Better windows support

.circleci/config.yml

@@ -1,4 +1,8 @@
-version: 2
+version: 2.1
+
+orbs:
+    win: circleci/windows@2.2.0
+
 jobs:
     run_dataset_script_tests_pyarrow_0p17:
         working_directory: ~/datasets
@@ -26,6 +30,41 @@ jobs:
             - run: pip install pyarrow==1.0.0
             - run: HF_SCRIPTS_VERSION=master python -m pytest -sv ./tests/
 
+
+    run_dataset_script_tests_pyarrow_0p17_WIN:
+        working_directory: ~/datasets
+        executor:
+            name: win/default
+            shell: powershell
+        steps:
+            - checkout
+            - run: conda install python=3.6 --yes
+            - run: conda install pytorch --yes
+            - run: pip install virtualenv
+            - run: python -m virtualenv venv --system-site-packages
+            - run: "& venv/Scripts/activate.ps1"
+            - run: pip install .[tests]
+            - run: pip install pyarrow==0.17.1
+            - run: $env:HF_SCRIPTS_VERSION="master"
+            - run: python -m pytest -sv ./tests/
+
+    run_dataset_script_tests_pyarrow_1_WIN:
+        working_directory: ~/datasets
+        executor:
+            name: win/default
+            shell: powershell
+        steps:
+            - checkout
+            - run: conda install python=3.6 --yes
+            - run: conda install pytorch --yes
+            - run: pip install virtualenv
+            - run: python -m virtualenv venv --system-site-packages
+            - run: "& venv/Scripts/activate.ps1"
+            - run: pip install .[tests]
+            - run: pip install pyarrow==1.0.0
+            - run: $env:HF_SCRIPTS_VERSION="master"
+            - run: python -m pytest -sv ./tests/
+
     check_code_quality:
         working_directory: ~/datasets
         docker:
@@ -38,6 +77,7 @@ jobs:
             - run: black --check --line-length 119 --target-version py36 tests src benchmarks datasets metrics
             - run: isort --check-only tests src benchmarks datasets metrics
             - run: flake8 tests src benchmarks datasets metrics
+
     build_doc:
         working_directory: ~/datasets
         docker:
@@ -48,6 +88,7 @@ jobs:
             - run: cd docs && make html SPHINXOPTS="-W"
             - store_artifacts:
                   path: ./docs/_build
+
     deploy_doc:
         working_directory: ~/datasets
         docker:
@@ -73,5 +114,7 @@ workflows:
             - check_code_quality
             - run_dataset_script_tests_pyarrow_0p17
             - run_dataset_script_tests_pyarrow_1
+            - run_dataset_script_tests_pyarrow_0p17_WIN
+            - run_dataset_script_tests_pyarrow_1_WIN
             - build_doc
             - deploy_doc: *workflow_filters

datasets/sogou_news/sogou_news.py

@@ -19,13 +19,13 @@
 from __future__ import absolute_import, division, print_function
 
 import csv
+import ctypes
 import os
-import sys
 
 import datasets
 
 
-csv.field_size_limit(sys.maxsize)
+csv.field_size_limit(int(ctypes.c_ulong(-1).value // 2))
 
 
 _CITATION = """\

setup.py

@@ -107,6 +107,9 @@
     'zstandard'
 ]
 
+if os.name == "nt":  # windows
+    TESTS_REQUIRE.remove("faiss-cpu")  # faiss doesn't exist on windows
+
 
 QUALITY_REQUIRE = [
     "black",

src/datasets/arrow_dataset.py

@@ -28,6 +28,7 @@
 from functools import partial, wraps
 from math import ceil, floor
 from multiprocessing import Pool, RLock
+from pathlib import Path
 from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
 
 import numpy as np
@@ -374,6 +375,12 @@ def from_dict(
         pa_table: pa.Table = pa.Table.from_pydict(mapping=mapping)
         return cls(pa_table, info=info, split=split)
 
