openfl.utilities

class openfl.utilities.ABCMeta(name, bases, namespace, **kwargs)

Metaclass for defining Abstract Base Classes (ABCs).

Use this metaclass to create an ABC. An ABC can be subclassed directly, and then acts as a mix-in class. You can also register unrelated concrete classes (even built-in classes) and unrelated ABCs as ‘virtual subclasses’ – these and their descendants will be considered subclasses of the registering ABC by the built-in issubclass() function, but the registering ABC won’t show up in their MRO (Method Resolution Order) nor will method implementations defined by the registering ABC be callable (not even via super()).

register(subclass)

Register a virtual subclass of an ABC.

Returns the subclass, to allow usage as a class decorator.

openfl.utilities.Dynaconf: alias of LazySettings

class openfl.utilities.LocalTensor(col_name, tensor, weight)

col_name: Alias for field number 0

tensor: Alias for field number 1

weight: Alias for field number 2

class openfl.utilities.Metric(name, value)

name: Alias for field number 0

value: Alias for field number 1

class openfl.utilities.SingletonABCMeta(name, bases, namespace, **kwargs)

Metaclass for singleton instances.

This metaclass ensures that only one instance of any class using it can be created.

Class Attributes:: _instances (dict) – A dictionary mapping classes to their instances.

class openfl.utilities.TaskResultKey(task_name, owner, round_number)

owner: Alias for field number 1

round_number: Alias for field number 2

task_name: Alias for field number 0

class openfl.utilities.TensorKey(tensor_name, origin, round_number, report, tags)

origin: Alias for field number 1

report: Alias for field number 3

round_number: Alias for field number 2

tags: Alias for field number 4

tensor_name: Alias for field number 0

openfl.utilities.add_log_level(level_name, level_num, method_name=None)

Add a new logging level to the logging module.

This function adds a new logging level to the logging module with a specified name, value, and method name.

Parameters:

level_name (str) – The name of the new logging level.
level_num (int) – The value of the new logging level.
method_name (str, optional) – The name of the method to use for the new logging level. Defaults to None.

openfl.utilities.change_tags(tags, *, add_field=None, remove_field=None) → Tuple[str, ...]

Change tensor tags to add or remove fields.

This function adds or removes fields from tensor tags.

Parameters:

tags (Tuple[str, ...]) – The tensor tags.
add_field (str, optional) – A new tensor tag field to add. Defaults to None.
remove_field (str, optional) – A tensor tag field to remove. Defaults to None.

Returns:

Tuple[str, …] – The modified tensor tags.

Raises:

Exception – If remove_field is not in tags.

openfl.utilities.check_equal(x, y, logger)

Assert x and y are equal.

Parameters:

x (Any) – The first value to compare.
y (Any) – The second value to compare.
logger (Logger) – The logger to use for reporting the error.

Raises:

ValueError – If the values are not equal.

openfl.utilities.check_is_in(element, _list, logger)

Assert element is in _list collection.

Parameters:

element (Any) – The element to check.
_list (Iterable) – The collection to check in.
logger (Logger) – The logger to use for reporting the error.

Raises:

ValueError – If the element is not in the collection.

openfl.utilities.check_not_equal(x, y, logger, name='None provided')

Assert x and y are not equal.

Parameters:

x (Any) – The first value to compare.
y (Any) – The second value to compare.
logger (Logger) – The logger to use for reporting the error.
name (str, optional) – The name of the values. Defaults to ‘None provided’.

Raises:

ValueError – If the values are equal.

openfl.utilities.check_not_in(element, _list, logger)

Assert element is not in _list collection.

Parameters:

element (Any) – The element to check.
_list (Iterable) – The collection to check in.
logger (Logger) – The logger to use for reporting the error.

Raises:

ValueError – If the element is in the collection.

openfl.utilities.check_type(obj, expected_type, logger)

Assert obj is of expected_type type.

