AlexBerUtils is collection of the small utilities
Project description
AlexBerUtils
AlexBerUtils is collection of the small utilities. See CHANGELOG.md for detail description.
Getting Help
QuickStart
python -m pip install -U alex-ber-utils
Installing from Github
python -m pip install -U https://github.com/alex-ber/AlexBerUtils/archive/master.zip
Optionally installing tests requirements.
python -m pip install -U https://github.com/alex-ber/AlexBerUtils/archive/master.zip#egg=alex-ber-utils[tests]
Or explicitly:
wget https://github.com/alex-ber/AlexBerUtils/archive/master.zip -O master.zip; unzip master.zip; rm master.zip
And then installing from source (see below).
Installing from source
python -m pip install . # only installs "required"
python -m pip install .[tests] # installs dependencies for tests
python -m pip install .[piptools] # installs dependencies for pip-tools
python -m pip install .[fabric] # installs fabric (used in fabs.py)
python -m pip install .[yml] # installs Yml related dependencies
# (used in ymlparsers.py, init_app_conf.py, deploys.py;
# optionally used in ymlparsers_extra.py, emails.py)
python -m pip install .[env] # installs pydotenv (optionally used in deploys.py and mains.py)
Alternatively you install from requirements file:
python -m pip install -r requirements.txt # only installs "required"
python -m pip install -r requirements-tests.txt # installs dependencies for tests
python -m pip install -r requirements-piptools.txt # installs dependencies for pip-tools
python -m pip install -r requirements-fabric.txt # installs fabric (used in fabs.py)
python -m pip install -r requirements-yml.txt # installs Yml related dependencies
# (used in ymlparsers.py, init_app_conf.py, deploys.py;
# optionally used in ymlparsers_extra.py, emails.py)
python -m pip install -r requirements-env.txt # installs pydotenv (optionally used in deploys.py)
Using Docker
alexberkovich/AlexBerUtils:latest
contains all AlexBerUtils
dependencies.
This Dockerfile is very simple, you can take relevant part for you and put them into your Dockerfile.
Alternatively, you can use it as base Docker image for your project and add/upgrade another dependencies as you need.
For example:
FROM alexberkovich/alex_ber_utils:latest
COPY requirements.txt etc/requirements.txt
RUN set -ex && \
#latest pip,setuptools,wheel
pip install --upgrade pip setuptools wheel && \
pip install alex_ber_utils
pip install -r etc/requirements.txt
CMD ["/bin/sh"]
#CMD tail -f /dev/null
where requirements.txt
is requirements for your project.
From the directory with setup.py
python setup.py test #run all tests
or
pytest
Installing new version
See https://docs.python.org/3.1/distutils/uploading.html
Installing new version to venv
python -m pip uninstall --yes alex_ber_utils
python setup.py clean sdist bdist_wheel
python -m pip install --find-links=./dist alex_ber_utils==0.6.5
##Manual upload
#python setup.py clean sdist upload
Requirements
AlexBerUtils requires the following modules.
-
Python 3.8+
-
PyYAML>=6.0.1
-
packaging>=23.2
Changelog
All notable changes to this project will be documented in this file.
#https://pypi.org/manage/project/alex-ber-utils/releases/
Unreleased
[0.12.1] 16.11.2024
Changed
- Updated the
aadd_task()
method inAsyncExecutionQueue
to explicitly associate futures with the currently running event loop. This change enhances the robustness and maintainability of the code by ensuring that futures are bound to the correct event loop context, reducing the risk of potential issues related to event loop mismatches in future modifications or extensions of the codebase. This update is backward compatible as it does not alter the external behavior or interface of the aadd_task method. It only changes the internal implementation detail concerning how futures are managed.
[0.12.0] 16.11.2024
Added
-
Introduced a
deprecated
decorator to mark functions as deprecated.- The decorator allows specifying the version since which the function is deprecated, the reason for deprecation, and whether the function is marked for removal.
- It issues a customizable warning (defaulting to
DeprecationWarning
) when the decorated function is called. - This addition helps developers communicate deprecation status and future removal plans for functions in the codebase.
-
exec_in_executor_threading_future()
a thin wrapper aroundexec_in_executor()
, which returns anasyncio.Future
. This function executes a function or coroutine within a specified executor and converts the resultingasyncio.Future
into athreading.Future
. It preservesContextVars
, ensuring that context is maintained across asynchronous boundaries. For more details, see description ofexec_in_executor()
. -
exec_in_executor()
:- Added the
exec_in_executor
function to execute a function or coroutine within a specified executor while preservingContextVars
. - The function ensures context is maintained across asynchronous boundaries and resolves the executor in a prioritized manner:
- Uses the provided executor if available.
- Falls back to an executor set via
initConfig()
. - Defaults to the asyncio executor if none is set.
- Supports both coroutine and regular function execution.
- Added the
-
ensure_thread_event_loop()
:- Implemented the
ensure_thread_event_loop()
function to initialize an event loop for the current thread if it does not already exist.
- Implemented the
-
handle_result()
: Introduced a newhandle_result()
function that transfers the result or exception from one future to another. This function is designed to be generic and can be used with any types of futures, ensuring that the outcome of task execution is properly propagated between futures.- Usage: To use this function, add it as a callback to the
source_future
:# Add the chain_future_results function as a callback to the source_future source_future.add_done_callback(lambda fut: handle_result(fut, target_future))
- Arguments:
source_future
: The future from which to retrieve the result or exception.target_future
: The future on which to set the result or exception.
- Usage: To use this function, add it as a callback to the
-
AsyncExecutionQueue:
-
Introduced a new
AsyncExecutionQueue
class for managing asynchronous task execution using a specified executor. This class provides:- A context manager interface to start and stop a worker that processes tasks from the queue.
