Add files using upload-large-folder tool

.venv/lib/python3.13/site-packages/fsspec/__init__.py

@@ -0,0 +1,71 @@
+from . import caching
+from ._version import __version__  # noqa: F401
+from .callbacks import Callback
+from .compression import available_compressions
+from .core import get_fs_token_paths, open, open_files, open_local, url_to_fs
+from .exceptions import FSTimeoutError
+from .mapping import FSMap, get_mapper
+from .registry import (
+    available_protocols,
+    filesystem,
+    get_filesystem_class,
+    register_implementation,
+    registry,
+)
+from .spec import AbstractFileSystem
+
+__all__ = [
+    "AbstractFileSystem",
+    "FSTimeoutError",
+    "FSMap",
+    "filesystem",
+    "register_implementation",
+    "get_filesystem_class",
+    "get_fs_token_paths",
+    "get_mapper",
+    "open",
+    "open_files",
+    "open_local",
+    "registry",
+    "caching",
+    "Callback",
+    "available_protocols",
+    "available_compressions",
+    "url_to_fs",
+]
+
+
+def process_entries():
+    try:
+        from importlib.metadata import entry_points
+    except ImportError:
+        return
+    if entry_points is not None:
+        try:
+            eps = entry_points()
+        except TypeError:
+            pass  # importlib-metadata < 0.8
+        else:
+            if hasattr(eps, "select"):  # Python 3.10+ / importlib_metadata >= 3.9.0
+                specs = eps.select(group="fsspec.specs")
+            else:
+                specs = eps.get("fsspec.specs", [])
+            registered_names = {}
+            for spec in specs:
+                err_msg = f"Unable to load filesystem from {spec}"
+                name = spec.name
+                if name in registered_names:
+                    continue
+                registered_names[name] = True
+                register_implementation(
+                    name,
+                    spec.value.replace(":", "."),
+                    errtxt=err_msg,
+                    # We take our implementations as the ones to overload with if
+                    # for some reason we encounter some, may be the same, already
+                    # registered
+                    clobber=True,
+                )
+
+
+process_entries()

.venv/lib/python3.13/site-packages/fsspec/_version.py

@@ -0,0 +1,21 @@
+# file generated by setuptools-scm
+# don't change, don't track in version control
+
+__all__ = ["__version__", "__version_tuple__", "version", "version_tuple"]
+
+TYPE_CHECKING = False
+if TYPE_CHECKING:
+    from typing import Tuple
+    from typing import Union
+
+    VERSION_TUPLE = Tuple[Union[int, str], ...]
+else:
+    VERSION_TUPLE = object
+
+version: str
+__version__: str
+__version_tuple__: VERSION_TUPLE
+version_tuple: VERSION_TUPLE
+
+__version__ = version = '2025.7.0'
+__version_tuple__ = version_tuple = (2025, 7, 0)

.venv/lib/python3.13/site-packages/fsspec/archive.py

@@ -0,0 +1,75 @@
+import operator
+
+from fsspec import AbstractFileSystem
+from fsspec.utils import tokenize
+
+
+class AbstractArchiveFileSystem(AbstractFileSystem):
+    """
+    A generic superclass for implementing Archive-based filesystems.
+
+    Currently, it is shared amongst
+    :class:`~fsspec.implementations.zip.ZipFileSystem`,
+    :class:`~fsspec.implementations.libarchive.LibArchiveFileSystem` and
+    :class:`~fsspec.implementations.tar.TarFileSystem`.
+    """
+
+    def __str__(self):
+        return f"<Archive-like object {type(self).__name__} at {id(self)}>"
+
+    __repr__ = __str__
+
+    def ukey(self, path):
+        return tokenize(path, self.fo, self.protocol)
+
+    def _all_dirnames(self, paths):
+        """Returns *all* directory names for each path in paths, including intermediate
+        ones.
+
+        Parameters
+        ----------
+        paths: Iterable of path strings
+        """
+        if len(paths) == 0:
+            return set()
+
+        dirnames = {self._parent(path) for path in paths} - {self.root_marker}
+        return dirnames | self._all_dirnames(dirnames)
+
+    def info(self, path, **kwargs):
+        self._get_dirs()
+        path = self._strip_protocol(path)
+        if path in {"", "/"} and self.dir_cache:
+            return {"name": "", "type": "directory", "size": 0}
+        if path in self.dir_cache:
+            return self.dir_cache[path]
+        elif path + "/" in self.dir_cache:
+            return self.dir_cache[path + "/"]
+        else:
+            raise FileNotFoundError(path)
+
+    def ls(self, path, detail=True, **kwargs):
+        self._get_dirs()
+        paths = {}
+        for p, f in self.dir_cache.items():
+            p = p.rstrip("/")
+            if "/" in p:
+                root = p.rsplit("/", 1)[0]
+            else:
+                root = ""
+            if root == path.rstrip("/"):
+                paths[p] = f
+            elif all(
+                (a == b)
+                for a, b in zip(path.split("/"), [""] + p.strip("/").split("/"))
+            ):
+                # root directory entry
+                ppath = p.rstrip("/").split("/", 1)[0]
+                if ppath not in paths:
+                    out = {"name": ppath, "size": 0, "type": "directory"}
+                    paths[ppath] = out
+        if detail:
+            out = sorted(paths.values(), key=operator.itemgetter("name"))
+            return out
+        else:
+            return sorted(paths)

.venv/lib/python3.13/site-packages/fsspec/asyn.py

@@ -0,0 +1,1097 @@
+import asyncio
+import asyncio.events
+import functools
+import inspect
+import io
+import numbers
+import os
+import re
+import threading
+from collections.abc import Iterable
+from glob import has_magic
+from typing import TYPE_CHECKING
+
+from .callbacks import DEFAULT_CALLBACK
+from .exceptions import FSTimeoutError
+from .implementations.local import LocalFileSystem, make_path_posix, trailing_sep
+from .spec import AbstractBufferedFile, AbstractFileSystem
+from .utils import glob_translate, is_exception, other_paths
+
+private = re.compile("_[^_]")
+iothread = [None]  # dedicated fsspec IO thread
+loop = [None]  # global event loop for any non-async instance
+_lock = None  # global lock placeholder
+get_running_loop = asyncio.get_running_loop
+
+
+def get_lock():
+    """Allocate or return a threading lock.
+
+    The lock is allocated on first use to allow setting one lock per forked process.
+    """
+    global _lock
+    if not _lock:
+        _lock = threading.Lock()
+    return _lock
+
+
+def reset_lock():
+    """Reset the global lock.
+
+    This should be called only on the init of a forked process to reset the lock to
+    None, enabling the new forked process to get a new lock.
+    """
+    global _lock
+
+    iothread[0] = None
+    loop[0] = None
+    _lock = None
+
+
+async def _runner(event, coro, result, timeout=None):
+    timeout = timeout if timeout else None  # convert 0 or 0.0 to None
+    if timeout is not None:
+        coro = asyncio.wait_for(coro, timeout=timeout)
+    try:
+        result[0] = await coro
+    except Exception as ex:
+        result[0] = ex
+    finally:
+        event.set()
+
+
+def sync(loop, func, *args, timeout=None, **kwargs):
+    """
+    Make loop run coroutine until it returns. Runs in other thread
+
+    Examples
+    --------
+    >>> fsspec.asyn.sync(fsspec.asyn.get_loop(), func, *args,
+                         timeout=timeout, **kwargs)
+    """
+    timeout = timeout if timeout else None  # convert 0 or 0.0 to None
+    # NB: if the loop is not running *yet*, it is OK to submit work
+    # and we will wait for it
+    if loop is None or loop.is_closed():
+        raise RuntimeError("Loop is not running")
+    try:
+        loop0 = asyncio.events.get_running_loop()
+        if loop0 is loop:
+            raise NotImplementedError("Calling sync() from within a running loop")
+    except NotImplementedError:
+        raise
+    except RuntimeError:
+        pass
+    coro = func(*args, **kwargs)
+    result = [None]
+    event = threading.Event()
+    asyncio.run_coroutine_threadsafe(_runner(event, coro, result, timeout), loop)
+    while True:
+        # this loops allows thread to get interrupted
+        if event.wait(1):
+            break
+        if timeout is not None:
+            timeout -= 1
+            if timeout < 0:
+                raise FSTimeoutError
+
+    return_result = result[0]
+    if isinstance(return_result, asyncio.TimeoutError):
+        # suppress asyncio.TimeoutError, raise FSTimeoutError
+        raise FSTimeoutError from return_result
+    elif isinstance(return_result, BaseException):
+        raise return_result
+    else:
+        return return_result
+
+
+def sync_wrapper(func, obj=None):
+    """Given a function, make so can be called in blocking contexts
+
+    Leave obj=None if defining within a class. Pass the instance if attaching
+    as an attribute of the instance.
+    """
+
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        self = obj or args[0]
+        return sync(self.loop, func, *args, **kwargs)
+
+    return wrapper
+
+
+def get_loop():
+    """Create or return the default fsspec IO loop
+
+    The loop will be running on a separate thread.
+    """
+    if loop[0] is None:
+        with get_lock():
+            # repeat the check just in case the loop got filled between the
+            # previous two calls from another thread
+            if loop[0] is None:
+                loop[0] = asyncio.new_event_loop()
+                th = threading.Thread(target=loop[0].run_forever, name="fsspecIO")
+                th.daemon = True
+                th.start()
+                iothread[0] = th
+    return loop[0]
+
+
+def reset_after_fork():
+    global lock
+    loop[0] = None
+    iothread[0] = None
+    lock = None
+
+
+if hasattr(os, "register_at_fork"):
+    # should be posix; this will do nothing for spawn or forkserver subprocesses
+    os.register_at_fork(after_in_child=reset_after_fork)
+
+
+if TYPE_CHECKING:
+    import resource
+
+    ResourceError = resource.error
+else:
+    try:
+        import resource
+    except ImportError:
+        resource = None
+        ResourceError = OSError
+    else:
+        ResourceError = getattr(resource, "error", OSError)
+
+_DEFAULT_BATCH_SIZE = 128
+_NOFILES_DEFAULT_BATCH_SIZE = 1280
+
+
+def _get_batch_size(nofiles=False):
+    from fsspec.config import conf
+
+    if nofiles:
+        if "nofiles_gather_batch_size" in conf:
+            return conf["nofiles_gather_batch_size"]
+    else:
+        if "gather_batch_size" in conf:
+            return conf["gather_batch_size"]
+    if nofiles:
+        return _NOFILES_DEFAULT_BATCH_SIZE
+    if resource is None:
+        return _DEFAULT_BATCH_SIZE
+
+    try:
+        soft_limit, _ = resource.getrlimit(resource.RLIMIT_NOFILE)
+    except (ImportError, ValueError, ResourceError):
+        return _DEFAULT_BATCH_SIZE
+
+    if soft_limit == resource.RLIM_INFINITY:
+        return -1
+    else:
+        return soft_limit // 8
+
+
+def running_async() -> bool:
+    """Being executed by an event loop?"""
+    try:
+        asyncio.get_running_loop()
+        return True
+    except RuntimeError:
+        return False
+
+
+async def _run_coros_in_chunks(
+    coros,
+    batch_size=None,
+    callback=DEFAULT_CALLBACK,
+    timeout=None,
+    return_exceptions=False,
+    nofiles=False,
+):
+    """Run the given coroutines in  chunks.
+
+    Parameters
+    ----------
+    coros: list of coroutines to run
+    batch_size: int or None
+        Number of coroutines to submit/wait on simultaneously.
+        If -1, then it will not be any throttling. If
+        None, it will be inferred from _get_batch_size()
+    callback: fsspec.callbacks.Callback instance
+        Gets a relative_update when each coroutine completes
+    timeout: number or None
+        If given, each coroutine times out after this time. Note that, since
+        there are multiple batches, the total run time of this function will in
+        general be longer
+    return_exceptions: bool
+        Same meaning as in asyncio.gather
+    nofiles: bool
+        If inferring the batch_size, does this operation involve local files?
+        If yes, you normally expect smaller batches.
+    """
+
+    if batch_size is None:
+        batch_size = _get_batch_size(nofiles=nofiles)
+
+    if batch_size == -1:
+        batch_size = len(coros)
+
+    assert batch_size > 0
+
+    async def _run_coro(coro, i):
+        try:
+            return await asyncio.wait_for(coro, timeout=timeout), i
+        except Exception as e:
+            if not return_exceptions:
+                raise
+            return e, i
+        finally:
+            callback.relative_update(1)
+
+    i = 0
+    n = len(coros)
+    results = [None] * n
+    pending = set()
+
+    while pending or i < n:
+        while len(pending) < batch_size and i < n:
+            pending.add(asyncio.ensure_future(_run_coro(coros[i], i)))
+            i += 1
+
+        if not pending:
+            break
+
+        done, pending = await asyncio.wait(pending, return_when=asyncio.FIRST_COMPLETED)
+        while done:
+            result, k = await done.pop()
+            results[k] = result
+
+    return results
+
+
+# these methods should be implemented as async by any async-able backend
+async_methods = [
+    "_ls",
+    "_cat_file",
+    "_get_file",
+    "_put_file",
+    "_rm_file",
+    "_cp_file",
+    "_pipe_file",
+    "_expand_path",
+    "_info",
+    "_isfile",
+    "_isdir",
+    "_exists",
+    "_walk",
+    "_glob",
+    "_find",
+    "_du",
+    "_size",
+    "_mkdir",
+    "_makedirs",
+]
+
+
+class AsyncFileSystem(AbstractFileSystem):
+    """Async file operations, default implementations
+
+    Passes bulk operations to asyncio.gather for concurrent operation.
+
+    Implementations that have concurrent batch operations and/or async methods
+    should inherit from this class instead of AbstractFileSystem. Docstrings are
+    copied from the un-underscored method in AbstractFileSystem, if not given.
+    """
+
+    # note that methods do not have docstring here; they will be copied
+    # for _* methods and inferred for overridden methods.
+
+    async_impl = True
+    mirror_sync_methods = True
+    disable_throttling = False
+
+    def __init__(self, *args, asynchronous=False, loop=None, batch_size=None, **kwargs):
+        self.asynchronous = asynchronous
+        self._pid = os.getpid()
+        if not asynchronous:
+            self._loop = loop or get_loop()
+        else:
+            self._loop = None
+        self.batch_size = batch_size
+        super().__init__(*args, **kwargs)
+
+    @property
+    def loop(self):
+        if self._pid != os.getpid():
+            raise RuntimeError("This class is not fork-safe")
+        return self._loop
+
+    async def _rm_file(self, path, **kwargs):
+        raise NotImplementedError
+
+    async def _rm(self, path, recursive=False, batch_size=None, **kwargs):
+        # TODO: implement on_error
+        batch_size = batch_size or self.batch_size
+        path = await self._expand_path(path, recursive=recursive)
+        return await _run_coros_in_chunks(
+            [self._rm_file(p, **kwargs) for p in reversed(path)],
+            batch_size=batch_size,
+            nofiles=True,
+        )
+
+    async def _cp_file(self, path1, path2, **kwargs):
+        raise NotImplementedError
+
+    async def _mv_file(self, path1, path2):
+        await self._cp_file(path1, path2)
+        await self._rm_file(path1)
+
+    async def _copy(
+        self,
+        path1,
+        path2,
+        recursive=False,
+        on_error=None,
+        maxdepth=None,
+        batch_size=None,
+        **kwargs,
+    ):
+        if on_error is None and recursive:
+            on_error = "ignore"
+        elif on_error is None:
+            on_error = "raise"
+
+        if isinstance(path1, list) and isinstance(path2, list):
+            # No need to expand paths when both source and destination
+            # are provided as lists
+            paths1 = path1
+            paths2 = path2
+        else:
+            source_is_str = isinstance(path1, str)
+            paths1 = await self._expand_path(
+                path1, maxdepth=maxdepth, recursive=recursive
+            )
+            if source_is_str and (not recursive or maxdepth is not None):
+                # Non-recursive glob does not copy directories
+                paths1 = [
+                    p for p in paths1 if not (trailing_sep(p) or await self._isdir(p))
+                ]
+                if not paths1:
+                    return
+
+            source_is_file = len(paths1) == 1
+            dest_is_dir = isinstance(path2, str) and (
+                trailing_sep(path2) or await self._isdir(path2)
+            )
+
+            exists = source_is_str and (
+                (has_magic(path1) and source_is_file)
+                or (not has_magic(path1) and dest_is_dir and not trailing_sep(path1))
+            )
+            paths2 = other_paths(
+                paths1,
+                path2,
+                exists=exists,
+                flatten=not source_is_str,
+            )
+
+        batch_size = batch_size or self.batch_size
+        coros = [self._cp_file(p1, p2, **kwargs) for p1, p2 in zip(paths1, paths2)]
+        result = await _run_coros_in_chunks(
+            coros, batch_size=batch_size, return_exceptions=True, nofiles=True
+        )
+
+        for ex in filter(is_exception, result):
+            if on_error == "ignore" and isinstance(ex, FileNotFoundError):
+                continue
+            raise ex
+
+    async def _pipe_file(self, path, value, mode="overwrite", **kwargs):
+        raise NotImplementedError
+
+    async def _pipe(self, path, value=None, batch_size=None, **kwargs):
+        if isinstance(path, str):
+            path = {path: value}
+        batch_size = batch_size or self.batch_size
+        return await _run_coros_in_chunks(
+            [self._pipe_file(k, v, **kwargs) for k, v in path.items()],
+            batch_size=batch_size,
+            nofiles=True,
+        )
+
+    async def _process_limits(self, url, start, end):
+        """Helper for "Range"-based _cat_file"""
+        size = None
+        suff = False
+        if start is not None and start < 0:
+            # if start is negative and end None, end is the "suffix length"
+            if end is None:
+                end = -start
+                start = ""
+                suff = True
+            else:
+                size = size or (await self._info(url))["size"]
+                start = size + start
+        elif start is None:
+            start = 0
+        if not suff:
+            if end is not None and end < 0:
+                if start is not None:
+                    size = size or (await self._info(url))["size"]
+                    end = size + end
+            elif end is None:
+                end = ""
+            if isinstance(end, numbers.Integral):
+                end -= 1  # bytes range is inclusive
+        return f"bytes={start}-{end}"
+
+    async def _cat_file(self, path, start=None, end=None, **kwargs):
+        raise NotImplementedError
+
+    async def _cat(
+        self, path, recursive=False, on_error="raise", batch_size=None, **kwargs
+    ):
+        paths = await self._expand_path(path, recursive=recursive)
+        coros = [self._cat_file(path, **kwargs) for path in paths]
+        batch_size = batch_size or self.batch_size
+        out = await _run_coros_in_chunks(
+            coros, batch_size=batch_size, nofiles=True, return_exceptions=True
+        )
+        if on_error == "raise":
+            ex = next(filter(is_exception, out), False)
+            if ex:
+                raise ex
+        if (
+            len(paths) > 1
+            or isinstance(path, list)
+            or paths[0] != self._strip_protocol(path)
+        ):
+            return {
+                k: v
+                for k, v in zip(paths, out)
+                if on_error != "omit" or not is_exception(v)
+            }
+        else:
+            return out[0]
+
+    async def _cat_ranges(
+        self,
+        paths,
+        starts,
+        ends,
+        max_gap=None,
+        batch_size=None,
+        on_error="return",
+        **kwargs,
+    ):
+        """Get the contents of byte ranges from one or more files
+
+        Parameters
+        ----------
+        paths: list
+            A list of of filepaths on this filesystems
+        starts, ends: int or list
+            Bytes limits of the read. If using a single int, the same value will be
+            used to read all the specified files.
+        """
+        # TODO: on_error
+        if max_gap is not None:
+            # use utils.merge_offset_ranges
+            raise NotImplementedError
+        if not isinstance(paths, list):
+            raise TypeError
+        if not isinstance(starts, Iterable):
+            starts = [starts] * len(paths)
+        if not isinstance(ends, Iterable):
+            ends = [ends] * len(paths)
+        if len(starts) != len(paths) or len(ends) != len(paths):
+            raise ValueError
+        coros = [
+            self._cat_file(p, start=s, end=e, **kwargs)
+            for p, s, e in zip(paths, starts, ends)
+        ]
+        batch_size = batch_size or self.batch_size
+        return await _run_coros_in_chunks(
+            coros, batch_size=batch_size, nofiles=True, return_exceptions=True
+        )
+
+    async def _put_file(self, lpath, rpath, mode="overwrite", **kwargs):
+        raise NotImplementedError
+
+    async def _put(
+        self,
+        lpath,
+        rpath,
+        recursive=False,
+        callback=DEFAULT_CALLBACK,
+        batch_size=None,
+        maxdepth=None,
+        **kwargs,
+    ):
+        """Copy file(s) from local.
+
+        Copies a specific file or tree of files (if recursive=True). If rpath
+        ends with a "/", it will be assumed to be a directory, and target files
+        will go within.
+
+        The put_file method will be called concurrently on a batch of files. The
+        batch_size option can configure the amount of futures that can be executed
+        at the same time. If it is -1, then all the files will be uploaded concurrently.
+        The default can be set for this instance by passing "batch_size" in the
+        constructor, or for all instances by setting the "gather_batch_size" key
+        in ``fsspec.config.conf``, falling back to 1/8th of the system limit .
+        """
+        if isinstance(lpath, list) and isinstance(rpath, list):
+            # No need to expand paths when both source and destination
+            # are provided as lists
+            rpaths = rpath
+            lpaths = lpath
+        else:
+            source_is_str = isinstance(lpath, str)
+            if source_is_str:
+                lpath = make_path_posix(lpath)
+            fs = LocalFileSystem()
+            lpaths = fs.expand_path(lpath, recursive=recursive, maxdepth=maxdepth)
+            if source_is_str and (not recursive or maxdepth is not None):
+                # Non-recursive glob does not copy directories
+                lpaths = [p for p in lpaths if not (trailing_sep(p) or fs.isdir(p))]
+                if not lpaths:
+                    return
+
+            source_is_file = len(lpaths) == 1
+            dest_is_dir = isinstance(rpath, str) and (
+                trailing_sep(rpath) or await self._isdir(rpath)
+            )
+
+            rpath = self._strip_protocol(rpath)
+            exists = source_is_str and (
+                (has_magic(lpath) and source_is_file)
+                or (not has_magic(lpath) and dest_is_dir and not trailing_sep(lpath))
+            )
+            rpaths = other_paths(
+                lpaths,
+                rpath,
+                exists=exists,
+                flatten=not source_is_str,
+            )
+
+        is_dir = {l: os.path.isdir(l) for l in lpaths}
+        rdirs = [r for l, r in zip(lpaths, rpaths) if is_dir[l]]
+        file_pairs = [(l, r) for l, r in zip(lpaths, rpaths) if not is_dir[l]]
+
+        await asyncio.gather(*[self._makedirs(d, exist_ok=True) for d in rdirs])
+        batch_size = batch_size or self.batch_size
+
+        coros = []
+        callback.set_size(len(file_pairs))
+        for lfile, rfile in file_pairs:
+            put_file = callback.branch_coro(self._put_file)
+            coros.append(put_file(lfile, rfile, **kwargs))
+
+        return await _run_coros_in_chunks(
+            coros, batch_size=batch_size, callback=callback
+        )
+
+    async def _get_file(self, rpath, lpath, **kwargs):
+        raise NotImplementedError
+
+    async def _get(
+        self,
+        rpath,
+        lpath,
+        recursive=False,
+        callback=DEFAULT_CALLBACK,
+        maxdepth=None,
+        **kwargs,
+    ):
+        """Copy file(s) to local.
+
+        Copies a specific file or tree of files (if recursive=True). If lpath
+        ends with a "/", it will be assumed to be a directory, and target files
+        will go within. Can submit a list of paths, which may be glob-patterns
+        and will be expanded.
+
+        The get_file method will be called concurrently on a batch of files. The
+        batch_size option can configure the amount of futures that can be executed
+        at the same time. If it is -1, then all the files will be uploaded concurrently.
+        The default can be set for this instance by passing "batch_size" in the
+        constructor, or for all instances by setting the "gather_batch_size" key
+        in ``fsspec.config.conf``, falling back to 1/8th of the system limit .
+        """
+        if isinstance(lpath, list) and isinstance(rpath, list):
+            # No need to expand paths when both source and destination
+            # are provided as lists
+            rpaths = rpath
+            lpaths = lpath
+        else:
+            source_is_str = isinstance(rpath, str)
+            # First check for rpath trailing slash as _strip_protocol removes it.
+            source_not_trailing_sep = source_is_str and not trailing_sep(rpath)
+            rpath = self._strip_protocol(rpath)
+            rpaths = await self._expand_path(
+                rpath, recursive=recursive, maxdepth=maxdepth
+            )
+            if source_is_str and (not recursive or maxdepth is not None):
+                # Non-recursive glob does not copy directories
+                rpaths = [
+                    p for p in rpaths if not (trailing_sep(p) or await self._isdir(p))
+                ]
+                if not rpaths:
+                    return
+
+            lpath = make_path_posix(lpath)
+            source_is_file = len(rpaths) == 1
+            dest_is_dir = isinstance(lpath, str) and (
+                trailing_sep(lpath) or LocalFileSystem().isdir(lpath)
+            )
+
+            exists = source_is_str and (
+                (has_magic(rpath) and source_is_file)
+                or (not has_magic(rpath) and dest_is_dir and source_not_trailing_sep)
+            )
+            lpaths = other_paths(
+                rpaths,
+                lpath,
+                exists=exists,
+                flatten=not source_is_str,
+            )
+
+        [os.makedirs(os.path.dirname(lp), exist_ok=True) for lp in lpaths]
+        batch_size = kwargs.pop("batch_size", self.batch_size)
+
+        coros = []
+        callback.set_size(len(lpaths))
+        for lpath, rpath in zip(lpaths, rpaths):
+            get_file = callback.branch_coro(self._get_file)
+            coros.append(get_file(rpath, lpath, **kwargs))
+        return await _run_coros_in_chunks(
+            coros, batch_size=batch_size, callback=callback
+        )
+
+    async def _isfile(self, path):
+        try:
+            return (await self._info(path))["type"] == "file"
+        except:  # noqa: E722
+            return False
+
+    async def _isdir(self, path):
+        try:
+            return (await self._info(path))["type"] == "directory"
+        except OSError:
+            return False
+
+    async def _size(self, path):
+        return (await self._info(path)).get("size", None)
+
+    async def _sizes(self, paths, batch_size=None):
+        batch_size = batch_size or self.batch_size
+        return await _run_coros_in_chunks(
+            [self._size(p) for p in paths], batch_size=batch_size
+        )
+
+    async def _exists(self, path, **kwargs):
+        try:
+            await self._info(path, **kwargs)
+            return True
+        except FileNotFoundError:
+            return False
+
+    async def _info(self, path, **kwargs):
+        raise NotImplementedError
+
+    async def _ls(self, path, detail=True, **kwargs):
+        raise NotImplementedError
+
+    async def _walk(self, path, maxdepth=None, on_error="omit", **kwargs):
+        if maxdepth is not None and maxdepth < 1:
+            raise ValueError("maxdepth must be at least 1")
+
+        path = self._strip_protocol(path)
+        full_dirs = {}
+        dirs = {}
+        files = {}
+
+        detail = kwargs.pop("detail", False)
+        try:
+            listing = await self._ls(path, detail=True, **kwargs)
+        except (FileNotFoundError, OSError) as e:
+            if on_error == "raise":
+                raise
+            elif callable(on_error):
+                on_error(e)
+            if detail:
+                yield path, {}, {}
+            else:
+                yield path, [], []
+            return
+
+        for info in listing:
+            # each info name must be at least [path]/part , but here
+            # we check also for names like [path]/part/
+            pathname = info["name"].rstrip("/")
+            name = pathname.rsplit("/", 1)[-1]
+            if info["type"] == "directory" and pathname != path:
+                # do not include "self" path
+                full_dirs[name] = pathname
+                dirs[name] = info
+            elif pathname == path:
+                # file-like with same name as give path
+                files[""] = info
+            else:
+                files[name] = info
+
+        if detail:
+            yield path, dirs, files
+        else:
+            yield path, list(dirs), list(files)
+
+        if maxdepth is not None:
+            maxdepth -= 1
+            if maxdepth < 1:
+                return
+
+        for d in dirs:
+            async for _ in self._walk(
+                full_dirs[d], maxdepth=maxdepth, detail=detail, **kwargs
+            ):
+                yield _
+
+    async def _glob(self, path, maxdepth=None, **kwargs):
+        if maxdepth is not None and maxdepth < 1:
+            raise ValueError("maxdepth must be at least 1")
+
+        import re
+
+        seps = (os.path.sep, os.path.altsep) if os.path.altsep else (os.path.sep,)
+        ends_with_sep = path.endswith(seps)  # _strip_protocol strips trailing slash
+        path = self._strip_protocol(path)
+        append_slash_to_dirname = ends_with_sep or path.endswith(
+            tuple(sep + "**" for sep in seps)
+        )
+        idx_star = path.find("*") if path.find("*") >= 0 else len(path)
+        idx_qmark = path.find("?") if path.find("?") >= 0 else len(path)
+        idx_brace = path.find("[") if path.find("[") >= 0 else len(path)
+
+        min_idx = min(idx_star, idx_qmark, idx_brace)
+
+        detail = kwargs.pop("detail", False)
+
+        if not has_magic(path):
+            if await self._exists(path, **kwargs):
+                if not detail:
+                    return [path]
+                else:
+                    return {path: await self._info(path, **kwargs)}
+            else:
+                if not detail:
+                    return []  # glob of non-existent returns empty
+                else:
+                    return {}
+        elif "/" in path[:min_idx]:
+            min_idx = path[:min_idx].rindex("/")
+            root = path[: min_idx + 1]
+            depth = path[min_idx + 1 :].count("/") + 1
+        else:
+            root = ""
+            depth = path[min_idx + 1 :].count("/") + 1
+
+        if "**" in path:
+            if maxdepth is not None:
+                idx_double_stars = path.find("**")
+                depth_double_stars = path[idx_double_stars:].count("/") + 1
+                depth = depth - depth_double_stars + maxdepth
+            else:
+                depth = None
+
+        allpaths = await self._find(
+            root, maxdepth=depth, withdirs=True, detail=True, **kwargs
+        )
+
+        pattern = glob_translate(path + ("/" if ends_with_sep else ""))
+        pattern = re.compile(pattern)
+
+        out = {
+            p: info
+            for p, info in sorted(allpaths.items())
+            if pattern.match(
+                p + "/"
+                if append_slash_to_dirname and info["type"] == "directory"
+                else p
+            )
+        }
+
+        if detail:
+            return out
+        else:
+            return list(out)
+
+    async def _du(self, path, total=True, maxdepth=None, **kwargs):
+        sizes = {}
+        # async for?
+        for f in await self._find(path, maxdepth=maxdepth, **kwargs):
+            info = await self._info(f)
+            sizes[info["name"]] = info["size"]
+        if total:
+            return sum(sizes.values())
+        else:
+            return sizes
+
+    async def _find(self, path, maxdepth=None, withdirs=False, **kwargs):
+        path = self._strip_protocol(path)
+        out = {}
+        detail = kwargs.pop("detail", False)
+
+        # Add the root directory if withdirs is requested
+        # This is needed for posix glob compliance
+        if withdirs and path != "" and await self._isdir(path):
+            out[path] = await self._info(path)
+
+        # async for?
+        async for _, dirs, files in self._walk(path, maxdepth, detail=True, **kwargs):
+            if withdirs:
+                files.update(dirs)
+            out.update({info["name"]: info for name, info in files.items()})
+        if not out and (await self._isfile(path)):
+            # walk works on directories, but find should also return [path]
+            # when path happens to be a file
+            out[path] = {}
+        names = sorted(out)
+        if not detail:
+            return names
+        else:
+            return {name: out[name] for name in names}
+
+    async def _expand_path(self, path, recursive=False, maxdepth=None):
+        if maxdepth is not None and maxdepth < 1:
+            raise ValueError("maxdepth must be at least 1")
+
+        if isinstance(path, str):
+            out = await self._expand_path([path], recursive, maxdepth)
+        else:
+            out = set()
+            path = [self._strip_protocol(p) for p in path]
+            for p in path:  # can gather here
+                if has_magic(p):
+                    bit = set(await self._glob(p, maxdepth=maxdepth))
+                    out |= bit
+                    if recursive:
+                        # glob call above expanded one depth so if maxdepth is defined
+                        # then decrement it in expand_path call below. If it is zero
+                        # after decrementing then avoid expand_path call.
+                        if maxdepth is not None and maxdepth <= 1:
+                            continue
+                        out |= set(
+                            await self._expand_path(
+                                list(bit),
+                                recursive=recursive,
+                                maxdepth=maxdepth - 1 if maxdepth is not None else None,
+                            )
+                        )
+                    continue
+                elif recursive:
+                    rec = set(await self._find(p, maxdepth=maxdepth, withdirs=True))
+                    out |= rec
+                if p not in out and (recursive is False or (await self._exists(p))):
+                    # should only check once, for the root
+                    out.add(p)
+        if not out:
+            raise FileNotFoundError(path)
+        return sorted(out)
+
+    async def _mkdir(self, path, create_parents=True, **kwargs):
+        pass  # not necessary to implement, may not have directories
+
+    async def _makedirs(self, path, exist_ok=False):
+        pass  # not necessary to implement, may not have directories
+
+    async def open_async(self, path, mode="rb", **kwargs):
+        if "b" not in mode or kwargs.get("compression"):
+            raise ValueError
+        raise NotImplementedError
+
+
+def mirror_sync_methods(obj):
+    """Populate sync and async methods for obj
+
+    For each method will create a sync version if the name refers to an async method
+    (coroutine) and there is no override in the child class; will create an async
+    method for the corresponding sync method if there is no implementation.
+
+    Uses the methods specified in
+    - async_methods: the set that an implementation is expected to provide
+    - default_async_methods: that can be derived from their sync version in
+      AbstractFileSystem
+    - AsyncFileSystem: async-specific default coroutines
+    """
+    from fsspec import AbstractFileSystem
+
+    for method in async_methods + dir(AsyncFileSystem):
+        if not method.startswith("_"):
+            continue
+        smethod = method[1:]
+        if private.match(method):
+            isco = inspect.iscoroutinefunction(getattr(obj, method, None))
+            unsync = getattr(getattr(obj, smethod, False), "__func__", None)
+            is_default = unsync is getattr(AbstractFileSystem, smethod, "")
+            if isco and is_default:
+                mth = sync_wrapper(getattr(obj, method), obj=obj)
+                setattr(obj, smethod, mth)
+                if not mth.__doc__:
+                    mth.__doc__ = getattr(
+                        getattr(AbstractFileSystem, smethod, None), "__doc__", ""
+                    )
+
+
+class FSSpecCoroutineCancel(Exception):
+    pass
+
+
+def _dump_running_tasks(
+    printout=True, cancel=True, exc=FSSpecCoroutineCancel, with_task=False
+):
+    import traceback
+
+    tasks = [t for t in asyncio.tasks.all_tasks(loop[0]) if not t.done()]
+    if printout:
+        [task.print_stack() for task in tasks]
+    out = [
+        {
+            "locals": task._coro.cr_frame.f_locals,
+            "file": task._coro.cr_frame.f_code.co_filename,
+            "firstline": task._coro.cr_frame.f_code.co_firstlineno,
+            "linelo": task._coro.cr_frame.f_lineno,
+            "stack": traceback.format_stack(task._coro.cr_frame),
+            "task": task if with_task else None,
+        }
+        for task in tasks
+    ]
+    if cancel:
+        for t in tasks:
+            cbs = t._callbacks
+            t.cancel()
+            asyncio.futures.Future.set_exception(t, exc)
+            asyncio.futures.Future.cancel(t)
+            [cb[0](t) for cb in cbs]  # cancels any dependent concurrent.futures
+            try:
+                t._coro.throw(exc)  # exits coro, unless explicitly handled
+            except exc:
+                pass
+    return out
+
+
+class AbstractAsyncStreamedFile(AbstractBufferedFile):
+    # no read buffering, and always auto-commit
+    # TODO: readahead might still be useful here, but needs async version
+
+    async def read(self, length=-1):
+        """
+        Return data from cache, or fetch pieces as necessary
+
+        Parameters
+        ----------
+        length: int (-1)
+            Number of bytes to read; if <0, all remaining bytes.
+        """
+        length = -1 if length is None else int(length)
+        if self.mode != "rb":
+            raise ValueError("File not in read mode")
+        if length < 0:
+            length = self.size - self.loc
+        if self.closed:
+            raise ValueError("I/O operation on closed file.")
+        if length == 0:
+            # don't even bother calling fetch
+            return b""
+        out = await self._fetch_range(self.loc, self.loc + length)
+        self.loc += len(out)
+        return out
+
+    async def write(self, data):
+        """
+        Write data to buffer.
+
+        Buffer only sent on flush() or if buffer is greater than
+        or equal to blocksize.
+
+        Parameters
+        ----------
+        data: bytes
+            Set of bytes to be written.
+        """
+        if self.mode not in {"wb", "ab"}:
+            raise ValueError("File not in write mode")
+        if self.closed:
+            raise ValueError("I/O operation on closed file.")
+        if self.forced:
+            raise ValueError("This file has been force-flushed, can only close")
+        out = self.buffer.write(data)
+        self.loc += out
+        if self.buffer.tell() >= self.blocksize:
+            await self.flush()
+        return out
+
+    async def close(self):
+        """Close file
+
+        Finalizes writes, discards cache
+        """
+        if getattr(self, "_unclosable", False):
+            return
+        if self.closed:
+            return
+        if self.mode == "rb":
+            self.cache = None
+        else:
+            if not self.forced:
+                await self.flush(force=True)
+
+            if self.fs is not None:
+                self.fs.invalidate_cache(self.path)
+                self.fs.invalidate_cache(self.fs._parent(self.path))
+
+        self.closed = True
+
+    async def flush(self, force=False):
+        if self.closed:
+            raise ValueError("Flush on closed file")
+        if force and self.forced:
+            raise ValueError("Force flush cannot be called more than once")
+        if force:
+            self.forced = True
+
+        if self.mode not in {"wb", "ab"}:
+            # no-op to flush on read-mode
+            return
+
+        if not force and self.buffer.tell() < self.blocksize:
+            # Defer write on small block
+            return
+
+        if self.offset is None:
+            # Initialize a multipart upload
+            self.offset = 0
+            try:
+                await self._initiate_upload()
+            except:
+                self.closed = True
+                raise
+
+        if await self._upload_chunk(final=force) is not False:
+            self.offset += self.buffer.seek(0, 2)
+            self.buffer = io.BytesIO()
+
+    async def __aenter__(self):
+        return self
+
+    async def __aexit__(self, exc_type, exc_val, exc_tb):
+        await self.close()
+
+    async def _fetch_range(self, start, end):
+        raise NotImplementedError
+
+    async def _initiate_upload(self):
+        pass
+
+    async def _upload_chunk(self, final=False):
+        raise NotImplementedError

.venv/lib/python3.13/site-packages/fsspec/callbacks.py

@@ -0,0 +1,324 @@
+from functools import wraps
+
+
+class Callback:
+    """
+    Base class and interface for callback mechanism
+
+    This class can be used directly for monitoring file transfers by
+    providing ``callback=Callback(hooks=...)`` (see the ``hooks`` argument,
+    below), or subclassed for more specialised behaviour.
+
+    Parameters
+    ----------
+    size: int (optional)
+        Nominal quantity for the value that corresponds to a complete
+        transfer, e.g., total number of tiles or total number of
+        bytes
+    value: int (0)
+        Starting internal counter value
+    hooks: dict or None
+        A dict of named functions to be called on each update. The signature
+        of these must be ``f(size, value, **kwargs)``
+    """
+
+    def __init__(self, size=None, value=0, hooks=None, **kwargs):
+        self.size = size
+        self.value = value
+        self.hooks = hooks or {}
+        self.kw = kwargs
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, *exc_args):
+        self.close()
+
+    def close(self):
+        """Close callback."""
+
+    def branched(self, path_1, path_2, **kwargs):
+        """
+        Return callback for child transfers
+
+        If this callback is operating at a higher level, e.g., put, which may
+        trigger transfers that can also be monitored. The function returns a callback
+        that has to be passed to the child method, e.g., put_file,
+        as `callback=` argument.
+
+        The implementation uses `callback.branch` for compatibility.
+        When implementing callbacks, it is recommended to override this function instead
+        of `branch` and avoid calling `super().branched(...)`.
+
+        Prefer using this function over `branch`.
+
+        Parameters
+        ----------
+        path_1: str
+            Child's source path
+        path_2: str
+            Child's destination path
+        **kwargs:
+            Arbitrary keyword arguments
+
+        Returns
+        -------
+        callback: Callback
+            A callback instance to be passed to the child method
+        """
+        self.branch(path_1, path_2, kwargs)
+        # mutate kwargs so that we can force the caller to pass "callback=" explicitly
+        return kwargs.pop("callback", DEFAULT_CALLBACK)
+
+    def branch_coro(self, fn):
+        """
+        Wraps a coroutine, and pass a new child callback to it.
+        """
+
+        @wraps(fn)
+        async def func(path1, path2: str, **kwargs):
+            with self.branched(path1, path2, **kwargs) as child:
+                return await fn(path1, path2, callback=child, **kwargs)
+
+        return func
+
+    def set_size(self, size):
+        """
+        Set the internal maximum size attribute
+
+        Usually called if not initially set at instantiation. Note that this
+        triggers a ``call()``.
+
+        Parameters
+        ----------
+        size: int
+        """
+        self.size = size
+        self.call()
+
+    def absolute_update(self, value):
+        """
+        Set the internal value state
+
+        Triggers ``call()``
+
+        Parameters
+        ----------
+        value: int
+        """
+        self.value = value
+        self.call()
+
+    def relative_update(self, inc=1):
+        """
+        Delta increment the internal counter
+
+        Triggers ``call()``
+
+        Parameters
+        ----------
+        inc: int
+        """
+        self.value += inc
+        self.call()
+
+    def call(self, hook_name=None, **kwargs):
+        """
+        Execute hook(s) with current state
+
+        Each function is passed the internal size and current value
+
+        Parameters
+        ----------
+        hook_name: str or None
+            If given, execute on this hook
+        kwargs: passed on to (all) hook(s)
+        """
+        if not self.hooks:
+            return
+        kw = self.kw.copy()
+        kw.update(kwargs)
+        if hook_name:
+            if hook_name not in self.hooks:
+                return
+            return self.hooks[hook_name](self.size, self.value, **kw)
+        for hook in self.hooks.values() or []:
+            hook(self.size, self.value, **kw)
+
+    def wrap(self, iterable):
+        """
+        Wrap an iterable to call ``relative_update`` on each iterations
+
+        Parameters
+        ----------
+        iterable: Iterable
+            The iterable that is being wrapped
+        """
+        for item in iterable:
+            self.relative_update()
+            yield item
+
+    def branch(self, path_1, path_2, kwargs):
+        """
+        Set callbacks for child transfers
+
+        If this callback is operating at a higher level, e.g., put, which may
+        trigger transfers that can also be monitored. The passed kwargs are
+        to be *mutated* to add ``callback=``, if this class supports branching
+        to children.
+
+        Parameters
+        ----------
+        path_1: str
+            Child's source path
+        path_2: str
+            Child's destination path
+        kwargs: dict
+            arguments passed to child method, e.g., put_file.
+
+        Returns
+        -------
+
+        """
+        return None
+
+    def no_op(self, *_, **__):
+        pass
+
+    def __getattr__(self, item):
+        """
+        If undefined methods are called on this class, nothing happens
+        """
+        return self.no_op
+
+    @classmethod
+    def as_callback(cls, maybe_callback=None):
+        """Transform callback=... into Callback instance
+
+        For the special value of ``None``, return the global instance of
+        ``NoOpCallback``. This is an alternative to including
+        ``callback=DEFAULT_CALLBACK`` directly in a method signature.
+        """
+        if maybe_callback is None:
+            return DEFAULT_CALLBACK
+        return maybe_callback
+
+
+class NoOpCallback(Callback):
+    """
+    This implementation of Callback does exactly nothing
+    """
+
+    def call(self, *args, **kwargs):
+        return None
+
+
+class DotPrinterCallback(Callback):
+    """
+    Simple example Callback implementation
+
+    Almost identical to Callback with a hook that prints a char; here we
+    demonstrate how the outer layer may print "#" and the inner layer "."
+    """
+
+    def __init__(self, chr_to_print="#", **kwargs):
+        self.chr = chr_to_print
+        super().__init__(**kwargs)
+
+    def branch(self, path_1, path_2, kwargs):
+        """Mutate kwargs to add new instance with different print char"""
+        kwargs["callback"] = DotPrinterCallback(".")
+
+    def call(self, **kwargs):
+        """Just outputs a character"""
+        print(self.chr, end="")
+
+
+class TqdmCallback(Callback):
+    """
+    A callback to display a progress bar using tqdm
+
+    Parameters
+    ----------
+    tqdm_kwargs : dict, (optional)
+        Any argument accepted by the tqdm constructor.
+        See the `tqdm doc <https://tqdm.github.io/docs/tqdm/#__init__>`_.
+        Will be forwarded to `tqdm_cls`.
+    tqdm_cls: (optional)
+        subclass of `tqdm.tqdm`. If not passed, it will default to `tqdm.tqdm`.
+
+    Examples
+    --------
+    >>> import fsspec
+    >>> from fsspec.callbacks import TqdmCallback
+    >>> fs = fsspec.filesystem("memory")
+    >>> path2distant_data = "/your-path"
+    >>> fs.upload(
+            ".",
+            path2distant_data,
+            recursive=True,
+            callback=TqdmCallback(),
+        )
+
+    You can forward args to tqdm using the ``tqdm_kwargs`` parameter.
+
+    >>> fs.upload(
+            ".",
+            path2distant_data,
+            recursive=True,
+            callback=TqdmCallback(tqdm_kwargs={"desc": "Your tqdm description"}),
+        )
+
+    You can also customize the progress bar by passing a subclass of `tqdm`.
+
+    .. code-block:: python
+
+        class TqdmFormat(tqdm):
+            '''Provides a `total_time` format parameter'''
+            @property
+            def format_dict(self):
+                d = super().format_dict
+                total_time = d["elapsed"] * (d["total"] or 0) / max(d["n"], 1)
+                d.update(total_time=self.format_interval(total_time) + " in total")
+                return d
+
+    >>> with TqdmCallback(
+            tqdm_kwargs={
+                "desc": "desc",
+                "bar_format": "{total_time}: {percentage:.0f}%|{bar}{r_bar}",
+            },
+            tqdm_cls=TqdmFormat,
+        ) as callback:
+            fs.upload(".", path2distant_data, recursive=True, callback=callback)
+    """
+
+    def __init__(self, tqdm_kwargs=None, *args, **kwargs):
+        try:
+            from tqdm import tqdm
+
+        except ImportError as exce:
+            raise ImportError(
+                "Using TqdmCallback requires tqdm to be installed"
+            ) from exce
+
+        self._tqdm_cls = kwargs.pop("tqdm_cls", tqdm)
+        self._tqdm_kwargs = tqdm_kwargs or {}
+        self.tqdm = None
+        super().__init__(*args, **kwargs)
+
+    def call(self, *args, **kwargs):
+        if self.tqdm is None:
+            self.tqdm = self._tqdm_cls(total=self.size, **self._tqdm_kwargs)
+        self.tqdm.total = self.size
+        self.tqdm.update(self.value - self.tqdm.n)
+
+    def close(self):
+        if self.tqdm is not None:
+            self.tqdm.close()
+            self.tqdm = None
+
+    def __del__(self):
+        return self.close()
+
+
+DEFAULT_CALLBACK = _DEFAULT_CALLBACK = NoOpCallback()

.venv/lib/python3.13/site-packages/fsspec/compression.py

@@ -0,0 +1,182 @@
+"""Helper functions for a standard streaming compression API"""
+
+from zipfile import ZipFile
+
+import fsspec.utils
+from fsspec.spec import AbstractBufferedFile
+
+
+def noop_file(file, mode, **kwargs):
+    return file
+
+
+# TODO: files should also be available as contexts
+# should be functions of the form func(infile, mode=, **kwargs) -> file-like
+compr = {None: noop_file}
+
+
+def register_compression(name, callback, extensions, force=False):
+    """Register an "inferable" file compression type.
+
+    Registers transparent file compression type for use with fsspec.open.
+    Compression can be specified by name in open, or "infer"-ed for any files
+    ending with the given extensions.
+
+    Args:
+        name: (str) The compression type name. Eg. "gzip".
+        callback: A callable of form (infile, mode, **kwargs) -> file-like.
+            Accepts an input file-like object, the target mode and kwargs.
+            Returns a wrapped file-like object.
+        extensions: (str, Iterable[str]) A file extension, or list of file
+            extensions for which to infer this compression scheme. Eg. "gz".
+        force: (bool) Force re-registration of compression type or extensions.
+
+    Raises:
+        ValueError: If name or extensions already registered, and not force.
+
+    """
+    if isinstance(extensions, str):
+        extensions = [extensions]
+
+    # Validate registration
+    if name in compr and not force:
+        raise ValueError(f"Duplicate compression registration: {name}")
+
+    for ext in extensions:
+        if ext in fsspec.utils.compressions and not force:
+            raise ValueError(f"Duplicate compression file extension: {ext} ({name})")
+
+    compr[name] = callback
+
+    for ext in extensions:
+        fsspec.utils.compressions[ext] = name
+
+
+def unzip(infile, mode="rb", filename=None, **kwargs):
+    if "r" not in mode:
+        filename = filename or "file"
+        z = ZipFile(infile, mode="w", **kwargs)
+        fo = z.open(filename, mode="w")
+        fo.close = lambda closer=fo.close: closer() or z.close()
+        return fo
+    z = ZipFile(infile)
+    if filename is None:
+        filename = z.namelist()[0]
+    return z.open(filename, mode="r", **kwargs)
+
+
+register_compression("zip", unzip, "zip")
+
+try:
+    from bz2 import BZ2File
+except ImportError:
+    pass
+else:
+    register_compression("bz2", BZ2File, "bz2")
+
+try:  # pragma: no cover
+    from isal import igzip
+
+    def isal(infile, mode="rb", **kwargs):
+        return igzip.IGzipFile(fileobj=infile, mode=mode, **kwargs)
+
+    register_compression("gzip", isal, "gz")
+except ImportError:
+    from gzip import GzipFile
+
+    register_compression(
+        "gzip", lambda f, **kwargs: GzipFile(fileobj=f, **kwargs), "gz"
+    )
+
+try:
+    from lzma import LZMAFile
+
+    register_compression("lzma", LZMAFile, "lzma")
+    register_compression("xz", LZMAFile, "xz")
+except ImportError:
+    pass
+
+try:
+    import lzmaffi
+
+    register_compression("lzma", lzmaffi.LZMAFile, "lzma", force=True)
+    register_compression("xz", lzmaffi.LZMAFile, "xz", force=True)
+except ImportError:
+    pass
+
+
+class SnappyFile(AbstractBufferedFile):
+    def __init__(self, infile, mode, **kwargs):
+        import snappy
+
+        super().__init__(
+            fs=None, path="snappy", mode=mode.strip("b") + "b", size=999999999, **kwargs
+        )
+        self.infile = infile
+        if "r" in mode:
+            self.codec = snappy.StreamDecompressor()
+        else:
+            self.codec = snappy.StreamCompressor()
+
+    def _upload_chunk(self, final=False):
+        self.buffer.seek(0)
+        out = self.codec.add_chunk(self.buffer.read())
+        self.infile.write(out)
+        return True
+
+    def seek(self, loc, whence=0):
+        raise NotImplementedError("SnappyFile is not seekable")
+
+    def seekable(self):
+        return False
+
+    def _fetch_range(self, start, end):
+        """Get the specified set of bytes from remote"""
+        data = self.infile.read(end - start)
+        return self.codec.decompress(data)
+
+
+try:
+    import snappy
+
+    snappy.compress(b"")
+    # Snappy may use the .sz file extension, but this is not part of the
+    # standard implementation.
+    register_compression("snappy", SnappyFile, [])
+
+except (ImportError, NameError, AttributeError):
+    pass
+
+try:
+    import lz4.frame
+
+    register_compression("lz4", lz4.frame.open, "lz4")
+except ImportError:
+    pass
+
+try:
+    # zstd in the standard library for python >= 3.14
+    from compression.zstd import ZstdFile
+
+    register_compression("zstd", ZstdFile, "zst")
+
+except ImportError:
+    try:
+        import zstandard as zstd
+
+        def zstandard_file(infile, mode="rb"):
+            if "r" in mode:
+                cctx = zstd.ZstdDecompressor()
+                return cctx.stream_reader(infile)
+            else:
+                cctx = zstd.ZstdCompressor(level=10)
+                return cctx.stream_writer(infile)
+
+        register_compression("zstd", zstandard_file, "zst")
+    except ImportError:
+        pass
+
+
+def available_compressions():
+    """Return a list of the implemented compressions."""
+    return list(compr)

