Support writing dictionary-encoded strings

src/pantab/writer.cpp

@@ -64,6 +64,25 @@ static auto GetHyperTypeFromArrowSchema(struct ArrowSchema *schema,
     constexpr int16_t scale = 0;
     return hyperapi::SqlType::numeric(precision, scale);
   }
+  case NANOARROW_TYPE_DICTIONARY: {
+    struct ArrowSchemaView value_view {};
+    struct ArrowError error {};
+    NANOARROW_THROW_NOT_OK(
+        ArrowSchemaViewInit(&value_view, schema->dictionary, &error));
+
+    // only support dictionary-encoded string values for now
+    switch (value_view.type) {
+    case NANOARROW_TYPE_STRING:
+    case NANOARROW_TYPE_LARGE_STRING:
+    case NANOARROW_TYPE_STRING_VIEW:
+      return hyperapi::SqlType::text();
+    default:
+      throw std::invalid_argument(
+          std::string(
+              "Can only encode dictionaries with binary value types, got:") +
+          ArrowTypeString(value_view.type));
+    }
+  }
   default:
     throw std::invalid_argument(std::string("Unsupported Arrow type: ") +
                                 ArrowTypeString(schema_view.type));
@@ -467,6 +486,26 @@ class DecimalInsertHelper : public InsertHelper {
   int32_t scale_;
 };
 
+class DictionaryInsertHelper : public InsertHelper {
+public:
+  using InsertHelper::InsertHelper;
+
+  void InsertValueAtIndex(int64_t idx) override {
+    if (CheckNull(idx)) {
+      InsertNull<hyperapi::Time>();
+      return;
+    }
+
+    const auto key = ArrowArrayViewGetIntUnsafe(GetArrayView(), idx);
+    const auto value =
+        ArrowArrayViewGetStringUnsafe(GetArrayView()->dictionary, key);
+
+    const hyperapi::string_view result{value.data,
+                                       static_cast<size_t>(value.size_bytes)};
+    InsertValue(std::move(result));
+  }
+};
+
 static auto MakeInsertHelper(hyperapi::Inserter &inserter,
                              struct ArrowArray *chunk,
                              const struct ArrowSchema *schema,
@@ -593,6 +632,25 @@ static auto MakeInsertHelper(hyperapi::Inserter &inserter,
   case NANOARROW_TYPE_STRING_VIEW:
     return std::make_unique<BinaryViewInsertHelper<true>>(
         inserter, chunk, child_schema, error, column_position);
+  case NANOARROW_TYPE_DICTIONARY: {
+    struct ArrowSchemaView value_view {};
+    NANOARROW_THROW_NOT_OK(
+        ArrowSchemaViewInit(&value_view, child_schema->dictionary, error));
+
+    // only support dictionary-encoded string values for now
+    switch (value_view.type) {
+    case NANOARROW_TYPE_STRING:
+    case NANOARROW_TYPE_LARGE_STRING:
+    case NANOARROW_TYPE_STRING_VIEW:
+      return std::make_unique<DictionaryInsertHelper>(
+          inserter, chunk, child_schema, error, column_position);
+    default:
+      throw std::invalid_argument(
+          std::string("MakeInsertHelper: Can only encode dictionaries with "
+                      "binary value types, got:") +
+          ArrowTypeString(value_view.type));
+    }
+  }
   default:
     throw std::invalid_argument(
         std::string("MakeInsertHelper: Unsupported Arrow type: ") +

tests/conftest.py

@@ -46,6 +46,7 @@ def basic_arrow_table():
             ("decimal", pa.decimal128(38, 10)),
             ("string_view", pa.string_view()),
             ("binary_view", pa.binary_view()),
+            ("categorical", pa.dictionary(pa.int8(), pa.utf8())),
         ]
     )
     tbl = pa.Table.from_arrays(
@@ -110,6 +111,7 @@ def basic_arrow_table():
             pa.array(["1234567890.123456789", "99876543210.987654321", None]),
             pa.array(["foo", "longer_than_prefix_size", None], type=pa.string_view()),
             pa.array([b"foo", b"longer_than_prefix_size", None], type=pa.binary_view()),
+            pa.array(["foo", "foo", None]),
         ],
         schema=schema,
     )
@@ -291,13 +293,15 @@ def basic_dataframe():
         dtype=pd.ArrowDtype(pa.decimal128(38, 10)),
     )
     """
+    https://github.com/pandas-dev/pandas/issues/59883
     df["string_view"] = pd.Series(
         ["foo", "longer_than_prefix_size", None],
         dtype=pd.ArrowDtype(pa.string_view())),
     df["binary_view"] = pd.Series(
         [b"foo", b"longer_than_prefix_size", None],
         dtype=pd.ArrowDtype(pa.binary_view())),
     """
+    df["categorical"] = pd.Series(["foo", "foo", pd.NA]).astype(pd.CategoricalDtype())
 
     return df
 
@@ -374,13 +378,15 @@ def roundtripped_pyarrow():
 
     # pyarrow does not support casting from string_view to large_string,
     # so we have to handle manually
-    tbl = tbl.drop_columns(["string_view", "binary_view"])
+    tbl = tbl.drop_columns(["string_view", "binary_view", "categorical"])
     tbl = tbl.cast(schema)
 
     sv = (pa.array(["foo", "longer_than_prefix_size", None], type=pa.large_string()),)
     bv = pa.array([b"foo", b"longer_than_prefix_size", None], type=pa.large_binary())
+    cat = pa.array(["foo", "foo", None], type=pa.large_string())
     tbl = tbl.append_column("string_view", sv)
     tbl = tbl.append_column("binary_view", bv)
+    tbl = tbl.append_column("categorical", cat)
 
     return tbl
 
@@ -420,6 +426,7 @@ def roundtripped_pandas():
             "geography": "large_binary[pyarrow]",
             # "string_view": "string_view[pyarrow]",
             # "binary_view": "binary_view[pyarrow]",
+            "categorical": "large_string[pyarrow]",
         }
     )
     return df