+    def __del__(self):
+        if hasattr(self, "_data"):
+            del self._data
+        if hasattr(self, "_indices"):
+            del self._indices
+
     def __getstate__(self):
         state = dict(self.__dict__)
         state["_info"] = json.dumps(asdict(state["_info"]))
@@ -443,7 +450,7 @@ def save_to_disk(self, dataset_path: str):
         for data_file in self._data_files + self._indices_data_files:
             # Copy file to destination directory
             src = data_file["filename"]
-            filename = src.split("/")[-1]
+            filename = Path(src).name
             dest = os.path.join(dataset_path, filename)
             if src != dest:
                 shutil.copy(src, dest)
@@ -458,9 +465,9 @@ def save_to_disk(self, dataset_path: str):
             len(h["transforms"]) == 0 for h in state.get("_inplace_history", [])
         ), "in-place history needs to be empty"
         # Serialize state
-        with open(os.path.join(dataset_path, "state.json"), "w") as state_file:
+        with open(os.path.join(dataset_path, "state.json"), "w", encoding="utf-8") as state_file:
             json.dump(state, state_file, indent=2, sort_keys=True)
-        with open(os.path.join(dataset_path, "dataset_info.json"), "w") as dataset_info_file:
+        with open(os.path.join(dataset_path, "dataset_info.json"), "w", encoding="utf-8") as dataset_info_file:
             json.dump(dataset_info, dataset_info_file, indent=2, sort_keys=True)
         logger.info("Dataset saved in {}".format(dataset_path))
 
@@ -471,9 +478,9 @@ def load_from_disk(dataset_path: str) -> "Dataset":
         Args:
             dataset_path (``str``): path of the dataset directory where the dataset will be loaded from
         """
-        with open(os.path.join(dataset_path, "state.json"), "r") as state_file:
+        with open(os.path.join(dataset_path, "state.json"), "r", encoding="utf-8") as state_file:
             state = json.load(state_file)
-        with open(os.path.join(dataset_path, "dataset_info.json"), "r") as dataset_info_file:
+        with open(os.path.join(dataset_path, "dataset_info.json"), "r", encoding="utf-8") as dataset_info_file:
             dataset_info = json.load(dataset_info_file)
         state["_info"] = json.dumps(dataset_info)
         dataset = Dataset.from_dict({})
@@ -1500,12 +1507,16 @@ def apply_function_on_filtered_inputs(inputs, indices, check_same_num_examples=F
             if update_data:
                 writer.finalize()  # close_stream=bool(buf_writer is None))  # We only close if we are writing in a file
         except (Exception, KeyboardInterrupt):
+            if update_data:
+                writer.finalize()
             if update_data and tmp_file is not None:
+                tmp_file.close()
                 if os.path.exists(tmp_file.name):
                     os.remove(tmp_file.name)
             raise
 
         if update_data and tmp_file is not None:
+            tmp_file.close()
             shutil.move(tmp_file.name, cache_file_name)
 
         if update_data:
@@ -1748,11 +1759,13 @@ def select(
             writer.finalize()  # close_stream=bool(buf_writer is None))  # We only close if we are writing in a file
         except (Exception, KeyboardInterrupt):
             if tmp_file is not None:
+                tmp_file.close()
                 if os.path.exists(tmp_file.name):
                     os.remove(tmp_file.name)
             raise
 
         if tmp_file is not None:
+            tmp_file.close()
             shutil.move(tmp_file.name, indices_cache_file_name)
 
         # Return new Dataset object
@@ -2207,7 +2220,7 @@ def _feature(values: np.ndarray) -> "tf.train.Feature":
             if isinstance(values, np.ndarray):
                 if values.dtype == np.dtype(float):
                     return _float_feature(values)
-                elif values.dtype == np.dtype(int):
+                elif values.dtype == np.int64:
                     return _int64_feature(values)
                 elif values.dtype == np.dtype(str) or (
                     values.dtype == np.dtype(object) and len(values) > 0 and isinstance(values[0], str)
@@ -2246,6 +2259,7 @@ def generator():
         logger.info(f"Writing TFRecord to {filename}")
         writer.write(tf_dataset)
         logger.info(f"Finished writing TFRecord to {filename}")
+        self = None  # delete the dataset reference used by tf_dataset
 
     def add_faiss_index(
         self,

src/datasets/arrow_reader.py

@@ -242,10 +242,10 @@ def download_from_hf_gcs(self, cache_dir, relative_data_dir):
                 the `datasets` directory on GCS.
 
         """
-        remote_cache_dir = os.path.join(HF_GCP_BASE_URL, relative_data_dir)
+        remote_cache_dir = HF_GCP_BASE_URL + "/" + relative_data_dir.replace(os.sep, "/")
         try:
             remote_dataset_info = os.path.join(remote_cache_dir, "dataset_info.json")
-            downloaded_dataset_info = cached_path(remote_dataset_info)
+            downloaded_dataset_info = cached_path(remote_dataset_info.replace(os.sep, "/"))
             shutil.move(downloaded_dataset_info, os.path.join(cache_dir, "dataset_info.json"))
             if self._info is not None:
                 self._info.update(self._info.from_directory(cache_dir))
@@ -260,7 +260,7 @@ def download_from_hf_gcs(self, cache_dir, relative_data_dir):
                 )
                 for file_instruction in file_instructions:
                     remote_prepared_filename = os.path.join(remote_cache_dir, file_instruction["filename"])
-                    downloaded_prepared_filename = cached_path(remote_prepared_filename)
+                    downloaded_prepared_filename = cached_path(remote_prepared_filename.replace(os.sep, "/"))
                     shutil.move(downloaded_prepared_filename, os.path.join(cache_dir, file_instruction["filename"]))
         except FileNotFoundError:
             raise MissingFilesOnHfGcs()

