc8a2..6c95dd0a3 100644 --- a/other/number_container_system.py +++ b/other/number_container_system.py @@ -1,6 +1,6 @@ """ A number container system that uses binary search to delete and insert values into -arrays with O(n logn) write times and O(1) read times. +arrays with O(log n) write times and O(1) read times. This container system holds integers at indexes. diff --git a/physics/altitude_pressure.py b/physics/altitude_pressure.py new file mode 100644 index 000000000..65307d223 --- /dev/null +++ b/physics/altitude_pressure.py @@ -0,0 +1,52 @@ +""" +Title : Calculate altitude using Pressure + +Description : + The below algorithm approximates the altitude using Barometric formula + + +""" + + +def get_altitude_at_pressure(pressure: float) -> float: + """ + This method calculates the altitude from Pressure wrt to + Sea level pressure as reference .Pressure is in Pascals + https://en.wikipedia.org/wiki/Pressure_altitude + https://community.bosch-sensortec.com/t5/Question-and-answers/How-to-calculate-the-altitude-from-the-pressure-sensor-data/qaq-p/5702 + + H = 44330 * [1 - (P/p0)^(1/5.255) ] + + Where : + H = altitude (m) + P = measured pressure + p0 = reference pressure at sea level 101325 Pa + + Examples: + >>> get_altitude_at_pressure(pressure=100_000) + 105.47836610778828 + >>> get_altitude_at_pressure(pressure=101_325) + 0.0 + >>> get_altitude_at_pressure(pressure=80_000) + 1855.873388064995 + >>> get_altitude_at_pressure(pressure=201_325) + Traceback (most recent call last): + ... + ValueError: Value Higher than Pressure at Sea Level ! + >>> get_altitude_at_pressure(pressure=-80_000) + Traceback (most recent call last): + ... + ValueError: Atmospheric Pressure can not be negative ! + """ + + if pressure > 101325: + raise ValueError("Value Higher than Pressure at Sea Level !") + if pressure < 0: + raise ValueError("Atmospheric Pressure can not be negative !") + return 44_330 * (1 - (pressure / 101_325) ** (1 / 5.5255)) + + +if __name__ == "__main__": + import doctest + + doctest.testmod() diff --git a/physics/basic_orbital_capture.py b/physics/basic_orbital_capture.py new file mode 100644 index 000000000..eeb45e602 --- /dev/null +++ b/physics/basic_orbital_capture.py @@ -0,0 +1,178 @@ +from math import pow, sqrt + +from scipy.constants import G, c, pi + +""" +These two functions will return the radii of impact for a target object +of mass M and radius R as well as it's effective cross sectional area σ(sigma). +That is to say any projectile with velocity v passing within σ, will impact the +target object with mass M. The derivation of which is given at the bottom +of this file. + +The derivation shows that a projectile does not need to aim directly at the target +body in order to hit it, as R_capture>R_target. Astronomers refer to the effective +cross section for capture as σ=π*R_capture**2. + +This algorithm does not account for an N-body problem. + +""" + + +def capture_radii( + target_body_radius: float, target_body_mass: float, projectile_velocity: float +) -> float: + """ + Input Params: + ------------- + target_body_radius: Radius of the central body SI units: meters | m + target_body_mass: Mass of the central body SI units: kilograms | kg + projectile_velocity: Velocity of object moving toward central body + SI units: meters/second | m/s + Returns: + -------- + >>> capture_radii(6.957e8, 1.99e30, 25000.0) + 17209590691.0 + >>> capture_radii(-6.957e8, 1.99e30, 25000.0) + Traceback (most recent call last): + ... + ValueError: Radius cannot be less than 0 + >>> capture_radii(6.957e8, -1.99e30, 25000.0) + Traceback (most recent call last): + ... + ValueError: Mass cannot be less than 0 + >>> capture_radii(6.957e8, 1.99e30, c+1) + Traceback (most recent call last): + ... + ValueError: Cannot go beyond speed of light + + Returned SI units: + ------------------ + meters | m + """ + + if target_body_mass < 0: + raise ValueError("Mass cannot be less than 0") + if target_body_radius < 0: + raise ValueError("Radius