|Logo|
|Py-Versions| |Versions| |Conda-Forge-Status| |Docker| |Snapcraft|
|Build-Status| |Coverage-Status| |Branch-Coverage-Status| |Codacy-Grade| |Libraries-Rank| |PyPI-Downloads|
|DOI| |LICENCE| |OpenHub-Status| |binder-demo| |notebook-demo| |awesome-python|
tqdm derives from the Arabic word taqaddum (تقدّم) which can mean "progress,"
and is 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| |Video| |Slides|
It can also be executed as a module with pipes:
.. code:: sh
$ seq 9999999 | tqdm --bytes | wc -l
75.2MB [00:00, 217MB/s]
9999999
$ tar -zcf - docs/ | tqdm --bytes --total `du -sb docs/ | cut -f1` \
> backup.tgz
32%|██████████▍ | 8.89G/27.9G [00:42<01:31, 223MB/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, NetBSD, Solaris/SunOS),
in any console or in a GUI, and is also friendly with IPython/Jupyter notebooks.
tqdm does not require any dependencies (not even curses!), just
Python and an environment supporting carriage return \r and
line feed \n control characters.
.. contents:: Table of contents :backlinks: top :local:
Latest PyPI stable release ~~~~~~~~~~~~~~~~~~~~~~~~~~
|Versions| |PyPI-Downloads| |Libraries-Dependents|
.. code:: sh
pip install tqdm
Latest development release on GitHub ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
|GitHub-Status| |GitHub-Stars| |GitHub-Commits| |GitHub-Forks| |GitHub-Updated|
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
Latest Snapcraft release ~~~~~~~~~~~~~~~~~~~~~~~~
|Snapcraft|
There are 3 channels to choose from:
.. code:: sh
snap install tqdm # implies --stable, i.e. latest tagged release
snap install tqdm --candidate # master branch
snap install tqdm --edge # devel branch
Latest Docker release ~~~~~~~~~~~~~~~~~~~~~
|Docker|
.. code:: sh
docker pull tqdm/tqdm
docker run -i --rm tqdm/tqdm --help
Other ~~~~~
There are other (unofficial) places where tqdm may be downloaded, particularly for CLI use:
|Repology|
.. |Repology| image:: https://repology.org/badge/tiny-repos/python:tqdm.svg :target: https://repology.org/project/python:tqdm/versions
The list of all changes is available either on GitHub's Releases:
|GitHub-Status|, on the
wiki <https://github.com/tqdm/tqdm/wiki/Releases>, on the
website <https://tqdm.github.io/releases/>, 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
from tqdm import tqdm
from time import sleep
text = ""
for char in tqdm(["a", "b", "c", "d"]):
sleep(0.25)
text = text + char
trange(i) is a special optimised instance of tqdm(range(i)):
.. code:: python
from tqdm import trange
for i in trange(100):
sleep(0.01)
Instantiation outside of the loop allows for manual control over tqdm():
.. code:: python
pbar = tqdm(["a", "b", "c", "d"])
for char in pbar:
sleep(0.25)
pbar.set_description("Processing %s" % char)
Manual ~~~~~~
Manual control of tqdm() updates using a with statement:
.. code:: python
with tqdm(total=100) as pbar:
for i in range(10):
sleep(0.1)
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):
sleep(0.1)
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' -type f -exec cat \{} \; | wc -l
857365
real 0m3.458s
user 0m0.274s
sys 0m3.325s
$ time find . -name '*.py' -type f -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' -type f -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
tar -zcf - docs/ | tqdm --bytes --total `du -sb docs/ | cut -f1` \
> backup.tgz
44%|██████████████▊ | 153M/352M [00:14<00:18, 11.0MB/s]
This can be beautified further:
.. code:: sh
BYTES="$(du -sb docs/ | cut -f1)"
tar -cf - docs/ \
| tqdm --bytes --total "$BYTES" --desc Processing | gzip \
| tqdm --bytes --total "$BYTES" --desc Compressed --position 1 \
> ~/backup.tgz
Processing: 100%|██████████████████████| 352M/352M [00:14<00:00, 30.2MB/s]
Compressed: 42%|█████████▎ | 148M/352M [00:14<00:19, 10.9MB/s]
Or done on a file level using 7-zip:
.. code:: sh
7z a -bd -r backup.7z docs/ | grep Compressing \
| tqdm --total $(find docs/ -type f | wc -l) --unit files \
| grep -v Compressing
100%|██████████████████████████▉| 15327/15327 [01:00<00:00, 712.96files/s]
|GitHub-Issues|
The most common issues relate to excessive output on multiple lines, instead of a neat one-line progress bar.