src/datasets/builder.py

@@ -173,7 +173,7 @@ def __init__(
         # prepare data dirs
         self._cache_dir_root = os.path.expanduser(cache_dir or HF_DATASETS_CACHE)
         self._cache_dir = self._build_cache_dir()
-        lock_path = os.path.join(self._cache_dir_root, self._cache_dir.replace("/", "_") + ".lock")
+        lock_path = os.path.join(self._cache_dir_root, self._cache_dir.replace(os.sep, "_") + ".lock")
         with FileLock(lock_path):
             if os.path.exists(self._cache_dir):  # check if data exist
                 if len(os.listdir(self._cache_dir)) > 0:
@@ -396,7 +396,7 @@ def download_and_prepare(
             )
 
         # Prevent parallel disk operations
-        lock_path = os.path.join(self._cache_dir_root, self._cache_dir.replace("/", "_") + ".lock")
+        lock_path = os.path.join(self._cache_dir_root, self._cache_dir.replace(os.sep, "_") + ".lock")
         with FileLock(lock_path):
             data_exists = os.path.exists(self._cache_dir)
             if data_exists and download_mode == REUSE_DATASET_IF_EXISTS:
@@ -493,13 +493,13 @@ def _download_prepared_from_hf_gcs(self):
         downloaded_info = DatasetInfo.from_directory(self._cache_dir)
         self.info.update(downloaded_info)
         # download post processing resources
-        remote_cache_dir = os.path.join(HF_GCP_BASE_URL, relative_data_dir)
+        remote_cache_dir = HF_GCP_BASE_URL + "/" + relative_data_dir.replace(os.sep, "/")
         for split in self.info.splits:
             for resource_file_name in self._post_processing_resources(split).values():
-                if "/" in resource_file_name:
+                if os.sep in resource_file_name:
                     raise ValueError("Resources shouldn't be in a sub-directory: {}".format(resource_file_name))
                 try:
-                    resource_path = utils.cached_path(os.path.join(remote_cache_dir, resource_file_name))
+                    resource_path = utils.cached_path(remote_cache_dir + "/" + resource_file_name)
                     shutil.move(resource_path, os.path.join(self._cache_dir, resource_file_name))
                 except ConnectionError:
                     logger.info(
@@ -559,7 +559,7 @@ def _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs
     def download_post_processing_resources(self, dl_manager):
         for split in self.info.splits:
             for resource_name, resource_file_name in self._post_processing_resources(split).items():
-                if "/" in resource_file_name:
+                if os.sep in resource_file_name:
                     raise ValueError("Resources shouldn't be in a sub-directory: {}".format(resource_file_name))
                 resource_path = os.path.join(self._cache_dir, resource_file_name)
                 if not os.path.exists(resource_path):
@@ -573,12 +573,12 @@ def download_post_processing_resources(self, dl_manager):
                         shutil.move(downloaded_resource_path, resource_path)
 
     def _save_info(self):
-        lock_path = os.path.join(self._cache_dir_root, self._cache_dir.replace("/", "_") + ".lock")
+        lock_path = os.path.join(self._cache_dir_root, self._cache_dir.replace(os.sep, "_") + ".lock")
         with FileLock(lock_path):
             self.info.write_to_directory(self._cache_dir)
 
     def _save_infos(self):
-        lock_path = os.path.join(self._cache_dir_root, self._cache_dir.replace("/", "_") + ".lock")
+        lock_path = os.path.join(self._cache_dir_root, self._cache_dir.replace(os.sep, "_") + ".lock")
         with FileLock(lock_path):
             DatasetInfosDict(**{self.config.name: self.info}).write_to_directory(self.get_imported_module_dir())
 
