diff --git a/.github/workflows/ci_docs_build.yml b/.github/workflows/ci_docs_build.yml
new file mode 100644
index 0000000..2ae0fcc
--- /dev/null
+++ b/.github/workflows/ci_docs_build.yml
@@ -0,0 +1,37 @@
+name: Verify docs build correctly
+
+on:
+ pull_request:
+ branches:
+ - main
+ types: [opened, reopened, synchronize]
+
+jobs:
+ build:
+ runs-on: ubuntu-24.04
+ steps:
+ - uses: actions/checkout@v5
+
+ - name: Install extra dependencies for a python install
+ run: |
+ sudo apt-get update
+ sudo apt -y install --no-install-recommends liblzma-dev libbz2-dev libreadline-dev
+
+ - name: Install asdf cli
+ uses: asdf-vm/actions/setup@b7bcd026f18772e44fe1026d729e1611cc435d47
+
+ - name: Install software through asdf
+ uses: asdf-vm/actions/install@b7bcd026f18772e44fe1026d729e1611cc435d47
+
+ - name: reshim asdf
+ run: asdf reshim
+
+ - name: ensure poetry using desired python version
+ run: poetry env use $(asdf which python)
+
+ - name: install docs requirements
+ run: |
+ poetry install --sync --no-interaction --with docs
+
+ - name: verify docs build correctly
+ run: poetry run zensical build --strict
diff --git a/CHANGELOG.md b/CHANGELOG.md
index a496cab..690c385 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,3 +1,14 @@
+## v0.8.3 (2026-07-14)
+
+### Fix
+
+- fix issue with non iso date/datetime values in duck db casting after data contract validations (#129)
+- implement non iso timestamp formats in spark. constrain ddb and spark parsers to only cast where format exactly as stipulated (#129)
+
+### Build
+
+- bump pyspark to 3.5.5 (#129)
+
## v0.8.2 (2026-07-01)
### Feat
diff --git a/docs/user_guidance/business_rules.md b/docs/user_guidance/business_rules.md
index e7bd8b6..0f4093f 100644
--- a/docs/user_guidance/business_rules.md
+++ b/docs/user_guidance/business_rules.md
@@ -50,7 +50,7 @@ For the simplest rules, you can write them in the filters section. For example,
"failure_type": "record",
"error_code": "MOVIE_TOO_LONG",
"failure_message": "Movie must be less than 4 hours long.",
- "category": "Bad Value"
+ "category": "Bad value"
}
]
}
@@ -81,7 +81,7 @@ For the simplest rules, you can write them in the filters section. For example,
"failure_type": "submission",
"error_code": "MOVIE_TOO_LONG",
"failure_message": "Movie must be less than 4 hours long.",
- "category": "Bad Value"
+ "category": "Bad value"
}
]
}
@@ -113,7 +113,7 @@ For the simplest rules, you can write them in the filters section. For example,
"is_informational": true,
"error_code": "MOVIE_TOO_LONG",
"failure_message": "Movie must be less than 4 hours long.",
- "category": "Bad Value",
+ "category": "Bad value",
}
]
}
diff --git a/docs/user_guidance/data_contract.md b/docs/user_guidance/data_contract.md
index 3c931b1..55913da 100644
--- a/docs/user_guidance/data_contract.md
+++ b/docs/user_guidance/data_contract.md
@@ -417,13 +417,13 @@ When a [Feedback Message](./feedback_messages.md) is produced during the contrac
"error_message": "File Rejected - movie_uuid is blank.",
"error_level": "submission"
},
- "Bad Value": {
+ "Bad value": {
"error_code": "MOVIE_UUID_02",
"error_message": "Record Rejected - movie_uuid has an incorrect data format. movie_uuid={{ movie_uuid }}.",
}
},
"movie_name": {
- "Bad Value": {
+ "Bad value": {
"error_code": "MOVIE_NAME_01",
"error_message": "Warning - movie_name has an incorrect data format. movie_name={{ movie_name }}.",
"is_informational": true
diff --git a/docs/user_guidance/install.md b/docs/user_guidance/install.md
index 8c93e5c..e0c2ce4 100644
--- a/docs/user_guidance/install.md
+++ b/docs/user_guidance/install.md
@@ -79,7 +79,7 @@ You can install the DVE package through python package managers such as [pip](ht
Python dependencies are listed in the [`pyproject.toml`](https://github.com/NHSDigital/data-validation-engine/blob/main/pyproject.toml). Many of the dependencies are locked to quite restrictive versions due to complexity of this package. Core packages such as Pydantic, Pyspark and DuckDB are unlikely to receive flexible version constraints as changes in those packages could cause the DVE to malfunction. For less important dependencies, we have tried to make the contraints more flexible. Therefore, we would advise you to install the DVE into a seperate environment rather than trying to integrate it into an existing Python environment.
-Once you have installed the DVE you are almost ready to use it. To be able to run the DVE, you will need to choose one of the supported pipeline runners (see Backend implementations here - [DuckDB](user_guidance/implementations/duckdb.md) *or* [Spark](user_guidance/implementations/spark.md)) and you will need to create your own dischema document to configure how the DVE should validate incoming data. You can read more about this in the [Getting Started](getting_started.md) page.
+Once you have installed the DVE you are almost ready to use it. To be able to run the DVE, you will need to choose one of the supported pipeline runners (see Backend implementations here - [DuckDB](implementations/duckdb.md) *or* [Spark](implementations/spark.md)) and you will need to create your own dischema document to configure how the DVE should validate incoming data. You can read more about this in the [Getting Started](getting_started.md) page.
## DVE Version Compatability Matrix
diff --git a/poetry.lock b/poetry.lock
index 320ff93..c2674f9 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 2.4.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand.
[[package]]
name = "argcomplete"
@@ -535,109 +535,125 @@ types-awscrt = "*"
[[package]]
name = "certifi"
-version = "2026.4.22"
+version = "2026.6.17"
description = "Python package for providing Mozilla's CA Bundle."
optional = false
python-versions = ">=3.7"
groups = ["dev", "test"]
files = [
- {file = "certifi-2026.4.22-py3-none-any.whl", hash = "sha256:3cb2210c8f88ba2318d29b0388d1023c8492ff72ecdde4ebdaddbb13a31b1c4a"},
- {file = "certifi-2026.4.22.tar.gz", hash = "sha256:8d455352a37b71bf76a79caa83a3d6c25afee4a385d632127b6afb3963f1c580"},
+ {file = "certifi-2026.6.17-py3-none-any.whl", hash = "sha256:2227dcbaafe0d2f59279d1762ddddc37783ed4354594f194ffc31d20f41fc3db"},
+ {file = "certifi-2026.6.17.tar.gz", hash = "sha256:024c88eeec92ca068db80f02b8b07c9cef7b9fe261d1d535abfd5abd6f6af432"},
]
[[package]]
name = "cffi"
-version = "2.0.0"
+version = "2.1.0"
description = "Foreign Function Interface for Python calling C code."
optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
groups = ["dev", "test"]
markers = "platform_python_implementation != \"PyPy\""
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[[package]]
name = "cucumber-expressions"
-version = "19.0.0"
+version = "20.0.0"
description = "Cucumber Expressions - a simpler alternative to Regular Expressions"
optional = false
python-versions = ">=3.10"
groups = ["dev", "test"]
files = [
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name = "cucumber-tag-expressions"
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description = "Provides a tag-expression parser and evaluation logic for cucumber/behave"
optional = false
python-versions = ">=3.10"
groups = ["dev", "test"]
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description = "A toolset for deeply merging Python dictionaries."
optional = false
python-versions = ">=3.8"
groups = ["docs"]
files = [
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[[package]]
name = "delta-spark"
@@ -1123,14 +1139,14 @@ profile = ["gprof2dot (>=2022.7.29)"]
[[package]]
name = "distlib"
-version = "0.4.0"
+version = "0.4.3"
description = "Distribution utilities"
optional = false
python-versions = "*"
groups = ["dev"]
files = [
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@@ -1228,14 +1244,14 @@ test = ["pytest (>=6)"]
[[package]]
name = "filelock"
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+version = "3.29.7"
description = "A platform independent file lock."
optional = false
python-versions = ">=3.10"
groups = ["dev"]
files = [
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[[package]]
name = "mkdocstrings-python"
-version = "2.0.3"
+version = "2.0.5"
description = "A Python handler for mkdocstrings."