- Asynchronous task execution with graceful queue closure.
- Note: as a side fact, threads in the executor may have an event loop attached. This allows for the execution of asynchronous tasks within those threads.
Attributes
executor (Executor)
: The mandatory executor used to run tasks.queue (asyncio.Queue)
: The optional queue that holds tasks to be executed. If not provided, a newasyncio.Queue
is created by default.
Methods
worker()
: Continuously processes tasks from the queue until theaclose()
method is called.aadd_task(func, *args, **kwargs)
: Asynchronously adds a task to the queue for execution and returns a future.aclose()
: Asynchronously closes the queue and waits for the worker to finish processing.
Initialization
- The
AsyncExecutionQueue
is initialized with a specified executor and an optional queue. The executor is required to run tasks, while a custom queue can be provided or the defaultasyncio.Queue
will be used.
Context Management
- The
AsyncExecutionQueue
can be used as a context manager. When entering the context, the worker is started, and when exiting, the queue is closed, and the worker is stopped.
Changed
initConfig()
:- The
initConfig
function now also supportsexec_in_executor()
through theexecutor
parameter. - This function is designed to be called from the main thread.
- It accepts optional keyword arguments to configure a global executor that can be (optionally) used in
exec_in_executor()
.
- The
- GitHub Issue #14: Enhanced the
lift_to_async
function to handleStopAsyncIteration
exceptions more gracefully. If aStopAsyncIteration
exception is raised fromafunc
, it is now converted to aRuntimeError
with a descriptive message. This change prevents aTypeError
from being raised and ensures that theFuture
does not remain pending indefinitely. - Updated
initConfig()
:- Initializes the configuration for
lift_to_async()
andexec_in_executor()
. - Ensures it is called from the main thread with a running event loop.
- Sets a global executor if provided via keyword arguments.
- Initializes the configuration for
Example Usage
# Example usage of the decorator
@deprecated(version='1.0', reason="Use `new_function` instead.", for_removal=True)
def old_function(x, y):
"""Returns the sum of two numbers."""
return x + y
# Call the deprecated function
result = old_function(3, 4)
[0.11.11] 22.10.2024
Changed
-
OptionalNumpyWarning: Moved the definition of
OptionalNumpyWarning
to a separate module (alexber.utils.warnings
) to allow for easier suppression of the warning without triggering it during import. This change improves the flexibility and usability of the library for users who do not require NumPy. -
Type Hints: Fixed and improved type hints across the codebase to enhance code clarity and support for static type checking tools. This ensures better integration with IDEs and type checkers, providing more accurate code suggestions and error detection.
[0.11.10] 22.10.2024 yanked
Added
- USE_NUMPY: Introduced a flag to determine whether NumPy is available and should be used for sampling operations. This allows for performance optimizations when NumPy is installed.
- SamplingError: Added a custom exception class to handle errors when sampling fails after a maximum number of retries. It provides detailed error messages, including distribution type, retries, and bounds, aiding in debugging and error handling.
- OptionalNumpyWarning: Introduced a custom warning to notify users when NumPy is not available, and the system falls back to standard Python operations. The primary purpose of this warning is to provide users with the ability to suppress it if desired.
Changed
- BaseSampler: Refactored the base class for sampling to support various statistical distributions with configurable parameters. This includes validation for distribution types and bounds.
- Sampler: The class can optionally use NumPy for sampling if it is available, allowing for potentially faster and more efficient sampling operations. If NumPy is not available, the class defaults to using Python's standard
random
module, ensuring compatibility across environments.- Note: The
expovariate
method has been adjusted to align with NumPy's exponential function, using the scale directly as the mean of the distribution.
- Note: The
- max_retries: Added a parameter to limit the number of attempts to sample a valid value, primarily to avoid infinite loops. This ensures that the sampling process terminates gracefully if a valid sample cannot be obtained within the specified number of retries.
[0.11.9] 21.10.2024
Added
- Sampler Class: Introduced the
Sampler
class, a flexible utility for sampling from various statistical distributions.
Distribution Support
- The class supports multiple distributions, including:
- Log-normal (
lognormvariate
): Usesmath.log(self.scale)
for the mean of the underlying normal distribution. - Normal (
normalvariate
): Standard normal distribution with specified mean and standard deviation. - Exponential (
expovariate
): Uses1 / self.scale
as the rate parameter (lambda). - Von Mises (
vonmisesvariate
): Circular distribution with specified mean and concentration. - Gamma (
gammavariate
): Two-parameter distribution with shape and scale. - Gaussian (
gauss
): Similar to normalvariate, with mean and standard deviation. - Beta (
betavariate
): Distribution defined on the interval [0, 1] with two shape parameters. - Pareto (
paretovariate
): Heavy-tailed distribution with a single shape parameter. - Weibull (
weibullvariate
): Distribution with shape and scale parameters.
- Log-normal (
Configurable Parameters
- The class requires configuration of key parameters:
distribution
: Specifies the distribution to sample from (required).shape
: Shape parameter for the distribution, controlling the spread and skewness. For log-normal, it represents sigma of the underlying normal distribution (required).scale
: Scale parameter for the distribution, shifting the distribution and determining its median. For log-normal, it represents exp(mu) of the underlying normal distribution. For exponential, it is the inverse of the rate parameter (1/lambda) (required).lower_bound
: Optional lower bound for the sampled value, defaulting toNone
(no lower bound).upper_bound
: Optional upper bound for the sampled value, defaulting toNone
(no upper bound).random_seed
: Optional seed for the random number generator, allowing for reproducibility.random_instance
: Optional custom instance ofrandom.Random
for generating random numbers.