CR, \r).Nested progress bars:
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>,
here <https://github.com/tqdm/tqdm/issues/307>, and
here <https://github.com/tqdm/tqdm/issues/454#issuecomment-335416815>_)
lack full support.colorama
to ensure nested bars stay within their respective lines.Unicode:
ascii-only bar.often require explicit ascii=True <https://github.com/tqdm/tqdm/issues/454#issuecomment-335416815>_
(also here <https://github.com/tqdm/tqdm/issues/499>_). This is due to
either normal-width unicode characters being incorrectly displayed as
"wide", or some unicode characters not rendering.Wrapping generators:
tqdm does not.tqdm(enumerate(...)) with enumerate(tqdm(...)) or
tqdm(enumerate(x), total=len(x), ...).
The same applies to numpy.ndenumerate.tqdm(zip(a, b)) with zip(tqdm(a), b) or even
zip(tqdm(a), tqdm(b)).itertools.tqdm.contrib.Hanging pipes in python2 <https://github.com/tqdm/tqdm/issues/359>__:
when using tqdm on the CLI, you may need to use Python 3.5+ for correct
buffering.
If you come across any other difficulties, browse and file |GitHub-Issues|.
|Py-Versions| |README-Hits| (Since 19 May 2016)
.. code:: python
class tqdm():
"""
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=None, 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, unit_divisor=1000):
Parameters ~~~~~~~~~~
gui is True and this parameter needs subsequent updating,
specify an initial arbitrary large positive number,
e.g. 9e9.None, will leave only if position is 0.io.TextIOWrapper or io.StringIO, optionalfile.write(str) and file.flush()
methods. For encoding, see write_bytes.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.total and n.ncols and nrows to the
environment (allowing for window resizes) [default: False].{n:.3f}
or similar in bar_format, or specifying unit_scale.*, optionalset_postfix(**postfix) if possible (dict).unit_scale is True.file is unspecified,
bytes will be written in Python 2. If True will also write
bytes. In all other cases will default to unicode.refresh for intermediate output
(initialisation, iterating, and updating).Extra CLI Options ~~~~~~~~~~~~~~~~~
delim is specified.delim, and default
unit_scale to True, unit_divisor to 1024, and unit to 'B'.Returns ~~~~~~~
.. code:: python
class tqdm():
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 or float, optional
Increment to add to the internal counter of iterations
[default: 1]. If using float, consider specifying ``{n:.3f}``
or similar in ``bar_format``, or specifying ``unit_scale``.
"""
def close(self):
"""Cleanup and (if leave=False) close the progressbar."""
def clear(self, nomove=False):
"""Clear current bar display."""
def refresh(self):
"""
Force refresh the display of this bar.
Parameters
----------
nolock : bool, optional
If ``True``, does not lock.
If [default: ``False``]: calls ``acquire()`` on internal lock.
lock_args : tuple, optional
Passed to internal lock's ``acquire()``.
If specified, will only ``display()`` if ``acquire()`` returns ``True``.
"""
def unpause(self):
"""Restart tqdm timer from last print time."""
def reset(self, total=None):
"""
Resets to 0 iterations for repeated use.
Consider combining with ``leave=True``.
Parameters
----------
total : int or float, optional. Total to use for the new bar.
"""
def set_description(self, desc=None, refresh=True):
"""
Set/modify description of the progress bar.
Parameters
----------
desc : str, optional
refresh : bool, optional
Forces refresh [default: True].