optional = false
python-versions = ">=3.10"
groups = ["docs"]
files = [
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- {version = ">=1.23.2", markers = "python_version == \"3.11\""},
{version = ">=1.26.0", markers = "python_version >= \"3.12\""},
+ {version = ">=1.23.2", markers = "python_version == \"3.11\""},
]
python-dateutil = ">=2.8.2"
pytz = ">=2020.1"
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name = "parse"
-version = "1.21.1"
+version = "1.22.1"
description = "parse() is the opposite of format()"
optional = false
python-versions = "*"
groups = ["dev", "test"]
files = [
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[[package]]
name = "platformdirs"
-version = "4.9.6"
+version = "4.10.0"
description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
optional = false
python-versions = ">=3.10"
groups = ["dev", "docs", "lint"]
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colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
dill = [
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- {version = ">=0.3.6", markers = "python_version == \"3.11\""},
{version = ">=0.3.7", markers = "python_version >= \"3.12\""},
+ {version = ">=0.3.6", markers = "python_version == \"3.11\""},
]
isort = ">=4.2.5,<5.13 || >5.13,<7"
mccabe = ">=0.6,<0.8"
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[[package]]
name = "pyspark"
-version = "3.5.2"
+version = "3.5.5"
description = "Apache Spark Python API"
optional = false
python-versions = ">=3.8"
groups = ["main"]
files = [
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[[package]]
name = "pytz"
-version = "2026.1.post1"
+version = "2026.2"
description = "World timezone definitions, modern and historical"
optional = false
python-versions = "*"
groups = ["main"]
files = [
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[[package]]
name = "responses"
-version = "0.26.0"
+version = "0.26.2"
description = "A utility library for mocking out the `requests` Python library."
optional = false
python-versions = ">=3.8"
groups = ["dev", "test"]
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python-versions = ">=3.8"
groups = ["dev", "docs", "lint", "test"]
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[[package]]
name = "tomlkit"
-version = "0.14.0"
+version = "0.15.0"
description = "Style preserving TOML library"
optional = false
python-versions = ">=3.9"
groups = ["dev", "lint"]
files = [
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name = "tzdata"
-version = "2026.2"
+version = "2026.3"
description = "Provider of IANA time zone data"
optional = false
python-versions = ">=2"
groups = ["main"]
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+ {file = "wrapt-2.2.2-cp39-cp39-win_arm64.whl", hash = "sha256:3179a4db066b53d40562e368b12895440c8f0953b6543b89d6acc41c0273996e"},
+ {file = "wrapt-2.2.2-py3-none-any.whl", hash = "sha256:5bad217350f19ce99ca5b5e71d406765ea86fe541628426772b657375ee1c048"},
+ {file = "wrapt-2.2.2.tar.gz", hash = "sha256:0788e321027c999bf221b667bd4a54aaefd1a36283749a860ac3eb77daed0302"},
]
[package.extras]
@@ -3355,57 +3371,58 @@ test = ["pytest", "pytest-cov"]
[[package]]
name = "zensical"
-version = "0.0.31"
+version = "0.0.46"
description = "A modern static site generator built by the creators of Material for MkDocs"
optional = false
python-versions = ">=3.10"
groups = ["docs"]
files = [
- {file = "zensical-0.0.31-cp310-abi3-macosx_10_12_x86_64.whl", hash = "sha256:b489936d670733dd204f16b689a2acc0e45b69e42cc4901f5131ae57658b8fbc"},
- {file = "zensical-0.0.31-cp310-abi3-macosx_11_0_arm64.whl", hash = "sha256:d9f678efc0d9918e45eeb8bc62847b2cce23db7393c8c59c1be6d1c064bbaacd"},
- {file = "zensical-0.0.31-cp310-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fb2b50ecf674997f818e53f12f2a67875a21b0c79ed74c151dfaef2f1475e5bf"},
- {file = "zensical-0.0.31-cp310-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:6fb5c634fe88254770a2d4db5c05b06f1c3ee5e29d2ae3e7efdae8905e435b1d"},
- {file = "zensical-0.0.31-cp310-abi3-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:94e64630552793274db1ec66c971e49a15ad351536d5d12de67ec6da7358ac50"},
- {file = "zensical-0.0.31-cp310-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:738a2fd5832e3b3c10ff642eebaf89c89ca1d28e4451dad0f36fdac53c415577"},
- {file = "zensical-0.0.31-cp310-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:bd601f6132e285ef6c3e4c3852be2094fc0473295a8080003db76a79760f84fb"},
- {file = "zensical-0.0.31-cp310-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:dc3b6a9dfb5903c0aa779ef65cd6185add2b8aa1db237be840874b8c9db761b8"},
- {file = "zensical-0.0.31-cp310-abi3-musllinux_1_2_i686.whl", hash = "sha256:ddd4321b275e82c4897aa45b05038ce204b88fb311ad55f8c2af572173a9b56c"},
- {file = "zensical-0.0.31-cp310-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:147ab4bc17f3088f703aa6c4b9c416411f4ea8ca64d26f6586beae49d97fd3c7"},
- {file = "zensical-0.0.31-cp310-abi3-win32.whl", hash = "sha256:03fa11e629a308507693489541f43e751697784e94365e7435b02104aefd1c2c"},
- {file = "zensical-0.0.31-cp310-abi3-win_amd64.whl", hash = "sha256:d6621d4bb46af4143560045d4a18c8c76302db56bf1dbb6e2ce107d7fb643e09"},
- {file = "zensical-0.0.31.tar.gz", hash = "sha256:9c12f07bde70c4bfdb13d6cae1bedf8d18064d257a6e81128a152502b28a8fc3"},
+ {file = "zensical-0.0.46-cp310-abi3-macosx_10_12_x86_64.whl", hash = "sha256:d91af81ab058c8693dfd75f2f77b4c73bcba4125681d1d276f38624291820bd2"},
+ {file = "zensical-0.0.46-cp310-abi3-macosx_11_0_arm64.whl", hash = "sha256:d9221264a9a87409900a47e29985607b0c9245dacb89077e87c8e16e31edc167"},
+ {file = "zensical-0.0.46-cp310-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ec43018d5343ca2e1d71aa352eeddd560fef504effd03025840a5a783abefa4f"},
+ {file = "zensical-0.0.46-cp310-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:26e98fb8ab7ab50cdd20a73e2c7d4d9aae0b46cf2d8691e6bb22f9c261b8a60a"},
+ {file = "zensical-0.0.46-cp310-abi3-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:46fe578f26963f8ee89567983e62737b6fadc9197d4742e1020b522e092d7baa"},
+ {file = "zensical-0.0.46-cp310-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aef03fa186a5589148e10b62610500989c6b075a2c08e1554233adbf91b2a3dc"},
+ {file = "zensical-0.0.46-cp310-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:bc7446cdf97a8dea390f20ed2bd6b030cddc1bd36a8ce113ea3efef6fa61c573"},
