Changed release version to be 0.4.0 (#271)

* wip

* wip

* corrected version information

* wip

* wip

* updated build instructions

CHANGELOG.md

@@ -3,9 +3,10 @@
 ## Change History
 All notable changes to the Databricks Labs Data Generator will be documented in this file.
 
-### Unreleased
+### Version 0.4.0
 
 #### Changed
+* Updated minimum pyspark version to be 3.2.1, compatible with Databricks runtime 10.4 LTS or later
 * Modified data generator to allow specification of constraints to the data generation process
 * Updated documentation for generating text data.
 * Modified data distribiutions to use abstract base classes

CONTRIBUTING.md

@@ -26,7 +26,7 @@ runtime 9.1 LTS or later.
 
 ## Checking your code for common issues
 
-Run `./lint.sh` from the project root directory to run various code style checks. 
+Run `make dev-lint` from the project root directory to run various code style checks. 
 These are based on the use of `prospector`, `pylint` and related tools.
 
 ## Setting up your build environment
@@ -45,6 +45,11 @@ Our recommended mechanism for building the code is to use a `conda` or `pipenv`
 
 But it can be built with any Python virtualization environment.
 
+### Spark dependencies
+The builds have been tested against Spark 3.2.1. This requires the OpenJDK 1.8.56 or later version of Java 8.
+The Databricks runtimes use the Azul Zulu version of OpenJDK 8 and we have used these in local testing.
+These are not installed automatically by the build process, so you will need to install them separately.
+
 ### Building with Conda
 To build with `conda`, perform the following commands:
   - `make create-dev-env` from the main project directory to create your conda environment, if using
@@ -70,7 +75,7 @@ To build with `pipenv`, perform the following commands:
     - Run `make dist` from the main project directory
   - The resulting wheel file will be placed in the `dist` subdirectory
 
-The resulting build has been tested against Spark 3.0.1
+The resulting build has been tested against Spark 3.2.1
 
 ## Creating the HTML documentation
 

README.md

@@ -65,7 +65,7 @@ details of use and many examples.
 
 Release notes and details of the latest changes for this specific release
 can be found in the GitHub repository
-[here](https://github.com/databrickslabs/dbldatagen/blob/release/v0.3.6post1/CHANGELOG.md)
+[here](https://github.com/databrickslabs/dbldatagen/blob/release/v0.4.0/CHANGELOG.md)
 
 # Installation
 

dbldatagen/_version.py

@@ -34,7 +34,7 @@ def get_version(version):
     return version_info
 
 
-__version__ = "0.3.6post1"  # DO NOT EDIT THIS DIRECTLY!  It is managed by bumpversion
+__version__ = "0.4.0"  # DO NOT EDIT THIS DIRECTLY!  It is managed by bumpversion
 __version_info__ = get_version(__version__)
 
 

docs/source/conf.py

@@ -32,7 +32,7 @@
 author = 'Databricks Inc'
 
 # The full version, including alpha/beta/rc tags
-release = "0.3.6post1"  # DO NOT EDIT THIS DIRECTLY!  It is managed by bumpversion
+release = "0.4.0"  # DO NOT EDIT THIS DIRECTLY!  It is managed by bumpversion
 
 # -- General configuration ---------------------------------------------------
 

python/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.3.6post1
+current_version = 0.4.0
 commit = False
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+){0,1}(?P<release>\D*)(?P<build>\d*)

python/dev_require.txt

@@ -3,9 +3,9 @@
 numpy==1.22.0
 pandas==1.2.4
 pickleshare==0.7.5
-py4j==0.10.9
+py4j>=0.10.9.3
 pyarrow==4.0.1
-pyspark>=3.1.3
+pyspark>=3.2.1,<=3.3.0
 python-dateutil==2.8.1
 six==1.15.0
 pyparsing==2.4.7

python/require.txt

@@ -5,7 +5,7 @@ pandas==1.2.5
 pickleshare==0.7.5
 py4j==0.10.9
 pyarrow==4.0.1
-pyspark>=3.1.3
+pyspark>=3.2.1
 python-dateutil==2.8.1
 six==1.15.0
 pyparsing==2.4.7

setup.py

@@ -31,7 +31,7 @@
 
 setuptools.setup(
     name="dbldatagen",
-    version="0.3.6post1",
+    version="0.4.0",
     author="Ronan Stokes, Databricks",
     description="Databricks Labs -  PySpark Synthetic Data Generator",
     long_description=long_description,