"""
def set_postfix(self, ordered_dict=None, refresh=True, **kwargs):
"""
Set/modify postfix (additional stats)
with automatic formatting based on datatype.
Parameters
----------
ordered_dict : dict or OrderedDict, optional
refresh : bool, optional
Forces refresh [default: True].
kwargs : dict, optional
"""
@classmethod
def write(cls, s, file=sys.stdout, end="\n"):
"""Print a message via tqdm (without overlap with bars)."""
@property
def format_dict(self):
"""Public API for read-only member access."""
def display(self, msg=None, pos=None):
"""
Use ``self.sp`` to display ``msg`` in the specified ``pos``.
Consider overloading this function when inheriting to use e.g.:
``self.some_frontend(**self.format_dict)`` instead of ``self.sp``.
Parameters
----------
msg : str, optional. What to display (default: ``repr(self)``).
pos : int, optional. Position to ``moveto``
(default: ``abs(self.pos)``).
"""
def trange(*args, **kwargs):
"""
A shortcut for tqdm(xrange(*args), **kwargs).
On Python3+ range is used instead of xrange.
"""
class tqdm.gui.tqdm(tqdm.tqdm):
"""Experimental GUI version"""
def tqdm.gui.trange(*args, **kwargs):
"""Experimental GUI version of trange"""
class tqdm.notebook.tqdm(tqdm.tqdm):
"""Experimental IPython/Jupyter Notebook widget"""
def tqdm.notebook.trange(*args, **kwargs):
"""Experimental IPython/Jupyter Notebook widget version of trange"""
class tqdm.keras.TqdmCallback(keras.callbacks.Callback):
"""`keras` callback for epoch and batch progress"""
def tqdm.contrib.tenumerate(iterable, start=0, total=None,
tqdm_class=tqdm.auto.tqdm, **kwargs):
"""Equivalent of `numpy.ndenumerate` or builtin `enumerate`."""
def tqdm.contrib.tzip(iter1, *iter2plus, **tqdm_kwargs):
"""Equivalent of builtin `zip`."""
def tqdm.contrib.tmap(function, *sequences, **tqdm_kwargs):
"""Equivalent of builtin `map`."""
The tqdm.contrib package also contains experimental modules:
tqdm.contrib.itertools: Thin wrappers around itertoolstqdm.contrib.concurrent: Thin wrappers around concurrent.futuresexamples <https://github.com/tqdm/tqdm/tree/master/examples>__
folder;help();consult the wiki <https://github.com/tqdm/tqdm/wiki>__;
excellent article <https://github.com/tqdm/tqdm/wiki/How-to-make-a-great-Progress-Bar>__
on how to make a great progressbar;check out the slides from PyData London <https://tqdm.github.io/PyData2019/slides.html>__, or
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 tqdm, trange
from random import random, randint
from time import sleep
with trange(10) as t:
for i in t:
# Description will be displayed on the left
t.set_description('GEN %i' % i)
# Postfix will be displayed on the right,
# formatted automatically based on argument's datatype
t.set_postfix(loss=random(), gen=randint(1,999), str='h',
lst=[1, 2])
sleep(0.1)
with tqdm(total=10, bar_format="{postfix[0]} {postfix[1][value]:>8.2g}",
postfix=["Batch", dict(value=0)]) as t:
for i in range(10):
sleep(0.1)
t.postfix[1]["value"] = i / 2
t.update()
Points to remember when using {postfix[...]} in the bar_format string:
postfix also needs to be passed as an initial argument in a compatible
format, andpostfix will be auto-converted to a string if it is a dict-like
object. To prevent this behaviour, insert an extra item into the dictionary
where the key is not a string.Additional bar_format parameters may also be defined by overriding
format_dict, and the bar itself may be modified using ascii:
.. code:: python
from tqdm import tqdm
class TqdmExtraFormat(tqdm):
"""Provides a `total_time` format parameter"""
@property
def format_dict(self):
d = super(TqdmExtraFormat, self).format_dict
total_time = d["elapsed"] * (d["total"] or 0) / max(d["n"], 1)
d.update(total_time=self.format_interval(total_time) + " in total")
return d
for i in TqdmExtraFormat(
range(9), ascii=" .oO0",
bar_format="{total_time}: {percentage:.0f}%|{bar}{r_bar}"):
if i == 4:
break
.. code::
00:00 in total: 44%|0000. | 4/9 [00:00<00:00, 962.93it/s]
Note that {bar} also supports a format specifier [width][type].