[0.11.8] 01.08.2024
Changed
find_most_similar()
andfind_most_similar()
was fixed for the edge case when no comparison texts are provided. If no texts are provided,find_most_similar_with_scores()
now returns [(some negative number, input_text), 0.0)], andfind_most_similar()
returns (some negative number, input_text). Docstrings of both method were also changed to reflect this change.
[0.11.7] 01.08.2024
Changed
find_most_similar()
andfind_most_similar()
was fixed for the edge case when no comparison texts are provided. If no texts are provided,find_most_similar_with_scores()
now returns [(some negative number, input_text), 1.0)], andfind_most_similar()
returns (some negative number, input_text). Docstrings of both method were also changed to reflect this change.
[0.11.6] 31.07.2024
Changed
_LRUCache
and_LFUCache
now supports the in operator. Beforehand the work of theAsyncCache
was incorrect.
[0.11.5] 31.07.2024 YANKED
Changed
async_cache()
is now support correctly methods.
[0.11.4] 31.07.2024 YANKED
Changed
async_cache()
is now support correctly methods.
[0.11.3] 30.07.2024
Added
- New class
AsyncCache
which supports both LFU (Least Frequently Used) and LRU (Least Recently Used) caching policies with optional Time-to-Live (TTL) for cache entries. Additional profiling and statistics gathering for cache hits, misses, average, max, and min execution times. - New decorator
async_cache()
for applying asynchronous caching to a function with configurable caching policy and TTL. HashableWrapper
class: This class wraps an object to make it hashable. It provides a fallback for objects that do not natively support hashing by using the string representation for hashing.make_hashable()
function: A utility to convert various types of objects into hashable types. This function handles mappings, iterables, and objects with the__hash__
method. Non-hashable objects are wrapped in aHashableWrapper
to ensure compatibility as dictionary keys or set members.is_iterable()
function: A utility to check if a value is iterable, excludingNone
,str
, andbytes
.is_mapping()
function: A utility to check if a value is a mapping (dict-like). It determines this by checking whether the given value implements the.items()
method and whether that method is callable.
[0.11.2] 30.07.2024
Added
-
Introduced
is_running_in_main_thread()
utility function to check if the current thread is the main thread. -
A configuration initializer
initConfig()
has been added. You MUST callinitConfig()
from the MainThread before usinglift_to_async()
. It initializes the necessary configuration for using thelift_to_async()
method. -
lift_to_async()
primitive ensures seamless execution of async functions in a synchronous environment, while preserving the context of ContextVar instances. It makes easier to integrate async calls within existing synchronous codebases.
Changed
- In the
RLock
class, the comparison of the lock owner with the current thread/task was changed from using the equality operator (==
) to theis
operator. This change should not affect the functionality because the__eq__
method was not overridden.
[0.11.1] 23.07.2024
Added
-
RLock
class to provide a reentrant lock that supports both synchronous and asynchronous operations. This lock ensures fairness by handling acquisition requests in the order they are made, both for threads and asynchronous tasks. See https://alex-ber.medium.com/a6b9a9021be8 for more details -
LockingProxy
class to provide a comprehensive locking mechanism, ensuring thread-safe access and operations for various object types including iterables, async iterables, attributes, and callables. See https://alex-ber.medium.com/7a7a14021427 for more details. -
prof_to_callgrind.sh
script for converting.prof
files to.callgrind
format using Docker. See https://alex-ber.medium.com/converting-prof-files-to-callgrind-f6ae56fae0d3 for more details. -
prof_to_callgrind.py
to handle the conversion ofprofile
statistics tocallgrind
files. See https://alex-ber.medium.com/converting-prof-files-to-callgrind-f6ae56fae0d3 for more details.
Profiling Script with High-Resolution Timer
This script demonstrates how to set up a cProfile profiler in Python using a high-resolution timer based on time.perf_counter_ns()
.
import time
import cProfile
# Define a precise timer function using time.perf_counter_ns()
def precise_timer():
return time.perf_counter_ns()
# Create a cProfile.Profile object with the precise timer function
profiler = cProfile.Profile(timer=precise_timer)
# Usage note:
# The profiler is now configured to use the precise_timer function,
# which provides higher resolution timing measurements in nanoseconds.
Misc
-
pyproject.toml
to specify build system requirements and configurations, ensuring compatibility withsetuptools
>=42 andwheel
. -
validate_param()
function to check for the presence of required parameters and raise a ValueError if they are missing. -
RootMixin
class with an initializer that stops the delegation chain -
LockingIterableMixin
to provide locking for iterable objects, ensuring thread-safe iteration. -
LockingAsyncIterableMixin
to provide locking for asynchronous iterable objects, ensuring thread-safe iteration. -
LockingAccessMixin
to provide locking for attribute access, ensuring thread-safe access to object attributes. -
LockingCallableMixin
to provide locking for callable objects, ensuring thread-safe execution of callable objects. -
LockingDefaultLockMixin
to provide a default lock if none is provided during initialization. -
LockingBaseLanguageModelMixin
to provide locking for BaseLanguageModel objects, ensuring thread-safe access. -
LockingDefaultAndBaseLanguageModelMixin
to combine default lock and BaseLanguageModel locking.
[0.11.0] 22.06.2024
Added
- New module
in_memory_similarity_search
added.
This module is usable to calculate cosine similarity for small number of vectors.
It has 2 public function and 1 type hint.
-
find_most_similar()
- this function identifies the most similar text to a given input text from a list of provided texts. It uses an embedding class instance to convert texts into vectors and calculates the cosine similarity based on the specified Euclidean norm. The function returns a tuple containing the index and the most similar text. -
find_most_similar_with_scores()
- this function finds the most similar texts to a given input text from a list of provided texts and returns their cosine similarity scores. It uses an embedding class instance to convert texts into vectors and calculates the similarity based on the specified Euclidean norm. The function returns a list of tuples, each containing the index, text, and similarity score.
