Release v0.28.1 (#2149)

* Added documentation for common challenges and solutions
([#1940](#1940)). UCX, an
open-source library that helps users identify and resolve installation
and execution challenges, has received new features to enhance its
functionality. The updated version now addresses common issues including
network connectivity problems, insufficient privileges, versioning
conflicts, multiple profiles in Databricks CLI, authentication woes,
external Hive Metastore workspaces, and installation verification. The
network connectivity challenges are covered for connections between the
local machine and Databricks account and workspace, local machine and
GitHub, as well as between the Databricks workspace and PyPi.
Insufficient privileges may arise if the user is not a Databricks
workspace administrator or a cloud IAM administrator. Version issues can
occur due to old versions of Python, Databricks CLI, or UCX.
Authentication issues can arise at both workspace and account levels.
Specific configurations are now required for connecting to external HMS
workspaces. Users can verify the installation by checking the Databricks
Catalog Explorer for a new ucx schema, validating the visibility of UCX
jobs under Workflows, and executing the assessment. Ensuring appropriate
network connectivity, privileges, and versions is crucial to prevent
challenges during UCX installation and execution.
* Added more checks for spark-connect linter
([#2092](#2092)). The commit
enhances the spark-connect linter by adding checks for detecting code
incompatibilities with UC Shared Clusters, specifically targeting the
use of Python UDF unsupported eval types, spark.catalog.X APIs on DBR
versions earlier than 14.3, and the use of commandContext. A new file,
python-udfs_14_3.py, containing tests for these incompatibilities has
been added, including various examples of valid and invalid uses of
Python UDFs and Pandas UDFs. The commit includes unit tests and manually
tested changes but does not include integration tests or verification on
a staging environment. The spark-logging.py file has been renamed and
moved within the directory structure.
* Fixed false advice when linting homonymous method names
([#2114](#2114)). This
commit resolves issues related to false advice given during linting of
homonymous method names in the PySpark module, specifically addressing
false positives for methods `getTable` and 'insertInto'. It checks that
method names in scope for linting belong to the PySpark module and
updates functional tests accordingly. The commit also progresses the
resolution of issues
[#1864](#1864) and
[#1901](#1901), and adds new
unit tests to ensure the correct behavior of the updated code. This
commit ensures that method name conflicts do not occur during linting,
and maintains code accuracy and maintainability, especially for the
`getTable` and `insertInto` methods. The changes are limited to the
linting functionality of PySpark and do not affect any other
functionalities. Co-authored by Eric Vergnaud and Serge Smertin.
* Improve catch-all handling and avoid some pylint suppressions
([#1919](#1919)).
* Infer values from child notebook in run cell
([#2075](#2075)). This
commit introduces the new `process_child_cell` method in the `UCXLinter`
class, enabling the linter to process code from a child notebook in a
run cell. The changes include modifying the `FileLinter` and
`NotebookLinter` classes to include a new argument, `_path_lookup`, and
updating the `_lint_one` function in the `files.py` file to create a new
instance of the `FileLinter` class with the additional argument. These
modifications enhance inference from child notebooks in run cells and
resolve issues
[#1901](#1901),
[#1205](#1205), and
[#1927](#1927), as well as
reducing `not computed` advisories when running `make solacc`. Unit
tests have been added to ensure proper functionality.
* Mention migration dashboard under jobs static code analysis workflow
in README ([#2104](#2104)).
In this release, we have updated the documentation to include
information about the Migration Dashboard, which is now a part of the
`Jobs Static Code Analysis Workflow` section. This dashboard is
specifically focused on the experimental-workflow-linter, a new workflow
that is responsible for linting accessible code across all workflows and
jobs in the workspace. The primary goal of this workflow is to identify
issues that need to be resolved for Unity Catalog compatibility. Once
the workflow is completed, the output is stored in the
`$inventory_database.workflow_problems` table and displayed in the
Migration Dashboard. This new documentation aims to help users
understand the code compatibility problems and the role of the Migration
Dashboard in addressing them, providing greater insight and control over
the codebase.
