VARCHAR support (#227)

innobi · Jan 18, 2024 · 00f0c54 · 00f0c54
1 parent 48f6541
commit 00f0c54
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Showing 2 changed files with 56 additions and 33 deletions.
diff --git a/pantab/src/pantab.cpp b/pantab/src/pantab.cpp
@@ -615,36 +615,22 @@ static auto makeReadHelper(const ArrowSchemaView *schema_view,
   }
 }
 
-static auto
-arrowTypeFromHyper(const hyperapi::SqlType &sqltype) -> enum ArrowType {
-  if (sqltype == hyperapi::SqlType::smallInt()){return NANOARROW_TYPE_INT16;}
-else if (sqltype == hyperapi::SqlType::integer()) {
-  return NANOARROW_TYPE_INT32;
-}
-else if (sqltype == hyperapi::SqlType::bigInt()) {
-  return NANOARROW_TYPE_INT64;
-}
-else if (sqltype == hyperapi::SqlType::doublePrecision()) {
-  return NANOARROW_TYPE_DOUBLE;
-}
-else if (sqltype == hyperapi::SqlType::text()) {
-  return NANOARROW_TYPE_LARGE_STRING;
-}
-else if (sqltype == hyperapi::SqlType::boolean()) {
-  return NANOARROW_TYPE_BOOL;
-}
-else if (sqltype == hyperapi::SqlType::timestamp()) {
-  return NANOARROW_TYPE_TIMESTAMP;
-}
-else if (sqltype == hyperapi::SqlType::timestampTZ()) {
-  return NANOARROW_TYPE_TIMESTAMP; // todo: how to encode tz info?
-}
-else if (sqltype == hyperapi::SqlType::date()) {
-  return NANOARROW_TYPE_DATE32;
-}
-
-throw nb::type_error(
-    ("unimplemented pandas dtype for type: " + sqltype.toString()).c_str());
+static auto arrowTypeFromHyper(const hyperapi::SqlType &sqltype)
+    -> enum ArrowType {
+      switch (sqltype.getTag()){
+        case hyperapi::TypeTag::SmallInt : return NANOARROW_TYPE_INT16;
+        case hyperapi::TypeTag::Int : return NANOARROW_TYPE_INT32;
+        case hyperapi::TypeTag::BigInt : return NANOARROW_TYPE_INT64;
+        case hyperapi::TypeTag::Double : return NANOARROW_TYPE_DOUBLE;
+        case hyperapi::TypeTag::Varchar : case hyperapi::TypeTag::Char :
+            case hyperapi::TypeTag::Text : return NANOARROW_TYPE_LARGE_STRING;
+        case hyperapi::TypeTag::Bool : return NANOARROW_TYPE_BOOL;
+        case hyperapi::TypeTag::Date : return NANOARROW_TYPE_DATE32;
+        case hyperapi::TypeTag::Timestamp : case hyperapi::TypeTag::
+        TimestampTZ : return NANOARROW_TYPE_TIMESTAMP;
+        default : throw nb::type_error(
+            ("Reader not implemented for type: " + sqltype.toString()).c_str());
+      }
 }
 
 static auto releaseArrowStream(void *ptr) noexcept -> void {

diff --git a/pantab/tests/test_reader.py b/pantab/tests/test_reader.py
@@ -1,7 +1,7 @@
 import pandas as pd
 import pandas.testing as tm
 import pytest
-from tableauhyperapi import TableName
+import tableauhyperapi as tab_api
 
 import pantab
 
@@ -31,7 +31,7 @@ def test_reports_unsupported_type(datapath):
 
 def test_read_non_roundtrippable(datapath):
     result = pantab.frame_from_hyper(
-        datapath / "dates.hyper", table=TableName("Extract", "Extract")
+        datapath / "dates.hyper", table=tab_api.TableName("Extract", "Extract")
     )
     expected = pd.DataFrame(
         [["1900-01-01", "2000-01-01"], [pd.NaT, "2050-01-01"]],
@@ -43,7 +43,8 @@ def test_read_non_roundtrippable(datapath):
 
 def test_reads_non_writeable(datapath):
     result = pantab.frame_from_hyper(
-        datapath / "non_pantab_writeable.hyper", table=TableName("public", "table")
+        datapath / "non_pantab_writeable.hyper",
+        table=tab_api.TableName("public", "table"),
     )
 
     expected = pd.DataFrame(
@@ -85,3 +86,39 @@ def test_empty_read_query(df: pd.DataFrame, roundtripped, tmp_hyper):
 
     result = pantab.frame_from_hyper_query(tmp_hyper, query)
     tm.assert_frame_equal(result, expected)
+
+
+def test_read_varchar(tmp_hyper):
+    column_name = "VARCHAR Column"
+    table_name = tab_api.TableName("public", "table")
+    table = tab_api.TableDefinition(
+        table_name=table_name,
+        columns=[
+            tab_api.TableDefinition.Column(
+                name=column_name,
+                type=tab_api.SqlType.varchar(42),
+                nullability=tab_api.NOT_NULLABLE,
+            )
+        ],
+    )
+
+    with tab_api.HyperProcess(
+        telemetry=tab_api.Telemetry.DO_NOT_SEND_USAGE_DATA_TO_TABLEAU
+    ) as hyper:
+        with tab_api.Connection(
+            endpoint=hyper.endpoint,
+            database=tmp_hyper,
+            create_mode=tab_api.CreateMode.CREATE_AND_REPLACE,
+        ) as connection:
+            connection.catalog.create_table(table_definition=table)
+
+            with tab_api.Inserter(connection, table) as inserter:
+                inserter.add_rows([["foo"], ["bar"]])
+                inserter.execute()
+
+    expected = pd.DataFrame(
+        [["foo"], ["bar"]], columns=[column_name], dtype="large_string[pyarrow]"
+    )
+
+    result = pantab.frame_from_hyper(tmp_hyper, table=table_name)
+    tm.assert_frame_equal(result, expected)