See https://alex-ber.medium.com/in-memory-similarity-search-998582fbb802 for details.
Changed
- Removed leftover from multidispatch dependecy.
- Rename python3 to python across the documentation.
[0.10.2] 05.05.2024
- Lose packaging constraint to packaging>=23.2.
- Fixed README.md to include packaging>=23.2.
[0.10.1] 31.05.2024
Changed
- Remove no longer supported Python versions 3.6 and 3.7 from setup's classifier.
[0.10.0] 31.05.2024
Changed
- Fixed README.md to include packaging<24.0,>=23.2
- Minimum library requirement is Python 3.8 now (not 3.9).
- Dockerfile's base docker image was changed to be based on Python 3.8 (not 3.9).
- importlib-metadata and it's dependency zipp are back. This is backport from Python 3.9.
It is a library that provides access to the metadata of installed packages. It was
originally developed as a backport of the
importlib.metadata
module introduced in Python 3.8, allowing users of earlier Python versions to access package metadata in a consistent way. It is used bybuild
.
[0.9.1] 31.05.2024
Changed
- Fixed README.md to reflect changes in 0.9.0.
[0.9.0] 31.05.2024
Changed
-
Minimum library requirement is Python 3.9 now.
-
Dockerfile's base docker image was changed to be based on Python 3.9
-
Some functionality was moved from dropped method_overloading_test.py to importer_test.py
-
Implementation of inspects.ismethod() and inspects.has_method() was changed.
-
inspect_test.py was changed. inspects.has_method() now expected to return False on descriptors, including property, (as it should in the first place).
-
In Dockerfile setuptools was downgraded from 67.8.0 to 65.6.3. See https://stackoverflow.com/questions/76043689/pkg-resources-is-deprecated-as-an-api#comment136784284_76044568
-
In Dockerfile reference to requirements-md.txt was droped.
-
To requirements.in, req-piptools.txt and req-tests.txt packaging<24.0,>=23.2 was added.
-
All requirements.txt was regenerated, so version has changed:
-
importlib-metadata (and it's dependency zipp) were dropped.
-
bcrypt upgraded from 4.1.1 to 4.1.3.
-
build from 1.0.3 to 1.2.1.
-
cryptography from 41.0.7 to 42.0.7.
-
exceptiongroup from 1.2.0 to 1.2.1.
-
hiyapyco from 0.5.4 to 0.6.0.
-
jinja2 from 3.1.2 to 3.1.4.
-
markupsafe from 2.1.3 to 2.1.5.
-
paramiko from 3.3.1 to 3.4.0
-
pip-tools from 7.3.0 to 7.4.1
-
pluggy from 1.3.0 to 1.5.0
-
pycparser 2.21 to 2.22.
-
pyopenssl from 23.3.0 to 24.1.0.
-
pyproject-hooks from 1.0.0 to 1.1.0.
-
python-dotenv from 1.0.0 to 1.0.1
-
wheel from 0.42.0 to 0.43.0
-
(minor) Import to dropped enums.py was removed from parsers_test.py
Added
- inspects.resolve_function_args() - maps both explicit and default arguments of a function call by parameter name. It merges args and kwargs, taking into account default values from func. See https://alex-ber.medium.com/my-inspect-module-aa2d311246cb for more details.
- inspects.update_function_defaults() - decorator to change and remove default value. See https://alex-ber.medium.com/my-inspect-module-aa2d311246cb for more details.
- pprint.py module. This module effectively changes the default values of the standard
pprint.pprint
module. Intended Usage: See https://alex-ber.medium.com/my-pprint-module-f25a7b695e5f for more details.
Instead of:
from pprint import pprint
use
from alexber.utils.pprint import pprint
The defaults are:
indent
: 4width
: 120depth
: Nonestream
: Nonecompact
: Falsesort_dicts
: Falseunderscore_numbers
: False
See docstring of pprint.py module for more details.
Removed
- Optional dependency alex-ber-utils[md] was removed. Unit-tests for multidispatch was removed. Also files req-md.txt and requirements-md.txt was deleted.
- Module enums was removed. It does monkey-patching to standard library's enums, that breaks them in Python 3.9+.
[0.8.0] 04.12.2023
Changed
- In setup.cfg flag mock_use_standalone_module was changed to false (to use unittest.mock).
- Many version of the packages in extra was updated to latest:
- python-dotenv from 0.15.0 to 1.0.0.
- MarkupSafe is downgraded from 2.1.3 to 2.0.1
- bcrypt is upgraded from 3.2.0 to 4.1.1
- cffi is upgraded from 1.14.5 to 1.16.0
- cryptography is upgraded from 38.0.4 to to 41.0.7
- fabric is upgraded from 2.5.0 to 3.2.2
- invoke is upgraded from 1.7.3 to 2.2.0
- paramiko is upgraded from 2.7.2 to 3.3.1
- pycparser is upgraded from 2.20 to 2.21
- PyNaCl is upgraded from 1.3.0 to 1.5.0
- HiYaPyCo is upgraded from 0.5.1 to 0.5.4
Added
- new extra-group, with name requirements-piptools.txt is added.
- alexber.utils.props.lazyproperty is added. TODO: add test for it
- New file requirements.in that have all high-level dependecies together.
- New file requirements.all that have pinned low-level dependecies resolution.
Removed
- mock package was removed. pytest will use unittest.mock. See Changed p.1 above.
- six was removed.