Parameters:

obj (Any) – The object to check.
expected_type (type) – The expected type of the object.
logger (Logger) – The logger to use for reporting the error.

Raises:

TypeError – If the object is not of the expected type.

openfl.utilities.getfqdn(name='')

Get fully qualified domain name from name.

An empty argument is interpreted as meaning the local host.

First the hostname returned by gethostbyaddr() is checked, then possibly existing aliases. In case no FQDN is available and name was given, it is returned unchanged. If name was empty, ‘0.0.0.0’ or ‘::’, hostname from gethostname() is returned.

openfl.utilities.getfqdn_env(name: str = '') → str

Get the system FQDN, with priority given to environment variables.

This function retrieves the fully qualified domain name (FQDN) of the system. If the ‘FQDN’ environment variable is set, its value is returned. Otherwise,the FQDN is determined based on the system’s hostname.

Parameters:: name (str, optional) – The name from which to extract the FQDN. Defaults to ‘’.
Returns:: str – The FQDN of the system.

openfl.utilities.is_api_adress(address: str) → bool

Validate IP address value.

This function checks if a string is a valid IP address.

Parameters:: address (str) – The string to check.
Returns:: bool – True if the string is a valid IP address, False otherwise.

openfl.utilities.is_fqdn(hostname: str) → bool

Check if a hostname is a fully qualified domain name.

This function checks if a hostname is a fully qualified domain name (FQDN) according to the rules specified on Wikipedia. https://en.m.wikipedia.org/wiki/Fully_qualified_domain_name.

Parameters:: hostname (str) – The hostname to check.
Returns:: bool – True if the hostname is a FQDN, False otherwise.

openfl.utilities.merge_configs(overwrite_dict: dict | None = None, value_transform: List[Tuple[str, Callable]] | None = None, **kwargs) → LazySettings

Create Dynaconf settings, merge its with overwrite_dict and validate result.

This function creates a Dynaconf settings object, merges it with an optional dictionary, applies an optional value transformation, and validates the result.

Parameters:

overwrite_dict (Optional[dict], optional) – A dictionary to merge with the settings. Defaults to None.
value_transform (Optional[List[Tuple[str, Callable]]], optional) – A list of tuples, each containing a key and a function to apply to the value of that key. Defaults to None.
**kwargs – Additional keyword arguments to pass to the Dynaconf constructor.

Returns:

Dynaconf – The merged and validated settings.

openfl.utilities.namedtuple(typename, field_names, *, rename=False, defaults=None, module=None)

Returns a new subclass of tuple with named fields.

>>> Point = namedtuple('Point', ['x', 'y'])
>>> Point.__doc__                   # docstring for the new class
'Point(x, y)'
>>> p = Point(11, y=22)             # instantiate with positional args or keywords
>>> p[0] + p[1]                     # indexable like a plain tuple
33
>>> x, y = p                        # unpack like a regular tuple
>>> x, y
(11, 22)
>>> p.x + p.y                       # fields also accessible by name
33
>>> d = p._asdict()                 # convert to a dictionary
>>> d['x']
11
>>> Point(**d)                      # convert from a dictionary
Point(x=11, y=22)
>>> p._replace(x=100)               # _replace() is like str.replace() but targets named fields
Point(x=100, y=22)

class openfl.utilities.partial

partial(func, *args, **keywords) - new function with partial application of the given arguments and keywords.

args: tuple of arguments to future partial calls

func: function object to use in future partial calls

keywords: dictionary of keyword arguments to future partial calls

openfl.utilities.rmtree(path, ignore_errors=False)

Remove a directory tree.

This function removes a directory tree. If a file in the directory tree is read-only, its read-only attribute is cleared before it is removed.

Parameters:

path (str) – The path to the directory tree to remove.
ignore_errors (bool, optional) – Whether to ignore errors. Defaults to False.

Returns:

str – The path to the removed directory tree.

class openfl.utilities.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.

