tqdm
Fast, Extensible Progress Meter
Fast, Extensible Progress Meter
To install this package, run one of the following:
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tqdm means "progress" in Arabic (taqadum, )
and an abbreviation for "I love you so much" in Spanish (te quiero demasiado).
Instantly make your loops show a smart progress meter - just wrap any
iterable with tqdm(iterable), and you're done!
.. code:: python
from tqdm import tqdm
for i in tqdm(range(10000)):
...
76%| | 7568/10000 [00:33<00:10, 229.00it/s]
trange(N) can be also used as a convenient shortcut for
tqdm(xrange(N)).
|Screenshot|
REPL: ptpython <https://github.com/jonathanslenders/ptpython>__
It can also be executed as a module with pipes:
.. code:: sh
$ seq 9999999 | tqdm --unit_scale | wc -l
10.0Mit [00:02, 3.58Mit/s]
9999999
$ 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]
Overhead is low -- about 60ns per iteration (80ns with tqdm_gui), and is
unit tested against performance regression.
By comparison, the well established
ProgressBar <https://github.com/niltonvolpato/python-progressbar>__ has
an 800ns/iter overhead.
In addition to its low overhead, tqdm uses smart algorithms to predict
the remaining time and to skip unnecessary iteration displays, which allows
for a negligible overhead in most cases.
tqdm works on any platform (Linux, Windows, Mac, FreeBSD, Solaris/SunOS),
in any console or in a GUI, and is also friendly with IPython/Jupyter notebooks.
tqdm does not require any library (not even curses!) to run, just a
vanilla Python interpreter will do and an environment supporting carriage
return \r and line feed \n control characters.
.. contents:: Table of contents :backlinks: top :local:
Latest PyPI stable release ~~~~~~~~~~~~~~~~~~~~~~~~~~
|PyPI-Status|
.. code:: sh
pip install tqdm
Latest development release on github ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
|GitHub-Status| |GitHub-Stars| |GitHub-Forks|
Pull and install in the current directory:
.. code:: sh
pip install -e git+https://github.com/tqdm/tqdm.git@master#egg=tqdm
Latest Conda release ~~~~~~~~~~~~~~~~~~~~
|Conda-Forge-Status|
.. code:: sh
conda install -c conda-forge tqdm
The list of all changes is available either on GitHub's Releases:
|GitHub-Status| or on crawlers such as
allmychanges.com <https://allmychanges.com/p/python/tqdm/>_.
tqdm is very versatile and can be used in a number of ways.
The three main ones are given below.
Iterable-based ~~~~~~~~~~~~~~
Wrap tqdm() around any iterable:
.. code:: python
text = ""
for char in tqdm(["a", "b", "c", "d"]):
text = text + char
trange(i) is a special optimised instance of tqdm(range(i)):
.. code:: python
for i in trange(100):
pass
Instantiation outside of the loop allows for manual control over tqdm():
.. code:: python
pbar = tqdm(["a", "b", "c", "d"])
for char in pbar:
pbar.set_description("Processing %s" % char)
Manual ~~~~~~
Manual control on tqdm() updates by using a with statement:
.. code:: python
with tqdm(total=100) as pbar:
for i in range(10):
pbar.update(10)
If the optional variable total (or an iterable with len()) is
provided, predictive stats are displayed.
with is also optional (you can just assign tqdm() to a variable,
but in this case don't forget to del or close() at the end:
.. code:: python
pbar = tqdm(total=100)
for i in range(10):
pbar.update(10)
pbar.close()
Module ~~~~~~
Perhaps the most wonderful use of tqdm is in a script or on the command
line. Simply inserting tqdm (or python -m tqdm) between pipes will pass
through all stdin to stdout while printing progress to stderr.
The example below demonstrated counting the number of lines in all python files in the current directory, with timing information included.
.. code:: sh
$ 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
Note that the usual arguments for tqdm can also be specified.
.. code:: sh
$ find . -name '*.py' -exec cat \{} \; |
tqdm --unit loc --unit_scale --total 857366 >> /dev/null
100%|| 857K/857K [00:04<00:00, 246Kloc/s]
Backing up a large directory?
.. code:: sh
$ 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]
The most common issues relate to excessive output on multiple lines, instead of a neat one-line progress bar.
CR, \r).IDLE <https://github.com/tqdm/tqdm/issues/191#issuecomment-230168030>,
ConEmu <https://github.com/tqdm/tqdm/issues/254> and
PyCharm <https://github.com/tqdm/tqdm/issues/203>_ (also
here <https://github.com/tqdm/tqdm/issues/208>_ and
here <https://github.com/tqdm/tqdm/issues/307>__)
lack full support.colorama.enumerate(tqdm(...)) instead of
tqdm(enumerate(...))`. The same applies tonumpy.ndenumerate.