[0.7.0] - 04-08-2023
Changed
- Upgrade pyparsing==2.4.7 to 3.1.1.
- Upgrade cryptography from 3.4.7 to 41.0.3.
- Upgrade invoke from 1.4.1 to 1.7.3.
- Upgrade six from 1.15.0 to 1.16.0.
- Upgrade colorama from 0.4.3 to 0.4.4.
- Change declaration of namespace to
declare_namespace()
mechanism.
Added
- Explicit dependency on pyOpenSSL==22.1.0 (lowest version where cryptography version is pinned). cryptography's and pyOpenSSL's version change should be in sync.
[0.6.6] - 13-06-2021
Added
stdLogging
module. The main function isinitStream()
. This is Thin adapter layer that redirects stdout/stderr (or any other stream-like object) to standard Python's logger. Based on https://github.com/fx-kirin/py-stdlogging/blob/master/stdlogging.py See https://github.com/fx-kirin/py-stdlogging/pull/1 Quote from https://stackoverflow.com/questions/47325506/making-python-loggers-log-all-stdout-and-stderr-messages : "But be careful to capture stdout because it's very fragile". I decided to focus on redirecting stderr only to the logger. If you want you can also redirect stdout, by making 2 calls to initStream() package-level method. But, because of https://unix.stackexchange.com/questions/616616/separate-stdout-and-stderr-for-docker-run it is sufficient only to do it for stderr for me. See [https://alex-ber.medium.com/stdlogging-module-d5d69ff7103f] for details.
Changed
Doockerfiles
base-image. Now, you can transparentely switch betwee AMD64 to ARM 64 proccessor.cffi
dependency from 1.14.3 to 1.14.5.cryptography
dependency from 3.1.1 to 3.4.7.
[0.6.5] - 12-04-2021
Added
-
FixRelCwd
context-manager inmains
module - This context-manager temporary changes current working directory to the one where relPackage is installed. What if you have some script or application that use relative path and you want to invoke in from another directory. To get things more complicated. maybe your “external” code also use relative path, but relative to another directory. See [https://alex-ber.medium.com/making-more-yo-relative-path-to-file-to-work-fbf6280f9511] for details. -
GuardedWorkerException
context-manager inmains
module - context manager that mitigate exception propogation from another process. It is very difficult if not impossible to pickle exceptions back to the parent process. Simple ones work, but many others don’t. For example, CalledProcessError is not pickable (my guess, this is because of stdout, stderr data-members). This means, that if child process raise CalledProcessError that is not catched, it will propagate to the parent process, but the propagation will fail, apparently because of bug in Python itself. This cause pool.join() to halt forever — and thus memory leak! See [https://alex-ber.medium.com/exception-propagation-from-another-process-bb09894ba4ce] for details. -
join_files()
function infiles
module - Suppose, that you have some multi-threaded/multi-process application where each thread/process creates some file (each thread/process create different file) and you want to join them to one file. See [https://alex-ber.medium.com/join-files-cc5e38e3c658] for details.
Changed
-
fixabscwd()
function inmains
module - minour refactoring - moving out some internal helper function for reuse in new function. -
Base docker image version to alexberkovich/alpine-anaconda3:0.2.1-slim. alexberkovich/alpine-anaconda3:0.1.1 has some minor changes relative to alexberkovich/alpine-anaconda3:0.1.1. See [https://github.com/alex-ber/alpine-anaconda3/blob/master/CHANGELOG.md] for details.
Updated
Documentation
- See [https://github.com/alex-ber/AlexBerUtils/issues/8] Config file from another directory is not resolved
(using
argumentParser
with--general.config.file
can't be passed toinit_app_conf.parse_config()
)
[0.6.4] - 12/12/2020
Changed
-
Base docker image version to alexberkovich/alpine-anaconda3:0.1.1-slim. alexberkovich/alpine-anaconda3:0.1.1 has some minor changes relative to alexberkovich/alpine-anaconda3:0.1.0. See [https://github.com/alex-ber/alpine-anaconda3/blob/master/CHANGELOG.md] for details. alexberkovich/alpine-anaconda3:0.1.1-slim is "slim" version of the same docker image, most unused packaged are removed.
-
update versions to pip==20.3.1 setuptools==51.0.0 wheel==0.36.1
Removed
- Script check_d.py
[0.6.3] - 18/11/2020
Changed
- Base docker image version to alexberkovich/alpine-anaconda3:0.1.0, it has fix for potential security risk: Git was changed not to store credential as plain text, but to keep them in memory for 1 hour, see https://git-scm.com/docs/git-credential-cache
Updated
Documentation
- My
deploys
module [https://medium.com/analytics-vidhya/my-deploys-module-26c5599f1b15 for documentation] is updated to containfix_retry_env()
function inmains
module.
Added
Documentation
fix_retry_env()
function inmains
module. [https://alex-ber.medium.com/make-path-to-file-on-windows-works-on-linux-402ed3624f66]
[0.6.2] - 17/11/2020
Deprecation
method_overloading_test.py
is deprecated and will be removed once AlexBerUtils will support Python 3.9. It will happen approximately at 01.11.2021.
This test uses multidispatch
project that wasn't updated since 2014.
In Python 3.8 it has following warning:
multidispatch.py:163: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.9 it will stop working from collections import MutableMapping
Added
- class
OsEnvrionPathRetry
, functionfix_retry_env()
tomains
module.
Changed
OsEnvrionPathExpender
- refactored, functionality is preserved.
[0.6.1] - 16/11/2020
Added
-
optional Dockerfile
-
optional .env.docker for reference.
