fix missing inlines in various headers and incorrect pointers in 'from_variable'

mdio/dataset.h

@@ -53,7 +53,7 @@ namespace internal {
  * @return An `mdio::Result` containing the .zarray JSON metadata on success, or
  * an error on failure.
  */
-Result<nlohmann::json> get_zarray(const ::nlohmann::json metadata) {
+inline Result<nlohmann::json> get_zarray(const ::nlohmann::json metadata) {
   // derive .zarray json metadata (without reading it).
   auto json =
       metadata;  // Why am I doing this? It's an extra copy that does nothing!
@@ -125,7 +125,7 @@ Result<nlohmann::json> get_zarray(const ::nlohmann::json metadata) {
  * @param json_variables The JSON variables.
  * @return An `mdio::Future<void>` representing the asynchronous write.
  */
-Future<void> write_zmetadata(
+inline Future<void> write_zmetadata(
     const ::nlohmann::json& dataset_metadata,
     const std::vector<::nlohmann::json>& json_variables) {
   // header material at the root of the dataset ...
@@ -252,7 +252,7 @@ Future<void> write_zmetadata(
  * It will default to the "file" driver if no prefix is found.
  * @param dataset_path The path to the dataset.
  */
-Future<tensorstore::KvStore> dataset_kvs_store(
+inline Future<tensorstore::KvStore> dataset_kvs_store(
     const std::string& dataset_path) {
   // the tensorstore driver needs a bucket field
   ::nlohmann::json kvstore;
@@ -298,7 +298,7 @@ Future<tensorstore::KvStore> dataset_kvs_store(
  * @return An `mdio::Future` containing the .zmetadata JSON on success, or an
  * error on failure.
  */
-Future<std::tuple<::nlohmann::json, std::vector<::nlohmann::json>>>
+inline Future<std::tuple<::nlohmann::json, std::vector<::nlohmann::json>>>
 from_zmetadata(const std::string& dataset_path) {
   // e.g. dataset_path = "zarrs/acceptance/";
   //  FIXME - enable async

mdio/dataset_factory.h

@@ -36,7 +36,7 @@
  * @param raw A string to be encoded
  * @return A string encoded in base64
  */
-std::string encode_base64(const std::string raw) {
+inline std::string encode_base64(const std::string raw) {
   std::string encoded = absl::Base64Escape(raw);
   return encoded;
 }
@@ -50,7 +50,7 @@ std::string encode_base64(const std::string raw) {
  * @return A string representing the dtype in numpy format limited to the dtypes
  * supported by MDIO Dataset
  */
-tensorstore::Result<std::string> to_zarr_dtype(const std::string dtype) {
+inline tensorstore::Result<std::string> to_zarr_dtype(const std::string dtype) {
   // Convert the input dtype to Zarr dtype
   if (dtype == "int8") {
     return "<i1";
@@ -93,8 +93,8 @@ tensorstore::Result<std::string> to_zarr_dtype(const std::string dtype) {
  * @return OkStatus if successful, InvalidArgumentError if dtype is not
  * supported
  */
-absl::Status transform_dtype(nlohmann::json& input /*NOLINT*/,
-                             nlohmann::json& variable /*NOLINT*/) {
+inline absl::Status transform_dtype(nlohmann::json& input /*NOLINT*/,
+                                    nlohmann::json& variable /*NOLINT*/) {
   if (input["dataType"].contains("fields")) {
     nlohmann::json dtypeFields = nlohmann::json::array();
     for (const auto& field : input["dataType"]["fields"]) {
@@ -124,8 +124,8 @@ absl::Status transform_dtype(nlohmann::json& input /*NOLINT*/,
  * @return OkStatus if successful, InvalidArgumentError if compressor is invalid
  * for MDIO
  */
-absl::Status transform_compressor(nlohmann::json& input /*NOLINT*/,
-                                  nlohmann::json& variable /*NOLINT*/) {
+inline absl::Status transform_compressor(nlohmann::json& input /*NOLINT*/,
+                                         nlohmann::json& variable /*NOLINT*/) {
   if (input.contains("compressor")) {
     if (input["compressor"].contains("name")) {
       if (input["compressor"]["name"] != "blosc") {
@@ -182,7 +182,7 @@ absl::Status transform_compressor(nlohmann::json& input /*NOLINT*/,
  * before this step This presumes that the user does not attempt to use these
  * functions directly
  */
-void transform_shape(
+inline void transform_shape(
     nlohmann::json& input /*NOLINT*/, nlohmann::json& variable /*NOLINT*/,
     std::unordered_map<std::string, uint64_t>& dimensionMap /*NOLINT*/) {
   if (input["dimensions"][0].is_object()) {
@@ -208,8 +208,8 @@ void transform_shape(
  * @param variable A Variable stub (Will be modified)
  * @return OkStatus if successful, InvalidArgumentError if the path is invalid
  */
-absl::Status transform_metadata(const std::string& path,
-                                nlohmann::json& variable /*NOLINT*/) {
+inline absl::Status transform_metadata(const std::string& path,
+                                       nlohmann::json& variable /*NOLINT*/) {
   std::string bucket =
       "NULL";  // Default value, if is NULL don't add a bucket field
   std::string driver = "file";
@@ -261,7 +261,7 @@ absl::Status transform_metadata(const std::string& path,
  * @param dimensionMap A map of dimension names to sizes
  * @return A Variable spec or an error if the Variable spec is invalid
  */
-tensorstore::Result<nlohmann::json> from_json_to_spec(
+inline tensorstore::Result<nlohmann::json> from_json_to_spec(
     nlohmann::json& json /*NOLINT*/,
     std::unordered_map<std::string, uint64_t>& dimensionMap /*NOLINT*/,
     const std::string& path) {
@@ -404,8 +404,8 @@ tensorstore::Result<nlohmann::json> from_json_to_spec(
  * @return A map of dimension names to sizes or error if the dimensions are not
  * consistently sized
  */
-tensorstore::Result<std::unordered_map<std::string, uint64_t>> get_dimensions(
-    nlohmann::json& spec /*NOLINT*/) {
+inline tensorstore::Result<std::unordered_map<std::string, uint64_t>>
+get_dimensions(nlohmann::json& spec /*NOLINT*/) {
   std::unordered_map<std::string, uint64_t> dimensions;
   for (auto& variable : spec["variables"]) {
     if (variable["dimensions"][0].is_object()) {
@@ -438,7 +438,8 @@ tensorstore::Result<std::unordered_map<std::string, uint64_t>> get_dimensions(
  * @param spec A Dataset spec
  * @return A vector of Variable specs or an error if the Dataset spec is invalid
  */
-tensorstore::Result<std::tuple<nlohmann::json, std::vector<nlohmann::json>>>
+inline tensorstore::Result<
+    std::tuple<nlohmann::json, std::vector<nlohmann::json>>>
 Construct(nlohmann::json& spec /*NOLINT*/, const std::string& path) {
   // Validation should only return status codes. If it returns data then it
   // should be a "constructor"