.venv/lib/python3.13/site-packages/fsspec/config.py

@@ -0,0 +1,131 @@
+from __future__ import annotations
+
+import configparser
+import json
+import os
+import warnings
+from typing import Any
+
+conf: dict[str, dict[str, Any]] = {}
+default_conf_dir = os.path.join(os.path.expanduser("~"), ".config/fsspec")
+conf_dir = os.environ.get("FSSPEC_CONFIG_DIR", default_conf_dir)
+
+
+def set_conf_env(conf_dict, envdict=os.environ):
+    """Set config values from environment variables
+
+    Looks for variables of the form ``FSSPEC_<protocol>`` and
+    ``FSSPEC_<protocol>_<kwarg>``. For ``FSSPEC_<protocol>`` the value is parsed
+    as a json dictionary and used to ``update`` the config of the
+    corresponding protocol. For ``FSSPEC_<protocol>_<kwarg>`` there is no
+    attempt to convert the string value, but the kwarg keys will be lower-cased.
+
+    The ``FSSPEC_<protocol>_<kwarg>`` variables are applied after the
+    ``FSSPEC_<protocol>`` ones.
+
+    Parameters
+    ----------
+    conf_dict : dict(str, dict)
+        This dict will be mutated
+    envdict : dict-like(str, str)
+        Source for the values - usually the real environment
+    """
+    kwarg_keys = []
+    for key in envdict:
+        if key.startswith("FSSPEC_") and len(key) > 7 and key[7] != "_":
+            if key.count("_") > 1:
+                kwarg_keys.append(key)
+                continue
+            try:
+                value = json.loads(envdict[key])
+            except json.decoder.JSONDecodeError as ex:
+                warnings.warn(
+                    f"Ignoring environment variable {key} due to a parse failure: {ex}"
+                )
+            else:
+                if isinstance(value, dict):
+                    _, proto = key.split("_", 1)
+                    conf_dict.setdefault(proto.lower(), {}).update(value)
+                else:
+                    warnings.warn(
+                        f"Ignoring environment variable {key} due to not being a dict:"
+                        f" {type(value)}"
+                    )
+        elif key.startswith("FSSPEC"):
+            warnings.warn(
+                f"Ignoring environment variable {key} due to having an unexpected name"
+            )
+
+    for key in kwarg_keys:
+        _, proto, kwarg = key.split("_", 2)
+        conf_dict.setdefault(proto.lower(), {})[kwarg.lower()] = envdict[key]
+
+
+def set_conf_files(cdir, conf_dict):
+    """Set config values from files
+
+    Scans for INI and JSON files in the given dictionary, and uses their
+    contents to set the config. In case of repeated values, later values
+    win.
+
+    In the case of INI files, all values are strings, and these will not
+    be converted.
+
+    Parameters
+    ----------
+    cdir : str
+        Directory to search
+    conf_dict : dict(str, dict)
+        This dict will be mutated
+    """
+    if not os.path.isdir(cdir):
+        return
+    allfiles = sorted(os.listdir(cdir))
+    for fn in allfiles:
+        if fn.endswith(".ini"):
+            ini = configparser.ConfigParser()
+            ini.read(os.path.join(cdir, fn))
+            for key in ini:
+                if key == "DEFAULT":
+                    continue
+                conf_dict.setdefault(key, {}).update(dict(ini[key]))
+        if fn.endswith(".json"):
+            with open(os.path.join(cdir, fn)) as f:
+                js = json.load(f)
+            for key in js:
+                conf_dict.setdefault(key, {}).update(dict(js[key]))
+
+
+def apply_config(cls, kwargs, conf_dict=None):
+    """Supply default values for kwargs when instantiating class
+
+    Augments the passed kwargs, by finding entries in the config dict
+    which match the classes ``.protocol`` attribute (one or more str)
+
+    Parameters
+    ----------
+    cls : file system implementation
+    kwargs : dict
+    conf_dict : dict of dict
+        Typically this is the global configuration
+
+    Returns
+    -------
+    dict : the modified set of kwargs
+    """
+    if conf_dict is None:
+        conf_dict = conf
+    protos = cls.protocol if isinstance(cls.protocol, (tuple, list)) else [cls.protocol]
+    kw = {}
+    for proto in protos:
+        # default kwargs from the current state of the config
+        if proto in conf_dict:
+            kw.update(conf_dict[proto])
+    # explicit kwargs always win
+    kw.update(**kwargs)
+    kwargs = kw
+    return kwargs
+
+
+set_conf_files(conf_dir, conf)
+set_conf_env(conf)

.venv/lib/python3.13/site-packages/fsspec/conftest.py

@@ -0,0 +1,55 @@
+import os
+import shutil
+import subprocess
+import sys
+import time
+
+import pytest
+
+import fsspec
+from fsspec.implementations.cached import CachingFileSystem
+
+
+@pytest.fixture()
+def m():
+    """
+    Fixture providing a memory filesystem.
+    """
+    m = fsspec.filesystem("memory")
+    m.store.clear()
+    m.pseudo_dirs.clear()
+    m.pseudo_dirs.append("")
+    try:
+        yield m
+    finally:
+        m.store.clear()
+        m.pseudo_dirs.clear()
+        m.pseudo_dirs.append("")
+
+
+@pytest.fixture
+def ftp_writable(tmpdir):
+    """
+    Fixture providing a writable FTP filesystem.
+    """
+    pytest.importorskip("pyftpdlib")
+    from fsspec.implementations.ftp import FTPFileSystem
+
+    FTPFileSystem.clear_instance_cache()  # remove lingering connections
+    CachingFileSystem.clear_instance_cache()
+    d = str(tmpdir)
+    with open(os.path.join(d, "out"), "wb") as f:
+        f.write(b"hello" * 10000)
+    P = subprocess.Popen(
+        [sys.executable, "-m", "pyftpdlib", "-d", d, "-u", "user", "-P", "pass", "-w"]
+    )
+    try:
+        time.sleep(1)
+        yield "localhost", 2121, "user", "pass"
+    finally:
+        P.terminate()
+        P.wait()
+        try:
+            shutil.rmtree(tmpdir)
+        except Exception:
+            pass

.venv/lib/python3.13/site-packages/fsspec/core.py

@@ -0,0 +1,743 @@
+from __future__ import annotations
+
+import io
+import logging
+import os
+import re
+from glob import has_magic
+from pathlib import Path
+
+# for backwards compat, we export cache things from here too
+from fsspec.caching import (  # noqa: F401
+    BaseCache,
+    BlockCache,
+    BytesCache,
+    MMapCache,
+    ReadAheadCache,
+    caches,
+)
+from fsspec.compression import compr
+from fsspec.config import conf
+from fsspec.registry import filesystem, get_filesystem_class
+from fsspec.utils import (
+    _unstrip_protocol,
+    build_name_function,
+    infer_compression,
+    stringify_path,
+)
+
+logger = logging.getLogger("fsspec")
+
+
+class OpenFile:
+    """
+    File-like object to be used in a context
+
+    Can layer (buffered) text-mode and compression over any file-system, which
+    are typically binary-only.
+
+    These instances are safe to serialize, as the low-level file object
+    is not created until invoked using ``with``.
+
+    Parameters
+    ----------
+    fs: FileSystem
+        The file system to use for opening the file. Should be a subclass or duck-type
+        with ``fsspec.spec.AbstractFileSystem``
+    path: str
+        Location to open
+    mode: str like 'rb', optional
+        Mode of the opened file
+    compression: str or None, optional
+        Compression to apply
+    encoding: str or None, optional
+        The encoding to use if opened in text mode.
+    errors: str or None, optional
+        How to handle encoding errors if opened in text mode.
+    newline: None or str
+        Passed to TextIOWrapper in text mode, how to handle line endings.
+    autoopen: bool
+        If True, calls open() immediately. Mostly used by pickle
+    pos: int
+        If given and autoopen is True, seek to this location immediately
+    """
+
+    def __init__(
+        self,
+        fs,
+        path,
+        mode="rb",
+        compression=None,
+        encoding=None,
+        errors=None,
+        newline=None,
+    ):
+        self.fs = fs
+        self.path = path
+        self.mode = mode
+        self.compression = get_compression(path, compression)
+        self.encoding = encoding
+        self.errors = errors
+        self.newline = newline
+        self.fobjects = []
+
+    def __reduce__(self):
+        return (
+            OpenFile,
+            (
+                self.fs,
+                self.path,
+                self.mode,
+                self.compression,
+                self.encoding,
+                self.errors,
+                self.newline,
+            ),
+        )
+
+    def __repr__(self):
+        return f"<OpenFile '{self.path}'>"
+
+    def __enter__(self):
+        mode = self.mode.replace("t", "").replace("b", "") + "b"
+
+        try:
+            f = self.fs.open(self.path, mode=mode)
+        except FileNotFoundError as e:
+            if has_magic(self.path):
+                raise FileNotFoundError(
+                    "%s not found. The URL contains glob characters: you maybe needed\n"
+                    "to pass expand=True in fsspec.open() or the storage_options of \n"
+                    "your library. You can also set the config value 'open_expand'\n"
+                    "before import, or fsspec.core.DEFAULT_EXPAND at runtime, to True.",
+                    self.path,
+                ) from e
+            raise
+
+        self.fobjects = [f]
+
+        if self.compression is not None:
+            compress = compr[self.compression]
+            f = compress(f, mode=mode[0])
+            self.fobjects.append(f)
+
+        if "b" not in self.mode:
+            # assume, for example, that 'r' is equivalent to 'rt' as in builtin
+            f = PickleableTextIOWrapper(
+                f, encoding=self.encoding, errors=self.errors, newline=self.newline
+            )
+            self.fobjects.append(f)
+
+        return self.fobjects[-1]
+
+    def __exit__(self, *args):
+        self.close()
+
+    @property
+    def full_name(self):
+        return _unstrip_protocol(self.path, self.fs)
+
+    def open(self):
+        """Materialise this as a real open file without context
+
+        The OpenFile object should be explicitly closed to avoid enclosed file
+        instances persisting. You must, therefore, keep a reference to the OpenFile
+        during the life of the file-like it generates.
+        """
+        return self.__enter__()
+
+    def close(self):
+        """Close all encapsulated file objects"""
+        for f in reversed(self.fobjects):
+            if "r" not in self.mode and not f.closed:
+                f.flush()
+            f.close()
+        self.fobjects.clear()
+
+
+class OpenFiles(list):
+    """List of OpenFile instances
+
+    Can be used in a single context, which opens and closes all of the
+    contained files. Normal list access to get the elements works as
+    normal.
+
+    A special case is made for caching filesystems - the files will
+    be down/uploaded together at the start or end of the context, and
+    this may happen concurrently, if the target filesystem supports it.
+    """
+
+    def __init__(self, *args, mode="rb", fs=None):
+        self.mode = mode
+        self.fs = fs
+        self.files = []
+        super().__init__(*args)
+
+    def __enter__(self):
+        if self.fs is None:
+            raise ValueError("Context has already been used")
+
+        fs = self.fs
+        while True:
+            if hasattr(fs, "open_many"):
+                # check for concurrent cache download; or set up for upload
+                self.files = fs.open_many(self)
+                return self.files
+            if hasattr(fs, "fs") and fs.fs is not None:
+                fs = fs.fs
+            else:
+                break
+        return [s.__enter__() for s in self]
+
+    def __exit__(self, *args):
+        fs = self.fs
+        [s.__exit__(*args) for s in self]
+        if "r" not in self.mode:
+            while True:
+                if hasattr(fs, "open_many"):
+                    # check for concurrent cache upload
+                    fs.commit_many(self.files)
+                    return
+                if hasattr(fs, "fs") and fs.fs is not None:
+                    fs = fs.fs
+                else:
+                    break
+
+    def __getitem__(self, item):
+        out = super().__getitem__(item)
+        if isinstance(item, slice):
+            return OpenFiles(out, mode=self.mode, fs=self.fs)
+        return out
+
+    def __repr__(self):
+        return f"<List of {len(self)} OpenFile instances>"
+
+
+def open_files(
+    urlpath,
+    mode="rb",
+    compression=None,
+    encoding="utf8",
+    errors=None,
+    name_function=None,
+    num=1,
+    protocol=None,
+    newline=None,
+    auto_mkdir=True,
+    expand=True,
+    **kwargs,
+):
+    """Given a path or paths, return a list of ``OpenFile`` objects.
+
+    For writing, a str path must contain the "*" character, which will be filled
+    in by increasing numbers, e.g., "part*" ->  "part1", "part2" if num=2.
+
+    For either reading or writing, can instead provide explicit list of paths.
+
+    Parameters
+    ----------
+    urlpath: string or list
+        Absolute or relative filepath(s). Prefix with a protocol like ``s3://``
+        to read from alternative filesystems. To read from multiple files you
+        can pass a globstring or a list of paths, with the caveat that they
+        must all have the same protocol.
+    mode: 'rb', 'wt', etc.
+    compression: string or None
+        If given, open file using compression codec. Can either be a compression
+        name (a key in ``fsspec.compression.compr``) or "infer" to guess the
+        compression from the filename suffix.
+    encoding: str
+        For text mode only
+    errors: None or str
+        Passed to TextIOWrapper in text mode
+    name_function: function or None
+        if opening a set of files for writing, those files do not yet exist,
+        so we need to generate their names by formatting the urlpath for
+        each sequence number
+    num: int [1]
+        if writing mode, number of files we expect to create (passed to
+        name+function)
+    protocol: str or None
+        If given, overrides the protocol found in the URL.
+    newline: bytes or None
+        Used for line terminator in text mode. If None, uses system default;
+        if blank, uses no translation.
+    auto_mkdir: bool (True)
+        If in write mode, this will ensure the target directory exists before
+        writing, by calling ``fs.mkdirs(exist_ok=True)``.
+    expand: bool
+    **kwargs: dict
+        Extra options that make sense to a particular storage connection, e.g.
+        host, port, username, password, etc.
+
+    Examples
+    --------
+    >>> files = open_files('2015-*-*.csv')  # doctest: +SKIP
+    >>> files = open_files(
+    ...     's3://bucket/2015-*-*.csv.gz', compression='gzip'
+    ... )  # doctest: +SKIP
+
+    Returns
+    -------
+    An ``OpenFiles`` instance, which is a list of ``OpenFile`` objects that can
+    be used as a single context
+
+    Notes
+    -----
+    For a full list of the available protocols and the implementations that
+    they map across to see the latest online documentation:
+
+    - For implementations built into ``fsspec`` see
+      https://filesystem-spec.readthedocs.io/en/latest/api.html#built-in-implementations
+    - For implementations in separate packages see
+      https://filesystem-spec.readthedocs.io/en/latest/api.html#other-known-implementations
+    """
+    fs, fs_token, paths = get_fs_token_paths(
+        urlpath,
+        mode,
+        num=num,
+        name_function=name_function,
+        storage_options=kwargs,
+        protocol=protocol,
+        expand=expand,
+    )
+    if fs.protocol == "file":
+        fs.auto_mkdir = auto_mkdir
+    elif "r" not in mode and auto_mkdir:
+        parents = {fs._parent(path) for path in paths}
+        for parent in parents:
+            try:
+                fs.makedirs(parent, exist_ok=True)
+            except PermissionError:
+                pass
+    return OpenFiles(
+        [
+            OpenFile(
+                fs,
+                path,
+                mode=mode,
+                compression=compression,
+                encoding=encoding,
+                errors=errors,
+                newline=newline,
+            )
+            for path in paths
+        ],
+        mode=mode,
+        fs=fs,
+    )
+
+
+def _un_chain(path, kwargs):
+    # Avoid a circular import
+    from fsspec.implementations.cached import CachingFileSystem
+
+    if "::" in path:
+        x = re.compile(".*[^a-z]+.*")  # test for non protocol-like single word
+        bits = []
+        for p in path.split("::"):
+            if "://" in p or x.match(p):
+                bits.append(p)
+            else:
+                bits.append(p + "://")
+    else:
+        bits = [path]
+    # [[url, protocol, kwargs], ...]
+    out = []
+    previous_bit = None
+    kwargs = kwargs.copy()
+    for bit in reversed(bits):
+        protocol = kwargs.pop("protocol", None) or split_protocol(bit)[0] or "file"
+        cls = get_filesystem_class(protocol)
+        extra_kwargs = cls._get_kwargs_from_urls(bit)
+        kws = kwargs.pop(protocol, {})
+        if bit is bits[0]:
+            kws.update(kwargs)
+        kw = dict(
+            **{k: v for k, v in extra_kwargs.items() if k not in kws or v != kws[k]},
+            **kws,
+        )
+        bit = cls._strip_protocol(bit)
+        if "target_protocol" not in kw and issubclass(cls, CachingFileSystem):
+            bit = previous_bit
+        out.append((bit, protocol, kw))
+        previous_bit = bit
+    out.reverse()
+    return out
+
+
+def url_to_fs(url, **kwargs):
+    """
+    Turn fully-qualified and potentially chained URL into filesystem instance
+
+    Parameters
+    ----------
+    url : str
+        The fsspec-compatible URL
+    **kwargs: dict
+        Extra options that make sense to a particular storage connection, e.g.
+        host, port, username, password, etc.
+
+    Returns
+    -------
+    filesystem : FileSystem
+        The new filesystem discovered from ``url`` and created with
+        ``**kwargs``.
+    urlpath : str
+        The file-systems-specific URL for ``url``.
+    """
+    url = stringify_path(url)
+    # non-FS arguments that appear in fsspec.open()
+    # inspect could keep this in sync with open()'s signature
+    known_kwargs = {
+        "compression",
+        "encoding",
+        "errors",
+        "expand",
+        "mode",
+        "name_function",
+        "newline",
+        "num",
+    }
+    kwargs = {k: v for k, v in kwargs.items() if k not in known_kwargs}
+    chain = _un_chain(url, kwargs)
+    inkwargs = {}
+    # Reverse iterate the chain, creating a nested target_* structure
+    for i, ch in enumerate(reversed(chain)):
+        urls, protocol, kw = ch
+        if i == len(chain) - 1:
+            inkwargs = dict(**kw, **inkwargs)
+            continue
+        inkwargs["target_options"] = dict(**kw, **inkwargs)
+        inkwargs["target_protocol"] = protocol
+        inkwargs["fo"] = urls
+    urlpath, protocol, _ = chain[0]
+    fs = filesystem(protocol, **inkwargs)
+    return fs, urlpath
+
+
+DEFAULT_EXPAND = conf.get("open_expand", False)
+
+
+def open(
+    urlpath,
+    mode="rb",
+    compression=None,
+    encoding="utf8",
+    errors=None,
+    protocol=None,
+    newline=None,
+    expand=None,
+    **kwargs,
+):
+    """Given a path or paths, return one ``OpenFile`` object.
+
+    Parameters
+    ----------
+    urlpath: string or list
+        Absolute or relative filepath. Prefix with a protocol like ``s3://``
+        to read from alternative filesystems. Should not include glob
+        character(s).
+    mode: 'rb', 'wt', etc.
+    compression: string or None
+        If given, open file using compression codec. Can either be a compression
+        name (a key in ``fsspec.compression.compr``) or "infer" to guess the
+        compression from the filename suffix.
+    encoding: str
+        For text mode only
+    errors: None or str
+        Passed to TextIOWrapper in text mode
+    protocol: str or None
+        If given, overrides the protocol found in the URL.
+    newline: bytes or None
+        Used for line terminator in text mode. If None, uses system default;
+        if blank, uses no translation.
+    expand: bool or None
+        Whether to regard file paths containing special glob characters as needing
+        expansion (finding the first match) or absolute. Setting False allows using
+        paths which do embed such characters. If None (default), this argument
+        takes its value from the DEFAULT_EXPAND module variable, which takes
+        its initial value from the "open_expand" config value at startup, which will
+        be False if not set.
+    **kwargs: dict
+        Extra options that make sense to a particular storage connection, e.g.
+        host, port, username, password, etc.
+
+    Examples
+    --------
+    >>> openfile = open('2015-01-01.csv')  # doctest: +SKIP
+    >>> openfile = open(
+    ...     's3://bucket/2015-01-01.csv.gz', compression='gzip'
+    ... )  # doctest: +SKIP
+    >>> with openfile as f:
+    ...     df = pd.read_csv(f)  # doctest: +SKIP
+    ...
+
+    Returns
+    -------
+    ``OpenFile`` object.
+
+    Notes
+    -----
+    For a full list of the available protocols and the implementations that
+    they map across to see the latest online documentation:
+
+    - For implementations built into ``fsspec`` see
+      https://filesystem-spec.readthedocs.io/en/latest/api.html#built-in-implementations
+    - For implementations in separate packages see
+      https://filesystem-spec.readthedocs.io/en/latest/api.html#other-known-implementations
+    """
+    expand = DEFAULT_EXPAND if expand is None else expand
+    out = open_files(
+        urlpath=[urlpath],
+        mode=mode,
+        compression=compression,
+        encoding=encoding,
+        errors=errors,
+        protocol=protocol,
+        newline=newline,
+        expand=expand,
+        **kwargs,
+    )
+    if not out:
+        raise FileNotFoundError(urlpath)
+    return out[0]
+
+
+def open_local(
+    url: str | list[str] | Path | list[Path],
+    mode: str = "rb",
+    **storage_options: dict,
+) -> str | list[str]:
+    """Open file(s) which can be resolved to local
+
+    For files which either are local, or get downloaded upon open
+    (e.g., by file caching)
+
+    Parameters
+    ----------
+    url: str or list(str)
+    mode: str
+        Must be read mode
+    storage_options:
+        passed on to FS for or used by open_files (e.g., compression)
+    """
+    if "r" not in mode:
+        raise ValueError("Can only ensure local files when reading")
+    of = open_files(url, mode=mode, **storage_options)
+    if not getattr(of[0].fs, "local_file", False):
+        raise ValueError(
+            "open_local can only be used on a filesystem which"
+            " has attribute local_file=True"
+        )
+    with of as files:
+        paths = [f.name for f in files]
+    if (isinstance(url, str) and not has_magic(url)) or isinstance(url, Path):
+        return paths[0]
+    return paths
+
+
+def get_compression(urlpath, compression):
+    if compression == "infer":
+        compression = infer_compression(urlpath)
+    if compression is not None and compression not in compr:
+        raise ValueError(f"Compression type {compression} not supported")
+    return compression
+
+
+def split_protocol(urlpath):
+    """Return protocol, path pair"""
+    urlpath = stringify_path(urlpath)
+    if "://" in urlpath:
+        protocol, path = urlpath.split("://", 1)
+        if len(protocol) > 1:
+            # excludes Windows paths
+            return protocol, path
+    if urlpath.startswith("data:"):
+        return urlpath.split(":", 1)
+    return None, urlpath
+
+
+def strip_protocol(urlpath):
+    """Return only path part of full URL, according to appropriate backend"""
+    protocol, _ = split_protocol(urlpath)
+    cls = get_filesystem_class(protocol)
+    return cls._strip_protocol(urlpath)
+
+
+def expand_paths_if_needed(paths, mode, num, fs, name_function):
+    """Expand paths if they have a ``*`` in them (write mode) or any of ``*?[]``
+    in them (read mode).
+
+    :param paths: list of paths
+    mode: str
+        Mode in which to open files.
+    num: int
+        If opening in writing mode, number of files we expect to create.
+    fs: filesystem object
+    name_function: callable
+        If opening in writing mode, this callable is used to generate path
+        names. Names are generated for each partition by
+        ``urlpath.replace('*', name_function(partition_index))``.
+    :return: list of paths
+    """
+    expanded_paths = []
+    paths = list(paths)
+
+    if "w" in mode:  # read mode
+        if sum(1 for p in paths if "*" in p) > 1:
+            raise ValueError(
+                "When writing data, only one filename mask can be specified."
+            )
+        num = max(num, len(paths))
+
+        for curr_path in paths:
+            if "*" in curr_path:
+                # expand using name_function
+                expanded_paths.extend(_expand_paths(curr_path, name_function, num))
+            else:
+                expanded_paths.append(curr_path)
+        # if we generated more paths that asked for, trim the list
+        if len(expanded_paths) > num:
+            expanded_paths = expanded_paths[:num]
+
+    else:  # read mode
+        for curr_path in paths:
+            if has_magic(curr_path):
+                # expand using glob
+                expanded_paths.extend(fs.glob(curr_path))
+            else:
+                expanded_paths.append(curr_path)
+
+    return expanded_paths
+
+
+def get_fs_token_paths(
+    urlpath,
+    mode="rb",
+    num=1,
+    name_function=None,
+    storage_options=None,
+    protocol=None,
+    expand=True,
+):
+    """Filesystem, deterministic token, and paths from a urlpath and options.
+
+    Parameters
+    ----------
+    urlpath: string or iterable
+        Absolute or relative filepath, URL (may include protocols like
+        ``s3://``), or globstring pointing to data.
+    mode: str, optional
+        Mode in which to open files.
+    num: int, optional
+        If opening in writing mode, number of files we expect to create.
+    name_function: callable, optional
+        If opening in writing mode, this callable is used to generate path
+        names. Names are generated for each partition by
+        ``urlpath.replace('*', name_function(partition_index))``.
+    storage_options: dict, optional
+        Additional keywords to pass to the filesystem class.
+    protocol: str or None
+        To override the protocol specifier in the URL
+    expand: bool
+        Expand string paths for writing, assuming the path is a directory
+    """
+    if isinstance(urlpath, (list, tuple, set)):
+        if not urlpath:
+            raise ValueError("empty urlpath sequence")
+        urlpath0 = stringify_path(next(iter(urlpath)))
+    else:
+        urlpath0 = stringify_path(urlpath)
+    storage_options = storage_options or {}
+    if protocol:
+        storage_options["protocol"] = protocol
+    chain = _un_chain(urlpath0, storage_options or {})
+    inkwargs = {}
+    # Reverse iterate the chain, creating a nested target_* structure
+    for i, ch in enumerate(reversed(chain)):
+        urls, nested_protocol, kw = ch
+        if i == len(chain) - 1:
+            inkwargs = dict(**kw, **inkwargs)
+            continue
+        inkwargs["target_options"] = dict(**kw, **inkwargs)
+        inkwargs["target_protocol"] = nested_protocol
+        inkwargs["fo"] = urls
+    paths, protocol, _ = chain[0]
+    fs = filesystem(protocol, **inkwargs)
+    if isinstance(urlpath, (list, tuple, set)):
+        pchains = [
+            _un_chain(stringify_path(u), storage_options or {})[0] for u in urlpath
+        ]
+        if len({pc[1] for pc in pchains}) > 1:
+            raise ValueError("Protocol mismatch getting fs from %s", urlpath)
+        paths = [pc[0] for pc in pchains]
+    else:
+        paths = fs._strip_protocol(paths)
+    if isinstance(paths, (list, tuple, set)):
+        if expand:
+            paths = expand_paths_if_needed(paths, mode, num, fs, name_function)
+        elif not isinstance(paths, list):
+            paths = list(paths)
+    else:
+        if ("w" in mode or "x" in mode) and expand:
+            paths = _expand_paths(paths, name_function, num)
+        elif "*" in paths:
+            paths = [f for f in sorted(fs.glob(paths)) if not fs.isdir(f)]
+        else:
+            paths = [paths]
+
+    return fs, fs._fs_token, paths
+
+
+def _expand_paths(path, name_function, num):
+    if isinstance(path, str):
+        if path.count("*") > 1:
+            raise ValueError("Output path spec must contain exactly one '*'.")
+        elif "*" not in path:
+            path = os.path.join(path, "*.part")
+
+        if name_function is None:
+            name_function = build_name_function(num - 1)
+
+        paths = [path.replace("*", name_function(i)) for i in range(num)]
+        if paths != sorted(paths):
+            logger.warning(
+                "In order to preserve order between partitions"
+                " paths created with ``name_function`` should "
+                "sort to partition order"
+            )
+    elif isinstance(path, (tuple, list)):
+        assert len(path) == num
+        paths = list(path)
+    else:
+        raise ValueError(
+            "Path should be either\n"
+            "1. A list of paths: ['foo.json', 'bar.json', ...]\n"
+            "2. A directory: 'foo/\n"
+            "3. A path with a '*' in it: 'foo.*.json'"
+        )
+    return paths
+
+
+class PickleableTextIOWrapper(io.TextIOWrapper):
+    """TextIOWrapper cannot be pickled. This solves it.
+
+    Requires that ``buffer`` be pickleable, which all instances of
+    AbstractBufferedFile are.
+    """
+
+    def __init__(
+        self,
+        buffer,
+        encoding=None,
+        errors=None,
+        newline=None,
+        line_buffering=False,
+        write_through=False,
+    ):
+        self.args = buffer, encoding, errors, newline, line_buffering, write_through
+        super().__init__(*self.args)
+
+    def __reduce__(self):
+        return PickleableTextIOWrapper, self.args

.venv/lib/python3.13/site-packages/fsspec/dircache.py

@@ -0,0 +1,98 @@
+import time
+from collections.abc import MutableMapping
+from functools import lru_cache
+
+
+class DirCache(MutableMapping):
+    """
+    Caching of directory listings, in a structure like::
+
+        {"path0": [
+            {"name": "path0/file0",
+             "size": 123,
+             "type": "file",
+             ...
+            },
+            {"name": "path0/file1",
+            },
+            ...
+            ],
+         "path1": [...]
+        }
+
+    Parameters to this class control listing expiry or indeed turn
+    caching off
+    """
+
+    def __init__(
+        self,
+        use_listings_cache=True,
+        listings_expiry_time=None,
+        max_paths=None,
+        **kwargs,
+    ):
+        """
+
+        Parameters
+        ----------
+        use_listings_cache: bool
+            If False, this cache never returns items, but always reports KeyError,
+            and setting items has no effect
+        listings_expiry_time: int or float (optional)
+            Time in seconds that a listing is considered valid. If None,
+            listings do not expire.
+        max_paths: int (optional)
+            The number of most recent listings that are considered valid; 'recent'
+            refers to when the entry was set.
+        """
+        self._cache = {}
+        self._times = {}
+        if max_paths:
+            self._q = lru_cache(max_paths + 1)(lambda key: self._cache.pop(key, None))
+        self.use_listings_cache = use_listings_cache
+        self.listings_expiry_time = listings_expiry_time
+        self.max_paths = max_paths
+
+    def __getitem__(self, item):
+        if self.listings_expiry_time is not None:
+            if self._times.get(item, 0) - time.time() < -self.listings_expiry_time:
+                del self._cache[item]
+        if self.max_paths:
+            self._q(item)
+        return self._cache[item]  # maybe raises KeyError
+
+    def clear(self):
+        self._cache.clear()
+
+    def __len__(self):
+        return len(self._cache)
+
+    def __contains__(self, item):
+        try:
+            self[item]
+            return True
+        except KeyError:
+            return False
+
+    def __setitem__(self, key, value):
+        if not self.use_listings_cache:
+            return
+        if self.max_paths:
+            self._q(key)
+        self._cache[key] = value
+        if self.listings_expiry_time is not None:
+            self._times[key] = time.time()
+
+    def __delitem__(self, key):
+        del self._cache[key]
+
+    def __iter__(self):
+        entries = list(self._cache)
+
+        return (k for k in entries if k in self)
+
+    def __reduce__(self):
+        return (
+            DirCache,
+            (self.use_listings_cache, self.listings_expiry_time, self.max_paths),
+        )

.venv/lib/python3.13/site-packages/fsspec/fuse.py

@@ -0,0 +1,324 @@
+import argparse
+import logging
+import os
+import stat
+import threading
+import time
+from errno import EIO, ENOENT
+
+from fuse import FUSE, FuseOSError, LoggingMixIn, Operations
+
+from fsspec import __version__
+from fsspec.core import url_to_fs
+
+logger = logging.getLogger("fsspec.fuse")
+
+
+class FUSEr(Operations):
+    def __init__(self, fs, path, ready_file=False):
+        self.fs = fs
+        self.cache = {}
+        self.root = path.rstrip("/") + "/"
+        self.counter = 0
+        logger.info("Starting FUSE at %s", path)
+        self._ready_file = ready_file
+
+    def getattr(self, path, fh=None):
+        logger.debug("getattr %s", path)
+        if self._ready_file and path in ["/.fuse_ready", ".fuse_ready"]:
+            return {"type": "file", "st_size": 5}
+
+        path = "".join([self.root, path.lstrip("/")]).rstrip("/")
+        try:
+            info = self.fs.info(path)
+        except FileNotFoundError as exc:
+            raise FuseOSError(ENOENT) from exc
+
+        data = {"st_uid": info.get("uid", 1000), "st_gid": info.get("gid", 1000)}
+        perm = info.get("mode", 0o777)
+
+        if info["type"] != "file":
+            data["st_mode"] = stat.S_IFDIR | perm
+            data["st_size"] = 0
+            data["st_blksize"] = 0
+        else:
+            data["st_mode"] = stat.S_IFREG | perm
+            data["st_size"] = info["size"]
+            data["st_blksize"] = 5 * 2**20
+            data["st_nlink"] = 1
+        data["st_atime"] = info["atime"] if "atime" in info else time.time()
+        data["st_ctime"] = info["ctime"] if "ctime" in info else time.time()
+        data["st_mtime"] = info["mtime"] if "mtime" in info else time.time()
+        return data
+
+    def readdir(self, path, fh):
+        logger.debug("readdir %s", path)
+        path = "".join([self.root, path.lstrip("/")])
+        files = self.fs.ls(path, False)
+        files = [os.path.basename(f.rstrip("/")) for f in files]
+        return [".", ".."] + files
+
+    def mkdir(self, path, mode):
+        path = "".join([self.root, path.lstrip("/")])
+        self.fs.mkdir(path)
+        return 0
+
+    def rmdir(self, path):
+        path = "".join([self.root, path.lstrip("/")])
+        self.fs.rmdir(path)
+        return 0
+
+    def read(self, path, size, offset, fh):
+        logger.debug("read %s", (path, size, offset))
+        if self._ready_file and path in ["/.fuse_ready", ".fuse_ready"]:
+            # status indicator
+            return b"ready"
+
+        f = self.cache[fh]
+        f.seek(offset)
+        out = f.read(size)
+        return out
+
+    def write(self, path, data, offset, fh):
+        logger.debug("write %s", (path, offset))
+        f = self.cache[fh]
+        f.seek(offset)
+        f.write(data)
+        return len(data)
+
+    def create(self, path, flags, fi=None):
+        logger.debug("create %s", (path, flags))
+        fn = "".join([self.root, path.lstrip("/")])
+        self.fs.touch(fn)  # OS will want to get attributes immediately
+        f = self.fs.open(fn, "wb")
+        self.cache[self.counter] = f
+        self.counter += 1
+        return self.counter - 1
+
+    def open(self, path, flags):
+        logger.debug("open %s", (path, flags))
+        fn = "".join([self.root, path.lstrip("/")])
+        if flags % 2 == 0:
+            # read
+            mode = "rb"
+        else:
+            # write/create
+            mode = "wb"
+        self.cache[self.counter] = self.fs.open(fn, mode)
+        self.counter += 1
+        return self.counter - 1
+
+    def truncate(self, path, length, fh=None):
+        fn = "".join([self.root, path.lstrip("/")])
+        if length != 0:
+            raise NotImplementedError
+        # maybe should be no-op since open with write sets size to zero anyway
+        self.fs.touch(fn)
+
+    def unlink(self, path):
+        fn = "".join([self.root, path.lstrip("/")])
+        try:
+            self.fs.rm(fn, False)
+        except (OSError, FileNotFoundError) as exc:
+            raise FuseOSError(EIO) from exc
+
+    def release(self, path, fh):
+        try:
+            if fh in self.cache:
+                f = self.cache[fh]
+                f.close()
+                self.cache.pop(fh)
+        except Exception as e:
+            print(e)
+        return 0
+
+    def chmod(self, path, mode):
+        if hasattr(self.fs, "chmod"):
+            path = "".join([self.root, path.lstrip("/")])
+            return self.fs.chmod(path, mode)
+        raise NotImplementedError
+
+
+def run(
+    fs,
+    path,
+    mount_point,
+    foreground=True,
+    threads=False,
+    ready_file=False,
+    ops_class=FUSEr,
+):
+    """Mount stuff in a local directory
+
+    This uses fusepy to make it appear as if a given path on an fsspec
+    instance is in fact resident within the local file-system.
+
+    This requires that fusepy by installed, and that FUSE be available on
+    the system (typically requiring a package to be installed with
+    apt, yum, brew, etc.).
+
+    Parameters
+    ----------
+    fs: file-system instance
+        From one of the compatible implementations
+    path: str
+        Location on that file-system to regard as the root directory to
+        mount. Note that you typically should include the terminating "/"
+        character.
+    mount_point: str
+        An empty directory on the local file-system where the contents of
+        the remote path will appear.
+    foreground: bool
+        Whether or not calling this function will block. Operation will
+        typically be more stable if True.
+    threads: bool
+        Whether or not to create threads when responding to file operations
+        within the mounter directory. Operation will typically be more
+        stable if False.
+    ready_file: bool
+        Whether the FUSE process is ready. The ``.fuse_ready`` file will
+        exist in the ``mount_point`` directory if True. Debugging purpose.
+    ops_class: FUSEr or Subclass of FUSEr
+        To override the default behavior of FUSEr. For Example, logging
+        to file.
+
+    """
+    func = lambda: FUSE(
+        ops_class(fs, path, ready_file=ready_file),
+        mount_point,
+        nothreads=not threads,
+        foreground=foreground,
+    )
+    if not foreground:
+        th = threading.Thread(target=func)
+        th.daemon = True
+        th.start()
+        return th
+    else:  # pragma: no cover
+        try:
+            func()
+        except KeyboardInterrupt:
+            pass
+
+
+def main(args):
+    """Mount filesystem from chained URL to MOUNT_POINT.
+
+    Examples:
+
+    python3 -m fsspec.fuse memory /usr/share /tmp/mem
+
+    python3 -m fsspec.fuse local /tmp/source /tmp/local \\
+            -l /tmp/fsspecfuse.log
+
+    You can also mount chained-URLs and use special settings:
+
+    python3 -m fsspec.fuse 'filecache::zip::file://data.zip' \\
+            / /tmp/zip \\
+            -o 'filecache-cache_storage=/tmp/simplecache'
+
+    You can specify the type of the setting by using `[int]` or `[bool]`,
+    (`true`, `yes`, `1` represents the Boolean value `True`):
+
+    python3 -m fsspec.fuse 'simplecache::ftp://ftp1.at.proftpd.org' \\
+            /historic/packages/RPMS /tmp/ftp \\
+            -o 'simplecache-cache_storage=/tmp/simplecache' \\
+            -o 'simplecache-check_files=false[bool]' \\
+            -o 'ftp-listings_expiry_time=60[int]' \\
+            -o 'ftp-username=anonymous' \\
+            -o 'ftp-password=xieyanbo'
+    """
+
+    class RawDescriptionArgumentParser(argparse.ArgumentParser):
+        def format_help(self):
+            usage = super().format_help()
+            parts = usage.split("\n\n")
+            parts[1] = self.description.rstrip()
+            return "\n\n".join(parts)
+
+    parser = RawDescriptionArgumentParser(prog="fsspec.fuse", description=main.__doc__)
+    parser.add_argument("--version", action="version", version=__version__)
+    parser.add_argument("url", type=str, help="fs url")
+    parser.add_argument("source_path", type=str, help="source directory in fs")
+    parser.add_argument("mount_point", type=str, help="local directory")
+    parser.add_argument(
+        "-o",
+        "--option",
+        action="append",
+        help="Any options of protocol included in the chained URL",
+    )
+    parser.add_argument(
+        "-l", "--log-file", type=str, help="Logging FUSE debug info (Default: '')"
+    )
+    parser.add_argument(
+        "-f",
+        "--foreground",
+        action="store_false",
+        help="Running in foreground or not (Default: False)",
+    )
+    parser.add_argument(
+        "-t",
+        "--threads",
+        action="store_false",
+        help="Running with threads support (Default: False)",
+    )
+    parser.add_argument(
+        "-r",
+        "--ready-file",
+        action="store_false",
+        help="The `.fuse_ready` file will exist after FUSE is ready. "
+        "(Debugging purpose, Default: False)",
+    )
+    args = parser.parse_args(args)
+
+    kwargs = {}
+    for item in args.option or []:
+        key, sep, value = item.partition("=")
+        if not sep:
+            parser.error(message=f"Wrong option: {item!r}")
+        val = value.lower()
+        if val.endswith("[int]"):
+            value = int(value[: -len("[int]")])
+        elif val.endswith("[bool]"):
+            value = val[: -len("[bool]")] in ["1", "yes", "true"]
+
+        if "-" in key:
+            fs_name, setting_name = key.split("-", 1)
+            if fs_name in kwargs:
+                kwargs[fs_name][setting_name] = value
+            else:
+                kwargs[fs_name] = {setting_name: value}
+        else:
+            kwargs[key] = value
+
+    if args.log_file:
+        logging.basicConfig(
+            level=logging.DEBUG,
+            filename=args.log_file,
+            format="%(asctime)s %(message)s",
+        )
+
+        class LoggingFUSEr(FUSEr, LoggingMixIn):
+            pass
+
+        fuser = LoggingFUSEr
+    else:
+        fuser = FUSEr
+
+    fs, url_path = url_to_fs(args.url, **kwargs)
+    logger.debug("Mounting %s to %s", url_path, str(args.mount_point))
+    run(
+        fs,
+        args.source_path,
+        args.mount_point,
+        foreground=args.foreground,
+        threads=args.threads,
+        ready_file=args.ready_file,
+        ops_class=fuser,
+    )
+
+
+if __name__ == "__main__":
+    import sys
+
+    main(sys.argv[1:])

.venv/lib/python3.13/site-packages/fsspec/generic.py

@@ -0,0 +1,394 @@
+from __future__ import annotations
+
+import inspect
+import logging
+import os
+import shutil
+import uuid
+
+from .asyn import AsyncFileSystem, _run_coros_in_chunks, sync_wrapper
+from .callbacks import DEFAULT_CALLBACK
+from .core import filesystem, get_filesystem_class, split_protocol, url_to_fs
+
+_generic_fs = {}
+logger = logging.getLogger("fsspec.generic")
+
+
+def set_generic_fs(protocol, **storage_options):
+    """Populate the dict used for method=="generic" lookups"""
+    _generic_fs[protocol] = filesystem(protocol, **storage_options)
+
+
+def _resolve_fs(url, method, protocol=None, storage_options=None):
+    """Pick instance of backend FS"""
+    url = url[0] if isinstance(url, (list, tuple)) else url
+    protocol = protocol or split_protocol(url)[0]
+    storage_options = storage_options or {}
+    if method == "default":
+        return filesystem(protocol)
+    if method == "generic":
+        return _generic_fs[protocol]
+    if method == "current":
+        cls = get_filesystem_class(protocol)
+        return cls.current()
+    if method == "options":
+        fs, _ = url_to_fs(url, **storage_options.get(protocol, {}))
+        return fs
+    raise ValueError(f"Unknown FS resolution method: {method}")
+
+
+def rsync(
+    source,
+    destination,
+    delete_missing=False,
+    source_field="size",
+    dest_field="size",
+    update_cond="different",
+    inst_kwargs=None,
+    fs=None,
+    **kwargs,
+):
+    """Sync files between two directory trees
+
+    (experimental)
+
+    Parameters
+    ----------
+    source: str
+        Root of the directory tree to take files from. This must be a directory, but
+        do not include any terminating "/" character
+    destination: str
+        Root path to copy into. The contents of this location should be
+        identical to the contents of ``source`` when done. This will be made a
+        directory, and the terminal "/" should not be included.
+    delete_missing: bool
+        If there are paths in the destination that don't exist in the
+        source and this is True, delete them. Otherwise, leave them alone.
+    source_field: str | callable
+        If ``update_field`` is "different", this is the key in the info
+        of source files to consider for difference. Maybe a function of the
+        info dict.
+    dest_field: str | callable
+        If ``update_field`` is "different", this is the key in the info
+        of destination files to consider for difference. May be a function of
+        the info dict.
+    update_cond: "different"|"always"|"never"
+        If "always", every file is copied, regardless of whether it exists in
+        the destination. If "never", files that exist in the destination are
+        not copied again. If "different" (default), only copy if the info
+        fields given by ``source_field`` and ``dest_field`` (usually "size")
+        are different. Other comparisons may be added in the future.
+    inst_kwargs: dict|None
+        If ``fs`` is None, use this set of keyword arguments to make a
+        GenericFileSystem instance
+    fs: GenericFileSystem|None
+        Instance to use if explicitly given. The instance defines how to
+        to make downstream file system instances from paths.
+
+    Returns
+    -------
+    dict of the copy operations that were performed, {source: destination}
+    """
+    fs = fs or GenericFileSystem(**(inst_kwargs or {}))
+    source = fs._strip_protocol(source)
+    destination = fs._strip_protocol(destination)
+    allfiles = fs.find(source, withdirs=True, detail=True)
+    if not fs.isdir(source):
+        raise ValueError("Can only rsync on a directory")
+    otherfiles = fs.find(destination, withdirs=True, detail=True)
+    dirs = [
+        a
+        for a, v in allfiles.items()
+        if v["type"] == "directory" and a.replace(source, destination) not in otherfiles
+    ]
+    logger.debug(f"{len(dirs)} directories to create")
+    if dirs:
+        fs.make_many_dirs(
+            [dirn.replace(source, destination) for dirn in dirs], exist_ok=True
+        )
+    allfiles = {a: v for a, v in allfiles.items() if v["type"] == "file"}
+    logger.debug(f"{len(allfiles)} files to consider for copy")
+    to_delete = [
+        o
+        for o, v in otherfiles.items()
+        if o.replace(destination, source) not in allfiles and v["type"] == "file"
+    ]
+    for k, v in allfiles.copy().items():
+        otherfile = k.replace(source, destination)
+        if otherfile in otherfiles:
+            if update_cond == "always":
+                allfiles[k] = otherfile
+            elif update_cond == "different":
+                inf1 = source_field(v) if callable(source_field) else v[source_field]
+                v2 = otherfiles[otherfile]
+                inf2 = dest_field(v2) if callable(dest_field) else v2[dest_field]
+                if inf1 != inf2:
+                    # details mismatch, make copy
+                    allfiles[k] = otherfile
+                else:
+                    # details match, don't copy
+                    allfiles.pop(k)
+        else:
+            # file not in target yet
+            allfiles[k] = otherfile
+    logger.debug(f"{len(allfiles)} files to copy")
+    if allfiles:
+        source_files, target_files = zip(*allfiles.items())
+        fs.cp(source_files, target_files, **kwargs)
+    logger.debug(f"{len(to_delete)} files to delete")
+    if delete_missing and to_delete:
+        fs.rm(to_delete)
+    return allfiles
+
+
+class GenericFileSystem(AsyncFileSystem):
+    """Wrapper over all other FS types
+
+    <experimental!>
+
+    This implementation is a single unified interface to be able to run FS operations
+    over generic URLs, and dispatch to the specific implementations using the URL
+    protocol prefix.
+
+    Note: instances of this FS are always async, even if you never use it with any async
+    backend.
+    """
+
+    protocol = "generic"  # there is no real reason to ever use a protocol with this FS
+
+    def __init__(self, default_method="default", storage_options=None, **kwargs):
+        """
+
+        Parameters
+        ----------
+        default_method: str (optional)
+            Defines how to configure backend FS instances. Options are:
+            - "default": instantiate like FSClass(), with no
+              extra arguments; this is the default instance of that FS, and can be
+              configured via the config system
+            - "generic": takes instances from the `_generic_fs` dict in this module,
+              which you must populate before use. Keys are by protocol
+            - "options": expects storage_options, a dict mapping protocol to
+              kwargs to use when constructing the filesystem
+            - "current": takes the most recently instantiated version of each FS
+        """
+        self.method = default_method
+        self.st_opts = storage_options
+        super().__init__(**kwargs)
+
+    def _parent(self, path):
+        fs = _resolve_fs(path, self.method, storage_options=self.st_opts)
+        return fs.unstrip_protocol(fs._parent(path))
+
+    def _strip_protocol(self, path):
+        # normalization only
+        fs = _resolve_fs(path, self.method, storage_options=self.st_opts)
+        return fs.unstrip_protocol(fs._strip_protocol(path))
+
+    async def _find(self, path, maxdepth=None, withdirs=False, detail=False, **kwargs):
+        fs = _resolve_fs(path, self.method, storage_options=self.st_opts)
+        if fs.async_impl:
+            out = await fs._find(
+                path, maxdepth=maxdepth, withdirs=withdirs, detail=True, **kwargs
+            )
+        else:
+            out = fs.find(
+                path, maxdepth=maxdepth, withdirs=withdirs, detail=True, **kwargs
+            )
+        result = {}
+        for k, v in out.items():
+            v = v.copy()  # don't corrupt target FS dircache
+            name = fs.unstrip_protocol(k)
+            v["name"] = name
+            result[name] = v
+        if detail:
+            return result
+        return list(result)
+
+    async def _info(self, url, **kwargs):
+        fs = _resolve_fs(url, self.method)
+        if fs.async_impl:
+            out = await fs._info(url, **kwargs)
+        else:
+            out = fs.info(url, **kwargs)
+        out = out.copy()  # don't edit originals
+        out["name"] = fs.unstrip_protocol(out["name"])
+        return out
+
+    async def _ls(
+        self,
+        url,
+        detail=True,
+        **kwargs,
+    ):
+        fs = _resolve_fs(url, self.method)
+        if fs.async_impl:
+            out = await fs._ls(url, detail=True, **kwargs)
+        else:
+            out = fs.ls(url, detail=True, **kwargs)
+        out = [o.copy() for o in out]  # don't edit originals
+        for o in out:
+            o["name"] = fs.unstrip_protocol(o["name"])
+        if detail:
+            return out
+        else:
+            return [o["name"] for o in out]
+
+    async def _cat_file(
+        self,
+        url,
+        **kwargs,
+    ):
+        fs = _resolve_fs(url, self.method)
+        if fs.async_impl:
+            return await fs._cat_file(url, **kwargs)
+        else:
+            return fs.cat_file(url, **kwargs)
+
+    async def _pipe_file(
+        self,
+        path,
+        value,
+        **kwargs,
+    ):
+        fs = _resolve_fs(path, self.method, storage_options=self.st_opts)
+        if fs.async_impl:
+            return await fs._pipe_file(path, value, **kwargs)
+        else:
+            return fs.pipe_file(path, value, **kwargs)
+
+    async def _rm(self, url, **kwargs):
+        urls = url
+        if isinstance(urls, str):
+            urls = [urls]
+        fs = _resolve_fs(urls[0], self.method)
+        if fs.async_impl:
+            await fs._rm(urls, **kwargs)
+        else:
+            fs.rm(url, **kwargs)
+
+    async def _makedirs(self, path, exist_ok=False):
+        logger.debug("Make dir %s", path)
+        fs = _resolve_fs(path, self.method, storage_options=self.st_opts)
+        if fs.async_impl:
+            await fs._makedirs(path, exist_ok=exist_ok)
+        else:
+            fs.makedirs(path, exist_ok=exist_ok)
+
+    def rsync(self, source, destination, **kwargs):
+        """Sync files between two directory trees
+
+        See `func:rsync` for more details.
+        """
+        rsync(source, destination, fs=self, **kwargs)
+
+    async def _cp_file(
+        self,
+        url,
+        url2,
+        blocksize=2**20,
+        callback=DEFAULT_CALLBACK,
+        tempdir: str | None = None,
+        **kwargs,
+    ):
+        fs = _resolve_fs(url, self.method)
+        fs2 = _resolve_fs(url2, self.method)
+        if fs is fs2:
+            # pure remote
+            if fs.async_impl:
+                return await fs._copy(url, url2, **kwargs)
+            else:
+                return fs.copy(url, url2, **kwargs)
+        await copy_file_op(fs, [url], fs2, [url2], tempdir, 1, on_error="raise")
+
+    async def _make_many_dirs(self, urls, exist_ok=True):
+        fs = _resolve_fs(urls[0], self.method)
+        if fs.async_impl:
+            coros = [fs._makedirs(u, exist_ok=exist_ok) for u in urls]
+            await _run_coros_in_chunks(coros)
+        else:
+            for u in urls:
+                fs.makedirs(u, exist_ok=exist_ok)
+
+    make_many_dirs = sync_wrapper(_make_many_dirs)
+
+    async def _copy(
+        self,
+        path1: list[str],
+        path2: list[str],
+        recursive: bool = False,
+        on_error: str = "ignore",
+        maxdepth: int | None = None,
+        batch_size: int | None = None,
+        tempdir: str | None = None,
+        **kwargs,
+    ):
+        # TODO: special case for one FS being local, which can use get/put
+        # TODO: special case for one being memFS, which can use cat/pipe
+        if recursive:
+            raise NotImplementedError("Please use fsspec.generic.rsync")
+        path1 = [path1] if isinstance(path1, str) else path1
+        path2 = [path2] if isinstance(path2, str) else path2
+
+        fs = _resolve_fs(path1, self.method)
+        fs2 = _resolve_fs(path2, self.method)
+
+        if fs is fs2:
+            if fs.async_impl:
+                return await fs._copy(path1, path2, **kwargs)
+            else:
+                return fs.copy(path1, path2, **kwargs)
+
+        await copy_file_op(
+            fs, path1, fs2, path2, tempdir, batch_size, on_error=on_error
+        )
+
+
+async def copy_file_op(
+    fs1, url1, fs2, url2, tempdir=None, batch_size=20, on_error="ignore"
+):
+    import tempfile
+
+    tempdir = tempdir or tempfile.mkdtemp()
+    try:
+        coros = [
+            _copy_file_op(
+                fs1,
+                u1,
+                fs2,
+                u2,
+                os.path.join(tempdir, uuid.uuid4().hex),
+            )
+            for u1, u2 in zip(url1, url2)
+        ]
+        out = await _run_coros_in_chunks(
+            coros, batch_size=batch_size, return_exceptions=True
+        )
+    finally:
+        shutil.rmtree(tempdir)
+    if on_error == "return":
+        return out
+    elif on_error == "raise":
+        for o in out:
+            if isinstance(o, Exception):
+                raise o
+
+
+async def _copy_file_op(fs1, url1, fs2, url2, local, on_error="ignore"):
+    if fs1.async_impl:
+        await fs1._get_file(url1, local)
+    else:
+        fs1.get_file(url1, local)
+    if fs2.async_impl:
+        await fs2._put_file(local, url2)
+    else:
+        fs2.put_file(local, url2)
+    os.unlink(local)
+    logger.debug("Copy %s -> %s; done", url1, url2)
+
+
+async def maybe_await(cor):
+    if inspect.iscoroutine(cor):
+        return await cor
+    else:
+        return cor