+ {file = "zensical-0.0.46-cp310-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:bbee37801f1ed500f158dc0992c569282950f780ae353c37fe6969f99983d701"},
+ {file = "zensical-0.0.46-cp310-abi3-musllinux_1_2_i686.whl", hash = "sha256:9487c147c9cceb50c04d0ad70b024821a6eab1629dafd70ab6d1e86ec841e623"},
+ {file = "zensical-0.0.46-cp310-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:f42a4683c762f026878d19ede4bcf7bfbb84dbecb5ad923949abb77806ed88a5"},
+ {file = "zensical-0.0.46-cp310-abi3-win32.whl", hash = "sha256:85f018f2a7ee76a83915c87ddb12b58cf343fd6154081d33ac95b6751b011dd7"},
+ {file = "zensical-0.0.46-cp310-abi3-win_amd64.whl", hash = "sha256:1543a693a160de60e86ca589592401b584670e7e12c5ae30e3c2ba76786f7ec3"},
+ {file = "zensical-0.0.46.tar.gz", hash = "sha256:3ec21f4fb1e78cd7c0d6b07ae336b04770e27ba020dabc457b2790e5d34f1978"},
]
[package.dependencies]
click = ">=8.1.8"
deepmerge = ">=2.0"
+jinja2 = ">=3.1"
markdown = ">=3.7"
-pygments = ">=2.16"
-pymdown-extensions = ">=10.15"
+pygments = ">=2.20"
+pymdown-extensions = ">=10.21.3"
pyyaml = ">=6.0.2"
-tomli = {version = ">=2.0", markers = "python_full_version < \"3.11.0\""}
+tomli = ">=2.4.0"
[[package]]
name = "zipp"
-version = "3.23.1"
+version = "4.1.0"
description = "Backport of pathlib-compatible object wrapper for zip files"
optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
groups = ["main"]
files = [
- {file = "zipp-3.23.1-py3-none-any.whl", hash = "sha256:0b3596c50a5c700c9cb40ba8d86d9f2cc4807e9bedb06bcdf7fac85633e444dc"},
- {file = "zipp-3.23.1.tar.gz", hash = "sha256:32120e378d32cd9714ad503c1d024619063ec28aad2248dc6672ad13edfa5110"},
+ {file = "zipp-4.1.0-py3-none-any.whl", hash = "sha256:25ad4e16390cd314347dd8f1de67a2ac538ae658ed4ab9db16029c07c188e97f"},
+ {file = "zipp-4.1.0.tar.gz", hash = "sha256:4cb57381f544315db7688e976e922a2b18cdb513d21cc194eb42232ba2a3e602"},
]
[package.extras]
-check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""]
+check = ["pytest-checkdocs (>=2.14)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""]
cover = ["pytest-cov"]
doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-enabler = ["pytest-enabler (>=2.2)"]
+enabler = ["pytest-enabler (>=3.4)"]
test = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more_itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
-type = ["pytest-mypy"]
+type = ["pytest-mypy (>=1.0.1) ; platform_python_implementation != \"PyPy\""]
[metadata]
lock-version = "2.1"
python-versions = ">=3.10,<3.13"
-content-hash = "9a5c663fa3e691692e436c406dbb282b8657c5fc7f5eb70d26928191b4f9896c"
+content-hash = "305caceb6c037646196a148e44272bc1a39901af5027c3f27b6858bd67edff41"
diff --git a/pyproject.toml b/pyproject.toml
index 17d5bff..9658e6d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -10,6 +10,7 @@ classifiers = [
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
+ "Programming Language :: Python :: 3.12",
"Operating System :: OS Independent",
"Topic :: Software Development :: Libraries",
"Typing :: Typed",
@@ -24,7 +25,7 @@ Issues = "https://github.com/NHSDigital/data-validation-engine/issues"
Changelog = "https://github.com/NHSDigital/data-validation-engine/blob/main/CHANGELOG.md"
[tool.poetry]
-version = "0.8.2"
+version = "0.8.3"
packages = [
{ include = "dve", from = "src" },
]
@@ -43,7 +44,7 @@ pandas = "2.3.3"
polars = "0.20.31"
pyarrow = "23.0.1"
pydantic = "1.10.19"
-pyspark = ">=3.0.0,<=3.5.2"
+pyspark = ">=3.5.0,<=3.5.5"
typing_extensions = "4.15.0"
urllib3 = "2.7.0" # dependency of boto3 & botocore
@@ -106,7 +107,7 @@ mkdocs = "1.6.1"
mkdocstrings = { version = "1.0.3", extras = ["python"] }
griffelib = "2.0.1"
pymdown-extensions = "10.21.3"
-zensical = "0.0.31"
+zensical = "0.0.46"
[tool.ruff]
line-length = 100
diff --git a/src/dve/core_engine/backends/implementations/duckdb/duckdb_helpers.py b/src/dve/core_engine/backends/implementations/duckdb/duckdb_helpers.py
index acb51e0..b54192f 100644
--- a/src/dve/core_engine/backends/implementations/duckdb/duckdb_helpers.py
+++ b/src/dve/core_engine/backends/implementations/duckdb/duckdb_helpers.py
@@ -21,6 +21,7 @@
from dve.common.error_utils import get_feedback_errors_uri
from dve.core_engine.backends.base.utilities import _get_non_heterogenous_type
+from dve.core_engine.backends.utilities import DEFAULT_ISO_FORMATS, datetime_format_to_regex
from dve.core_engine.constants import RECORD_INDEX_COLUMN_NAME
from dve.core_engine.type_hints import URI, EntityName
from dve.parser.file_handling.service import LocalFilesystemImplementation, _get_implementation
@@ -361,7 +362,7 @@ def duckdb_record_index(cls):
def _cast_as_ddb_type(field_expr: str, type_annotation: Any) -> str:
"""Cast to Duck DB type"""
- return f"""try_cast({field_expr} as {get_duckdb_type_from_annotation(type_annotation)})"""
+ return f"""TRY_CAST({field_expr} as {get_duckdb_type_from_annotation(type_annotation)})"""
def _ddb_safely_quote_name(field_name: str) -> str:
@@ -378,9 +379,6 @@ def get_duckdb_cast_statement_from_annotation(
element_name: str,
type_annotation: Any,
parent_element: bool = True,
- date_regex: str = r"^[0-9]{4}-[0-9]{2}-[0-9]{2}$",
- timestamp_regex: str = r"^[0-9]{4}-[0-9]{2}-[0-9]{2}T[0-9]{2}:[0-9]{2}:[0-9]{2}((\+|\-)[0-9]{2}:[0-9]{2})?$", # pylint: disable=C0301
- time_regex: str = r"^[0-9]{2}:[0-9]{2}:[0-9]{2}$",
) -> str:
"""Generate casting statements for duckdb relations from type annotations"""
type_origin = get_origin(type_annotation)
@@ -391,19 +389,23 @@ def get_duckdb_cast_statement_from_annotation(
if type_origin is Union:
python_type = _get_non_heterogenous_type(get_args(type_annotation))
return get_duckdb_cast_statement_from_annotation(
- element_name, python_type, parent_element, date_regex, timestamp_regex
+ element_name,
+ python_type,
+ parent_element,
)
# Type hint is e.g. `List[str]`, check to ensure non-heterogenity.
if type_origin is list or (isinstance(type_origin, type) and issubclass(type_origin, list)):
element_type = _get_non_heterogenous_type(get_args(type_annotation))
- stmt = f"list_transform({quoted_name}, x -> {get_duckdb_cast_statement_from_annotation('x',element_type, False, date_regex, timestamp_regex)})" # pylint: disable=C0301
+ stmt = f"LIST_TRANSFORM({quoted_name}, x -> {get_duckdb_cast_statement_from_annotation('x',element_type, False,)})" # pylint: disable=C0301
return stmt if not parent_element else _cast_as_ddb_type(stmt, type_annotation)
if type_origin is Annotated:
python_type, *other_args = get_args(type_annotation) # pylint: disable=unused-variable