Parameters:

iterable (iterable, optional) – Iterable to decorate with a progressbar. Leave blank to manually manage the updates.
desc (str, optional) – Prefix for the progressbar.
total (int or float, optional) – The number of expected iterations. If unspecified, len(iterable) is used if possible. If float(“inf”) or as a last resort, only basic progress statistics are displayed (no ETA, no progressbar). If gui is True and this parameter needs subsequent updating, specify an initial arbitrary large positive number, e.g. 9e9.
leave (bool, optional) – If [default: True], keeps all traces of the progressbar upon termination of iteration. If None, will leave only if position is 0.
file (io.TextIOWrapper or io.StringIO, optional) – Specifies where to output the progress messages (default: sys.stderr). Uses file.write(str) and file.flush() methods. For encoding, see write_bytes.
ncols (int, optional) – The width of the entire output message. If specified, dynamically resizes the progressbar to stay within this bound. If unspecified, attempts to use environment width. The fallback is a meter width of 10 and no limit for the counter and statistics. If 0, will not print any meter (only stats).
mininterval (float, optional) – Minimum progress display update interval [default: 0.1] seconds.
maxinterval (float, optional) – Maximum progress display update interval [default: 10] seconds. Automatically adjusts miniters to correspond to mininterval after long display update lag. Only works if dynamic_miniters or monitor thread is enabled.
miniters (int or float, optional) – Minimum progress display update interval, in iterations. If 0 and 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.
ascii (bool or str, optional) – If unspecified or False, use unicode (smooth blocks) to fill the meter. The fallback is to use ASCII characters “ 123456789#”.
disable (bool, optional) – Whether to disable the entire progressbar wrapper [default: False]. If set to None, disable on non-TTY.
unit (str, optional) – String that will be used to define the unit of each iteration [default: it].
unit_scale (bool or int or float, optional) – If 1 or True, the number of iterations will be reduced/scaled automatically and a metric prefix following the International System of Units standard will be added (kilo, mega, etc.) [default: False]. If any other non-zero number, will scale total and n.
dynamic_ncols (bool, optional) – If set, constantly alters ncols and nrows to the environment (allowing for window resizes) [default: False].
smoothing (float, optional) – Exponential moving average smoothing factor for speed estimates (ignored in GUI mode). Ranges from 0 (average speed) to 1 (current/instantaneous speed) [default: 0.3].
bar_format (str, optional) –
Specify a custom bar string formatting. May impact performance. [default: ‘{l_bar}{bar}{r_bar}’], where l_bar=’{desc}: {percentage:3.0f}%|’ and r_bar=’| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, ‘

’{rate_fmt}{postfix}]’

Possible vars: l_bar, bar, r_bar, n, n_fmt, total, total_fmt,
percentage, elapsed, elapsed_s, ncols, nrows, desc, unit, rate, rate_fmt, rate_noinv, rate_noinv_fmt, rate_inv, rate_inv_fmt, postfix, unit_divisor, remaining, remaining_s, eta.

Note that a trailing “: “ is automatically removed after {desc} if the latter is empty.
initial (int or float, optional) – The initial counter value. Useful when restarting a progress bar [default: 0]. If using float, consider specifying {n:.3f} or similar in bar_format, or specifying unit_scale.
position (int, optional) – Specify the line offset to print this bar (starting from 0) Automatic if unspecified. Useful to manage multiple bars at once (eg, from threads).
postfix (dict or *, optional) – Specify additional stats to display at the end of the bar. Calls set_postfix(**postfix) if possible (dict).
unit_divisor (float, optional) – [default: 1000], ignored unless unit_scale is True.
write_bytes (bool, optional) – Whether to write bytes. If (default: False) will write unicode.
lock_args (tuple, optional) – Passed to refresh for intermediate output (initialisation, iterating, and updating).
nrows (int, optional) – The screen height. If specified, hides nested bars outside this bound. If unspecified, attempts to use environment height. The fallback is 20.
colour (str, optional) – Bar colour (e.g. ‘green’, ‘#00ff00’).
delay (float, optional) – Don’t display until [default: 0] seconds have elapsed.
gui (bool, optional) – WARNING: internal parameter - do not use. Use tqdm.gui.tqdm(…) instead. If set, will attempt to use matplotlib animations for a graphical output [default: False].