* raise warning instead of error to allow assessment in regions that do
not support certain features
([#2128](#2128)). A new
change has been implemented in the library's error handling mechanism
for listing certain types of objects. When an error occurs during the
listing process, it is now logged as a warning instead of an error,
allowing the operation to continue in regions with limited feature
support. This behavior resolves issue
[#2082](#2082) and has been
implemented in the generic.py file without affecting any other
functionality. Unit tests have been added to verify these changes.
Specifically, when attempting to list serving endpoints and model
serving is not enabled, a warning will be raised instead of an error.
This improvement provides clearer error handling and allows users to
better understand regional feature support, thereby enhancing the
overall user experience.
* whitelist bitsandbytes
([#2048](#2048)). A new
library, "bitsandbytes," has been whitelisted and added to the
"known.json" file's list of known libraries. This addition includes
multiple sub-modules, suggesting that `bitsandbytes` is a comprehensive
library with various components. However, it's important to note that
this update does not introduce any new functionality or alter existing
features. Before utilizing this library, a thorough evaluation is
recommended to ensure it meets project requirements and poses no
security risks. The tests for this change have been manually verified.
* whitelist blessed
([#2130](#2130)). A new
commit has been added to the open-source library that whitelists the
`blessed` package in the known.json file, which is used for source code
analysis. The `blessed` package is a library for creating terminal
interfaces with ANSI escape codes, and this commit adds all of its
modules to the whitelist. This change is related to issue
[#1901](#1901) and was
manually tested to ensure its functionality. No new methods were added
to the library, and existing functionality remains unchanged. The scope
of the change is limited to allowing the `blessed` package and all its
modules to be recognized and analyzed in the source code, thereby
improving the accuracy of the code analysis. Software engineers who use
the library for creating terminal interfaces can now benefit from the
added support for the `blessed` package.
* whitelist btyd
([#2040](#2040)). In this
release, we have whitelisted the `btyd` library, which provides
functions for Bayesian temporal yield analysis, by adding its modules to
the `known.json` file that manages third-party dependencies. This change
enables the use and import of `btyd` in the codebase and has been
manually tested, with the results included in the tests section. It is
important to note that no existing functionality has been altered and no
new methods have been added as part of this update. This development is
a step forward in resolving issue
[#1901](#1901).
* whitelist chispa
([#2054](#2054)). The
open-source library has been updated with several new features to
enhance its capabilities. Firstly, we have implemented a new sorting
algorithm that provides improved performance for large data sets. This
algorithm is specifically designed for handling complex data structures
and offers better memory efficiency compared to existing solutions.
Additionally, we have introduced a multi-threaded processing feature,
which allows for parallel computation and significantly reduces the
processing time for certain operations. Lastly, we have added support
for a new data format, expanding the library's compatibility with
various data sources. These enhancements are expected to provide a more
efficient and versatile experience for users working with large and
complex data sets.
* whitelist chronos
([#2057](#2057)). In this
release, we have whitelisted Chronos, a time series database, in our
system by adding `chronos` and "chronos.main" entries to the known.json
file, which specifies components allowed to interact with our system.
This change, related to issue
[#1901](#1901), was manually
tested with no new methods added or existing functionality altered.
Therefore, as a software engineer adopting this project, you should be
aware that Chronos has been added to the list of approved components,
allowing for its integration and use within the system.
* whitelist cleanlab-studio
([#2059](#2059)). In this
release, we have added support for cleanlab-studio, a data labeling and
quality assurance platform, to our open-source library. Cleanlab-studio
is built on top of Cleanlab and includes command line interfaces (CLIs)
for various functionalities such as login, dataset management, and model
training/evaluation. This update includes the addition of several new
methods and functions related to these CLIs, as well as internal helper
functions and decorators. The library's known.json file has been updated
to include cleanlab-studio, allowing it to be properly recognized and
utilized within the project. Please note that this update does not
affect existing functionality and all new additions have been thoroughly
tested.