return get_duckdb_cast_statement_from_annotation(
- element_name, python_type, parent_element, date_regex, timestamp_regex
+ element_name,
+ python_type,
+ parent_element,
) # add other expected params here
# Ensure that we have a concrete type at this point.
if not isinstance(type_annotation, type):
@@ -428,7 +430,9 @@ def get_duckdb_cast_statement_from_annotation(
continue
fields[field_name] = get_duckdb_cast_statement_from_annotation(
- f"{element_name}.{field_name}", field_annotation, False, date_regex, timestamp_regex
+ f"{element_name}.{field_name}",
+ field_annotation,
+ False,
)
if not fields:
@@ -436,7 +440,7 @@ def get_duckdb_cast_statement_from_annotation(
f"No type annotations in dict/dataclass type (got {type_annotation!r})"
)
cast_exprs = ",".join([f'"{nme}":= {stmt}' for nme, stmt in fields.items()])
- stmt = f"struct_pack({cast_exprs})"
+ stmt = f"STRUCT_PACK({cast_exprs})"
return stmt if not parent_element else _cast_as_ddb_type(stmt, type_annotation)
if type_annotation is list:
@@ -447,18 +451,23 @@ def get_duckdb_cast_statement_from_annotation(
raise ValueError(f"dict must be `typing.TypedDict` subclass, got {type_annotation!r}")
for type_ in type_annotation.mro():
+ _date_format: str = getattr( # type: ignore
+ type_, "DATE_FORMAT", DEFAULT_ISO_FORMATS.get(type_, DEFAULT_ISO_FORMATS.get(datetime))
+ )
+ dt_cast_statement = rf"CASE WHEN REGEXP_FULL_MATCH(TRIM({quoted_name}), '{datetime_format_to_regex(_date_format)}') THEN TRY_STRPTIME(TRIM({quoted_name}), '{_date_format}') ELSE NULL END" # pylint: disable=C0301
+
# datetime is subclass of date, so needs to be handled first
if issubclass(type_, datetime):
- stmt = rf"CASE WHEN REGEXP_MATCHES(TRIM({quoted_name}), '{timestamp_regex}') THEN TRY_CAST(TRIM({quoted_name}) as TIMESTAMP) ELSE NULL END" # pylint: disable=C0301
+ stmt = rf"TRY_CAST({dt_cast_statement} as TIMESTAMP)"
return stmt
if issubclass(type_, date):
- stmt = rf"CASE WHEN REGEXP_MATCHES(TRIM({quoted_name}), '{date_regex}') THEN TRY_CAST(TRIM({quoted_name}) as DATE) ELSE NULL END" # pylint: disable=C0301
+ stmt = rf"TRY_CAST({dt_cast_statement} as DATE)"
return stmt
if issubclass(type_, time):
- stmt = rf"CASE WHEN REGEXP_MATCHES(TRIM({quoted_name}), '{time_regex}') THEN TRY_CAST(TRIM({quoted_name}) as TIME) ELSE NULL END" # pylint: disable=C0301
+ stmt = rf"TRY_CAST({dt_cast_statement} as TIME)"
return stmt
duck_type = get_duckdb_type_from_annotation(type_)
if duck_type:
- stmt = f"trim({quoted_name})"
+ stmt = f"TRIM({quoted_name})"
return _cast_as_ddb_type(stmt, type_) if parent_element else stmt
raise ValueError(f"No equivalent DuckDB type for {type_annotation!r}")
diff --git a/src/dve/core_engine/backends/implementations/spark/contract.py b/src/dve/core_engine/backends/implementations/spark/contract.py
index 7215113..e84958e 100644
--- a/src/dve/core_engine/backends/implementations/spark/contract.py
+++ b/src/dve/core_engine/backends/implementations/spark/contract.py
@@ -7,6 +7,7 @@
from uuid import uuid4
from pydantic import BaseModel
+from pydantic.fields import ModelField
from pyspark.sql import DataFrame, SparkSession
from pyspark.sql import functions as sf
from pyspark.sql.functions import col, lit
@@ -26,6 +27,7 @@
)
from dve.core_engine.backends.implementations.spark.spark_helpers import (
df_is_empty,
+ get_spark_cast_statement_from_annotation,
get_type_from_annotation,
spark_read_parquet,
spark_record_index,
@@ -86,7 +88,7 @@ def create_entity_from_py_iterator(
schema=get_type_from_annotation(schema),
)
- # pylint: disable=R0915
+ # pylint: disable=R0914,R0915
def apply_data_contract(
self,
working_dir: URI,
@@ -102,6 +104,7 @@ def apply_data_contract(
successful = True
for entity_name, record_df in entities.items():
+ entity_fields: dict[str, ModelField] = contract_metadata.schemas[entity_name].__fields__
spark_schema = get_type_from_annotation(contract_metadata.schemas[entity_name])
spark_schema.add(StructField(RECORD_INDEX_COLUMN_NAME, LongType()))
if df_is_empty(record_df):
@@ -144,12 +147,21 @@ def apply_data_contract(
self.logger.info(f"Data contract found {msg_count} issues in {entity_name}")
try:
+ # TODO: will need to revisit in pydantic v2 bump as model field no longer available
record_df = record_df.select(
- [
- col(column.name).cast(column.dataType)
- for column in spark_schema
- if column.name in record_df.columns
- ]
+ *[
+ (
+ get_spark_cast_statement_from_annotation(
+ fld, mdl_field.annotation
+ ).alias(fld)
+ if fld in record_df.columns
+ else lit(None).cast(
+ get_type_from_annotation(mdl_field.annotation).alias(fld)
+ )
+ )
+ for fld, mdl_field in entity_fields.items()
+ ],
+ col(RECORD_INDEX_COLUMN_NAME).cast(LongType()).alias(RECORD_INDEX_COLUMN_NAME),
)
except Exception as err: # pylint: disable=broad-except
successful = False
diff --git a/src/dve/core_engine/backends/implementations/spark/spark_helpers.py b/src/dve/core_engine/backends/implementations/spark/spark_helpers.py
index c8e949d..ae714a6 100644
--- a/src/dve/core_engine/backends/implementations/spark/spark_helpers.py
+++ b/src/dve/core_engine/backends/implementations/spark/spark_helpers.py
@@ -28,6 +28,7 @@
from dve.common.error_utils import get_feedback_errors_uri
from dve.core_engine.backends.base.utilities import _get_non_heterogenous_type
+from dve.core_engine.backends.utilities import DEFAULT_ISO_FORMATS, datetime_format_to_regex
from dve.core_engine.constants import RECORD_INDEX_COLUMN_NAME
from dve.core_engine.type_hints import URI, EntityName
@@ -99,6 +100,21 @@ def __post_init__(self):
}
"""A mapping of Python types to the equivalent Spark types."""
+PYTHON_TO_JAVA_DT_FORMAT_MAP: dict[str, str] = {
+ "%Y": "yyyy",
+ "%y": "yy",
+ "%m": "MM",
+ "%d": "dd",
+ "%H": "HH",
+ "%M": "mm",
+ "%S": "ss",
+ "%z": "XX",
+ "%Z": "z",
+}
+"""A mapping of python to java datetime component formats. Not exhaustive but will hopefully support
+ all requirements.
+"""
+
PydanticModel = TypeVar("PydanticModel", bound=BaseModel)
"""An Pydantic model."""
@@ -272,6 +288,13 @@ def create_udf(function: Callable) -> Callable:
return udf(function, returnType=return_type)
+def python_to_java_datetime_format(datetime_fmt: str) -> str:
+ "Helper to convert python datetime formats to Java datetime formats"
+ for pt, jt in PYTHON_TO_JAVA_DT_FORMAT_MAP.items():
+ datetime_fmt = datetime_fmt.replace(pt, jt)
+ return datetime_fmt.replace("T", "'T'")
+
+
SupportedBaseType = Union[str, int, bool, float, Decimal, dt.date, dt.datetime]
"""Supported base types for Spark literals."""
SparkLiteralType = Union[ # type: ignore
@@ -506,11 +529,7 @@ def _spark_safely_quote_name(field_name: str) -> str:
# pylint: disable=R0801
def get_spark_cast_statement_from_annotation(
- element_name: str,
- type_annotation: Any,
- parent_element: bool = True,
- date_regex: str = r"^[0-9]{4}-[0-9]{2}-[0-9]{2}$",
- timestamp_regex: str = r"^[0-9]{4}-[0-9]{2}-[0-9]{2}T[0-9]{2}:[0-9]{2}:[0-9]{2}((\\+|\\-)[0-9]{2}:[0-9]{2})?$", # pylint: disable=C0301
+ element_name: str, type_annotation: Any, parent_element: bool = True
):
"""Generate casting statements for spark dataframes based on type annotations"""
type_origin = get_origin(type_annotation)
@@ -520,20 +539,18 @@ def get_spark_cast_statement_from_annotation(
# An `Optional` or `Union` type, check to ensure non-heterogenity.
if type_origin is Union:
python_type = _get_non_heterogenous_type(get_args(type_annotation))
- return get_spark_cast_statement_from_annotation(
- element_name, python_type, parent_element, date_regex, timestamp_regex
- )
+ return get_spark_cast_statement_from_annotation(element_name, python_type, parent_element)
# Type hint is e.g. `List[str]`, check to ensure non-heterogenity.
if type_origin is list or (isinstance(type_origin, type) and issubclass(type_origin, list)):
element_type = _get_non_heterogenous_type(get_args(type_annotation))
- stmt = f"transform({quoted_name}, x -> {get_spark_cast_statement_from_annotation('x',element_type, False, date_regex, timestamp_regex)})" # pylint: disable=C0301
+ stmt = f"TRANSFORM({quoted_name}, x -> {get_spark_cast_statement_from_annotation('x',element_type, False)})" # pylint: disable=C0301
return stmt if not parent_element else _cast_as_spark_type(stmt, type_annotation)
if type_origin is Annotated:
python_type, *_ = get_args(type_annotation) # pylint: disable=unused-variable
return get_spark_cast_statement_from_annotation(
- element_name, python_type, parent_element, date_regex, timestamp_regex
+ element_name, python_type, parent_element
) # add other expected params here
# Ensure that we have a concrete type at this point.
if not isinstance(type_annotation, type):
@@ -558,7 +575,7 @@ def get_spark_cast_statement_from_annotation(
continue
fields[field_name] = get_spark_cast_statement_from_annotation(
- f"{element_name}.{field_name}", field_annotation, False, date_regex, timestamp_regex
+ f"{element_name}.{field_name}", field_annotation, False
)
if not fields:
@@ -566,7 +583,7 @@ def get_spark_cast_statement_from_annotation(
f"No type annotations in dict/dataclass type (got {type_annotation!r})"
)
cast_exprs = ",".join([f"{stmt} AS `{nme}`" for nme, stmt in fields.items()])
- stmt = f"struct({cast_exprs})"
+ stmt = f"STRUCT({cast_exprs})"
return stmt if not parent_element else _cast_as_spark_type(stmt, type_annotation)
if type_annotation is list:
raise ValueError(
@@ -576,15 +593,29 @@ def get_spark_cast_statement_from_annotation(
raise ValueError(f"dict must be `typing.TypedDict` subclass, got {type_annotation!r}")
for type_ in type_annotation.mro():
+ _date_format: str = getattr( # type: ignore
+ type_,
+ "DATE_FORMAT",
+ DEFAULT_ISO_FORMATS.get(type_, DEFAULT_ISO_FORMATS.get(dt.datetime)),
+ )
+
+ # pylint: disable=C0301
+ dt_cast_statement = f"CASE WHEN REGEXP(TRIM({quoted_name}), '{datetime_format_to_regex(_date_format)}') THEN TRY_TO_TIMESTAMP(TRIM({quoted_name}), \"{python_to_java_datetime_format(_date_format)}\") ELSE NULL END" # pylint: disable=C0301
# datetime is subclass of date, so needs to be handled first
if issubclass(type_, dt.datetime):
- stmt = rf"CASE WHEN REGEXP(TRIM({quoted_name}), '{timestamp_regex}') THEN TRIM({quoted_name}) ELSE NULL END" # pylint: disable=C0301
- return _cast_as_spark_type(stmt, type_) if parent_element else stmt
+ return (
+ _cast_as_spark_type(dt_cast_statement, type_)
+ if parent_element
+ else dt_cast_statement
+ )
if issubclass(type_, dt.date):
- stmt = rf"CASE WHEN REGEXP(TRIM({quoted_name}), '{date_regex}') THEN TRIM({quoted_name}) ELSE NULL END" # pylint: disable=C0301
- return _cast_as_spark_type(stmt, type_) if parent_element else stmt
+ return (
+ _cast_as_spark_type(dt_cast_statement, type_)
+ if parent_element
+ else dt_cast_statement
+ )
spark_type = get_type_from_annotation(type_)
if spark_type:
- stmt = f"trim({quoted_name})"
+ stmt = f"TRIM({quoted_name})"
return _cast_as_spark_type(stmt, type_) if parent_element else stmt
raise ValueError(f"No equivalent Spark type for {type_annotation!r}")
diff --git a/src/dve/core_engine/backends/utilities.py b/src/dve/core_engine/backends/utilities.py
index ee4c2ab..66f4750 100644
--- a/src/dve/core_engine/backends/utilities.py
+++ b/src/dve/core_engine/backends/utilities.py
@@ -23,6 +23,49 @@
else:
from typing import Annotated, get_args, get_origin, get_type_hints
+DEFAULT_ISO_FORMATS: dict[type, str] = {
+ date: "%Y-%m-%d",
+ datetime: "%Y-%m-%dT%H:%M:%S",
+ time: "%H:%M:%S",
+}
+"""Mapping of default ISO formats to use when date format not supplied"""
+
+PYTHON_DATE_FORMAT_REGEX_HELPER: dict[str, str] = {
+ "Y": r"[0-9]{4}",
+ "y": r"[0-9]{2}",
+ "m": r"[0-9]{2}",
+ "d": r"[0-9]{2}",
+ "H": r"[0-9]{2}",
+ "M": r"[0-9]{2}",
+ "S": r"[0-9]{2}",
+ "z": r"(\+|\-)?[0-9]+(\.[0-9]*)?",
+ "Z": r"[A-Z]{0,3}",
+}
+
+REGEXP_NEED_ESCAPE_CHARS: tuple[str, str, str] = ("+", "-", ".")
+"""Helper to map python date format to regexp expression. Not exhaustive, but aims to cover
+ all foreseen use cases."""
+
+
+def datetime_format_to_regex(format_str: str) -> str:
+ """
+ Helper function to convert python datetime formats to regexp string checks for casting
+ purposes.
+ """
+
+ tokens = list(format_str.replace("%", ""))
+
+ for idx, tkn in enumerate(tokens):
+ if rpl := PYTHON_DATE_FORMAT_REGEX_HELPER.get(tkn):
+ tokens[idx] = rpl
+ elif tkn in REGEXP_NEED_ESCAPE_CHARS:
+ tokens[idx] = rf"\{tkn}"
+ else:
+ continue
+ tokens = [PYTHON_DATE_FORMAT_REGEX_HELPER.get(tkn, tkn) for tkn in tokens]
+ return "".join(["^", *tokens, "$"])
+
+
PYTHON_TYPE_TO_POLARS_TYPE: dict[type, PolarsType] = {
# issue with decimal conversion at the moment...
str: pl.Utf8, # type: ignore
diff --git a/tests/features/books.feature b/tests/features/books.feature
index 60cc5db..8551a6f 100644
--- a/tests/features/books.feature
+++ b/tests/features/books.feature
@@ -49,3 +49,30 @@ Feature: Pipeline tests using the books dataset
Then the latest audit record for the submission is marked with processing status error_report
When I run the error report phase
Then An error report is produced
+
+ Scenario: Validate complex nested XML data (spark)
+ Given I submit the books file nested_books.XML for processing
+ And A spark pipeline is configured with schema file 'nested_books.dischema.json'
+ And I add initial audit entries for the submission
+ Then the latest audit record for the submission is marked with processing status file_transformation
+ When I run the file transformation phase
+ Then the header entity is stored as a parquet after the file_transformation phase
+ And the nested_books entity is stored as a parquet after the file_transformation phase
+ And the latest audit record for the submission is marked with processing status data_contract
+ When I run the data contract phase
+ Then there is 1 record rejection from the data_contract phase
+ And the header entity is stored as a parquet after the data_contract phase
+ And the nested_books entity is stored as a parquet after the data_contract phase
+ And the latest audit record for the submission is marked with processing status business_rules
+ When I run the business rules phase
+ Then The rules restrict "nested_books" to 3 qualifying records
+ And The entity "nested_books" contains an entry for "17.85" in column "total_value_of_books"
+ And the nested_books entity is stored as a parquet after the business_rules phase
+ And the latest audit record for the submission is marked with processing status error_report
+ When I run the error report phase
+ Then An error report is produced
+ And The statistics entry for the submission shows the following information
+ | parameter | value |
+ | record_count | 4 |
+ | number_record_rejections | 2 |
+ | number_warnings | 0 |
diff --git a/tests/test_core_engine/test_backends/test_implementations/test_duckdb/test_duckdb_helpers.py b/tests/test_core_engine/test_backends/test_implementations/test_duckdb/test_duckdb_helpers.py
index 4a24960..7926ad9 100644
--- a/tests/test_core_engine/test_backends/test_implementations/test_duckdb/test_duckdb_helpers.py
+++ b/tests/test_core_engine/test_backends/test_implementations/test_duckdb/test_duckdb_helpers.py