-
Support of Python 3.8 is validated, see https://github.com/alex-ber/AlexBerUtils/issues/5
-
Email formatting changed in Python 3.8, see https://github.com/alex-ber/AlexBerUtils/issues/7
Note that it is possible that 7bit
will be replaced with 8bit
as Content-Transfer-Encoding
,
that I'm considering as ok.
-
check_all.py
to run all unit test. -
check_d.py
for sanity test. -
.dockerignore
-
requirements*.txt - dependencies version changed, see https://github.com/alex-ber/AlexBerUtils/issues/6
-
Because of pytest upgrade
conftest.py
was changed:pytest_configure()
was added to support dynamically used marks. -
In
ymlparsers_test.py
deprecation warning removed (it will be error in Python 3.9)collections.Mapping
was changed tocollections.abc.Mapping
.
Changed
- README.MD added section about Docker usage.
- setup.py to indicate support of Python 3.8
[0.5.3] - 10/09/2020
Changed
alexber.utils.emails.initConfig
is fixed. Before this default variables where ignored.- 2 Unit tests for
init_app_conf
are fixed. These fix are minors.
Documentation
importer
module [https://medium.com/analytics-vidhya/how-to-write-easily-customizable-code-8b00b43406b2]fixabscwd()
function inmains
module. [https://medium.com/@alex_ber/making-relative-path-to-file-to-work-d5d0f1da67bf]fix_retry_env()
function inmains
module. [https://alex-ber.medium.com/make-path-to-file-on-windows-works-on-linux-402ed3624f66]- My
parser
module [https://medium.com/analytics-vidhya/my-parser-module-429ed1457718] - My
ymlparsers
module [https://medium.com/analytics-vidhya/my-ymlparsers-module-88221edf16a6] - My major
init_app_conf
module [https://medium.com/analytics-vidhya/my-major-init-app-conf-module-1a5d9fb3998c] - My
deploys
module [https://medium.com/analytics-vidhya/my-deploys-module-26c5599f1b15] - My
emails
module [https://medium.com/analytics-vidhya/my-emails-module-3ad36a4861c5] - My
processinvokes
module [https://medium.com/analytics-vidhya/my-processinvokes-module-de4d301518df]
[0.5.2] - 21/06/2020
Added
path()
function inmains
module. For older Python version usesimportlib_resources
module. For newer version built inimportlib.resources
.load_env()
function inmains
module. Added kwargs forwarding. if dotenv_path or stream is present it will be used. if ENV_PCK is present, dotenv_path will be constructed from ENV_PCK and ENV_NAME. Otherwise, kwargs will be forwarded as is to load_dotenv.fix_env()
function inmains
module. For each key in ENV_KEYS, this method prepends full_prefix to os.environ[key]. full_prefix is calculated as absolute path of__init__.py
of ENV_PCK.
Changed
processinvokes
function run_sub_process
- documentation typo fixed.
Lower Python version to 3.6.
[0.5.1] - 06-05-2020
Added
-
mains
module explanation article https://medium.com/@alex_ber/making-relative-path-to-file-to-work-d5d0f1da67bf is published. -
fabs
module. It adds cp method to fabric.Connection.
This method is Linux-like cp command. It copies single file to remote (Posix) machine.
-
Spited dependency list for setup.py req.txt (inexact versions, direct dependency only) and for reproducible installation requirements.txt (exact versions, all, including transitive dependencies).
-
Added req-fabric.txt, requirements-fabric.txt - Fabric, used in
fabs
module. -
Added req-yml.txt, requirements-yml.txt - Yml-related dependencies, used in ymlparsers.py and in init_app_conf.py, deploys.py; optionally used in ymlparsers_extra.py, emails.py.
Main dependency is HiYaPyCo. I'm using feature that is availlable in the minimal version.
HiYaPyCo depends upon PyYAML and Jinja2. Limitations for Jinja2 is from HiYaPyCo project.
-
Added req-env.txt, requirements-env.txt - pydotenv, optionally used in deploys.py.
-
Added
inspects.has_method
(cls, methodName). Check if class cls has method with name methodName directly, or in one of it's super-classes. -
Added
pareser.parse_sys_args
function parses command line arguments. -
Added
ymlparsers
module -load
/safe_dump
a Hierarchical Yml files. This is essentially wrapper arround HiYaPyCo project with streamlined and extended API and couple of work-arrounds.
Note: this module doesn't use any package-level variables in hiYaPyCo module, including hiYaPyCo.jinja2env.
This module do use Jinja2's Environment
.
It also has another defaults for load
/safe_dump
methods.
They can be overridden in initConfig()
function.
safe_dump()
method supports simple Python objects like primitive types (str, integer, etc), list, dict, OrderedDict.
as_str()
- convenient method for getting str representation of the data,
for example of dict.
DisableVarSubst
- use of this context manager disables variable substation in the load()
function.
initConfig
- this method reset some defaults. If running from the MainThread, this method is idempotent.
- Added
init_app_conf
major module.
The main function is parse_config
. This function parses command line arguments first.
Than it parse yml files. Command line arguments overrides yml files arguments.
Parameters of yml files we always try to convert on best-effort basses.
Parameters of system args we try convert according to implicit_convert
param.
If you supply implicit_convert=True
, than mask_value()
will be applied to the flat map (first parameter).
Otherwise, implicit_convert
wiil have the value that was set in intiConfig()
. By default it is True
.
Command line key --general.profiles or appropriate key default yml file is used to find 'profiles'. Let suppose, that --config_file is resolved to config.yml. If 'profiles' is not empty, than it will be used to calculate filenames that will be used to override default yml file. Let suppose, 'profiles' resolved to ['dev', 'local']. Than first config.yml will be loaded, than it will be overridden with config-dev.yml, than it will be overridden with config-local.yml. At last, it will be overridden with system args. This entry can be always be overridden with system args.
ymlparsers
and parser
modules serves as Low-Level API for this module.
mask_value()
implemented as a wrapper to parsers.safe_eval()
method with support for boolean
variables. This implementation is used to get type for arguments that we get from system args.