Returns:

out (decorated iterator.)

clear(nolock=False): Clear current bar display.

close(): Cleanup and (if leave=False) close the progressbar.

display(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)).

classmethod external_write_mode(file=None, nolock=False): Disable tqdm within context and refresh tqdm when exits. Useful when writing to standard output stream

property format_dict: Public API for read-only member access.

static format_interval(t)

Formats a number of seconds as a clock time, [H:]MM:SS

Parameters:: t (int) – Number of seconds.
Returns:: out (str) – [H:]MM:SS

static format_meter(n, total, elapsed, ncols=None, prefix='', ascii=False, unit='it', unit_scale=False, rate=None, bar_format=None, postfix=None, unit_divisor=1000, initial=0, colour=None, **extra_kwargs)

Return a string-based progress bar given some parameters

Parameters:

n (int or float) – Number of finished iterations.
total (int or float) – The expected total number of iterations. If meaningless (None), only basic progress statistics are displayed (no ETA).
elapsed (float) – Number of seconds passed since start.
ncols (int, optional) – The width of the entire output message. If specified, dynamically resizes {bar} to stay within this bound [default: None]. If 0, will not print any bar (only stats). The fallback is {bar:10}.
prefix (str, optional) – Prefix message (included in total width) [default: ‘’]. Use as {desc} in bar_format string.
ascii (bool, optional or str, optional) – If not set, use unicode (smooth blocks) to fill the meter [default: False]. The fallback is to use ASCII characters “ 123456789#”.
unit (str, optional) – The iteration unit [default: ‘it’].
unit_scale (bool or int or float, optional) – If 1 or True, the number of iterations will be printed with an appropriate SI metric prefix (k = 10^3, M = 10^6, etc.) [default: False]. If any other non-zero number, will scale total and n.
rate (float, optional) – Manual override for iteration rate. If [default: None], uses n/elapsed.
bar_format (str, optional) –
Specify a custom bar string formatting. May impact performance. [default: ‘{l_bar}{bar}{r_bar}’], where l_bar=’{desc}: {percentage:3.0f}%|’ and r_bar=’| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, ‘

’{rate_fmt}{postfix}]’

Possible vars: l_bar, bar, r_bar, n, n_fmt, total, total_fmt,
percentage, elapsed, elapsed_s, ncols, nrows, desc, unit, rate, rate_fmt, rate_noinv, rate_noinv_fmt, rate_inv, rate_inv_fmt, postfix, unit_divisor, remaining, remaining_s, eta.

Note that a trailing “: “ is automatically removed after {desc} if the latter is empty.
postfix (*, optional) – Similar to prefix, but placed at the end (e.g. for additional stats). Note: postfix is usually a string (not a dict) for this method, and will if possible be set to postfix = ‘, ‘ + postfix. However other types are supported (#382).
unit_divisor (float, optional) – [default: 1000], ignored unless unit_scale is True.
initial (int or float, optional) – The initial counter value [default: 0].
colour (str, optional) – Bar colour (e.g. ‘green’, ‘#00ff00’).

Returns:

out (Formatted meter and stats, ready to display.)

static format_num(n)

Intelligent scientific notation (.3g).

Parameters:: n (int or float or Numeric) – A Number.
Returns:: out (str) – Formatted number.

static format_sizeof(num, suffix='', divisor=1000)

Formats a number (greater than unity) with SI Order of Magnitude prefixes.