This is because enumerate functions tend to hide the length of iterables.
tqdm`` does not.tqdm(zip(a, b)) should be replaced with zip(tqdm(a), b) or even
zip(tqdm(a), tqdm(b))If you come across any other difficulties, browse/open issues
here <https://github.com/tqdm/tqdm/issues?q=is%3Aissue>__.
|PyPI-Versions| |README-Hits| (Since 19 May 2016)
.. code:: python
class tqdm(object):
"""
Decorate an iterable object, returning an iterator which acts exactly
like the original iterable, but prints a dynamically updating
progressbar every time a value is requested.
"""
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,
postfix=None):
Parameters ~~~~~~~~~~
gui is True and this parameter needs subsequent updating,
specify an initial arbitrary large positive integer,
e.g. int(9e9).io.TextIOWrapper or io.StringIO, optionalfile.write(str) and file.flush()
methods.miniters to correspond to mininterval
after long display update lag. Only works if dynamic_miniters
or monitor thread is enabled.dynamic_miniters, will automatically adjust to equal
mininterval (more CPU efficient, good for tight loops).
If > 0, will skip display of specified number of iterations.
Tweak this and mininterval to get very efficient loops.
If your progress is erratic with both fast and slow iterations
(network, skipping items, etc) you should set miniters=1.1-9 #.ncols to the environment (allowing
for window resizes) [default: False].Extra CLI Options ~~~~~~~~~~~~~~~~~
delim is specified.delim.Returns ~~~~~~~
.. code:: python
def update(self, n=1):
"""
Manually update the progress bar, useful for streams
such as reading files.
E.g.:
>>> t = tqdm(total=filesize) # Initialise
>>> for current_buffer in stream:
... ...
... t.update(len(current_buffer))
>>> t.close()
The last line is highly recommended, but possibly not necessary if
``t.update()`` will be called in such a way that ``filesize`` will be
exactly reached and printed.
Parameters
----------
n : int
Increment to add to the internal counter of iterations
[default: 1].
"""
def close(self):
"""
Cleanup and (if leave=False) close the progressbar.
"""
def clear(self):
"""
Clear current bar display
"""
def refresh(self):
"""
Force refresh the display of this bar
"""
def write(cls, s, file=sys.stdout, end="\n"):
"""
Print a message via tqdm (without overlap with bars)
"""
def set_description(self, desc=None):
"""
Set/modify description of the progress bar.
"""
def set_postfix(self, **kwargs):
"""
Set/modify postfix (additional stats)
with automatic formatting based on datatype.
"""
def trange(*args, **kwargs):
"""
A shortcut for tqdm(xrange(*args), **kwargs).
On Python3+ range is used instead of xrange.
"""
class tqdm_gui(tqdm):
"""
Experimental GUI version of tqdm!
"""
def tgrange(*args, **kwargs):
"""
Experimental GUI version of trange!
"""
class tqdm_notebook(tqdm):
"""
Experimental IPython/Jupyter Notebook widget using tqdm!
"""
def tnrange(*args, **kwargs):
"""
Experimental IPython/Jupyter Notebook widget using tqdm!
"""
examples <https://github.com/tqdm/tqdm/tree/master/examples>__
folder;help(), orwiki <https://github.com/tqdm/tqdm/wiki>.
excellent article <https://github.com/tqdm/tqdm/wiki/How-to-make-a-great-Progress-Bar>Description and additional stats ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Custom information can be displayed and updated dynamically on tqdm bars
with the desc and postfix arguments:
.. code:: python
from tqdm import trange
from random import random, randint
from time import sleep
t = trange(100)
for i in t:
# Description will be displayed on the left
t.set_description('GEN %i' % i)
# Postfix will be displayed on the right, and will format automatically
# based on argument's datatype
t.set_postfix(loss=random(), gen=randint(1,999), str='h', lst=[1, 2])
sleep(0.1)
Nested progress bars ~~~~~~~~~~~~~~~~~~~~
tqdm supports nested progress bars. Here's an example:
.. code:: python
from tqdm import trange
from time import sleep
for i in trange(10, desc='1st loop'):
for j in trange(5, desc='2nd loop', leave=False):
for k in trange(100, desc='3nd loop'):
sleep(0.01)
On Windows colorama <https://github.com/tartley/colorama>__ will be used if
available to produce a beautiful nested display.
For manual control over positioning (e.g. for multi-threaded use),
you may specify position=n where n=0 for the outermost bar,
n=1 for the next, and so on.
Hooks and callbacks ~~~~~~~~~~~~~~~~~~~
tqdm can easily support callbacks/hooks and manual updates.
Here's an example with urllib:
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.
| [...]
.. code:: python
import urllib
from tqdm import tqdm
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
eg_link = 'http://www.doc.ic.ac.uk/~cod11/matryoshka.zip'
with tqdm(unit='B', unit_scale=True, miniters=1,
desc=eg_link.split('/')[-1]) as t: # all optional kwargs
urllib.urlretrieve(eg_link, filename='/dev/null',
reporthook=my_hook(t), data=None)
It is recommend to use miniters=1 whenever there is potentially
large differences in iteration speed (e.g. downloading a file over
a patchy connection).