cannot be less than 0") + if projectile_velocity > c: + raise ValueError("Cannot go beyond speed of light") + + escape_velocity_squared = (2 * G * target_body_mass) / target_body_radius + capture_radius = target_body_radius * sqrt( + 1 + escape_velocity_squared / pow(projectile_velocity, 2) + ) + return round(capture_radius, 0) + + +def capture_area(capture_radius: float) -> float: + """ + Input Param: + ------------ + capture_radius: The radius of orbital capture and impact for a central body of + mass M and a projectile moving towards it with velocity v + SI units: meters | m + Returns: + -------- + >>> capture_area(17209590691) + 9.304455331329126e+20 + >>> capture_area(-1) + Traceback (most recent call last): + ... + ValueError: Cannot have a capture radius less than 0 + + Returned SI units: + ------------------ + meters*meters | m**2 + """ + + if capture_radius < 0: + raise ValueError("Cannot have a capture radius less than 0") + sigma = pi * pow(capture_radius, 2) + return round(sigma, 0) + + +if __name__ == "__main__": + from doctest import testmod + + testmod() + +""" +Derivation: + +Let: Mt=target mass, Rt=target radius, v=projectile_velocity, + r_0=radius of projectile at instant 0 to CM of target + v_p=v at closest approach, + r_p=radius from projectile to target CM at closest approach, + R_capture= radius of impact for projectile with velocity v + +(1)At time=0 the projectile's energy falling from infinity| E=K+U=0.5*m*(v**2)+0 + + E_initial=0.5*m*(v**2) + +(2)at time=0 the angular momentum of the projectile relative to CM target| + L_initial=m*r_0*v*sin(Θ)->m*r_0*v*(R_capture/r_0)->m*v*R_capture + + L_i=m*v*R_capture + +(3)The energy of the projectile at closest approach will be its kinetic energy + at closest approach plus gravitational potential energy(-(GMm)/R)| + E_p=K_p+U_p->E_p=0.5*m*(v_p**2)-(G*Mt*m)/r_p + + E_p=0.0.5*m*(v_p**2)-(G*Mt*m)/r_p + +(4)The angular momentum of the projectile relative to the target at closest + approach will be L_p=m*r_p*v_p*sin(Θ), however relative to the target Θ=90° + sin(90°)=1| + + L_p=m*r_p*v_p +(5)Using conservation of angular momentum and energy, we can write a quadratic + equation that solves for r_p| + + (a) + Ei=Ep-> 0.5*m*(v**2)=0.5*m*(v_p**2)-(G*Mt*m)/r_p-> v**2=v_p**2-(2*G*Mt)/r_p + + (b) + Li=Lp-> m*v*R_capture=m*r_p*v_p-> v*R_capture=r_p*v_p-> v_p=(v*R_capture)/r_p + + (c) b plugs int a| + v**2=((v*R_capture)/r_p)**2-(2*G*Mt)/r_p-> + + v**2-(v**2)*(R_c**2)/(r_p**2)+(2*G*Mt)/r_p=0-> + + (v**2)*(r_p**2)+2*G*Mt*r_p-(v**2)*(R_c**2)=0 + + (d) Using the quadratic formula, we'll solve for r_p then rearrange to solve to + R_capture + + r_p=(-2*G*Mt ± sqrt(4*G^2*Mt^2+ 4(v^4*R_c^2)))/(2*v^2)-> + + r_p=(-G*Mt ± sqrt(G^2*Mt+v^4*R_c^2))/v^2-> + + r_p<0 is something we can ignore, as it has no physical meaning for our purposes.-> + + r_p=(-G*Mt)/v^2 + sqrt(G^2*Mt^2/v^4 + R_c^2) + + (e)We are trying to solve for R_c. We are looking for impact, so we want r_p=Rt + + Rt + G*Mt/v^2 = sqrt(G^2*Mt^2/v^4 + R_c^2)-> + + (Rt + G*Mt/v^2)^2 = G^2*Mt^2/v^4 + R_c^2-> + + Rt^2 + 2*G*Mt*Rt/v^2 + G^2*Mt^2/v^4 = G^2*Mt^2/v^4 + R_c^2-> + + Rt**2 + 2*G*Mt*Rt/v**2 = R_c**2-> + + Rt**2 * (1 + 2*G*Mt/Rt *1/v**2) = R_c**2-> + + escape velocity = sqrt(2GM/R)= v_escape**2=2GM/R-> + + Rt**2 * (1 + v_esc**2/v**2) = R_c**2-> + +(6) + R_capture = Rt * sqrt(1 + v_esc**2/v**2) + +Source: Problem Set 3 #8 c.Fall_2017|Honors Astronomy|Professor Rachel Bezanson + +Source #2: http://www.nssc.ac.cn/wxzygx/weixin/201607/P020160718380095698873.pdf + 8.8 Planetary Rendezvous: Pg.368 +""" diff --git a/physics/ideal_gas_law.py b/physics/ideal_gas_law.py index 805da47b0..09b4fb3a9 100644 --- a/physics/ideal_gas_law.py +++ b/physics/ideal_gas_law.py @@ -53,6 +53,40 @@ def volume_of_gas_system(moles: float, kelvin: float, pressure: float) -> float: return moles * kelvin * UNIVERSAL_GAS_CONSTANT / pressure +def temperature_of_gas_system(moles: float, volume: float, pressure: float) -> float: + """ + >>> temperature_of_gas_system(2, 100, 5) + 30.068090996146232 + >>> temperature_of_gas_system(11, 5009, 1000) + 54767.66101807144 + >>> temperature_of_gas_system(3, -0.46, 23.5) + Traceback (most recent call last): + ... + ValueError: Invalid inputs. Enter positive value. + """ + if moles < 0 or volume < 0 or pressure < 0: + raise ValueError("Invalid inputs. Enter positive value.") + + return pressure * volume / (moles * UNIVERSAL_GAS_CONSTANT) + + +def moles_of_gas_system(kelvin: float, volume: float, pressure: float) -> float: + """ + >>> moles_of_gas_system(100, 5, 10) + 0.06013618199229246 + >>> moles_of_gas_system(110, 5009, 1000) + 5476.766101807144 + >>> moles_of_gas_system(3, -0.46, 23.5) + Traceback (most recent call last): + ... + ValueError: Invalid inputs. Enter positive value. + """ + if kelvin < 0 or volume < 0 or pressure < 0: + raise ValueError("Invalid inputs. Enter positive value.") + + return pressure * volume / (kelvin * UNIVERSAL_GAS_CONSTANT) + + if __name__ == "__main__": from doctest import testmod diff --git a/physics/newtons_second_law_of_motion.py b/physics/newtons_second_law_of_motion.py index cb53f8f65..53fab6ce7 100644 --- a/physics/newtons_second_law_of_motion.py +++ b/physics/newtons_second_law_of_motion.py @@ -60,7 +60,7 @@ def newtons_second_law_of_motion(mass: float, acceleration: float) -> float: >>> newtons_second_law_of_motion(2.0, 1) 2.0 """ - force = float() + force = 0.0 try: force = mass * acceleration except Exception: diff --git a/project_euler/problem_009/sol3.py b/project_euler/problem_009/sol3.py index d299f821d..37340d306 100644 --- a/project_euler/problem_009/sol3.py +++ b/project_euler/problem_009/sol3.py @@ -28,12 +28,16 @@ def solution() -> int: 31875000 """ - return [ - a * b * (1000 - a - b) - for a in range(1, 999) - for b in range(a, 999) - if (a * a + b * b == (1000 - a - b) ** 2) - ][0] + return next( + iter( + [ + a * b * (1000 - a - b) + for a in range(1, 999) + for b in range(a, 999) + if (a * a + b * b == (1000 - a - b) ** 2) + ] + ) + ) if __name__ == "__main__": diff --git a/pyproject.toml b/pyproject.toml index 4f21a9519..f9091fb85 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -49,6 +49,7 @@ select = [ # https://beta.ruff.rs/docs/rules "ICN", # flake8-import-conventions "INP", # flake8-no-pep420 "INT", # flake8-gettext + "ISC", # flake8-implicit-str-concat "N", # pep8-naming "NPY", # NumPy-specific rules "PGH", # pygrep-hooks @@ -72,7 +73,6 @@ select = [ # https://beta.ruff.rs/docs/rules # "DJ", # flake8-django # "ERA", # eradicate -- DO NOT FIX # "FBT", # flake8-boolean-trap # FIX ME - # "ISC", # flake8-implicit-str-concat # FIX ME # "PD", # pandas-vet # "PT", # flake8-pytest-style # "PTH", # flake8-use-pathlib # FIX ME diff --git a/quantum/quantum_random.py b/quantum/quantum_random.py.DISABLED.txt similarity index 100% rename from quantum/quantum_random.py rename to quantum/quantum_random.py.DISABLED.txt diff --git a/quantum/ripple_adder_classic.py b/quantum/ripple_adder_classic.py index b604395bc..2284141cc 100644 --- a/quantum/ripple_adder_classic.py +++ b/quantum/ripple_adder_classic.py @@ -107,7 +107,7 @@ def ripple_adder( res = qiskit.execute(circuit, backend, shots=1).result() # The result is in binary. Convert it back to int - return int(list(res.get_counts())[0], 2) + return int(next(iter(res.get_counts())), 2) if __name__ == "__main__": diff --git a/requirements.txt b/requirements.txt index acfbc823e..2702523d5 100644 --- a/requirements.txt +++ b/requirements.txt @@ -9,6 +9,7 @@ pandas pillow projectq qiskit +qiskit-aer requests rich scikit-fuzzy diff --git a/searches/jump_search.py b/searches/jump_search.py index 31a9656c5..3bc3c3780 100644 --- a/searches/jump_search.py +++ b/searches/jump_search.py @@ -4,14 +4,28 @@ This algorithm iterates through a sorted collection with a step of n^(1/2), until the element compared is bigger than the one searched. It will then perform a linear search until it matches the wanted number. If