leave=True by default, doc updates

This commit is contained in:
Casper da Costa-Luis 2016-01-25 08:28:59 +00:00
parent 0328832e04
commit 770b219ff8
2 changed files with 19 additions and 20 deletions

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@ -126,7 +126,7 @@ 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 ``close()`` at the end:
but in this case don't forget to ``del`` or ``close()`` at the end:
.. code:: python
@ -148,7 +148,7 @@ Documentation
progressbar every time a value is requested.
"""
def __init__(self, iterable=None, desc=None, total=None, leave=False,
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,
@ -170,7 +170,7 @@ Parameters
True and this parameter needs subsequent updating, specify an
initial arbitrary large positive integer, e.g. int(9e9).
* leave : bool, optional
If [default: False], removes all traces of the progressbar
If [default: True], removes all traces of the progressbar
upon termination of iteration.
* file : `io.TextIOWrapper` or `io.StringIO`, optional
Specifies where to output the progress messages
@ -382,9 +382,9 @@ bar. Here's an example:
from tqdm import trange
from time import sleep
for i in trange(10, desc='1st loop', leave=True):
for j in trange(5, desc='2nd loop', leave=True, nested=True):
for k in trange(100, desc='3nd loop', leave=True, nested=True):
for i in trange(10, desc='1st loop'):
for j in trange(5, desc='2nd loop', leave=False, nested=True):
for k in trange(100, desc='3nd loop', nested=True):
sleep(0.01)
On Windows `colorama <https://github.com/tartley/colorama>`__ will be used if
@ -400,16 +400,14 @@ a variety of use cases with no or minimal configuration.
However, there is one thing that ``tqdm`` cannot do: choose a pertinent
progress indicator. To display a useful progress bar, it is very important that
you ensure that you supply ``tqdm`` with the most pertinent progress indicator,
which will reflect most accurately the current state of your program.
``tqdm`` is supplied with the most pertinent progress indicator.
This will reflect most accurately the current state of your program.
Usually, a good way is to preprocess quickly to first evaluate the total amount
of work to do before beginning the real processing.
To illustrate the importance of a good progress indicator, let's take the
To illustrate the importance of a good progress indicator, take the
following example: you want to walk through all files of a directory and
process their contents to do your biddings.
Here is a basic program to do that:
process their contents with some external function:
.. code:: python
@ -436,7 +434,7 @@ Here is a basic program to do that:
buf = fh.read(blocksize)
dosomething(buf)
``process_content_no_progress()`` does the job alright, but it does not show
``process_content_no_progress()`` does the job, but does not show
any information about the current progress, nor how long it will take.
To quickly fix that using ``tqdm``, we can use this naive approach:
@ -485,10 +483,10 @@ now we have predictive information:
However, the progress is not smooth: it increments in steps, 1 step being
1 file processed. The problem is that we do not just walk through files tree,
but we process the files contents. Thus, if we stumble on one big fat file,
it will take a huge deal more time to process than other smaller files, but
the progress bar cannot know that, because we only supplied the files count,
so it considers that every element is of equal processing weight.
but we process the files contents. Thus, if we stumble on one very large file
which takes a great deal more time to process than other smaller files,
the progress bar
will still considers that file is of equal processing weight.
To fix this, we should use another indicator than the files count: the total
sum of all files sizes. This would be more pertinent since the data we
@ -525,6 +523,7 @@ predicted time and statistics:
47%|██████████████████▍\ \| 152K/321K [00:03<00:03, 46.2KB/s]
Contributions
-------------
@ -551,7 +550,7 @@ file for more information.
License
-------
`MIT LICENSE <https://raw.githubusercontent.com/tqdm/tqdm/master/LICENSE>`__.
Mostly `CC, MIT licence <https://raw.githubusercontent.com/tqdm/tqdm/master/LICENSE>`__.
Authors

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@ -247,7 +247,7 @@ class tqdm(object):
return (prefix if prefix else '') + '{0}{1} [{2}, {3}]'.format(
n_fmt, unit, elapsed_str, rate_fmt)
def __init__(self, iterable=None, desc=None, total=None, leave=False,
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,
@ -268,7 +268,7 @@ class tqdm(object):
True and this parameter needs subsequent updating, specify an
initial arbitrary large positive integer, e.g. int(9e9).
leave : bool, optional
If [default: False], removes all traces of the progressbar
If [default: True], removes all traces of the progressbar
upon termination of iteration.
file : `io.TextIOWrapper` or `io.StringIO`, optional
Specifies where to output the progress messages