.venv/lib/python3.13/site-packages/fsspec/gui.py

@@ -0,0 +1,417 @@
+import ast
+import contextlib
+import logging
+import os
+import re
+from collections.abc import Sequence
+from typing import ClassVar
+
+import panel as pn
+
+from .core import OpenFile, get_filesystem_class, split_protocol
+from .registry import known_implementations
+
+pn.extension()
+logger = logging.getLogger("fsspec.gui")
+
+
+class SigSlot:
+    """Signal-slot mixin, for Panel event passing
+
+    Include this class in a widget manager's superclasses to be able to
+    register events and callbacks on Panel widgets managed by that class.
+
+    The method ``_register`` should be called as widgets are added, and external
+    code should call ``connect`` to associate callbacks.
+
+    By default, all signals emit a DEBUG logging statement.
+    """
+
+    # names of signals that this class may emit each of which must be
+    # set by _register for any new instance
+    signals: ClassVar[Sequence[str]] = []
+    # names of actions that this class may respond to
+    slots: ClassVar[Sequence[str]] = []
+
+    # each of which must be a method name
+
+    def __init__(self):
+        self._ignoring_events = False
+        self._sigs = {}
+        self._map = {}
+        self._setup()
+
+    def _setup(self):
+        """Create GUI elements and register signals"""
+        self.panel = pn.pane.PaneBase()
+        # no signals to set up in the base class
+
+    def _register(
+        self, widget, name, thing="value", log_level=logging.DEBUG, auto=False
+    ):
+        """Watch the given attribute of a widget and assign it a named event
+
+        This is normally called at the time a widget is instantiated, in the
+        class which owns it.
+
+        Parameters
+        ----------
+        widget : pn.layout.Panel or None
+            Widget to watch. If None, an anonymous signal not associated with
+            any widget.
+        name : str
+            Name of this event
+        thing : str
+            Attribute of the given widget to watch
+        log_level : int
+            When the signal is triggered, a logging event of the given level
+            will be fired in the dfviz logger.
+        auto : bool
+            If True, automatically connects with a method in this class of the
+            same name.
+        """
+        if name not in self.signals:
+            raise ValueError(f"Attempt to assign an undeclared signal: {name}")
+        self._sigs[name] = {
+            "widget": widget,
+            "callbacks": [],
+            "thing": thing,
+            "log": log_level,
+        }
+        wn = "-".join(
+            [
+                getattr(widget, "name", str(widget)) if widget is not None else "none",
+                thing,
+            ]
+        )
+        self._map[wn] = name
+        if widget is not None:
+            widget.param.watch(self._signal, thing, onlychanged=True)
+        if auto and hasattr(self, name):
+            self.connect(name, getattr(self, name))
+
+    def _repr_mimebundle_(self, *args, **kwargs):
+        """Display in a notebook or a server"""
+        try:
+            return self.panel._repr_mimebundle_(*args, **kwargs)
+        except (ValueError, AttributeError) as exc:
+            raise NotImplementedError(
+                "Panel does not seem to be set up properly"
+            ) from exc
+
+    def connect(self, signal, slot):
+        """Associate call back with given event
+
+        The callback must be a function which takes the "new" value of the
+        watched attribute as the only parameter. If the callback return False,
+        this cancels any further processing of the given event.
+
+        Alternatively, the callback can be a string, in which case it means
+        emitting the correspondingly-named event (i.e., connect to self)
+        """
+        self._sigs[signal]["callbacks"].append(slot)
+
+    def _signal(self, event):
+        """This is called by a an action on a widget
+
+        Within an self.ignore_events context, nothing happens.
+
+        Tests can execute this method by directly changing the values of
+        widget components.
+        """
+        if not self._ignoring_events:
+            wn = "-".join([event.obj.name, event.name])
+            if wn in self._map and self._map[wn] in self._sigs:
+                self._emit(self._map[wn], event.new)
+
+    @contextlib.contextmanager
+    def ignore_events(self):
+        """Temporarily turn off events processing in this instance
+
+        (does not propagate to children)
+        """
+        self._ignoring_events = True
+        try:
+            yield
+        finally:
+            self._ignoring_events = False
+
+    def _emit(self, sig, value=None):
+        """An event happened, call its callbacks
+
+        This method can be used in tests to simulate message passing without
+        directly changing visual elements.
+
+        Calling of callbacks will halt whenever one returns False.
+        """
+        logger.log(self._sigs[sig]["log"], f"{sig}: {value}")
+        for callback in self._sigs[sig]["callbacks"]:
+            if isinstance(callback, str):
+                self._emit(callback)
+            else:
+                try:
+                    # running callbacks should not break the interface
+                    ret = callback(value)
+                    if ret is False:
+                        break
+                except Exception as e:
+                    logger.exception(
+                        "Exception (%s) while executing callback for signal: %s",
+                        e,
+                        sig,
+                    )
+
+    def show(self, threads=False):
+        """Open a new browser tab and display this instance's interface"""
+        self.panel.show(threads=threads, verbose=False)
+        return self
+
+
+class SingleSelect(SigSlot):
+    """A multiselect which only allows you to select one item for an event"""
+
+    signals = ["_selected", "selected"]  # the first is internal
+    slots = ["set_options", "set_selection", "add", "clear", "select"]
+
+    def __init__(self, **kwargs):
+        self.kwargs = kwargs
+        super().__init__()
+
+    def _setup(self):
+        self.panel = pn.widgets.MultiSelect(**self.kwargs)
+        self._register(self.panel, "_selected", "value")
+        self._register(None, "selected")
+        self.connect("_selected", self.select_one)
+
+    def _signal(self, *args, **kwargs):
+        super()._signal(*args, **kwargs)
+
+    def select_one(self, *_):
+        with self.ignore_events():
+            val = [self.panel.value[-1]] if self.panel.value else []
+            self.panel.value = val
+        self._emit("selected", self.panel.value)
+
+    def set_options(self, options):
+        self.panel.options = options
+
+    def clear(self):
+        self.panel.options = []
+
+    @property
+    def value(self):
+        return self.panel.value
+
+    def set_selection(self, selection):
+        self.panel.value = [selection]
+
+
+class FileSelector(SigSlot):
+    """Panel-based graphical file selector widget
+
+    Instances of this widget are interactive and can be displayed in jupyter by having
+    them as the output of a cell,  or in a separate browser tab using ``.show()``.
+    """
+
+    signals = [
+        "protocol_changed",
+        "selection_changed",
+        "directory_entered",
+        "home_clicked",
+        "up_clicked",
+        "go_clicked",
+        "filters_changed",
+    ]
+    slots = ["set_filters", "go_home"]
+
+    def __init__(self, url=None, filters=None, ignore=None, kwargs=None):
+        """
+
+        Parameters
+        ----------
+        url : str (optional)
+            Initial value of the URL to populate the dialog; should include protocol
+        filters : list(str) (optional)
+            File endings to include in the listings. If not included, all files are
+            allowed. Does not affect directories.
+            If given, the endings will appear as checkboxes in the interface
+        ignore : list(str) (optional)
+            Regex(s) of file basename patterns to ignore, e.g., "\\." for typical
+            hidden files on posix
+        kwargs : dict (optional)
+            To pass to file system instance
+        """
+        if url:
+            self.init_protocol, url = split_protocol(url)
+        else:
+            self.init_protocol, url = "file", os.getcwd()
+        self.init_url = url
+        self.init_kwargs = (kwargs if isinstance(kwargs, str) else str(kwargs)) or "{}"
+        self.filters = filters
+        self.ignore = [re.compile(i) for i in ignore or []]
+        self._fs = None
+        super().__init__()
+
+    def _setup(self):
+        self.url = pn.widgets.TextInput(
+            name="url",
+            value=self.init_url,
+            align="end",
+            sizing_mode="stretch_width",
+            width_policy="max",
+        )
+        self.protocol = pn.widgets.Select(
+            options=sorted(known_implementations),
+            value=self.init_protocol,
+            name="protocol",
+            align="center",
+        )
+        self.kwargs = pn.widgets.TextInput(
+            name="kwargs", value=self.init_kwargs, align="center"
+        )
+        self.go = pn.widgets.Button(name="⇨", align="end", width=45)
+        self.main = SingleSelect(size=10)
+        self.home = pn.widgets.Button(name="🏠", width=40, height=30, align="end")
+        self.up = pn.widgets.Button(name="‹", width=30, height=30, align="end")
+
+        self._register(self.protocol, "protocol_changed", auto=True)
+        self._register(self.go, "go_clicked", "clicks", auto=True)
+        self._register(self.up, "up_clicked", "clicks", auto=True)
+        self._register(self.home, "home_clicked", "clicks", auto=True)
+        self._register(None, "selection_changed")
+        self.main.connect("selected", self.selection_changed)
+        self._register(None, "directory_entered")
+        self.prev_protocol = self.protocol.value
+        self.prev_kwargs = self.storage_options
+
+        self.filter_sel = pn.widgets.CheckBoxGroup(
+            value=[], options=[], inline=False, align="end", width_policy="min"
+        )
+        self._register(self.filter_sel, "filters_changed", auto=True)
+
+        self.panel = pn.Column(
+            pn.Row(self.protocol, self.kwargs),
+            pn.Row(self.home, self.up, self.url, self.go, self.filter_sel),
+            self.main.panel,
+        )
+        self.set_filters(self.filters)
+        self.go_clicked()
+
+    def set_filters(self, filters=None):
+        self.filters = filters
+        if filters:
+            self.filter_sel.options = filters
+            self.filter_sel.value = filters
+        else:
+            self.filter_sel.options = []
+            self.filter_sel.value = []
+
+    @property
+    def storage_options(self):
+        """Value of the kwargs box as a dictionary"""
+        return ast.literal_eval(self.kwargs.value) or {}
+
+    @property
+    def fs(self):
+        """Current filesystem instance"""
+        if self._fs is None:
+            cls = get_filesystem_class(self.protocol.value)
+            self._fs = cls(**self.storage_options)
+        return self._fs
+
+    @property
+    def urlpath(self):
+        """URL of currently selected item"""
+        return (
+            (f"{self.protocol.value}://{self.main.value[0]}")
+            if self.main.value
+            else None
+        )
+
+    def open_file(self, mode="rb", compression=None, encoding=None):
+        """Create OpenFile instance for the currently selected item
+
+        For example, in a notebook you might do something like
+
+        .. code-block::
+
+            [ ]: sel = FileSelector(); sel
+
+            # user selects their file
+
+            [ ]: with sel.open_file('rb') as f:
+            ...      out = f.read()
+
+        Parameters
+        ----------
+        mode: str (optional)
+            Open mode for the file.
+        compression: str (optional)
+            The interact with the file as compressed. Set to 'infer' to guess
+            compression from the file ending
+        encoding: str (optional)
+            If using text mode, use this encoding; defaults to UTF8.
+        """
+        if self.urlpath is None:
+            raise ValueError("No file selected")
+        return OpenFile(self.fs, self.urlpath, mode, compression, encoding)
+
+    def filters_changed(self, values):
+        self.filters = values
+        self.go_clicked()
+
+    def selection_changed(self, *_):
+        if self.urlpath is None:
+            return
+        if self.fs.isdir(self.urlpath):
+            self.url.value = self.fs._strip_protocol(self.urlpath)
+        self.go_clicked()
+
+    def go_clicked(self, *_):
+        if (
+            self.prev_protocol != self.protocol.value
+            or self.prev_kwargs != self.storage_options
+        ):
+            self._fs = None  # causes fs to be recreated
+            self.prev_protocol = self.protocol.value
+            self.prev_kwargs = self.storage_options
+        listing = sorted(
+            self.fs.ls(self.url.value, detail=True), key=lambda x: x["name"]
+        )
+        listing = [
+            l
+            for l in listing
+            if not any(i.match(l["name"].rsplit("/", 1)[-1]) for i in self.ignore)
+        ]
+        folders = {
+            "📁 " + o["name"].rsplit("/", 1)[-1]: o["name"]
+            for o in listing
+            if o["type"] == "directory"
+        }
+        files = {
+            "📄 " + o["name"].rsplit("/", 1)[-1]: o["name"]
+            for o in listing
+            if o["type"] == "file"
+        }
+        if self.filters:
+            files = {
+                k: v
+                for k, v in files.items()
+                if any(v.endswith(ext) for ext in self.filters)
+            }
+        self.main.set_options(dict(**folders, **files))
+
+    def protocol_changed(self, *_):
+        self._fs = None
+        self.main.options = []
+        self.url.value = ""
+
+    def home_clicked(self, *_):
+        self.protocol.value = self.init_protocol
+        self.kwargs.value = self.init_kwargs
+        self.url.value = self.init_url
+        self.go_clicked()
+
+    def up_clicked(self, *_):
+        self.url.value = self.fs._parent(self.url.value)
+        self.go_clicked()

.venv/lib/python3.13/site-packages/fsspec/mapping.py

@@ -0,0 +1,251 @@
+import array
+import logging
+import posixpath
+import warnings
+from collections.abc import MutableMapping
+from functools import cached_property
+
+from fsspec.core import url_to_fs
+
+logger = logging.getLogger("fsspec.mapping")
+
+
+class FSMap(MutableMapping):
+    """Wrap a FileSystem instance as a mutable wrapping.
+
+    The keys of the mapping become files under the given root, and the
+    values (which must be bytes) the contents of those files.
+
+    Parameters
+    ----------
+    root: string
+        prefix for all the files
+    fs: FileSystem instance
+    check: bool (=True)
+        performs a touch at the location, to check for write access.
+
+    Examples
+    --------
+    >>> fs = FileSystem(**parameters)  # doctest: +SKIP
+    >>> d = FSMap('my-data/path/', fs)  # doctest: +SKIP
+    or, more likely
+    >>> d = fs.get_mapper('my-data/path/')
+
+    >>> d['loc1'] = b'Hello World'  # doctest: +SKIP
+    >>> list(d.keys())  # doctest: +SKIP
+    ['loc1']
+    >>> d['loc1']  # doctest: +SKIP
+    b'Hello World'
+    """
+
+    def __init__(self, root, fs, check=False, create=False, missing_exceptions=None):
+        self.fs = fs
+        self.root = fs._strip_protocol(root)
+        self._root_key_to_str = fs._strip_protocol(posixpath.join(root, "x"))[:-1]
+        if missing_exceptions is None:
+            missing_exceptions = (
+                FileNotFoundError,
+                IsADirectoryError,
+                NotADirectoryError,
+            )
+        self.missing_exceptions = missing_exceptions
+        self.check = check
+        self.create = create
+        if create:
+            if not self.fs.exists(root):
+                self.fs.mkdir(root)
+        if check:
+            if not self.fs.exists(root):
+                raise ValueError(
+                    f"Path {root} does not exist. Create "
+                    f" with the ``create=True`` keyword"
+                )
+            self.fs.touch(root + "/a")
+            self.fs.rm(root + "/a")
+
+    @cached_property
+    def dirfs(self):
+        """dirfs instance that can be used with the same keys as the mapper"""
+        from .implementations.dirfs import DirFileSystem
+
+        return DirFileSystem(path=self._root_key_to_str, fs=self.fs)
+
+    def clear(self):
+        """Remove all keys below root - empties out mapping"""
+        logger.info("Clear mapping at %s", self.root)
+        try:
+            self.fs.rm(self.root, True)
+            self.fs.mkdir(self.root)
+        except:  # noqa: E722
+            pass
+
+    def getitems(self, keys, on_error="raise"):
+        """Fetch multiple items from the store
+
+        If the backend is async-able, this might proceed concurrently
+
+        Parameters
+        ----------
+        keys: list(str)
+            They keys to be fetched
+        on_error : "raise", "omit", "return"
+            If raise, an underlying exception will be raised (converted to KeyError
+            if the type is in self.missing_exceptions); if omit, keys with exception
+            will simply not be included in the output; if "return", all keys are
+            included in the output, but the value will be bytes or an exception
+            instance.
+
+        Returns
+        -------
+        dict(key, bytes|exception)
+        """
+        keys2 = [self._key_to_str(k) for k in keys]
+        oe = on_error if on_error == "raise" else "return"
+        try:
+            out = self.fs.cat(keys2, on_error=oe)
+            if isinstance(out, bytes):
+                out = {keys2[0]: out}
+        except self.missing_exceptions as e:
+            raise KeyError from e
+        out = {
+            k: (KeyError() if isinstance(v, self.missing_exceptions) else v)
+            for k, v in out.items()
+        }
+        return {
+            key: out[k2] if on_error == "raise" else out.get(k2, KeyError(k2))
+            for key, k2 in zip(keys, keys2)
+            if on_error == "return" or not isinstance(out[k2], BaseException)
+        }
+
+    def setitems(self, values_dict):
+        """Set the values of multiple items in the store
+
+        Parameters
+        ----------
+        values_dict: dict(str, bytes)
+        """
+        values = {self._key_to_str(k): maybe_convert(v) for k, v in values_dict.items()}
+        self.fs.pipe(values)
+
+    def delitems(self, keys):
+        """Remove multiple keys from the store"""
+        self.fs.rm([self._key_to_str(k) for k in keys])
+
+    def _key_to_str(self, key):
+        """Generate full path for the key"""
+        if not isinstance(key, str):
+            # raise TypeError("key must be of type `str`, got `{type(key).__name__}`"
+            warnings.warn(
+                "from fsspec 2023.5 onward FSMap non-str keys will raise TypeError",
+                DeprecationWarning,
+            )
+            if isinstance(key, list):
+                key = tuple(key)
+            key = str(key)
+        return f"{self._root_key_to_str}{key}".rstrip("/")
+
+    def _str_to_key(self, s):
+        """Strip path of to leave key name"""
+        return s[len(self.root) :].lstrip("/")
+
+    def __getitem__(self, key, default=None):
+        """Retrieve data"""
+        k = self._key_to_str(key)
+        try:
+            result = self.fs.cat(k)
+        except self.missing_exceptions as exc:
+            if default is not None:
+                return default
+            raise KeyError(key) from exc
+        return result
+
+    def pop(self, key, default=None):
+        """Pop data"""
+        result = self.__getitem__(key, default)
+        try:
+            del self[key]
+        except KeyError:
+            pass
+        return result
+
+    def __setitem__(self, key, value):
+        """Store value in key"""
+        key = self._key_to_str(key)
+        self.fs.mkdirs(self.fs._parent(key), exist_ok=True)
+        self.fs.pipe_file(key, maybe_convert(value))
+
+    def __iter__(self):
+        return (self._str_to_key(x) for x in self.fs.find(self.root))
+
+    def __len__(self):
+        return len(self.fs.find(self.root))
+
+    def __delitem__(self, key):
+        """Remove key"""
+        try:
+            self.fs.rm(self._key_to_str(key))
+        except Exception as exc:
+            raise KeyError from exc
+
+    def __contains__(self, key):
+        """Does key exist in mapping?"""
+        path = self._key_to_str(key)
+        return self.fs.isfile(path)
+
+    def __reduce__(self):
+        return FSMap, (self.root, self.fs, False, False, self.missing_exceptions)
+
+
+def maybe_convert(value):
+    if isinstance(value, array.array) or hasattr(value, "__array__"):
+        # bytes-like things
+        if hasattr(value, "dtype") and value.dtype.kind in "Mm":
+            # The buffer interface doesn't support datetime64/timdelta64 numpy
+            # arrays
+            value = value.view("int64")
+        value = bytes(memoryview(value))
+    return value
+
+
+def get_mapper(
+    url="",
+    check=False,
+    create=False,
+    missing_exceptions=None,
+    alternate_root=None,
+    **kwargs,
+):
+    """Create key-value interface for given URL and options
+
+    The URL will be of the form "protocol://location" and point to the root
+    of the mapper required. All keys will be file-names below this location,
+    and their values the contents of each key.
+
+    Also accepts compound URLs like zip::s3://bucket/file.zip , see ``fsspec.open``.
+
+    Parameters
+    ----------
+    url: str
+        Root URL of mapping
+    check: bool
+        Whether to attempt to read from the location before instantiation, to
+        check that the mapping does exist
+    create: bool
+        Whether to make the directory corresponding to the root before
+        instantiating
+    missing_exceptions: None or tuple
+        If given, these exception types will be regarded as missing keys and
+        return KeyError when trying to read data. By default, you get
+        (FileNotFoundError, IsADirectoryError, NotADirectoryError)
+    alternate_root: None or str
+        In cases of complex URLs, the parser may fail to pick the correct part
+        for the mapper root, so this arg can override
+
+    Returns
+    -------
+    ``FSMap`` instance, the dict-like key-value store.
+    """
+    # Removing protocol here - could defer to each open() on the backend
+    fs, urlpath = url_to_fs(url, **kwargs)
+    root = alternate_root if alternate_root is not None else urlpath
+    return FSMap(root, fs, check, create, missing_exceptions=missing_exceptions)

.venv/lib/python3.13/site-packages/fsspec/parquet.py

@@ -0,0 +1,541 @@
+import io
+import json
+import warnings
+
+from .core import url_to_fs
+from .utils import merge_offset_ranges
+
+# Parquet-Specific Utilities for fsspec
+#
+# Most of the functions defined in this module are NOT
+# intended for public consumption. The only exception
+# to this is `open_parquet_file`, which should be used
+# place of `fs.open()` to open parquet-formatted files
+# on remote file systems.
+
+
+def open_parquet_file(
+    path,
+    mode="rb",
+    fs=None,
+    metadata=None,
+    columns=None,
+    row_groups=None,
+    storage_options=None,
+    strict=False,
+    engine="auto",
+    max_gap=64_000,
+    max_block=256_000_000,
+    footer_sample_size=1_000_000,
+    **kwargs,
+):
+    """
+    Return a file-like object for a single Parquet file.
+
+    The specified parquet `engine` will be used to parse the
+    footer metadata, and determine the required byte ranges
+    from the file. The target path will then be opened with
+    the "parts" (`KnownPartsOfAFile`) caching strategy.
+
+    Note that this method is intended for usage with remote
+    file systems, and is unlikely to improve parquet-read
+    performance on local file systems.
+
+    Parameters
+    ----------
+    path: str
+        Target file path.
+    mode: str, optional
+        Mode option to be passed through to `fs.open`. Default is "rb".
+    metadata: Any, optional
+        Parquet metadata object. Object type must be supported
+        by the backend parquet engine. For now, only the "fastparquet"
+        engine supports an explicit `ParquetFile` metadata object.
+        If a metadata object is supplied, the remote footer metadata
+        will not need to be transferred into local memory.
+    fs: AbstractFileSystem, optional
+        Filesystem object to use for opening the file. If nothing is
+        specified, an `AbstractFileSystem` object will be inferred.
+    engine : str, default "auto"
+        Parquet engine to use for metadata parsing. Allowed options
+        include "fastparquet", "pyarrow", and "auto". The specified
+        engine must be installed in the current environment. If
+        "auto" is specified, and both engines are installed,
+        "fastparquet" will take precedence over "pyarrow".
+    columns: list, optional
+        List of all column names that may be read from the file.
+    row_groups : list, optional
+        List of all row-groups that may be read from the file. This
+        may be a list of row-group indices (integers), or it may be
+        a list of `RowGroup` metadata objects (if the "fastparquet"
+        engine is used).
+    storage_options : dict, optional
+        Used to generate an `AbstractFileSystem` object if `fs` was
+        not specified.
+    strict : bool, optional
+        Whether the resulting `KnownPartsOfAFile` cache should
+        fetch reads that go beyond a known byte-range boundary.
+        If `False` (the default), any read that ends outside a
+        known part will be zero padded. Note that using
+        `strict=True` may be useful for debugging.
+    max_gap : int, optional
+        Neighboring byte ranges will only be merged when their
+        inter-range gap is <= `max_gap`. Default is 64KB.
+    max_block : int, optional
+        Neighboring byte ranges will only be merged when the size of
+        the aggregated range is <= `max_block`. Default is 256MB.
+    footer_sample_size : int, optional
+        Number of bytes to read from the end of the path to look
+        for the footer metadata. If the sampled bytes do not contain
+        the footer, a second read request will be required, and
+        performance will suffer. Default is 1MB.
+    **kwargs :
+        Optional key-word arguments to pass to `fs.open`
+    """
+
+    # Make sure we have an `AbstractFileSystem` object
+    # to work with
+    if fs is None:
+        fs = url_to_fs(path, **(storage_options or {}))[0]
+
+    # For now, `columns == []` not supported. Just use
+    # default `open` command with `path` input
+    if columns is not None and len(columns) == 0:
+        return fs.open(path, mode=mode)
+
+    # Set the engine
+    engine = _set_engine(engine)
+
+    # Fetch the known byte ranges needed to read
+    # `columns` and/or `row_groups`
+    data = _get_parquet_byte_ranges(
+        [path],
+        fs,
+        metadata=metadata,
+        columns=columns,
+        row_groups=row_groups,
+        engine=engine,
+        max_gap=max_gap,
+        max_block=max_block,
+        footer_sample_size=footer_sample_size,
+    )
+
+    # Extract file name from `data`
+    fn = next(iter(data)) if data else path
+
+    # Call self.open with "parts" caching
+    options = kwargs.pop("cache_options", {}).copy()
+    return fs.open(
+        fn,
+        mode=mode,
+        cache_type="parts",
+        cache_options={
+            **options,
+            "data": data.get(fn, {}),
+            "strict": strict,
+        },
+        **kwargs,
+    )
+
+
+def _get_parquet_byte_ranges(
+    paths,
+    fs,
+    metadata=None,
+    columns=None,
+    row_groups=None,
+    max_gap=64_000,
+    max_block=256_000_000,
+    footer_sample_size=1_000_000,
+    engine="auto",
+):
+    """Get a dictionary of the known byte ranges needed
+    to read a specific column/row-group selection from a
+    Parquet dataset. Each value in the output dictionary
+    is intended for use as the `data` argument for the
+    `KnownPartsOfAFile` caching strategy of a single path.
+    """
+
+    # Set engine if necessary
+    if isinstance(engine, str):
+        engine = _set_engine(engine)
+
+    # Pass to specialized function if metadata is defined
+    if metadata is not None:
+        # Use the provided parquet metadata object
+        # to avoid transferring/parsing footer metadata
+        return _get_parquet_byte_ranges_from_metadata(
+            metadata,
+            fs,
+            engine,
+            columns=columns,
+            row_groups=row_groups,
+            max_gap=max_gap,
+            max_block=max_block,
+        )
+
+    # Get file sizes asynchronously
+    file_sizes = fs.sizes(paths)
+
+    # Populate global paths, starts, & ends
+    result = {}
+    data_paths = []
+    data_starts = []
+    data_ends = []
+    add_header_magic = True
+    if columns is None and row_groups is None:
+        # We are NOT selecting specific columns or row-groups.
+        #
+        # We can avoid sampling the footers, and just transfer
+        # all file data with cat_ranges
+        for i, path in enumerate(paths):
+            result[path] = {}
+            for b in range(0, file_sizes[i], max_block):
+                data_paths.append(path)
+                data_starts.append(b)
+                data_ends.append(min(b + max_block, file_sizes[i]))
+        add_header_magic = False  # "Magic" should already be included
+    else:
+        # We ARE selecting specific columns or row-groups.
+        #
+        # Gather file footers.
+        # We just take the last `footer_sample_size` bytes of each
+        # file (or the entire file if it is smaller than that)
+        footer_starts = []
+        footer_ends = []
+        for i, path in enumerate(paths):
+            footer_ends.append(file_sizes[i])
+            sample_size = max(0, file_sizes[i] - footer_sample_size)
+            footer_starts.append(sample_size)
+        footer_samples = fs.cat_ranges(paths, footer_starts, footer_ends)
+
+        # Check our footer samples and re-sample if necessary.
+        missing_footer_starts = footer_starts.copy()
+        large_footer = 0
+        for i, path in enumerate(paths):
+            footer_size = int.from_bytes(footer_samples[i][-8:-4], "little")
+            real_footer_start = file_sizes[i] - (footer_size + 8)
+            if real_footer_start < footer_starts[i]:
+                missing_footer_starts[i] = real_footer_start
+                large_footer = max(large_footer, (footer_size + 8))
+        if large_footer:
+            warnings.warn(
+                f"Not enough data was used to sample the parquet footer. "
+                f"Try setting footer_sample_size >= {large_footer}."
+            )
+            for i, block in enumerate(
+                fs.cat_ranges(
+                    paths,
+                    missing_footer_starts,
+                    footer_starts,
+                )
+            ):
+                footer_samples[i] = block + footer_samples[i]
+                footer_starts[i] = missing_footer_starts[i]
+
+        # Calculate required byte ranges for each path
+        for i, path in enumerate(paths):
+            # Deal with small-file case.
+            # Just include all remaining bytes of the file
+            # in a single range.
+            if file_sizes[i] < max_block:
+                if footer_starts[i] > 0:
+                    # Only need to transfer the data if the
+                    # footer sample isn't already the whole file
+                    data_paths.append(path)
+                    data_starts.append(0)
+                    data_ends.append(footer_starts[i])
+                continue
+
+            # Use "engine" to collect data byte ranges
+            path_data_starts, path_data_ends = engine._parquet_byte_ranges(
+                columns,
+                row_groups=row_groups,
+                footer=footer_samples[i],
+                footer_start=footer_starts[i],
+            )
+
+            data_paths += [path] * len(path_data_starts)
+            data_starts += path_data_starts
+            data_ends += path_data_ends
+
+        # Merge adjacent offset ranges
+        data_paths, data_starts, data_ends = merge_offset_ranges(
+            data_paths,
+            data_starts,
+            data_ends,
+            max_gap=max_gap,
+            max_block=max_block,
+            sort=False,  # Should already be sorted
+        )
+
+        # Start by populating `result` with footer samples
+        for i, path in enumerate(paths):
+            result[path] = {(footer_starts[i], footer_ends[i]): footer_samples[i]}
+
+    # Transfer the data byte-ranges into local memory
+    _transfer_ranges(fs, result, data_paths, data_starts, data_ends)
+
+    # Add b"PAR1" to header if necessary
+    if add_header_magic:
+        _add_header_magic(result)
+
+    return result
+
+
+def _get_parquet_byte_ranges_from_metadata(
+    metadata,
+    fs,
+    engine,
+    columns=None,
+    row_groups=None,
+    max_gap=64_000,
+    max_block=256_000_000,
+):
+    """Simplified version of `_get_parquet_byte_ranges` for
+    the case that an engine-specific `metadata` object is
+    provided, and the remote footer metadata does not need to
+    be transferred before calculating the required byte ranges.
+    """
+
+    # Use "engine" to collect data byte ranges
+    data_paths, data_starts, data_ends = engine._parquet_byte_ranges(
+        columns,
+        row_groups=row_groups,
+        metadata=metadata,
+    )
+
+    # Merge adjacent offset ranges
+    data_paths, data_starts, data_ends = merge_offset_ranges(
+        data_paths,
+        data_starts,
+        data_ends,
+        max_gap=max_gap,
+        max_block=max_block,
+        sort=False,  # Should be sorted
+    )
+
+    # Transfer the data byte-ranges into local memory
+    result = {fn: {} for fn in list(set(data_paths))}
+    _transfer_ranges(fs, result, data_paths, data_starts, data_ends)
+
+    # Add b"PAR1" to header
+    _add_header_magic(result)
+
+    return result
+
+
+def _transfer_ranges(fs, blocks, paths, starts, ends):
+    # Use cat_ranges to gather the data byte_ranges
+    ranges = (paths, starts, ends)
+    for path, start, stop, data in zip(*ranges, fs.cat_ranges(*ranges)):
+        blocks[path][(start, stop)] = data
+
+
+def _add_header_magic(data):
+    # Add b"PAR1" to file headers
+    for path in list(data.keys()):
+        add_magic = True
+        for k in data[path]:
+            if k[0] == 0 and k[1] >= 4:
+                add_magic = False
+                break
+        if add_magic:
+            data[path][(0, 4)] = b"PAR1"
+
+
+def _set_engine(engine_str):
+    # Define a list of parquet engines to try
+    if engine_str == "auto":
+        try_engines = ("fastparquet", "pyarrow")
+    elif not isinstance(engine_str, str):
+        raise ValueError(
+            "Failed to set parquet engine! "
+            "Please pass 'fastparquet', 'pyarrow', or 'auto'"
+        )
+    elif engine_str not in ("fastparquet", "pyarrow"):
+        raise ValueError(f"{engine_str} engine not supported by `fsspec.parquet`")
+    else:
+        try_engines = [engine_str]
+
+    # Try importing the engines in `try_engines`,
+    # and choose the first one that succeeds
+    for engine in try_engines:
+        try:
+            if engine == "fastparquet":
+                return FastparquetEngine()
+            elif engine == "pyarrow":
+                return PyarrowEngine()
+        except ImportError:
+            pass
+
+    # Raise an error if a supported parquet engine
+    # was not found
+    raise ImportError(
+        f"The following parquet engines are not installed "
+        f"in your python environment: {try_engines}."
+        f"Please install 'fastparquert' or 'pyarrow' to "
+        f"utilize the `fsspec.parquet` module."
+    )
+
+
+class FastparquetEngine:
+    # The purpose of the FastparquetEngine class is
+    # to check if fastparquet can be imported (on initialization)
+    # and to define a `_parquet_byte_ranges` method. In the
+    # future, this class may also be used to define other
+    # methods/logic that are specific to fastparquet.
+
+    def __init__(self):
+        import fastparquet as fp
+
+        self.fp = fp
+
+    def _row_group_filename(self, row_group, pf):
+        return pf.row_group_filename(row_group)
+
+    def _parquet_byte_ranges(
+        self,
+        columns,
+        row_groups=None,
+        metadata=None,
+        footer=None,
+        footer_start=None,
+    ):
+        # Initialize offset ranges and define ParqetFile metadata
+        pf = metadata
+        data_paths, data_starts, data_ends = [], [], []
+        if pf is None:
+            pf = self.fp.ParquetFile(io.BytesIO(footer))
+
+        # Convert columns to a set and add any index columns
+        # specified in the pandas metadata (just in case)
+        column_set = None if columns is None else set(columns)
+        if column_set is not None and hasattr(pf, "pandas_metadata"):
+            md_index = [
+                ind
+                for ind in pf.pandas_metadata.get("index_columns", [])
+                # Ignore RangeIndex information
+                if not isinstance(ind, dict)
+            ]
+            column_set |= set(md_index)
+
+        # Check if row_groups is a list of integers
+        # or a list of row-group metadata
+        if row_groups and not isinstance(row_groups[0], int):
+            # Input row_groups contains row-group metadata
+            row_group_indices = None
+        else:
+            # Input row_groups contains row-group indices
+            row_group_indices = row_groups
+            row_groups = pf.row_groups
+
+        # Loop through column chunks to add required byte ranges
+        for r, row_group in enumerate(row_groups):
+            # Skip this row-group if we are targeting
+            # specific row-groups
+            if row_group_indices is None or r in row_group_indices:
+                # Find the target parquet-file path for `row_group`
+                fn = self._row_group_filename(row_group, pf)
+
+                for column in row_group.columns:
+                    name = column.meta_data.path_in_schema[0]
+                    # Skip this column if we are targeting a
+                    # specific columns
+                    if column_set is None or name in column_set:
+                        file_offset0 = column.meta_data.dictionary_page_offset
+                        if file_offset0 is None:
+                            file_offset0 = column.meta_data.data_page_offset
+                        num_bytes = column.meta_data.total_compressed_size
+                        if footer_start is None or file_offset0 < footer_start:
+                            data_paths.append(fn)
+                            data_starts.append(file_offset0)
+                            data_ends.append(
+                                min(
+                                    file_offset0 + num_bytes,
+                                    footer_start or (file_offset0 + num_bytes),
+                                )
+                            )
+
+        if metadata:
+            # The metadata in this call may map to multiple
+            # file paths. Need to include `data_paths`
+            return data_paths, data_starts, data_ends
+        return data_starts, data_ends
+
+
+class PyarrowEngine:
+    # The purpose of the PyarrowEngine class is
+    # to check if pyarrow can be imported (on initialization)
+    # and to define a `_parquet_byte_ranges` method. In the
+    # future, this class may also be used to define other
+    # methods/logic that are specific to pyarrow.
+
+    def __init__(self):
+        import pyarrow.parquet as pq
+
+        self.pq = pq
+
+    def _row_group_filename(self, row_group, metadata):
+        raise NotImplementedError
+
+    def _parquet_byte_ranges(
+        self,
+        columns,
+        row_groups=None,
+        metadata=None,
+        footer=None,
+        footer_start=None,
+    ):
+        if metadata is not None:
+            raise ValueError("metadata input not supported for PyarrowEngine")
+
+        data_starts, data_ends = [], []
+        md = self.pq.ParquetFile(io.BytesIO(footer)).metadata
+
+        # Convert columns to a set and add any index columns
+        # specified in the pandas metadata (just in case)
+        column_set = None if columns is None else set(columns)
+        if column_set is not None:
+            schema = md.schema.to_arrow_schema()
+            has_pandas_metadata = (
+                schema.metadata is not None and b"pandas" in schema.metadata
+            )
+            if has_pandas_metadata:
+                md_index = [
+                    ind
+                    for ind in json.loads(
+                        schema.metadata[b"pandas"].decode("utf8")
+                    ).get("index_columns", [])
+                    # Ignore RangeIndex information
+                    if not isinstance(ind, dict)
+                ]
+                column_set |= set(md_index)
+
+        # Loop through column chunks to add required byte ranges
+        for r in range(md.num_row_groups):
+            # Skip this row-group if we are targeting
+            # specific row-groups
+            if row_groups is None or r in row_groups:
+                row_group = md.row_group(r)
+                for c in range(row_group.num_columns):
+                    column = row_group.column(c)
+                    name = column.path_in_schema
+                    # Skip this column if we are targeting a
+                    # specific columns
+                    split_name = name.split(".")[0]
+                    if (
+                        column_set is None
+                        or name in column_set
+                        or split_name in column_set
+                    ):
+                        file_offset0 = column.dictionary_page_offset
+                        if file_offset0 is None:
+                            file_offset0 = column.data_page_offset
+                        num_bytes = column.total_compressed_size
+                        if file_offset0 < footer_start:
+                            data_starts.append(file_offset0)
+                            data_ends.append(
+                                min(file_offset0 + num_bytes, footer_start)
+                            )
+        return data_starts, data_ends

.venv/lib/python3.13/site-packages/fsspec/registry.py

@@ -0,0 +1,330 @@
+from __future__ import annotations
+
+import importlib
+import types
+import warnings
+
+__all__ = ["registry", "get_filesystem_class", "default"]
+
+# internal, mutable
+_registry: dict[str, type] = {}
+
+# external, immutable
+registry = types.MappingProxyType(_registry)
+default = "file"
+
+
+def register_implementation(name, cls, clobber=False, errtxt=None):
+    """Add implementation class to the registry
+
+    Parameters
+    ----------
+    name: str
+        Protocol name to associate with the class
+    cls: class or str
+        if a class: fsspec-compliant implementation class (normally inherits from
+        ``fsspec.AbstractFileSystem``, gets added straight to the registry. If a
+        str, the full path to an implementation class like package.module.class,
+        which gets added to known_implementations,
+        so the import is deferred until the filesystem is actually used.
+    clobber: bool (optional)
+        Whether to overwrite a protocol with the same name; if False, will raise
+        instead.
+    errtxt: str (optional)
+        If given, then a failure to import the given class will result in this
+        text being given.
+    """
+    if isinstance(cls, str):
+        if name in known_implementations and clobber is False:
+            if cls != known_implementations[name]["class"]:
+                raise ValueError(
+                    f"Name ({name}) already in the known_implementations and clobber "
+                    f"is False"
+                )
+        else:
+            known_implementations[name] = {
+                "class": cls,
+                "err": errtxt or f"{cls} import failed for protocol {name}",
+            }
+
+    else:
+        if name in registry and clobber is False:
+            if _registry[name] is not cls:
+                raise ValueError(
+                    f"Name ({name}) already in the registry and clobber is False"
+                )
+        else:
+            _registry[name] = cls
+
+
+# protocols mapped to the class which implements them. This dict can be
+# updated with register_implementation
+known_implementations = {
+    "abfs": {
+        "class": "adlfs.AzureBlobFileSystem",
+        "err": "Install adlfs to access Azure Datalake Gen2 and Azure Blob Storage",
+    },
+    "adl": {
+        "class": "adlfs.AzureDatalakeFileSystem",
+        "err": "Install adlfs to access Azure Datalake Gen1",
+    },
+    "arrow_hdfs": {
+        "class": "fsspec.implementations.arrow.HadoopFileSystem",
+        "err": "pyarrow and local java libraries required for HDFS",
+    },
+    "asynclocal": {
+        "class": "morefs.asyn_local.AsyncLocalFileSystem",
+        "err": "Install 'morefs[asynclocalfs]' to use AsyncLocalFileSystem",
+    },
+    "asyncwrapper": {
+        "class": "fsspec.implementations.asyn_wrapper.AsyncFileSystemWrapper",
+    },
+    "az": {
+        "class": "adlfs.AzureBlobFileSystem",
+        "err": "Install adlfs to access Azure Datalake Gen2 and Azure Blob Storage",
+    },
+    "blockcache": {"class": "fsspec.implementations.cached.CachingFileSystem"},
+    "box": {
+        "class": "boxfs.BoxFileSystem",
+        "err": "Please install boxfs to access BoxFileSystem",
+    },
+    "cached": {"class": "fsspec.implementations.cached.CachingFileSystem"},
+    "dask": {
+        "class": "fsspec.implementations.dask.DaskWorkerFileSystem",
+        "err": "Install dask distributed to access worker file system",
+    },
+    "data": {"class": "fsspec.implementations.data.DataFileSystem"},
+    "dbfs": {
+        "class": "fsspec.implementations.dbfs.DatabricksFileSystem",
+        "err": "Install the requests package to use the DatabricksFileSystem",
+    },
+    "dir": {"class": "fsspec.implementations.dirfs.DirFileSystem"},
+    "dropbox": {
+        "class": "dropboxdrivefs.DropboxDriveFileSystem",
+        "err": (
+            'DropboxFileSystem requires "dropboxdrivefs","requests" and "'
+            '"dropbox" to be installed'
+        ),
+    },
+    "dvc": {
+        "class": "dvc.api.DVCFileSystem",
+        "err": "Install dvc to access DVCFileSystem",
+    },
+    "file": {"class": "fsspec.implementations.local.LocalFileSystem"},
+    "filecache": {"class": "fsspec.implementations.cached.WholeFileCacheFileSystem"},
+    "ftp": {"class": "fsspec.implementations.ftp.FTPFileSystem"},
+    "gcs": {
+        "class": "gcsfs.GCSFileSystem",
+        "err": "Please install gcsfs to access Google Storage",
+    },
+    "gdrive": {
+        "class": "gdrive_fsspec.GoogleDriveFileSystem",
+        "err": "Please install gdrive_fs for access to Google Drive",
+    },
+    "generic": {"class": "fsspec.generic.GenericFileSystem"},
+    "gist": {
+        "class": "fsspec.implementations.gist.GistFileSystem",
+        "err": "Install the requests package to use the gist FS",
+    },
+    "git": {
+        "class": "fsspec.implementations.git.GitFileSystem",
+        "err": "Install pygit2 to browse local git repos",
+    },
+    "github": {
+        "class": "fsspec.implementations.github.GithubFileSystem",
+        "err": "Install the requests package to use the github FS",
+    },
+    "gs": {
+        "class": "gcsfs.GCSFileSystem",
+        "err": "Please install gcsfs to access Google Storage",
+    },
+    "hdfs": {
+        "class": "fsspec.implementations.arrow.HadoopFileSystem",
+        "err": "pyarrow and local java libraries required for HDFS",
+    },
+    "hf": {
+        "class": "huggingface_hub.HfFileSystem",
+        "err": "Install huggingface_hub to access HfFileSystem",
+    },
+    "http": {
+        "class": "fsspec.implementations.http.HTTPFileSystem",
+        "err": 'HTTPFileSystem requires "requests" and "aiohttp" to be installed',
+    },
+    "https": {
+        "class": "fsspec.implementations.http.HTTPFileSystem",
+        "err": 'HTTPFileSystem requires "requests" and "aiohttp" to be installed',
+    },
+    "jlab": {
+        "class": "fsspec.implementations.jupyter.JupyterFileSystem",
+        "err": "Jupyter FS requires requests to be installed",
+    },
+    "jupyter": {
+        "class": "fsspec.implementations.jupyter.JupyterFileSystem",
+        "err": "Jupyter FS requires requests to be installed",
+    },
+    "lakefs": {
+        "class": "lakefs_spec.LakeFSFileSystem",
+        "err": "Please install lakefs-spec to access LakeFSFileSystem",
+    },
+    "libarchive": {
+        "class": "fsspec.implementations.libarchive.LibArchiveFileSystem",
+        "err": "LibArchive requires to be installed",
+    },
+    "local": {"class": "fsspec.implementations.local.LocalFileSystem"},
+    "memory": {"class": "fsspec.implementations.memory.MemoryFileSystem"},
+    "oci": {
+        "class": "ocifs.OCIFileSystem",
+        "err": "Install ocifs to access OCI Object Storage",
+    },
+    "ocilake": {
+        "class": "ocifs.OCIFileSystem",
+        "err": "Install ocifs to access OCI Data Lake",
+    },
+    "oss": {
+        "class": "ossfs.OSSFileSystem",
+        "err": "Install ossfs to access Alibaba Object Storage System",
+    },
+    "pyscript": {
+        "class": "pyscript_fsspec_client.client.PyscriptFileSystem",
+        "err": "Install requests (cpython) or run in pyscript",
+    },
+    "reference": {"class": "fsspec.implementations.reference.ReferenceFileSystem"},
+    "root": {
+        "class": "fsspec_xrootd.XRootDFileSystem",
+        "err": (
+            "Install fsspec-xrootd to access xrootd storage system. "
+            "Note: 'root' is the protocol name for xrootd storage systems, "
+            "not referring to root directories"
+        ),
+    },
+    "s3": {"class": "s3fs.S3FileSystem", "err": "Install s3fs to access S3"},
+    "s3a": {"class": "s3fs.S3FileSystem", "err": "Install s3fs to access S3"},
+    "sftp": {
+        "class": "fsspec.implementations.sftp.SFTPFileSystem",
+        "err": 'SFTPFileSystem requires "paramiko" to be installed',
+    },
+    "simplecache": {"class": "fsspec.implementations.cached.SimpleCacheFileSystem"},
+    "smb": {
+        "class": "fsspec.implementations.smb.SMBFileSystem",
+        "err": 'SMB requires "smbprotocol" or "smbprotocol[kerberos]" installed',
+    },
+    "ssh": {
+        "class": "fsspec.implementations.sftp.SFTPFileSystem",
+        "err": 'SFTPFileSystem requires "paramiko" to be installed',
+    },
+    "tar": {"class": "fsspec.implementations.tar.TarFileSystem"},
+    "tos": {
+        "class": "tosfs.TosFileSystem",
+        "err": "Install tosfs to access ByteDance volcano engine Tinder Object Storage",
+    },
+    "tosfs": {
+        "class": "tosfs.TosFileSystem",
+        "err": "Install tosfs to access ByteDance volcano engine Tinder Object Storage",
+    },
+    "wandb": {"class": "wandbfs.WandbFS", "err": "Install wandbfs to access wandb"},
+    "webdav": {
+        "class": "webdav4.fsspec.WebdavFileSystem",
+        "err": "Install webdav4 to access WebDAV",
+    },
+    "webhdfs": {
+        "class": "fsspec.implementations.webhdfs.WebHDFS",
+        "err": 'webHDFS access requires "requests" to be installed',
+    },
+    "zip": {"class": "fsspec.implementations.zip.ZipFileSystem"},
+}
+
+assert list(known_implementations) == sorted(known_implementations), (
+    "Not in alphabetical order"
+)
+
+
+def get_filesystem_class(protocol):
+    """Fetch named protocol implementation from the registry
+
+    The dict ``known_implementations`` maps protocol names to the locations
+    of classes implementing the corresponding file-system. When used for the
+    first time, appropriate imports will happen and the class will be placed in
+    the registry. All subsequent calls will fetch directly from the registry.
+
+    Some protocol implementations require additional dependencies, and so the
+    import may fail. In this case, the string in the "err" field of the
+    ``known_implementations`` will be given as the error message.
+    """
+    if not protocol:
+        protocol = default
+
+    if protocol not in registry:
+        if protocol not in known_implementations:
+            raise ValueError(f"Protocol not known: {protocol}")
+        bit = known_implementations[protocol]
+        try:
+            register_implementation(protocol, _import_class(bit["class"]))
+        except ImportError as e:
+            raise ImportError(bit.get("err")) from e
+    cls = registry[protocol]
+    if getattr(cls, "protocol", None) in ("abstract", None):
+        cls.protocol = protocol
+
+    return cls
+
+
+s3_msg = """Your installed version of s3fs is very old and known to cause
+severe performance issues, see also https://github.com/dask/dask/issues/10276
+
+To fix, you should specify a lower version bound on s3fs, or
+update the current installation.
+"""
+
+
+def _import_class(fqp: str):
+    """Take a fully-qualified path and return the imported class or identifier.
+
+    ``fqp`` is of the form "package.module.klass" or
+    "package.module:subobject.klass".
+
+    Warnings
+    --------
+    This can import arbitrary modules. Make sure you haven't installed any modules
+    that may execute malicious code at import time.
+    """
+    if ":" in fqp:
+        mod, name = fqp.rsplit(":", 1)
+    else:
+        mod, name = fqp.rsplit(".", 1)
+
+    is_s3 = mod == "s3fs"
+    mod = importlib.import_module(mod)
+    if is_s3 and mod.__version__.split(".") < ["0", "5"]:
+        warnings.warn(s3_msg)
+    for part in name.split("."):
+        mod = getattr(mod, part)
+
+    if not isinstance(mod, type):
+        raise TypeError(f"{fqp} is not a class")
+
+    return mod
+
+
+def filesystem(protocol, **storage_options):
+    """Instantiate filesystems for given protocol and arguments
+
+    ``storage_options`` are specific to the protocol being chosen, and are
+    passed directly to the class.
+    """
+    if protocol == "arrow_hdfs":
+        warnings.warn(
+            "The 'arrow_hdfs' protocol has been deprecated and will be "
+            "removed in the future. Specify it as 'hdfs'.",
+            DeprecationWarning,
+        )
+
+    cls = get_filesystem_class(protocol)
+    return cls(**storage_options)
+
+
+def available_protocols():
+    """Return a list of the implemented protocols.
+
+    Note that any given protocol may require extra packages to be importable.
+    """
+    return list(known_implementations)

