bumping to version 0.3.0

Summary:
Updated CHANGELOG, init, and some misc fixes to setup.py and README.

This version fixes #19.

Props to tomwagstaff-opml for flagging the need for supporting Python 3.11.

Reviewed By: SarigT

Differential Revision: D42850883

fbshipit-source-id: f4822baafd11938981ba6b3a12258d3e5e7e478c

CHANGELOG.md

@@ -1,10 +1,16 @@
-[Unreleased]
+0.3.0 (2023-01-30)
 ==================
 ### New Features
-- Added compatibility for SciPy 1.9.2 and Python 3.11
+- Added compatibility for Python 3.11 (by supporting SciPy 1.9.2) (props to @tomwagstaff-opml for flagging this issue).
+- Added the `session-info` package as a dependency.
 
 ### Bug Fixes
-- Fixed pip install from source on Windows machines
+- Fixed pip install from source on Windows machines (props to @tomwagstaff-opml for the bug report).
+
+### Documentation
+- Added `session_info.show()` outputs to the end of the three tutorials (at: https://import-balance.org/docs/tutorials/)
+- Misc updates to the README.
+
 
 0.2.0 (2023-01-19)
 ==================
@@ -43,6 +49,7 @@
 - Added automated Github Action package builds & deployment to PyPi on release.
   - See [release.yml](https://github.com/facebookresearch/balance/blob/main/.github/workflows/release.yml)
 
+
 0.1.0 (2022-11-20)
 ==================
 ### Summary

README.md

@@ -13,14 +13,13 @@ Biased samples often occur in [survey statistics](https://en.wikipedia.org/wiki/
 
 Under the missing at random assumption ([MAR](https://en.wikipedia.org/wiki/Missing_data#Missing_at_random)), bias in samples could sometimes be (at least partially) mitigated by relying on auxiliary information (a.k.a.: “covariates” or “features”) that is present for all items in the sample, as well as present in a sample of items from the population. For example, if we want to infer from a sample of respondents to some survey, we may wish to adjust for non-response using demographic information such as age, gender, education, etc. This can be done by weighing the sample to the population using auxiliary information.
 
-The package is intended for researchers who are interested in balancing biased samples, such as the ones coming from surveys, using a Python package. This need may arise by survey methodologists, demographers, UX researchers, market researchers, and generally data scientists, statisticiains, and machine learners.
+The package is intended for researchers who are interested in balancing biased samples, such as the ones coming from surveys, using a Python package. This need may arise by survey methodologists, demographers, UX researchers, market researchers, and generally data scientists, statisticians, and machine learners.
 
 
 # Installation
 
 ## Requirements
-You need Python 3.8 or later to run *balance*. *balance* can be built and run
-from OSX, Linux, and Windows
+You need Python 3.8 or later to run *balance*. *balance* can be built and run from Linux, OSX, and Windows (NOTE: `method="ipw"` is currently not supported on Windows).
 
 The required Python dependencies are:
 ```python
@@ -131,7 +130,7 @@ adjusted = sample_with_target.adjust(max_de=None)
 
 *You can read more on adjustment process in the [Adjusting Sample to Population](https://import-balance.org/docs/docs/general_framework/adjusting_sample_to_population/) page.*
 
-The above code gets us an `adjusted` object with weights. We can evaluate the benefit of the weights to the coveriate balance, for example by running:
+The above code gets us an `adjusted` object with weights. We can evaluate the benefit of the weights to the covariate balance, for example by running:
 
 ```python
 print(adjusted.summary())
@@ -169,7 +168,7 @@ adjusted.outcomes().plot()
 *You can read more on evaluation of the post-adjusted data in the [Evaluating and using the adjustment weights](https://import-balance.org/docs/docs/general_framework/evaluation_of_results/) page.*
 
 
-Finally, the adjusted data can be downloded using:
+Finally, the adjusted data can be downloaded using:
 ```python
 adjusted.to_download()  # Or:
 # adjusted.to_csv()

balance/__init__.py

@@ -20,7 +20,7 @@
 # TODO: verify this works.
 
 global __version__
-__version__ = "0.2.0"  # open source version
+__version__ = "0.3.0"  # open source version
 
 
 def setup_logging(

setup.py

@@ -9,11 +9,11 @@
 Core library deps
 
 Version requirements
-* scipy<=1.8.1: Required by glmnet-python
+* scipy<=1.9.2: Required by glmnet-python
 * pandas<=1.4.3: 1.5.0 moved UndefinedVariableError into pandas.errors
 
 Other requirements:
-* [email protected], from https://github.com/bbalasub1/glmnet_python.git@1.0
+* [email protected], from https://github.com/bbalasub1/glmnet_python.git
 
 """
 REQUIRES = [
@@ -81,6 +81,8 @@ def setup_package() -> None:
             "Programming Language :: Python :: 3.7",
             "Programming Language :: Python :: 3.8",
             "Programming Language :: Python :: 3.9",
+            "Programming Language :: Python :: 3.10",
+            "Programming Language :: Python :: 3.11",
             "License :: OSI Approved :: GNU General Public License v2 (GPLv2)",
         ],
     )