@@ -22,8 +22,10 @@
duckdb_rel_to_dictionaries,
get_duckdb_cast_statement_from_annotation,
get_duckdb_type_from_annotation,
- relation_is_empty,
+ relation_is_empty
)
+from dve.core_engine.backends.utilities import datetime_format_to_regex
+from dve.metadata_parser.domain_types import formatteddatetime
@pytest.fixture
def casting_test_table(temp_ddb_conn):
@@ -34,26 +36,26 @@ def casting_test_table(temp_ddb_conn):
date_test VARCHAR,
timestamp_test VARCHAR,
list_int_field VARCHAR[],
- basic_model STRUCT(str_field VARCHAR, date_field VARCHAR),
- another_model STRUCT(unique_id VARCHAR, basic_models STRUCT(str_field VARCHAR, date_field VARCHAR)[]))""")
+ basic_model STRUCT(str_field VARCHAR, date_field VARCHAR, timestamp_field VARCHAR),
+ another_model STRUCT(unique_id VARCHAR, basic_models STRUCT(str_field VARCHAR, date_field VARCHAR, timestamp_field VARCHAR)[]))""")
conn.sql("""INSERT INTO test_casting
VALUES(
'good_one',
'1',
'2024-11-13',
- '2024-04-15 12:25:36',
+ '2021-04-15T12:25:36',
['1', '2', '3'],
- {'str_field': 'test', 'date_field': '2024-12-11'},
- {'unique_id': '1', "basic_models": [{'str_field': 'test_nest', 'date_field': '2020-01-04'}, {'str_field': 'test_nest2', 'date_field': '2020-01-05'}]}),
+ {'str_field': 'test', 'date_field': '2024-12-11', 'timestamp_field': '02/05/2017 12:34:56+0100'},
+ {'unique_id': '1', "basic_models": [{'str_field': 'test_nest', 'date_field': '2020-01-04', 'timestamp_field': '08/12/2017 23:42:17-0200'}, {'str_field': 'test_nest2', 'date_field': '2020-01-05', 'timestamp_field': '21/12/2025 23:42:17-0300'}]}),
(
'dodgy_dates',
'2',
'24-11-13',
'2024-4-15 12:25:36',
['4', '5', '6'],
- {'str_field': 'test', 'date_field': '202-1-11'},
- {'unique_id': '2', "basic_models": [{'str_field': 'test_dd', 'date_field': '20-01-04'}, {'str_field': 'test_dd2', 'date_field': '2020-1-5'}]})""")
+ {'str_field': 'test', 'date_field': '202-1-11', 'timestamp_field': '59/27/2019 59:59:82+1000'},
+ {'unique_id': '2', "basic_models": [{'str_field': 'test_dd', 'date_field': '20-01-04', 'timestamp_field': '1/2/34T12:11:23'}, {'str_field': 'test_dd2', 'date_field': '2020-1-5', 'timestamp_field': '2015-04-16 11:22:34+0100'}]})""")
yield temp_ddb_conn
@@ -117,6 +119,7 @@ def example_data_contract_error_codes(temp_ddb_conn):
class BasicModel(BaseModel):
str_field: str
date_field: datetime.date
+ timestamp_field: formatteddatetime(date_format="%d/%m/%Y %H:%M:%S%z") # type: ignore
class AnotherModel(BaseModel):
unique_id: int
@@ -214,13 +217,13 @@ def test_duckdb_rel_to_dictionaries(temp_ddb_conn: DuckDBPyConnection,
# add decimal check
@pytest.mark.parametrize("field_name,field_type,cast_statement",
- [("str_test", str, "try_cast(trim(\"str_test\") as VARCHAR)"),
- ("int_test", int, "try_cast(trim(\"int_test\") as BIGINT)"),
- ("date_test", datetime.date,"CASE WHEN REGEXP_MATCHES(TRIM(\"date_test\"), '^[0-9]{4}-[0-9]{2}-[0-9]{2}$') THEN TRY_CAST(TRIM(\"date_test\") as DATE) ELSE NULL END"),
- ("timestamp_test", datetime.datetime,"CASE WHEN REGEXP_MATCHES(TRIM(\"timestamp_test\"), '^[0-9]{4}-[0-9]{2}-[0-9]{2}T[0-9]{2}:[0-9]{2}:[0-9]{2}((\+|\-)[0-9]{2}:[0-9]{2})?$') THEN TRY_CAST(TRIM(\"timestamp_test\") as TIMESTAMP) ELSE NULL END"),
- ("list_int_field", list[int], "try_cast(list_transform(\"list_int_field\", x -> trim(\"x\")) as BIGINT[])"),
- ("basic_model", BasicModel, "try_cast(struct_pack(\"str_field\":= trim(\"basic_model\".str_field),\"date_field\":= CASE WHEN REGEXP_MATCHES(TRIM(\"basic_model\".date_field), '^[0-9]{4}-[0-9]{2}-[0-9]{2}$') THEN TRY_CAST(TRIM(\"basic_model\".date_field) as DATE) ELSE NULL END) as STRUCT(str_field VARCHAR, date_field DATE))"),
- ("another_model", AnotherModel, "try_cast(struct_pack(\"unique_id\":= trim(\"another_model\".unique_id),\"basic_models\":= list_transform(\"another_model\".basic_models, x -> struct_pack(\"str_field\":= trim(\"x\".str_field),\"date_field\":= CASE WHEN REGEXP_MATCHES(TRIM(\"x\".date_field), '^[0-9]{4}-[0-9]{2}-[0-9]{2}$') THEN TRY_CAST(TRIM(\"x\".date_field) as DATE) ELSE NULL END))) as STRUCT(unique_id BIGINT, basic_models STRUCT(str_field VARCHAR, date_field DATE)[]))")])
+ [("str_test", str, "TRY_CAST(TRIM(\"str_test\") as VARCHAR)"),
+ ("int_test", int, "TRY_CAST(TRIM(\"int_test\") as BIGINT)"),
+ ("date_test", datetime.date,"TRY_CAST(CASE WHEN REGEXP_FULL_MATCH(TRIM(\"date_test\"), '^[0-9]{4}\-[0-9]{2}\-[0-9]{2}$') THEN TRY_STRPTIME(TRIM(\"date_test\"), '%Y-%m-%d') ELSE NULL END as DATE)"),
+ ("timestamp_test", datetime.datetime, "TRY_CAST(CASE WHEN REGEXP_FULL_MATCH(TRIM(\"timestamp_test\"), '^[0-9]{4}\-[0-9]{2}\-[0-9]{2}T[0-9]{2}:[0-9]{2}:[0-9]{2}$') THEN TRY_STRPTIME(TRIM(\"timestamp_test\"), '%Y-%m-%dT%H:%M:%S') ELSE NULL END as TIMESTAMP)"),
+ ("list_int_field", list[int], "TRY_CAST(LIST_TRANSFORM(\"list_int_field\", x -> TRIM(\"x\")) as BIGINT[])"),
+ ("basic_model", BasicModel, "TRY_CAST(STRUCT_PACK(\"str_field\":= TRIM(\"basic_model\".str_field),\"date_field\":= TRY_CAST(CASE WHEN REGEXP_FULL_MATCH(TRIM(\"basic_model\".date_field), '^[0-9]{4}\-[0-9]{2}\-[0-9]{2}$') THEN TRY_STRPTIME(TRIM(\"basic_model\".date_field), '%Y-%m-%d') ELSE NULL END as DATE),\"timestamp_field\":= TRY_CAST(CASE WHEN REGEXP_FULL_MATCH(TRIM(\"basic_model\".timestamp_field), '^[0-9]{2}/[0-9]{2}/[0-9]{4} [0-9]{2}:[0-9]{2}:[0-9]{2}(\+|\-)?[0-9]+(\.[0-9]*)?$') THEN TRY_STRPTIME(TRIM(\"basic_model\".timestamp_field), '%d/%m/%Y %H:%M:%S%z') ELSE NULL END as TIMESTAMP)) as STRUCT(str_field VARCHAR, date_field DATE, timestamp_field TIMESTAMP))"),
+ ("another_model", AnotherModel, "TRY_CAST(STRUCT_PACK(\"unique_id\":= TRIM(\"another_model\".unique_id),\"basic_models\":= LIST_TRANSFORM(\"another_model\".basic_models, x -> STRUCT_PACK(\"str_field\":= TRIM(\"x\".str_field),\"date_field\":= TRY_CAST(CASE WHEN REGEXP_FULL_MATCH(TRIM(\"x\".date_field), '^[0-9]{4}\-[0-9]{2}\-[0-9]{2}$') THEN TRY_STRPTIME(TRIM(\"x\".date_field), '%Y-%m-%d') ELSE NULL END as DATE),\"timestamp_field\":= TRY_CAST(CASE WHEN REGEXP_FULL_MATCH(TRIM(\"x\".timestamp_field), '^[0-9]{2}/[0-9]{2}/[0-9]{4} [0-9]{2}:[0-9]{2}:[0-9]{2}(\+|\-)?[0-9]+(\.[0-9]*)?$') THEN TRY_STRPTIME(TRIM(\"x\".timestamp_field), '%d/%m/%Y %H:%M:%S%z') ELSE NULL END as TIMESTAMP)))) as STRUCT(unique_id BIGINT, basic_models STRUCT(str_field VARCHAR, date_field DATE, timestamp_field TIMESTAMP)[]))")])
def test_get_duckdb_cast_statement_from_annotation(field_name, field_type, cast_statement):
assert get_duckdb_cast_statement_from_annotation(field_name, field_type) == cast_statement
@@ -231,10 +234,15 @@ def test_use_cast_statements(casting_test_table):
casting_statements = [ f"{get_duckdb_cast_statement_from_annotation(fld.name, fld.annotation)} as {fld.name}" for fld in CastingRecord.__fields__.values()]
test_rel = test_rel.project(",".join(casting_statements))