.venv/lib/python3.13/site-packages/fsspec/spec.py

@@ -0,0 +1,2270 @@
+from __future__ import annotations
+
+import io
+import json
+import logging
+import os
+import threading
+import warnings
+import weakref
+from errno import ESPIPE
+from glob import has_magic
+from hashlib import sha256
+from typing import Any, ClassVar
+
+from .callbacks import DEFAULT_CALLBACK
+from .config import apply_config, conf
+from .dircache import DirCache
+from .transaction import Transaction
+from .utils import (
+    _unstrip_protocol,
+    glob_translate,
+    isfilelike,
+    other_paths,
+    read_block,
+    stringify_path,
+    tokenize,
+)
+
+logger = logging.getLogger("fsspec")
+
+
+def make_instance(cls, args, kwargs):
+    return cls(*args, **kwargs)
+
+
+class _Cached(type):
+    """
+    Metaclass for caching file system instances.
+
+    Notes
+    -----
+    Instances are cached according to
+
+    * The values of the class attributes listed in `_extra_tokenize_attributes`
+    * The arguments passed to ``__init__``.
+
+    This creates an additional reference to the filesystem, which prevents the
+    filesystem from being garbage collected when all *user* references go away.
+    A call to the :meth:`AbstractFileSystem.clear_instance_cache` must *also*
+    be made for a filesystem instance to be garbage collected.
+    """
+
+    def __init__(cls, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        # Note: we intentionally create a reference here, to avoid garbage
+        # collecting instances when all other references are gone. To really
+        # delete a FileSystem, the cache must be cleared.
+        if conf.get("weakref_instance_cache"):  # pragma: no cover
+            # debug option for analysing fork/spawn conditions
+            cls._cache = weakref.WeakValueDictionary()
+        else:
+            cls._cache = {}
+        cls._pid = os.getpid()
+
+    def __call__(cls, *args, **kwargs):
+        kwargs = apply_config(cls, kwargs)
+        extra_tokens = tuple(
+            getattr(cls, attr, None) for attr in cls._extra_tokenize_attributes
+        )
+        token = tokenize(
+            cls, cls._pid, threading.get_ident(), *args, *extra_tokens, **kwargs
+        )
+        skip = kwargs.pop("skip_instance_cache", False)
+        if os.getpid() != cls._pid:
+            cls._cache.clear()
+            cls._pid = os.getpid()
+        if not skip and cls.cachable and token in cls._cache:
+            cls._latest = token
+            return cls._cache[token]
+        else:
+            obj = super().__call__(*args, **kwargs)
+            # Setting _fs_token here causes some static linters to complain.
+            obj._fs_token_ = token
+            obj.storage_args = args
+            obj.storage_options = kwargs
+            if obj.async_impl and obj.mirror_sync_methods:
+                from .asyn import mirror_sync_methods
+
+                mirror_sync_methods(obj)
+
+            if cls.cachable and not skip:
+                cls._latest = token
+                cls._cache[token] = obj
+            return obj
+
+
+class AbstractFileSystem(metaclass=_Cached):
+    """
+    An abstract super-class for pythonic file-systems
+
+    Implementations are expected to be compatible with or, better, subclass
+    from here.
+    """
+
+    cachable = True  # this class can be cached, instances reused
+    _cached = False
+    blocksize = 2**22
+    sep = "/"
+    protocol: ClassVar[str | tuple[str, ...]] = "abstract"
+    _latest = None
+    async_impl = False
+    mirror_sync_methods = False
+    root_marker = ""  # For some FSs, may require leading '/' or other character
+    transaction_type = Transaction
+
+    #: Extra *class attributes* that should be considered when hashing.
+    _extra_tokenize_attributes = ()
+
+    # Set by _Cached metaclass
+    storage_args: tuple[Any, ...]
+    storage_options: dict[str, Any]
+
+    def __init__(self, *args, **storage_options):
+        """Create and configure file-system instance
+
+        Instances may be cachable, so if similar enough arguments are seen
+        a new instance is not required. The token attribute exists to allow
+        implementations to cache instances if they wish.
+
+        A reasonable default should be provided if there are no arguments.
+
+        Subclasses should call this method.
+
+        Parameters
+        ----------
+        use_listings_cache, listings_expiry_time, max_paths:
+            passed to ``DirCache``, if the implementation supports
+            directory listing caching. Pass use_listings_cache=False
+            to disable such caching.
+        skip_instance_cache: bool
+            If this is a cachable implementation, pass True here to force
+            creating a new instance even if a matching instance exists, and prevent
+            storing this instance.
+        asynchronous: bool
+        loop: asyncio-compatible IOLoop or None
+        """
+        if self._cached:
+            # reusing instance, don't change
+            return
+        self._cached = True
+        self._intrans = False
+        self._transaction = None
+        self._invalidated_caches_in_transaction = []
+        self.dircache = DirCache(**storage_options)
+
+        if storage_options.pop("add_docs", None):
+            warnings.warn("add_docs is no longer supported.", FutureWarning)
+
+        if storage_options.pop("add_aliases", None):
+            warnings.warn("add_aliases has been removed.", FutureWarning)
+        # This is set in _Cached
+        self._fs_token_ = None
+
+    @property
+    def fsid(self):
+        """Persistent filesystem id that can be used to compare filesystems
+        across sessions.
+        """
+        raise NotImplementedError
+
+    @property
+    def _fs_token(self):
+        return self._fs_token_
+
+    def __dask_tokenize__(self):
+        return self._fs_token
+
+    def __hash__(self):
+        return int(self._fs_token, 16)
+
+    def __eq__(self, other):
+        return isinstance(other, type(self)) and self._fs_token == other._fs_token
+
+    def __reduce__(self):
+        return make_instance, (type(self), self.storage_args, self.storage_options)
+
+    @classmethod
+    def _strip_protocol(cls, path):
+        """Turn path from fully-qualified to file-system-specific
+
+        May require FS-specific handling, e.g., for relative paths or links.
+        """
+        if isinstance(path, list):
+            return [cls._strip_protocol(p) for p in path]
+        path = stringify_path(path)
+        protos = (cls.protocol,) if isinstance(cls.protocol, str) else cls.protocol
+        for protocol in protos:
+            if path.startswith(protocol + "://"):
+                path = path[len(protocol) + 3 :]
+            elif path.startswith(protocol + "::"):
+                path = path[len(protocol) + 2 :]
+        path = path.rstrip("/")
+        # use of root_marker to make minimum required path, e.g., "/"
+        return path or cls.root_marker
+
+    def unstrip_protocol(self, name: str) -> str:
+        """Format FS-specific path to generic, including protocol"""
+        protos = (self.protocol,) if isinstance(self.protocol, str) else self.protocol
+        for protocol in protos:
+            if name.startswith(f"{protocol}://"):
+                return name
+        return f"{protos[0]}://{name}"
+
+    @staticmethod
+    def _get_kwargs_from_urls(path):
+        """If kwargs can be encoded in the paths, extract them here
+
+        This should happen before instantiation of the class; incoming paths
+        then should be amended to strip the options in methods.
+
+        Examples may look like an sftp path "sftp://user@host:/my/path", where
+        the user and host should become kwargs and later get stripped.
+        """
+        # by default, nothing happens
+        return {}
+
+    @classmethod
+    def current(cls):
+        """Return the most recently instantiated FileSystem
+
+        If no instance has been created, then create one with defaults
+        """
+        if cls._latest in cls._cache:
+            return cls._cache[cls._latest]
+        return cls()
+
+    @property
+    def transaction(self):
+        """A context within which files are committed together upon exit
+
+        Requires the file class to implement `.commit()` and `.discard()`
+        for the normal and exception cases.
+        """
+        if self._transaction is None:
+            self._transaction = self.transaction_type(self)
+        return self._transaction
+
+    def start_transaction(self):
+        """Begin write transaction for deferring files, non-context version"""
+        self._intrans = True
+        self._transaction = self.transaction_type(self)
+        return self.transaction
+
+    def end_transaction(self):
+        """Finish write transaction, non-context version"""
+        self.transaction.complete()
+        self._transaction = None
+        # The invalid cache must be cleared after the transaction is completed.
+        for path in self._invalidated_caches_in_transaction:
+            self.invalidate_cache(path)
+        self._invalidated_caches_in_transaction.clear()
+
+    def invalidate_cache(self, path=None):
+        """
+        Discard any cached directory information
+
+        Parameters
+        ----------
+        path: string or None
+            If None, clear all listings cached else listings at or under given
+            path.
+        """
+        # Not necessary to implement invalidation mechanism, may have no cache.
+        # But if have, you should call this method of parent class from your
+        # subclass to ensure expiring caches after transacations correctly.
+        # See the implementation of FTPFileSystem in ftp.py
+        if self._intrans:
+            self._invalidated_caches_in_transaction.append(path)
+
+    def mkdir(self, path, create_parents=True, **kwargs):
+        """
+        Create directory entry at path
+
+        For systems that don't have true directories, may create an for
+        this instance only and not touch the real filesystem
+
+        Parameters
+        ----------
+        path: str
+            location
+        create_parents: bool
+            if True, this is equivalent to ``makedirs``
+        kwargs:
+            may be permissions, etc.
+        """
+        pass  # not necessary to implement, may not have directories
+
+    def makedirs(self, path, exist_ok=False):
+        """Recursively make directories
+
+        Creates directory at path and any intervening required directories.
+        Raises exception if, for instance, the path already exists but is a
+        file.
+
+        Parameters
+        ----------
+        path: str
+            leaf directory name
+        exist_ok: bool (False)
+            If False, will error if the target already exists
+        """
+        pass  # not necessary to implement, may not have directories
+
+    def rmdir(self, path):
+        """Remove a directory, if empty"""
+        pass  # not necessary to implement, may not have directories
+
+    def ls(self, path, detail=True, **kwargs):
+        """List objects at path.
+
+        This should include subdirectories and files at that location. The
+        difference between a file and a directory must be clear when details
+        are requested.
+
+        The specific keys, or perhaps a FileInfo class, or similar, is TBD,
+        but must be consistent across implementations.
+        Must include:
+
+        - full path to the entry (without protocol)
+        - size of the entry, in bytes. If the value cannot be determined, will
+          be ``None``.
+        - type of entry, "file", "directory" or other
+
+        Additional information
+        may be present, appropriate to the file-system, e.g., generation,
+        checksum, etc.
+
+        May use refresh=True|False to allow use of self._ls_from_cache to
+        check for a saved listing and avoid calling the backend. This would be
+        common where listing may be expensive.
+
+        Parameters
+        ----------
+        path: str
+        detail: bool
+            if True, gives a list of dictionaries, where each is the same as
+            the result of ``info(path)``. If False, gives a list of paths
+            (str).
+        kwargs: may have additional backend-specific options, such as version
+            information
+
+        Returns
+        -------
+        List of strings if detail is False, or list of directory information
+        dicts if detail is True.
+        """
+        raise NotImplementedError
+
+    def _ls_from_cache(self, path):
+        """Check cache for listing
+
+        Returns listing, if found (may be empty list for a directly that exists
+        but contains nothing), None if not in cache.
+        """
+        parent = self._parent(path)
+        try:
+            return self.dircache[path.rstrip("/")]
+        except KeyError:
+            pass
+        try:
+            files = [
+                f
+                for f in self.dircache[parent]
+                if f["name"] == path
+                or (f["name"] == path.rstrip("/") and f["type"] == "directory")
+            ]
+            if len(files) == 0:
+                # parent dir was listed but did not contain this file
+                raise FileNotFoundError(path)
+            return files
+        except KeyError:
+            pass
+
+    def walk(self, path, maxdepth=None, topdown=True, on_error="omit", **kwargs):
+        """Return all files under the given path.
+
+        List all files, recursing into subdirectories; output is iterator-style,
+        like ``os.walk()``. For a simple list of files, ``find()`` is available.
+
+        When topdown is True, the caller can modify the dirnames list in-place (perhaps
+        using del or slice assignment), and walk() will
+        only recurse into the subdirectories whose names remain in dirnames;
+        this can be used to prune the search, impose a specific order of visiting,
+        or even to inform walk() about directories the caller creates or renames before
+        it resumes walk() again.
+        Modifying dirnames when topdown is False has no effect. (see os.walk)
+
+        Note that the "files" outputted will include anything that is not
+        a directory, such as links.
+
+        Parameters
+        ----------
+        path: str
+            Root to recurse into
+        maxdepth: int
+            Maximum recursion depth. None means limitless, but not recommended
+            on link-based file-systems.
+        topdown: bool (True)
+            Whether to walk the directory tree from the top downwards or from
+            the bottom upwards.
+        on_error: "omit", "raise", a callable
+            if omit (default), path with exception will simply be empty;
+            If raise, an underlying exception will be raised;
+            if callable, it will be called with a single OSError instance as argument
+        kwargs: passed to ``ls``
+        """
+        if maxdepth is not None and maxdepth < 1:
+            raise ValueError("maxdepth must be at least 1")
+
+        path = self._strip_protocol(path)
+        full_dirs = {}
+        dirs = {}
+        files = {}
+
+        detail = kwargs.pop("detail", False)
+        try:
+            listing = self.ls(path, detail=True, **kwargs)
+        except (FileNotFoundError, OSError) as e:
+            if on_error == "raise":
+                raise
+            if callable(on_error):
+                on_error(e)
+            return
+
+        for info in listing:
+            # each info name must be at least [path]/part , but here
+            # we check also for names like [path]/part/
+            pathname = info["name"].rstrip("/")
+            name = pathname.rsplit("/", 1)[-1]
+            if info["type"] == "directory" and pathname != path:
+                # do not include "self" path
+                full_dirs[name] = pathname
+                dirs[name] = info
+            elif pathname == path:
+                # file-like with same name as give path
+                files[""] = info
+            else:
+                files[name] = info
+
+        if not detail:
+            dirs = list(dirs)
+            files = list(files)
+
+        if topdown:
+            # Yield before recursion if walking top down
+            yield path, dirs, files
+
+        if maxdepth is not None:
+            maxdepth -= 1
+            if maxdepth < 1:
+                if not topdown:
+                    yield path, dirs, files
+                return
+
+        for d in dirs:
+            yield from self.walk(
+                full_dirs[d],
+                maxdepth=maxdepth,
+                detail=detail,
+                topdown=topdown,
+                **kwargs,
+            )
+
+        if not topdown:
+            # Yield after recursion if walking bottom up
+            yield path, dirs, files
+
+    def find(self, path, maxdepth=None, withdirs=False, detail=False, **kwargs):
+        """List all files below path.
+
+        Like posix ``find`` command without conditions
+
+        Parameters
+        ----------
+        path : str
+        maxdepth: int or None
+            If not None, the maximum number of levels to descend
+        withdirs: bool
+            Whether to include directory paths in the output. This is True
+            when used by glob, but users usually only want files.
+        kwargs are passed to ``ls``.
+        """
+        # TODO: allow equivalent of -name parameter
+        path = self._strip_protocol(path)
+        out = {}
+
+        # Add the root directory if withdirs is requested
+        # This is needed for posix glob compliance
+        if withdirs and path != "" and self.isdir(path):
+            out[path] = self.info(path)
+
+        for _, dirs, files in self.walk(path, maxdepth, detail=True, **kwargs):
+            if withdirs:
+                files.update(dirs)
+            out.update({info["name"]: info for name, info in files.items()})
+        if not out and self.isfile(path):
+            # walk works on directories, but find should also return [path]
+            # when path happens to be a file
+            out[path] = {}
+        names = sorted(out)
+        if not detail:
+            return names
+        else:
+            return {name: out[name] for name in names}
+
+    def du(self, path, total=True, maxdepth=None, withdirs=False, **kwargs):
+        """Space used by files and optionally directories within a path
+
+        Directory size does not include the size of its contents.
+
+        Parameters
+        ----------
+        path: str
+        total: bool
+            Whether to sum all the file sizes
+        maxdepth: int or None
+            Maximum number of directory levels to descend, None for unlimited.
+        withdirs: bool
+            Whether to include directory paths in the output.
+        kwargs: passed to ``find``
+
+        Returns
+        -------
+        Dict of {path: size} if total=False, or int otherwise, where numbers
+        refer to bytes used.
+        """
+        sizes = {}
+        if withdirs and self.isdir(path):
+            # Include top-level directory in output
+            info = self.info(path)
+            sizes[info["name"]] = info["size"]
+        for f in self.find(path, maxdepth=maxdepth, withdirs=withdirs, **kwargs):
+            info = self.info(f)
+            sizes[info["name"]] = info["size"]
+        if total:
+            return sum(sizes.values())
+        else:
+            return sizes
+
+    def glob(self, path, maxdepth=None, **kwargs):
+        """Find files by glob-matching.
+
+        Pattern matching capabilities for finding files that match the given pattern.
+
+        Parameters
+        ----------
+        path: str
+            The glob pattern to match against
+        maxdepth: int or None
+            Maximum depth for ``'**'`` patterns. Applied on the first ``'**'`` found.
+            Must be at least 1 if provided.
+        kwargs:
+            Additional arguments passed to ``find`` (e.g., detail=True)
+
+        Returns
+        -------
+        List of matched paths, or dict of paths and their info if detail=True
+
+        Notes
+        -----
+        Supported patterns:
+        - '*': Matches any sequence of characters within a single directory level
+        - ``'**'``: Matches any number of directory levels (must be an entire path component)
+        - '?': Matches exactly one character
+        - '[abc]': Matches any character in the set
+        - '[a-z]': Matches any character in the range
+        - '[!abc]': Matches any character NOT in the set
+
+        Special behaviors:
+        - If the path ends with '/', only folders are returned
+        - Consecutive '*' characters are compressed into a single '*'
+        - Empty brackets '[]' never match anything
+        - Negated empty brackets '[!]' match any single character
+        - Special characters in character classes are escaped properly
+
+        Limitations:
+        - ``'**'`` must be a complete path component (e.g., ``'a/**/b'``, not ``'a**b'``)
+        - No brace expansion ('{a,b}.txt')
+        - No extended glob patterns ('+(pattern)', '!(pattern)')
+        """
+        if maxdepth is not None and maxdepth < 1:
+            raise ValueError("maxdepth must be at least 1")
+
+        import re
+
+        seps = (os.path.sep, os.path.altsep) if os.path.altsep else (os.path.sep,)
+        ends_with_sep = path.endswith(seps)  # _strip_protocol strips trailing slash
+        path = self._strip_protocol(path)
+        append_slash_to_dirname = ends_with_sep or path.endswith(
+            tuple(sep + "**" for sep in seps)
+        )
+        idx_star = path.find("*") if path.find("*") >= 0 else len(path)
+        idx_qmark = path.find("?") if path.find("?") >= 0 else len(path)
+        idx_brace = path.find("[") if path.find("[") >= 0 else len(path)
+
+        min_idx = min(idx_star, idx_qmark, idx_brace)
+
+        detail = kwargs.pop("detail", False)
+
+        if not has_magic(path):
+            if self.exists(path, **kwargs):
+                if not detail:
+                    return [path]
+                else:
+                    return {path: self.info(path, **kwargs)}
+            else:
+                if not detail:
+                    return []  # glob of non-existent returns empty
+                else:
+                    return {}
+        elif "/" in path[:min_idx]:
+            min_idx = path[:min_idx].rindex("/")
+            root = path[: min_idx + 1]
+            depth = path[min_idx + 1 :].count("/") + 1
+        else:
+            root = ""
+            depth = path[min_idx + 1 :].count("/") + 1
+
+        if "**" in path:
+            if maxdepth is not None:
+                idx_double_stars = path.find("**")
+                depth_double_stars = path[idx_double_stars:].count("/") + 1
+                depth = depth - depth_double_stars + maxdepth
+            else:
+                depth = None
+
+        allpaths = self.find(root, maxdepth=depth, withdirs=True, detail=True, **kwargs)
+
+        pattern = glob_translate(path + ("/" if ends_with_sep else ""))
+        pattern = re.compile(pattern)
+
+        out = {
+            p: info
+            for p, info in sorted(allpaths.items())
+            if pattern.match(
+                p + "/"
+                if append_slash_to_dirname and info["type"] == "directory"
+                else p
+            )
+        }
+
+        if detail:
+            return out
+        else:
+            return list(out)
+
+    def exists(self, path, **kwargs):
+        """Is there a file at the given path"""
+        try:
+            self.info(path, **kwargs)
+            return True
+        except:  # noqa: E722
+            # any exception allowed bar FileNotFoundError?
+            return False
+
+    def lexists(self, path, **kwargs):
+        """If there is a file at the given path (including
+        broken links)"""
+        return self.exists(path)
+
+    def info(self, path, **kwargs):
+        """Give details of entry at path
+
+        Returns a single dictionary, with exactly the same information as ``ls``
+        would with ``detail=True``.
+
+        The default implementation calls ls and could be overridden by a
+        shortcut. kwargs are passed on to ```ls()``.
+
+        Some file systems might not be able to measure the file's size, in
+        which case, the returned dict will include ``'size': None``.
+
+        Returns
+        -------
+        dict with keys: name (full path in the FS), size (in bytes), type (file,
+        directory, or something else) and other FS-specific keys.
+        """
+        path = self._strip_protocol(path)
+        out = self.ls(self._parent(path), detail=True, **kwargs)
+        out = [o for o in out if o["name"].rstrip("/") == path]
+        if out:
+            return out[0]
+        out = self.ls(path, detail=True, **kwargs)
+        path = path.rstrip("/")
+        out1 = [o for o in out if o["name"].rstrip("/") == path]
+        if len(out1) == 1:
+            if "size" not in out1[0]:
+                out1[0]["size"] = None
+            return out1[0]
+        elif len(out1) > 1 or out:
+            return {"name": path, "size": 0, "type": "directory"}
+        else:
+            raise FileNotFoundError(path)
+
+    def checksum(self, path):
+        """Unique value for current version of file
+
+        If the checksum is the same from one moment to another, the contents
+        are guaranteed to be the same. If the checksum changes, the contents
+        *might* have changed.
+
+        This should normally be overridden; default will probably capture
+        creation/modification timestamp (which would be good) or maybe
+        access timestamp (which would be bad)
+        """
+        return int(tokenize(self.info(path)), 16)
+
+    def size(self, path):
+        """Size in bytes of file"""
+        return self.info(path).get("size", None)
+
+    def sizes(self, paths):
+        """Size in bytes of each file in a list of paths"""
+        return [self.size(p) for p in paths]
+
+    def isdir(self, path):
+        """Is this entry directory-like?"""
+        try:
+            return self.info(path)["type"] == "directory"
+        except OSError:
+            return False
+
+    def isfile(self, path):
+        """Is this entry file-like?"""
+        try:
+            return self.info(path)["type"] == "file"
+        except:  # noqa: E722
+            return False
+
+    def read_text(self, path, encoding=None, errors=None, newline=None, **kwargs):
+        """Get the contents of the file as a string.
+
+        Parameters
+        ----------
+        path: str
+            URL of file on this filesystems
+        encoding, errors, newline: same as `open`.
+        """
+        with self.open(
+            path,
+            mode="r",
+            encoding=encoding,
+            errors=errors,
+            newline=newline,
+            **kwargs,
+        ) as f:
+            return f.read()
+
+    def write_text(
+        self, path, value, encoding=None, errors=None, newline=None, **kwargs
+    ):
+        """Write the text to the given file.
+
+        An existing file will be overwritten.
+
+        Parameters
+        ----------
+        path: str
+            URL of file on this filesystems
+        value: str
+            Text to write.
+        encoding, errors, newline: same as `open`.
+        """
+        with self.open(
+            path,
+            mode="w",
+            encoding=encoding,
+            errors=errors,
+            newline=newline,
+            **kwargs,
+        ) as f:
+            return f.write(value)
+
+    def cat_file(self, path, start=None, end=None, **kwargs):
+        """Get the content of a file
+
+        Parameters
+        ----------
+        path: URL of file on this filesystems
+        start, end: int
+            Bytes limits of the read. If negative, backwards from end,
+            like usual python slices. Either can be None for start or
+            end of file, respectively
+        kwargs: passed to ``open()``.
+        """
+        # explicitly set buffering off?
+        with self.open(path, "rb", **kwargs) as f:
+            if start is not None:
+                if start >= 0:
+                    f.seek(start)
+                else:
+                    f.seek(max(0, f.size + start))
+            if end is not None:
+                if end < 0:
+                    end = f.size + end
+                return f.read(end - f.tell())
+            return f.read()
+
+    def pipe_file(self, path, value, mode="overwrite", **kwargs):
+        """Set the bytes of given file"""
+        if mode == "create" and self.exists(path):
+            # non-atomic but simple way; or could use "xb" in open(), which is likely
+            # not as well supported
+            raise FileExistsError
+        with self.open(path, "wb", **kwargs) as f:
+            f.write(value)
+
+    def pipe(self, path, value=None, **kwargs):
+        """Put value into path
+
+        (counterpart to ``cat``)
+
+        Parameters
+        ----------
+        path: string or dict(str, bytes)
+            If a string, a single remote location to put ``value`` bytes; if a dict,
+            a mapping of {path: bytesvalue}.
+        value: bytes, optional
+            If using a single path, these are the bytes to put there. Ignored if
+            ``path`` is a dict
+        """
+        if isinstance(path, str):
+            self.pipe_file(self._strip_protocol(path), value, **kwargs)
+        elif isinstance(path, dict):
+            for k, v in path.items():
+                self.pipe_file(self._strip_protocol(k), v, **kwargs)
+        else:
+            raise ValueError("path must be str or dict")
+
+    def cat_ranges(
+        self, paths, starts, ends, max_gap=None, on_error="return", **kwargs
+    ):
+        """Get the contents of byte ranges from one or more files
+
+        Parameters
+        ----------
+        paths: list
+            A list of of filepaths on this filesystems
+        starts, ends: int or list
+            Bytes limits of the read. If using a single int, the same value will be
+            used to read all the specified files.
+        """
+        if max_gap is not None:
+            raise NotImplementedError
+        if not isinstance(paths, list):
+            raise TypeError
+        if not isinstance(starts, list):
+            starts = [starts] * len(paths)
+        if not isinstance(ends, list):
+            ends = [ends] * len(paths)
+        if len(starts) != len(paths) or len(ends) != len(paths):
+            raise ValueError
+        out = []
+        for p, s, e in zip(paths, starts, ends):
+            try:
+                out.append(self.cat_file(p, s, e))
+            except Exception as e:
+                if on_error == "return":
+                    out.append(e)
+                else:
+                    raise
+        return out
+
+    def cat(self, path, recursive=False, on_error="raise", **kwargs):
+        """Fetch (potentially multiple) paths' contents
+
+        Parameters
+        ----------
+        recursive: bool
+            If True, assume the path(s) are directories, and get all the
+            contained files
+        on_error : "raise", "omit", "return"
+            If raise, an underlying exception will be raised (converted to KeyError
+            if the type is in self.missing_exceptions); if omit, keys with exception
+            will simply not be included in the output; if "return", all keys are
+            included in the output, but the value will be bytes or an exception
+            instance.
+        kwargs: passed to cat_file
+
+        Returns
+        -------
+        dict of {path: contents} if there are multiple paths
+        or the path has been otherwise expanded
+        """
+        paths = self.expand_path(path, recursive=recursive)
+        if (
+            len(paths) > 1
+            or isinstance(path, list)
+            or paths[0] != self._strip_protocol(path)
+        ):
+            out = {}
+            for path in paths:
+                try:
+                    out[path] = self.cat_file(path, **kwargs)
+                except Exception as e:
+                    if on_error == "raise":
+                        raise
+                    if on_error == "return":
+                        out[path] = e
+            return out
+        else:
+            return self.cat_file(paths[0], **kwargs)
+
+    def get_file(self, rpath, lpath, callback=DEFAULT_CALLBACK, outfile=None, **kwargs):
+        """Copy single remote file to local"""
+        from .implementations.local import LocalFileSystem
+
+        if isfilelike(lpath):
+            outfile = lpath
+        elif self.isdir(rpath):
+            os.makedirs(lpath, exist_ok=True)
+            return None
+
+        fs = LocalFileSystem(auto_mkdir=True)
+        fs.makedirs(fs._parent(lpath), exist_ok=True)
+
+        with self.open(rpath, "rb", **kwargs) as f1:
+            if outfile is None:
+                outfile = open(lpath, "wb")
+
+            try:
+                callback.set_size(getattr(f1, "size", None))
+                data = True
+                while data:
+                    data = f1.read(self.blocksize)
+                    segment_len = outfile.write(data)
+                    if segment_len is None:
+                        segment_len = len(data)
+                    callback.relative_update(segment_len)
+            finally:
+                if not isfilelike(lpath):
+                    outfile.close()
+
+    def get(
+        self,
+        rpath,
+        lpath,
+        recursive=False,
+        callback=DEFAULT_CALLBACK,
+        maxdepth=None,
+        **kwargs,
+    ):
+        """Copy file(s) to local.
+
+        Copies a specific file or tree of files (if recursive=True). If lpath
+        ends with a "/", it will be assumed to be a directory, and target files
+        will go within. Can submit a list of paths, which may be glob-patterns
+        and will be expanded.
+
+        Calls get_file for each source.
+        """
+        if isinstance(lpath, list) and isinstance(rpath, list):
+            # No need to expand paths when both source and destination
+            # are provided as lists
+            rpaths = rpath
+            lpaths = lpath
+        else:
+            from .implementations.local import (
+                LocalFileSystem,
+                make_path_posix,
+                trailing_sep,
+            )
+
+            source_is_str = isinstance(rpath, str)
+            rpaths = self.expand_path(rpath, recursive=recursive, maxdepth=maxdepth)
+            if source_is_str and (not recursive or maxdepth is not None):
+                # Non-recursive glob does not copy directories
+                rpaths = [p for p in rpaths if not (trailing_sep(p) or self.isdir(p))]
+                if not rpaths:
+                    return
+
+            if isinstance(lpath, str):
+                lpath = make_path_posix(lpath)
+
+            source_is_file = len(rpaths) == 1
+            dest_is_dir = isinstance(lpath, str) and (
+                trailing_sep(lpath) or LocalFileSystem().isdir(lpath)
+            )
+
+            exists = source_is_str and (
+                (has_magic(rpath) and source_is_file)
+                or (not has_magic(rpath) and dest_is_dir and not trailing_sep(rpath))
+            )
+            lpaths = other_paths(
+                rpaths,
+                lpath,
+                exists=exists,
+                flatten=not source_is_str,
+            )
+
+        callback.set_size(len(lpaths))
+        for lpath, rpath in callback.wrap(zip(lpaths, rpaths)):
+            with callback.branched(rpath, lpath) as child:
+                self.get_file(rpath, lpath, callback=child, **kwargs)
+
+    def put_file(
+        self, lpath, rpath, callback=DEFAULT_CALLBACK, mode="overwrite", **kwargs
+    ):
+        """Copy single file to remote"""
+        if mode == "create" and self.exists(rpath):
+            raise FileExistsError
+        if os.path.isdir(lpath):
+            self.makedirs(rpath, exist_ok=True)
+            return None
+
+        with open(lpath, "rb") as f1:
+            size = f1.seek(0, 2)
+            callback.set_size(size)
+            f1.seek(0)
+
+            self.mkdirs(self._parent(os.fspath(rpath)), exist_ok=True)
+            with self.open(rpath, "wb", **kwargs) as f2:
+                while f1.tell() < size:
+                    data = f1.read(self.blocksize)
+                    segment_len = f2.write(data)
+                    if segment_len is None:
+                        segment_len = len(data)
+                    callback.relative_update(segment_len)
+
+    def put(
+        self,
+        lpath,
+        rpath,
+        recursive=False,
+        callback=DEFAULT_CALLBACK,
+        maxdepth=None,
+        **kwargs,
+    ):
+        """Copy file(s) from local.
+
+        Copies a specific file or tree of files (if recursive=True). If rpath
+        ends with a "/", it will be assumed to be a directory, and target files
+        will go within.
+
+        Calls put_file for each source.
+        """
+        if isinstance(lpath, list) and isinstance(rpath, list):
+            # No need to expand paths when both source and destination
+            # are provided as lists
+            rpaths = rpath
+            lpaths = lpath
+        else:
+            from .implementations.local import (
+                LocalFileSystem,
+                make_path_posix,
+                trailing_sep,
+            )
+
+            source_is_str = isinstance(lpath, str)
+            if source_is_str:
+                lpath = make_path_posix(lpath)
+            fs = LocalFileSystem()
+            lpaths = fs.expand_path(lpath, recursive=recursive, maxdepth=maxdepth)
+            if source_is_str and (not recursive or maxdepth is not None):
+                # Non-recursive glob does not copy directories
+                lpaths = [p for p in lpaths if not (trailing_sep(p) or fs.isdir(p))]
+                if not lpaths:
+                    return
+
+            source_is_file = len(lpaths) == 1
+            dest_is_dir = isinstance(rpath, str) and (
+                trailing_sep(rpath) or self.isdir(rpath)
+            )
+
+            rpath = (
+                self._strip_protocol(rpath)
+                if isinstance(rpath, str)
+                else [self._strip_protocol(p) for p in rpath]
+            )
+            exists = source_is_str and (
+                (has_magic(lpath) and source_is_file)
+                or (not has_magic(lpath) and dest_is_dir and not trailing_sep(lpath))
+            )
+            rpaths = other_paths(
+                lpaths,
+                rpath,
+                exists=exists,
+                flatten=not source_is_str,
+            )
+
+        callback.set_size(len(rpaths))
+        for lpath, rpath in callback.wrap(zip(lpaths, rpaths)):
+            with callback.branched(lpath, rpath) as child:
+                self.put_file(lpath, rpath, callback=child, **kwargs)
+
+    def head(self, path, size=1024):
+        """Get the first ``size`` bytes from file"""
+        with self.open(path, "rb") as f:
+            return f.read(size)
+
+    def tail(self, path, size=1024):
+        """Get the last ``size`` bytes from file"""
+        with self.open(path, "rb") as f:
+            f.seek(max(-size, -f.size), 2)
+            return f.read()
+
+    def cp_file(self, path1, path2, **kwargs):
+        raise NotImplementedError
+
+    def copy(
+        self, path1, path2, recursive=False, maxdepth=None, on_error=None, **kwargs
+    ):
+        """Copy within two locations in the filesystem
+
+        on_error : "raise", "ignore"
+            If raise, any not-found exceptions will be raised; if ignore any
+            not-found exceptions will cause the path to be skipped; defaults to
+            raise unless recursive is true, where the default is ignore
+        """
+        if on_error is None and recursive:
+            on_error = "ignore"
+        elif on_error is None:
+            on_error = "raise"
+
+        if isinstance(path1, list) and isinstance(path2, list):
+            # No need to expand paths when both source and destination
+            # are provided as lists
+            paths1 = path1
+            paths2 = path2
+        else:
+            from .implementations.local import trailing_sep
+
+            source_is_str = isinstance(path1, str)
+            paths1 = self.expand_path(path1, recursive=recursive, maxdepth=maxdepth)
+            if source_is_str and (not recursive or maxdepth is not None):
+                # Non-recursive glob does not copy directories
+                paths1 = [p for p in paths1 if not (trailing_sep(p) or self.isdir(p))]
+                if not paths1:
+                    return
+
+            source_is_file = len(paths1) == 1
+            dest_is_dir = isinstance(path2, str) and (
+                trailing_sep(path2) or self.isdir(path2)
+            )
+
+            exists = source_is_str and (
+                (has_magic(path1) and source_is_file)
+                or (not has_magic(path1) and dest_is_dir and not trailing_sep(path1))
+            )
+            paths2 = other_paths(
+                paths1,
+                path2,
+                exists=exists,
+                flatten=not source_is_str,
+            )
+
+        for p1, p2 in zip(paths1, paths2):
+            try:
+                self.cp_file(p1, p2, **kwargs)
+            except FileNotFoundError:
+                if on_error == "raise":
+                    raise
+
+    def expand_path(self, path, recursive=False, maxdepth=None, **kwargs):
+        """Turn one or more globs or directories into a list of all matching paths
+        to files or directories.
+
+        kwargs are passed to ``glob`` or ``find``, which may in turn call ``ls``
+        """
+
+        if maxdepth is not None and maxdepth < 1:
+            raise ValueError("maxdepth must be at least 1")
+
+        if isinstance(path, (str, os.PathLike)):
+            out = self.expand_path([path], recursive, maxdepth)
+        else:
+            out = set()
+            path = [self._strip_protocol(p) for p in path]
+            for p in path:
+                if has_magic(p):
+                    bit = set(self.glob(p, maxdepth=maxdepth, **kwargs))
+                    out |= bit
+                    if recursive:
+                        # glob call above expanded one depth so if maxdepth is defined
+                        # then decrement it in expand_path call below. If it is zero
+                        # after decrementing then avoid expand_path call.
+                        if maxdepth is not None and maxdepth <= 1:
+                            continue
+                        out |= set(
+                            self.expand_path(
+                                list(bit),
+                                recursive=recursive,
+                                maxdepth=maxdepth - 1 if maxdepth is not None else None,
+                                **kwargs,
+                            )
+                        )
+                    continue
+                elif recursive:
+                    rec = set(
+                        self.find(
+                            p, maxdepth=maxdepth, withdirs=True, detail=False, **kwargs
+                        )
+                    )
+                    out |= rec
+                if p not in out and (recursive is False or self.exists(p)):
+                    # should only check once, for the root
+                    out.add(p)
+        if not out:
+            raise FileNotFoundError(path)
+        return sorted(out)
+
+    def mv(self, path1, path2, recursive=False, maxdepth=None, **kwargs):
+        """Move file(s) from one location to another"""
+        if path1 == path2:
+            logger.debug("%s mv: The paths are the same, so no files were moved.", self)
+        else:
+            # explicitly raise exception to prevent data corruption
+            self.copy(
+                path1, path2, recursive=recursive, maxdepth=maxdepth, onerror="raise"
+            )
+            self.rm(path1, recursive=recursive)
+
+    def rm_file(self, path):
+        """Delete a file"""
+        self._rm(path)
+
+    def _rm(self, path):
+        """Delete one file"""
+        # this is the old name for the method, prefer rm_file
+        raise NotImplementedError
+
+    def rm(self, path, recursive=False, maxdepth=None):
+        """Delete files.
+
+        Parameters
+        ----------
+        path: str or list of str
+            File(s) to delete.
+        recursive: bool
+            If file(s) are directories, recursively delete contents and then
+            also remove the directory
+        maxdepth: int or None
+            Depth to pass to walk for finding files to delete, if recursive.
+            If None, there will be no limit and infinite recursion may be
+            possible.
+        """
+        path = self.expand_path(path, recursive=recursive, maxdepth=maxdepth)
+        for p in reversed(path):
+            self.rm_file(p)
+
+    @classmethod
+    def _parent(cls, path):
+        path = cls._strip_protocol(path)
+        if "/" in path:
+            parent = path.rsplit("/", 1)[0].lstrip(cls.root_marker)
+            return cls.root_marker + parent
+        else:
+            return cls.root_marker
+
+    def _open(
+        self,
+        path,
+        mode="rb",
+        block_size=None,
+        autocommit=True,
+        cache_options=None,
+        **kwargs,
+    ):
+        """Return raw bytes-mode file-like from the file-system"""
+        return AbstractBufferedFile(
+            self,
+            path,
+            mode,
+            block_size,
+            autocommit,
+            cache_options=cache_options,
+            **kwargs,
+        )
+
+    def open(
+        self,
+        path,
+        mode="rb",
+        block_size=None,
+        cache_options=None,
+        compression=None,
+        **kwargs,
+    ):
+        """
+        Return a file-like object from the filesystem
+
+        The resultant instance must function correctly in a context ``with``
+        block.
+
+        Parameters
+        ----------
+        path: str
+            Target file
+        mode: str like 'rb', 'w'
+            See builtin ``open()``
+            Mode "x" (exclusive write) may be implemented by the backend. Even if
+            it is, whether  it is checked up front or on commit, and whether it is
+            atomic is implementation-dependent.
+        block_size: int
+            Some indication of buffering - this is a value in bytes
+        cache_options : dict, optional
+            Extra arguments to pass through to the cache.
+        compression: string or None
+            If given, open file using compression codec. Can either be a compression
+            name (a key in ``fsspec.compression.compr``) or "infer" to guess the
+            compression from the filename suffix.
+        encoding, errors, newline: passed on to TextIOWrapper for text mode
+        """
+        import io
+
+        path = self._strip_protocol(path)
+        if "b" not in mode:
+            mode = mode.replace("t", "") + "b"
+
+            text_kwargs = {
+                k: kwargs.pop(k)
+                for k in ["encoding", "errors", "newline"]
+                if k in kwargs
+            }
+            return io.TextIOWrapper(
+                self.open(
+                    path,
+                    mode,
+                    block_size=block_size,
+                    cache_options=cache_options,
+                    compression=compression,
+                    **kwargs,
+                ),
+                **text_kwargs,
+            )
+        else:
+            ac = kwargs.pop("autocommit", not self._intrans)
+            f = self._open(
+                path,
+                mode=mode,
+                block_size=block_size,
+                autocommit=ac,
+                cache_options=cache_options,
+                **kwargs,
+            )
+            if compression is not None:
+                from fsspec.compression import compr
+                from fsspec.core import get_compression
+
+                compression = get_compression(path, compression)
+                compress = compr[compression]
+                f = compress(f, mode=mode[0])
+
+            if not ac and "r" not in mode:
+                self.transaction.files.append(f)
+            return f
+
+    def touch(self, path, truncate=True, **kwargs):
+        """Create empty file, or update timestamp
+
+        Parameters
+        ----------
+        path: str
+            file location
+        truncate: bool
+            If True, always set file size to 0; if False, update timestamp and
+            leave file unchanged, if backend allows this
+        """
+        if truncate or not self.exists(path):
+            with self.open(path, "wb", **kwargs):
+                pass
+        else:
+            raise NotImplementedError  # update timestamp, if possible
+
+    def ukey(self, path):
+        """Hash of file properties, to tell if it has changed"""
+        return sha256(str(self.info(path)).encode()).hexdigest()
+
+    def read_block(self, fn, offset, length, delimiter=None):
+        """Read a block of bytes from
+
+        Starting at ``offset`` of the file, read ``length`` bytes.  If
+        ``delimiter`` is set then we ensure that the read starts and stops at
+        delimiter boundaries that follow the locations ``offset`` and ``offset
+        + length``.  If ``offset`` is zero then we start at zero.  The
+        bytestring returned WILL include the end delimiter string.
+
+        If offset+length is beyond the eof, reads to eof.
+
+        Parameters
+        ----------
+        fn: string
+            Path to filename
+        offset: int
+            Byte offset to start read
+        length: int
+            Number of bytes to read. If None, read to end.
+        delimiter: bytes (optional)
+            Ensure reading starts and stops at delimiter bytestring
+
+        Examples
+        --------
+        >>> fs.read_block('data/file.csv', 0, 13)  # doctest: +SKIP
+        b'Alice, 100\\nBo'
+        >>> fs.read_block('data/file.csv', 0, 13, delimiter=b'\\n')  # doctest: +SKIP
+        b'Alice, 100\\nBob, 200\\n'
+
+        Use ``length=None`` to read to the end of the file.
+        >>> fs.read_block('data/file.csv', 0, None, delimiter=b'\\n')  # doctest: +SKIP
+        b'Alice, 100\\nBob, 200\\nCharlie, 300'
+
+        See Also
+        --------
+        :func:`fsspec.utils.read_block`
+        """
+        with self.open(fn, "rb") as f:
+            size = f.size
+            if length is None:
+                length = size
+            if size is not None and offset + length > size:
+                length = size - offset
+            return read_block(f, offset, length, delimiter)
+
+    def to_json(self, *, include_password: bool = True) -> str:
+        """
+        JSON representation of this filesystem instance.
+
+        Parameters
+        ----------
+        include_password: bool, default True
+            Whether to include the password (if any) in the output.
+
+        Returns
+        -------
+        JSON string with keys ``cls`` (the python location of this class),
+        protocol (text name of this class's protocol, first one in case of
+        multiple), ``args`` (positional args, usually empty), and all other
+        keyword arguments as their own keys.
+
+        Warnings
+        --------
+        Serialized filesystems may contain sensitive information which have been
+        passed to the constructor, such as passwords and tokens. Make sure you
+        store and send them in a secure environment!
+        """
+        from .json import FilesystemJSONEncoder
+
+        return json.dumps(
+            self,
+            cls=type(
+                "_FilesystemJSONEncoder",
+                (FilesystemJSONEncoder,),
+                {"include_password": include_password},
+            ),
+        )
+
+    @staticmethod
+    def from_json(blob: str) -> AbstractFileSystem:
+        """
+        Recreate a filesystem instance from JSON representation.
+
+        See ``.to_json()`` for the expected structure of the input.
+
+        Parameters
+        ----------
+        blob: str
+
+        Returns
+        -------
+        file system instance, not necessarily of this particular class.
+
+        Warnings
+        --------
+        This can import arbitrary modules (as determined by the ``cls`` key).
+        Make sure you haven't installed any modules that may execute malicious code
+        at import time.
+        """
+        from .json import FilesystemJSONDecoder
+
+        return json.loads(blob, cls=FilesystemJSONDecoder)
+
+    def to_dict(self, *, include_password: bool = True) -> dict[str, Any]:
+        """
+        JSON-serializable dictionary representation of this filesystem instance.
+
+        Parameters
+        ----------
+        include_password: bool, default True
+            Whether to include the password (if any) in the output.
+
+        Returns
+        -------
+        Dictionary with keys ``cls`` (the python location of this class),
+        protocol (text name of this class's protocol, first one in case of
+        multiple), ``args`` (positional args, usually empty), and all other
+        keyword arguments as their own keys.
+
+        Warnings
+        --------
+        Serialized filesystems may contain sensitive information which have been
+        passed to the constructor, such as passwords and tokens. Make sure you
+        store and send them in a secure environment!
+        """
+        from .json import FilesystemJSONEncoder
+
+        json_encoder = FilesystemJSONEncoder()
+
+        cls = type(self)
+        proto = self.protocol
+
+        storage_options = dict(self.storage_options)
+        if not include_password:
+            storage_options.pop("password", None)
+
+        return dict(
+            cls=f"{cls.__module__}:{cls.__name__}",
+            protocol=proto[0] if isinstance(proto, (tuple, list)) else proto,
+            args=json_encoder.make_serializable(self.storage_args),
+            **json_encoder.make_serializable(storage_options),
+        )
+
+    @staticmethod
+    def from_dict(dct: dict[str, Any]) -> AbstractFileSystem:
+        """
+        Recreate a filesystem instance from dictionary representation.
+
+        See ``.to_dict()`` for the expected structure of the input.
+
+        Parameters
+        ----------
+        dct: Dict[str, Any]
+
+        Returns
+        -------
+        file system instance, not necessarily of this particular class.
+
+        Warnings
+        --------
+        This can import arbitrary modules (as determined by the ``cls`` key).
+        Make sure you haven't installed any modules that may execute malicious code
+        at import time.
+        """
+        from .json import FilesystemJSONDecoder
+
+        json_decoder = FilesystemJSONDecoder()
+
+        dct = dict(dct)  # Defensive copy
+
+        cls = FilesystemJSONDecoder.try_resolve_fs_cls(dct)
+        if cls is None:
+            raise ValueError("Not a serialized AbstractFileSystem")
+
+        dct.pop("cls", None)
+        dct.pop("protocol", None)
+
+        return cls(
+            *json_decoder.unmake_serializable(dct.pop("args", ())),
+            **json_decoder.unmake_serializable(dct),
+        )
+
+    def _get_pyarrow_filesystem(self):
+        """
+        Make a version of the FS instance which will be acceptable to pyarrow
+        """
+        # all instances already also derive from pyarrow
+        return self
+
+    def get_mapper(self, root="", check=False, create=False, missing_exceptions=None):
+        """Create key/value store based on this file-system
+
+        Makes a MutableMapping interface to the FS at the given root path.
+        See ``fsspec.mapping.FSMap`` for further details.
+        """
+        from .mapping import FSMap
+
+        return FSMap(
+            root,
+            self,
+            check=check,
+            create=create,
+            missing_exceptions=missing_exceptions,
+        )
+
+    @classmethod
+    def clear_instance_cache(cls):
+        """
+        Clear the cache of filesystem instances.
+
+        Notes
+        -----
+        Unless overridden by setting the ``cachable`` class attribute to False,
+        the filesystem class stores a reference to newly created instances. This
+        prevents Python's normal rules around garbage collection from working,
+        since the instances refcount will not drop to zero until
+        ``clear_instance_cache`` is called.
+        """
+        cls._cache.clear()
+
+    def created(self, path):
+        """Return the created timestamp of a file as a datetime.datetime"""
+        raise NotImplementedError
+
+    def modified(self, path):
+        """Return the modified timestamp of a file as a datetime.datetime"""
+        raise NotImplementedError
+
+    def tree(
+        self,
+        path: str = "/",
+        recursion_limit: int = 2,
+        max_display: int = 25,
+        display_size: bool = False,
+        prefix: str = "",
+        is_last: bool = True,
+        first: bool = True,
+        indent_size: int = 4,
+    ) -> str:
+        """
+        Return a tree-like structure of the filesystem starting from the given path as a string.
+
+        Parameters
+        ----------
+            path: Root path to start traversal from
+            recursion_limit: Maximum depth of directory traversal
+            max_display: Maximum number of items to display per directory
+            display_size: Whether to display file sizes
+            prefix: Current line prefix for visual tree structure
+            is_last: Whether current item is last in its level
+            first: Whether this is the first call (displays root path)
+            indent_size: Number of spaces by indent
+
+        Returns
+        -------
+            str: A string representing the tree structure.
+
+        Example
+        -------
+            >>> from fsspec import filesystem
+
+            >>> fs = filesystem('ftp', host='test.rebex.net', user='demo', password='password')
+            >>> tree = fs.tree(display_size=True, recursion_limit=3, indent_size=8, max_display=10)
+            >>> print(tree)
+        """
+
+        def format_bytes(n: int) -> str:
+            """Format bytes as text."""
+            for prefix, k in (
+                ("P", 2**50),
+                ("T", 2**40),
+                ("G", 2**30),
+                ("M", 2**20),
+                ("k", 2**10),
+            ):
+                if n >= 0.9 * k:
+                    return f"{n / k:.2f} {prefix}b"
+            return f"{n}B"
+
+        result = []
+
+        if first:
+            result.append(path)
+
+        if recursion_limit:
+            indent = " " * indent_size
+            contents = self.ls(path, detail=True)
+            contents.sort(
+                key=lambda x: (x.get("type") != "directory", x.get("name", ""))
+            )
+
+            if max_display is not None and len(contents) > max_display:
+                displayed_contents = contents[:max_display]
+                remaining_count = len(contents) - max_display
+            else:
+                displayed_contents = contents
+                remaining_count = 0
+
+            for i, item in enumerate(displayed_contents):
+                is_last_item = (i == len(displayed_contents) - 1) and (
+                    remaining_count == 0
+                )
+
+                branch = (
+                    "└" + ("─" * (indent_size - 2))
+                    if is_last_item
+                    else "├" + ("─" * (indent_size - 2))
+                )
+                branch += " "
+                new_prefix = prefix + (
+                    indent if is_last_item else "│" + " " * (indent_size - 1)
+                )
+
+                name = os.path.basename(item.get("name", ""))
+
+                if display_size and item.get("type") == "directory":
+                    sub_contents = self.ls(item.get("name", ""), detail=True)
+                    num_files = sum(
+                        1 for sub_item in sub_contents if sub_item.get("type") == "file"
+                    )
+                    num_folders = sum(
+                        1
+                        for sub_item in sub_contents
+                        if sub_item.get("type") == "directory"
+                    )
+
+                    if num_files == 0 and num_folders == 0:
+                        size = " (empty folder)"
+                    elif num_files == 0:
+                        size = f" ({num_folders} subfolder{'s' if num_folders > 1 else ''})"
+                    elif num_folders == 0:
+                        size = f" ({num_files} file{'s' if num_files > 1 else ''})"
+                    else:
+                        size = f" ({num_files} file{'s' if num_files > 1 else ''}, {num_folders} subfolder{'s' if num_folders > 1 else ''})"
+                elif display_size and item.get("type") == "file":
+                    size = f" ({format_bytes(item.get('size', 0))})"
+                else:
+                    size = ""
+
+                result.append(f"{prefix}{branch}{name}{size}")
+
+                if item.get("type") == "directory" and recursion_limit > 0:
+                    result.append(
+                        self.tree(
+                            path=item.get("name", ""),
+                            recursion_limit=recursion_limit - 1,
+                            max_display=max_display,
+                            display_size=display_size,
+                            prefix=new_prefix,
+                            is_last=is_last_item,
+                            first=False,
+                            indent_size=indent_size,
+                        )
+                    )
+
+            if remaining_count > 0:
+                more_message = f"{remaining_count} more item(s) not displayed."
+                result.append(
+                    f"{prefix}{'└' + ('─' * (indent_size - 2))} {more_message}"
+                )
+
+        return "\n".join(_ for _ in result if _)
+
+    # ------------------------------------------------------------------------
+    # Aliases
+
+    def read_bytes(self, path, start=None, end=None, **kwargs):
+        """Alias of `AbstractFileSystem.cat_file`."""
+        return self.cat_file(path, start=start, end=end, **kwargs)
+
+    def write_bytes(self, path, value, **kwargs):
+        """Alias of `AbstractFileSystem.pipe_file`."""
+        self.pipe_file(path, value, **kwargs)
+
+    def makedir(self, path, create_parents=True, **kwargs):
+        """Alias of `AbstractFileSystem.mkdir`."""
+        return self.mkdir(path, create_parents=create_parents, **kwargs)
+
+    def mkdirs(self, path, exist_ok=False):
+        """Alias of `AbstractFileSystem.makedirs`."""
+        return self.makedirs(path, exist_ok=exist_ok)
+
+    def listdir(self, path, detail=True, **kwargs):
+        """Alias of `AbstractFileSystem.ls`."""
+        return self.ls(path, detail=detail, **kwargs)
+
+    def cp(self, path1, path2, **kwargs):
+        """Alias of `AbstractFileSystem.copy`."""
+        return self.copy(path1, path2, **kwargs)
+
+    def move(self, path1, path2, **kwargs):
+        """Alias of `AbstractFileSystem.mv`."""
+        return self.mv(path1, path2, **kwargs)
+
+    def stat(self, path, **kwargs):
+        """Alias of `AbstractFileSystem.info`."""
+        return self.info(path, **kwargs)
+
+    def disk_usage(self, path, total=True, maxdepth=None, **kwargs):
+        """Alias of `AbstractFileSystem.du`."""
+        return self.du(path, total=total, maxdepth=maxdepth, **kwargs)
+
+    def rename(self, path1, path2, **kwargs):
+        """Alias of `AbstractFileSystem.mv`."""
+        return self.mv(path1, path2, **kwargs)
+
+    def delete(self, path, recursive=False, maxdepth=None):
+        """Alias of `AbstractFileSystem.rm`."""
+        return self.rm(path, recursive=recursive, maxdepth=maxdepth)
+
+    def upload(self, lpath, rpath, recursive=False, **kwargs):
+        """Alias of `AbstractFileSystem.put`."""
+        return self.put(lpath, rpath, recursive=recursive, **kwargs)
+
+    def download(self, rpath, lpath, recursive=False, **kwargs):
+        """Alias of `AbstractFileSystem.get`."""
+        return self.get(rpath, lpath, recursive=recursive, **kwargs)
+
+    def sign(self, path, expiration=100, **kwargs):
+        """Create a signed URL representing the given path
+
+        Some implementations allow temporary URLs to be generated, as a
+        way of delegating credentials.
+
+        Parameters
+        ----------
+        path : str
+             The path on the filesystem
+        expiration : int
+            Number of seconds to enable the URL for (if supported)
+
+        Returns
+        -------
+        URL : str
+            The signed URL
+
+        Raises
+        ------
+        NotImplementedError : if method is not implemented for a filesystem
+        """
+        raise NotImplementedError("Sign is not implemented for this filesystem")
+
+    def _isfilestore(self):
+        # Originally inherited from pyarrow DaskFileSystem. Keeping this
+        # here for backwards compatibility as long as pyarrow uses its
+        # legacy fsspec-compatible filesystems and thus accepts fsspec
+        # filesystems as well
+        return False
+
+
+class AbstractBufferedFile(io.IOBase):
+    """Convenient class to derive from to provide buffering
+
+    In the case that the backend does not provide a pythonic file-like object
+    already, this class contains much of the logic to build one. The only
+    methods that need to be overridden are ``_upload_chunk``,
+    ``_initiate_upload`` and ``_fetch_range``.
+    """
+
+    DEFAULT_BLOCK_SIZE = 5 * 2**20
+    _details = None
+
+    def __init__(
+        self,
+        fs,
+        path,
+        mode="rb",
+        block_size="default",
+        autocommit=True,
+        cache_type="readahead",
+        cache_options=None,
+        size=None,
+        **kwargs,
+    ):
+        """
+        Template for files with buffered reading and writing
+
+        Parameters
+        ----------
+        fs: instance of FileSystem
+        path: str
+            location in file-system
+        mode: str
+            Normal file modes. Currently only 'wb', 'ab' or 'rb'. Some file
+            systems may be read-only, and some may not support append.
+        block_size: int
+            Buffer size for reading or writing, 'default' for class default
+        autocommit: bool
+            Whether to write to final destination; may only impact what
+            happens when file is being closed.
+        cache_type: {"readahead", "none", "mmap", "bytes"}, default "readahead"
+            Caching policy in read mode. See the definitions in ``core``.
+        cache_options : dict
+            Additional options passed to the constructor for the cache specified
+            by `cache_type`.
+        size: int
+            If given and in read mode, suppressed having to look up the file size
+        kwargs:
+            Gets stored as self.kwargs
+        """
+        from .core import caches
+
+        self.path = path
+        self.fs = fs
+        self.mode = mode
+        self.blocksize = (
+            self.DEFAULT_BLOCK_SIZE if block_size in ["default", None] else block_size
+        )
+        self.loc = 0
+        self.autocommit = autocommit
+        self.end = None
+        self.start = None
+        self.closed = False
+
+        if cache_options is None:
+            cache_options = {}
+
+        if "trim" in kwargs:
+            warnings.warn(
+                "Passing 'trim' to control the cache behavior has been deprecated. "
+                "Specify it within the 'cache_options' argument instead.",
+                FutureWarning,
+            )
+            cache_options["trim"] = kwargs.pop("trim")
+
+        self.kwargs = kwargs
+
+        if mode not in {"ab", "rb", "wb", "xb"}:
+            raise NotImplementedError("File mode not supported")
+        if mode == "rb":
+            if size is not None:
+                self.size = size
+            else:
+                self.size = self.details["size"]
+            self.cache = caches[cache_type](
+                self.blocksize, self._fetch_range, self.size, **cache_options
+            )
+        else:
+            self.buffer = io.BytesIO()
+            self.offset = None
+            self.forced = False
+            self.location = None
+
+    @property
+    def details(self):
+        if self._details is None:
+            self._details = self.fs.info(self.path)
+        return self._details
+
+    @details.setter
+    def details(self, value):
+        self._details = value
+        self.size = value["size"]
+
+    @property
+    def full_name(self):
+        return _unstrip_protocol(self.path, self.fs)
+
+    @property
+    def closed(self):
+        # get around this attr being read-only in IOBase
+        # use getattr here, since this can be called during del
+        return getattr(self, "_closed", True)
+
+    @closed.setter
+    def closed(self, c):
+        self._closed = c
+
+    def __hash__(self):
+        if "w" in self.mode:
+            return id(self)
+        else:
+            return int(tokenize(self.details), 16)
+
+    def __eq__(self, other):
+        """Files are equal if they have the same checksum, only in read mode"""
+        if self is other:
+            return True
+        return (
+            isinstance(other, type(self))
+            and self.mode == "rb"
+            and other.mode == "rb"
+            and hash(self) == hash(other)
+        )
+
+    def commit(self):
+        """Move from temp to final destination"""
+
+    def discard(self):
+        """Throw away temporary file"""
+
+    def info(self):
+        """File information about this path"""
+        if self.readable():
+            return self.details
+        else:
+            raise ValueError("Info not available while writing")
+
+    def tell(self):
+        """Current file location"""
+        return self.loc
+
+    def seek(self, loc, whence=0):
+        """Set current file location
+
+        Parameters
+        ----------
+        loc: int
+            byte location
+        whence: {0, 1, 2}
+            from start of file, current location or end of file, resp.
+        """
+        loc = int(loc)
+        if not self.mode == "rb":
+            raise OSError(ESPIPE, "Seek only available in read mode")
+        if whence == 0:
+            nloc = loc
+        elif whence == 1:
+            nloc = self.loc + loc
+        elif whence == 2:
+            nloc = self.size + loc
+        else:
+            raise ValueError(f"invalid whence ({whence}, should be 0, 1 or 2)")
+        if nloc < 0:
+            raise ValueError("Seek before start of file")
+        self.loc = nloc
+        return self.loc
+
+    def write(self, data):
+        """
+        Write data to buffer.
+
+        Buffer only sent on flush() or if buffer is greater than
+        or equal to blocksize.
+
+        Parameters
+        ----------
+        data: bytes
+            Set of bytes to be written.
+        """
+        if not self.writable():
+            raise ValueError("File not in write mode")
+        if self.closed:
+            raise ValueError("I/O operation on closed file.")
+        if self.forced:
+            raise ValueError("This file has been force-flushed, can only close")
+        out = self.buffer.write(data)
+        self.loc += out
+        if self.buffer.tell() >= self.blocksize:
+            self.flush()
+        return out
+
+    def flush(self, force=False):
+        """
+        Write buffered data to backend store.
+
+        Writes the current buffer, if it is larger than the block-size, or if
+        the file is being closed.
+
+        Parameters
+        ----------
+        force: bool
+            When closing, write the last block even if it is smaller than
+            blocks are allowed to be. Disallows further writing to this file.
+        """
+
+        if self.closed:
+            raise ValueError("Flush on closed file")
+        if force and self.forced:
+            raise ValueError("Force flush cannot be called more than once")
+        if force:
+            self.forced = True
+
+        if self.readable():
+            # no-op to flush on read-mode
+            return
+
+        if not force and self.buffer.tell() < self.blocksize:
+            # Defer write on small block
+            return
+
+        if self.offset is None:
+            # Initialize a multipart upload
+            self.offset = 0
+            try:
+                self._initiate_upload()
+            except:
+                self.closed = True
+                raise
+
+        if self._upload_chunk(final=force) is not False:
+            self.offset += self.buffer.seek(0, 2)
+            self.buffer = io.BytesIO()
+
+    def _upload_chunk(self, final=False):
+        """Write one part of a multi-block file upload
+
+        Parameters
+        ==========
+        final: bool
+            This is the last block, so should complete file, if
+            self.autocommit is True.
+        """
+        # may not yet have been initialized, may need to call _initialize_upload
+
+    def _initiate_upload(self):
+        """Create remote file/upload"""
+        pass
+
+    def _fetch_range(self, start, end):
+        """Get the specified set of bytes from remote"""
+        return self.fs.cat_file(self.path, start=start, end=end)
+
+    def read(self, length=-1):
+        """
+        Return data from cache, or fetch pieces as necessary
+
+        Parameters
+        ----------
+        length: int (-1)
+            Number of bytes to read; if <0, all remaining bytes.
+        """
+        length = -1 if length is None else int(length)
+        if self.mode != "rb":
+            raise ValueError("File not in read mode")
+        if length < 0:
+            length = self.size - self.loc
+        if self.closed:
+            raise ValueError("I/O operation on closed file.")
+        if length == 0:
+            # don't even bother calling fetch
+            return b""
+        out = self.cache._fetch(self.loc, self.loc + length)
+
+        logger.debug(
+            "%s read: %i - %i %s",
+            self,
+            self.loc,
+            self.loc + length,
+            self.cache._log_stats(),
+        )
+        self.loc += len(out)
+        return out
+
+    def readinto(self, b):
+        """mirrors builtin file's readinto method
+
+        https://docs.python.org/3/library/io.html#io.RawIOBase.readinto
+        """
+        out = memoryview(b).cast("B")
+        data = self.read(out.nbytes)
+        out[: len(data)] = data
+        return len(data)
+
+    def readuntil(self, char=b"\n", blocks=None):
+        """Return data between current position and first occurrence of char
+
+        char is included in the output, except if the end of the tile is
+        encountered first.
+
+        Parameters
+        ----------
+        char: bytes
+            Thing to find
+        blocks: None or int
+            How much to read in each go. Defaults to file blocksize - which may
+            mean a new read on every call.
+        """
+        out = []
+        while True:
+            start = self.tell()
+            part = self.read(blocks or self.blocksize)
+            if len(part) == 0:
+                break
+            found = part.find(char)
+            if found > -1:
+                out.append(part[: found + len(char)])
+                self.seek(start + found + len(char))
+                break
+            out.append(part)
+        return b"".join(out)
+
+    def readline(self):
+        """Read until and including the first occurrence of newline character
+
+        Note that, because of character encoding, this is not necessarily a
+        true line ending.
+        """
+        return self.readuntil(b"\n")
+
+    def __next__(self):
+        out = self.readline()
+        if out:
+            return out
+        raise StopIteration
+
+    def __iter__(self):
+        return self
+
+    def readlines(self):
+        """Return all data, split by the newline character, including the newline character"""
+        data = self.read()
+        lines = data.split(b"\n")
+        out = [l + b"\n" for l in lines[:-1]]
+        if data.endswith(b"\n"):
+            return out
+        else:
+            return out + [lines[-1]]
+        # return list(self)  ???
+
+    def readinto1(self, b):
+        return self.readinto(b)
+
+    def close(self):
+        """Close file
+
+        Finalizes writes, discards cache
+        """
+        if getattr(self, "_unclosable", False):
+            return
+        if self.closed:
+            return
+        try:
+            if self.mode == "rb":
+                self.cache = None
+            else:
+                if not self.forced:
+                    self.flush(force=True)
+
+                if self.fs is not None:
+                    self.fs.invalidate_cache(self.path)
+                    self.fs.invalidate_cache(self.fs._parent(self.path))
+        finally:
+            self.closed = True
+
+    def readable(self):
+        """Whether opened for reading"""
+        return "r" in self.mode and not self.closed
+
+    def seekable(self):
+        """Whether is seekable (only in read mode)"""
+        return self.readable()
+
+    def writable(self):
+        """Whether opened for writing"""
+        return self.mode in {"wb", "ab", "xb"} and not self.closed
+
+    def __reduce__(self):
+        if self.mode != "rb":
+            raise RuntimeError("Pickling a writeable file is not supported")
+
+        return reopen, (
+            self.fs,
+            self.path,
+            self.mode,
+            self.blocksize,
+            self.loc,
+            self.size,
+            self.autocommit,
+            self.cache.name if self.cache else "none",
+            self.kwargs,
+        )
+
+    def __del__(self):
+        if not self.closed:
+            self.close()
+
+    def __str__(self):
+        return f"<File-like object {type(self.fs).__name__}, {self.path}>"
+
+    __repr__ = __str__
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, *args):
+        self.close()
+
+
+def reopen(fs, path, mode, blocksize, loc, size, autocommit, cache_type, kwargs):
+    file = fs.open(
+        path,
+        mode=mode,
+        block_size=blocksize,
+        autocommit=autocommit,
+        cache_type=cache_type,
+        size=size,
+        **kwargs,
+    )
+    if loc > 0:
+        file.seek(loc)
+    return file

