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fix(datasets): Cleanup of dependency #822

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merged 4 commits into from
Sep 9, 2024
Merged

fix(datasets): Cleanup of dependency #822

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3425b28
Update dependencies
DmitrySorokinQB Sep 3, 2024
1e8e49c
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DmitrySorokinQB Sep 6, 2024
54aae58
Merge branch 'main' into 747-kedro-datasets-cleanup-of-dependency-groups
DimedS Sep 6, 2024
25d93a0
Merge branch 'main' into 747-kedro-datasets-cleanup-of-dependency-groups
DimedS Sep 9, 2024
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26 changes: 18 additions & 8 deletions kedro-datasets/pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -33,8 +33,9 @@ api = ["kedro-datasets[api-apidataset]"]
biosequence-biosequencedataset = ["biopython~=1.73"]
biosequence = ["kedro-datasets[biosequence-biosequencedataset]"]

dask-csvdataset = ["dask[dataframe]>=2021.10"]
dask-parquetdataset = ["dask[complete]>=2021.10", "triad>=0.6.7, <1.0"]
dask = ["kedro-datasets[dask-parquetdataset]"]
dask = ["kedro-datasets[dask-parquetdataset, dask-csvdataset]"]

databricks-managedtabledataset = ["kedro-datasets[spark-base,pandas-base,delta-base,hdfs-base,s3fs-base]"]
databricks = ["kedro-datasets[databricks-managedtabledataset]"]
Expand Down Expand Up @@ -127,9 +128,12 @@ plotly = ["kedro-datasets[plotly-htmldataset,plotly-jsondataset,plotly-plotlydat

polars-csvdataset = ["kedro-datasets[polars-base]"]
polars-eagerpolarsdataset = ["kedro-datasets[polars-base]", "pyarrow>=4.0", "xlsx2csv>=0.8.0", "deltalake >= 0.6.2"]
polars-genericdataset = ["kedro-datasets[polars-base]", "pyarrow>=4.0", "xlsx2csv>=0.8.0", "deltalake >= 0.6.2"]
polars-lazypolarsdataset = ["kedro-datasets[polars-base]", "pyarrow>=4.0", "deltalake >= 0.6.2"]
polars = ["kedro-datasets[polars-genericdataset]"]
polars = [
"""kedro-datasets[polars-csvdataset,\
polars-eagerpolarsdataset,\
polars-lazypolarsdataset]"""
]

redis-pickledataset = ["redis~=4.1"]
redis = ["kedro-datasets[redis-pickledataset]"]
Expand All @@ -140,8 +144,15 @@ snowflake = ["kedro-datasets[snowflake-snowparktabledataset]"]
spark-deltatabledataset = ["kedro-datasets[spark-base,hdfs-base,s3fs-base,delta-base]"]
spark-sparkdataset = ["kedro-datasets[spark-base,hdfs-base,s3fs-base]"]
spark-sparkhivedataset = ["kedro-datasets[spark-base,hdfs-base,s3fs-base]"]
spark-sparkjdbcdataset = ["kedro-datasets[spark-base,hdfs-base,s3fs-base]"]
spark = ["kedro-datasets[spark-deltatabledataset]"]
spark-sparkjdbcdataset = ["kedro-datasets[spark-base]"]
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does jbdbcdataset not need the hdfs-base or s3fs-base anymore?

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I believe JDBC is intended for relational databases and cannot be used with HDFS or S3FS?

spark-sparkstreamingdataset = ["kedro-datasets[spark-base,hdfs-base,s3fs-base]"]
spark = [
"""kedro-datasets[spark-deltatabledataset,\
spark-sparkdataset,\
spark-sparkhivedataset,\
spark-sparkjdbcdataset,\
spark-sparkstreamingdataset]"""
]

svmlight-svmlightdataset = ["scikit-learn>=1.0.2", "scipy~=1.7.3"]
svmlight = ["kedro-datasets[svmlight-svmlightdataset]"]
Expand Down Expand Up @@ -209,7 +220,7 @@ test = [
"ibis-framework[duckdb,examples]",
"import-linter[toml]==1.2.6",
"ipython>=7.31.1, <8.0",
"Jinja2<3.1.0",
"Jinja2<3.2.0",
"joblib>=0.14",
"jupyterlab>=3.0",
"jupyter~=1.0",
Expand Down Expand Up @@ -248,8 +259,7 @@ test = [
"scipy>=1.7.3",
"packaging",
"SQLAlchemy>=1.2",
"tables>=3.8.0; platform_system == 'Windows'", # Import issues with python 3.8 with pytables pinning to 3.8.0 fixes this https://github.com/PyTables/PyTables/issues/933#issuecomment-1555917593
"tables~=3.6; platform_system != 'Windows'",
"tables~=3.6",
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"tensorflow-macos~=2.0; platform_system == 'Darwin' and platform_machine == 'arm64'",
"tensorflow~=2.0; platform_system != 'Darwin' or platform_machine != 'arm64'",
"triad>=0.6.7, <1.0",
Expand Down