pooltool.utils

Utilities

Overview

Classes

classproperty	Decorator for a class property
PProfile	Small wrapper for pprofile that accepts a filepath and outputs cachegrind file

Function

save_pickle(x, path)	Save an object x to filepath path
is_pickleable(obj)	https://stackoverflow.com/a/53398070
get_total_memory_usage(keep_raw)	Get the total memory, including children
display_top_memory_usage(snapshot, key_type, limit)	A pretty-print for the tracemalloc memory usage module
memory_usage_to_dataframe(snapshot, key_type, limit)	Convert memory usage data from tracemalloc into a pandas DataFrame.

Classes

class pooltool.utils.classproperty(fget=None, fset=None, fdel=None, doc=None)

Decorator for a class property

Examples

>>> from pooltool.utils import classproperty
>>> class Test:
>>>     @classproperty
>>>     def foo(cls):
>>>         return cls.__name__

Bases: property

class pooltool.utils.PProfile(path, should_run: bool = True)

Small wrapper for pprofile that accepts a filepath and outputs cachegrind file

Bases: pprofile.Profile

Functions

pooltool.utils.save_pickle(x, path)

Save an object x to filepath path

pooltool.utils.is_pickleable(obj)

https://stackoverflow.com/a/53398070

pooltool.utils.get_total_memory_usage(keep_raw=False)

Get the total memory, including children

Parameters:

keep_raw (bool, False) -- A human readable format is returned, e.g. “1.41 GB”. If keep_raw, the raw number is returned, e.g. 1515601920

pooltool.utils.display_top_memory_usage(snapshot, key_type='lineno', limit=10)

A pretty-print for the tracemalloc memory usage module

Modified from https://docs.python.org/3/library/tracemalloc.html

Examples

>>> import tracemalloc
>>> import pooltool.utils as utils
>>> tracemalloc.start()
>>> snap = tracemalloc.take_snapshot
>>> utils.display_top_memory_usage(snap)
Top 10 lines
#1: anvio/bamops.py:160: 4671.3 KiB
    constants.cigar_consumption,
#2: anvio/bamops.py:96: 2571.6 KiB
    self.cigartuples = np.array(read.cigartuples)
#3: python3.6/linecache.py:137: 1100.0 KiB
    lines = fp.readlines()
#4: <frozen importlib._bootstrap_external>:487: 961.4 KiB
#5: typing/templates.py:627: 334.3 KiB
    return type(base)(name, (base,), dct)
#6: typing/templates.py:923: 315.7 KiB
    class Template(cls):
#7: python3.6/_weakrefset.py:84: 225.2 KiB
    self.data.add(ref(item, self._remove))
#8: targets/npyimpl.py:411: 143.2 KiB
    class _KernelImpl(_Kernel):
#9: _vendor/pyparsing.py:3349: 139.7 KiB
    self.errmsg = "Expected " + _ustr(self)
#10: typing/context.py:456: 105.1 KiB
    def on_disposal(wr, pop=self._globals.pop):
3212 other: 4611.9 KiB
Total allocated size: 15179.4 KiB

pooltool.utils.memory_usage_to_dataframe(snapshot, key_type='lineno', limit=10)

Convert memory usage data from tracemalloc into a pandas DataFrame.

Args: snapshot (tracemalloc.Snapshot): The snapshot of memory allocation. key_type (str): The type of key to categorize memory usage. limit (int): The number of top entries to include.

Returns: pd.DataFrame: DataFrame containing memory usage information.