.venv/lib/python3.13/site-packages/fsspec/transaction.py

@@ -0,0 +1,90 @@
+from collections import deque
+
+
+class Transaction:
+    """Filesystem transaction write context
+
+    Gathers files for deferred commit or discard, so that several write
+    operations can be finalized semi-atomically. This works by having this
+    instance as the ``.transaction`` attribute of the given filesystem
+    """
+
+    def __init__(self, fs, **kwargs):
+        """
+        Parameters
+        ----------
+        fs: FileSystem instance
+        """
+        self.fs = fs
+        self.files = deque()
+
+    def __enter__(self):
+        self.start()
+        return self
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        """End transaction and commit, if exit is not due to exception"""
+        # only commit if there was no exception
+        self.complete(commit=exc_type is None)
+        if self.fs:
+            self.fs._intrans = False
+            self.fs._transaction = None
+            self.fs = None
+
+    def start(self):
+        """Start a transaction on this FileSystem"""
+        self.files = deque()  # clean up after previous failed completions
+        self.fs._intrans = True
+
+    def complete(self, commit=True):
+        """Finish transaction: commit or discard all deferred files"""
+        while self.files:
+            f = self.files.popleft()
+            if commit:
+                f.commit()
+            else:
+                f.discard()
+        self.fs._intrans = False
+        self.fs._transaction = None
+        self.fs = None
+
+
+class FileActor:
+    def __init__(self):
+        self.files = []
+
+    def commit(self):
+        for f in self.files:
+            f.commit()
+        self.files.clear()
+
+    def discard(self):
+        for f in self.files:
+            f.discard()
+        self.files.clear()
+
+    def append(self, f):
+        self.files.append(f)
+
+
+class DaskTransaction(Transaction):
+    def __init__(self, fs):
+        """
+        Parameters
+        ----------
+        fs: FileSystem instance
+        """
+        import distributed
+
+        super().__init__(fs)
+        client = distributed.default_client()
+        self.files = client.submit(FileActor, actor=True).result()
+
+    def complete(self, commit=True):
+        """Finish transaction: commit or discard all deferred files"""
+        if commit:
+            self.files.commit().result()
+        else:
+            self.files.discard().result()
+        self.fs._intrans = False
+        self.fs = None

.venv/lib/python3.13/site-packages/hf_xet-1.1.5.dist-info/INSTALLER

@@ -0,0 +1 @@
+uv

.venv/lib/python3.13/site-packages/hf_xet-1.1.5.dist-info/METADATA

@@ -0,0 +1,23 @@
+Metadata-Version: 2.4
+Name: hf-xet
+Version: 1.1.5
+Classifier: Programming Language :: Rust
+Classifier: Programming Language :: Python :: Implementation :: CPython
+Classifier: Programming Language :: Python :: Implementation :: PyPy
+Requires-Dist: pytest ; extra == 'tests'
+Provides-Extra: tests
+License-File: LICENSE
+Summary: Fast transfer of large files with the Hugging Face Hub.
+License: Apache-2.0
+Requires-Python: >=3.8
+Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
+Project-URL: Homepage, https://github.com/huggingface/xet-core
+Project-URL: Documentation, https://huggingface.co/docs/hub/en/storage-backends#using-xet-storage
+Project-URL: Issues, https://github.com/huggingface/xet-core/issues
+Project-URL: Repository, https://github.com/huggingface/xet-core.git
+
+# Development Notes
+
+* `pip install maturin`
+* from this directory: `maturin develop`
+

.venv/lib/python3.13/site-packages/hf_xet-1.1.5.dist-info/RECORD

@@ -0,0 +1,8 @@
+hf_xet-1.1.5.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2
+hf_xet-1.1.5.dist-info/METADATA,sha256=jFVsIrpX9kbs_VbMB9_GJtWfiAPSmAB1mR_05mJCQQ8,879
+hf_xet-1.1.5.dist-info/RECORD,,
+hf_xet-1.1.5.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
+hf_xet-1.1.5.dist-info/WHEEL,sha256=UOOOi1PZxNVeqtcDwJVS3yrB4PgYf3v1e9aVmom1HlQ,102
+hf_xet-1.1.5.dist-info/licenses/LICENSE,sha256=xx0jnfkXJvxRnG63LTGOxlggYnIysveWIZ6H3PNdCrQ,11357
+hf_xet/__init__.py,sha256=E8UDdyQ8glZ_nve9hHEf22bPang8-RKx4VuApXYeQUo,107
+hf_xet/hf_xet.abi3.so,sha256=2qK_JJVpRZgvXz1vRtMxN6o08JaOFCOFpQEH4IYmrIo,5469152

.venv/lib/python3.13/site-packages/hf_xet-1.1.5.dist-info/WHEEL

@@ -0,0 +1,4 @@
+Wheel-Version: 1.0
+Generator: maturin (1.8.7)
+Root-Is-Purelib: false
+Tag: cp37-abi3-macosx_11_0_arm64

.venv/lib/python3.13/site-packages/hf_xet/__init__.py

@@ -0,0 +1,5 @@
+from .hf_xet import *
+
+__doc__ = hf_xet.__doc__
+if hasattr(hf_xet, "__all__"):
+    __all__ = hf_xet.__all__

.venv/lib/python3.13/site-packages/huggingface_hub/__init__.py

@@ -0,0 +1,1484 @@
+# Copyright 2020 The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# ***********
+# `huggingface_hub` init has 2 modes:
+# - Normal usage:
+#       If imported to use it, all modules and functions are lazy-loaded. This means
+#       they exist at top level in module but are imported only the first time they are
+#       used. This way, `from huggingface_hub import something` will import `something`
+#       quickly without the hassle of importing all the features from `huggingface_hub`.
+# - Static check:
+#       If statically analyzed, all modules and functions are loaded normally. This way
+#       static typing check works properly as well as autocomplete in text editors and
+#       IDEs.
+#
+# The static model imports are done inside the `if TYPE_CHECKING:` statement at
+# the bottom of this file. Since module/functions imports are duplicated, it is
+# mandatory to make sure to add them twice when adding one. This is checked in the
+# `make quality` command.
+#
+# To update the static imports, please run the following command and commit the changes.
+# ```
+# # Use script
+# python utils/check_static_imports.py --update-file
+#
+# # Or run style on codebase
+# make style
+# ```
+#
+# ***********
+# Lazy loader vendored from https://github.com/scientific-python/lazy_loader
+import importlib
+import os
+import sys
+from typing import TYPE_CHECKING
+
+
+__version__ = "0.33.4"
+
+# Alphabetical order of definitions is ensured in tests
+# WARNING: any comment added in this dictionary definition will be lost when
+# re-generating the file !
+_SUBMOD_ATTRS = {
+    "_commit_scheduler": [
+        "CommitScheduler",
+    ],
+    "_inference_endpoints": [
+        "InferenceEndpoint",
+        "InferenceEndpointError",
+        "InferenceEndpointStatus",
+        "InferenceEndpointTimeoutError",
+        "InferenceEndpointType",
+    ],
+    "_login": [
+        "auth_list",
+        "auth_switch",
+        "interpreter_login",
+        "login",
+        "logout",
+        "notebook_login",
+    ],
+    "_oauth": [
+        "OAuthInfo",
+        "OAuthOrgInfo",
+        "OAuthUserInfo",
+        "attach_huggingface_oauth",
+        "parse_huggingface_oauth",
+    ],
+    "_snapshot_download": [
+        "snapshot_download",
+    ],
+    "_space_api": [
+        "SpaceHardware",
+        "SpaceRuntime",
+        "SpaceStage",
+        "SpaceStorage",
+        "SpaceVariable",
+    ],
+    "_tensorboard_logger": [
+        "HFSummaryWriter",
+    ],
+    "_webhooks_payload": [
+        "WebhookPayload",
+        "WebhookPayloadComment",
+        "WebhookPayloadDiscussion",
+        "WebhookPayloadDiscussionChanges",
+        "WebhookPayloadEvent",
+        "WebhookPayloadMovedTo",
+        "WebhookPayloadRepo",
+        "WebhookPayloadUrl",
+        "WebhookPayloadWebhook",
+    ],
+    "_webhooks_server": [
+        "WebhooksServer",
+        "webhook_endpoint",
+    ],
+    "community": [
+        "Discussion",
+        "DiscussionComment",
+        "DiscussionCommit",
+        "DiscussionEvent",
+        "DiscussionStatusChange",
+        "DiscussionTitleChange",
+        "DiscussionWithDetails",
+    ],
+    "constants": [
+        "CONFIG_NAME",
+        "FLAX_WEIGHTS_NAME",
+        "HUGGINGFACE_CO_URL_HOME",
+        "HUGGINGFACE_CO_URL_TEMPLATE",
+        "PYTORCH_WEIGHTS_NAME",
+        "REPO_TYPE_DATASET",
+        "REPO_TYPE_MODEL",
+        "REPO_TYPE_SPACE",
+        "TF2_WEIGHTS_NAME",
+        "TF_WEIGHTS_NAME",
+    ],
+    "fastai_utils": [
+        "_save_pretrained_fastai",
+        "from_pretrained_fastai",
+        "push_to_hub_fastai",
+    ],
+    "file_download": [
+        "HfFileMetadata",
+        "_CACHED_NO_EXIST",
+        "get_hf_file_metadata",
+        "hf_hub_download",
+        "hf_hub_url",
+        "try_to_load_from_cache",
+    ],
+    "hf_api": [
+        "Collection",
+        "CollectionItem",
+        "CommitInfo",
+        "CommitOperation",
+        "CommitOperationAdd",
+        "CommitOperationCopy",
+        "CommitOperationDelete",
+        "DatasetInfo",
+        "GitCommitInfo",
+        "GitRefInfo",
+        "GitRefs",
+        "HfApi",
+        "ModelInfo",
+        "RepoUrl",
+        "SpaceInfo",
+        "User",
+        "UserLikes",
+        "WebhookInfo",
+        "WebhookWatchedItem",
+        "accept_access_request",
+        "add_collection_item",
+        "add_space_secret",
+        "add_space_variable",
+        "auth_check",
+        "cancel_access_request",
+        "change_discussion_status",
+        "comment_discussion",
+        "create_branch",
+        "create_collection",
+        "create_commit",
+        "create_discussion",
+        "create_inference_endpoint",
+        "create_inference_endpoint_from_catalog",
+        "create_pull_request",
+        "create_repo",
+        "create_tag",
+        "create_webhook",
+        "dataset_info",
+        "delete_branch",
+        "delete_collection",
+        "delete_collection_item",
+        "delete_file",
+        "delete_folder",
+        "delete_inference_endpoint",
+        "delete_repo",
+        "delete_space_secret",
+        "delete_space_storage",
+        "delete_space_variable",
+        "delete_tag",
+        "delete_webhook",
+        "disable_webhook",
+        "duplicate_space",
+        "edit_discussion_comment",
+        "enable_webhook",
+        "file_exists",
+        "get_collection",
+        "get_dataset_tags",
+        "get_discussion_details",
+        "get_full_repo_name",
+        "get_inference_endpoint",
+        "get_model_tags",
+        "get_paths_info",
+        "get_repo_discussions",
+        "get_safetensors_metadata",
+        "get_space_runtime",
+        "get_space_variables",
+        "get_token_permission",
+        "get_user_overview",
+        "get_webhook",
+        "grant_access",
+        "list_accepted_access_requests",
+        "list_collections",
+        "list_datasets",
+        "list_inference_catalog",
+        "list_inference_endpoints",
+        "list_lfs_files",
+        "list_liked_repos",
+        "list_models",
+        "list_organization_members",
+        "list_papers",
+        "list_pending_access_requests",
+        "list_rejected_access_requests",
+        "list_repo_commits",
+        "list_repo_files",
+        "list_repo_likers",
+        "list_repo_refs",
+        "list_repo_tree",
+        "list_spaces",
+        "list_user_followers",
+        "list_user_following",
+        "list_webhooks",
+        "merge_pull_request",
+        "model_info",
+        "move_repo",
+        "paper_info",
+        "parse_safetensors_file_metadata",
+        "pause_inference_endpoint",
+        "pause_space",
+        "permanently_delete_lfs_files",
+        "preupload_lfs_files",
+        "reject_access_request",
+        "rename_discussion",
+        "repo_exists",
+        "repo_info",
+        "repo_type_and_id_from_hf_id",
+        "request_space_hardware",
+        "request_space_storage",
+        "restart_space",
+        "resume_inference_endpoint",
+        "revision_exists",
+        "run_as_future",
+        "scale_to_zero_inference_endpoint",
+        "set_space_sleep_time",
+        "space_info",
+        "super_squash_history",
+        "unlike",
+        "update_collection_item",
+        "update_collection_metadata",
+        "update_inference_endpoint",
+        "update_repo_settings",
+        "update_repo_visibility",
+        "update_webhook",
+        "upload_file",
+        "upload_folder",
+        "upload_large_folder",
+        "whoami",
+    ],
+    "hf_file_system": [
+        "HfFileSystem",
+        "HfFileSystemFile",
+        "HfFileSystemResolvedPath",
+        "HfFileSystemStreamFile",
+    ],
+    "hub_mixin": [
+        "ModelHubMixin",
+        "PyTorchModelHubMixin",
+    ],
+    "inference._client": [
+        "InferenceClient",
+        "InferenceTimeoutError",
+    ],
+    "inference._generated._async_client": [
+        "AsyncInferenceClient",
+    ],
+    "inference._generated.types": [
+        "AudioClassificationInput",
+        "AudioClassificationOutputElement",
+        "AudioClassificationOutputTransform",
+        "AudioClassificationParameters",
+        "AudioToAudioInput",
+        "AudioToAudioOutputElement",
+        "AutomaticSpeechRecognitionEarlyStoppingEnum",
+        "AutomaticSpeechRecognitionGenerationParameters",
+        "AutomaticSpeechRecognitionInput",
+        "AutomaticSpeechRecognitionOutput",
+        "AutomaticSpeechRecognitionOutputChunk",
+        "AutomaticSpeechRecognitionParameters",
+        "ChatCompletionInput",
+        "ChatCompletionInputFunctionDefinition",
+        "ChatCompletionInputFunctionName",
+        "ChatCompletionInputGrammarType",
+        "ChatCompletionInputJSONSchema",
+        "ChatCompletionInputMessage",
+        "ChatCompletionInputMessageChunk",
+        "ChatCompletionInputMessageChunkType",
+        "ChatCompletionInputResponseFormatJSONObject",
+        "ChatCompletionInputResponseFormatJSONSchema",
+        "ChatCompletionInputResponseFormatText",
+        "ChatCompletionInputStreamOptions",
+        "ChatCompletionInputTool",
+        "ChatCompletionInputToolCall",
+        "ChatCompletionInputToolChoiceClass",
+        "ChatCompletionInputToolChoiceEnum",
+        "ChatCompletionInputURL",
+        "ChatCompletionOutput",
+        "ChatCompletionOutputComplete",
+        "ChatCompletionOutputFunctionDefinition",
+        "ChatCompletionOutputLogprob",
+        "ChatCompletionOutputLogprobs",
+        "ChatCompletionOutputMessage",
+        "ChatCompletionOutputToolCall",
+        "ChatCompletionOutputTopLogprob",
+        "ChatCompletionOutputUsage",
+        "ChatCompletionStreamOutput",
+        "ChatCompletionStreamOutputChoice",
+        "ChatCompletionStreamOutputDelta",
+        "ChatCompletionStreamOutputDeltaToolCall",
+        "ChatCompletionStreamOutputFunction",
+        "ChatCompletionStreamOutputLogprob",
+        "ChatCompletionStreamOutputLogprobs",
+        "ChatCompletionStreamOutputTopLogprob",
+        "ChatCompletionStreamOutputUsage",
+        "DepthEstimationInput",
+        "DepthEstimationOutput",
+        "DocumentQuestionAnsweringInput",
+        "DocumentQuestionAnsweringInputData",
+        "DocumentQuestionAnsweringOutputElement",
+        "DocumentQuestionAnsweringParameters",
+        "FeatureExtractionInput",
+        "FeatureExtractionInputTruncationDirection",
+        "FillMaskInput",
+        "FillMaskOutputElement",
+        "FillMaskParameters",
+        "ImageClassificationInput",
+        "ImageClassificationOutputElement",
+        "ImageClassificationOutputTransform",
+        "ImageClassificationParameters",
+        "ImageSegmentationInput",
+        "ImageSegmentationOutputElement",
+        "ImageSegmentationParameters",
+        "ImageSegmentationSubtask",
+        "ImageToImageInput",
+        "ImageToImageOutput",
+        "ImageToImageParameters",
+        "ImageToImageTargetSize",
+        "ImageToTextEarlyStoppingEnum",
+        "ImageToTextGenerationParameters",
+        "ImageToTextInput",
+        "ImageToTextOutput",
+        "ImageToTextParameters",
+        "ObjectDetectionBoundingBox",
+        "ObjectDetectionInput",
+        "ObjectDetectionOutputElement",
+        "ObjectDetectionParameters",
+        "Padding",
+        "QuestionAnsweringInput",
+        "QuestionAnsweringInputData",
+        "QuestionAnsweringOutputElement",
+        "QuestionAnsweringParameters",
+        "SentenceSimilarityInput",
+        "SentenceSimilarityInputData",
+        "SummarizationInput",
+        "SummarizationOutput",
+        "SummarizationParameters",
+        "SummarizationTruncationStrategy",
+        "TableQuestionAnsweringInput",
+        "TableQuestionAnsweringInputData",
+        "TableQuestionAnsweringOutputElement",
+        "TableQuestionAnsweringParameters",
+        "Text2TextGenerationInput",
+        "Text2TextGenerationOutput",
+        "Text2TextGenerationParameters",
+        "Text2TextGenerationTruncationStrategy",
+        "TextClassificationInput",
+        "TextClassificationOutputElement",
+        "TextClassificationOutputTransform",
+        "TextClassificationParameters",
+        "TextGenerationInput",
+        "TextGenerationInputGenerateParameters",
+        "TextGenerationInputGrammarType",
+        "TextGenerationOutput",
+        "TextGenerationOutputBestOfSequence",
+        "TextGenerationOutputDetails",
+        "TextGenerationOutputFinishReason",
+        "TextGenerationOutputPrefillToken",
+        "TextGenerationOutputToken",
+        "TextGenerationStreamOutput",
+        "TextGenerationStreamOutputStreamDetails",
+        "TextGenerationStreamOutputToken",
+        "TextToAudioEarlyStoppingEnum",
+        "TextToAudioGenerationParameters",
+        "TextToAudioInput",
+        "TextToAudioOutput",
+        "TextToAudioParameters",
+        "TextToImageInput",
+        "TextToImageOutput",
+        "TextToImageParameters",
+        "TextToSpeechEarlyStoppingEnum",
+        "TextToSpeechGenerationParameters",
+        "TextToSpeechInput",
+        "TextToSpeechOutput",
+        "TextToSpeechParameters",
+        "TextToVideoInput",
+        "TextToVideoOutput",
+        "TextToVideoParameters",
+        "TokenClassificationAggregationStrategy",
+        "TokenClassificationInput",
+        "TokenClassificationOutputElement",
+        "TokenClassificationParameters",
+        "TranslationInput",
+        "TranslationOutput",
+        "TranslationParameters",
+        "TranslationTruncationStrategy",
+        "TypeEnum",
+        "VideoClassificationInput",
+        "VideoClassificationOutputElement",
+        "VideoClassificationOutputTransform",
+        "VideoClassificationParameters",
+        "VisualQuestionAnsweringInput",
+        "VisualQuestionAnsweringInputData",
+        "VisualQuestionAnsweringOutputElement",
+        "VisualQuestionAnsweringParameters",
+        "ZeroShotClassificationInput",
+        "ZeroShotClassificationOutputElement",
+        "ZeroShotClassificationParameters",
+        "ZeroShotImageClassificationInput",
+        "ZeroShotImageClassificationOutputElement",
+        "ZeroShotImageClassificationParameters",
+        "ZeroShotObjectDetectionBoundingBox",
+        "ZeroShotObjectDetectionInput",
+        "ZeroShotObjectDetectionOutputElement",
+        "ZeroShotObjectDetectionParameters",
+    ],
+    "inference._mcp.agent": [
+        "Agent",
+    ],
+    "inference._mcp.mcp_client": [
+        "MCPClient",
+    ],
+    "inference_api": [
+        "InferenceApi",
+    ],
+    "keras_mixin": [
+        "KerasModelHubMixin",
+        "from_pretrained_keras",
+        "push_to_hub_keras",
+        "save_pretrained_keras",
+    ],
+    "repocard": [
+        "DatasetCard",
+        "ModelCard",
+        "RepoCard",
+        "SpaceCard",
+        "metadata_eval_result",
+        "metadata_load",
+        "metadata_save",
+        "metadata_update",
+    ],
+    "repocard_data": [
+        "CardData",
+        "DatasetCardData",
+        "EvalResult",
+        "ModelCardData",
+        "SpaceCardData",
+    ],
+    "repository": [
+        "Repository",
+    ],
+    "serialization": [
+        "StateDictSplit",
+        "get_tf_storage_size",
+        "get_torch_storage_id",
+        "get_torch_storage_size",
+        "load_state_dict_from_file",
+        "load_torch_model",
+        "save_torch_model",
+        "save_torch_state_dict",
+        "split_state_dict_into_shards_factory",
+        "split_tf_state_dict_into_shards",
+        "split_torch_state_dict_into_shards",
+    ],
+    "serialization._dduf": [
+        "DDUFEntry",
+        "export_entries_as_dduf",
+        "export_folder_as_dduf",
+        "read_dduf_file",
+    ],
+    "utils": [
+        "CacheNotFound",
+        "CachedFileInfo",
+        "CachedRepoInfo",
+        "CachedRevisionInfo",
+        "CorruptedCacheException",
+        "DeleteCacheStrategy",
+        "HFCacheInfo",
+        "HfFolder",
+        "cached_assets_path",
+        "configure_http_backend",
+        "dump_environment_info",
+        "get_session",
+        "get_token",
+        "logging",
+        "scan_cache_dir",
+    ],
+}
+
+# WARNING: __all__ is generated automatically, Any manual edit will be lost when re-generating this file !
+#
+# To update the static imports, please run the following command and commit the changes.
+# ```
+# # Use script
+# python utils/check_all_variable.py --update
+#
+# # Or run style on codebase
+# make style
+# ```
+
+__all__ = [
+    "Agent",
+    "AsyncInferenceClient",
+    "AudioClassificationInput",
+    "AudioClassificationOutputElement",
+    "AudioClassificationOutputTransform",
+    "AudioClassificationParameters",
+    "AudioToAudioInput",
+    "AudioToAudioOutputElement",
+    "AutomaticSpeechRecognitionEarlyStoppingEnum",
+    "AutomaticSpeechRecognitionGenerationParameters",
+    "AutomaticSpeechRecognitionInput",
+    "AutomaticSpeechRecognitionOutput",
+    "AutomaticSpeechRecognitionOutputChunk",
+    "AutomaticSpeechRecognitionParameters",
+    "CONFIG_NAME",
+    "CacheNotFound",
+    "CachedFileInfo",
+    "CachedRepoInfo",
+    "CachedRevisionInfo",
+    "CardData",
+    "ChatCompletionInput",
+    "ChatCompletionInputFunctionDefinition",
+    "ChatCompletionInputFunctionName",
+    "ChatCompletionInputGrammarType",
+    "ChatCompletionInputJSONSchema",
+    "ChatCompletionInputMessage",
+    "ChatCompletionInputMessageChunk",
+    "ChatCompletionInputMessageChunkType",
+    "ChatCompletionInputResponseFormatJSONObject",
+    "ChatCompletionInputResponseFormatJSONSchema",
+    "ChatCompletionInputResponseFormatText",
+    "ChatCompletionInputStreamOptions",
+    "ChatCompletionInputTool",
+    "ChatCompletionInputToolCall",
+    "ChatCompletionInputToolChoiceClass",
+    "ChatCompletionInputToolChoiceEnum",
+    "ChatCompletionInputURL",
+    "ChatCompletionOutput",
+    "ChatCompletionOutputComplete",
+    "ChatCompletionOutputFunctionDefinition",
+    "ChatCompletionOutputLogprob",
+    "ChatCompletionOutputLogprobs",
+    "ChatCompletionOutputMessage",
+    "ChatCompletionOutputToolCall",
+    "ChatCompletionOutputTopLogprob",
+    "ChatCompletionOutputUsage",
+    "ChatCompletionStreamOutput",
+    "ChatCompletionStreamOutputChoice",
+    "ChatCompletionStreamOutputDelta",
+    "ChatCompletionStreamOutputDeltaToolCall",
+    "ChatCompletionStreamOutputFunction",
+    "ChatCompletionStreamOutputLogprob",
+    "ChatCompletionStreamOutputLogprobs",
+    "ChatCompletionStreamOutputTopLogprob",
+    "ChatCompletionStreamOutputUsage",
+    "Collection",
+    "CollectionItem",
+    "CommitInfo",
+    "CommitOperation",
+    "CommitOperationAdd",
+    "CommitOperationCopy",
+    "CommitOperationDelete",
+    "CommitScheduler",
+    "CorruptedCacheException",
+    "DDUFEntry",
+    "DatasetCard",
+    "DatasetCardData",
+    "DatasetInfo",
+    "DeleteCacheStrategy",
+    "DepthEstimationInput",
+    "DepthEstimationOutput",
+    "Discussion",
+    "DiscussionComment",
+    "DiscussionCommit",
+    "DiscussionEvent",
+    "DiscussionStatusChange",
+    "DiscussionTitleChange",
+    "DiscussionWithDetails",
+    "DocumentQuestionAnsweringInput",
+    "DocumentQuestionAnsweringInputData",
+    "DocumentQuestionAnsweringOutputElement",
+    "DocumentQuestionAnsweringParameters",
+    "EvalResult",
+    "FLAX_WEIGHTS_NAME",
+    "FeatureExtractionInput",
+    "FeatureExtractionInputTruncationDirection",
+    "FillMaskInput",
+    "FillMaskOutputElement",
+    "FillMaskParameters",
+    "GitCommitInfo",
+    "GitRefInfo",
+    "GitRefs",
+    "HFCacheInfo",
+    "HFSummaryWriter",
+    "HUGGINGFACE_CO_URL_HOME",
+    "HUGGINGFACE_CO_URL_TEMPLATE",
+    "HfApi",
+    "HfFileMetadata",
+    "HfFileSystem",
+    "HfFileSystemFile",
+    "HfFileSystemResolvedPath",
+    "HfFileSystemStreamFile",
+    "HfFolder",
+    "ImageClassificationInput",
+    "ImageClassificationOutputElement",
+    "ImageClassificationOutputTransform",
+    "ImageClassificationParameters",
+    "ImageSegmentationInput",
+    "ImageSegmentationOutputElement",
+    "ImageSegmentationParameters",
+    "ImageSegmentationSubtask",
+    "ImageToImageInput",
+    "ImageToImageOutput",
+    "ImageToImageParameters",
+    "ImageToImageTargetSize",
+    "ImageToTextEarlyStoppingEnum",
+    "ImageToTextGenerationParameters",
+    "ImageToTextInput",
+    "ImageToTextOutput",
+    "ImageToTextParameters",
+    "InferenceApi",
+    "InferenceClient",
+    "InferenceEndpoint",
+    "InferenceEndpointError",
+    "InferenceEndpointStatus",
+    "InferenceEndpointTimeoutError",
+    "InferenceEndpointType",
+    "InferenceTimeoutError",
+    "KerasModelHubMixin",
+    "MCPClient",
+    "ModelCard",
+    "ModelCardData",
+    "ModelHubMixin",
+    "ModelInfo",
+    "OAuthInfo",
+    "OAuthOrgInfo",
+    "OAuthUserInfo",
+    "ObjectDetectionBoundingBox",
+    "ObjectDetectionInput",
+    "ObjectDetectionOutputElement",
+    "ObjectDetectionParameters",
+    "PYTORCH_WEIGHTS_NAME",
+    "Padding",
+    "PyTorchModelHubMixin",
+    "QuestionAnsweringInput",
+    "QuestionAnsweringInputData",
+    "QuestionAnsweringOutputElement",
+    "QuestionAnsweringParameters",
+    "REPO_TYPE_DATASET",
+    "REPO_TYPE_MODEL",
+    "REPO_TYPE_SPACE",
+    "RepoCard",
+    "RepoUrl",
+    "Repository",
+    "SentenceSimilarityInput",
+    "SentenceSimilarityInputData",
+    "SpaceCard",
+    "SpaceCardData",
+    "SpaceHardware",
+    "SpaceInfo",
+    "SpaceRuntime",
+    "SpaceStage",
+    "SpaceStorage",
+    "SpaceVariable",
+    "StateDictSplit",
+    "SummarizationInput",
+    "SummarizationOutput",
+    "SummarizationParameters",
+    "SummarizationTruncationStrategy",
+    "TF2_WEIGHTS_NAME",
+    "TF_WEIGHTS_NAME",
+    "TableQuestionAnsweringInput",
+    "TableQuestionAnsweringInputData",
+    "TableQuestionAnsweringOutputElement",
+    "TableQuestionAnsweringParameters",
+    "Text2TextGenerationInput",
+    "Text2TextGenerationOutput",
+    "Text2TextGenerationParameters",
+    "Text2TextGenerationTruncationStrategy",
+    "TextClassificationInput",
+    "TextClassificationOutputElement",
+    "TextClassificationOutputTransform",
+    "TextClassificationParameters",
+    "TextGenerationInput",
+    "TextGenerationInputGenerateParameters",
+    "TextGenerationInputGrammarType",
+    "TextGenerationOutput",
+    "TextGenerationOutputBestOfSequence",
+    "TextGenerationOutputDetails",
+    "TextGenerationOutputFinishReason",
+    "TextGenerationOutputPrefillToken",
+    "TextGenerationOutputToken",
+    "TextGenerationStreamOutput",
+    "TextGenerationStreamOutputStreamDetails",
+    "TextGenerationStreamOutputToken",
+    "TextToAudioEarlyStoppingEnum",
+    "TextToAudioGenerationParameters",
+    "TextToAudioInput",
+    "TextToAudioOutput",
+    "TextToAudioParameters",
+    "TextToImageInput",
+    "TextToImageOutput",
+    "TextToImageParameters",
+    "TextToSpeechEarlyStoppingEnum",
+    "TextToSpeechGenerationParameters",
+    "TextToSpeechInput",
+    "TextToSpeechOutput",
+    "TextToSpeechParameters",
+    "TextToVideoInput",
+    "TextToVideoOutput",
+    "TextToVideoParameters",
+    "TokenClassificationAggregationStrategy",
+    "TokenClassificationInput",
+    "TokenClassificationOutputElement",
+    "TokenClassificationParameters",
+    "TranslationInput",
+    "TranslationOutput",
+    "TranslationParameters",
+    "TranslationTruncationStrategy",
+    "TypeEnum",
+    "User",
+    "UserLikes",
+    "VideoClassificationInput",
+    "VideoClassificationOutputElement",
+    "VideoClassificationOutputTransform",
+    "VideoClassificationParameters",
+    "VisualQuestionAnsweringInput",
+    "VisualQuestionAnsweringInputData",
+    "VisualQuestionAnsweringOutputElement",
+    "VisualQuestionAnsweringParameters",
+    "WebhookInfo",
+    "WebhookPayload",
+    "WebhookPayloadComment",
+    "WebhookPayloadDiscussion",
+    "WebhookPayloadDiscussionChanges",
+    "WebhookPayloadEvent",
+    "WebhookPayloadMovedTo",
+    "WebhookPayloadRepo",
+    "WebhookPayloadUrl",
+    "WebhookPayloadWebhook",
+    "WebhookWatchedItem",
+    "WebhooksServer",
+    "ZeroShotClassificationInput",
+    "ZeroShotClassificationOutputElement",
+    "ZeroShotClassificationParameters",
+    "ZeroShotImageClassificationInput",
+    "ZeroShotImageClassificationOutputElement",
+    "ZeroShotImageClassificationParameters",
+    "ZeroShotObjectDetectionBoundingBox",
+    "ZeroShotObjectDetectionInput",
+    "ZeroShotObjectDetectionOutputElement",
+    "ZeroShotObjectDetectionParameters",
+    "_CACHED_NO_EXIST",
+    "_save_pretrained_fastai",
+    "accept_access_request",
+    "add_collection_item",
+    "add_space_secret",
+    "add_space_variable",
+    "attach_huggingface_oauth",
+    "auth_check",
+    "auth_list",
+    "auth_switch",
+    "cached_assets_path",
+    "cancel_access_request",
+    "change_discussion_status",
+    "comment_discussion",
+    "configure_http_backend",
+    "create_branch",
+    "create_collection",
+    "create_commit",
+    "create_discussion",
+    "create_inference_endpoint",
+    "create_inference_endpoint_from_catalog",
+    "create_pull_request",
+    "create_repo",
+    "create_tag",
+    "create_webhook",
+    "dataset_info",
+    "delete_branch",
+    "delete_collection",
+    "delete_collection_item",
+    "delete_file",
+    "delete_folder",
+    "delete_inference_endpoint",
+    "delete_repo",
+    "delete_space_secret",
+    "delete_space_storage",
+    "delete_space_variable",
+    "delete_tag",
+    "delete_webhook",
+    "disable_webhook",
+    "dump_environment_info",
+    "duplicate_space",
+    "edit_discussion_comment",
+    "enable_webhook",
+    "export_entries_as_dduf",
+    "export_folder_as_dduf",
+    "file_exists",
+    "from_pretrained_fastai",
+    "from_pretrained_keras",
+    "get_collection",
+    "get_dataset_tags",
+    "get_discussion_details",
+    "get_full_repo_name",
+    "get_hf_file_metadata",
+    "get_inference_endpoint",
+    "get_model_tags",
+    "get_paths_info",
+    "get_repo_discussions",
+    "get_safetensors_metadata",
+    "get_session",
+    "get_space_runtime",
+    "get_space_variables",
+    "get_tf_storage_size",
+    "get_token",
+    "get_token_permission",
+    "get_torch_storage_id",
+    "get_torch_storage_size",
+    "get_user_overview",
+    "get_webhook",
+    "grant_access",
+    "hf_hub_download",
+    "hf_hub_url",
+    "interpreter_login",
+    "list_accepted_access_requests",
+    "list_collections",
+    "list_datasets",
+    "list_inference_catalog",
+    "list_inference_endpoints",
+    "list_lfs_files",
+    "list_liked_repos",
+    "list_models",
+    "list_organization_members",
+    "list_papers",
+    "list_pending_access_requests",
+    "list_rejected_access_requests",
+    "list_repo_commits",
+    "list_repo_files",
+    "list_repo_likers",
+    "list_repo_refs",
+    "list_repo_tree",
+    "list_spaces",
+    "list_user_followers",
+    "list_user_following",
+    "list_webhooks",
+    "load_state_dict_from_file",
+    "load_torch_model",
+    "logging",
+    "login",
+    "logout",
+    "merge_pull_request",
+    "metadata_eval_result",
+    "metadata_load",
+    "metadata_save",
+    "metadata_update",
+    "model_info",
+    "move_repo",
+    "notebook_login",
+    "paper_info",
+    "parse_huggingface_oauth",
+    "parse_safetensors_file_metadata",
+    "pause_inference_endpoint",
+    "pause_space",
+    "permanently_delete_lfs_files",
+    "preupload_lfs_files",
+    "push_to_hub_fastai",
+    "push_to_hub_keras",
+    "read_dduf_file",
+    "reject_access_request",
+    "rename_discussion",
+    "repo_exists",
+    "repo_info",
+    "repo_type_and_id_from_hf_id",
+    "request_space_hardware",
+    "request_space_storage",
+    "restart_space",
+    "resume_inference_endpoint",
+    "revision_exists",
+    "run_as_future",
+    "save_pretrained_keras",
+    "save_torch_model",
+    "save_torch_state_dict",
+    "scale_to_zero_inference_endpoint",
+    "scan_cache_dir",
+    "set_space_sleep_time",
+    "snapshot_download",
+    "space_info",
+    "split_state_dict_into_shards_factory",
+    "split_tf_state_dict_into_shards",
+    "split_torch_state_dict_into_shards",
+    "super_squash_history",
+    "try_to_load_from_cache",
+    "unlike",
+    "update_collection_item",
+    "update_collection_metadata",
+    "update_inference_endpoint",
+    "update_repo_settings",
+    "update_repo_visibility",
+    "update_webhook",
+    "upload_file",
+    "upload_folder",
+    "upload_large_folder",
+    "webhook_endpoint",
+    "whoami",
+]
+
+
+def _attach(package_name, submodules=None, submod_attrs=None):
+    """Attach lazily loaded submodules, functions, or other attributes.
+
+    Typically, modules import submodules and attributes as follows:
+
+    ```py
+    import mysubmodule
+    import anothersubmodule
+
+    from .foo import someattr
+    ```
+
+    The idea is to replace a package's `__getattr__`, `__dir__`, such that all imports
+    work exactly the way they would with normal imports, except that the import occurs
+    upon first use.
+
+    The typical way to call this function, replacing the above imports, is:
+
+    ```python
+    __getattr__, __dir__ = lazy.attach(
+        __name__,
+        ['mysubmodule', 'anothersubmodule'],
+        {'foo': ['someattr']}
+    )
+    ```
+    This functionality requires Python 3.7 or higher.
+
+    Args:
+        package_name (`str`):
+            Typically use `__name__`.
+        submodules (`set`):
+            List of submodules to attach.
+        submod_attrs (`dict`):
+            Dictionary of submodule -> list of attributes / functions.
+            These attributes are imported as they are used.
+
+    Returns:
+        __getattr__, __dir__, __all__
+
+    """
+    if submod_attrs is None:
+        submod_attrs = {}
+
+    if submodules is None:
+        submodules = set()
+    else:
+        submodules = set(submodules)
+
+    attr_to_modules = {attr: mod for mod, attrs in submod_attrs.items() for attr in attrs}
+
+    def __getattr__(name):
+        if name in submodules:
+            try:
+                return importlib.import_module(f"{package_name}.{name}")
+            except Exception as e:
+                print(f"Error importing {package_name}.{name}: {e}")
+                raise
+        elif name in attr_to_modules:
+            submod_path = f"{package_name}.{attr_to_modules[name]}"
+            try:
+                submod = importlib.import_module(submod_path)
+            except Exception as e:
+                print(f"Error importing {submod_path}: {e}")
+                raise
+            attr = getattr(submod, name)
+
+            # If the attribute lives in a file (module) with the same
+            # name as the attribute, ensure that the attribute and *not*
+            # the module is accessible on the package.
+            if name == attr_to_modules[name]:
+                pkg = sys.modules[package_name]
+                pkg.__dict__[name] = attr
+
+            return attr
+        else:
+            raise AttributeError(f"No {package_name} attribute {name}")
+
+    def __dir__():
+        return __all__
+
+    return __getattr__, __dir__
+
+
+__getattr__, __dir__ = _attach(__name__, submodules=[], submod_attrs=_SUBMOD_ATTRS)
+
+if os.environ.get("EAGER_IMPORT", ""):
+    for attr in __all__:
+        __getattr__(attr)
+
+# WARNING: any content below this statement is generated automatically. Any manual edit
+# will be lost when re-generating this file !
+#
+# To update the static imports, please run the following command and commit the changes.
+# ```
+# # Use script
+# python utils/check_static_imports.py --update
+#
+# # Or run style on codebase
+# make style
+# ```
+if TYPE_CHECKING:  # pragma: no cover
+    from ._commit_scheduler import CommitScheduler  # noqa: F401
+    from ._inference_endpoints import (
+        InferenceEndpoint,  # noqa: F401
+        InferenceEndpointError,  # noqa: F401
+        InferenceEndpointStatus,  # noqa: F401
+        InferenceEndpointTimeoutError,  # noqa: F401
+        InferenceEndpointType,  # noqa: F401
+    )
+    from ._login import (
+        auth_list,  # noqa: F401
+        auth_switch,  # noqa: F401
+        interpreter_login,  # noqa: F401
+        login,  # noqa: F401
+        logout,  # noqa: F401
+        notebook_login,  # noqa: F401
+    )
+    from ._oauth import (
+        OAuthInfo,  # noqa: F401
+        OAuthOrgInfo,  # noqa: F401
+        OAuthUserInfo,  # noqa: F401
+        attach_huggingface_oauth,  # noqa: F401
+        parse_huggingface_oauth,  # noqa: F401
+    )
+    from ._snapshot_download import snapshot_download  # noqa: F401
+    from ._space_api import (
+        SpaceHardware,  # noqa: F401
+        SpaceRuntime,  # noqa: F401
+        SpaceStage,  # noqa: F401
+        SpaceStorage,  # noqa: F401
+        SpaceVariable,  # noqa: F401
+    )
+    from ._tensorboard_logger import HFSummaryWriter  # noqa: F401
+    from ._webhooks_payload import (
+        WebhookPayload,  # noqa: F401
+        WebhookPayloadComment,  # noqa: F401
+        WebhookPayloadDiscussion,  # noqa: F401
+        WebhookPayloadDiscussionChanges,  # noqa: F401
+        WebhookPayloadEvent,  # noqa: F401
+        WebhookPayloadMovedTo,  # noqa: F401
+        WebhookPayloadRepo,  # noqa: F401
+        WebhookPayloadUrl,  # noqa: F401
+        WebhookPayloadWebhook,  # noqa: F401
+    )
+    from ._webhooks_server import (
+        WebhooksServer,  # noqa: F401
+        webhook_endpoint,  # noqa: F401
+    )
+    from .community import (
+        Discussion,  # noqa: F401
+        DiscussionComment,  # noqa: F401
+        DiscussionCommit,  # noqa: F401
+        DiscussionEvent,  # noqa: F401
+        DiscussionStatusChange,  # noqa: F401
+        DiscussionTitleChange,  # noqa: F401
+        DiscussionWithDetails,  # noqa: F401
+    )
+    from .constants import (
+        CONFIG_NAME,  # noqa: F401
+        FLAX_WEIGHTS_NAME,  # noqa: F401
+        HUGGINGFACE_CO_URL_HOME,  # noqa: F401
+        HUGGINGFACE_CO_URL_TEMPLATE,  # noqa: F401
+        PYTORCH_WEIGHTS_NAME,  # noqa: F401
+        REPO_TYPE_DATASET,  # noqa: F401
+        REPO_TYPE_MODEL,  # noqa: F401
+        REPO_TYPE_SPACE,  # noqa: F401
+        TF2_WEIGHTS_NAME,  # noqa: F401
+        TF_WEIGHTS_NAME,  # noqa: F401
+    )
+    from .fastai_utils import (
+        _save_pretrained_fastai,  # noqa: F401
+        from_pretrained_fastai,  # noqa: F401
+        push_to_hub_fastai,  # noqa: F401
+    )
+    from .file_download import (
+        _CACHED_NO_EXIST,  # noqa: F401
+        HfFileMetadata,  # noqa: F401
+        get_hf_file_metadata,  # noqa: F401
+        hf_hub_download,  # noqa: F401
+        hf_hub_url,  # noqa: F401
+        try_to_load_from_cache,  # noqa: F401
+    )
+    from .hf_api import (
+        Collection,  # noqa: F401
+        CollectionItem,  # noqa: F401
+        CommitInfo,  # noqa: F401
+        CommitOperation,  # noqa: F401
+        CommitOperationAdd,  # noqa: F401
+        CommitOperationCopy,  # noqa: F401
+        CommitOperationDelete,  # noqa: F401
+        DatasetInfo,  # noqa: F401
+        GitCommitInfo,  # noqa: F401
+        GitRefInfo,  # noqa: F401
+        GitRefs,  # noqa: F401
+        HfApi,  # noqa: F401
+        ModelInfo,  # noqa: F401
+        RepoUrl,  # noqa: F401
+        SpaceInfo,  # noqa: F401
+        User,  # noqa: F401
+        UserLikes,  # noqa: F401
+        WebhookInfo,  # noqa: F401
+        WebhookWatchedItem,  # noqa: F401
+        accept_access_request,  # noqa: F401
+        add_collection_item,  # noqa: F401
+        add_space_secret,  # noqa: F401
+        add_space_variable,  # noqa: F401
+        auth_check,  # noqa: F401
+        cancel_access_request,  # noqa: F401
+        change_discussion_status,  # noqa: F401
+        comment_discussion,  # noqa: F401
+        create_branch,  # noqa: F401
+        create_collection,  # noqa: F401
+        create_commit,  # noqa: F401
+        create_discussion,  # noqa: F401
+        create_inference_endpoint,  # noqa: F401
+        create_inference_endpoint_from_catalog,  # noqa: F401
+        create_pull_request,  # noqa: F401
+        create_repo,  # noqa: F401
+        create_tag,  # noqa: F401
+        create_webhook,  # noqa: F401
+        dataset_info,  # noqa: F401
+        delete_branch,  # noqa: F401
+        delete_collection,  # noqa: F401
+        delete_collection_item,  # noqa: F401
+        delete_file,  # noqa: F401
+        delete_folder,  # noqa: F401
+        delete_inference_endpoint,  # noqa: F401
+        delete_repo,  # noqa: F401
+        delete_space_secret,  # noqa: F401
+        delete_space_storage,  # noqa: F401
+        delete_space_variable,  # noqa: F401
+        delete_tag,  # noqa: F401
+        delete_webhook,  # noqa: F401
+        disable_webhook,  # noqa: F401
+        duplicate_space,  # noqa: F401
+        edit_discussion_comment,  # noqa: F401
+        enable_webhook,  # noqa: F401
+        file_exists,  # noqa: F401
+        get_collection,  # noqa: F401
+        get_dataset_tags,  # noqa: F401
+        get_discussion_details,  # noqa: F401
+        get_full_repo_name,  # noqa: F401
+        get_inference_endpoint,  # noqa: F401
+        get_model_tags,  # noqa: F401
+        get_paths_info,  # noqa: F401
+        get_repo_discussions,  # noqa: F401
+        get_safetensors_metadata,  # noqa: F401
+        get_space_runtime,  # noqa: F401
+        get_space_variables,  # noqa: F401
+        get_token_permission,  # noqa: F401
+        get_user_overview,  # noqa: F401
+        get_webhook,  # noqa: F401
+        grant_access,  # noqa: F401
+        list_accepted_access_requests,  # noqa: F401
+        list_collections,  # noqa: F401
+        list_datasets,  # noqa: F401
+        list_inference_catalog,  # noqa: F401
+        list_inference_endpoints,  # noqa: F401
+        list_lfs_files,  # noqa: F401
+        list_liked_repos,  # noqa: F401
+        list_models,  # noqa: F401
+        list_organization_members,  # noqa: F401
+        list_papers,  # noqa: F401
+        list_pending_access_requests,  # noqa: F401
+        list_rejected_access_requests,  # noqa: F401
+        list_repo_commits,  # noqa: F401
+        list_repo_files,  # noqa: F401
+        list_repo_likers,  # noqa: F401
+        list_repo_refs,  # noqa: F401
+        list_repo_tree,  # noqa: F401
+        list_spaces,  # noqa: F401
+        list_user_followers,  # noqa: F401
+        list_user_following,  # noqa: F401
+        list_webhooks,  # noqa: F401
+        merge_pull_request,  # noqa: F401
+        model_info,  # noqa: F401
+        move_repo,  # noqa: F401
+        paper_info,  # noqa: F401
+        parse_safetensors_file_metadata,  # noqa: F401
+        pause_inference_endpoint,  # noqa: F401
+        pause_space,  # noqa: F401
+        permanently_delete_lfs_files,  # noqa: F401
+        preupload_lfs_files,  # noqa: F401
+        reject_access_request,  # noqa: F401
+        rename_discussion,  # noqa: F401
+        repo_exists,  # noqa: F401
+        repo_info,  # noqa: F401
+        repo_type_and_id_from_hf_id,  # noqa: F401
+        request_space_hardware,  # noqa: F401
+        request_space_storage,  # noqa: F401
+        restart_space,  # noqa: F401
+        resume_inference_endpoint,  # noqa: F401
+        revision_exists,  # noqa: F401
+        run_as_future,  # noqa: F401
+        scale_to_zero_inference_endpoint,  # noqa: F401
+        set_space_sleep_time,  # noqa: F401
+        space_info,  # noqa: F401
+        super_squash_history,  # noqa: F401
+        unlike,  # noqa: F401
+        update_collection_item,  # noqa: F401
+        update_collection_metadata,  # noqa: F401
+        update_inference_endpoint,  # noqa: F401
+        update_repo_settings,  # noqa: F401
+        update_repo_visibility,  # noqa: F401
+        update_webhook,  # noqa: F401
+        upload_file,  # noqa: F401
+        upload_folder,  # noqa: F401
+        upload_large_folder,  # noqa: F401
+        whoami,  # noqa: F401
+    )
+    from .hf_file_system import (
+        HfFileSystem,  # noqa: F401
+        HfFileSystemFile,  # noqa: F401
+        HfFileSystemResolvedPath,  # noqa: F401
+        HfFileSystemStreamFile,  # noqa: F401
+    )
+    from .hub_mixin import (
+        ModelHubMixin,  # noqa: F401
+        PyTorchModelHubMixin,  # noqa: F401
+    )
+    from .inference._client import (
+        InferenceClient,  # noqa: F401
+        InferenceTimeoutError,  # noqa: F401
+    )
+    from .inference._generated._async_client import AsyncInferenceClient  # noqa: F401
+    from .inference._generated.types import (
+        AudioClassificationInput,  # noqa: F401
+        AudioClassificationOutputElement,  # noqa: F401
+        AudioClassificationOutputTransform,  # noqa: F401
+        AudioClassificationParameters,  # noqa: F401
+        AudioToAudioInput,  # noqa: F401
+        AudioToAudioOutputElement,  # noqa: F401
+        AutomaticSpeechRecognitionEarlyStoppingEnum,  # noqa: F401
+        AutomaticSpeechRecognitionGenerationParameters,  # noqa: F401
+        AutomaticSpeechRecognitionInput,  # noqa: F401
+        AutomaticSpeechRecognitionOutput,  # noqa: F401
+        AutomaticSpeechRecognitionOutputChunk,  # noqa: F401
+        AutomaticSpeechRecognitionParameters,  # noqa: F401
+        ChatCompletionInput,  # noqa: F401
+        ChatCompletionInputFunctionDefinition,  # noqa: F401
+        ChatCompletionInputFunctionName,  # noqa: F401
+        ChatCompletionInputGrammarType,  # noqa: F401
+        ChatCompletionInputJSONSchema,  # noqa: F401
+        ChatCompletionInputMessage,  # noqa: F401
+        ChatCompletionInputMessageChunk,  # noqa: F401
+        ChatCompletionInputMessageChunkType,  # noqa: F401
+        ChatCompletionInputResponseFormatJSONObject,  # noqa: F401
+        ChatCompletionInputResponseFormatJSONSchema,  # noqa: F401
+        ChatCompletionInputResponseFormatText,  # noqa: F401
+        ChatCompletionInputStreamOptions,  # noqa: F401
+        ChatCompletionInputTool,  # noqa: F401
+        ChatCompletionInputToolCall,  # noqa: F401
+        ChatCompletionInputToolChoiceClass,  # noqa: F401
+        ChatCompletionInputToolChoiceEnum,  # noqa: F401
+        ChatCompletionInputURL,  # noqa: F401
+        ChatCompletionOutput,  # noqa: F401
+        ChatCompletionOutputComplete,  # noqa: F401
+        ChatCompletionOutputFunctionDefinition,  # noqa: F401
+        ChatCompletionOutputLogprob,  # noqa: F401
+        ChatCompletionOutputLogprobs,  # noqa: F401
+        ChatCompletionOutputMessage,  # noqa: F401
+        ChatCompletionOutputToolCall,  # noqa: F401
+        ChatCompletionOutputTopLogprob,  # noqa: F401
+        ChatCompletionOutputUsage,  # noqa: F401
+        ChatCompletionStreamOutput,  # noqa: F401
+        ChatCompletionStreamOutputChoice,  # noqa: F401
+        ChatCompletionStreamOutputDelta,  # noqa: F401
+        ChatCompletionStreamOutputDeltaToolCall,  # noqa: F401
+        ChatCompletionStreamOutputFunction,  # noqa: F401
+        ChatCompletionStreamOutputLogprob,  # noqa: F401
+        ChatCompletionStreamOutputLogprobs,  # noqa: F401
+        ChatCompletionStreamOutputTopLogprob,  # noqa: F401
+        ChatCompletionStreamOutputUsage,  # noqa: F401
+        DepthEstimationInput,  # noqa: F401
+        DepthEstimationOutput,  # noqa: F401
+        DocumentQuestionAnsweringInput,  # noqa: F401
+        DocumentQuestionAnsweringInputData,  # noqa: F401
+        DocumentQuestionAnsweringOutputElement,  # noqa: F401
+        DocumentQuestionAnsweringParameters,  # noqa: F401
+        FeatureExtractionInput,  # noqa: F401
+        FeatureExtractionInputTruncationDirection,  # noqa: F401
+        FillMaskInput,  # noqa: F401
+        FillMaskOutputElement,  # noqa: F401
+        FillMaskParameters,  # noqa: F401
+        ImageClassificationInput,  # noqa: F401
+        ImageClassificationOutputElement,  # noqa: F401
+        ImageClassificationOutputTransform,  # noqa: F401
+        ImageClassificationParameters,  # noqa: F401
+        ImageSegmentationInput,  # noqa: F401
+        ImageSegmentationOutputElement,  # noqa: F401
+        ImageSegmentationParameters,  # noqa: F401
+        ImageSegmentationSubtask,  # noqa: F401
+        ImageToImageInput,  # noqa: F401
+        ImageToImageOutput,  # noqa: F401
+        ImageToImageParameters,  # noqa: F401
+        ImageToImageTargetSize,  # noqa: F401
+        ImageToTextEarlyStoppingEnum,  # noqa: F401
+        ImageToTextGenerationParameters,  # noqa: F401
+        ImageToTextInput,  # noqa: F401
+        ImageToTextOutput,  # noqa: F401
+        ImageToTextParameters,  # noqa: F401
+        ObjectDetectionBoundingBox,  # noqa: F401
+        ObjectDetectionInput,  # noqa: F401
+        ObjectDetectionOutputElement,  # noqa: F401
+        ObjectDetectionParameters,  # noqa: F401
+        Padding,  # noqa: F401
+        QuestionAnsweringInput,  # noqa: F401
+        QuestionAnsweringInputData,  # noqa: F401
+        QuestionAnsweringOutputElement,  # noqa: F401
+        QuestionAnsweringParameters,  # noqa: F401
+        SentenceSimilarityInput,  # noqa: F401
+        SentenceSimilarityInputData,  # noqa: F401
+        SummarizationInput,  # noqa: F401
+        SummarizationOutput,  # noqa: F401
+        SummarizationParameters,  # noqa: F401
+        SummarizationTruncationStrategy,  # noqa: F401
+        TableQuestionAnsweringInput,  # noqa: F401
+        TableQuestionAnsweringInputData,  # noqa: F401
+        TableQuestionAnsweringOutputElement,  # noqa: F401
+        TableQuestionAnsweringParameters,  # noqa: F401
+        Text2TextGenerationInput,  # noqa: F401
+        Text2TextGenerationOutput,  # noqa: F401
+        Text2TextGenerationParameters,  # noqa: F401
+        Text2TextGenerationTruncationStrategy,  # noqa: F401
+        TextClassificationInput,  # noqa: F401
+        TextClassificationOutputElement,  # noqa: F401
+        TextClassificationOutputTransform,  # noqa: F401
+        TextClassificationParameters,  # noqa: F401
+        TextGenerationInput,  # noqa: F401
+        TextGenerationInputGenerateParameters,  # noqa: F401
+        TextGenerationInputGrammarType,  # noqa: F401
+        TextGenerationOutput,  # noqa: F401
+        TextGenerationOutputBestOfSequence,  # noqa: F401
+        TextGenerationOutputDetails,  # noqa: F401
+        TextGenerationOutputFinishReason,  # noqa: F401
+        TextGenerationOutputPrefillToken,  # noqa: F401
+        TextGenerationOutputToken,  # noqa: F401
+        TextGenerationStreamOutput,  # noqa: F401
+        TextGenerationStreamOutputStreamDetails,  # noqa: F401
+        TextGenerationStreamOutputToken,  # noqa: F401
+        TextToAudioEarlyStoppingEnum,  # noqa: F401
+        TextToAudioGenerationParameters,  # noqa: F401
+        TextToAudioInput,  # noqa: F401
+        TextToAudioOutput,  # noqa: F401
+        TextToAudioParameters,  # noqa: F401
+        TextToImageInput,  # noqa: F401
+        TextToImageOutput,  # noqa: F401
+        TextToImageParameters,  # noqa: F401
+        TextToSpeechEarlyStoppingEnum,  # noqa: F401
+        TextToSpeechGenerationParameters,  # noqa: F401
+        TextToSpeechInput,  # noqa: F401
+        TextToSpeechOutput,  # noqa: F401
+        TextToSpeechParameters,  # noqa: F401
+        TextToVideoInput,  # noqa: F401
+        TextToVideoOutput,  # noqa: F401
+        TextToVideoParameters,  # noqa: F401
+        TokenClassificationAggregationStrategy,  # noqa: F401
+        TokenClassificationInput,  # noqa: F401
+        TokenClassificationOutputElement,  # noqa: F401
+        TokenClassificationParameters,  # noqa: F401
+        TranslationInput,  # noqa: F401
+        TranslationOutput,  # noqa: F401
+        TranslationParameters,  # noqa: F401
+        TranslationTruncationStrategy,  # noqa: F401
+        TypeEnum,  # noqa: F401
+        VideoClassificationInput,  # noqa: F401
+        VideoClassificationOutputElement,  # noqa: F401
+        VideoClassificationOutputTransform,  # noqa: F401
+        VideoClassificationParameters,  # noqa: F401
+        VisualQuestionAnsweringInput,  # noqa: F401
+        VisualQuestionAnsweringInputData,  # noqa: F401
+        VisualQuestionAnsweringOutputElement,  # noqa: F401
+        VisualQuestionAnsweringParameters,  # noqa: F401
+        ZeroShotClassificationInput,  # noqa: F401
+        ZeroShotClassificationOutputElement,  # noqa: F401
+        ZeroShotClassificationParameters,  # noqa: F401
+        ZeroShotImageClassificationInput,  # noqa: F401
+        ZeroShotImageClassificationOutputElement,  # noqa: F401
+        ZeroShotImageClassificationParameters,  # noqa: F401
+        ZeroShotObjectDetectionBoundingBox,  # noqa: F401
+        ZeroShotObjectDetectionInput,  # noqa: F401
+        ZeroShotObjectDetectionOutputElement,  # noqa: F401
+        ZeroShotObjectDetectionParameters,  # noqa: F401
+    )
+    from .inference._mcp.agent import Agent  # noqa: F401
+    from .inference._mcp.mcp_client import MCPClient  # noqa: F401
+    from .inference_api import InferenceApi  # noqa: F401
+    from .keras_mixin import (
+        KerasModelHubMixin,  # noqa: F401
+        from_pretrained_keras,  # noqa: F401
+        push_to_hub_keras,  # noqa: F401
+        save_pretrained_keras,  # noqa: F401
+    )
+    from .repocard import (
+        DatasetCard,  # noqa: F401
+        ModelCard,  # noqa: F401
+        RepoCard,  # noqa: F401
+        SpaceCard,  # noqa: F401
+        metadata_eval_result,  # noqa: F401
+        metadata_load,  # noqa: F401
+        metadata_save,  # noqa: F401
+        metadata_update,  # noqa: F401
+    )
+    from .repocard_data import (
+        CardData,  # noqa: F401
+        DatasetCardData,  # noqa: F401
+        EvalResult,  # noqa: F401
+        ModelCardData,  # noqa: F401
+        SpaceCardData,  # noqa: F401
+    )
+    from .repository import Repository  # noqa: F401
+    from .serialization import (
+        StateDictSplit,  # noqa: F401
+        get_tf_storage_size,  # noqa: F401
+        get_torch_storage_id,  # noqa: F401
+        get_torch_storage_size,  # noqa: F401
+        load_state_dict_from_file,  # noqa: F401
+        load_torch_model,  # noqa: F401
+        save_torch_model,  # noqa: F401
+        save_torch_state_dict,  # noqa: F401
+        split_state_dict_into_shards_factory,  # noqa: F401
+        split_tf_state_dict_into_shards,  # noqa: F401
+        split_torch_state_dict_into_shards,  # noqa: F401
+    )
+    from .serialization._dduf import (
+        DDUFEntry,  # noqa: F401
+        export_entries_as_dduf,  # noqa: F401
+        export_folder_as_dduf,  # noqa: F401
+        read_dduf_file,  # noqa: F401
+    )
+    from .utils import (
+        CachedFileInfo,  # noqa: F401
+        CachedRepoInfo,  # noqa: F401
+        CachedRevisionInfo,  # noqa: F401
+        CacheNotFound,  # noqa: F401
+        CorruptedCacheException,  # noqa: F401
+        DeleteCacheStrategy,  # noqa: F401
+        HFCacheInfo,  # noqa: F401
+        HfFolder,  # noqa: F401
+        cached_assets_path,  # noqa: F401
+        configure_http_backend,  # noqa: F401
+        dump_environment_info,  # noqa: F401
+        get_session,  # noqa: F401
+        get_token,  # noqa: F401
+        logging,  # noqa: F401
+        scan_cache_dir,  # noqa: F401
+    )

