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这篇文章将为大家详细讲解有关如何在python中使用Tqdm模块，文章内容质量较高，因此小编分享给大家做个参考，希望大家阅读完这篇文章后对相关知识有一定的了解。
Tqdm 是一个快速，可扩展的Python进度条，可以在 Python 长循环中添加一个进度提示信息，用户只需要封装任意的迭代器 tqdm(iterator)。
我的系统是window环境，首先安装python，接下来就是pip。
pip安装：
在python根目录下创建一个get-pip.py的文件，内容：
https://bootstrap.pypa.io/get-pip.py
然后在CMD窗口进入python下面：
输出：
python -m pip install -U pip
由于Tqdm要求的pip版本是9.0所以需要手动安装pip9.0
http://pypi.python.org/pypi/pip
下载安装包9.0
然后解压进入，CMD窗口输入：python setup.py install
然后就可以安装Tqdm了，
pip install tqdm
安装最新的开发版的话
pip install -e git+https://github.com/tqdm/tqdm.git@master#egg=tqdm
最后看看怎么用呢？https://pypi.python.org/pypi/tqdm
基本用法：
from tqdm import tqdm for i in tqdm(range(10000)): sleep(0.01)
当然除了tqdm，还有trange,使用方式完全相同
for i in trange(100): sleep(0.1)
只要传入list都可以：
pbar = tqdm(["a", "b", "c", "d"])
for char in pbar:
pbar.set_description("Processing %s" % char)也可以手动控制更新
with tqdm(total=100) as pbar: for i in range(10): pbar.update(10)
也可以这样：
pbar = tqdm(total=100) for i in range(10): pbar.update(10) pbar.close()
在Shell的tqdm用法
统计所有python脚本的行数：
$ time find . -name '*.py' -exec cat \{} \; | wc -l
857365
real 0m3.458s
user 0m0.274s
sys 0m3.325s
$ time find . -name '*.py' -exec cat \{} \; | tqdm | wc -l
857366it [00:03, 246471.31it/s]
857365
real 0m3.585s
user 0m0.862s
sys 0m3.358s使用参数：
$ find . -name '*.py' -exec cat \{} \; |
tqdm --unit loc --unit_scale --total 857366 >> /dev/null
100%|███████████████████████████████████| 857K/857K [00:04<00:00, 246Kloc/s]备份一个目录：
$ 7z a -bd -r backup.7z docs/ | grep Compressing | tqdm --total $(find docs/ -type f | wc -l) --unit files >> backup.log 100%|███████████████████████████████▉| 8014/8014 [01:37<00:00, 82.29files/s]
通过看示范的代码，我们能发现使用的核心是tqdm和trange这两个函数，从代码层面分析tqdm的功能，那首先是init.py
__all__ = ['tqdm', 'tqdm_gui', 'trange', 'tgrange', 'tqdm_pandas', 'tqdm_notebook', 'tnrange', 'main', 'TqdmKeyError', 'TqdmTypeError', '__version__']
跟踪到_tqdm.py，能看到tqdm类的声明，首先是初始化
def __init__(self, iterable=None, desc=None, total=None, leave=True, file=sys.stderr, ncols=None, mininterval=0.1, maxinterval=10.0, miniters=None, ascii=None, disable=False, unit='it', unit_scale=False, dynamic_ncols=False, smoothing=0.3, bar_format=None, initial=0, position=None, gui=False, **kwargs):
Parameters
iterable : iterable, optional
Iterable to decorate with a progressbar.
可迭代的进度条。
Leave blank to manually manage the updates.
留空手动管理更新？？
desc : str, optional
Prefix for the progressbar.
进度条的描述
total : int, optional
The number of expected iterations. If unspecified,
len(iterable) is used if possible. As a last resort, only basic
progress statistics are displayed (no ETA, no progressbar).
If gui is True and this parameter needs subsequent updating,
specify an initial arbitrary large positive integer,
e.g. int(9e9).