width
ncolsint >= 0: fixed width overriding ncols logicint < 0: subtract from the automatic defaulttype
a: ascii (ascii=True override)u: unicode (ascii=False override)b: blank (ascii=" " override)This means a fixed bar with right-justified text may be created by using:
bar_format="{l_bar}{bar:10}|{bar:-10b}right-justified"
Nested progress bars ~~~~~~~~~~~~~~~~~~~~
tqdm supports nested progress bars. Here's an example:
.. code:: python
from tqdm.auto import trange
from time import sleep
for i in trange(4, desc='1st loop'):
for j in trange(5, desc='2nd loop'):
for k in trange(50, desc='3rd loop', leave=False):
sleep(0.01)
On Windows colorama <https://github.com/tartley/colorama>__ will be used if
available to keep nested bars on their respective lines.
For manual control over positioning (e.g. for multi-processing use),
you may specify position=n where n=0 for the outermost bar,
n=1 for the next, and so on.
However, it's best to check if tqdm can work without manual position first.
.. code:: python
from time import sleep
from tqdm import trange, tqdm
from multiprocessing import Pool, freeze_support
L = list(range(9))
def progresser(n):
interval = 0.001 / (n + 2)
total = 5000
text = "#{}, est. {:<04.2}s".format(n, interval * total)
for _ in trange(total, desc=text, position=n):
sleep(interval)
if __name__ == '__main__':
freeze_support() # for Windows support
p = Pool(initializer=tqdm.set_lock, initargs=(tqdm.get_lock(),))
p.map(progresser, L)
Note that in Python 3, tqdm.write is thread-safe:
.. code:: python
from time import sleep
from tqdm import tqdm, trange
from concurrent.futures import ThreadPoolExecutor
L = list(range(9))
def progresser(n):
interval = 0.001 / (n + 2)
total = 5000
text = "#{}, est. {:<04.2}s".format(n, interval * total)
for _ in trange(total, desc=text):
sleep(interval)
if n == 6:
tqdm.write("n == 6 completed.")
tqdm.write("`tqdm.write()` is thread-safe in py3!")
if __name__ == '__main__':
with ThreadPoolExecutor() as p:
p.map(progresser, L)
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, os
from tqdm import tqdm
class TqdmUpTo(tqdm):
"""Provides `update_to(n)` which uses `tqdm.update(delta_n)`."""
def update_to(self, b=1, bsize=1, tsize=None):
"""
b : int, optional
Number of blocks transferred so far [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:
self.total = tsize
self.update(b * bsize - self.n) # will also set self.n = b * bsize
eg_link = "https://caspersci.uk.to/matryoshka.zip"
with TqdmUpTo(unit='B', unit_scale=True, miniters=1,
desc=eg_link.split('/')[-1]) as t: # all optional kwargs
urllib.urlretrieve(eg_link, filename=os.devnull,
reporthook=t.update_to, data=None)
t.total = t.n
Inspired by twine#242 <https://github.com/pypa/twine/pull/242>.
Functional alternative in
examples/tqdm_wget.py <https://github.com/tqdm/tqdm/blob/master/examples/tqdm_wget.py>.
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).
Wrapping read/write methods
To measure throughput through a file-like object's read or write
methods, use CallbackIOWrapper:
.. code:: python
from tqdm.auto import tqdm
from tqdm.utils import CallbackIOWrapper
with tqdm(total=file_obj.size,
unit='B', unit_scale=True, unit_divisor=1024) as t:
fobj = CallbackIOWrapper(t.update, file_obj, "read")
while True:
chunk = fobj.read(chunk_size)
if not chunk:
break
t.reset()
# ... continue to use `t` for something else
Alternatively, use the even simpler wrapattr convenience function,
which would condense both the urllib and CallbackIOWrapper examples
down to:
.. code:: python
import urllib, os
from tqdm import tqdm
eg_link = "https://caspersci.uk.to/matryoshka.zip"
with tqdm.wrapattr(open(os.devnull, "wb"), "write",
miniters=1, desc=eg_link.split('/')[-1]) as fout:
for chunk in urllib.urlopen(eg_link):
fout.write(chunk)
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`, `tqdm.notebook.tqdm`, 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().
