使用os_sys lib:

我在许多类型的条形图中使用它，例如:

from os_sys.progress import bar as Bar
bar = Bar('progresing: ', max=20)
for i in range(20):
    #do somthing
    bar.next()
bar.finish()

你的输出将是:

procesing:  |######                          | 2/10

请在os_sys的描述中阅读更多信息

这里有一个非常简单的版本，如果你有一个循环，只是想了解迭代的进展，比如每一个点，比如说，5000次迭代。

my_list = range(0,100000)

counter = 0
for x in my_list:
    #your code here

    counter = counter + 1
    if counter % 5000 == 0:
        print(".", end="") # end="" avoids a newline, keeps dots together

print() #this makes sure whatever you print next is in a new line

My_list不是方案的一部分。使用你自己的迭代对象，不管你在循环什么。 这个版本没有提前告诉您总共有多少次迭代。

我想我有点晚了，但这应该适用于使用当前版本的python 3的人，因为这使用了“f-strings”，正如python 3.6 PEP 498中介绍的那样:

Code

from numpy import interp

class Progress:
    def __init__(self, value, end, title='Downloading',buffer=20):
        self.title = title
        #when calling in a for loop it doesn't include the last number
        self.end = end -1
        self.buffer = buffer
        self.value = value
        self.progress()

    def progress(self):
        maped = int(interp(self.value, [0, self.end], [0, self.buffer]))
        print(f'{self.title}: [{"#"*maped}{"-"*(self.buffer - maped)}]{self.value}/{self.end} {((self.value/self.end)*100):.2f}%', end='\r')

例子

#some loop that does perfroms a task
for x in range(21)  #set to 21 to include until 20
    Progress(x, 21)

输出

Downloading: [########------------] 8/20 40.00%

iterrows的Progressbar。调整了@eusoubrasileiro代码，用于在循环遍历数据帧的行时显示进度。此外还显示百分比、ith/count、经过秒数、eps /sec、剩余秒数。允许指定第n个更新计数。

import time
import sys
def progressbar_iterrows(df, prefix="", size=60, file=sys.stdout, per=1000):
    count = len(df)
    t = 0
    def show(j,elapsed):
        avg = 0 if elapsed == 0 else j/elapsed
        remaining = 0 if avg == 0 else (count-j)/avg
        x = int(size*j/count)
        file.write("%s[%s%s] %i%% %i/%i elapsed:%i %i/sec remaining:%i\r" % (prefix, "#"*x, "."*(size-x), j/count, j, count, elapsed, avg, remaining))
        file.flush()
    file.write("Initializing ...\r")
    file.flush()
    for i, item in df.iterrows():
        yield i,item
        if t == 0:
            t = time.time()
        if i % per == 0:
            show(i,time.time()-t)
    file.write("\n")
    file.flush()

用法:

    for n,r in progressbar_iterrows(br_b_sections_df, "Processed: "):
        # do something

输出:

Processed: [........................] 0% 5000/28751240 elapsed:12 413/sec remaining:55054

这个进度条显示了每完成2%的点和每完成10%的数字。

import sys

def ProgressBar (num, total, nextPercent, nextPoint):
    num = float (num)
    total = float (total) - 1
    if not nextPoint:
        nextPoint = 0.0
    if not nextPercent:
        nextPoint += 2.0
        sys.stdout.write ("[0%")
        nextPercent = 10
    elif num == total:
        sys.stdout.write ("100%]\n")
        nextPercent += 10
    elif not nextPoint:
        nextPoint = 0.0
    elif num / total * 100 >= nextPercent:
        sys.stdout.write (str(int (nextPercent)) + "%")
        nextPercent += 10
    elif num / total * 100 >= nextPoint:
        sys.stdout.write (":")
        nextPoint += 2
    return (nextPercent, nextPoint)

nextPercent, nextPoint = 0, 0
total = 1000

for num in range (total):
    nextPercent, nextPoint = ProgressBar (num, total, nextPercent, nextPoint)

结果:

>>> 
[0%::::10%:::::20%:::::30%:::::40%:::::50%:::::60%:::::70%:::::80%:::::90%:::::100%]
>>> 

当在jupyter笔记本上运行时，使用普通的tqdm无法工作，因为它将输出写在多行上。用这个代替:

import time
from tqdm import tqdm_notebook as tqdm

for i in tqdm(range(100))
    time.sleep(0.5)