预期的迭代数目，默认为None，则尽可能的迭代下去，如果gui设置为True，这里则需要后续的更新，将需要指定为一个初始随意值较大的正整数，例如int(9e9)
leave : bool, optional
If [default: True], keeps all traces of the progressbar
upon termination of iteration.
保留进度条存在的痕迹，简单来说就是会把进度条的最终形态保留下来，默认为True
file : io.TextIOWrapper or io.StringIO, optional
Specifies where to output the progress messages
[default: sys.stderr]. Uses file.write(str) and file.flush()
methods.
指定消息的输出
ncols : int, optional
The width of the entire output message. If specified,
dynamically resizes the progressbar to stay within this bound.
If unspecified, attempts to use environment width. The
fallback is a meter width of 10 and no limit for the counter and
statistics. If 0, will not print any meter (only stats).
整个输出消息的宽度。如果指定，动态调整的进度停留在这个边界。如果未指定，尝试使用环境的宽度。如果为0，将不打印任何东西（只统计）。
mininterval : float, optional
Minimum progress update interval, in seconds [default: 0.1].
最小进度更新间隔，以秒为单位（默认值：0.1）。
maxinterval : float, optional
Maximum progress update interval, in seconds [default: 10.0].
最大进度更新间隔，以秒为单位（默认值：10）。
miniters : int, optional
Minimum progress update interval, in iterations.
If specified, will set mininterval to 0.
最小进度更新周期
ascii : bool, optional
If unspecified or False, use unicode (smooth blocks) to fill
the meter. The fallback is to use ASCII characters 1-9 #.
如果不设置，默认为unicode编码
disable : bool, optional
Whether to disable the entire progressbar wrapper
[default: False].
是否禁用整个进度条包装(如果为True，进度条不显示)
unit : str, optional
String that will be used to define the unit of each iteration
[default: it].
将被用来定义每个单元的字符串？？？
unit_scale : bool, optional
If set, the number of iterations will be reduced/scaled
automatically and a metric prefix following the
International System of Units standard will be added
(kilo, mega, etc.) [default: False].
如果设置，迭代的次数会自动按照十、百、千来添加前缀，默认为false
dynamic_ncols : bool, optional
If set, constantly alters ncols to the environment (allowing
for window resizes) [default: False].
不断改变ncols环境，允许调整窗口大小
smoothing : float, optional
Exponential moving average smoothing factor for speed estimates
(ignored in GUI mode). Ranges from 0 (average speed) to 1
(current/instantaneous speed) [default: 0.3].
bar_format : str, optional
Specify a custom bar string formatting. May impact performance.
If unspecified, will use ‘{l_bar}{bar}{r_bar}', where l_bar is
‘{desc}{percentage:3.0f}%|' and r_bar is
‘| {n_fmt}/{total_fmt} [{elapsed_str}<{remaining_str}, {rate_fmt}]'
Possible vars: bar, n, n_fmt, total, total_fmt, percentage,
rate, rate_fmt, elapsed, remaining, l_bar, r_bar, desc.
自定义栏字符串格式化…默认会使用{l_bar}{bar}{r_bar}的格式，格式同上
initial : int, optional
The initial counter value. Useful when restarting a progress
bar [default: 0].
初始计数器值，默认为0
position : int, optional
Specify the line offset to print this bar (starting from 0)
Automatic if unspecified.
Useful to manage multiple bars at once (eg, from threads).
指定偏移，这个功能在多个条中有用
gui : bool, optional
WARNING: internal parameter - do not use.
Use tqdm_gui(…) instead. If set, will attempt to use
matplotlib animations for a graphical output [default: False].
内部参数…
Returns
out : decorated iterator.
返回为一个迭代器其实不用分析更多代码，多看看几个例子：(官网的例子)
7zx.py压缩进度条
# -*- coding: utf-8 -*-
"""Usage:
7zx.py [--help | options] <zipfiles>...