Keras Integration ~~~~~~~~~~~~~~~~~
A keras callback is also available:
.. code:: python
from tqdm.keras import TqdmCallback
...
model.fit(..., verbose=0, callbacks=[TqdmCallback()])
IPython/Jupyter Integration ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
IPython/Jupyter is supported via the tqdm.notebook submodule:
.. code:: python
from tqdm.notebook import trange, tqdm
from time import sleep
for i in trange(3, desc='1st loop'):
for j in tqdm(range(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 colour hints (blue: normal, green: completed, red: error/interrupt,
light blue: no ETA); as demonstrated below.
|Screenshot-Jupyter1| |Screenshot-Jupyter2| |Screenshot-Jupyter3|
The notebook version supports percentage or pixels for overall width
(e.g.: ncols='100%' or ncols='480px').
It is also possible to let tqdm automatically choose between
console or notebook versions by using the autonotebook submodule:
.. code:: python
from tqdm.autonotebook import tqdm
tqdm.pandas()
Note that this will issue a TqdmExperimentalWarning if run in a notebook
since it is not meant to be possible to distinguish between jupyter notebook
and jupyter console. Use auto instead of autonotebook to suppress
this warning.
Note that notebooks will display the bar in the cell where it was created. This may be a different cell from the one where it is used. If this is not desired, the creation of the bar must be delayed/moved to the cell where it is desired to be displayed.
Another possibility is to have a single bar (near the top of the notebook)
which is constantly re-used (using reset() rather than close()).
For this reason, the notebook version (unlike the CLI version) does not
automatically call close() upon Exception.
.. code:: python
from tqdm.notebook import tqdm
pbar = tqdm()
.. code:: python
# different cell
iterable = range(100)
pbar.reset(total=len(iterable)) # initialise with new `total`
for i in iterable:
pbar.update()
pbar.refresh() # force print final status but don't `close()`
Custom Integration ~~~~~~~~~~~~~~~~~~
To change the default arguments (such as making dynamic_ncols=True),
simply use built-in Python magic:
.. code:: python
from functools import partial
from tqdm import tqdm as std_tqdm
tqdm = partial(std_tqdm, dynamic_ncols=True)
For further customisation,
tqdm may be inherited from to create custom callbacks (as with the
TqdmUpTo example above <#hooks-and-callbacks>__) or for custom frontends
(e.g. GUIs such as notebook or plotting packages). In the latter case:
def __init__() to call super().__init__(..., gui=True) to disable
terminal status_printer creation.close(), clear(), display().Consider overloading display() to use e.g.
self.frontend(**self.format_dict) instead of self.sp(repr(self)).
tqdm/notebook.py <https://github.com/tqdm/tqdm/blob/master/tqdm/notebook.py>_
and tqdm/gui.py <https://github.com/tqdm/tqdm/blob/master/tqdm/gui.py>_
submodules are examples of inheritance which don't (yet) strictly conform to the
above recommendation.
Dynamic Monitor/Meter ~~~~~~~~~~~~~~~~~~~~~
You can use a tqdm as a meter which is not monotonically increasing.
This could be because n decreases (e.g. a CPU usage monitor) or total
changes.