assert dict(zip(test_rel.columns, test_rel.dtypes)) == {fld.name: get_duckdb_type_from_annotation(fld.annotation) for fld in CastingRecord.__fields__.values()}
+ good_date_rec = test_rel.pl()[0].to_dicts()[0]
dodgy_date_rec = test_rel.pl()[1].to_dicts()[0]
- assert (not dodgy_date_rec.get("date_test") and
- not dodgy_date_rec.get("basic_model",{}).get("date_field")
- and all(not val.get("date_field") for val in dodgy_date_rec.get("another_model",{}).get("basic_models",[]))
+ assert (good_date_rec.get("date_test") and good_date_rec.get("timestamp_test") and
+ good_date_rec.get("basic_model",{}).get("date_field") and good_date_rec.get("basic_model",{}).get("timestamp_field")
+ and all(val.get("date_field") and val.get("timestamp_field") for val in good_date_rec.get("another_model",{}).get("basic_models",[]))
+ )
+ assert (not dodgy_date_rec.get("date_test") and not dodgy_date_rec.get("timestamp_field") and
+ not dodgy_date_rec.get("basic_model",{}).get("date_field") and not dodgy_date_rec.get("basic_model",{}).get("timestamp_field")
+ and all(not (val.get("date_field") or val.get("timestamp_field")) for val in dodgy_date_rec.get("another_model",{}).get("basic_models",[]))
)
@@ -256,3 +264,10 @@ def test_relation_is_empty(temp_ddb_conn: DuckDBPyConnection):
_, con = temp_ddb_conn
rel = con.sql("SELECT 'abc' AS test").filter("test IS NULL")
assert relation_is_empty(rel)
+
+@pytest.mark.parametrize("date_format, expected_regex", [("%Y-%m-%d", r"^[0-9]{4}\-[0-9]{2}\-[0-9]{2}$"),
+ ("%Y-%m-%dT%H:%M:%S", r"^[0-9]{4}\-[0-9]{2}\-[0-9]{2}T[0-9]{2}:[0-9]{2}:[0-9]{2}$"),
+ ("%m/%d/%Y", r"^[0-9]{2}/[0-9]{2}/[0-9]{4}$"),
+ ("%Y/%m/%d %H:%M:%S%z", r"^[0-9]{4}/[0-9]{2}/[0-9]{2} [0-9]{2}:[0-9]{2}:[0-9]{2}(\+|\-)?[0-9]+(\.[0-9]*)?$")])
+def test_datetime_format_to_regex(date_format, expected_regex):
+ assert datetime_format_to_regex(date_format) == expected_regex
\ No newline at end of file
diff --git a/tests/test_core_engine/test_backends/test_implementations/test_spark/test_spark_helpers.py b/tests/test_core_engine/test_backends/test_implementations/test_spark/test_spark_helpers.py
index 8a0e45e..3fcf5d8 100644
--- a/tests/test_core_engine/test_backends/test_implementations/test_spark/test_spark_helpers.py
+++ b/tests/test_core_engine/test_backends/test_implementations/test_spark/test_spark_helpers.py
@@ -29,20 +29,22 @@
get_spark_cast_statement_from_annotation,
get_type_from_annotation,
object_to_spark_literal,
+ python_to_java_datetime_format,
)
+from dve.metadata_parser.domain_types import conformatteddate
from .....fixtures import spark # pylint: disable=unused-import
@pytest.fixture
def casting_dataframe(spark):
- data = [{"str_test": "good_one", "int_test": "1", "date_test": "2024-11-13", "timestamp_test": "2024-04-15 12:25:36",
- "list_int_field":['1', '2', '3'], "basic_model": {'str_field': 'test', 'date_field': '2024-12-11'},
- "another_model": {'unique_id': '1', "basic_models": [{'str_field': 'test_nest', 'date_field': '2020-01-04'}, {'str_field': 'test_nest2', 'date_field': '2020-01-05'}]}},
- {"str_test": "dodgy_dates", "int_test": "2", "date_test": "24-11-13", "timestamp_test": "2024-4-15 12:25:36",
- "list_int_field":['4', '5', '6'], "basic_model": {'str_field': 'test', 'date_field': '202-12-11'},
- "another_model": {'unique_id': '2', "basic_models": [{'str_field': 'test_dd', 'date_field': '20-01-04'}, {'str_field': 'test_dd2', 'date_field': '2020-1-05'}]}}]
+ data = [{"str_test": "good_one", "int_test": "1", "date_test": "2024-11-13", "timestamp_test": "2024-04-15T12:25:36",
+ "list_int_field":['1', '2', '3'], "basic_model": {'str_field': 'test', 'date_field': '12/11/2024' ,"timestamp_field": "2024-04-15T12:25:36"},
+ "another_model": {'unique_id': '1', "basic_models": [{'str_field': 'test_nest', 'date_field': '01/04/2020', "timestamp_field": "2023-07-09T12:25:36" }, {'str_field': 'test_nest2', 'date_field': '01/05/2020', "timestamp_field": "2026-02-21T13:25:36"}]}},
+ {"str_test": "dodgy_dates", "int_test": "2", "date_test": "11/13/24", "timestamp_test": "2024-4-15T12:25:36",
+ "list_int_field":['4', '5', '6'], "basic_model": {'str_field': 'test', 'date_field': '12/11/202', "timestamp_field": "2024-15-24T12:25:36"},
+ "another_model": {'unique_id': '2', "basic_models": [{'str_field': 'test_dd', 'date_field': '01/04/20', "timestamp_field": "20-15-24T12:92:36"}, {'str_field': 'test_dd2', 'date_field': '1/05/2020', "timestamp_field": "20-11-24T12:2:3"}]}}]
- bm_schema = StructType([StructField("str_field", StringType()), StructField("date_field", StringType())])
+ bm_schema = StructType([StructField("str_field", StringType()), StructField("date_field", StringType()), StructField("timestamp_field", StringType())])
schema = StructType([StructField("str_test", StringType()), StructField("int_test", StringType()), StructField("date_test", StringType()),
StructField("timestamp_test", StringType()), StructField("list_int_field", ArrayType(StringType())),
@@ -99,11 +101,10 @@ def example_data_contract_error_codes(spark: SparkSession):
yield test_df, temp_dir_path
-
class BasicModel(BaseModel):
str_field: str
- date_field: dt.date
-
+ date_field: conformatteddate(date_format="%m/%d/%Y") # type: ignore
+ timestamp_field: dt.datetime
class AnotherModel(BaseModel):
unique_id: int
basic_models: List[BasicModel]
@@ -298,13 +299,13 @@ def test_object_to_spark_literal_blocks_some_footguns(obj: Any):
object_to_spark_literal(obj)
@pytest.mark.parametrize("field_name,field_type,expression,spark_type",
- [("str_test", str, "trim(`str_test`)", StringType()),
- ("int_test", int, "trim(`int_test`)", LongType()),
- ("date_test", dt.date, "CASE WHEN REGEXP(TRIM(`date_test`), '^[0-9]{4}-[0-9]{2}-[0-9]{2}$') THEN TRIM(`date_test`) ELSE NULL END", DateType()),
- ("timestamp_test", dt.datetime, r"CASE WHEN REGEXP(TRIM(`timestamp_test`), '^[0-9]{4}-[0-9]{2}-[0-9]{2}T[0-9]{2}:[0-9]{2}:[0-9]{2}((\\+|\\-)[0-9]{2}:[0-9]{2})?$') THEN TRIM(`timestamp_test`) ELSE NULL END", TimestampType()),
- ("list_int_field", list[int], "transform(`list_int_field`, x -> trim(`x`))", ArrayType(LongType(), True)),
- ("basic_model", BasicModel, "struct(trim(`basic_model`.str_field) as str_field, CASE WHEN REGEXP(TRIM(`basic_model`.date_field), '^[0-9]{4}-[0-9]{2}-[0-9]{2}$') THEN TRIM(`basic_model`.date_field) ELSE NULL END as date_field)", StructType([StructField("str_field", StringType(), True), StructField("date_field", DateType(), True)])),
- ("another_model", AnotherModel, "struct(trim(`another_model`.unique_id) as unique_id, transform(`another_model`.basic_models, x -> struct(trim(x.str_field) as str_field, CASE WHEN REGEXP(TRIM(x.date_field), '^[0-9]{4}-[0-9]{2}-[0-9]{2}$') THEN TRIM(x.date_field) ELSE NULL END as date_field)) as basic_models)", StructType([StructField("unique_id", LongType(), True), StructField("basic_models", ArrayType(StructType([StructField("str_field", StringType()), StructField("date_field", DateType(), True)])))]))])
