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這篇文章將為大家詳細講解有關如何在python中使用Tqdm模塊,文章內容質量較高,因此小編分享給大家做個參考,希望大家閱讀完這篇文章后對相關知識有一定的了解。
Tqdm 是一個快速,可擴展的Python進度條,可以在 Python 長循環中添加一個進度提示信息,用戶只需要封裝任意的迭代器 tqdm(iterator)。
我的系統是window環境,首先安裝python,接下來就是pip。
pip安裝:
在python根目錄下創建一個get-pip.py的文件,內容:
https://bootstrap.pypa.io/get-pip.py
然后在CMD窗口進入python下面:
輸出:
python -m pip install -U pip
由于Tqdm要求的pip版本是9.0所以需要手動安裝pip9.0
http://pypi.python.org/pypi/pip
下載安裝包9.0
然后解壓進入,CMD窗口輸入:python setup.py install
然后就可以安裝Tqdm了,
pip install tqdm
安裝最新的開發版的話
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)
當然除了tqdm,還有trange,使用方式完全相同
for i in trange(100): sleep(0.1)
只要傳入list都可以:
pbar = tqdm(["a", "b", "c", "d"]) for char in pbar: pbar.set_description("Processing %s" % char)
也可以手動控制更新
with tqdm(total=100) as pbar: for i in range(10): pbar.update(10)
也可以這樣:
pbar = tqdm(total=100) for i in range(10): pbar.update(10) pbar.close()
在Shell的tqdm用法
統計所有python腳本的行數:
$ 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
使用參數:
$ find . -name '*.py' -exec cat \{} \; | tqdm --unit loc --unit_scale --total 857366 >> /dev/null 100%|███████████████████████████████████| 857K/857K [00:04<00:00, 246Kloc/s]
備份一個目錄:
$ 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]
通過看示范的代碼,我們能發現使用的核心是tqdm和trange這兩個函數,從代碼層面分析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__']
跟蹤到_tqdm.py,能看到tqdm類的聲明,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. 可迭代的進度條。 Leave blank to manually manage the updates. 留空手動管理更新?? desc : str, optional Prefix for the progressbar. 進度條的描述 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). 預期的迭代數目,默認為None,則盡可能的迭代下去,如果gui設置為True,這里則需要后續的更新,將需要指定為一個初始隨意值較大的正整數,例如int(9e9) leave : bool, optional If [default: True], keeps all traces of the progressbar upon termination of iteration. 保留進度條存在的痕跡,簡單來說就是會把進度條的最終形態保留下來,默認為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. 指定消息的輸出 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). 整個輸出消息的寬度。如果指定,動態調整的進度停留在這個邊界。如果未指定,嘗試使用環境的寬度。如果為0,將不打印任何東西(只統計)。 mininterval : float, optional Minimum progress update interval, in seconds [default: 0.1]. 最小進度更新間隔,以秒為單位(默認值:0.1)。 maxinterval : float, optional Maximum progress update interval, in seconds [default: 10.0]. 最大進度更新間隔,以秒為單位(默認值:10)。 miniters : int, optional Minimum progress update interval, in iterations. If specified, will set mininterval to 0. 最小進度更新周期 ascii : bool, optional If unspecified or False, use unicode (smooth blocks) to fill the meter. The fallback is to use ASCII characters 1-9 #. 如果不設置,默認為unicode編碼 disable : bool, optional Whether to disable the entire progressbar wrapper [default: False]. 是否禁用整個進度條包裝(如果為True,進度條不顯示) unit : str, optional String that will be used to define the unit of each iteration [default: it]. 將被用來定義每個單元的字符串??? 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]. 如果設置,迭代的次數會自動按照十、百、千來添加前綴,默認為false dynamic_ncols : bool, optional If set, constantly alters ncols to the environment (allowing for window resizes) [default: False]. 不斷改變ncols環境,允許調整窗口大小 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. 自定義欄字符串格式化…默認會使用{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]. 初始計數器值,默認為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,這個功能在多個條中有用 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]. 內部參數… Returns out : decorated iterator. 返回為一個迭代器
其實不用分析更多代碼,多看看幾個例子:(官網的例子)
7zx.py壓縮進度條
# -*- 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并非強制作為依賴:
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)
關于如何在python中使用Tqdm模塊就分享到這里了,希望以上內容可以對大家有一定的幫助,可以學到更多知識。如果覺得文章不錯,可以把它分享出去讓更多的人看到。
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