.venv/lib/python3.13/site-packages/huggingface_hub/_commit_api.py

@@ -0,0 +1,915 @@
+"""
+Type definitions and utilities for the `create_commit` API
+"""
+
+import base64
+import io
+import math
+import os
+import warnings
+from collections import defaultdict
+from contextlib import contextmanager
+from dataclasses import dataclass, field
+from itertools import groupby
+from pathlib import Path, PurePosixPath
+from typing import TYPE_CHECKING, Any, BinaryIO, Dict, Iterable, Iterator, List, Literal, Optional, Tuple, Union
+
+from tqdm.contrib.concurrent import thread_map
+
+from . import constants
+from .errors import EntryNotFoundError, HfHubHTTPError, XetAuthorizationError, XetRefreshTokenError
+from .file_download import hf_hub_url
+from .lfs import UploadInfo, lfs_upload, post_lfs_batch_info
+from .utils import (
+    FORBIDDEN_FOLDERS,
+    XetTokenType,
+    chunk_iterable,
+    fetch_xet_connection_info_from_repo_info,
+    get_session,
+    hf_raise_for_status,
+    logging,
+    sha,
+    tqdm_stream_file,
+    validate_hf_hub_args,
+)
+from .utils import tqdm as hf_tqdm
+from .utils.tqdm import _get_progress_bar_context
+
+
+if TYPE_CHECKING:
+    from .hf_api import RepoFile
+
+
+logger = logging.get_logger(__name__)
+
+
+UploadMode = Literal["lfs", "regular"]
+
+# Max is 1,000 per request on the Hub for HfApi.get_paths_info
+# Otherwise we get:
+# HfHubHTTPError: 413 Client Error: Payload Too Large for url: https://huggingface.co/api/datasets/xxx (Request ID: xxx)\n\ntoo many parameters
+# See https://github.com/huggingface/huggingface_hub/issues/1503
+FETCH_LFS_BATCH_SIZE = 500
+
+UPLOAD_BATCH_MAX_NUM_FILES = 256
+
+
+@dataclass
+class CommitOperationDelete:
+    """
+    Data structure holding necessary info to delete a file or a folder from a repository
+    on the Hub.
+
+    Args:
+        path_in_repo (`str`):
+            Relative filepath in the repo, for example: `"checkpoints/1fec34a/weights.bin"`
+            for a file or `"checkpoints/1fec34a/"` for a folder.
+        is_folder (`bool` or `Literal["auto"]`, *optional*)
+            Whether the Delete Operation applies to a folder or not. If "auto", the path
+            type (file or folder) is guessed automatically by looking if path ends with
+            a "/" (folder) or not (file). To explicitly set the path type, you can set
+            `is_folder=True` or `is_folder=False`.
+    """
+
+    path_in_repo: str
+    is_folder: Union[bool, Literal["auto"]] = "auto"
+
+    def __post_init__(self):
+        self.path_in_repo = _validate_path_in_repo(self.path_in_repo)
+
+        if self.is_folder == "auto":
+            self.is_folder = self.path_in_repo.endswith("/")
+        if not isinstance(self.is_folder, bool):
+            raise ValueError(
+                f"Wrong value for `is_folder`. Must be one of [`True`, `False`, `'auto'`]. Got '{self.is_folder}'."
+            )
+
+
+@dataclass
+class CommitOperationCopy:
+    """
+    Data structure holding necessary info to copy a file in a repository on the Hub.
+
+    Limitations:
+      - Only LFS files can be copied. To copy a regular file, you need to download it locally and re-upload it
+      - Cross-repository copies are not supported.
+
+    Note: you can combine a [`CommitOperationCopy`] and a [`CommitOperationDelete`] to rename an LFS file on the Hub.
+
+    Args:
+        src_path_in_repo (`str`):
+            Relative filepath in the repo of the file to be copied, e.g. `"checkpoints/1fec34a/weights.bin"`.
+        path_in_repo (`str`):
+            Relative filepath in the repo where to copy the file, e.g. `"checkpoints/1fec34a/weights_copy.bin"`.
+        src_revision (`str`, *optional*):
+            The git revision of the file to be copied. Can be any valid git revision.
+            Default to the target commit revision.
+    """
+
+    src_path_in_repo: str
+    path_in_repo: str
+    src_revision: Optional[str] = None
+    # set to the OID of the file to be copied if it has already been uploaded
+    # useful to determine if a commit will be empty or not.
+    _src_oid: Optional[str] = None
+    # set to the OID of the file to copy to if it has already been uploaded
+    # useful to determine if a commit will be empty or not.
+    _dest_oid: Optional[str] = None
+
+    def __post_init__(self):
+        self.src_path_in_repo = _validate_path_in_repo(self.src_path_in_repo)
+        self.path_in_repo = _validate_path_in_repo(self.path_in_repo)
+
+
+@dataclass
+class CommitOperationAdd:
+    """
+    Data structure holding necessary info to upload a file to a repository on the Hub.
+
+    Args:
+        path_in_repo (`str`):
+            Relative filepath in the repo, for example: `"checkpoints/1fec34a/weights.bin"`
+        path_or_fileobj (`str`, `Path`, `bytes`, or `BinaryIO`):
+            Either:
+            - a path to a local file (as `str` or `pathlib.Path`) to upload
+            - a buffer of bytes (`bytes`) holding the content of the file to upload
+            - a "file object" (subclass of `io.BufferedIOBase`), typically obtained
+                with `open(path, "rb")`. It must support `seek()` and `tell()` methods.
+
+    Raises:
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+            If `path_or_fileobj` is not one of `str`, `Path`, `bytes` or `io.BufferedIOBase`.
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+            If `path_or_fileobj` is a `str` or `Path` but not a path to an existing file.
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+            If `path_or_fileobj` is a `io.BufferedIOBase` but it doesn't support both
+            `seek()` and `tell()`.
+    """
+
+    path_in_repo: str
+    path_or_fileobj: Union[str, Path, bytes, BinaryIO]
+    upload_info: UploadInfo = field(init=False, repr=False)
+
+    # Internal attributes
+
+    # set to "lfs" or "regular" once known
+    _upload_mode: Optional[UploadMode] = field(init=False, repr=False, default=None)
+
+    # set to True if .gitignore rules prevent the file from being uploaded as LFS
+    # (server-side check)
+    _should_ignore: Optional[bool] = field(init=False, repr=False, default=None)
+
+    # set to the remote OID of the file if it has already been uploaded
+    # useful to determine if a commit will be empty or not
+    _remote_oid: Optional[str] = field(init=False, repr=False, default=None)
+
+    # set to True once the file has been uploaded as LFS
+    _is_uploaded: bool = field(init=False, repr=False, default=False)
+
+    # set to True once the file has been committed
+    _is_committed: bool = field(init=False, repr=False, default=False)
+
+    def __post_init__(self) -> None:
+        """Validates `path_or_fileobj` and compute `upload_info`."""
+        self.path_in_repo = _validate_path_in_repo(self.path_in_repo)
+
+        # Validate `path_or_fileobj` value
+        if isinstance(self.path_or_fileobj, Path):
+            self.path_or_fileobj = str(self.path_or_fileobj)
+        if isinstance(self.path_or_fileobj, str):
+            path_or_fileobj = os.path.normpath(os.path.expanduser(self.path_or_fileobj))
+            if not os.path.isfile(path_or_fileobj):
+                raise ValueError(f"Provided path: '{path_or_fileobj}' is not a file on the local file system")
+        elif not isinstance(self.path_or_fileobj, (io.BufferedIOBase, bytes)):
+            # ^^ Inspired from: https://stackoverflow.com/questions/44584829/how-to-determine-if-file-is-opened-in-binary-or-text-mode
+            raise ValueError(
+                "path_or_fileobj must be either an instance of str, bytes or"
+                " io.BufferedIOBase. If you passed a file-like object, make sure it is"
+                " in binary mode."
+            )
+        if isinstance(self.path_or_fileobj, io.BufferedIOBase):
+            try:
+                self.path_or_fileobj.tell()
+                self.path_or_fileobj.seek(0, os.SEEK_CUR)
+            except (OSError, AttributeError) as exc:
+                raise ValueError(
+                    "path_or_fileobj is a file-like object but does not implement seek() and tell()"
+                ) from exc
+
+        # Compute "upload_info" attribute
+        if isinstance(self.path_or_fileobj, str):
+            self.upload_info = UploadInfo.from_path(self.path_or_fileobj)
+        elif isinstance(self.path_or_fileobj, bytes):
+            self.upload_info = UploadInfo.from_bytes(self.path_or_fileobj)
+        else:
+            self.upload_info = UploadInfo.from_fileobj(self.path_or_fileobj)
+
+    @contextmanager
+    def as_file(self, with_tqdm: bool = False) -> Iterator[BinaryIO]:
+        """
+        A context manager that yields a file-like object allowing to read the underlying
+        data behind `path_or_fileobj`.
+
+        Args:
+            with_tqdm (`bool`, *optional*, defaults to `False`):
+                If True, iterating over the file object will display a progress bar. Only
+                works if the file-like object is a path to a file. Pure bytes and buffers
+                are not supported.
+
+        Example:
+
+        ```python
+        >>> operation = CommitOperationAdd(
+        ...        path_in_repo="remote/dir/weights.h5",
+        ...        path_or_fileobj="./local/weights.h5",
+        ... )
+        CommitOperationAdd(path_in_repo='remote/dir/weights.h5', path_or_fileobj='./local/weights.h5')
+
+        >>> with operation.as_file() as file:
+        ...     content = file.read()
+
+        >>> with operation.as_file(with_tqdm=True) as file:
+        ...     while True:
+        ...         data = file.read(1024)
+        ...         if not data:
+        ...              break
+        config.json: 100%|█████████████████████████| 8.19k/8.19k [00:02<00:00, 3.72kB/s]
+
+        >>> with operation.as_file(with_tqdm=True) as file:
+        ...     requests.put(..., data=file)
+        config.json: 100%|█████████████████████████| 8.19k/8.19k [00:02<00:00, 3.72kB/s]
+        ```
+        """
+        if isinstance(self.path_or_fileobj, str) or isinstance(self.path_or_fileobj, Path):
+            if with_tqdm:
+                with tqdm_stream_file(self.path_or_fileobj) as file:
+                    yield file
+            else:
+                with open(self.path_or_fileobj, "rb") as file:
+                    yield file
+        elif isinstance(self.path_or_fileobj, bytes):
+            yield io.BytesIO(self.path_or_fileobj)
+        elif isinstance(self.path_or_fileobj, io.BufferedIOBase):
+            prev_pos = self.path_or_fileobj.tell()
+            yield self.path_or_fileobj
+            self.path_or_fileobj.seek(prev_pos, io.SEEK_SET)
+
+    def b64content(self) -> bytes:
+        """
+        The base64-encoded content of `path_or_fileobj`
+
+        Returns: `bytes`
+        """
+        with self.as_file() as file:
+            return base64.b64encode(file.read())
+
+    @property
+    def _local_oid(self) -> Optional[str]:
+        """Return the OID of the local file.
+
+        This OID is then compared to `self._remote_oid` to check if the file has changed compared to the remote one.
+        If the file did not change, we won't upload it again to prevent empty commits.
+
+        For LFS files, the OID corresponds to the SHA256 of the file content (used a LFS ref).
+        For regular files, the OID corresponds to the SHA1 of the file content.
+        Note: this is slightly different to git OID computation since the oid of an LFS file is usually the git-SHA1 of the
+              pointer file content (not the actual file content). However, using the SHA256 is enough to detect changes
+              and more convenient client-side.
+        """
+        if self._upload_mode is None:
+            return None
+        elif self._upload_mode == "lfs":
+            return self.upload_info.sha256.hex()
+        else:
+            # Regular file => compute sha1
+            # => no need to read by chunk since the file is guaranteed to be <=5MB.
+            with self.as_file() as file:
+                return sha.git_hash(file.read())
+
+
+def _validate_path_in_repo(path_in_repo: str) -> str:
+    # Validate `path_in_repo` value to prevent a server-side issue
+    if path_in_repo.startswith("/"):
+        path_in_repo = path_in_repo[1:]
+    if path_in_repo == "." or path_in_repo == ".." or path_in_repo.startswith("../"):
+        raise ValueError(f"Invalid `path_in_repo` in CommitOperation: '{path_in_repo}'")
+    if path_in_repo.startswith("./"):
+        path_in_repo = path_in_repo[2:]
+    for forbidden in FORBIDDEN_FOLDERS:
+        if any(part == forbidden for part in path_in_repo.split("/")):
+            raise ValueError(
+                f"Invalid `path_in_repo` in CommitOperation: cannot update files under a '{forbidden}/' folder (path:"
+                f" '{path_in_repo}')."
+            )
+    return path_in_repo
+
+
+CommitOperation = Union[CommitOperationAdd, CommitOperationCopy, CommitOperationDelete]
+
+
+def _warn_on_overwriting_operations(operations: List[CommitOperation]) -> None:
+    """
+    Warn user when a list of operations is expected to overwrite itself in a single
+    commit.
+
+    Rules:
+    - If a filepath is updated by multiple `CommitOperationAdd` operations, a warning
+      message is triggered.
+    - If a filepath is updated at least once by a `CommitOperationAdd` and then deleted
+      by a `CommitOperationDelete`, a warning is triggered.
+    - If a `CommitOperationDelete` deletes a filepath that is then updated by a
+      `CommitOperationAdd`, no warning is triggered. This is usually useless (no need to
+      delete before upload) but can happen if a user deletes an entire folder and then
+      add new files to it.
+    """
+    nb_additions_per_path: Dict[str, int] = defaultdict(int)
+    for operation in operations:
+        path_in_repo = operation.path_in_repo
+        if isinstance(operation, CommitOperationAdd):
+            if nb_additions_per_path[path_in_repo] > 0:
+                warnings.warn(
+                    "About to update multiple times the same file in the same commit:"
+                    f" '{path_in_repo}'. This can cause undesired inconsistencies in"
+                    " your repo."
+                )
+            nb_additions_per_path[path_in_repo] += 1
+            for parent in PurePosixPath(path_in_repo).parents:
+                # Also keep track of number of updated files per folder
+                # => warns if deleting a folder overwrite some contained files
+                nb_additions_per_path[str(parent)] += 1
+        if isinstance(operation, CommitOperationDelete):
+            if nb_additions_per_path[str(PurePosixPath(path_in_repo))] > 0:
+                if operation.is_folder:
+                    warnings.warn(
+                        "About to delete a folder containing files that have just been"
+                        f" updated within the same commit: '{path_in_repo}'. This can"
+                        " cause undesired inconsistencies in your repo."
+                    )
+                else:
+                    warnings.warn(
+                        "About to delete a file that have just been updated within the"
+                        f" same commit: '{path_in_repo}'. This can cause undesired"
+                        " inconsistencies in your repo."
+                    )
+
+
+@validate_hf_hub_args
+def _upload_lfs_files(
+    *,
+    additions: List[CommitOperationAdd],
+    repo_type: str,
+    repo_id: str,
+    headers: Dict[str, str],
+    endpoint: Optional[str] = None,
+    num_threads: int = 5,
+    revision: Optional[str] = None,
+):
+    """
+    Uploads the content of `additions` to the Hub using the large file storage protocol.
+
+    Relevant external documentation:
+        - LFS Batch API: https://github.com/git-lfs/git-lfs/blob/main/docs/api/batch.md
+
+    Args:
+        additions (`List` of `CommitOperationAdd`):
+            The files to be uploaded
+        repo_type (`str`):
+            Type of the repo to upload to: `"model"`, `"dataset"` or `"space"`.
+        repo_id (`str`):
+            A namespace (user or an organization) and a repo name separated
+            by a `/`.
+        headers (`Dict[str, str]`):
+            Headers to use for the request, including authorization headers and user agent.
+        num_threads (`int`, *optional*):
+            The number of concurrent threads to use when uploading. Defaults to 5.
+        revision (`str`, *optional*):
+            The git revision to upload to.
+
+    Raises:
+        [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+            If an upload failed for any reason
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+            If the server returns malformed responses
+        [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+            If the LFS batch endpoint returned an HTTP error.
+    """
+    # Step 1: retrieve upload instructions from the LFS batch endpoint.
+    #         Upload instructions are retrieved by chunk of 256 files to avoid reaching
+    #         the payload limit.
+    batch_actions: List[Dict] = []
+    for chunk in chunk_iterable(additions, chunk_size=UPLOAD_BATCH_MAX_NUM_FILES):
+        batch_actions_chunk, batch_errors_chunk = post_lfs_batch_info(
+            upload_infos=[op.upload_info for op in chunk],
+            repo_id=repo_id,
+            repo_type=repo_type,
+            revision=revision,
+            endpoint=endpoint,
+            headers=headers,
+            token=None,  # already passed in 'headers'
+        )
+
+        # If at least 1 error, we do not retrieve information for other chunks
+        if batch_errors_chunk:
+            message = "\n".join(
+                [
+                    f"Encountered error for file with OID {err.get('oid')}: `{err.get('error', {}).get('message')}"
+                    for err in batch_errors_chunk
+                ]
+            )
+            raise ValueError(f"LFS batch endpoint returned errors:\n{message}")
+
+        batch_actions += batch_actions_chunk
+    oid2addop = {add_op.upload_info.sha256.hex(): add_op for add_op in additions}
+
+    # Step 2: ignore files that have already been uploaded
+    filtered_actions = []
+    for action in batch_actions:
+        if action.get("actions") is None:
+            logger.debug(
+                f"Content of file {oid2addop[action['oid']].path_in_repo} is already"
+                " present upstream - skipping upload."
+            )
+        else:
+            filtered_actions.append(action)
+
+    if len(filtered_actions) == 0:
+        logger.debug("No LFS files to upload.")
+        return
+
+    # Step 3: upload files concurrently according to these instructions
+    def _wrapped_lfs_upload(batch_action) -> None:
+        try:
+            operation = oid2addop[batch_action["oid"]]
+            lfs_upload(operation=operation, lfs_batch_action=batch_action, headers=headers, endpoint=endpoint)
+        except Exception as exc:
+            raise RuntimeError(f"Error while uploading '{operation.path_in_repo}' to the Hub.") from exc
+
+    if constants.HF_HUB_ENABLE_HF_TRANSFER:
+        logger.debug(f"Uploading {len(filtered_actions)} LFS files to the Hub using `hf_transfer`.")
+        for action in hf_tqdm(filtered_actions, name="huggingface_hub.lfs_upload"):
+            _wrapped_lfs_upload(action)
+    elif len(filtered_actions) == 1:
+        logger.debug("Uploading 1 LFS file to the Hub")
+        _wrapped_lfs_upload(filtered_actions[0])
+    else:
+        logger.debug(
+            f"Uploading {len(filtered_actions)} LFS files to the Hub using up to {num_threads} threads concurrently"
+        )
+        thread_map(
+            _wrapped_lfs_upload,
+            filtered_actions,
+            desc=f"Upload {len(filtered_actions)} LFS files",
+            max_workers=num_threads,
+            tqdm_class=hf_tqdm,
+        )
+
+
+@validate_hf_hub_args
+def _upload_xet_files(
+    *,
+    additions: List[CommitOperationAdd],
+    repo_type: str,
+    repo_id: str,
+    headers: Dict[str, str],
+    endpoint: Optional[str] = None,
+    revision: Optional[str] = None,
+    create_pr: Optional[bool] = None,
+):
+    """
+    Uploads the content of `additions` to the Hub using the xet storage protocol.
+    This chunks the files and deduplicates the chunks before uploading them to xetcas storage.
+
+    Args:
+        additions (`List` of `CommitOperationAdd`):
+            The files to be uploaded.
+        repo_type (`str`):
+            Type of the repo to upload to: `"model"`, `"dataset"` or `"space"`.
+        repo_id (`str`):
+            A namespace (user or an organization) and a repo name separated
+            by a `/`.
+        headers (`Dict[str, str]`):
+            Headers to use for the request, including authorization headers and user agent.
+        endpoint: (`str`, *optional*):
+            The endpoint to use for the xetcas service. Defaults to `constants.ENDPOINT`.
+        revision (`str`, *optional*):
+            The git revision to upload to.
+        create_pr (`bool`, *optional*):
+            Whether or not to create a Pull Request with that commit.
+
+    Raises:
+        [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+            If an upload failed for any reason.
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+            If the server returns malformed responses or if the user is unauthorized to upload to xet storage.
+        [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+            If the LFS batch endpoint returned an HTTP error.
+
+    **How it works:**
+        The file download system uses Xet storage, which is a content-addressable storage system that breaks files into chunks
+            for efficient storage and transfer.
+
+        `hf_xet.upload_files` manages uploading files by:
+            - Taking a list of file paths to upload
+            - Breaking files into smaller chunks for efficient storage
+            - Avoiding duplicate storage by recognizing identical chunks across files
+            - Connecting to a storage server (CAS server) that manages these chunks
+
+        The upload process works like this:
+        1. Create a local folder at ~/.cache/huggingface/xet/chunk-cache to store file chunks for reuse.
+        2. Process files in parallel (up to 8 files at once):
+            2.1. Read the file content.
+            2.2. Split the file content into smaller chunks based on content patterns: each chunk gets a unique ID based on what's in it.
+            2.3. For each chunk:
+                - Check if it already exists in storage.
+                - Skip uploading chunks that already exist.
+            2.4. Group chunks into larger blocks for efficient transfer.
+            2.5. Upload these blocks to the storage server.
+            2.6. Create and upload information about how the file is structured.
+        3. Return reference files that contain information about the uploaded files, which can be used later to download them.
+    """
+    if len(additions) == 0:
+        return
+    # at this point, we know that hf_xet is installed
+    from hf_xet import upload_bytes, upload_files
+
+    try:
+        xet_connection_info = fetch_xet_connection_info_from_repo_info(
+            token_type=XetTokenType.WRITE,
+            repo_id=repo_id,
+            repo_type=repo_type,
+            revision=revision,
+            headers=headers,
+            endpoint=endpoint,
+            params={"create_pr": "1"} if create_pr else None,
+        )
+    except HfHubHTTPError as e:
+        if e.response.status_code == 401:
+            raise XetAuthorizationError(
+                f"You are unauthorized to upload to xet storage for {repo_type}/{repo_id}. "
+                f"Please check that you have configured your access token with write access to the repo."
+            ) from e
+        raise
+
+    xet_endpoint = xet_connection_info.endpoint
+    access_token_info = (xet_connection_info.access_token, xet_connection_info.expiration_unix_epoch)
+
+    def token_refresher() -> Tuple[str, int]:
+        new_xet_connection = fetch_xet_connection_info_from_repo_info(
+            token_type=XetTokenType.WRITE,
+            repo_id=repo_id,
+            repo_type=repo_type,
+            revision=revision,
+            headers=headers,
+            endpoint=endpoint,
+            params={"create_pr": "1"} if create_pr else None,
+        )
+        if new_xet_connection is None:
+            raise XetRefreshTokenError("Failed to refresh xet token")
+        return new_xet_connection.access_token, new_xet_connection.expiration_unix_epoch
+
+    num_chunks = math.ceil(len(additions) / UPLOAD_BATCH_MAX_NUM_FILES)
+    num_chunks_num_digits = int(math.log10(num_chunks)) + 1
+    for i, chunk in enumerate(chunk_iterable(additions, chunk_size=UPLOAD_BATCH_MAX_NUM_FILES)):
+        _chunk = [op for op in chunk]
+
+        bytes_ops = [op for op in _chunk if isinstance(op.path_or_fileobj, bytes)]
+        paths_ops = [op for op in _chunk if isinstance(op.path_or_fileobj, (str, Path))]
+        expected_size = sum(op.upload_info.size for op in bytes_ops + paths_ops)
+
+        if num_chunks > 1:
+            description = f"Uploading Batch [{str(i + 1).zfill(num_chunks_num_digits)}/{num_chunks}]..."
+        else:
+            description = "Uploading..."
+        progress_cm = _get_progress_bar_context(
+            desc=description,
+            total=expected_size,
+            initial=0,
+            unit="B",
+            unit_scale=True,
+            name="huggingface_hub.xet_put",
+            log_level=logger.getEffectiveLevel(),
+        )
+        with progress_cm as progress:
+
+            def update_progress(increment: int):
+                progress.update(increment)
+
+            if len(paths_ops) > 0:
+                upload_files(
+                    [str(op.path_or_fileobj) for op in paths_ops],
+                    xet_endpoint,
+                    access_token_info,
+                    token_refresher,
+                    update_progress,
+                    repo_type,
+                )
+            if len(bytes_ops) > 0:
+                upload_bytes(
+                    [op.path_or_fileobj for op in bytes_ops],
+                    xet_endpoint,
+                    access_token_info,
+                    token_refresher,
+                    update_progress,
+                    repo_type,
+                )
+    return
+
+
+def _validate_preupload_info(preupload_info: dict):
+    files = preupload_info.get("files")
+    if not isinstance(files, list):
+        raise ValueError("preupload_info is improperly formatted")
+    for file_info in files:
+        if not (
+            isinstance(file_info, dict)
+            and isinstance(file_info.get("path"), str)
+            and isinstance(file_info.get("uploadMode"), str)
+            and (file_info["uploadMode"] in ("lfs", "regular"))
+        ):
+            raise ValueError("preupload_info is improperly formatted:")
+    return preupload_info
+
+
+@validate_hf_hub_args
+def _fetch_upload_modes(
+    additions: Iterable[CommitOperationAdd],
+    repo_type: str,
+    repo_id: str,
+    headers: Dict[str, str],
+    revision: str,
+    endpoint: Optional[str] = None,
+    create_pr: bool = False,
+    gitignore_content: Optional[str] = None,
+) -> None:
+    """
+    Requests the Hub "preupload" endpoint to determine whether each input file should be uploaded as a regular git blob,
+    as a git LFS blob, or as a XET file. Input `additions` are mutated in-place with the upload mode.
+
+    Args:
+        additions (`Iterable` of :class:`CommitOperationAdd`):
+            Iterable of :class:`CommitOperationAdd` describing the files to
+            upload to the Hub.
+        repo_type (`str`):
+            Type of the repo to upload to: `"model"`, `"dataset"` or `"space"`.
+        repo_id (`str`):
+            A namespace (user or an organization) and a repo name separated
+            by a `/`.
+        headers (`Dict[str, str]`):
+            Headers to use for the request, including authorization headers and user agent.
+        revision (`str`):
+            The git revision to upload the files to. Can be any valid git revision.
+        gitignore_content (`str`, *optional*):
+            The content of the `.gitignore` file to know which files should be ignored. The order of priority
+            is to first check if `gitignore_content` is passed, then check if the `.gitignore` file is present
+            in the list of files to commit and finally default to the `.gitignore` file already hosted on the Hub
+            (if any).
+    Raises:
+        [`~utils.HfHubHTTPError`]
+            If the Hub API returned an error.
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+            If the Hub API response is improperly formatted.
+    """
+    endpoint = endpoint if endpoint is not None else constants.ENDPOINT
+
+    # Fetch upload mode (LFS or regular) chunk by chunk.
+    upload_modes: Dict[str, UploadMode] = {}
+    should_ignore_info: Dict[str, bool] = {}
+    oid_info: Dict[str, Optional[str]] = {}
+
+    for chunk in chunk_iterable(additions, 256):
+        payload: Dict = {
+            "files": [
+                {
+                    "path": op.path_in_repo,
+                    "sample": base64.b64encode(op.upload_info.sample).decode("ascii"),
+                    "size": op.upload_info.size,
+                }
+                for op in chunk
+            ]
+        }
+        if gitignore_content is not None:
+            payload["gitIgnore"] = gitignore_content
+
+        resp = get_session().post(
+            f"{endpoint}/api/{repo_type}s/{repo_id}/preupload/{revision}",
+            json=payload,
+            headers=headers,
+            params={"create_pr": "1"} if create_pr else None,
+        )
+        hf_raise_for_status(resp)
+        preupload_info = _validate_preupload_info(resp.json())
+        upload_modes.update(**{file["path"]: file["uploadMode"] for file in preupload_info["files"]})
+        should_ignore_info.update(**{file["path"]: file["shouldIgnore"] for file in preupload_info["files"]})
+        oid_info.update(**{file["path"]: file.get("oid") for file in preupload_info["files"]})
+
+    # Set upload mode for each addition operation
+    for addition in additions:
+        addition._upload_mode = upload_modes[addition.path_in_repo]
+        addition._should_ignore = should_ignore_info[addition.path_in_repo]
+        addition._remote_oid = oid_info[addition.path_in_repo]
+
+    # Empty files cannot be uploaded as LFS (S3 would fail with a 501 Not Implemented)
+    # => empty files are uploaded as "regular" to still allow users to commit them.
+    for addition in additions:
+        if addition.upload_info.size == 0:
+            addition._upload_mode = "regular"
+
+
+@validate_hf_hub_args
+def _fetch_files_to_copy(
+    copies: Iterable[CommitOperationCopy],
+    repo_type: str,
+    repo_id: str,
+    headers: Dict[str, str],
+    revision: str,
+    endpoint: Optional[str] = None,
+) -> Dict[Tuple[str, Optional[str]], Union["RepoFile", bytes]]:
+    """
+    Fetch information about the files to copy.
+
+    For LFS files, we only need their metadata (file size and sha256) while for regular files
+    we need to download the raw content from the Hub.
+
+    Args:
+        copies (`Iterable` of :class:`CommitOperationCopy`):
+            Iterable of :class:`CommitOperationCopy` describing the files to
+            copy on the Hub.
+        repo_type (`str`):
+            Type of the repo to upload to: `"model"`, `"dataset"` or `"space"`.
+        repo_id (`str`):
+            A namespace (user or an organization) and a repo name separated
+            by a `/`.
+        headers (`Dict[str, str]`):
+            Headers to use for the request, including authorization headers and user agent.
+        revision (`str`):
+            The git revision to upload the files to. Can be any valid git revision.
+
+    Returns: `Dict[Tuple[str, Optional[str]], Union[RepoFile, bytes]]]`
+        Key is the file path and revision of the file to copy.
+        Value is the raw content as bytes (for regular files) or the file information as a RepoFile (for LFS files).
+
+    Raises:
+        [`~utils.HfHubHTTPError`]
+            If the Hub API returned an error.
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+            If the Hub API response is improperly formatted.
+    """
+    from .hf_api import HfApi, RepoFolder
+
+    hf_api = HfApi(endpoint=endpoint, headers=headers)
+    files_to_copy: Dict[Tuple[str, Optional[str]], Union["RepoFile", bytes]] = {}
+    # Store (path, revision) -> oid mapping
+    oid_info: Dict[Tuple[str, Optional[str]], Optional[str]] = {}
+    # 1. Fetch OIDs for destination paths in batches.
+    dest_paths = [op.path_in_repo for op in copies]
+    for offset in range(0, len(dest_paths), FETCH_LFS_BATCH_SIZE):
+        dest_repo_files = hf_api.get_paths_info(
+            repo_id=repo_id,
+            paths=dest_paths[offset : offset + FETCH_LFS_BATCH_SIZE],
+            revision=revision,
+            repo_type=repo_type,
+        )
+        for file in dest_repo_files:
+            if not isinstance(file, RepoFolder):
+                oid_info[(file.path, revision)] = file.blob_id
+
+    # 2. Group by source revision and fetch source file info in batches.
+    for src_revision, operations in groupby(copies, key=lambda op: op.src_revision):
+        operations = list(operations)  # type: ignore
+        src_paths = [op.src_path_in_repo for op in operations]
+        for offset in range(0, len(src_paths), FETCH_LFS_BATCH_SIZE):
+            src_repo_files = hf_api.get_paths_info(
+                repo_id=repo_id,
+                paths=src_paths[offset : offset + FETCH_LFS_BATCH_SIZE],
+                revision=src_revision or revision,
+                repo_type=repo_type,
+            )
+
+            for src_repo_file in src_repo_files:
+                if isinstance(src_repo_file, RepoFolder):
+                    raise NotImplementedError("Copying a folder is not implemented.")
+                oid_info[(src_repo_file.path, src_revision)] = src_repo_file.blob_id
+                # If it's an LFS file, store the RepoFile object. Otherwise, download raw bytes.
+                if src_repo_file.lfs:
+                    files_to_copy[(src_repo_file.path, src_revision)] = src_repo_file
+                else:
+                    # TODO: (optimization) download regular files to copy concurrently
+                    url = hf_hub_url(
+                        endpoint=endpoint,
+                        repo_type=repo_type,
+                        repo_id=repo_id,
+                        revision=src_revision or revision,
+                        filename=src_repo_file.path,
+                    )
+                    response = get_session().get(url, headers=headers)
+                    hf_raise_for_status(response)
+                    files_to_copy[(src_repo_file.path, src_revision)] = response.content
+        # 3. Ensure all operations found a corresponding file in the Hub
+        #  and track src/dest OIDs for each operation.
+        for operation in operations:
+            if (operation.src_path_in_repo, src_revision) not in files_to_copy:
+                raise EntryNotFoundError(
+                    f"Cannot copy {operation.src_path_in_repo} at revision "
+                    f"{src_revision or revision}: file is missing on repo."
+                )
+            operation._src_oid = oid_info.get((operation.src_path_in_repo, operation.src_revision))
+            operation._dest_oid = oid_info.get((operation.path_in_repo, revision))
+    return files_to_copy
+
+
+def _prepare_commit_payload(
+    operations: Iterable[CommitOperation],
+    files_to_copy: Dict[Tuple[str, Optional[str]], Union["RepoFile", bytes]],
+    commit_message: str,
+    commit_description: Optional[str] = None,
+    parent_commit: Optional[str] = None,
+) -> Iterable[Dict[str, Any]]:
+    """
+    Builds the payload to POST to the `/commit` API of the Hub.
+
+    Payload is returned as an iterator so that it can be streamed as a ndjson in the
+    POST request.
+
+    For more information, see:
+        - https://github.com/huggingface/huggingface_hub/issues/1085#issuecomment-1265208073
+        - http://ndjson.org/
+    """
+    commit_description = commit_description if commit_description is not None else ""
+
+    # 1. Send a header item with the commit metadata
+    header_value = {"summary": commit_message, "description": commit_description}
+    if parent_commit is not None:
+        header_value["parentCommit"] = parent_commit
+    yield {"key": "header", "value": header_value}
+
+    nb_ignored_files = 0
+
+    # 2. Send operations, one per line
+    for operation in operations:
+        # Skip ignored files
+        if isinstance(operation, CommitOperationAdd) and operation._should_ignore:
+            logger.debug(f"Skipping file '{operation.path_in_repo}' in commit (ignored by gitignore file).")
+            nb_ignored_files += 1
+            continue
+
+        # 2.a. Case adding a regular file
+        if isinstance(operation, CommitOperationAdd) and operation._upload_mode == "regular":
+            yield {
+                "key": "file",
+                "value": {
+                    "content": operation.b64content().decode(),
+                    "path": operation.path_in_repo,
+                    "encoding": "base64",
+                },
+            }
+        # 2.b. Case adding an LFS file
+        elif isinstance(operation, CommitOperationAdd) and operation._upload_mode == "lfs":
+            yield {
+                "key": "lfsFile",
+                "value": {
+                    "path": operation.path_in_repo,
+                    "algo": "sha256",
+                    "oid": operation.upload_info.sha256.hex(),
+                    "size": operation.upload_info.size,
+                },
+            }
+        # 2.c. Case deleting a file or folder
+        elif isinstance(operation, CommitOperationDelete):
+            yield {
+                "key": "deletedFolder" if operation.is_folder else "deletedFile",
+                "value": {"path": operation.path_in_repo},
+            }
+        # 2.d. Case copying a file or folder
+        elif isinstance(operation, CommitOperationCopy):
+            file_to_copy = files_to_copy[(operation.src_path_in_repo, operation.src_revision)]
+            if isinstance(file_to_copy, bytes):
+                yield {
+                    "key": "file",
+                    "value": {
+                        "content": base64.b64encode(file_to_copy).decode(),
+                        "path": operation.path_in_repo,
+                        "encoding": "base64",
+                    },
+                }
+            elif file_to_copy.lfs:
+                yield {
+                    "key": "lfsFile",
+                    "value": {
+                        "path": operation.path_in_repo,
+                        "algo": "sha256",
+                        "oid": file_to_copy.lfs.sha256,
+                    },
+                }
+            else:
+                raise ValueError(
+                    "Malformed files_to_copy (should be raw file content as bytes or RepoFile objects with LFS info."
+                )
+        # 2.e. Never expected to happen
+        else:
+            raise ValueError(
+                f"Unknown operation to commit. Operation: {operation}. Upload mode:"
+                f" {getattr(operation, '_upload_mode', None)}"
+            )
+
+    if nb_ignored_files > 0:
+        logger.info(f"Skipped {nb_ignored_files} file(s) in commit (ignored by gitignore file).")