This mechanism can be easily replaced with your own one.
to_convex_map()
This method receives dictionary with 'flat keys', it has simple key:value structure
where value can't be another dictionary.
It will return dictionary of dictionaries with natural key mapping,
optionally, entries will be filtered out according to white_list_flat_keys and,
optionally, value will be implicitly converted to appropriate type.
In order to simulate dictionary of dictionaries 'flat keys' compose key from outer dict with key from inner dict separated with dot. For example, 'general.profiles' 'flat key' corresponds to convex map with 'general' key with dictionary as value that have one of the keys 'profiles' with corresponding value.
If you supply implicit_convert=True
, than mask_value()
will be applied to the values of the received flat dictionary.
Otherwise, implicit_convert
wiil have the value that was set in intiConfig()
. By default it is True.
merge_list_value_in_dicts
- merges value of 2 dicts. This value represents list of values.
Value from flat_d is roughly obtained by flat_d[main_key+'.'+sub_key].
Value from d is roughly obtained by d[main_key][sub_key].
If you supply implicit_convert=True
, than mask_value()
will be applied to the flat map (first parameter).
Otherwise, implicit_convert
wiil have the value that was set in intiConfig()
. By default it is True
.
initConfig
- you can set default value of implicit_convert
. By default it is True
.
This parameters is used if implicit_convert
wasn't explicitly supplied. This method is idempotent.
- Added
deploys
module. This module is usable in your deployment script. See alsofabs
module.
This method use parsers
, ymlparsers,
init_app_confas it's low-level API.
init_app_conf` usage is limited.
The main function is load_config()
. It is simplified method for parsing yml configuration file with optionally
overrided profiles only. See init_app_conf.parse_config()
for another variant.
split_path
- Split filename in 2 part parts by split_dirname. first_part will ends with split_dirname.
second_part will start immediately after split_dirname.
add_to_zip_copy_function
- Factory method that returns closure that can be used as copy_function param in
shutil.copytree()
.
- Added
emails
module. This module contains extensions of the logging handlers. This module optionally depends onymlparseser
module. It is better to useEmailStatus
context manager with configuredemailLogger
. It is intended to configure first youremailLogger
withOneMemoryHandler
(together withSMTPHandler
). Than the code block that you want to aggregate log messages from is better to be enclosed withEmailStatus
context manager.
alexber.utils.emails.SMTPHandler
is customization of logging.handlers.SMTPHandler
. It's purpose is to connect to
SMTP server and actually send the e-mail. Unlike logging.handlers.SMTPHandler
this class expects for record.msg to be built EmailMessage.
You can also change use of underline SMTP class to SMTP_SSL, LMTP, etc.
This implementation is thread-safe.
alexber.utils.emails.OneMemoryHandler
is variant of logging.handlers.MemoryHandler
. This handler aggregates
log messages until FINISHED
log-level is received or application is going to terminate abruptly (see docstring
of calc_abrupt_vars()
method for the details) and we have some log messages in the buffer. On such event
all messages (in the current Thread) are aggregated to the single EmailMessage
. The subject of the EmailMessage
is determined by get_subject()
method.
If you want to change delimeters used to indicate variable declaration inside template, see docstring of the
get_subject()
method.
It is better to use EmailStatus
context manager with configured emailLogger. See docstring of EmailStatus
.
This implementation is thread-safe.
alexber.utils.emails.EmailStatus
- if contextmanager exits with exception (it fails), than e-mail with
subject formatted with faildargs and faildkwargs will be send.
Otherwise, e-mail with subject formatted with successargs and successkwargs will be send.
All messages (in the current Thread) will be aggregated to one long e-mail with the subject described in
OneMemoryHandler.get_subject()
method.
alexber.utils.emails.initConfig
- this method reset some defaults. This method is idempotent.
By default, SMTP
class from smtplib
is used to send actual e-mail. You can change it to SMTP_SSL
, LMTP
,
or another class by specifying default_smpt_cls_name.
You can also specified default port for sending e-mails.
processInvokes
module has one primary function - run_sub_process()
This method run subprocess and logs it's out
to the logger. This method is sophisticated decorator to subprocess.run()
. It is useful, when your subprocess
run's a lot of time and you're interesting to receive it's stdout
and stderr
. By default, it's streamed to log.
You can easily customize this behavior, see initConig()
method.
initConig()
This method can be optionally called prior any call to another function in this module. You can use your
custom class for the logging. For example, FilePipe.
Changed
-
Spited dependency list for setup.py req.txt (inexact versions, direct dependency only) and for reproducible installation requirements.txt (exact versions, all, including transitive dependencies).
-
README.md changed, added section 'Alternatively you install install from requirements file:'. Some other misc changed done.
-
CHANGELOG.md version 0.4.1 misc changes.
-
Misc improvement in unit tests.
-
Fixed
parser.safe_eval
- safe_eval('%(message)s') was blow up, now it returns value as is. See https://github.com/alex-ber/AlexBerUtils/issues/2 -
Enhanced
importer.importer
- added support for PEP 420 (implicit Namespace Packages).
Namespace packages are a mechanism for splitting a single Python package across multiple directories on disk. When interpreted encounter with non-empty path attribute it adds modules found in those locations to the current package. See https://github.com/alex-ber/AlexBerUtils/issues/3 -
In all documentation refference to
pip3
was changed topython3 -m pip
[0.4.1] - 2020-04-02
BREAKING CHANGE I highly recommend not to use 0.3.X versions.