mdio/dataset_validator.h

@@ -30,8 +30,8 @@
  * @brief Checks if a key exists in a map
  * Specific for our case of {coordinate: index} mapping
  */
-bool contains(const std::unordered_set<std::string>& set,
-              const std::string key) {
+inline bool contains(const std::unordered_set<std::string>& set,
+                     const std::string key) {
   return set.count(key);
 }
 
@@ -42,7 +42,7 @@ bool contains(const std::unordered_set<std::string>& set,
  * @return OkStatus if valid, NotFoundError if schema file load fails,
  * InvalidArgumentError if validation fails for any reason
  */
-absl::Status validate_schema(nlohmann::json& spec /*NOLINT*/) {
+inline absl::Status validate_schema(nlohmann::json& spec /*NOLINT*/) {
   nlohmann::json targetSchema =
       nlohmann::json::parse(kDatasetSchema, nullptr, false);
   if (targetSchema.is_discarded()) {
@@ -72,7 +72,7 @@ absl::Status validate_schema(nlohmann::json& spec /*NOLINT*/) {
  * @return OkStatus if valid, InvalidArgumentError if a coordinate does not have
  * a matching Variable.
  */
-absl::Status validate_coordinates_present(const nlohmann::json& spec) {
+inline absl::Status validate_coordinates_present(const nlohmann::json& spec) {
   // Build a mapping of all the dimension coordinates
   std::unordered_set<std::string>
       dimension;  //  name of all 1-d Variables who's name matches the dimension
@@ -145,7 +145,7 @@ absl::Status validate_coordinates_present(const nlohmann::json& spec) {
  * reason
 
 */
-absl::Status validate_dataset(nlohmann::json& spec /*NOLINT*/) {
+inline absl::Status validate_dataset(nlohmann::json& spec /*NOLINT*/) {
   absl::Status schemaStatus = validate_schema(spec);
   if (!schemaStatus.ok()) {
     return schemaStatus;

mdio/utils/delete.h

@@ -34,7 +34,7 @@ namespace utils {
  * @return OK result if the dataset was valid and deleted successfully,
  * otherwise an error result
  */
-Result<void> DeleteDataset(const std::string dataset_path) {
+inline Result<void> DeleteDataset(const std::string dataset_path) {
   // Open the dataset
   // This is to ensure that what is getting deleted by MDIO is a valid MDIO
   // dataset itself.

mdio/variable.h

@@ -214,7 +214,7 @@ namespace internal {
  * @return A driver specific message if the status is a missing driver message,
  * otherwise the original status.
  */
-absl::Status CheckMissingDriverStatus(const absl::Status& status) {
+inline absl::Status CheckMissingDriverStatus(const absl::Status& status) {
   std::string error(status.message());
   if (error.find("Error parsing object member \"driver\"") !=
       std::string::npos) {
@@ -1837,10 +1837,12 @@ Result<VariableData<T, R, OriginKind>> from_variable(
     size_t element_size = variable.dtype().size();
 
     if (variable.dtype() == constants::kFloat32) {
-      auto* data = reinterpret_cast<float*>(_array.data());
+      auto* data =
+          reinterpret_cast<float*>(_array.byte_strided_origin_pointer().get());
       std::fill_n(data, num_elements, std::numeric_limits<float>::quiet_NaN());
     } else {  // double
-      auto* data = reinterpret_cast<double*>(_array.data());
+      auto* data =
+          reinterpret_cast<double*>(_array.byte_strided_origin_pointer().get());
       std::fill_n(data, num_elements, std::numeric_limits<double>::quiet_NaN());
     }
   }