Pandas Integration ~~~~~~~~~~~~~~~~~~
Due to popular demand we've added support for pandas -- here's an example
for DataFrame.progress_apply and DataFrameGroupBy.progress_apply:
.. code:: python
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)
In case you're interested in how this works (and how to modify it for your
own callbacks), see the
examples <https://github.com/tqdm/tqdm/tree/master/examples>__
folder or import the module and run help().
IPython/Jupyter Integration ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
IPython/Jupyter is supported via the tqdm_notebook submodule:
.. code:: python
from tqdm import tnrange, tqdm_notebook
from time import sleep
for i in tnrange(10, desc='1st loop'):
for j in tqdm_notebook(xrange(100), desc='2nd loop'):
sleep(0.01)
In addition to tqdm features, the submodule provides a native Jupyter
widget (compatible with IPython v1-v4 and Jupyter), fully working nested bars
and color hints (blue: normal, green: completed, red: error/interrupt,
light blue: no ETA); as demonstrated below.
|Screenshot-Jupyter1| |Screenshot-Jupyter2| |Screenshot-Jupyter3|
Writing messages ~~~~~~~~~~~~~~~~
Since tqdm uses a simple printing mechanism to display progress bars,
you should not write any message in the terminal using print().
To write messages in the terminal without any collision with tqdm bar
display, a .write() method is provided:
.. code:: python
from tqdm import tqdm, trange
from time import sleep
bar = trange(10)
for i in bar:
# Print using tqdm class method .write()
sleep(0.1)
if not (i % 3):
tqdm.write("Done task %i" % i)
# Can also use bar.write()
By default, this will print to standard output sys.stdout. but you can
specify any file-like object using the file argument. For example, this
can be used to redirect the messages writing to a log file or class.
Redirecting writing ~~~~~~~~~~~~~~~~~~~
If using a library that can print messages to the console, editing the library
by replacing print() with tqdm.write() may not be desirable.
In that case, redirecting sys.stdout to tqdm.write() is an option.
To redirect sys.stdout, create a file-like class that will write
any input string to tqdm.write(), and supply the arguments
file=sys.stdout, dynamic_ncols=True.
A reusable canonical example is given below:
.. code:: python
from time import sleep
import contextlib
import sys
from tqdm import tqdm
class DummyTqdmFile(object):
"""Dummy file-like that will write to tqdm"""
file = None
def __init__(self, file):
self.file = file
def write(self, x):
# Avoid print() second call (useless \n)
if len(x.rstrip()) > 0:
tqdm.write(x, file=self.file)
@contextlib.contextmanager
def stdout_redirect_to_tqdm():
save_stdout = sys.stdout
try:
sys.stdout = DummyTqdmFile(sys.stdout)
yield save_stdout
# Relay exceptions
except Exception as exc:
raise exc
# Always restore sys.stdout if necessary
finally:
sys.stdout = save_stdout
def blabla():
print("Foo blabla")
# Redirect stdout to tqdm.write() (don't forget the `as save_stdout`)
with stdout_redirect_to_tqdm() as save_stdout:
# tqdm call need to specify sys.stdout, not sys.stderr (default)
# and dynamic_ncols=True to autodetect console width
for _ in tqdm(range(3), file=save_stdout, dynamic_ncols=True):
blabla()
sleep(.5)
# After the `with`, printing is restored
print('Done!')
Monitoring thread, intervals and miniters ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
tqdm implements a few tricks to to increase efficiency and reduce overhead.
mininterval defines how long
to wait between each refresh. tqdm always gets updated in the background,
but it will diplay only every mininterval.mininterval is more intuitive to configure than miniters.
A clever adjustment system dynamic_miniters will automatically adjust
miniters to the amount of iterations that fit into time mininterval.
Essentially, tqdm will check if it's time to print without actually
checking time. This behavior can be still be bypassed by manually setting
miniters.However, consider a case with a combination of fast and slow iterations.
After a few fast iterations, dynamic_miniters will set miniters to a
large number. When interation rate subsequently slows, miniters will
remain large and thus reduce display update frequency. To address this:
maxinterval defines the maximum time between display refreshes.
A concurrent monitoring thread checks for overdue updates and forces one
where necessary.The monitoring thread should not have a noticeable overhead, and guarantees
updates at least every 10 seconds by default.
This value can be directly changed by setting the monitor_interval of
any tqdm instance (i.e. t = tqdm.tqdm(...); t.monitor_interval = 2).
The monitor thread may be disabled application-wide by setting
tqdm.tqdm.monitor_interval = 0 before instantiatiation of any tqdm bar.
All source code is hosted on GitHub <https://github.com/tqdm/tqdm>__.
Contributions are welcome.
See the
CONTRIBUTING <https://raw.githubusercontent.com/tqdm/tqdm/master/CONTRIBUTING.md>__
file for more information.
Open Source (OSI approved): |LICENCE|
Citation information: |DOI-URI|
Ranked by contributions.
* Original author
|README-Hits| (Since 19 May 2016)
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Summary
Fast, Extensible Progress Meter
Last Updated
Feb 8, 2017 at 07:14
License
MPLv2.0, MIT Licences
Total Downloads
65