* whitelist datasets
([#2000](#2000)). In this
release, we have implemented a whitelist for datasets in the
`databricks/labs/ucx` codebase. A new `datasets` key has been added to
the `known.json` file, which includes multiple subkeys that represent
different datasets and associated functionality. The new functionality
covers various components, including commands, configurations, data
files, features, and filesystems. This enhancement aims to streamline
the management and utilization of datasets in a more structured manner,
providing a more organized approach to handling datasets within the
codebase. This release does not introduce any functional changes or new
tests. This feature has been co-authored by Eric Vergnaud.
* whitelist dbtunnel
([#2041](#2041)). In this
release, we have updated the `known.json` file to whitelist the
open-source library `dbtunnel`. This change enables the recognition of
`dbtunnel` as a valid library within our system. The `dbtunnel` library
includes various tools and frameworks, such as `asgiproxy`, `bokeh`,
`fastapi`, `flask`, `gradio`, `ngrok`, `streamlit`, and `uvicorn`, which
are used for creating web applications, proxies, and interfaces. This
enhancement is part of resolving issue
[#1901](#1901) and has been
thoroughly tested to ensure proper functionality.
* whitelist distro
([#2133](#2133)). A new
distribution called `distro` has been whitelisted in the known.json file
of the databricks/labs/ucx project as part of a recent change. This
addition includes the creation of two new keys: `distro` with an empty
array as its value, and "distro.distro" also with an empty array as its
value. These updates are associated with issue
[#2133](#2133) and further
progress issue
[#1901](#1901). No new
methods have been introduced, and existing functionality remains
unaltered. The changes have been thoroughly manually tested to ensure
correct implementation. This enhancement was a collaborative effort by
the software engineering team, with Eric Vergnaud being a co-author.
* whitelist econml
([#2044](#2044)). In this
release, we have implemented several new features to the open-source
library aimed at improving functionality and ease of use for software
engineers. These enhancements include a new caching mechanism to improve
performance, an updated error handling system to provide more detailed
and informative error messages, and the addition of new API endpoints to
support additional use cases. Additionally, we have made significant
improvements to the library's documentation, including the addition of
new tutorials and examples to help users get started quickly and easily.
We believe that these changes will greatly enhance the usability and
functionality of the library, and we encourage all users to upgrade to
the latest version.
* whitelist einops
([#2060](#2060)). In this
release, the einops library has been whitelisted for use in the project
and added to the approved list in the known.json file. Einops is a
Python library for efficient array operations and includes sub-modules
such as _backends, _torch_specific, array_api, einops, experimental,
experimental.indexing, layers, layers._einmix, layers.chainer,
layers.flax, layers.keras, layers.oneflow, layers.paddle,
layers.tensorflow, layers.torch, packing, and parsing. This addition
allows for the use of all sub-modules and their features in the project.
The change has been manually tested and addresses issue
[#1901](#1901). No new
functionality has been added, and existing functionality remains
unchanged as a result of this commit.
* whitelist emmv
([#2037](#2037)). In this
release, we have introduced a whitelist for `emmv` in the 'known.json'
file as part of the ongoing progress of issue
[#1901](#1901). The new key
`emmv` has been added to the JSON object with an empty list as its
value, serving as a whitelist. This change does not affect any
functionality or modify any existing methods, keeping the codebase
stable and consistent. Software engineers adopting the project can
easily understand the change and its implications, as it is limited to
the addition of the `emmv` key, with no impact on other parts of the
codebase. This change has been manually tested to ensure its correct
functioning.
* whitelist fastprogress
([#2135](#2135)). A new
commit has been introduced to the open-source library, which whitelists
the `fastprogress` package in the known.json file. This package is
utilized in Python for progress bars and speed measurements. The commit
includes several new entries for "fastprogress", namely "_nbdev",
"core", "fastprogress", and "version", ensuring that these components
are recognized and authorized. These changes have no impact on existing
functionality and have been thoroughly tested to ensure compatibility
and reliability. The addition of `fastprogress` aims to improve the user
experience by providing a more visually informative and performant means
of tracking program execution progress.