Options:
-h, --help Print this help and exit
-v, --version Print version and exit
-c, --compressed Use compressed (instead of uncompressed) file sizes
-s, --silent Do not print one row per zip file
-y, --yes Assume yes to all queries (for extraction)
-D=<level>, --debug=<level>
Print various types of debugging information. Choices:
CRITICAL|FATAL
ERROR
WARN(ING)
[default: INFO]
DEBUG
NOTSET
-d, --debug-trace Print lots of debugging information (-D NOTSET)
"""
from __future__ import print_function
from docopt import docopt
import logging as log
import subprocess
import re
from tqdm import tqdm
import pty
import os
import io
__author__ = "Casper da Costa-Luis <casper.dcl@physics.org>"
__licence__ = "MPLv2.0"
__version__ = "0.2.0"
__license__ = __licence__
RE_SCN = re.compile("([0-9]+)\s+([0-9]+)\s+(.*)$", flags=re.M)
def main():
args = docopt(__doc__, version=__version__)
if args.pop('--debug-trace', False):
args['--debug'] = "NOTSET"
log.basicConfig(level=getattr(log, args['--debug'], log.INFO),
format='%(levelname)s: %(message)s')
log.debug(args)
# Get compressed sizes
zips = {}
for fn in args['<zipfiles>']:
info = subprocess.check_output(["7z", "l", fn]).strip()
finfo = RE_SCN.findall(info)
# builtin test: last line should be total sizes
log.debug(finfo)
totals = map(int, finfo[-1][:2])
# log.debug(totals)
for s in range(2):
assert(sum(map(int, (inf[s] for inf in finfo[:-1]))) == totals[s])
fcomp = dict((n, int(c if args['--compressed'] else u))
for (u, c, n) in finfo[:-1])
# log.debug(fcomp)
# zips : {'zipname' : {'filename' : int(size)}}
zips[fn] = fcomp
# Extract
cmd7zx = ["7z", "x", "-bd"]
if args['--yes']:
cmd7zx += ["-y"]
log.info("Extracting from {:d} file(s)".format(len(zips)))
with tqdm(total=sum(sum(fcomp.values()) for fcomp in zips.values()),
unit="B", unit_scale=True) as tall:
for fn, fcomp in zips.items():
md, sd = pty.openpty()
ex = subprocess.Popen(cmd7zx + [fn],
bufsize=1,
stdout=md, # subprocess.PIPE,
stderr=subprocess.STDOUT)
os.close(sd)
with io.open(md, mode="rU", buffering=1) as m:
with tqdm(total=sum(fcomp.values()), disable=len(zips) < 2,
leave=False, unit="B", unit_scale=True) as t:
while True:
try:
l_raw = m.readline()
except IOError:
break
l = l_raw.strip()
if l.startswith("Extracting"):
exname = l.lstrip("Extracting").lstrip()
s = fcomp.get(exname, 0) # 0 is likely folders
t.update(s)
tall.update(s)
elif l:
if not any(l.startswith(i) for i in
("7-Zip ",
"p7zip Version ",
"Everything is Ok",
"Folders: ",
"Files: ",
"Size: ",
"Compressed: ")):
if l.startswith("Processing archive: "):
if not args['--silent']:
t.write(t.format_interval(
t.start_t - tall.start_t) + ' ' +
l.lstrip("Processing archive: "))
else:
t.write(l)
ex.wait()
main.__doc__ = __doc__
if __name__ == "__main__":
main()tqdm_wget.py
"""An example of wrapping manual tqdm updates for urllib reporthook.
# urllib.urlretrieve documentation
> If present, the hook function will be called once
> on establishment of the network connection and once after each block read
> thereafter. The hook will be passed three arguments; a count of blocks
> transferred so far, a block size in bytes, and the total size of the file.
Usage:
tqdm_wget.py [options]
Options:
-h, --help
Print this help message and exit
-u URL, --url URL : string, optional
The url to fetch.
[default: http://www.doc.ic.ac.uk/~cod11/matryoshka.zip]
-o FILE, --output FILE : string, optional
The local file path in which to save the url [default: /dev/null].
"""
import urllib
from tqdm import tqdm
from docopt import docopt
def my_hook(t):
"""
Wraps tqdm instance. Don't forget to close() or __exit__()
the tqdm instance once you're done with it (easiest using `with` syntax).