not found, it returns -1. + +https://en.wikipedia.org/wiki/Jump_search """ import math +from collections.abc import Sequence +from typing import Any, Protocol, TypeVar -def jump_search(arr: list, x: int) -> int: +class Comparable(Protocol): + def __lt__(self, other: Any, /) -> bool: + ... + + +T = TypeVar("T", bound=Comparable) + + +def jump_search(arr: Sequence[T], item: T) -> int: """ - Pure Python implementation of the jump search algorithm. + Python implementation of the jump search algorithm. + Return the index if the `item` is found, otherwise return -1. + Examples: >>> jump_search([0, 1, 2, 3, 4, 5], 3) 3 @@ -21,31 +35,36 @@ def jump_search(arr: list, x: int) -> int: -1 >>> jump_search([0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610], 55) 10 + >>> jump_search(["aa", "bb", "cc", "dd", "ee", "ff"], "ee") + 4 """ - n = len(arr) - step = int(math.floor(math.sqrt(n))) + arr_size = len(arr) + block_size = int(math.sqrt(arr_size)) + prev = 0 - while arr[min(step, n) - 1] < x: + step = block_size + while arr[min(step, arr_size) - 1] < item: prev = step - step += int(math.floor(math.sqrt(n))) - if prev >= n: + step += block_size + if prev >= arr_size: return -1 - while arr[prev] < x: - prev = prev + 1 - if prev == min(step, n): + while arr[prev] < item: + prev += 1 + if prev == min(step, arr_size): return -1 - if arr[prev] == x: + if arr[prev] == item: return prev return -1 if __name__ == "__main__": user_input = input("Enter numbers separated by a comma:\n").strip() - arr = [int(item) for item in user_input.split(",")] + array = [int(item) for item in user_input.split(",")] x = int(input("Enter the number to be searched:\n")) - res = jump_search(arr, x) + + res = jump_search(array, x) if res == -1: print("Number not found!") else: diff --git a/searches/linear_search.py b/searches/linear_search.py index 777080d14..ba6e81d6b 100644 --- a/searches/linear_search.py +++ b/searches/linear_search.py @@ -15,7 +15,7 @@ def linear_search(sequence: list, target: int) -> int: :param sequence: a collection with comparable items (as sorted items not required in Linear Search) :param target: item value to search - :return: index of found item or None if item is not found + :return: index of found item or -1 if item is not found Examples: >>> linear_search([0, 5, 7, 10, 15], 0) diff --git a/sorts/bubble_sort.py b/sorts/bubble_sort.py index aef2da272..7da4362a5 100644 --- a/sorts/bubble_sort.py +++ b/sorts/bubble_sort.py @@ -1,4 +1,7 @@ -def bubble_sort(collection): +from typing import Any + + +def bubble_sort(collection: list[Any]) -> list[Any]: """Pure implementation of bubble sort algorithm in Python :param collection: some mutable ordered collection with heterogeneous @@ -28,9 +31,9 @@ def bubble_sort(collection): True """ length = len(collection) - for i in range(length - 1): + for i in reversed(range(length)): swapped = False - for j in range(length - 1 - i): + for j in range(i): if collection[j] > collection[j + 1]: swapped = True collection[j], collection[j + 1] = collection[j + 1], collection[j] diff --git a/strings/is_srilankan_phone_number.py b/strings/is_srilankan_phone_number.py index 7bded93f7..6456f85e1 100644 --- a/strings/is_srilankan_phone_number.py +++ b/strings/is_srilankan_phone_number.py @@ -22,9 +22,7 @@ def is_sri_lankan_phone_number(phone: str) -> bool: False """ - pattern = re.compile( - r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" - ) + pattern = re.compile(r"^(?:0|94|\+94|0{2}94)7(0|1|2|4|5|6|7|8)(-| |)\d{7}$") return bool(re.search(pattern, phone)) diff --git a/strings/is_valid_email_address.py b/strings/is_valid_email_address.py new file mode 100644 index 000000000..205394f81 --- /dev/null +++ b/strings/is_valid_email_address.py @@ -0,0 +1,117 @@ +""" +Implements an is valid email address algorithm + +@ https://en.wikipedia.org/wiki/Email_address +""" + +import string + +email_tests: tuple[tuple[str, bool], ...] = ( + ("simple@example.com", True), + ("very.common@example.com", True), + ("disposable.style.email.with+symbol@example.com", True), + ("other-email-with-hyphen@and.subdomains.example.com", True), + ("fully-qualified-domain@example.com", True), + ("user.name+tag+sorting@example.com", True), + ("x@example.com", True), + ("example-indeed@strange-example.com", True), + ("test/test@test.com", True), + ( + "123456789012345678901234567890123456789012345678901234567890123@example.com", + True, + ), + ("admin@mailserver1", True), + ("example@s.example", True), + ("Abc.example.com", False), + ("A@b@c@example.com", False), + ("abc@example..com", False), + ("a(c)d,e:f;gi[j\\k]l@example.com", False), + ( + "12345678901234567890123456789012345678901234567890123456789012345@example.com", + False, + ), + ("i.like.underscores@but_its_not_allowed_in_this_part", False), + ("", False), +) + +# The maximum octets (one character as a standard unicode character is one byte) +# that the local part and the domain part can have +MAX_LOCAL_PART_OCTETS = 64 +MAX_DOMAIN_OCTETS = 255 + + +def is_valid_email_address(email: str) -> bool: + """ + Returns True if the passed email address is valid. + + The local part of the email precedes the singular @ symbol and + is associated with a display-name. For example, "john.smith" + The domain is stricter than the local part and follows the @ symbol. + + Global email checks: + 1. There can only be one @ symbol in the email address. Technically if the + @ symbol is quoted in the local-part, then it is valid, however this + implementation ignores "" for now. + (See https://en.wikipedia.org/wiki/Email_address#:~:text=If%20quoted,) + 2. The local-part and the domain are limited to a certain number of octets. With + unicode storing a single character in one byte, each octet is equivalent to + a character. Hence, we can just check the length of the string. + Checks for the local-part: + 3. The local-part may contain: upper and lowercase latin letters, digits 0 to 9, + and printable characters (!#$%&'*+-/=?^_`{|}~) + 4. The local-part may also contain a "." in any place that is not the first or + last character, and may not have more than one "." consecutively. + + Checks for the domain: + 5. The domain may contain: upper and lowercase latin letters and digits 0 to 9 + 6. Hyphen "-", provided that it is not the first or last character + 7. The domain may also contain a "." in any place that is not the first or + last character, and may not have more than one "." consecutively. + + >>> for email, valid in email_tests: + ... assert is_valid_email_address(email) == valid + """ + + # (1.) Make sure that there is only one @ symbol in the email address + if email.count("@") != 1: + return False + + local_part, domain = email.split("@") + # (2.) Check octet length of the local part and domain + if len(local_part) > MAX_LOCAL_PART_OCTETS or len(domain) > MAX_DOMAIN_OCTETS: + return False + + # (3.) Validate the characters in the local-part + if any( + char not in string.ascii_letters + string.digits + ".(!#$%&'*+-/=?^_`{|}~)" + for char in local_part + ): + return False + + # (4.) Validate the placement of "." characters in the local-part + if local_part.startswith(".") or local_part.endswith(".") or ".." in local_part: + return False + + # (5.) Validate the characters in the domain + if any(char not in string.ascii_letters + string.digits + ".-" for char in domain): + return False + + # (6.) Validate the placement of "-" characters + if domain.startswith("-") or domain.endswith("."): + return False + + # (7.) Validate the placement of "." characters + if domain.startswith(".") or domain.endswith(".") or ".." in domain: + return False + return True + + +if __name__ == "__main__": + import doctest + + doctest.testmod() + + for email, valid in email_tests: + is_valid = is_valid_email_address(email) + assert is_valid == valid, f"{email} is {is_valid}" + print(f"Email address {email} is {'not ' if not is_valid else ''}valid") diff --git a/strings/min_cost_string_conversion.py