Removed
- module
warns
is droped
Changed
- Limitation::
mains
module wasn't tested with frozen python script (frozen using py2exe).
- module
mains
is rewritten. FunctioninitConf
is dropped entirely. - module
mains
now works with logger and with warnings (it was wrong decision to work with warnings).
[0.3.4] - 2020-04-02
Changed
- CHANGELOG.md fixed
warns
module bug fixed, now warnings.warn() works.- FixabscwdWarning is added to simplify warnings disabling.
- Changing how
mains
module usewarns
.
[0.3.3] - 2020-04-02
Changed
- CHANGELOG.md fixed
[0.3.2] - 2020-04-01
Changed
- To REAMDE.md add
Installing new version
section - Fix typo in REAMDE.md (tests, not test).
- Fixing bug: now, you're able to import package in the Python interpreter (
setups.py
fixed) - Fixing bug:
warns
module now doesn't change log_level in the preconfigured logger in any cases. - BREAKING CHANGE: In
mains
module methodwarnsInitConfig()
was renamed tomainInitConfig()
Also singature was changed. mains
module minor refactored.
Added
- Unit tests are added for
warns
module - Unit tests are added for
mains
module
[0.3.1] - 2020-04-01
Changed
- Tests minor improvements.
- Excluded tests, data from setup.py (from being installed from the sdist.)
- Created MANIFEST.in
Added
warns
module is added:
It provides better integration between warnings and logger.
Unlike logging._showwarning()
this variant will always go through logger.
warns.initConfig()
has optional file parameter (it's file-like object) to redirect warnings.
Default value is sys.stderr
.
If logger for log_name
(default is py.warnings
) will be configured before call to showwarning()
method,
than warning will go to the logger's handler with log_level
(default is logging.WARNING
).
If logger for log_name
(default is py.warnings
) willn't be configured before call to showwarning() method,
than warning will be done to file
(default is sys.stderr
) with log_level
(default is logging.WARNING
).
main
module is added:
main.fixabscwd()
changes os.getcwd()
to be the directory of the __main__
module.
main.warnsInitConfig()
reexports warns.initConfig()
for convenience.
Added
- Tests for alexber.utils.thread_locals added.
[0.2.5] - 2019-05-22
Changed
- Fixed bug in UploadCommand, git push should be before git tag.
[0.2.4] - 2019-05-22
Changed
- Fixed bug in setup.py, incorrect order between VERSION and UploadCommand (no tag was created on upload)
[0.2.1] - 2019-05-22
Changed
- setup url fixed.
- Added import of Enum to alexber.utils package.
[0.2.0] - 2019-05-22
Changed
- setup.py - keywords added.
[0.1.1] - 2019-05-22
Changed
- README.md fixed typo.
[0.1.0] - 2019-05-22
Changed
- alexber.utils.UploadCommand - bug fixed, failed on git tag, because VERSION was undefined.
[0.0.1] - 2019-05-22
Added
-
alexber.utils.StrAsReprMixinEnum - Enum Mixin that has str() equal to repr().
-
alexber.utils.AutoNameMixinEnum- Enum Mixin that generate value equal to the name.
-
alexber.utils.MissingNoneMixinEnum - Enum Mixin will return None if value will not be found.
-
alexber.utils.LookUpMixinEnum - Enim Mixin that is designed to be used for lookup by value.
If lookup fail, None will be return. Also, str() will return the same value as repr().
-
alexber.utils.threadlocal_var, get_threadlocal_var, del_threadlocal_var.
Inspired by https://stackoverflow.com/questions/1408171/thread-local-storage-in-python
-
alexber.utils.UploadCommand - Support setup.py upload.
UploadCommand is intented to be used only from setup.py
It's builds Source and Wheel distribution.
It's uploads the package to PyPI via Twine.
It's pushes the git tags.
-
alexber.utils.uuid1mc is is a hybrid between version 1 & version 4. This is v1 with random MAC ("v1mc").
uuid1mc() is deliberately generating v1 UUIDs with a random broadcast MAC address.
The resulting v1 UUID is time dependant (like regular v1), but lacks all host-specific information (like v4).
Note: somebody reported that ran into trouble using UUID1 in Amazon EC2 instances.
-
alexber.utils.importer.importer - Convert str to Python construct that target is represented.
-
alexber.utils.importer.new_instance - Convert str to Python construct that target is represented. args and kwargs will be passed in to appropriate new() / init() / init_subclass() methods.
-
alexber.utils.inspects.issetdescriptor - Return true if the object is a method descriptor with setters.
But not if ismethod() or isclass() or isfunction() are true.
-
alexber.utils.inspects.ismethod - Return false if object is not a class and not a function. Otherwise, return true iff signature has 2 params.
-
alexber.utils.parsers.safe_eval - The purpose of this function is convert numbers from str to correct type.
This function support convertion of built-in Python number to correct type (int, float)
This function doesn't support decimal.Decimal or datetime.datetime or numpy types.
-
alexber.utils.parsers.is_empty - if value is None returns True.
if value is empty iterable (for example, empty str or emptry list),returns true otherwise false.
Note: For not iterable values, behaivour is undefined.
-
alexber.utils.parsers.parse_boolean - if value is None returns None.
if value is boolean, it is returned as it is. if value is str and value is equals ignoring case to "True", True is returned. if value is str and value is equals ignoring case to "False", False is returned.
For every other value, the answer is undefined.
-
alexber.utils.props.Properties - A Python replacement for java.util.Properties class
This is modelled as closely as possible to the Java original.
Created - Anand B Pillai abpillai@gmail.com.
Update to Python 3 by Alex.
Also there are some tweeks that was done by Alex.
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