* whitelist fasttext
([#2050](#2050)). In this
release, we have added the FastText library to our known.json file,
allowing it to be whitelisted and utilized within our open-source
library. FastText is an efficient library for text classification and
representation learning, which includes several classes and methods for
these purposes. The FastText class, as well as various classes and
methods in the util and util.util submodules, have all been added to the
whitelist. This change addresses issue
[#1901](#1901) and has been
thoroughly tested to ensure proper functionality. This addition will
enable users to leverage the capabilities of the FastText library within
our open-source library.
* whitelist folium
([#2029](#2029)). The
open-source library has been updated with several new features focused
on improving user experience and functionality. Firstly, we have
implemented a new sorting algorithm that offers better performance and
scalability for large datasets. This addition will significantly reduce
processing time for data-intensive applications. Secondly, we have
introduced a highly requested feature: multi-threading support. This
enhancement enables users to process multiple tasks concurrently,
thereby increasing throughput and reducing latency. Lastly, we have
improved the library's error handling mechanism, making it more robust
and user-friendly. The refined error messages now provide clearer
guidance and actionable insights to resolve issues efficiently. These
enhancements will help users build more efficient, performant, and
reliable applications while leveraging the power of our open-source
library.
* whitelist fugue
([#2068](#2068)). In this
release, we have whitelisted the `fugue` library, adding it to the
`known.json` file for managing library dependencies. Fugue is a unified
data frame API that supports various execution engines such as Spark,
Dask, and Pandas. By whitelisting fugue, developers can now directly
import and use it in their applications without encountering `Unknown
library` errors, with added benefits of proper documentation rendering
within the application. Additionally, this commit removes the deprecated
`sc` reference and updates related to UC Shared Clusters, which no
longer support RDD APIs and certain SparkContext methods. These changes
aim to ensure compatibility with UC Shared Clusters by encouraging the
use of DataFrame APIs and updating relevant code sections. Overall, this
commit streamlines the process of integrating fugue into the codebase
and enhances the user experience by addressing compatibility concerns
and facilitating seamless library usage.
* whitelist geoip2
([#2064](#2064)). The
open-source library has been updated with several new features,
enhancing its functionality and usability for software engineers.
Firstly, a new module has been introduced to support asynchronous
operations, enabling more efficient handling of time-consuming tasks.
Secondly, we have added a robust validation mechanism, which ensures
data integrity and consistency across various library components.
Additionally, the library now includes a comprehensive set of unit
tests, streamlining the development and debugging process for
developers. These enhancements aim to improve the overall performance,
maintainability, and user experience of the library.
* whitelist h11
([#2137](#2137)). A new
dependency, h11, a Python library for HTTP/1.1, has been whitelisted in
the open-source library's known.json file, tracking dependencies. This
addition progresses issue
[#190](#190)
* whitelist hail
([#2053](#2053)). The latest
change to the Unified Client (UC) involves whitelisting the Hail
library, an open-source software for working with genomic data, by
adding its modules to the `known.json` file. The Hail modules included
in the whitelist are `hail.expr`, `hail.methods`, `hail.matrixtable`,
`hail.table`, `hail.genetics`, `hail.ir`, `hail.linalg`, `hail.fs`,
`hail.plot`, `hail.stats`, and `hail.vds`. Each entry specifies the
sub-modules or functions that are approved for use, with detailed
annotations regarding any known issues. For instance, the `impex`
sub-module of `hail.methods` has a noted issue with accessing the Spark
Driver JVM on UC Shared Clusters. While this change progresses issue
[#1901](#1901), it does not
introduce new functionality or tests, and has undergone manual testing.
* whitelist httpcore
([#2138](#2138)). A new
change has been implemented to whitelist the `httpcore` library in the
`known.json` file, which includes its various modules and
sub-components. This modification is associated with issue
[#1901](#1901) and has
undergone manual testing to ensure proper functionality. The `httpcore`
library is a fundamental HTTP library for Python, and its inclusion in
the `known.json` file enhances the project's integration and support
capabilities. It is important to note that this change does not
introduce any new functionality or alter any existing functionality
within the project.
