Python实用脚本/算法集合, 附源代码下载|buckets|image|key|python|源代码

学习编程、学习Python最好的方式就是练习，哪怕是新手，只要不断地敲代码输出，肯定会有神效。

Python的练手项目很多，特别是Github上，建议不管新手、老司机都去看看。

这里推荐给大家两个Github上练习的项目， 算法仓库-algorithms和 脚本仓库-Python master。

后文会有相应源代码集打包下载，给需要的小伙伴。

algorithms算法仓库

首先来看看算法仓库-algorithms。

这里面集合众多核心算法的Python实现，比如排序、图计算、回溯、队列、流计算、堆、搜索、压缩等等。

该仓库支持第三方库安装，在python中进行调用，非常方便。

首先使用pip进行安装：

pip3 install algorithms

然后导入相关模块进行调用，比如sort模块里的merge_sort归并排序算法。

from algorithms.sort import merge_sort

if __name__ == "__main__": my_list = [1, 8, 3, 5, 6] my_list = merge_sort(my_list) print(my_list)

个人感觉这个仓库里的算法很齐全，适合做练习，小伙伴们可以试试。

所有算法脚本 已经打包好，获取步骤如下：

1，点击下方公众号 数据STUDIO 名片

2，关注 数据STUDIO后，在消息后台回复 b

▲点击关注「数据STUDIO」回复b

另外，@公众号：数据STUDIO 还为大家整理和筛选了大量火爆全网的Python数据科学学习资料，全部资料按需自助免费获取！直接点击链接：

Python脚本仓库

另外还有一个很好的练手项目，脚本仓库-Python master。

这个项目收集了作者平时工作用到的几千个实用小脚本，作者虽然不是程序员，但他这种用代码解决问题的习惯会极大的提升效率，也会迸发出更多的创新思维。

我觉得这样的代码每个人都可以写出来，只要慢慢积累多练习就可以。

举一个简单的例子，作者写了一个创建二维码的脚本，可以自动将url转化为二维码。

import pyqrcode import png from pyqrcode import QRCode

# Text which is to be converted to QR code print("Enter text to convert") s = input(": ") # Name of QR code png file print("Enter image name to save") n = input(": ") # Adding extension as .pnf d = n + ".png" # Creating QR code url = pyqrcode.create(s) # Saving QR code as a png file url.show() url.png(d, scale=6)

除此之外，该仓库中还有很多这样实用的脚本文件。

所有算法脚本 已经打包好，获取步骤如下：

1，点击下方公众号 数据STUDIO 名片

2，关注 数据STUDIO后，在消息后台回复 d

▲点击关注「数据STUDIO」回复d

另外，@公众号：数据STUDIO 还为大家整理和筛选了大量火爆全网的Python数据科学学习资料，全部资料按需自助免费获取！直接点击链接：

接下来，展示一些更多的代码案例，供大家参考。

从图片中截取文字 # extract text from a img and its coordinates using the pytesseract module import cv2 import pytesseract

# You need to add tesseract binary dependency to system variable for this to work

img = cv2.imread("img.png") # We need to convert the img into RGB format img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

hI, wI, k = img.shape print(pytesseract.image_to_string(img)) boxes = pytesseract.image_to_boxes(img) for b in boxes.splitlines(): b = b.split(" ") x, y, w, h = int(b[1]), int(b[2]), int(b[3]), int(b[4]) cv2.rectangle(img, (x, hI - y), (w, hI - h), (0, 0, 255), 0.2)

cv2.imshow("img", img) cv2.waitKey(0) 判断闰年 def is_leap(year): leap = False if year % 4 == 0: leap = True if year % 100 == 0: leap = False if year % 400 == 0: leap = True return leap

year = int(input("Enter the year here: ")) print(is_leap(year)) 打印图片分辨率 def jpeg_res(filename): """"This function prints the resolution of the jpeg image file passed into it"""

# open image for reading in binary mode with open(filename,'rb') as img_file:

# height of image (in 2 bytes) is at 164th position img_file.seek(163)

# read the 2 bytes a = img_file.read(2)

# calculate height height = (a[0] << 8) + a[1]

# next 2 bytes is width a = img_file.read(2)

# calculate width width = (a[0] << 8) + a[1]

print("The resolution of the image is",width,"x",height)

jpeg_res("img1.jpg") 排序算法-桶排序 def bucket_sort(arr): ''' Bucket Sort Complexity: O(n^2) The complexity is dominated by nextSort ''' # The number of buckets and make buckets num_buckets = len(arr) buckets = [[] for bucket in range(num_buckets)] # Assign values into bucket_sort for value in arr: index = value * num_buckets // (max(arr) + 1) buckets[index].append(value) # Sort sorted_list = [] for i in range(num_buckets): sorted_list.extend(next_sort(buckets[i])) return sorted_list

def next_sort(arr): # We will use insertion sort here. for i in range(1, len(arr)): j = i - 1 key = arr[i] while arr[j] > key and j >= 0: arr[j+1] = arr[j] j = j - 1 arr[j + 1] = key return arr 机器学习-最近邻插值法 import math

def distance(x,y): """[summary] HELPER-FUNCTION calculates the (eulidean) distance between vector x and y.

Arguments: x {[tuple]} -- [vector] y {[tuple]} -- [vector] """ assert len(x) == len(y), "The vector must have same length" result = () sum = 0 for i in range(len(x)): result += (x[i] -y[i],) for component in result: sum += component**2 return math.sqrt(sum)

def nearest_neighbor(x, tSet): """[summary] Implements the nearest neighbor algorithm

Arguments: x {[tupel]} -- [vector] tSet {[dict]} -- [training set]

Returns: [type] -- [result of the AND-function] """ assert isinstance(x, tuple) and isinstance(tSet, dict) current_key = () min_d = float('inf') for key in tSet: d = distance(x, key) if d < min_d: min_d = d current_key = key return tSet[current_key] 符串解码编码 # Implement the encode and decode methods.

def encode(strs): """Encodes a list of strings to a single string. :type strs: List[str] :rtype: str """ res = '' for string in strs.split(): res += str(len(string)) + ":" + string return res

def decode(s): """Decodes a single string to a list of strings. :type s: str :rtype: List[str] """ strs = [] i = 0 while i < len(s): index = s.find(":", i) size = int(s[i:index]) strs.append(s[index+1: index+1+size]) i = index+1+size return strs 直方分布 def get_histogram(input_list: list) -> dict: """ Get histogram representation :param input_list: list with different and unordered values :return histogram: dict with histogram of input_list """ # Create dict to store histogram histogram = {} # For each list value, add one to the respective histogram dict position for i in input_list: histogram[i] = histogram.get(i, 0) + 1 return histogram