basic xml (mostly copy pasted from text)

docs/source/nlp_load.mdx

@@ -33,4 +33,14 @@ To load remote text files via HTTP, pass the URLs instead:
 
 ```py
 >>> dataset = load_dataset("text", data_files="https://huggingface.co/datasets/lhoestq/test/resolve/main/some_text.txt")
-```
+```
+
+To load XML data you can use the "xml" loader, which is equivalent to "text" with sample_by="document":
+
+```py
+>>> from datasets import load_dataset
+>>> dataset = load_dataset("xml", data_files={"train": ["my_xml_1.xml", "my_xml_2.xml"], "test": "my_xml_file.xml"})
+
+# Load from a directory
+>>> dataset = load_dataset("xml", data_dir="path/to/xml/dataset")
+```

docs/source/package_reference/loading_methods.mdx

@@ -49,6 +49,12 @@ load_dataset("csv", data_dir="path/to/data/dir", sep="\t")
 
 [[autodoc]] datasets.packaged_modules.json.Json
 
+### XML
+
+[[autodoc]] datasets.packaged_modules.xml.XmlConfig
+
+[[autodoc]] datasets.packaged_modules.xml.Xml
+
 ### Parquet
 
 [[autodoc]] datasets.packaged_modules.parquet.ParquetConfig

src/datasets/packaged_modules/__init__.py

@@ -15,6 +15,7 @@
 from .sql import sql
 from .text import text
 from .webdataset import webdataset
+from .xml import xml
 
 
 def _hash_python_lines(lines: List[str]) -> str:
@@ -41,6 +42,7 @@ def _hash_python_lines(lines: List[str]) -> str:
     "imagefolder": (imagefolder.__name__, _hash_python_lines(inspect.getsource(imagefolder).splitlines())),
     "audiofolder": (audiofolder.__name__, _hash_python_lines(inspect.getsource(audiofolder).splitlines())),
     "webdataset": (webdataset.__name__, _hash_python_lines(inspect.getsource(webdataset).splitlines())),
+    "xml": (xml.__name__, _hash_python_lines(inspect.getsource(xml).splitlines())),
 }
 
 # get importable module names and hash for caching
@@ -69,6 +71,7 @@ def _hash_python_lines(lines: List[str]) -> str:
     ".arrow": ("arrow", {}),
     ".txt": ("text", {}),
     ".tar": ("webdataset", {}),
+    ".xml": ("xml", {}),
 }
 _EXTENSION_TO_MODULE.update({ext: ("imagefolder", {}) for ext in imagefolder.ImageFolder.EXTENSIONS})
 _EXTENSION_TO_MODULE.update({ext.upper(): ("imagefolder", {}) for ext in imagefolder.ImageFolder.EXTENSIONS})

src/datasets/packaged_modules/xml/xml.py

@@ -0,0 +1,68 @@
+import itertools
+from dataclasses import dataclass
+from typing import Optional
+
+import pyarrow as pa
+
+import datasets
+from datasets.features.features import require_storage_cast
+from datasets.table import table_cast
+
+
+logger = datasets.utils.logging.get_logger(__name__)
+
+
+@dataclass
+class XmlConfig(datasets.BuilderConfig):
+    """BuilderConfig for xml files."""
+
+    features: Optional[datasets.Features] = None
+    encoding: str = "utf-8"
+    encoding_errors: Optional[str] = None
+
+
+class Xml(datasets.ArrowBasedBuilder):
+    BUILDER_CONFIG_CLASS = XmlConfig
+
+    def _info(self):
+        return datasets.DatasetInfo(features=self.config.features)
+
+    def _split_generators(self, dl_manager):
+        """The `data_files` kwarg in load_dataset() can be a str, List[str], Dict[str,str], or Dict[str,List[str]].
+
+        If str or List[str], then the dataset returns only the 'train' split.
+        If dict, then keys should be from the `datasets.Split` enum.
+        """
+        if not self.config.data_files:
+            raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
+        dl_manager.download_config.extract_on_the_fly = True
+        data_files = dl_manager.download_and_extract(self.config.data_files)
+        splits = []
+        for split_name, files in data_files.items():
+            if isinstance(files, str):
+                files = [files]
+            files = [dl_manager.iter_files(file) for file in files]
+            splits.append(datasets.SplitGenerator(name=split_name, gen_kwargs={"files": files}))
+        return splits
+
+    def _cast_table(self, pa_table: pa.Table) -> pa.Table:
+        if self.config.features is not None:
+            schema = self.config.features.arrow_schema
+            if all(not require_storage_cast(feature) for feature in self.config.features.values()):
+                # cheaper cast
+                pa_table = pa_table.cast(schema)
+            else:
+                # more expensive cast; allows str <-> int/float or str to Audio for example
+                pa_table = table_cast(pa_table, schema)
+            return pa_table
+        else:
+            return pa_table.cast(pa.schema({"xml": pa.string()}))
+
+    def _generate_tables(self, files):
+        pa_table_names = list(self.config.features) if self.config.features is not None else ["xml"]
+        for file_idx, file in enumerate(itertools.chain.from_iterable(files)):
+            # open in text mode, by default translates universal newlines ("\n", "\r\n" and "\r") into "\n"
+            with open(file, encoding=self.config.encoding, errors=self.config.encoding_errors) as f:
+                xml = f.read()
+                pa_table = pa.Table.from_arrays([pa.array([xml])], names=pa_table_names)
+                yield file_idx, self._cast_table(pa_table)