@@ -635,7 +635,7 @@ def _build_single_dataset(self, split: Union[str, Split], run_post_process: bool
         )
         if run_post_process:
             for resource_file_name in self._post_processing_resources(split).values():
-                if "/" in resource_file_name:
+                if os.sep in resource_file_name:
                     raise ValueError("Resources shouldn't be in a sub-directory: {}".format(resource_file_name))
             resources_paths = {
                 resource_name: os.path.join(self._cache_dir, resource_file_name)
@@ -831,12 +831,14 @@ def _prepare_split(self, split_generator):
 
         generator = self._generate_examples(**split_generator.gen_kwargs)
         not_verbose = bool(logger.getEffectiveLevel() > WARNING)
-        for key, record in utils.tqdm(
-            generator, unit=" examples", total=split_info.num_examples, leave=False, disable=not_verbose
-        ):
-            example = self.info.features.encode_example(record)
-            writer.write(example)
-        num_examples, num_bytes = writer.finalize()
+        try:
+            for key, record in utils.tqdm(
+                generator, unit=" examples", total=split_info.num_examples, leave=False, disable=not_verbose
+            ):
+                example = self.info.features.encode_example(record)
+                writer.write(example)
+        finally:
+            num_examples, num_bytes = writer.finalize()
 
         assert num_examples == num_examples, f"Expected to write {split_info.num_examples} but wrote {num_examples}"
         split_generator.split_info.num_examples = num_examples

src/datasets/commands/convert.py

@@ -106,7 +106,7 @@ def run(self):
                 self._logger.info("Skipping file")
                 continue
 
-            with open(input_file, "r") as f:
+            with open(input_file, "r", encoding="utf-8") as f:
                 lines = f.readlines()
 
             out_lines = []
@@ -174,7 +174,7 @@ def run(self):
             if needs_manual_update:
                 with_manual_update.append(output_file)
 
-            with open(output_file, "w") as f:
+            with open(output_file, "w", encoding="utf-8") as f:
                 f.writelines(out_lines)
             self._logger.info("Converted in %s", output_file)
 

src/datasets/commands/dummy_data.py

@@ -32,7 +32,7 @@ def __init__(
     ):
         self._path_to_dataset = path_to_dataset
         self._requires_manual = requires_manual
-        self._dataset_name = path_to_dataset.split("/")[-2]
+        self._dataset_name = path_to_dataset.replace(os.sep, "/").split("/")[-2]
 
     def run(self):
         module_path, hash = prepare_module(self._path_to_dataset)

src/datasets/commands/run_beam.py

@@ -1,5 +1,6 @@
 import os
 from argparse import ArgumentParser
+from pathlib import Path
 from shutil import copyfile
 from typing import List
 
@@ -126,7 +127,7 @@ def run(self):
         if self._save_infos:
             dataset_infos_path = os.path.join(builder_cls.get_imported_module_dir(), DATASET_INFOS_DICT_FILE_NAME)
 
-            name = list(filter(lambda x: x, path.split("/")))[-1] + ".py"
+            name = Path(path).name + ".py"
 
             combined_path = os.path.join(path, name)
             if os.path.isfile(path):

src/datasets/commands/test.py

@@ -1,5 +1,6 @@
 import os
 from argparse import ArgumentParser
+from pathlib import Path
 from shutil import copyfile
 from typing import List
 
@@ -101,7 +102,7 @@ def run(self):
         if self._save_infos:
             dataset_infos_path = os.path.join(builder_cls.get_imported_module_dir(), DATASET_INFOS_DICT_FILE_NAME)
 
-            name = list(filter(lambda x: x, path.split("/")))[-1] + ".py"
+            name = Path(path).name + ".py"
 
             combined_path = os.path.join(path, name)
             if os.path.isfile(path):

src/datasets/dataset_dict.py

@@ -476,7 +476,9 @@ def save_to_disk(self, dataset_dict_path: str):
             dataset_dict_path (``str``): path of the dataset dict directory where the dataset dict will be saved to
         """
         os.makedirs(dataset_dict_path, exist_ok=True)
-        json.dump({"splits": list(self)}, open(os.path.join(dataset_dict_path, "dataset_dict.json"), "w"))
+        json.dump(
+            {"splits": list(self)}, open(os.path.join(dataset_dict_path, "dataset_dict.json"), "w", encoding="utf-8")
+        )
         for k, dataset in self.items():
             dataset.save_to_disk(os.path.join(dataset_dict_path, k))
 
@@ -489,6 +491,8 @@ def load_from_disk(dataset_dict_path: str) -> "DatasetDict":
             dataset_dict_path (``str``): path of the dataset dict directory where the dataset dict will be loaded from
         """
         dataset_dict = DatasetDict()
-        for k in json.load(open(os.path.join(dataset_dict_path, "dataset_dict.json"), "r"))["splits"]:
+        for k in json.load(open(os.path.join(dataset_dict_path, "dataset_dict.json"), "r", encoding="utf-8"))[
+            "splits"
+        ]:
             dataset_dict[k] = Dataset.load_from_disk(os.path.join(dataset_dict_path, k))
         return dataset_dict