ProgIter documentation

ProgIter lets you measure and print the progress of an iterative process. This can be done either via an iterable interface or using the manual api. Using the iterable inferface is most common.

ProgIter was originally developed independantly of tqdm, but the newer versions of this library have been designed to be compatible with tqdm-API. ProgIter is now a (mostly) drop-in alternative to tqdm_. The tqdm library may be more appropriate in some cases. The main advantage of ``ProgIter`` is that it does not use any python threading, and therefore can be safer with code that makes heavy use of multiprocessing. `The reason`_ for this is that threading before forking may cause locks to be duplicated across processes, which may lead to deadlocks.

ProgIter is simpler than tqdm, which may be desirable for some applications. However, this also means ProgIter is not as extensible as tqdm. If you want a pretty bar, use tqdm; if you want useful information (rate, fraction-complete, estimated time remaining, time taken so far, current wall time) about your iteration by default, use progiter.

Example

The basic usage of ProgIter is simple and intuitive. Just wrap a python iterable. The following example wraps a range iterable and prints reported progress to stdout as the iterable is consumed. The ProgIter object accepts various keyword arguments to modify the details of how progress is measured and reported. See API documentation of the ProgIter classs here: https://progiter.readthedocs.io/en/latest/progiter.progiter.html#progiter.progiter.ProgIter

Note that by default ProgIter reports information about iteration-rate, fraction-complete, estimated time remaining, time taken so far, and the current wall time.

>>> from progiter import ProgIter
>>> def is_prime(n):
...     return n >= 2 and not any(n % i == 0 for i in range(2, n))
>>> for n in ProgIter(range(1000), verbose=2):
>>>     # do some work
>>>     is_prime(n)
    0/1000... rate=0.00 Hz, eta=?, total=0:00:00, wall=14:05 EST
    1/1000... rate=82241.25 Hz, eta=0:00:00, total=0:00:00, wall=14:05 EST
  257/1000... rate=177204.69 Hz, eta=0:00:00, total=0:00:00, wall=14:05 EST
  642/1000... rate=94099.22 Hz, eta=0:00:00, total=0:00:00, wall=14:05 EST
 1000/1000... rate=71886.74 Hz, eta=0:00:00, total=0:00:00, wall=14:05 EST

A Progress Iterator

ProgIter lets you measure and print the progress of an iterative process. This can be done either via an iterable interface or using the manual API. Using the iterable inferface is most common.

ProgIter was originally developed independantly of tqdm, but the newer versions of this library have been designed to be compatible with tqdm-API. ProgIter is now a (mostly) drop-in alternative to tqdm_. The tqdm library may be more appropriate in some cases. The main advantage of ``ProgIter`` is that it does not use any python threading, and therefore can be safer with code that makes heavy use of multiprocessing. `The reason`_ for this is that threading before forking may cause locks to be duplicated across processes, which may lead to deadlocks.

ProgIter is simpler than tqdm, which may be desirable for some applications. However, this also means ProgIter is not as extensible as tqdm. If you want a pretty bar or need something fancy, use tqdm; if you want useful information about your iteration by default, use progiter.

The basic usage of ProgIter is simple and intuitive. Just wrap a python iterable. The following example wraps a range iterable and prints reported progress to stdout as the iterable is consumed.

Example

>>> for n in ProgIter(range(1000)):
>>>     # do some work
>>>     pass

Note that by default ProgIter reports information about iteration-rate, fraction-complete, estimated time remaining, time taken so far, and the current wall time.

Example

>>> # xdoctest: +IGNORE_WANT
>>> def is_prime(n):
...     return n >= 2 and not any(n % i == 0 for i in range(2, n))
>>> for n in ProgIter(range(1000), verbose=1):
>>>     # do some work
>>>     is_prime(n)
1000/1000... rate=21153.08 Hz, eta=0:00:00, total=0:00:00, wall=13:00 EST

For more complex applications is may sometimes be desireable to manually use the ProgIter API. This is done as follows:

Example

>>> # xdoctest: +IGNORE_WANT
>>> n = 3
>>> prog = ProgIter(desc='manual', total=n, verbose=3)
>>> prog.begin() # Manually begin progress iteration
>>> for _ in range(n):
...     prog.step(inc=1)  # specify the number of steps to increment
>>> prog.end()  # Manually end progress iteration
manual 0/3... rate=0 Hz, eta=?, total=0:00:00, wall=12:46 EST
manual 1/3... rate=12036.01 Hz, eta=0:00:00, total=0:00:00, wall=12:46 EST
manual 2/3... rate=16510.10 Hz, eta=0:00:00, total=0:00:00, wall=12:46 EST
manual 3/3... rate=20067.43 Hz, eta=0:00:00, total=0:00:00, wall=12:46 EST

When working with ProgIter in either iterable or manual mode you can use the prog.ensure_newline method to guarantee that the next call you make to stdout will start on a new line. You can also use the prog.set_extra method to update a dynamci “extra” message that is shown in the formatted output. The following example demonstrates this.

Example

>>> # xdoctest: +IGNORE_WANT
>>> def is_prime(n):
...     return n >= 2 and not any(n % i == 0 for i in range(2, n))
>>> _iter = range(1000)
>>> prog = ProgIter(_iter, desc='check primes', verbose=2)
>>> for n in prog:
>>>     if n == 97:
>>>         print('!!! Special print at n=97 !!!')
>>>     if is_prime(n):
>>>         prog.set_extra('Biggest prime so far: {}'.format(n))
>>>         prog.ensure_newline()
check primes    0/1000... rate=0 Hz, eta=?, total=0:00:00, wall=12:55 EST
check primes    1/1000... rate=98376.78 Hz, eta=0:00:00, total=0:00:00, wall=12:55 EST
!!! Special print at n=97 !!!
check primes  257/1000...Biggest prime so far: 251 rate=308037.13 Hz, eta=0:00:00, total=0:00:00, wall=12:55 EST
check primes  642/1000...Biggest prime so far: 641 rate=185166.01 Hz, eta=0:00:00, total=0:00:00, wall=12:55 EST
check primes 1000/1000...Biggest prime so far: 997 rate=120063.72 Hz, eta=0:00:00, total=0:00:00, wall=12:55 EST