One example would be recursively searching for files. The total is the
number of objects found so far, while n is the number of those objects which
are files (rather than folders):
.. code:: python
from tqdm import tqdm
import os.path
def find_files_recursively(path, show_progress=True):
files = []
# total=1 assumes `path` is a file
t = tqdm(total=1, unit="file", disable=not show_progress)
if not os.path.exists(path):
raise IOError("Cannot find:" + path)
def append_found_file(f):
files.append(f)
t.update()
def list_found_dir(path):
"""returns os.listdir(path) assuming os.path.isdir(path)"""
listing = os.listdir(path)
# subtract 1 since a "file" we found was actually this directory
t.total += len(listing) - 1
# fancy way to give info without forcing a refresh
t.set_postfix(dir=path[-10:], refresh=False)
t.update(0) # may trigger a refresh
return listing
def recursively_search(path):
if os.path.isdir(path):
for f in list_found_dir(path):
recursively_search(os.path.join(path, f))
else:
append_found_file(path)
recursively_search(path)
t.set_postfix(dir=path)
t.close()
return files
Using update(0) is a handy way to let tqdm decide when to trigger a
display refresh to avoid console spamming.
Writing messages ~~~~~~~~~~~~~~~~
This is a work in progress (see
#737 <https://github.com/tqdm/tqdm/issues/737>__).
Since tqdm uses a simple printing mechanism to display progress bars,
you should not write any message in the terminal using print() while
a progressbar is open.
To write messages in the terminal without any collision with tqdm bar
display, a .write() method is provided:
.. code:: python
from tqdm.auto 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
from tqdm.contrib import DummyTqdmFile
@contextlib.contextmanager
def std_out_err_redirect_tqdm():
orig_out_err = sys.stdout, sys.stderr
try:
sys.stdout, sys.stderr = map(DummyTqdmFile, orig_out_err)
yield orig_out_err[0]
# Relay exceptions
except Exception as exc:
raise exc
# Always restore sys.stdout/err if necessary
finally:
sys.stdout, sys.stderr = orig_out_err
def some_fun(i):
print("Fee, fi, fo,".split()[i])
# Redirect stdout to tqdm.write() (don't forget the `as save_stdout`)
with std_out_err_redirect_tqdm() as orig_stdout:
# tqdm needs the original stdout
# and dynamic_ncols=True to autodetect console width
for i in tqdm(range(3), file=orig_stdout, dynamic_ncols=True):
sleep(.5)
some_fun(i)
# 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 display 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 behaviour 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 iteration 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 instantiation of any tqdm bar.
|GitHub-Commits| |GitHub-Issues| |GitHub-PRs| |OpenHub-Status| |GitHub-Contributions| |CII Best Practices|
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.
Developers who have made significant contributions, ranked by SLoC
(surviving lines of code,
git fame <https://github.com/casperdcl/git-fame>__ -wMC),
are:
==================== ======================================================== ==== ================================
Name ID SLoC Notes
==================== ======================================================== ==== ================================
Casper da Costa-Luis casperdcl <https://github.com/casperdcl>_ ~75% primary maintainer |Gift-Casper|
Stephen Larroque lrq3000 <https://github.com/lrq3000>_ ~15% team member
Martin Zugnoni martinzugnoni <https://github.com/martinzugnoni>_ ~3%
Guangshuo Chen chengs <https://github.com/chengs>_ ~1%
Hadrien Mary hadim <https://github.com/hadim>_ ~1% team member
Matthew Stevens mjstevens777 <https://github.com/mjstevens777>_ ~1%
Noam Yorav-Raphael noamraph <https://github.com/noamraph>_ ~1% original author
Kyle Altendorf altendky <https://github.com/altendky>_ ~1%
Ivan Ivanov obiwanus <https://github.com/obiwanus>_ ~1%
James E. King III jeking3 <https://github.com/jeking3>_ ~1%
Mikhail Korobov kmike <https://github.com/kmike>__ ~1% team member
==================== ======================================================== ==== ================================
|sourcerer-0| |sourcerer-1| |sourcerer-2| |sourcerer-3| |sourcerer-4| |sourcerer-5| |sourcerer-7|
Ports to Other Languages ~~~~~~~~~~~~~~~~~~~~~~~~
A list is available on
this wiki page <https://github.com/tqdm/tqdm/wiki/tqdm-ports>__.
Open Source (OSI approved): |LICENCE|
Citation information: |DOI| (publication), |DOI-code| (code)
|README-Hits| (Since 19 May 2016)
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