004.01 不同 Python 資料型別的搜尋

Jason990420發表於2019-12-08
Python資料型別

建檔日期: 2019/12/08

更新日期: None

相關軟體資訊:

Win 10 Python 3.7.2

說明：所有內容歡迎引用，只需註明來源及作者，本文內容如有錯誤或用詞不當，敬請指正.

主題: 004.01 不同Python資料型別的搜尋

最近在作資料搜尋比對的案子的時候, 發現大量的資料在搜尋比對時, 速度變的非常慢, 慢到完全無法接受, 我想要的是’立即’有結果, 結果卻是要等好幾小時, 暈 ! 雖然以Python來說, 肯定比不上C或Assembly語言, 但是還是要想辦法提升一下速度. 以下是在一萬筆資料中, 找一萬筆資料的各種方法以及所需的時間, 雖然最後一個方法index_list_sort(), 速度快了多, 但是我還是覺得不夠快, 而且這裡還只是整數的搜尋, 如果是字串呢? 如果是副字串呢? 各位如果有更好的方法, 也請提示, 謝謝 !

結果:

0:00:04.734338 : index_sequence
0:00:01.139984 : index_list
0:00:00.330116 : index_np
0:00:00.233343 : index_np_sort
0:00:00.223401 : index_dict
0:00:00.213462 : index_set
0:00:00.007977 : index_list_sort

程式碼:

from datetime import datetime
import numpy as np
import bisect
import time
import random
import inspect
import copy

size        = 10000
value       = size-1
db          = random.sample(range(size), size)
db_sort     = copy.deepcopy(db)
db_sort.sort()
db_set      = set(db)
db_dict     = {db[i]:i for i in range(size)}
db_np       = np.array(db)
value       = [i for i in range(size)]

def call(func):
    # Call function and calculate execution time, then print duration and function name
    start_time = datetime.now()
    func()
    print(datetime.now() - start_time,':',func.__name__)

def do_something():
    # Do something here, it may get duration different when multi-loop method used
    for i in range(1000):
        pass

def index_sequence():
    # List unsort and just by Python without any method used or built-in function.
    for i in range(size):
        for j in range(size):
            if value[j] == db[i]:
                index = j
                do_something()
                break

def index_list():
    # Unsorted list, use list.index()
    for i in range(size):
        try:
            index = db.index(value[i])
        except:
            index = -1
        if index >= 0:
            do_something()
def index_np():
    # By using numpy and np(where)
    for i in range(size):
        result = np.where(db_np==value[i])
        if len(result[0])!=0:
            do_something()

def index_np_sort():
    # By using numpy and sorted numpy array
    for i in range(size):
        result = np.searchsorted(db_np, value[i])
        if result != size:
            do_something()

def index_list_sort():
    # By using bisect library
    for i in range(size):
        index = bisect.bisect_left(db, value[i])
        if index < size-1 and value[index]==db[index]:
            do_something()

def index_set():
    # Set serach
    for i in range(size):
        if value[i] in db_set:
            do_something()

def index_dict():
    # Dictionary search
    for i in range(size):
        try:
            index = db_dict[value[i]]
        except:
            index = -1
        if index >= 0:
            do_something()
# Test execution time
call(index_sequence)
call(index_list)
call(index_np)
call(index_np_sort)
call(index_dict)
call(index_set)
call(index_list_sort)
本作品採用《CC 協議》，轉載必須註明作者和本文連結
Jason Yang

相關文章