Parameters:

num (float) – Number ( >= 1) to format.
suffix (str, optional) – Post-postfix [default: ‘’].
divisor (float, optional) – Divisor between prefixes [default: 1000].

Returns:

out (str) – Number with Order of Magnitude SI unit postfix.

classmethod get_lock(): Get the global lock. Construct it if it does not exist.

classmethod pandas(**tqdm_kwargs)

Registers the current tqdm class with: pandas.core. ( frame.DataFrame | series.Series | groupby.(generic.)DataFrameGroupBy | groupby.(generic.)SeriesGroupBy ).progress_apply

A new instance will be created every time progress_apply is called, and each instance will automatically close() upon completion.

Parameters:: tqdm_kwargs (arguments for the tqdm instance)

Examples

>>> import pandas as pd
>>> import numpy as np
>>> from tqdm import tqdm
>>> from tqdm.gui import tqdm as tqdm_gui
>>>
>>> df = pd.DataFrame(np.random.randint(0, 100, (100000, 6)))
>>> tqdm.pandas(ncols=50)  # can use tqdm_gui, optional kwargs, etc
>>> # Now you can use `progress_apply` instead of `apply`
>>> df.groupby(0).progress_apply(lambda x: x**2)

References

<https://stackoverflow.com/questions/18603270/ progress-indicator-during-pandas-operations-python>

refresh(nolock=False, lock_args=None)

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.

reset(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.)

set_description(desc=None, refresh=True)

Set/modify description of the progress bar.

Parameters:

desc (str, optional)
refresh (bool, optional) – Forces refresh [default: True].

set_description_str(desc=None, refresh=True): Set/modify description without ‘: ‘ appended.

classmethod set_lock(lock): Set the global lock.

set_postfix(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)

set_postfix_str(s='', refresh=True): Postfix without dictionary expansion, similar to prefix handling.

static status_printer(file): Manage the printing and in-place updating of a line of characters. Note that if the string is longer than a line, then in-place updating may not work (it will print a new line at each refresh).

unpause(): Restart tqdm timer from last print time.

update(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.
Returns:: out (bool or None) – True if a display() was triggered.

classmethod wrapattr(stream, method, total=None, bytes=True, **tqdm_kwargs)

stream : file-like object. method : str, “read” or “write”. The result of read() and

the first argument of write() should have a len().

>>> with tqdm.wrapattr(file_obj, "read", total=file_obj.size) as fobj:
...     while True:
...         chunk = fobj.read(chunk_size)
...         if not chunk:
...             break

classmethod write(s, file=None, end='\n', nolock=False): Print a message via tqdm (without overlap with bars).

openfl.utilities.tqdm_report_hook()

Visualize downloading.

This function creates a progress bar for visualizing the progress of a download.

Returns:: Callable – A function that updates the progress bar.

openfl.utilities.validate_file_hash(file_path, expected_hash, chunk_size=8192)

Validate SHA384 hash for file specified.

This function validates the SHA384 hash of a file against an expected hash.

Parameters:

file_path (str) – The path to the file to validate. (absolute or relative to the current working directory) of the file to be opened or an integer file descriptor of the file to be wrapped.
expected_hash (str) – The expected SHA384 hash of the file.
chunk_size (int, optional) – The size of the chunks to read from the file. Defaults to 8192.

Raises:

SystemError – If the hash of the file does not match the expected hash.

`ca`	CA package.
`checks`	Generic check functions.
`click_types`	Custom input types definition for Click
`data_splitters`	openfl.utilities.data package.
`fed_timer`	Components Timeout Configuration Module
`fedcurv`	openfl.utilities.fedcurv package.
`logs`	Logs utilities.
`mocks`	Mock objects to eliminate extraneous dependencies
`optimizers`	Optimizers package.
`path_check`	openfl path checks.
`split`	split tensors module.
`types`	openfl common object types.
`utils`	Utilities module.
`workspace`	Workspace utils module.