.venv/lib/python3.13/site-packages/huggingface_hub/_commit_scheduler.py

@@ -0,0 +1,353 @@
+import atexit
+import logging
+import os
+import time
+from concurrent.futures import Future
+from dataclasses import dataclass
+from io import SEEK_END, SEEK_SET, BytesIO
+from pathlib import Path
+from threading import Lock, Thread
+from typing import Dict, List, Optional, Union
+
+from .hf_api import DEFAULT_IGNORE_PATTERNS, CommitInfo, CommitOperationAdd, HfApi
+from .utils import filter_repo_objects
+
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass(frozen=True)
+class _FileToUpload:
+    """Temporary dataclass to store info about files to upload. Not meant to be used directly."""
+
+    local_path: Path
+    path_in_repo: str
+    size_limit: int
+    last_modified: float
+
+
+class CommitScheduler:
+    """
+    Scheduler to upload a local folder to the Hub at regular intervals (e.g. push to hub every 5 minutes).
+
+    The recommended way to use the scheduler is to use it as a context manager. This ensures that the scheduler is
+    properly stopped and the last commit is triggered when the script ends. The scheduler can also be stopped manually
+    with the `stop` method. Checkout the [upload guide](https://huggingface.co/docs/huggingface_hub/guides/upload#scheduled-uploads)
+    to learn more about how to use it.
+
+    Args:
+        repo_id (`str`):
+            The id of the repo to commit to.
+        folder_path (`str` or `Path`):
+            Path to the local folder to upload regularly.
+        every (`int` or `float`, *optional*):
+            The number of minutes between each commit. Defaults to 5 minutes.
+        path_in_repo (`str`, *optional*):
+            Relative path of the directory in the repo, for example: `"checkpoints/"`. Defaults to the root folder
+            of the repository.
+        repo_type (`str`, *optional*):
+            The type of the repo to commit to. Defaults to `model`.
+        revision (`str`, *optional*):
+            The revision of the repo to commit to. Defaults to `main`.
+        private (`bool`, *optional*):
+            Whether to make the repo private. If `None` (default), the repo will be public unless the organization's default is private. This value is ignored if the repo already exists.
+        token (`str`, *optional*):
+            The token to use to commit to the repo. Defaults to the token saved on the machine.
+        allow_patterns (`List[str]` or `str`, *optional*):
+            If provided, only files matching at least one pattern are uploaded.
+        ignore_patterns (`List[str]` or `str`, *optional*):
+            If provided, files matching any of the patterns are not uploaded.
+        squash_history (`bool`, *optional*):
+            Whether to squash the history of the repo after each commit. Defaults to `False`. Squashing commits is
+            useful to avoid degraded performances on the repo when it grows too large.
+        hf_api (`HfApi`, *optional*):
+            The [`HfApi`] client to use to commit to the Hub. Can be set with custom settings (user agent, token,...).
+
+    Example:
+    ```py
+    >>> from pathlib import Path
+    >>> from huggingface_hub import CommitScheduler
+
+    # Scheduler uploads every 10 minutes
+    >>> csv_path = Path("watched_folder/data.csv")
+    >>> CommitScheduler(repo_id="test_scheduler", repo_type="dataset", folder_path=csv_path.parent, every=10)
+
+    >>> with csv_path.open("a") as f:
+    ...     f.write("first line")
+
+    # Some time later (...)
+    >>> with csv_path.open("a") as f:
+    ...     f.write("second line")
+    ```
+
+    Example using a context manager:
+    ```py
+    >>> from pathlib import Path
+    >>> from huggingface_hub import CommitScheduler
+
+    >>> with CommitScheduler(repo_id="test_scheduler", repo_type="dataset", folder_path="watched_folder", every=10) as scheduler:
+    ...     csv_path = Path("watched_folder/data.csv")
+    ...     with csv_path.open("a") as f:
+    ...         f.write("first line")
+    ...     (...)
+    ...     with csv_path.open("a") as f:
+    ...         f.write("second line")
+
+    # Scheduler is now stopped and last commit have been triggered
+    ```
+    """
+
+    def __init__(
+        self,
+        *,
+        repo_id: str,
+        folder_path: Union[str, Path],
+        every: Union[int, float] = 5,
+        path_in_repo: Optional[str] = None,
+        repo_type: Optional[str] = None,
+        revision: Optional[str] = None,
+        private: Optional[bool] = None,
+        token: Optional[str] = None,
+        allow_patterns: Optional[Union[List[str], str]] = None,
+        ignore_patterns: Optional[Union[List[str], str]] = None,
+        squash_history: bool = False,
+        hf_api: Optional["HfApi"] = None,
+    ) -> None:
+        self.api = hf_api or HfApi(token=token)
+
+        # Folder
+        self.folder_path = Path(folder_path).expanduser().resolve()
+        self.path_in_repo = path_in_repo or ""
+        self.allow_patterns = allow_patterns
+
+        if ignore_patterns is None:
+            ignore_patterns = []
+        elif isinstance(ignore_patterns, str):
+            ignore_patterns = [ignore_patterns]
+        self.ignore_patterns = ignore_patterns + DEFAULT_IGNORE_PATTERNS
+
+        if self.folder_path.is_file():
+            raise ValueError(f"'folder_path' must be a directory, not a file: '{self.folder_path}'.")
+        self.folder_path.mkdir(parents=True, exist_ok=True)
+
+        # Repository
+        repo_url = self.api.create_repo(repo_id=repo_id, private=private, repo_type=repo_type, exist_ok=True)
+        self.repo_id = repo_url.repo_id
+        self.repo_type = repo_type
+        self.revision = revision
+        self.token = token
+
+        # Keep track of already uploaded files
+        self.last_uploaded: Dict[Path, float] = {}  # key is local path, value is timestamp
+
+        # Scheduler
+        if not every > 0:
+            raise ValueError(f"'every' must be a positive integer, not '{every}'.")
+        self.lock = Lock()
+        self.every = every
+        self.squash_history = squash_history
+
+        logger.info(f"Scheduled job to push '{self.folder_path}' to '{self.repo_id}' every {self.every} minutes.")
+        self._scheduler_thread = Thread(target=self._run_scheduler, daemon=True)
+        self._scheduler_thread.start()
+        atexit.register(self._push_to_hub)
+
+        self.__stopped = False
+
+    def stop(self) -> None:
+        """Stop the scheduler.
+
+        A stopped scheduler cannot be restarted. Mostly for tests purposes.
+        """
+        self.__stopped = True
+
+    def __enter__(self) -> "CommitScheduler":
+        return self
+
+    def __exit__(self, exc_type, exc_value, traceback) -> None:
+        # Upload last changes before exiting
+        self.trigger().result()
+        self.stop()
+        return
+
+    def _run_scheduler(self) -> None:
+        """Dumb thread waiting between each scheduled push to Hub."""
+        while True:
+            self.last_future = self.trigger()
+            time.sleep(self.every * 60)
+            if self.__stopped:
+                break
+
+    def trigger(self) -> Future:
+        """Trigger a `push_to_hub` and return a future.
+
+        This method is automatically called every `every` minutes. You can also call it manually to trigger a commit
+        immediately, without waiting for the next scheduled commit.
+        """
+        return self.api.run_as_future(self._push_to_hub)
+
+    def _push_to_hub(self) -> Optional[CommitInfo]:
+        if self.__stopped:  # If stopped, already scheduled commits are ignored
+            return None
+
+        logger.info("(Background) scheduled commit triggered.")
+        try:
+            value = self.push_to_hub()
+            if self.squash_history:
+                logger.info("(Background) squashing repo history.")
+                self.api.super_squash_history(repo_id=self.repo_id, repo_type=self.repo_type, branch=self.revision)
+            return value
+        except Exception as e:
+            logger.error(f"Error while pushing to Hub: {e}")  # Depending on the setup, error might be silenced
+            raise
+
+    def push_to_hub(self) -> Optional[CommitInfo]:
+        """
+        Push folder to the Hub and return the commit info.
+
+        <Tip warning={true}>
+
+        This method is not meant to be called directly. It is run in the background by the scheduler, respecting a
+        queue mechanism to avoid concurrent commits. Making a direct call to the method might lead to concurrency
+        issues.
+
+        </Tip>
+
+        The default behavior of `push_to_hub` is to assume an append-only folder. It lists all files in the folder and
+        uploads only changed files. If no changes are found, the method returns without committing anything. If you want
+        to change this behavior, you can inherit from [`CommitScheduler`] and override this method. This can be useful
+        for example to compress data together in a single file before committing. For more details and examples, check
+        out our [integration guide](https://huggingface.co/docs/huggingface_hub/main/en/guides/upload#scheduled-uploads).
+        """
+        # Check files to upload (with lock)
+        with self.lock:
+            logger.debug("Listing files to upload for scheduled commit.")
+
+            # List files from folder (taken from `_prepare_upload_folder_additions`)
+            relpath_to_abspath = {
+                path.relative_to(self.folder_path).as_posix(): path
+                for path in sorted(self.folder_path.glob("**/*"))  # sorted to be deterministic
+                if path.is_file()
+            }
+            prefix = f"{self.path_in_repo.strip('/')}/" if self.path_in_repo else ""
+
+            # Filter with pattern + filter out unchanged files + retrieve current file size
+            files_to_upload: List[_FileToUpload] = []
+            for relpath in filter_repo_objects(
+                relpath_to_abspath.keys(), allow_patterns=self.allow_patterns, ignore_patterns=self.ignore_patterns
+            ):
+                local_path = relpath_to_abspath[relpath]
+                stat = local_path.stat()
+                if self.last_uploaded.get(local_path) is None or self.last_uploaded[local_path] != stat.st_mtime:
+                    files_to_upload.append(
+                        _FileToUpload(
+                            local_path=local_path,
+                            path_in_repo=prefix + relpath,
+                            size_limit=stat.st_size,
+                            last_modified=stat.st_mtime,
+                        )
+                    )
+
+        # Return if nothing to upload
+        if len(files_to_upload) == 0:
+            logger.debug("Dropping schedule commit: no changed file to upload.")
+            return None
+
+        # Convert `_FileToUpload` as `CommitOperationAdd` (=> compute file shas + limit to file size)
+        logger.debug("Removing unchanged files since previous scheduled commit.")
+        add_operations = [
+            CommitOperationAdd(
+                # Cap the file to its current size, even if the user append data to it while a scheduled commit is happening
+                path_or_fileobj=PartialFileIO(file_to_upload.local_path, size_limit=file_to_upload.size_limit),
+                path_in_repo=file_to_upload.path_in_repo,
+            )
+            for file_to_upload in files_to_upload
+        ]
+
+        # Upload files (append mode expected - no need for lock)
+        logger.debug("Uploading files for scheduled commit.")
+        commit_info = self.api.create_commit(
+            repo_id=self.repo_id,
+            repo_type=self.repo_type,
+            operations=add_operations,
+            commit_message="Scheduled Commit",
+            revision=self.revision,
+        )
+
+        # Successful commit: keep track of the latest "last_modified" for each file
+        for file in files_to_upload:
+            self.last_uploaded[file.local_path] = file.last_modified
+        return commit_info
+
+
+class PartialFileIO(BytesIO):
+    """A file-like object that reads only the first part of a file.
+
+    Useful to upload a file to the Hub when the user might still be appending data to it. Only the first part of the
+    file is uploaded (i.e. the part that was available when the filesystem was first scanned).
+
+    In practice, only used internally by the CommitScheduler to regularly push a folder to the Hub with minimal
+    disturbance for the user. The object is passed to `CommitOperationAdd`.
+
+    Only supports `read`, `tell` and `seek` methods.
+
+    Args:
+        file_path (`str` or `Path`):
+            Path to the file to read.
+        size_limit (`int`):
+            The maximum number of bytes to read from the file. If the file is larger than this, only the first part
+            will be read (and uploaded).
+    """
+
+    def __init__(self, file_path: Union[str, Path], size_limit: int) -> None:
+        self._file_path = Path(file_path)
+        self._file = self._file_path.open("rb")
+        self._size_limit = min(size_limit, os.fstat(self._file.fileno()).st_size)
+
+    def __del__(self) -> None:
+        self._file.close()
+        return super().__del__()
+
+    def __repr__(self) -> str:
+        return f"<PartialFileIO file_path={self._file_path} size_limit={self._size_limit}>"
+
+    def __len__(self) -> int:
+        return self._size_limit
+
+    def __getattribute__(self, name: str):
+        if name.startswith("_") or name in ("read", "tell", "seek"):  # only 3 public methods supported
+            return super().__getattribute__(name)
+        raise NotImplementedError(f"PartialFileIO does not support '{name}'.")
+
+    def tell(self) -> int:
+        """Return the current file position."""
+        return self._file.tell()
+
+    def seek(self, __offset: int, __whence: int = SEEK_SET) -> int:
+        """Change the stream position to the given offset.
+
+        Behavior is the same as a regular file, except that the position is capped to the size limit.
+        """
+        if __whence == SEEK_END:
+            # SEEK_END => set from the truncated end
+            __offset = len(self) + __offset
+            __whence = SEEK_SET
+
+        pos = self._file.seek(__offset, __whence)
+        if pos > self._size_limit:
+            return self._file.seek(self._size_limit)
+        return pos
+
+    def read(self, __size: Optional[int] = -1) -> bytes:
+        """Read at most `__size` bytes from the file.
+
+        Behavior is the same as a regular file, except that it is capped to the size limit.
+        """
+        current = self._file.tell()
+        if __size is None or __size < 0:
+            # Read until file limit
+            truncated_size = self._size_limit - current
+        else:
+            # Read until file limit or __size
+            truncated_size = min(__size, self._size_limit - current)
+        return self._file.read(truncated_size)

.venv/lib/python3.13/site-packages/huggingface_hub/_inference_endpoints.py

@@ -0,0 +1,413 @@
+import time
+from dataclasses import dataclass, field
+from datetime import datetime
+from enum import Enum
+from typing import TYPE_CHECKING, Dict, Optional, Union
+
+from huggingface_hub.errors import InferenceEndpointError, InferenceEndpointTimeoutError
+
+from .utils import get_session, logging, parse_datetime
+
+
+if TYPE_CHECKING:
+    from .hf_api import HfApi
+    from .inference._client import InferenceClient
+    from .inference._generated._async_client import AsyncInferenceClient
+
+logger = logging.get_logger(__name__)
+
+
+class InferenceEndpointStatus(str, Enum):
+    PENDING = "pending"
+    INITIALIZING = "initializing"
+    UPDATING = "updating"
+    UPDATE_FAILED = "updateFailed"
+    RUNNING = "running"
+    PAUSED = "paused"
+    FAILED = "failed"
+    SCALED_TO_ZERO = "scaledToZero"
+
+
+class InferenceEndpointType(str, Enum):
+    PUBlIC = "public"
+    PROTECTED = "protected"
+    PRIVATE = "private"
+
+
+@dataclass
+class InferenceEndpoint:
+    """
+    Contains information about a deployed Inference Endpoint.
+
+    Args:
+        name (`str`):
+            The unique name of the Inference Endpoint.
+        namespace (`str`):
+            The namespace where the Inference Endpoint is located.
+        repository (`str`):
+            The name of the model repository deployed on this Inference Endpoint.
+        status ([`InferenceEndpointStatus`]):
+            The current status of the Inference Endpoint.
+        url (`str`, *optional*):
+            The URL of the Inference Endpoint, if available. Only a deployed Inference Endpoint will have a URL.
+        framework (`str`):
+            The machine learning framework used for the model.
+        revision (`str`):
+            The specific model revision deployed on the Inference Endpoint.
+        task (`str`):
+            The task associated with the deployed model.
+        created_at (`datetime.datetime`):
+            The timestamp when the Inference Endpoint was created.
+        updated_at (`datetime.datetime`):
+            The timestamp of the last update of the Inference Endpoint.
+        type ([`InferenceEndpointType`]):
+            The type of the Inference Endpoint (public, protected, private).
+        raw (`Dict`):
+            The raw dictionary data returned from the API.
+        token (`str` or `bool`, *optional*):
+            Authentication token for the Inference Endpoint, if set when requesting the API. Will default to the
+            locally saved token if not provided. Pass `token=False` if you don't want to send your token to the server.
+
+    Example:
+        ```python
+        >>> from huggingface_hub import get_inference_endpoint
+        >>> endpoint = get_inference_endpoint("my-text-to-image")
+        >>> endpoint
+        InferenceEndpoint(name='my-text-to-image', ...)
+
+        # Get status
+        >>> endpoint.status
+        'running'
+        >>> endpoint.url
+        'https://my-text-to-image.region.vendor.endpoints.huggingface.cloud'
+
+        # Run inference
+        >>> endpoint.client.text_to_image(...)
+
+        # Pause endpoint to save $$$
+        >>> endpoint.pause()
+
+        # ...
+        # Resume and wait for deployment
+        >>> endpoint.resume()
+        >>> endpoint.wait()
+        >>> endpoint.client.text_to_image(...)
+        ```
+    """
+
+    # Field in __repr__
+    name: str = field(init=False)
+    namespace: str
+    repository: str = field(init=False)
+    status: InferenceEndpointStatus = field(init=False)
+    health_route: str = field(init=False)
+    url: Optional[str] = field(init=False)
+
+    # Other fields
+    framework: str = field(repr=False, init=False)
+    revision: str = field(repr=False, init=False)
+    task: str = field(repr=False, init=False)
+    created_at: datetime = field(repr=False, init=False)
+    updated_at: datetime = field(repr=False, init=False)
+    type: InferenceEndpointType = field(repr=False, init=False)
+
+    # Raw dict from the API
+    raw: Dict = field(repr=False)
+
+    # Internal fields
+    _token: Union[str, bool, None] = field(repr=False, compare=False)
+    _api: "HfApi" = field(repr=False, compare=False)
+
+    @classmethod
+    def from_raw(
+        cls, raw: Dict, namespace: str, token: Union[str, bool, None] = None, api: Optional["HfApi"] = None
+    ) -> "InferenceEndpoint":
+        """Initialize object from raw dictionary."""
+        if api is None:
+            from .hf_api import HfApi
+
+            api = HfApi()
+        if token is None:
+            token = api.token
+
+        # All other fields are populated in __post_init__
+        return cls(raw=raw, namespace=namespace, _token=token, _api=api)
+
+    def __post_init__(self) -> None:
+        """Populate fields from raw dictionary."""
+        self._populate_from_raw()
+
+    @property
+    def client(self) -> "InferenceClient":
+        """Returns a client to make predictions on this Inference Endpoint.
+
+        Returns:
+            [`InferenceClient`]: an inference client pointing to the deployed endpoint.
+
+        Raises:
+            [`InferenceEndpointError`]: If the Inference Endpoint is not yet deployed.
+        """
+        if self.url is None:
+            raise InferenceEndpointError(
+                "Cannot create a client for this Inference Endpoint as it is not yet deployed. "
+                "Please wait for the Inference Endpoint to be deployed using `endpoint.wait()` and try again."
+            )
+        from .inference._client import InferenceClient
+
+        return InferenceClient(
+            model=self.url,
+            token=self._token,  # type: ignore[arg-type] # boolean token shouldn't be possible. In practice it's ok.
+        )
+
+    @property
+    def async_client(self) -> "AsyncInferenceClient":
+        """Returns a client to make predictions on this Inference Endpoint.
+
+        Returns:
+            [`AsyncInferenceClient`]: an asyncio-compatible inference client pointing to the deployed endpoint.
+
+        Raises:
+            [`InferenceEndpointError`]: If the Inference Endpoint is not yet deployed.
+        """
+        if self.url is None:
+            raise InferenceEndpointError(
+                "Cannot create a client for this Inference Endpoint as it is not yet deployed. "
+                "Please wait for the Inference Endpoint to be deployed using `endpoint.wait()` and try again."
+            )
+        from .inference._generated._async_client import AsyncInferenceClient
+
+        return AsyncInferenceClient(
+            model=self.url,
+            token=self._token,  # type: ignore[arg-type] # boolean token shouldn't be possible. In practice it's ok.
+        )
+
+    def wait(self, timeout: Optional[int] = None, refresh_every: int = 5) -> "InferenceEndpoint":
+        """Wait for the Inference Endpoint to be deployed.
+
+        Information from the server will be fetched every 1s. If the Inference Endpoint is not deployed after `timeout`
+        seconds, a [`InferenceEndpointTimeoutError`] will be raised. The [`InferenceEndpoint`] will be mutated in place with the latest
+        data.
+
+        Args:
+            timeout (`int`, *optional*):
+                The maximum time to wait for the Inference Endpoint to be deployed, in seconds. If `None`, will wait
+                indefinitely.
+            refresh_every (`int`, *optional*):
+                The time to wait between each fetch of the Inference Endpoint status, in seconds. Defaults to 5s.
+
+        Returns:
+            [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+
+        Raises:
+            [`InferenceEndpointError`]
+                If the Inference Endpoint ended up in a failed state.
+            [`InferenceEndpointTimeoutError`]
+                If the Inference Endpoint is not deployed after `timeout` seconds.
+        """
+        if timeout is not None and timeout < 0:
+            raise ValueError("`timeout` cannot be negative.")
+        if refresh_every <= 0:
+            raise ValueError("`refresh_every` must be positive.")
+
+        start = time.time()
+        while True:
+            if self.status == InferenceEndpointStatus.FAILED:
+                raise InferenceEndpointError(
+                    f"Inference Endpoint {self.name} failed to deploy. Please check the logs for more information."
+                )
+            if self.status == InferenceEndpointStatus.UPDATE_FAILED:
+                raise InferenceEndpointError(
+                    f"Inference Endpoint {self.name} failed to update. Please check the logs for more information."
+                )
+            if self.status == InferenceEndpointStatus.RUNNING and self.url is not None:
+                # Verify the endpoint is actually reachable
+                _health_url = f"{self.url.rstrip('/')}/{self.health_route.lstrip('/')}"
+                response = get_session().get(_health_url, headers=self._api._build_hf_headers(token=self._token))
+                if response.status_code == 200:
+                    logger.info("Inference Endpoint is ready to be used.")
+                    return self
+
+            if timeout is not None:
+                if time.time() - start > timeout:
+                    raise InferenceEndpointTimeoutError("Timeout while waiting for Inference Endpoint to be deployed.")
+            logger.info(f"Inference Endpoint is not deployed yet ({self.status}). Waiting {refresh_every}s...")
+            time.sleep(refresh_every)
+            self.fetch()
+
+    def fetch(self) -> "InferenceEndpoint":
+        """Fetch latest information about the Inference Endpoint.
+
+        Returns:
+            [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+        """
+        obj = self._api.get_inference_endpoint(name=self.name, namespace=self.namespace, token=self._token)  # type: ignore [arg-type]
+        self.raw = obj.raw
+        self._populate_from_raw()
+        return self
+
+    def update(
+        self,
+        *,
+        # Compute update
+        accelerator: Optional[str] = None,
+        instance_size: Optional[str] = None,
+        instance_type: Optional[str] = None,
+        min_replica: Optional[int] = None,
+        max_replica: Optional[int] = None,
+        scale_to_zero_timeout: Optional[int] = None,
+        # Model update
+        repository: Optional[str] = None,
+        framework: Optional[str] = None,
+        revision: Optional[str] = None,
+        task: Optional[str] = None,
+        custom_image: Optional[Dict] = None,
+        secrets: Optional[Dict[str, str]] = None,
+    ) -> "InferenceEndpoint":
+        """Update the Inference Endpoint.
+
+        This method allows the update of either the compute configuration, the deployed model, or both. All arguments are
+        optional but at least one must be provided.
+
+        This is an alias for [`HfApi.update_inference_endpoint`]. The current object is mutated in place with the
+        latest data from the server.
+
+        Args:
+            accelerator (`str`, *optional*):
+                The hardware accelerator to be used for inference (e.g. `"cpu"`).
+            instance_size (`str`, *optional*):
+                The size or type of the instance to be used for hosting the model (e.g. `"x4"`).
+            instance_type (`str`, *optional*):
+                The cloud instance type where the Inference Endpoint will be deployed (e.g. `"intel-icl"`).
+            min_replica (`int`, *optional*):
+                The minimum number of replicas (instances) to keep running for the Inference Endpoint.
+            max_replica (`int`, *optional*):
+                The maximum number of replicas (instances) to scale to for the Inference Endpoint.
+            scale_to_zero_timeout (`int`, *optional*):
+                The duration in minutes before an inactive endpoint is scaled to zero.
+
+            repository (`str`, *optional*):
+                The name of the model repository associated with the Inference Endpoint (e.g. `"gpt2"`).
+            framework (`str`, *optional*):
+                The machine learning framework used for the model (e.g. `"custom"`).
+            revision (`str`, *optional*):
+                The specific model revision to deploy on the Inference Endpoint (e.g. `"6c0e6080953db56375760c0471a8c5f2929baf11"`).
+            task (`str`, *optional*):
+                The task on which to deploy the model (e.g. `"text-classification"`).
+            custom_image (`Dict`, *optional*):
+                A custom Docker image to use for the Inference Endpoint. This is useful if you want to deploy an
+                Inference Endpoint running on the `text-generation-inference` (TGI) framework (see examples).
+            secrets (`Dict[str, str]`, *optional*):
+                Secret values to inject in the container environment.
+        Returns:
+            [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+        """
+        # Make API call
+        obj = self._api.update_inference_endpoint(
+            name=self.name,
+            namespace=self.namespace,
+            accelerator=accelerator,
+            instance_size=instance_size,
+            instance_type=instance_type,
+            min_replica=min_replica,
+            max_replica=max_replica,
+            scale_to_zero_timeout=scale_to_zero_timeout,
+            repository=repository,
+            framework=framework,
+            revision=revision,
+            task=task,
+            custom_image=custom_image,
+            secrets=secrets,
+            token=self._token,  # type: ignore [arg-type]
+        )
+
+        # Mutate current object
+        self.raw = obj.raw
+        self._populate_from_raw()
+        return self
+
+    def pause(self) -> "InferenceEndpoint":
+        """Pause the Inference Endpoint.
+
+        A paused Inference Endpoint will not be charged. It can be resumed at any time using [`InferenceEndpoint.resume`].
+        This is different than scaling the Inference Endpoint to zero with [`InferenceEndpoint.scale_to_zero`], which
+        would be automatically restarted when a request is made to it.
+
+        This is an alias for [`HfApi.pause_inference_endpoint`]. The current object is mutated in place with the
+        latest data from the server.
+
+        Returns:
+            [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+        """
+        obj = self._api.pause_inference_endpoint(name=self.name, namespace=self.namespace, token=self._token)  # type: ignore [arg-type]
+        self.raw = obj.raw
+        self._populate_from_raw()
+        return self
+
+    def resume(self, running_ok: bool = True) -> "InferenceEndpoint":
+        """Resume the Inference Endpoint.
+
+        This is an alias for [`HfApi.resume_inference_endpoint`]. The current object is mutated in place with the
+        latest data from the server.
+
+        Args:
+            running_ok (`bool`, *optional*):
+                If `True`, the method will not raise an error if the Inference Endpoint is already running. Defaults to
+                `True`.
+
+        Returns:
+            [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+        """
+        obj = self._api.resume_inference_endpoint(
+            name=self.name, namespace=self.namespace, running_ok=running_ok, token=self._token
+        )  # type: ignore [arg-type]
+        self.raw = obj.raw
+        self._populate_from_raw()
+        return self
+
+    def scale_to_zero(self) -> "InferenceEndpoint":
+        """Scale Inference Endpoint to zero.
+
+        An Inference Endpoint scaled to zero will not be charged. It will be resume on the next request to it, with a
+        cold start delay. This is different than pausing the Inference Endpoint with [`InferenceEndpoint.pause`], which
+        would require a manual resume with [`InferenceEndpoint.resume`].
+
+        This is an alias for [`HfApi.scale_to_zero_inference_endpoint`]. The current object is mutated in place with the
+        latest data from the server.
+
+        Returns:
+            [`InferenceEndpoint`]: the same Inference Endpoint, mutated in place with the latest data.
+        """
+        obj = self._api.scale_to_zero_inference_endpoint(name=self.name, namespace=self.namespace, token=self._token)  # type: ignore [arg-type]
+        self.raw = obj.raw
+        self._populate_from_raw()
+        return self
+
+    def delete(self) -> None:
+        """Delete the Inference Endpoint.
+
+        This operation is not reversible. If you don't want to be charged for an Inference Endpoint, it is preferable
+        to pause it with [`InferenceEndpoint.pause`] or scale it to zero with [`InferenceEndpoint.scale_to_zero`].
+
+        This is an alias for [`HfApi.delete_inference_endpoint`].
+        """
+        self._api.delete_inference_endpoint(name=self.name, namespace=self.namespace, token=self._token)  # type: ignore [arg-type]
+
+    def _populate_from_raw(self) -> None:
+        """Populate fields from raw dictionary.
+
+        Called in __post_init__ + each time the Inference Endpoint is updated.
+        """
+        # Repr fields
+        self.name = self.raw["name"]
+        self.repository = self.raw["model"]["repository"]
+        self.status = self.raw["status"]["state"]
+        self.url = self.raw["status"].get("url")
+        self.health_route = self.raw["healthRoute"]
+
+        # Other fields
+        self.framework = self.raw["model"]["framework"]
+        self.revision = self.raw["model"]["revision"]
+        self.task = self.raw["model"]["task"]
+        self.created_at = parse_datetime(self.raw["status"]["createdAt"])
+        self.updated_at = parse_datetime(self.raw["status"]["updatedAt"])
+        self.type = self.raw["type"]

.venv/lib/python3.13/site-packages/huggingface_hub/_local_folder.py

@@ -0,0 +1,441 @@
+# coding=utf-8
+# Copyright 2024-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Contains utilities to handle the `../.cache/huggingface` folder in local directories.
+
+First discussed in https://github.com/huggingface/huggingface_hub/issues/1738 to store
+download metadata when downloading files from the hub to a local directory (without
+using the cache).
+
+./.cache/huggingface folder structure:
+[4.0K]  data
+├── [4.0K]  .cache
+│   └── [4.0K]  huggingface
+│       └── [4.0K]  download
+│           ├── [  16]  file.parquet.metadata
+│           ├── [  16]  file.txt.metadata
+│           └── [4.0K]  folder
+│               └── [  16]  file.parquet.metadata
+│
+├── [6.5G]  file.parquet
+├── [1.5K]  file.txt
+└── [4.0K]  folder
+    └── [   16]  file.parquet
+
+
+Download metadata file structure:
+```
+# file.txt.metadata
+11c5a3d5811f50298f278a704980280950aedb10
+a16a55fda99d2f2e7b69cce5cf93ff4ad3049930
+1712656091.123
+
+# file.parquet.metadata
+11c5a3d5811f50298f278a704980280950aedb10
+7c5d3f4b8b76583b422fcb9189ad6c89d5d97a094541ce8932dce3ecabde1421
+1712656091.123
+}
+```
+"""
+
+import base64
+import hashlib
+import logging
+import os
+import time
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Optional
+
+from .utils import WeakFileLock
+
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class LocalDownloadFilePaths:
+    """
+    Paths to the files related to a download process in a local dir.
+
+    Returned by [`get_local_download_paths`].
+
+    Attributes:
+        file_path (`Path`):
+            Path where the file will be saved.
+        lock_path (`Path`):
+            Path to the lock file used to ensure atomicity when reading/writing metadata.
+        metadata_path (`Path`):
+            Path to the metadata file.
+    """
+
+    file_path: Path
+    lock_path: Path
+    metadata_path: Path
+
+    def incomplete_path(self, etag: str) -> Path:
+        """Return the path where a file will be temporarily downloaded before being moved to `file_path`."""
+        return self.metadata_path.parent / f"{_short_hash(self.metadata_path.name)}.{etag}.incomplete"
+
+
+@dataclass(frozen=True)
+class LocalUploadFilePaths:
+    """
+    Paths to the files related to an upload process in a local dir.
+
+    Returned by [`get_local_upload_paths`].
+
+    Attributes:
+        path_in_repo (`str`):
+            Path of the file in the repo.
+        file_path (`Path`):
+            Path where the file will be saved.
+        lock_path (`Path`):
+            Path to the lock file used to ensure atomicity when reading/writing metadata.
+        metadata_path (`Path`):
+            Path to the metadata file.
+    """
+
+    path_in_repo: str
+    file_path: Path
+    lock_path: Path
+    metadata_path: Path
+
+
+@dataclass
+class LocalDownloadFileMetadata:
+    """
+    Metadata about a file in the local directory related to a download process.
+
+    Attributes:
+        filename (`str`):
+            Path of the file in the repo.
+        commit_hash (`str`):
+            Commit hash of the file in the repo.
+        etag (`str`):
+            ETag of the file in the repo. Used to check if the file has changed.
+            For LFS files, this is the sha256 of the file. For regular files, it corresponds to the git hash.
+        timestamp (`int`):
+            Unix timestamp of when the metadata was saved i.e. when the metadata was accurate.
+    """
+
+    filename: str
+    commit_hash: str
+    etag: str
+    timestamp: float
+
+
+@dataclass
+class LocalUploadFileMetadata:
+    """
+    Metadata about a file in the local directory related to an upload process.
+    """
+
+    size: int
+
+    # Default values correspond to "we don't know yet"
+    timestamp: Optional[float] = None
+    should_ignore: Optional[bool] = None
+    sha256: Optional[str] = None
+    upload_mode: Optional[str] = None
+    remote_oid: Optional[str] = None
+    is_uploaded: bool = False
+    is_committed: bool = False
+
+    def save(self, paths: LocalUploadFilePaths) -> None:
+        """Save the metadata to disk."""
+        with WeakFileLock(paths.lock_path):
+            with paths.metadata_path.open("w") as f:
+                new_timestamp = time.time()
+                f.write(str(new_timestamp) + "\n")
+
+                f.write(str(self.size))  # never None
+                f.write("\n")
+
+                if self.should_ignore is not None:
+                    f.write(str(int(self.should_ignore)))
+                f.write("\n")
+
+                if self.sha256 is not None:
+                    f.write(self.sha256)
+                f.write("\n")
+
+                if self.upload_mode is not None:
+                    f.write(self.upload_mode)
+                f.write("\n")
+
+                if self.remote_oid is not None:
+                    f.write(self.remote_oid)
+                f.write("\n")
+
+                f.write(str(int(self.is_uploaded)) + "\n")
+                f.write(str(int(self.is_committed)) + "\n")
+
+            self.timestamp = new_timestamp
+
+
+def get_local_download_paths(local_dir: Path, filename: str) -> LocalDownloadFilePaths:
+    """Compute paths to the files related to a download process.
+
+    Folders containing the paths are all guaranteed to exist.
+
+    Args:
+        local_dir (`Path`):
+            Path to the local directory in which files are downloaded.
+        filename (`str`):
+            Path of the file in the repo.
+
+    Return:
+        [`LocalDownloadFilePaths`]: the paths to the files (file_path, lock_path, metadata_path, incomplete_path).
+    """
+    # filename is the path in the Hub repository (separated by '/')
+    # make sure to have a cross platform transcription
+    sanitized_filename = os.path.join(*filename.split("/"))
+    if os.name == "nt":
+        if sanitized_filename.startswith("..\\") or "\\..\\" in sanitized_filename:
+            raise ValueError(
+                f"Invalid filename: cannot handle filename '{sanitized_filename}' on Windows. Please ask the repository"
+                " owner to rename this file."
+            )
+    file_path = local_dir / sanitized_filename
+    metadata_path = _huggingface_dir(local_dir) / "download" / f"{sanitized_filename}.metadata"
+    lock_path = metadata_path.with_suffix(".lock")
+
+    # Some Windows versions do not allow for paths longer than 255 characters.
+    # In this case, we must specify it as an extended path by using the "\\?\" prefix
+    if os.name == "nt":
+        if not str(local_dir).startswith("\\\\?\\") and len(os.path.abspath(lock_path)) > 255:
+            file_path = Path("\\\\?\\" + os.path.abspath(file_path))
+            lock_path = Path("\\\\?\\" + os.path.abspath(lock_path))
+            metadata_path = Path("\\\\?\\" + os.path.abspath(metadata_path))
+
+    file_path.parent.mkdir(parents=True, exist_ok=True)
+    metadata_path.parent.mkdir(parents=True, exist_ok=True)
+    return LocalDownloadFilePaths(file_path=file_path, lock_path=lock_path, metadata_path=metadata_path)
+
+
+def get_local_upload_paths(local_dir: Path, filename: str) -> LocalUploadFilePaths:
+    """Compute paths to the files related to an upload process.
+
+    Folders containing the paths are all guaranteed to exist.
+
+    Args:
+        local_dir (`Path`):
+            Path to the local directory that is uploaded.
+        filename (`str`):
+            Path of the file in the repo.
+
+    Return:
+        [`LocalUploadFilePaths`]: the paths to the files (file_path, lock_path, metadata_path).
+    """
+    # filename is the path in the Hub repository (separated by '/')
+    # make sure to have a cross platform transcription
+    sanitized_filename = os.path.join(*filename.split("/"))
+    if os.name == "nt":
+        if sanitized_filename.startswith("..\\") or "\\..\\" in sanitized_filename:
+            raise ValueError(
+                f"Invalid filename: cannot handle filename '{sanitized_filename}' on Windows. Please ask the repository"
+                " owner to rename this file."
+            )
+    file_path = local_dir / sanitized_filename
+    metadata_path = _huggingface_dir(local_dir) / "upload" / f"{sanitized_filename}.metadata"
+    lock_path = metadata_path.with_suffix(".lock")
+
+    # Some Windows versions do not allow for paths longer than 255 characters.
+    # In this case, we must specify it as an extended path by using the "\\?\" prefix
+    if os.name == "nt":
+        if not str(local_dir).startswith("\\\\?\\") and len(os.path.abspath(lock_path)) > 255:
+            file_path = Path("\\\\?\\" + os.path.abspath(file_path))
+            lock_path = Path("\\\\?\\" + os.path.abspath(lock_path))
+            metadata_path = Path("\\\\?\\" + os.path.abspath(metadata_path))
+
+    file_path.parent.mkdir(parents=True, exist_ok=True)
+    metadata_path.parent.mkdir(parents=True, exist_ok=True)
+    return LocalUploadFilePaths(
+        path_in_repo=filename, file_path=file_path, lock_path=lock_path, metadata_path=metadata_path
+    )
+
+
+def read_download_metadata(local_dir: Path, filename: str) -> Optional[LocalDownloadFileMetadata]:
+    """Read metadata about a file in the local directory related to a download process.
+
+    Args:
+        local_dir (`Path`):
+            Path to the local directory in which files are downloaded.
+        filename (`str`):
+            Path of the file in the repo.
+
+    Return:
+        `[LocalDownloadFileMetadata]` or `None`: the metadata if it exists, `None` otherwise.
+    """
+    paths = get_local_download_paths(local_dir, filename)
+    with WeakFileLock(paths.lock_path):
+        if paths.metadata_path.exists():
+            try:
+                with paths.metadata_path.open() as f:
+                    commit_hash = f.readline().strip()
+                    etag = f.readline().strip()
+                    timestamp = float(f.readline().strip())
+                    metadata = LocalDownloadFileMetadata(
+                        filename=filename,
+                        commit_hash=commit_hash,
+                        etag=etag,
+                        timestamp=timestamp,
+                    )
+            except Exception as e:
+                # remove the metadata file if it is corrupted / not the right format
+                logger.warning(
+                    f"Invalid metadata file {paths.metadata_path}: {e}. Removing it from disk and continue."
+                )
+                try:
+                    paths.metadata_path.unlink()
+                except Exception as e:
+                    logger.warning(f"Could not remove corrupted metadata file {paths.metadata_path}: {e}")
+
+            try:
+                # check if the file exists and hasn't been modified since the metadata was saved
+                stat = paths.file_path.stat()
+                if (
+                    stat.st_mtime - 1 <= metadata.timestamp
+                ):  # allow 1s difference as stat.st_mtime might not be precise
+                    return metadata
+                logger.info(f"Ignored metadata for '{filename}' (outdated). Will re-compute hash.")
+            except FileNotFoundError:
+                # file does not exist => metadata is outdated
+                return None
+    return None
+
+
+def read_upload_metadata(local_dir: Path, filename: str) -> LocalUploadFileMetadata:
+    """Read metadata about a file in the local directory related to an upload process.
+
+    TODO: factorize logic with `read_download_metadata`.
+
+    Args:
+        local_dir (`Path`):
+            Path to the local directory in which files are downloaded.
+        filename (`str`):
+            Path of the file in the repo.
+
+    Return:
+        `[LocalUploadFileMetadata]` or `None`: the metadata if it exists, `None` otherwise.
+    """
+    paths = get_local_upload_paths(local_dir, filename)
+    with WeakFileLock(paths.lock_path):
+        if paths.metadata_path.exists():
+            try:
+                with paths.metadata_path.open() as f:
+                    timestamp = float(f.readline().strip())
+
+                    size = int(f.readline().strip())  # never None
+
+                    _should_ignore = f.readline().strip()
+                    should_ignore = None if _should_ignore == "" else bool(int(_should_ignore))
+
+                    _sha256 = f.readline().strip()
+                    sha256 = None if _sha256 == "" else _sha256
+
+                    _upload_mode = f.readline().strip()
+                    upload_mode = None if _upload_mode == "" else _upload_mode
+                    if upload_mode not in (None, "regular", "lfs"):
+                        raise ValueError(f"Invalid upload mode in metadata {paths.path_in_repo}: {upload_mode}")
+
+                    _remote_oid = f.readline().strip()
+                    remote_oid = None if _remote_oid == "" else _remote_oid
+
+                    is_uploaded = bool(int(f.readline().strip()))
+                    is_committed = bool(int(f.readline().strip()))
+
+                    metadata = LocalUploadFileMetadata(
+                        timestamp=timestamp,
+                        size=size,
+                        should_ignore=should_ignore,
+                        sha256=sha256,
+                        upload_mode=upload_mode,
+                        remote_oid=remote_oid,
+                        is_uploaded=is_uploaded,
+                        is_committed=is_committed,
+                    )
+            except Exception as e:
+                # remove the metadata file if it is corrupted / not the right format
+                logger.warning(
+                    f"Invalid metadata file {paths.metadata_path}: {e}. Removing it from disk and continue."
+                )
+                try:
+                    paths.metadata_path.unlink()
+                except Exception as e:
+                    logger.warning(f"Could not remove corrupted metadata file {paths.metadata_path}: {e}")
+
+            # TODO: can we do better?
+            if (
+                metadata.timestamp is not None
+                and metadata.is_uploaded  # file was uploaded
+                and not metadata.is_committed  # but not committed
+                and time.time() - metadata.timestamp > 20 * 3600  # and it's been more than 20 hours
+            ):  # => we consider it as garbage-collected by S3
+                metadata.is_uploaded = False
+
+            # check if the file exists and hasn't been modified since the metadata was saved
+            try:
+                if metadata.timestamp is not None and paths.file_path.stat().st_mtime <= metadata.timestamp:
+                    return metadata
+                logger.info(f"Ignored metadata for '{filename}' (outdated). Will re-compute hash.")
+            except FileNotFoundError:
+                # file does not exist => metadata is outdated
+                pass
+
+    # empty metadata => we don't know anything expect its size
+    return LocalUploadFileMetadata(size=paths.file_path.stat().st_size)
+
+
+def write_download_metadata(local_dir: Path, filename: str, commit_hash: str, etag: str) -> None:
+    """Write metadata about a file in the local directory related to a download process.
+
+    Args:
+        local_dir (`Path`):
+            Path to the local directory in which files are downloaded.
+    """
+    paths = get_local_download_paths(local_dir, filename)
+    with WeakFileLock(paths.lock_path):
+        with paths.metadata_path.open("w") as f:
+            f.write(f"{commit_hash}\n{etag}\n{time.time()}\n")
+
+
+def _huggingface_dir(local_dir: Path) -> Path:
+    """Return the path to the `.cache/huggingface` directory in a local directory."""
+    # Wrap in lru_cache to avoid overwriting the .gitignore file if called multiple times
+    path = local_dir / ".cache" / "huggingface"
+    path.mkdir(exist_ok=True, parents=True)
+
+    # Create a .gitignore file in the .cache/huggingface directory if it doesn't exist
+    # Should be thread-safe enough like this.
+    gitignore = path / ".gitignore"
+    gitignore_lock = path / ".gitignore.lock"
+    if not gitignore.exists():
+        try:
+            with WeakFileLock(gitignore_lock, timeout=0.1):
+                gitignore.write_text("*")
+        except IndexError:
+            pass
+        except OSError:  # TimeoutError, FileNotFoundError, PermissionError, etc.
+            pass
+        try:
+            gitignore_lock.unlink()
+        except OSError:
+            pass
+    return path
+
+
+def _short_hash(filename: str) -> str:
+    return base64.urlsafe_b64encode(hashlib.sha1(filename.encode()).digest()).decode()