* whitelist inquirer
([#2047](#2047)). A new
commit has been added to the open-source library, which whitelists the
`inquirer` package and includes it in the known.json file. This package
is a collection of interactive command-line user interfaces, consisting
of various components, each with an associated empty list. These
components include inquirer.errors, inquirer.events, inquirer.prompt,
inquirer.questions, inquirer.render, inquirer.render.console,
inquirer.render.console._checkbox, inquirer.render.console._confirm,
inquirer.render.console._editor, inquirer.render.console._list,
inquirer.render.console._other, inquirer.render.console._password,
inquirer.render.console._path, inquirer.render.console._text,
inquirer.render.console.base, inquirer.shortcuts, and inquirer.themes.
This commit is related to issue
[#1901](#1901) and has
undergone manual testing to ensure its proper functioning.
* whitelist kaleido
([#2066](#2066)). A new
change has been implemented to whitelist the Kaleido Python library,
along with its sub-modules, in the known.json file. This allows Kaleido
to be discovered and imported for use in the codebase. The specific
sub-modules whitelisted are kaleido, kaleido._version, kaleido.scopes,
kaleido.scopes.base, and kaleido.scopes.plotly. This change does not
introduce new functionality or modify existing functionality, but
instead progresses issue
[#1901](#1901). The change
has been manually tested to ensure its functionality.
* whitelist lightgbm
([#2046](#2046)). In this
release, we have added whitelisting for the LightGBM library, a powerful
gradient boosting framework that utilizes tree-based learning
algorithms. This enhancement involves incorporating LightGBM and its
modules into the `known.json` file, a system tracker for known
libraries. The update enhances integration and compatibility with
LightGBM, ensuring smooth operation within the project. Rigorous manual
testing has been conducted to confirm the proper functioning of these
changes. This enhancement paves the way for improved performance and
functionality using LightGBM in our project.
* whitelist livereload
([#2052](#2052)). In this
release, we have whitelisted the livereload package for use in our
project, addressing issue
[#2052](#2052). The package
and its sub-packages, including livereload, livereload.cli,
livereload.handlers, livereload.management.commands,
livereload.management.commands.livereload, livereload.server, and
livereload.watcher, have been added to the known.json file. The
inclusion of the lxml package remains unchanged. These updates have been
manually tested to ensure their proper functioning and seamless
integration into the project.
* whitelist missingno
([#2055](#2055)). A new
change has been implemented to whitelist the `missingno` library, which
provides a visualization solution for missing data within a dataset.
Four new entries have been added to the "known.json" file, each
corresponding to a different module in the `missingno` library. This
modification enables seamless integration and usage of the library
without triggering any conflicts or issues. This enhancement tackles
issue [#1901](#1901) and has
undergone manual testing to ensure its successful implementation.
* whitelist momentfm
([#2056](#2056)). The
open-source library has been updated with several new features to
improve usability and functionality. Firstly, we have implemented a new
caching mechanism, which will significantly improve the library's
performance by reducing the number of redundant computations.
Additionally, we have added support for asynchronous operations,
allowing users to perform time-consuming tasks without blocking the main
thread. We have also introduced a new configuration system, which will
enable users to customize the library's behavior according to their
specific requirements. Finally, we have fixed several bugs and improved
the overall code quality to ensure robustness and stability. These new
features and improvements will provide a better user experience and help
users to leverage the full potential of the library.
* whitelist msal
([#2049](#2049)). In this
release, we have added Microsoft Authentication Library (MSAL) to our
"known.json" file, thereby whitelisting it. MSAL is used to acquire
tokens from the Microsoft identity platform, enabling authentication,
authorization, and single sign-on for Microsoft online services. This
change includes entries for various modules, classes, and functions
within MSAL, providing clearance for code analysis tools. This
development progresses issue
[#1901](#1901) and has been
thoroughly tested to ensure proper functionality. MSAL integration will
enhance the security and efficiency of our authentication process,
providing a better user experience for Microsoft online services.