+ [("str_test", str, "TRIM(`str_test`)", StringType()),
+ ("int_test", int, "TRIM(`int_test`)", LongType()),
+ ("date_test", dt.date, "CASE WHEN REGEXP(TRIM(`date_test`), '^[0-9]{4}\-[0-9]{2}-[0-9]{2}$') THEN TRY_TO_TIMESTAMP(TRIM(`date_test`), \"yyyy-MM-dd\") ELSE NULL END", DateType()),
+ ("timestamp_test", dt.datetime, "CASE WHEN REGEXP(TRIM(`timestamp_test`), '^[0-9]{4}\-[0-9]{2}\-[0-9]{2}T[0-9]{2}:[0-9]{2}:[0-9]{2}$') THEN TRY_TO_TIMESTAMP(TRIM(`timestamp_test`), \"yyyy-MM-dd'T'HH:mm:ss\") ELSE NULL END", TimestampType()),
+ ("list_int_field", list[int], "TRANSFORM(`list_int_field`, x -> TRIM(`x`))", ArrayType(LongType(), True)),
+ ("basic_model", BasicModel, "STRUCT(TRIM(`basic_model`.str_field) as str_field, CASE WHEN REGEXP(TRIM(`basic_model`.date_field), '^[0-9]{2}/[0-9]{2}/[0-9]{4}$') THEN TRY_TO_TIMESTAMP(TRIM(`basic_model`.date_field), \"MM/dd/yyyy\") ELSE NULL END as date_field, CASE WHEN REGEXP(TRIM(`basic_model`.timestamp_field), '^[0-9]{4}\-[0-9]{2}\-[0-9]{2}T[0-9]{2}:[0-9]{2}:[0-9]{2}$') THEN TRY_TO_TIMESTAMP(TRIM(`basic_model`.timestamp_field), \"yyyy-MM-dd'T'HH:mm:ss\") ELSE NULL END as timestamp_field)", StructType([StructField("str_field", StringType(), True), StructField("date_field", DateType(), True), StructField("timestamp_field", TimestampType(), True)])),
+ ("another_model", AnotherModel, "STRUCT(TRIM(`another_model`.unique_id) as unique_id, TRANSFORM(`another_model`.basic_models, x -> STRUCT(TRIM(x.str_field) as str_field, CASE WHEN REGEXP(TRIM(x.date_field), '^[0-9]{2}/[0-9]{2}/[0-9]{4}$') THEN TRY_TO_TIMESTAMP(TRIM(x.date_field), \"MM/dd/yyyy\") ELSE NULL END as date_field, CASE WHEN REGEXP(TRIM(x.timestamp_field), '^[0-9]{4}\-[0-9]{2}\-[0-9]{2}T[0-9]{2}:[0-9]{2}:[0-9]{2}$') THEN TRY_TO_TIMESTAMP(TRIM(x.timestamp_field), \"yyyy-MM-dd'T'HH:mm:ss\") ELSE NULL END as timestamp_field)) as basic_models)", StructType([StructField("unique_id", LongType(), True), StructField("basic_models", ArrayType(StructType([StructField("str_field", StringType()), StructField("date_field", DateType(), True), StructField("timestamp_field", TimestampType(), True)])))]))])
def test_get_spark_cast_statement_from_annotation(field_name, field_type, expression, spark_type):
assert str(get_spark_cast_statement_from_annotation(field_name, field_type)) == str(expr(expression).cast(spark_type))
@@ -313,10 +314,14 @@ def test_use_cast_statements(spark, casting_dataframe):
casting_statements = [ get_spark_cast_statement_from_annotation(fld.name, fld.annotation).alias(fld.name) for fld in CastingRecord.__fields__.values()]
cast_df = casting_dataframe.select(*casting_statements)
assert {fld.name: fld.dataType for fld in cast_df.schema} == {fld.name: get_type_from_annotation(fld.annotation) for fld in CastingRecord.__fields__.values()}
- dodgy_date_rec = [rw.asDict(True) for rw in cast_df.collect()][1]
- assert (not dodgy_date_rec.get("date_test") and
- not dodgy_date_rec.get("basic_model",{}).get("date_field")
- and all(not val.get("date_field") for val in dodgy_date_rec.get("another_model",{}).get("basic_models",[]))
+ good_date_rec, dodgy_date_rec = (rw.asDict(True) for rw in cast_df.collect())
+ assert (good_date_rec.get("date_test") and good_date_rec.get("timestamp_test") and
+ good_date_rec.get("basic_model",{}).get("date_field") and good_date_rec.get("basic_model",{}).get("timestamp_field")
+ and all(val.get("date_field") and val.get("timestamp_field") for val in good_date_rec.get("another_model",{}).get("basic_models",[]))
+ )
+ assert (not dodgy_date_rec.get("date_test") and not dodgy_date_rec.get("timestamp_test") and
+ not dodgy_date_rec.get("basic_model",{}).get("date_field") and not dodgy_date_rec.get("basic_model",{}).get("timestamp_field")
+ and all(not (val.get("date_field") or val.get("timestamp_field")) for val in dodgy_date_rec.get("another_model",{}).get("basic_models",[]))
)
assert cast_df
@@ -340,3 +345,12 @@ def test_spark_filter_contract_errors(spark: SparkSession, example_data_contract
)
assert result_df.count() == 2
assert expected_df.join(result_df, "__record_index__", "anti").count() == 0
+
+
+@pytest.mark.parametrize("python_dt, expected_java_dt", [
+ ("%Y-%m-%d", "yyyy-MM-dd"),
+ ("%d/%m/%Y", "dd/MM/yyyy"),
+ ("%m/%d/%Y", "MM/dd/yyyy"),
+ ("%Y-%m-%dT%H:%M:%S", "yyyy-MM-dd'T'HH:mm:ss")])
+def test_python_to_java_datetime_format(python_dt, expected_java_dt):
+ assert python_to_java_datetime_format(python_dt) == expected_java_dt
diff --git a/tests/testdata/books/nested_books.XML b/tests/testdata/books/nested_books.XML
index 7dffc3e..4e27593 100644
--- a/tests/testdata/books/nested_books.XML
+++ b/tests/testdata/books/nested_books.XML
@@ -9,7 +9,7 @@
XML Developer's Guide
Computer
44.95
- 2000-10-01
+ 01-10-2000
An in-depth look at creating applications
with XML.
@@ -20,7 +20,7 @@
Midnight Rain
Fantasy
5.95
- 2000-12-16
+ 16-12-2000
A former architect battles corporate zombies,
an evil sorceress, and her own childhood to become queen
of the world.
@@ -35,7 +35,7 @@
Maeve Ascendant
Fantasy
5.95
- 2000-11-17
+ 17-11-2000
After the collapse of a nanotechnology
society in England, the young survivors lay the
foundation for a new society.
@@ -44,7 +44,7 @@
Oberon's Legacy
Fantasy
5.95
- 2001-03-10
+ 10-03-2001
In post-apocalypse England, the mysterious
agent known only as Oberon helps to create a new life
for the inhabitants of London. Sequel to Maeve
@@ -54,7 +54,7 @@
The Sundered Grail
Fantasy
5.95
- 2001-09-10
+ 10-09-2001
The two daughters of Maeve, half-sisters,
battle one another for control of England. Sequel to
Oberon's Legacy.
diff --git a/tests/testdata/books/nested_books.dischema.json b/tests/testdata/books/nested_books.dischema.json
index 5e53fce..52add54 100644
--- a/tests/testdata/books/nested_books.dischema.json
+++ b/tests/testdata/books/nested_books.dischema.json
@@ -1,12 +1,20 @@
{
"contract": {
+ "types": {
+ "non_iso_date": {
+ "callable": "conformatteddate",
+ "constraints": {
+ "date_format": "%d-%m-%Y"
+ }
+ }
+ },
"schemas": {
"book": {
"fields": {
"title": "str",
"genre": "str",
"price": "str",
- "publish_date": "date",
+ "publish_date": "non_iso_date",
"description": "str"
},
"mandatory_fields": [
diff --git a/tests/testdata/books/nested_books_ddb.dischema.json b/tests/testdata/books/nested_books_ddb.dischema.json
index b9c3314..d53c416 100644
--- a/tests/testdata/books/nested_books_ddb.dischema.json
+++ b/tests/testdata/books/nested_books_ddb.dischema.json
@@ -1,12 +1,20 @@
{
"contract": {
+ "types": {
+ "non_iso_date": {
+ "callable": "conformatteddate",
+ "constraints": {
+ "date_format": "%d-%m-%Y"
+ }
+ }
+ },
"schemas": {
"book": {
"fields": {
"title": "str",
"genre": "str",
"price": "str",
- "publish_date": "date",
+ "publish_date": "non_iso_date",
"description": "str"
},
"mandatory_fields": [