Example
-------
>>> with tqdm(...) as t:
... reporthook = my_hook(t)
... urllib.urlretrieve(..., reporthook=reporthook)
"""
last_b = [0]
def inner(b=1, bsize=1, tsize=None):
"""
b : int, optional
Number of blocks just transferred [default: 1].
bsize : int, optional
Size of each block (in tqdm units) [default: 1].
tsize : int, optional
Total size (in tqdm units). If [default: None] remains unchanged.
"""
if tsize is not None:
t.total = tsize
t.update((b - last_b[0]) * bsize)
last_b[0] = b
return inner
opts = docopt(__doc__)
eg_link = opts['--url']
eg_file = eg_link.replace('/', ' ').split()[-1]
with tqdm(unit='B', unit_scale=True, leave=True, miniters=1,
desc=eg_file) as t: # all optional kwargs
urllib.urlretrieve(eg_link, filename=opts['--output'],
reporthook=my_hook(t), data=None)examples.py
"""
# Simple tqdm examples and profiling
# Benchmark
for i in _range(int(1e8)):
pass
# Basic demo
import tqdm
for i in tqdm.trange(int(1e8)):
pass
# Some decorations
import tqdm
for i in tqdm.trange(int(1e8), miniters=int(1e6), ascii=True,
desc="cool", dynamic_ncols=True):
pass
# Nested bars
from tqdm import trange
for i in trange(10):
for j in trange(int(1e7), leave=False, unit_scale=True):
pass
# Experimental GUI demo
import tqdm
for i in tqdm.tgrange(int(1e8)):
pass
# Comparison to https://code.google.com/p/python-progressbar/
try:
from progressbar.progressbar import ProgressBar
except ImportError:
pass
else:
for i in ProgressBar()(_range(int(1e8))):
pass
# Dynamic miniters benchmark
from tqdm import trange
for i in trange(int(1e8), miniters=None, mininterval=0.1, smoothing=0):
pass
# Fixed miniters benchmark
from tqdm import trange
for i in trange(int(1e8), miniters=4500000, mininterval=0.1, smoothing=0):
pass
"""
from time import sleep
from timeit import timeit
import re
# Simple demo
from tqdm import trange
for i in trange(16, leave=True):
sleep(0.1)
# Profiling/overhead tests
stmts = filter(None, re.split(r'\n\s*#.*?\n', __doc__))
for s in stmts:
print(s.replace('import tqdm\n', ''))
print(timeit(stmt='try:\n\t_range = xrange'
'\nexcept:\n\t_range = range\n' + s, number=1),
'seconds')pandas_progress_apply.py
import pandas as pd import numpy as np from tqdm import tqdm df = pd.DataFrame(np.random.randint(0, 100, (100000, 6))) # Register `pandas.progress_apply` and `pandas.Series.map_apply` with `tqdm` # (can use `tqdm_gui`, `tqdm_notebook`, optional kwargs, etc.) tqdm.pandas(desc="my bar!") # Now you can use `progress_apply` instead of `apply` # and `progress_map` instead of `map` df.progress_apply(lambda x: x**2) # can also groupby: # df.groupby(0).progress_apply(lambda x: x**2) # -- Source code for `tqdm_pandas` (really simple!) # def tqdm_pandas(t): # from pandas.core.frame import DataFrame # def inner(df, func, *args, **kwargs): # t.total = groups.size // len(groups) # def wrapper(*args, **kwargs): # t.update(1) # return func(*args, **kwargs) # result = df.apply(wrapper, *args, **kwargs) # t.close() # return result # DataFrame.progress_apply = inner
引用tqdm并非强制作为依赖：
include_no_requirements.py
# How to import tqdm without enforcing it as a dependency
try:
from tqdm import tqdm
except ImportError:
def tqdm(*args, **kwargs):
if args:
return args[0]
return kwargs.get('iterable', None)关于如何在python中使用Tqdm模块就分享到这里了，希望以上内容可以对大家有一定的帮助，可以学到更多知识。如果觉得文章不错，可以把它分享出去让更多的人看到。
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