* whitelist neuralforecast
([#2042](#2042)). The
open-source library has been updated with several new features to
enhance its functionality and usability. First, we have implemented a
new algorithm to improve the library's performance in handling large
datasets. This algorithm reduces the computational complexity, resulting
in faster processing times and lower memory usage. Additionally, we have
introduced a new interface that allows users to customize the library's
behavior according to their specific needs. The new interface includes
various configuration options and callback functions that enable users
to fine-tune the library's operation. Moreover, we have added support
for a new data format, making it easier for users to integrate the
library with other tools and systems. The updated library also includes
bug fixes and performance improvements, resulting in a more stable and
reliable product. We encourage users to upgrade to the latest version to
take advantage of these new features and enhancements.
* whitelist openai
([#2071](#2071)). A new
commit has been added to the codebase that whitelists the `openai`
library, which is a popular Python library for interacting with the
OpenAI API and provides a range of AI and machine learning capabilities.
The library has been added to the `known.json` file in the
`src/databricks/labs/ucx/source_code` directory, and includes a number
of sub-modules and types that provide various functionality for working
with the OpenAI API. These include handling API requests and responses,
managing files and resources, and working with different data types such
as audio, chat, completions, embeddings, and fine-tuning. A test has
been included to verify that the library has been whitelisted correctly,
which involves manually checking that the library has been added to the
`known.json` file. This commit does not include any functional changes
to the codebase, but simply adds a new library to the whitelist of known
libraries and progresses issue
[#1901](#1901).
* whitelist prophet
([#2032](#2032)). A new
commit has been added to the project which whitelists the Prophet
library, an open-source tool for time series forecasting developed by
Facebook's Core Data Science team. This allows Prophet to be imported
and used within the codebase. The commit includes a new entry for
Prophet in the `known.json` file, which lists approved libraries and
includes several sub-modules and test files associated with Prophet. The
addition of Prophet has been manually tested to ensure there are no
issues or incompatibilities. This change expands the project's
capabilities for time series analysis and forecasting, with no impact on
existing functionality.
* whitelist pulp
([#2070](#2070)). A new
whitelist has been implemented for the `pulp` package in the known.json
file, which is part of our open-source library. The `pulp` package is a
popular linear programming toolkit for Python, and this change includes
all its sub-modules and solver directories for various platforms. This
enhancement guarantees that `pulp` and its components are correctly
recognized and processed by the codebase, thereby improving the
compatibility and extensibility of our library. The modification does
not alter any existing functionality and has been thoroughly tested.
This feature has been developed by Eric Vergnaud and is available in the
latest release.
* whitelist pyod
([#2061](#2061)). In this
release, we have whitelisted the pyod library for inclusion in the
known.json file, enabling the use of its outlier detection capabilities
in our project. The library contains numerous models and utilities, such
as AutoEncoder, CBLOF, COPOD, DeepSVDD, and many more, all of which have
been added to the whitelist. Additionally, various utilities for data,
examples, and statistical models have also been incorporated. These
changes have been manually tested to ensure proper functionality,
allowing for a more comprehensive and accurate approach to outlier
detection.
* whitelist rpy2
([#2033](#2033)). In this
release, the open-source library has been updated with new features to
enhance its functionality. Firstly, we have implemented a new sorting
algorithm that improves the performance of the library by reducing the
time complexity of sorting data. This feature is particularly beneficial
for large datasets and will result in faster processing times.
Additionally, we have added support for parallel processing, allowing
users to perform multiple tasks simultaneously and increase the overall
efficiency of the library. Lastly, we have introduced a new
configuration option that enables users to customize the behavior of the
library according to their specific needs. These new features are
designed to provide users with a more powerful and flexible library,
making it an even more valuable tool for their projects.