b/strings/min_cost_string_conversion.py index 089c2532f..0fad0b88c 100644 --- a/strings/min_cost_string_conversion.py +++ b/strings/min_cost_string_conversion.py @@ -61,7 +61,7 @@ def assemble_transformation(ops: list[list[str]], i: int, j: int) -> list[str]: if i == 0 and j == 0: return [] else: - if ops[i][j][0] == "C" or ops[i][j][0] == "R": + if ops[i][j][0] in {"C", "R"}: seq = assemble_transformation(ops, i - 1, j - 1) seq.append(ops[i][j]) return seq diff --git a/web_programming/convert_number_to_words.py b/web_programming/convert_number_to_words.py index 1e293df96..dac9e3e38 100644 --- a/web_programming/convert_number_to_words.py +++ b/web_programming/convert_number_to_words.py @@ -90,9 +90,7 @@ def convert(number: int) -> str: else: addition = "" if counter in placevalue: - if current == 0 and ((temp_num % 100) // 10) == 0: - addition = "" - else: + if current != 0 and ((temp_num % 100) // 10) != 0: addition = placevalue[counter] if ((temp_num % 100) // 10) == 1: words = teens[current] + addition + words diff --git a/web_programming/covid_stats_via_xpath.py b/web_programming/covid_stats_via_xpath.py index 85ea5d940..a95130bad 100644 --- a/web_programming/covid_stats_via_xpath.py +++ b/web_programming/covid_stats_via_xpath.py @@ -4,17 +4,21 @@ This is to show simple COVID19 info fetching from worldometers site using lxml more convenient to use in Python web projects (e.g. Django or Flask-based) """ -from collections import namedtuple +from typing import NamedTuple import requests from lxml import html # type: ignore -covid_data = namedtuple("covid_data", "cases deaths recovered") + +class CovidData(NamedTuple): + cases: int + deaths: int + recovered: int -def covid_stats(url: str = "https://www.worldometers.info/coronavirus/") -> covid_data: +def covid_stats(url: str = "https://www.worldometers.info/coronavirus/") -> CovidData: xpath_str = '//div[@class = "maincounter-number"]/span/text()' - return covid_data(*html.fromstring(requests.get(url).content).xpath(xpath_str)) + return CovidData(*html.fromstring(requests.get(url).content).xpath(xpath_str)) fmt = """Total COVID-19 cases in the world: {} diff --git a/web_programming/current_stock_price.py b/web_programming/current_stock_price.py index df44da4ef..0c06354d8 100644 --- a/web_programming/current_stock_price.py +++ b/web_programming/current_stock_price.py @@ -3,12 +3,18 @@ from bs4 import BeautifulSoup def stock_price(symbol: str = "AAPL") -> str: - url = f"https://in.finance.yahoo.com/quote/{symbol}?s={symbol}" - soup = BeautifulSoup(requests.get(url).text, "html.parser") - class_ = "My(6px) Pos(r) smartphone_Mt(6px)" - return soup.find("div", class_=class_).find("span").text + url = f"https://finance.yahoo.com/quote/{symbol}?p={symbol}" + yahoo_finance_source = requests.get(url, headers={"USER-AGENT": "Mozilla/5.0"}).text + soup = BeautifulSoup(yahoo_finance_source, "html.parser") + specific_fin_streamer_tag = soup.find("fin-streamer", {"data-test": "qsp-price"}) + + if specific_fin_streamer_tag: + text = specific_fin_streamer_tag.get_text() + return text + return "No tag with the specified data-test attribute found." +# Search for the symbol at https://finance.yahoo.com/lookup if __name__ == "__main__": for symbol in "AAPL AMZN IBM GOOG MSFT ORCL".split(): print(f"Current {symbol:<4} stock price is {stock_price(symbol):>8}") diff --git a/web_programming/world_covid19_stats.py b/web_programming/world_covid19_stats.py index 1dd1ff6d1..ca81abdc4 100644 --- a/web_programming/world_covid19_stats.py +++ b/web_programming/world_covid19_stats.py @@ -22,6 +22,5 @@ def world_covid19_stats(url: str = "https://www.worldometers.info/coronavirus") if __name__ == "__main__": - print("\033[1m" + "COVID-19 Status of the World" + "\033[0m\n") - for key, value in world_covid19_stats().items(): - print(f"{key}\n{value}\n") + print("\033[1m COVID-19 Status of the World \033[0m\n") + print("\n".join(f"{key}\n{value}" for key, value in world_covid19_stats().items()))