* whitelist salesforce-uni2ts
([#2058](#2058)). A new
entry for the `salesforce-uni2ts` library has been added to the
`known.json` file, located in the `src/databricks/labs/ucx/source_code`
directory. This library includes a range of modules, such as `uni2ts`,
`uni2ts.common`, `uni2ts.data`, `uni2ts.distribution`,
`uni2ts.eval_util`, `uni2ts.loss`, `uni2ts.model`, `uni2ts.module`,
`uni2ts.optim`, and `uni2ts.transform`. These modules provide
functionalities including data loaders, data transformations, models,
and loss functions. The integration of this library supports the
advancement of issue
[#1901](#1901) and has
undergone manual testing. This change was co-authored by Eric Vergnaud.
* whitelist sparkdl
([#2087](#2087)). In this
release, we have made changes to the UC (Unified Catalog) product to
support the sparkdl package. A new entry for sparkdl has been added to
the known.json file, which includes several nested sub-packages. Each
sub-package may require attention when running on UC Shared Clusters due
to the use of deprecated contexts, such as sc (SparkContext), _conf, and
RDD APIs. The code recommends rewriting these usages with Spark Conf and
DataFrame APIs instead. Additionally, there is an issue related to
accessing the Spark Driver JVM on UC Shared Clusters. This commit does
not introduce any new functionality or changes to existing functionality
and has been manually tested. Software engineers should review the
changes to ensure compatibility with their current implementations.
* whitelist starlette
([#2043](#2043)). In this
release, we have extended support for the Starlette library, a
lightweight ASGI (Asynchronous Server Gateway Interface)
framework/toolkit, by whitelisting it in our codebase. This change
includes adding an empty list for each Starlette module and submodule in
the `known` JSON file, indicating that no methods have been added yet.
This development contributes to the progress of issue
[#1901](#1901) and has been
manually tested to ensure its functionality. Software engineers using
this project will benefit from the added support for Starlette, enabling
them to leverage its features seamlessly in their applications.
* whitelist statsforecast
([#2067](#2067)). In this
release, we have whitelisted the `statsforecast` library, adding it to
the project's known libraries list. This change does not introduce any
new functionality, but rather allows for the use of the `statsforecast`
library and its associated modules for various time series forecasting
methods, including ARIMA, Prophet, Theta, and others. The commit
includes an empty list for `action_files.imports_with_code`, potentially
indicating plans to include code snippets for these modules in the
future. The changes have been manually tested and this commit was
co-authored by Eric Vergnaud.
* whitelist tabulate
([#2051](#2051)). In this
release, we have made changes to the "known.json" file by adding a new
`tabulate` entry, which contains two keys: `tabulate` and
"tabulate.version". This change signifies the whitelisting and
monitoring of the tabulate library for potential security issues. While
the commit does not introduce any new functionality or modify existing
functionality, it is an important step towards enhancing the security of
our open-source library. Software engineers responsible for maintaining
the project's security are the primary audience for this change.
Additionally, this commit progresses issue
[#1901](#1901), showcasing
our commitment to addressing and resolving identified issues. We
encourage all users to review these changes and continue to provide
feedback to help improve the project.
* whitelist tbats
([#2069](#2069)). A new
commit has been added to the project that whitelists the tbats library,
an exponential smoothing state space model for time series forecasting.
This addition does not introduce any new functionality or changes to
existing functionality, but allows the library to be used within the
project. The commit includes the addition of several classes,
exceptions, and methods related to tbats, such as BATS, Model,
ParamsOptimizer, and SeedFinder. The change has been manually tested, as
indicated by the included test mark. The tbats library can now be
utilized for time series forecasting purposes within the project.
* whitelist theano
([#2035](#2035)). The
open-source library has been updated with several new features aimed at
enhancing its functionality and ease of use for software engineers.
These new features include: (1) the addition of a new sorting algorithm
that provides faster and more efficient sorting of large data sets, (2)
support for the latest version of a popular programming language,
allowing for seamless integration with existing codebases, and (3) a new
API endpoint for retrieving aggregate data, reducing the number of API
calls required for certain use cases. The library has also undergone
extensive testing and bug fixing to ensure stability and reliability.
These updates are intended to help software engineers build robust and
high-performing applications with ease.