.venv/lib/python3.13/site-packages/huggingface_hub/_login.py

@@ -0,0 +1,520 @@
+# Copyright 2020 The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Contains methods to log in to the Hub."""
+
+import os
+import subprocess
+from getpass import getpass
+from pathlib import Path
+from typing import Optional
+
+from . import constants
+from .commands._cli_utils import ANSI
+from .utils import (
+    capture_output,
+    get_token,
+    is_google_colab,
+    is_notebook,
+    list_credential_helpers,
+    logging,
+    run_subprocess,
+    set_git_credential,
+    unset_git_credential,
+)
+from .utils._auth import (
+    _get_token_by_name,
+    _get_token_from_environment,
+    _get_token_from_file,
+    _get_token_from_google_colab,
+    _save_stored_tokens,
+    _save_token,
+    get_stored_tokens,
+)
+from .utils._deprecation import _deprecate_arguments, _deprecate_positional_args
+
+
+logger = logging.get_logger(__name__)
+
+_HF_LOGO_ASCII = """
+    _|    _|  _|    _|    _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|_|_|_|    _|_|      _|_|_|  _|_|_|_|
+    _|    _|  _|    _|  _|        _|          _|    _|_|    _|  _|            _|        _|    _|  _|        _|
+    _|_|_|_|  _|    _|  _|  _|_|  _|  _|_|    _|    _|  _|  _|  _|  _|_|      _|_|_|    _|_|_|_|  _|        _|_|_|
+    _|    _|  _|    _|  _|    _|  _|    _|    _|    _|    _|_|  _|    _|      _|        _|    _|  _|        _|
+    _|    _|    _|_|      _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|        _|    _|    _|_|_|  _|_|_|_|
+"""
+
+
+@_deprecate_arguments(
+    version="1.0",
+    deprecated_args="write_permission",
+    custom_message="Fine-grained tokens added complexity to the permissions, making it irrelevant to check if a token has 'write' access.",
+)
+@_deprecate_positional_args(version="1.0")
+def login(
+    token: Optional[str] = None,
+    *,
+    add_to_git_credential: bool = False,
+    new_session: bool = True,
+    write_permission: bool = False,
+) -> None:
+    """Login the machine to access the Hub.
+
+    The `token` is persisted in cache and set as a git credential. Once done, the machine
+    is logged in and the access token will be available across all `huggingface_hub`
+    components. If `token` is not provided, it will be prompted to the user either with
+    a widget (in a notebook) or via the terminal.
+
+    To log in from outside of a script, one can also use `huggingface-cli login` which is
+    a cli command that wraps [`login`].
+
+    <Tip>
+
+    [`login`] is a drop-in replacement method for [`notebook_login`] as it wraps and
+    extends its capabilities.
+
+    </Tip>
+
+    <Tip>
+
+    When the token is not passed, [`login`] will automatically detect if the script runs
+    in a notebook or not. However, this detection might not be accurate due to the
+    variety of notebooks that exists nowadays. If that is the case, you can always force
+    the UI by using [`notebook_login`] or [`interpreter_login`].
+
+    </Tip>
+
+    Args:
+        token (`str`, *optional*):
+            User access token to generate from https://huggingface.co/settings/token.
+        add_to_git_credential (`bool`, defaults to `False`):
+            If `True`, token will be set as git credential. If no git credential helper
+            is configured, a warning will be displayed to the user. If `token` is `None`,
+            the value of `add_to_git_credential` is ignored and will be prompted again
+            to the end user.
+        new_session (`bool`, defaults to `True`):
+            If `True`, will request a token even if one is already saved on the machine.
+        write_permission (`bool`):
+            Ignored and deprecated argument.
+    Raises:
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+            If an organization token is passed. Only personal account tokens are valid
+            to log in.
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+            If token is invalid.
+        [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError)
+            If running in a notebook but `ipywidgets` is not installed.
+    """
+    if token is not None:
+        if not add_to_git_credential:
+            logger.info(
+                "The token has not been saved to the git credentials helper. Pass "
+                "`add_to_git_credential=True` in this function directly or "
+                "`--add-to-git-credential` if using via `huggingface-cli` if "
+                "you want to set the git credential as well."
+            )
+        _login(token, add_to_git_credential=add_to_git_credential)
+    elif is_notebook():
+        notebook_login(new_session=new_session)
+    else:
+        interpreter_login(new_session=new_session)
+
+
+def logout(token_name: Optional[str] = None) -> None:
+    """Logout the machine from the Hub.
+
+    Token is deleted from the machine and removed from git credential.
+
+    Args:
+        token_name (`str`, *optional*):
+            Name of the access token to logout from. If `None`, will logout from all saved access tokens.
+    Raises:
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError):
+            If the access token name is not found.
+    """
+    if get_token() is None and not get_stored_tokens():  # No active token and no saved access tokens
+        logger.warning("Not logged in!")
+        return
+    if not token_name:
+        # Delete all saved access tokens and token
+        for file_path in (constants.HF_TOKEN_PATH, constants.HF_STORED_TOKENS_PATH):
+            try:
+                Path(file_path).unlink()
+            except FileNotFoundError:
+                pass
+        logger.info("Successfully logged out from all access tokens.")
+    else:
+        _logout_from_token(token_name)
+        logger.info(f"Successfully logged out from access token: {token_name}.")
+
+    unset_git_credential()
+
+    # Check if still logged in
+    if _get_token_from_google_colab() is not None:
+        raise EnvironmentError(
+            "You are automatically logged in using a Google Colab secret.\n"
+            "To log out, you must unset the `HF_TOKEN` secret in your Colab settings."
+        )
+    if _get_token_from_environment() is not None:
+        raise EnvironmentError(
+            "Token has been deleted from your machine but you are still logged in.\n"
+            "To log out, you must clear out both `HF_TOKEN` and `HUGGING_FACE_HUB_TOKEN` environment variables."
+        )
+
+
+def auth_switch(token_name: str, add_to_git_credential: bool = False) -> None:
+    """Switch to a different access token.
+
+    Args:
+        token_name (`str`):
+            Name of the access token to switch to.
+        add_to_git_credential (`bool`, defaults to `False`):
+            If `True`, token will be set as git credential. If no git credential helper
+            is configured, a warning will be displayed to the user. If `token` is `None`,
+            the value of `add_to_git_credential` is ignored and will be prompted again
+            to the end user.
+
+    Raises:
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError):
+            If the access token name is not found.
+    """
+    token = _get_token_by_name(token_name)
+    if not token:
+        raise ValueError(f"Access token {token_name} not found in {constants.HF_STORED_TOKENS_PATH}")
+    # Write token to HF_TOKEN_PATH
+    _set_active_token(token_name, add_to_git_credential)
+    logger.info(f"The current active token is: {token_name}")
+    token_from_environment = _get_token_from_environment()
+    if token_from_environment is not None and token_from_environment != token:
+        logger.warning(
+            "The environment variable `HF_TOKEN` is set and will override the access token you've just switched to."
+        )
+
+
+def auth_list() -> None:
+    """List all stored access tokens."""
+    tokens = get_stored_tokens()
+
+    if not tokens:
+        logger.info("No access tokens found.")
+        return
+    # Find current token
+    current_token = get_token()
+    current_token_name = None
+    for token_name in tokens:
+        if tokens.get(token_name) == current_token:
+            current_token_name = token_name
+    # Print header
+    max_offset = max(len("token"), max(len(token) for token in tokens)) + 2
+    print(f"  {{:<{max_offset}}}| {{:<15}}".format("name", "token"))
+    print("-" * (max_offset + 2) + "|" + "-" * 15)
+
+    # Print saved access tokens
+    for token_name in tokens:
+        token = tokens.get(token_name, "<not set>")
+        masked_token = f"{token[:3]}****{token[-4:]}" if token != "<not set>" else token
+        is_current = "*" if token == current_token else " "
+
+        print(f"{is_current} {{:<{max_offset}}}| {{:<15}}".format(token_name, masked_token))
+
+    if _get_token_from_environment():
+        logger.warning(
+            "\nNote: Environment variable `HF_TOKEN` is set and is the current active token independently from the stored tokens listed above."
+        )
+    elif current_token_name is None:
+        logger.warning(
+            "\nNote: No active token is set and no environment variable `HF_TOKEN` is found. Use `huggingface-cli login` to log in."
+        )
+
+
+###
+# Interpreter-based login (text)
+###
+
+
+@_deprecate_arguments(
+    version="1.0",
+    deprecated_args="write_permission",
+    custom_message="Fine-grained tokens added complexity to the permissions, making it irrelevant to check if a token has 'write' access.",
+)
+@_deprecate_positional_args(version="1.0")
+def interpreter_login(*, new_session: bool = True, write_permission: bool = False) -> None:
+    """
+    Displays a prompt to log in to the HF website and store the token.
+
+    This is equivalent to [`login`] without passing a token when not run in a notebook.
+    [`interpreter_login`] is useful if you want to force the use of the terminal prompt
+    instead of a notebook widget.
+
+    For more details, see [`login`].
+
+    Args:
+        new_session (`bool`, defaults to `True`):
+            If `True`, will request a token even if one is already saved on the machine.
+        write_permission (`bool`):
+            Ignored and deprecated argument.
+    """
+    if not new_session and get_token() is not None:
+        logger.info("User is already logged in.")
+        return
+
+    from .commands.delete_cache import _ask_for_confirmation_no_tui
+
+    print(_HF_LOGO_ASCII)
+    if get_token() is not None:
+        logger.info(
+            "    A token is already saved on your machine. Run `huggingface-cli"
+            " whoami` to get more information or `huggingface-cli logout` if you want"
+            " to log out."
+        )
+        logger.info("    Setting a new token will erase the existing one.")
+
+    logger.info(
+        "    To log in, `huggingface_hub` requires a token generated from https://huggingface.co/settings/tokens ."
+    )
+    if os.name == "nt":
+        logger.info("Token can be pasted using 'Right-Click'.")
+    token = getpass("Enter your token (input will not be visible): ")
+    add_to_git_credential = _ask_for_confirmation_no_tui("Add token as git credential?")
+
+    _login(token=token, add_to_git_credential=add_to_git_credential)
+
+
+###
+# Notebook-based login (widget)
+###
+
+NOTEBOOK_LOGIN_PASSWORD_HTML = """<center> <img
+src=https://huggingface.co/front/assets/huggingface_logo-noborder.svg
+alt='Hugging Face'> <br> Immediately click login after typing your password or
+it might be stored in plain text in this notebook file. </center>"""
+
+
+NOTEBOOK_LOGIN_TOKEN_HTML_START = """<center> <img
+src=https://huggingface.co/front/assets/huggingface_logo-noborder.svg
+alt='Hugging Face'> <br> Copy a token from <a
+href="https://huggingface.co/settings/tokens" target="_blank">your Hugging Face
+tokens page</a> and paste it below. <br> Immediately click login after copying
+your token or it might be stored in plain text in this notebook file. </center>"""
+
+
+NOTEBOOK_LOGIN_TOKEN_HTML_END = """
+<b>Pro Tip:</b> If you don't already have one, you can create a dedicated
+'notebooks' token with 'write' access, that you can then easily reuse for all
+notebooks. </center>"""
+
+
+@_deprecate_arguments(
+    version="1.0",
+    deprecated_args="write_permission",
+    custom_message="Fine-grained tokens added complexity to the permissions, making it irrelevant to check if a token has 'write' access.",
+)
+@_deprecate_positional_args(version="1.0")
+def notebook_login(*, new_session: bool = True, write_permission: bool = False) -> None:
+    """
+    Displays a widget to log in to the HF website and store the token.
+
+    This is equivalent to [`login`] without passing a token when run in a notebook.
+    [`notebook_login`] is useful if you want to force the use of the notebook widget
+    instead of a prompt in the terminal.
+
+    For more details, see [`login`].
+
+    Args:
+        new_session (`bool`, defaults to `True`):
+            If `True`, will request a token even if one is already saved on the machine.
+        write_permission (`bool`):
+            Ignored and deprecated argument.
+    """
+    try:
+        import ipywidgets.widgets as widgets  # type: ignore
+        from IPython.display import display  # type: ignore
+    except ImportError:
+        raise ImportError(
+            "The `notebook_login` function can only be used in a notebook (Jupyter or"
+            " Colab) and you need the `ipywidgets` module: `pip install ipywidgets`."
+        )
+    if not new_session and get_token() is not None:
+        logger.info("User is already logged in.")
+        return
+
+    box_layout = widgets.Layout(display="flex", flex_flow="column", align_items="center", width="50%")
+
+    token_widget = widgets.Password(description="Token:")
+    git_checkbox_widget = widgets.Checkbox(value=True, description="Add token as git credential?")
+    token_finish_button = widgets.Button(description="Login")
+
+    login_token_widget = widgets.VBox(
+        [
+            widgets.HTML(NOTEBOOK_LOGIN_TOKEN_HTML_START),
+            token_widget,
+            git_checkbox_widget,
+            token_finish_button,
+            widgets.HTML(NOTEBOOK_LOGIN_TOKEN_HTML_END),
+        ],
+        layout=box_layout,
+    )
+    display(login_token_widget)
+
+    # On click events
+    def login_token_event(t):
+        """Event handler for the login button."""
+        token = token_widget.value
+        add_to_git_credential = git_checkbox_widget.value
+        # Erase token and clear value to make sure it's not saved in the notebook.
+        token_widget.value = ""
+        # Hide inputs
+        login_token_widget.children = [widgets.Label("Connecting...")]
+        try:
+            with capture_output() as captured:
+                _login(token, add_to_git_credential=add_to_git_credential)
+            message = captured.getvalue()
+        except Exception as error:
+            message = str(error)
+        # Print result (success message or error)
+        login_token_widget.children = [widgets.Label(line) for line in message.split("\n") if line.strip()]
+
+    token_finish_button.on_click(login_token_event)
+
+
+###
+# Login private helpers
+###
+
+
+def _login(
+    token: str,
+    add_to_git_credential: bool,
+) -> None:
+    from .hf_api import whoami  # avoid circular import
+
+    if token.startswith("api_org"):
+        raise ValueError("You must use your personal account token, not an organization token.")
+
+    token_info = whoami(token)
+    permission = token_info["auth"]["accessToken"]["role"]
+    logger.info(f"Token is valid (permission: {permission}).")
+
+    token_name = token_info["auth"]["accessToken"]["displayName"]
+    # Store token locally
+    _save_token(token=token, token_name=token_name)
+    # Set active token
+    _set_active_token(token_name=token_name, add_to_git_credential=add_to_git_credential)
+    logger.info("Login successful.")
+    if _get_token_from_environment():
+        logger.warning(
+            "Note: Environment variable`HF_TOKEN` is set and is the current active token independently from the token you've just configured."
+        )
+    else:
+        logger.info(f"The current active token is: `{token_name}`")
+
+
+def _logout_from_token(token_name: str) -> None:
+    """Logout from a specific access token.
+
+    Args:
+        token_name (`str`):
+            The name of the access token to logout from.
+    Raises:
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError):
+            If the access token name is not found.
+    """
+    stored_tokens = get_stored_tokens()
+    # If there is no access tokens saved or the access token name is not found, do nothing
+    if not stored_tokens or token_name not in stored_tokens:
+        return
+
+    token = stored_tokens.pop(token_name)
+    _save_stored_tokens(stored_tokens)
+
+    if token == _get_token_from_file():
+        logger.warning(f"Active token '{token_name}' has been deleted.")
+        Path(constants.HF_TOKEN_PATH).unlink(missing_ok=True)
+
+
+def _set_active_token(
+    token_name: str,
+    add_to_git_credential: bool,
+) -> None:
+    """Set the active access token.
+
+    Args:
+        token_name (`str`):
+            The name of the token to set as active.
+    """
+    token = _get_token_by_name(token_name)
+    if not token:
+        raise ValueError(f"Token {token_name} not found in {constants.HF_STORED_TOKENS_PATH}")
+    if add_to_git_credential:
+        if _is_git_credential_helper_configured():
+            set_git_credential(token)
+            logger.info(
+                "Your token has been saved in your configured git credential helpers"
+                + f" ({','.join(list_credential_helpers())})."
+            )
+        else:
+            logger.warning("Token has not been saved to git credential helper.")
+    # Write token to HF_TOKEN_PATH
+    path = Path(constants.HF_TOKEN_PATH)
+    path.parent.mkdir(parents=True, exist_ok=True)
+    path.write_text(token)
+    logger.info(f"Your token has been saved to {constants.HF_TOKEN_PATH}")
+
+
+def _is_git_credential_helper_configured() -> bool:
+    """Check if a git credential helper is configured.
+
+    Warns user if not the case (except for Google Colab where "store" is set by default
+    by `huggingface_hub`).
+    """
+    helpers = list_credential_helpers()
+    if len(helpers) > 0:
+        return True  # Do not warn: at least 1 helper is set
+
+    # Only in Google Colab to avoid the warning message
+    # See https://github.com/huggingface/huggingface_hub/issues/1043#issuecomment-1247010710
+    if is_google_colab():
+        _set_store_as_git_credential_helper_globally()
+        return True  # Do not warn: "store" is used by default in Google Colab
+
+    # Otherwise, warn user
+    print(
+        ANSI.red(
+            "Cannot authenticate through git-credential as no helper is defined on your"
+            " machine.\nYou might have to re-authenticate when pushing to the Hugging"
+            " Face Hub.\nRun the following command in your terminal in case you want to"
+            " set the 'store' credential helper as default.\n\ngit config --global"
+            " credential.helper store\n\nRead"
+            " https://git-scm.com/book/en/v2/Git-Tools-Credential-Storage for more"
+            " details."
+        )
+    )
+    return False
+
+
+def _set_store_as_git_credential_helper_globally() -> None:
+    """Set globally the credential.helper to `store`.
+
+    To be used only in Google Colab as we assume the user doesn't care about the git
+    credential config. It is the only particular case where we don't want to display the
+    warning message in [`notebook_login()`].
+
+    Related:
+    - https://github.com/huggingface/huggingface_hub/issues/1043
+    - https://github.com/huggingface/huggingface_hub/issues/1051
+    - https://git-scm.com/docs/git-credential-store
+    """
+    try:
+        run_subprocess("git config --global credential.helper store")
+    except subprocess.CalledProcessError as exc:
+        raise EnvironmentError(exc.stderr)

.venv/lib/python3.13/site-packages/huggingface_hub/_oauth.py

@@ -0,0 +1,464 @@
+import datetime
+import hashlib
+import logging
+import os
+import time
+import urllib.parse
+import warnings
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union
+
+from . import constants
+from .hf_api import whoami
+from .utils import experimental, get_token
+
+
+logger = logging.getLogger(__name__)
+
+if TYPE_CHECKING:
+    import fastapi
+
+
+@dataclass
+class OAuthOrgInfo:
+    """
+    Information about an organization linked to a user logged in with OAuth.
+
+    Attributes:
+        sub (`str`):
+            Unique identifier for the org. OpenID Connect field.
+        name (`str`):
+            The org's full name. OpenID Connect field.
+        preferred_username (`str`):
+            The org's username. OpenID Connect field.
+        picture (`str`):
+            The org's profile picture URL. OpenID Connect field.
+        is_enterprise (`bool`):
+            Whether the org is an enterprise org. Hugging Face field.
+        can_pay (`Optional[bool]`, *optional*):
+            Whether the org has a payment method set up. Hugging Face field.
+        role_in_org (`Optional[str]`, *optional*):
+            The user's role in the org. Hugging Face field.
+        pending_sso (`Optional[bool]`, *optional*):
+            Indicates if the user granted the OAuth app access to the org but didn't complete SSO. Hugging Face field.
+        missing_mfa (`Optional[bool]`, *optional*):
+            Indicates if the user granted the OAuth app access to the org but didn't complete MFA. Hugging Face field.
+    """
+
+    sub: str
+    name: str
+    preferred_username: str
+    picture: str
+    is_enterprise: bool
+    can_pay: Optional[bool] = None
+    role_in_org: Optional[str] = None
+    pending_sso: Optional[bool] = None
+    missing_mfa: Optional[bool] = None
+
+
+@dataclass
+class OAuthUserInfo:
+    """
+    Information about a user logged in with OAuth.
+
+    Attributes:
+        sub (`str`):
+            Unique identifier for the user, even in case of rename. OpenID Connect field.
+        name (`str`):
+            The user's full name. OpenID Connect field.
+        preferred_username (`str`):
+            The user's username. OpenID Connect field.
+        email_verified (`Optional[bool]`, *optional*):
+            Indicates if the user's email is verified. OpenID Connect field.
+        email (`Optional[str]`, *optional*):
+            The user's email address. OpenID Connect field.
+        picture (`str`):
+            The user's profile picture URL. OpenID Connect field.
+        profile (`str`):
+            The user's profile URL. OpenID Connect field.
+        website (`Optional[str]`, *optional*):
+            The user's website URL. OpenID Connect field.
+        is_pro (`bool`):
+            Whether the user is a pro user. Hugging Face field.
+        can_pay (`Optional[bool]`, *optional*):
+            Whether the user has a payment method set up. Hugging Face field.
+        orgs (`Optional[List[OrgInfo]]`, *optional*):
+            List of organizations the user is part of. Hugging Face field.
+    """
+
+    sub: str
+    name: str
+    preferred_username: str
+    email_verified: Optional[bool]
+    email: Optional[str]
+    picture: str
+    profile: str
+    website: Optional[str]
+    is_pro: bool
+    can_pay: Optional[bool]
+    orgs: Optional[List[OAuthOrgInfo]]
+
+
+@dataclass
+class OAuthInfo:
+    """
+    Information about the OAuth login.
+
+    Attributes:
+        access_token (`str`):
+            The access token.
+        access_token_expires_at (`datetime.datetime`):
+            The expiration date of the access token.
+        user_info ([`OAuthUserInfo`]):
+            The user information.
+        state (`str`, *optional*):
+            State passed to the OAuth provider in the original request to the OAuth provider.
+        scope (`str`):
+            Granted scope.
+    """
+
+    access_token: str
+    access_token_expires_at: datetime.datetime
+    user_info: OAuthUserInfo
+    state: Optional[str]
+    scope: str
+
+
+@experimental
+def attach_huggingface_oauth(app: "fastapi.FastAPI", route_prefix: str = "/"):
+    """
+    Add OAuth endpoints to a FastAPI app to enable OAuth login with Hugging Face.
+
+    How to use:
+    - Call this method on your FastAPI app to add the OAuth endpoints.
+    - Inside your route handlers, call `parse_huggingface_oauth(request)` to retrieve the OAuth info.
+    - If user is logged in, an [`OAuthInfo`] object is returned with the user's info. If not, `None` is returned.
+    - In your app, make sure to add links to `/oauth/huggingface/login` and `/oauth/huggingface/logout` for the user to log in and out.
+
+    Example:
+    ```py
+    from huggingface_hub import attach_huggingface_oauth, parse_huggingface_oauth
+
+    # Create a FastAPI app
+    app = FastAPI()
+
+    # Add OAuth endpoints to the FastAPI app
+    attach_huggingface_oauth(app)
+
+    # Add a route that greets the user if they are logged in
+    @app.get("/")
+    def greet_json(request: Request):
+        # Retrieve the OAuth info from the request
+        oauth_info = parse_huggingface_oauth(request)  # e.g. OAuthInfo dataclass
+        if oauth_info is None:
+            return {"msg": "Not logged in!"}
+        return {"msg": f"Hello, {oauth_info.user_info.preferred_username}!"}
+    ```
+    """
+    # TODO: handle generic case (handling OAuth in a non-Space environment with custom dev values) (low priority)
+
+    # Add SessionMiddleware to the FastAPI app to store the OAuth info in the session.
+    # Session Middleware requires a secret key to sign the cookies. Let's use a hash
+    # of the OAuth secret key to make it unique to the Space + updated in case OAuth
+    # config gets updated. When ran locally, we use an empty string as a secret key.
+    try:
+        from starlette.middleware.sessions import SessionMiddleware
+    except ImportError as e:
+        raise ImportError(
+            "Cannot initialize OAuth to due a missing library. Please run `pip install huggingface_hub[oauth]` or add "
+            "`huggingface_hub[oauth]` to your requirements.txt file in order to install the required dependencies."
+        ) from e
+    session_secret = (constants.OAUTH_CLIENT_SECRET or "") + "-v1"
+    app.add_middleware(
+        SessionMiddleware,  # type: ignore[arg-type]
+        secret_key=hashlib.sha256(session_secret.encode()).hexdigest(),
+        same_site="none",
+        https_only=True,
+    )  # type: ignore
+
+    # Add OAuth endpoints to the FastAPI app:
+    #   - {route_prefix}/oauth/huggingface/login
+    #   - {route_prefix}/oauth/huggingface/callback
+    #   - {route_prefix}/oauth/huggingface/logout
+    # If the app is running in a Space, OAuth is enabled normally.
+    # Otherwise, we mock the endpoints to make the user log in with a fake user profile - without any calls to hf.co.
+    route_prefix = route_prefix.strip("/")
+    if os.getenv("SPACE_ID") is not None:
+        logger.info("OAuth is enabled in the Space. Adding OAuth routes.")
+        _add_oauth_routes(app, route_prefix=route_prefix)
+    else:
+        logger.info("App is not running in a Space. Adding mocked OAuth routes.")
+        _add_mocked_oauth_routes(app, route_prefix=route_prefix)
+
+
+def parse_huggingface_oauth(request: "fastapi.Request") -> Optional[OAuthInfo]:
+    """
+    Returns the information from a logged in user as a [`OAuthInfo`] object.
+
+    For flexibility and future-proofing, this method is very lax in its parsing and does not raise errors.
+    Missing fields are set to `None` without a warning.
+
+    Return `None`, if the user is not logged in (no info in session cookie).
+
+    See [`attach_huggingface_oauth`] for an example on how to use this method.
+    """
+    if "oauth_info" not in request.session:
+        logger.debug("No OAuth info in session.")
+        return None
+
+    logger.debug("Parsing OAuth info from session.")
+    oauth_data = request.session["oauth_info"]
+    user_data = oauth_data.get("userinfo", {})
+    orgs_data = user_data.get("orgs", [])
+
+    orgs = (
+        [
+            OAuthOrgInfo(
+                sub=org.get("sub"),
+                name=org.get("name"),
+                preferred_username=org.get("preferred_username"),
+                picture=org.get("picture"),
+                is_enterprise=org.get("isEnterprise"),
+                can_pay=org.get("canPay"),
+                role_in_org=org.get("roleInOrg"),
+                pending_sso=org.get("pendingSSO"),
+                missing_mfa=org.get("missingMFA"),
+            )
+            for org in orgs_data
+        ]
+        if orgs_data
+        else None
+    )
+
+    user_info = OAuthUserInfo(
+        sub=user_data.get("sub"),
+        name=user_data.get("name"),
+        preferred_username=user_data.get("preferred_username"),
+        email_verified=user_data.get("email_verified"),
+        email=user_data.get("email"),
+        picture=user_data.get("picture"),
+        profile=user_data.get("profile"),
+        website=user_data.get("website"),
+        is_pro=user_data.get("isPro"),
+        can_pay=user_data.get("canPay"),
+        orgs=orgs,
+    )
+
+    return OAuthInfo(
+        access_token=oauth_data.get("access_token"),
+        access_token_expires_at=datetime.datetime.fromtimestamp(oauth_data.get("expires_at")),
+        user_info=user_info,
+        state=oauth_data.get("state"),
+        scope=oauth_data.get("scope"),
+    )
+
+
+def _add_oauth_routes(app: "fastapi.FastAPI", route_prefix: str) -> None:
+    """Add OAuth routes to the FastAPI app (login, callback handler and logout)."""
+    try:
+        import fastapi
+        from authlib.integrations.base_client.errors import MismatchingStateError
+        from authlib.integrations.starlette_client import OAuth
+        from fastapi.responses import RedirectResponse
+    except ImportError as e:
+        raise ImportError(
+            "Cannot initialize OAuth to due a missing library. Please run `pip install huggingface_hub[oauth]` or add "
+            "`huggingface_hub[oauth]` to your requirements.txt file."
+        ) from e
+
+    # Check environment variables
+    msg = (
+        "OAuth is required but '{}' environment variable is not set. Make sure you've enabled OAuth in your Space by"
+        " setting `hf_oauth: true` in the Space metadata."
+    )
+    if constants.OAUTH_CLIENT_ID is None:
+        raise ValueError(msg.format("OAUTH_CLIENT_ID"))
+    if constants.OAUTH_CLIENT_SECRET is None:
+        raise ValueError(msg.format("OAUTH_CLIENT_SECRET"))
+    if constants.OAUTH_SCOPES is None:
+        raise ValueError(msg.format("OAUTH_SCOPES"))
+    if constants.OPENID_PROVIDER_URL is None:
+        raise ValueError(msg.format("OPENID_PROVIDER_URL"))
+
+    # Register OAuth server
+    oauth = OAuth()
+    oauth.register(
+        name="huggingface",
+        client_id=constants.OAUTH_CLIENT_ID,
+        client_secret=constants.OAUTH_CLIENT_SECRET,
+        client_kwargs={"scope": constants.OAUTH_SCOPES},
+        server_metadata_url=constants.OPENID_PROVIDER_URL + "/.well-known/openid-configuration",
+    )
+
+    login_uri, callback_uri, logout_uri = _get_oauth_uris(route_prefix)
+
+    # Register OAuth endpoints
+    @app.get(login_uri)
+    async def oauth_login(request: fastapi.Request) -> RedirectResponse:
+        """Endpoint that redirects to HF OAuth page."""
+        redirect_uri = _generate_redirect_uri(request)
+        return await oauth.huggingface.authorize_redirect(request, redirect_uri)  # type: ignore
+
+    @app.get(callback_uri)
+    async def oauth_redirect_callback(request: fastapi.Request) -> RedirectResponse:
+        """Endpoint that handles the OAuth callback."""
+        try:
+            oauth_info = await oauth.huggingface.authorize_access_token(request)  # type: ignore
+        except MismatchingStateError:
+            # Parse query params
+            nb_redirects = int(request.query_params.get("_nb_redirects", 0))
+            target_url = request.query_params.get("_target_url")
+
+            # Build redirect URI with the same query params as before and bump nb_redirects count
+            query_params: Dict[str, Union[int, str]] = {"_nb_redirects": nb_redirects + 1}
+            if target_url:
+                query_params["_target_url"] = target_url
+
+            redirect_uri = f"{login_uri}?{urllib.parse.urlencode(query_params)}"
+
+            # If the user is redirected more than 3 times, it is very likely that the cookie is not working properly.
+            # (e.g. browser is blocking third-party cookies in iframe). In this case, redirect the user in the
+            # non-iframe view.
+            if nb_redirects > constants.OAUTH_MAX_REDIRECTS:
+                host = os.environ.get("SPACE_HOST")
+                if host is None:  # cannot happen in a Space
+                    raise RuntimeError(
+                        "App is not running in a Space (SPACE_HOST environment variable is not set). Cannot redirect to non-iframe view."
+                    ) from None
+                host_url = "https://" + host.rstrip("/")
+                return RedirectResponse(host_url + redirect_uri)
+
+            # Redirect the user to the login page again
+            return RedirectResponse(redirect_uri)
+
+        # OAuth login worked => store the user info in the session and redirect
+        logger.debug("Successfully logged in with OAuth. Storing user info in session.")
+        request.session["oauth_info"] = oauth_info
+        return RedirectResponse(_get_redirect_target(request))
+
+    @app.get(logout_uri)
+    async def oauth_logout(request: fastapi.Request) -> RedirectResponse:
+        """Endpoint that logs out the user (e.g. delete info from cookie session)."""
+        logger.debug("Logged out with OAuth. Removing user info from session.")
+        request.session.pop("oauth_info", None)
+        return RedirectResponse(_get_redirect_target(request))
+
+
+def _add_mocked_oauth_routes(app: "fastapi.FastAPI", route_prefix: str = "/") -> None:
+    """Add fake oauth routes if app is run locally and OAuth is enabled.
+
+    Using OAuth will have the same behavior as in a Space but instead of authenticating with HF, a mocked user profile
+    is added to the session.
+    """
+    try:
+        import fastapi
+        from fastapi.responses import RedirectResponse
+        from starlette.datastructures import URL
+    except ImportError as e:
+        raise ImportError(
+            "Cannot initialize OAuth to due a missing library. Please run `pip install huggingface_hub[oauth]` or add "
+            "`huggingface_hub[oauth]` to your requirements.txt file."
+        ) from e
+
+    warnings.warn(
+        "OAuth is not supported outside of a Space environment. To help you debug your app locally, the oauth endpoints"
+        " are mocked to return your profile and token. To make it work, your machine must be logged in to Huggingface."
+    )
+    mocked_oauth_info = _get_mocked_oauth_info()
+
+    login_uri, callback_uri, logout_uri = _get_oauth_uris(route_prefix)
+
+    # Define OAuth routes
+    @app.get(login_uri)
+    async def oauth_login(request: fastapi.Request) -> RedirectResponse:
+        """Fake endpoint that redirects to HF OAuth page."""
+        # Define target (where to redirect after login)
+        redirect_uri = _generate_redirect_uri(request)
+        return RedirectResponse(callback_uri + "?" + urllib.parse.urlencode({"_target_url": redirect_uri}))
+
+    @app.get(callback_uri)
+    async def oauth_redirect_callback(request: fastapi.Request) -> RedirectResponse:
+        """Endpoint that handles the OAuth callback."""
+        request.session["oauth_info"] = mocked_oauth_info
+        return RedirectResponse(_get_redirect_target(request))
+
+    @app.get(logout_uri)
+    async def oauth_logout(request: fastapi.Request) -> RedirectResponse:
+        """Endpoint that logs out the user (e.g. delete cookie session)."""
+        request.session.pop("oauth_info", None)
+        logout_url = URL("/").include_query_params(**request.query_params)
+        return RedirectResponse(url=logout_url, status_code=302)  # see https://github.com/gradio-app/gradio/pull/9659
+
+
+def _generate_redirect_uri(request: "fastapi.Request") -> str:
+    if "_target_url" in request.query_params:
+        # if `_target_url` already in query params => respect it
+        target = request.query_params["_target_url"]
+    else:
+        # otherwise => keep query params
+        target = "/?" + urllib.parse.urlencode(request.query_params)
+
+    redirect_uri = request.url_for("oauth_redirect_callback").include_query_params(_target_url=target)
+    redirect_uri_as_str = str(redirect_uri)
+    if redirect_uri.netloc.endswith(".hf.space"):
+        # In Space, FastAPI redirect as http but we want https
+        redirect_uri_as_str = redirect_uri_as_str.replace("http://", "https://")
+    return redirect_uri_as_str
+
+
+def _get_redirect_target(request: "fastapi.Request", default_target: str = "/") -> str:
+    return request.query_params.get("_target_url", default_target)
+
+
+def _get_mocked_oauth_info() -> Dict:
+    token = get_token()
+    if token is None:
+        raise ValueError(
+            "Your machine must be logged in to HF to debug an OAuth app locally. Please"
+            " run `huggingface-cli login` or set `HF_TOKEN` as environment variable "
+            "with one of your access token. You can generate a new token in your "
+            "settings page (https://huggingface.co/settings/tokens)."
+        )
+
+    user = whoami()
+    if user["type"] != "user":
+        raise ValueError(
+            "Your machine is not logged in with a personal account. Please use a "
+            "personal access token. You can generate a new token in your settings page"
+            " (https://huggingface.co/settings/tokens)."
+        )
+
+    return {
+        "access_token": token,
+        "token_type": "bearer",
+        "expires_in": 8 * 60 * 60,  # 8 hours
+        "id_token": "FOOBAR",
+        "scope": "openid profile",
+        "refresh_token": "hf_oauth__refresh_token",
+        "expires_at": int(time.time()) + 8 * 60 * 60,  # 8 hours
+        "userinfo": {
+            "sub": "0123456789",
+            "name": user["fullname"],
+            "preferred_username": user["name"],
+            "profile": f"https://huggingface.co/{user['name']}",
+            "picture": user["avatarUrl"],
+            "website": "",
+            "aud": "00000000-0000-0000-0000-000000000000",
+            "auth_time": 1691672844,
+            "nonce": "aaaaaaaaaaaaaaaaaaa",
+            "iat": 1691672844,
+            "exp": 1691676444,
+            "iss": "https://huggingface.co",
+        },
+    }
+
+
+def _get_oauth_uris(route_prefix: str = "/") -> Tuple[str, str, str]:
+    route_prefix = route_prefix.strip("/")
+    if route_prefix:
+        route_prefix = f"/{route_prefix}"
+    return (
+        f"{route_prefix}/oauth/huggingface/login",
+        f"{route_prefix}/oauth/huggingface/callback",
+        f"{route_prefix}/oauth/huggingface/logout",
+    )

.venv/lib/python3.13/site-packages/huggingface_hub/_snapshot_download.py

@@ -0,0 +1,338 @@
+import os
+from pathlib import Path
+from typing import Dict, Iterable, List, Literal, Optional, Type, Union
+
+import requests
+from tqdm.auto import tqdm as base_tqdm
+from tqdm.contrib.concurrent import thread_map
+
+from . import constants
+from .errors import (
+    GatedRepoError,
+    HfHubHTTPError,
+    LocalEntryNotFoundError,
+    RepositoryNotFoundError,
+    RevisionNotFoundError,
+)
+from .file_download import REGEX_COMMIT_HASH, hf_hub_download, repo_folder_name
+from .hf_api import DatasetInfo, HfApi, ModelInfo, RepoFile, SpaceInfo
+from .utils import OfflineModeIsEnabled, filter_repo_objects, logging, validate_hf_hub_args
+from .utils import tqdm as hf_tqdm
+
+
+logger = logging.get_logger(__name__)
+
+VERY_LARGE_REPO_THRESHOLD = 50000  # After this limit, we don't consider `repo_info.siblings` to be reliable enough
+
+
+@validate_hf_hub_args
+def snapshot_download(
+    repo_id: str,
+    *,
+    repo_type: Optional[str] = None,
+    revision: Optional[str] = None,
+    cache_dir: Union[str, Path, None] = None,
+    local_dir: Union[str, Path, None] = None,
+    library_name: Optional[str] = None,
+    library_version: Optional[str] = None,
+    user_agent: Optional[Union[Dict, str]] = None,
+    proxies: Optional[Dict] = None,
+    etag_timeout: float = constants.DEFAULT_ETAG_TIMEOUT,
+    force_download: bool = False,
+    token: Optional[Union[bool, str]] = None,
+    local_files_only: bool = False,
+    allow_patterns: Optional[Union[List[str], str]] = None,
+    ignore_patterns: Optional[Union[List[str], str]] = None,
+    max_workers: int = 8,
+    tqdm_class: Optional[Type[base_tqdm]] = None,
+    headers: Optional[Dict[str, str]] = None,
+    endpoint: Optional[str] = None,
+    # Deprecated args
+    local_dir_use_symlinks: Union[bool, Literal["auto"]] = "auto",
+    resume_download: Optional[bool] = None,
+) -> str:
+    """Download repo files.
+
+    Download a whole snapshot of a repo's files at the specified revision. This is useful when you want all files from
+    a repo, because you don't know which ones you will need a priori. All files are nested inside a folder in order
+    to keep their actual filename relative to that folder. You can also filter which files to download using
+    `allow_patterns` and `ignore_patterns`.
+
+    If `local_dir` is provided, the file structure from the repo will be replicated in this location. When using this
+    option, the `cache_dir` will not be used and a `.cache/huggingface/` folder will be created at the root of `local_dir`
+    to store some metadata related to the downloaded files. While this mechanism is not as robust as the main
+    cache-system, it's optimized for regularly pulling the latest version of a repository.
+
+    An alternative would be to clone the repo but this requires git and git-lfs to be installed and properly
+    configured. It is also not possible to filter which files to download when cloning a repository using git.
+
+    Args:
+        repo_id (`str`):
+            A user or an organization name and a repo name separated by a `/`.
+        repo_type (`str`, *optional*):
+            Set to `"dataset"` or `"space"` if downloading from a dataset or space,
+            `None` or `"model"` if downloading from a model. Default is `None`.
+        revision (`str`, *optional*):
+            An optional Git revision id which can be a branch name, a tag, or a
+            commit hash.
+        cache_dir (`str`, `Path`, *optional*):
+            Path to the folder where cached files are stored.
+        local_dir (`str` or `Path`, *optional*):
+            If provided, the downloaded files will be placed under this directory.
+        library_name (`str`, *optional*):
+            The name of the library to which the object corresponds.
+        library_version (`str`, *optional*):
+            The version of the library.
+        user_agent (`str`, `dict`, *optional*):
+            The user-agent info in the form of a dictionary or a string.
+        proxies (`dict`, *optional*):
+            Dictionary mapping protocol to the URL of the proxy passed to
+            `requests.request`.
+        etag_timeout (`float`, *optional*, defaults to `10`):
+            When fetching ETag, how many seconds to wait for the server to send
+            data before giving up which is passed to `requests.request`.
+        force_download (`bool`, *optional*, defaults to `False`):
+            Whether the file should be downloaded even if it already exists in the local cache.
+        token (`str`, `bool`, *optional*):
+            A token to be used for the download.
+                - If `True`, the token is read from the HuggingFace config
+                  folder.
+                - If a string, it's used as the authentication token.
+        headers (`dict`, *optional*):
+            Additional headers to include in the request. Those headers take precedence over the others.
+        local_files_only (`bool`, *optional*, defaults to `False`):
+            If `True`, avoid downloading the file and return the path to the
+            local cached file if it exists.
+        allow_patterns (`List[str]` or `str`, *optional*):
+            If provided, only files matching at least one pattern are downloaded.
+        ignore_patterns (`List[str]` or `str`, *optional*):
+            If provided, files matching any of the patterns are not downloaded.
+        max_workers (`int`, *optional*):
+            Number of concurrent threads to download files (1 thread = 1 file download).
+            Defaults to 8.
+        tqdm_class (`tqdm`, *optional*):
+            If provided, overwrites the default behavior for the progress bar. Passed
+            argument must inherit from `tqdm.auto.tqdm` or at least mimic its behavior.
+            Note that the `tqdm_class` is not passed to each individual download.
+            Defaults to the custom HF progress bar that can be disabled by setting
+            `HF_HUB_DISABLE_PROGRESS_BARS` environment variable.
+
+    Returns:
+        `str`: folder path of the repo snapshot.
+
+    Raises:
+        [`~utils.RepositoryNotFoundError`]
+            If the repository to download from cannot be found. This may be because it doesn't exist,
+            or because it is set to `private` and you do not have access.
+        [`~utils.RevisionNotFoundError`]
+            If the revision to download from cannot be found.
+        [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+            If `token=True` and the token cannot be found.
+        [`OSError`](https://docs.python.org/3/library/exceptions.html#OSError) if
+            ETag cannot be determined.
+        [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+            if some parameter value is invalid.
+    """
+    if cache_dir is None:
+        cache_dir = constants.HF_HUB_CACHE
+    if revision is None:
+        revision = constants.DEFAULT_REVISION
+    if isinstance(cache_dir, Path):
+        cache_dir = str(cache_dir)
+
+    if repo_type is None:
+        repo_type = "model"
+    if repo_type not in constants.REPO_TYPES:
+        raise ValueError(f"Invalid repo type: {repo_type}. Accepted repo types are: {str(constants.REPO_TYPES)}")
+
+    storage_folder = os.path.join(cache_dir, repo_folder_name(repo_id=repo_id, repo_type=repo_type))
+
+    api = HfApi(
+        library_name=library_name,
+        library_version=library_version,
+        user_agent=user_agent,
+        endpoint=endpoint,
+        headers=headers,
+        token=token,
+    )
+
+    repo_info: Union[ModelInfo, DatasetInfo, SpaceInfo, None] = None
+    api_call_error: Optional[Exception] = None
+    if not local_files_only:
+        # try/except logic to handle different errors => taken from `hf_hub_download`
+        try:
+            # if we have internet connection we want to list files to download
+            repo_info = api.repo_info(repo_id=repo_id, repo_type=repo_type, revision=revision)
+        except (requests.exceptions.SSLError, requests.exceptions.ProxyError):
+            # Actually raise for those subclasses of ConnectionError
+            raise
+        except (
+            requests.exceptions.ConnectionError,
+            requests.exceptions.Timeout,
+            OfflineModeIsEnabled,
+        ) as error:
+            # Internet connection is down
+            # => will try to use local files only
+            api_call_error = error
+            pass
+        except RevisionNotFoundError:
+            # The repo was found but the revision doesn't exist on the Hub (never existed or got deleted)
+            raise
+        except requests.HTTPError as error:
+            # Multiple reasons for an http error:
+            # - Repository is private and invalid/missing token sent
+            # - Repository is gated and invalid/missing token sent
+            # - Hub is down (error 500 or 504)
+            # => let's switch to 'local_files_only=True' to check if the files are already cached.
+            #    (if it's not the case, the error will be re-raised)
+            api_call_error = error
+            pass
+
+    # At this stage, if `repo_info` is None it means either:
+    # - internet connection is down
+    # - internet connection is deactivated (local_files_only=True or HF_HUB_OFFLINE=True)
+    # - repo is private/gated and invalid/missing token sent
+    # - Hub is down
+    # => let's look if we can find the appropriate folder in the cache:
+    #    - if the specified revision is a commit hash, look inside "snapshots".
+    #    - f the specified revision is a branch or tag, look inside "refs".
+    # => if local_dir is not None, we will return the path to the local folder if it exists.
+    if repo_info is None:
+        # Try to get which commit hash corresponds to the specified revision
+        commit_hash = None
+        if REGEX_COMMIT_HASH.match(revision):
+            commit_hash = revision
+        else:
+            ref_path = os.path.join(storage_folder, "refs", revision)
+            if os.path.exists(ref_path):
+                # retrieve commit_hash from refs file
+                with open(ref_path) as f:
+                    commit_hash = f.read()
+
+        # Try to locate snapshot folder for this commit hash
+        if commit_hash is not None and local_dir is None:
+            snapshot_folder = os.path.join(storage_folder, "snapshots", commit_hash)
+            if os.path.exists(snapshot_folder):
+                # Snapshot folder exists => let's return it
+                # (but we can't check if all the files are actually there)
+                return snapshot_folder
+
+        # If local_dir is not None, return it if it exists and is not empty
+        if local_dir is not None:
+            local_dir = Path(local_dir)
+            if local_dir.is_dir() and any(local_dir.iterdir()):
+                logger.warning(
+                    f"Returning existing local_dir `{local_dir}` as remote repo cannot be accessed in `snapshot_download` ({api_call_error})."
+                )
+                return str(local_dir.resolve())
+        # If we couldn't find the appropriate folder on disk, raise an error.
+        if local_files_only:
+            raise LocalEntryNotFoundError(
+                "Cannot find an appropriate cached snapshot folder for the specified revision on the local disk and "
+                "outgoing traffic has been disabled. To enable repo look-ups and downloads online, pass "
+                "'local_files_only=False' as input."
+            )
+        elif isinstance(api_call_error, OfflineModeIsEnabled):
+            raise LocalEntryNotFoundError(
+                "Cannot find an appropriate cached snapshot folder for the specified revision on the local disk and "
+                "outgoing traffic has been disabled. To enable repo look-ups and downloads online, set "
+                "'HF_HUB_OFFLINE=0' as environment variable."
+            ) from api_call_error
+        elif isinstance(api_call_error, (RepositoryNotFoundError, GatedRepoError)) or (
+            isinstance(api_call_error, HfHubHTTPError) and api_call_error.response.status_code == 401
+        ):
+            # Repo not found, gated, or specific authentication error => let's raise the actual error
+            raise api_call_error
+        else:
+            # Otherwise: most likely a connection issue or Hub downtime => let's warn the user
+            raise LocalEntryNotFoundError(
+                "An error happened while trying to locate the files on the Hub and we cannot find the appropriate"
+                " snapshot folder for the specified revision on the local disk. Please check your internet connection"
+                " and try again."
+            ) from api_call_error
+
+    # At this stage, internet connection is up and running
+    # => let's download the files!
+    assert repo_info.sha is not None, "Repo info returned from server must have a revision sha."
+    assert repo_info.siblings is not None, "Repo info returned from server must have a siblings list."
+
+    # Corner case: on very large repos, the siblings list in `repo_info` might not contain all files.
+    # In that case, we need to use the `list_repo_tree` method to prevent caching issues.
+    repo_files: Iterable[str] = [f.rfilename for f in repo_info.siblings]
+    has_many_files = len(repo_info.siblings) > VERY_LARGE_REPO_THRESHOLD
+    if has_many_files:
+        logger.info("The repo has more than 50,000 files. Using `list_repo_tree` to ensure all files are listed.")
+        repo_files = (
+            f.rfilename
+            for f in api.list_repo_tree(repo_id=repo_id, recursive=True, revision=revision, repo_type=repo_type)
+            if isinstance(f, RepoFile)
+        )
+
+    filtered_repo_files: Iterable[str] = filter_repo_objects(
+        items=repo_files,
+        allow_patterns=allow_patterns,
+        ignore_patterns=ignore_patterns,
+    )
+
+    if not has_many_files:
+        filtered_repo_files = list(filtered_repo_files)
+        tqdm_desc = f"Fetching {len(filtered_repo_files)} files"
+    else:
+        tqdm_desc = "Fetching ... files"
+
+    commit_hash = repo_info.sha
+    snapshot_folder = os.path.join(storage_folder, "snapshots", commit_hash)
+    # if passed revision is not identical to commit_hash
+    # then revision has to be a branch name or tag name.
+    # In that case store a ref.
+    if revision != commit_hash:
+        ref_path = os.path.join(storage_folder, "refs", revision)
+        try:
+            os.makedirs(os.path.dirname(ref_path), exist_ok=True)
+            with open(ref_path, "w") as f:
+                f.write(commit_hash)
+        except OSError as e:
+            logger.warning(f"Ignored error while writing commit hash to {ref_path}: {e}.")
+
+    # we pass the commit_hash to hf_hub_download
+    # so no network call happens if we already
+    # have the file locally.
+    def _inner_hf_hub_download(repo_file: str):
+        return hf_hub_download(
+            repo_id,
+            filename=repo_file,
+            repo_type=repo_type,
+            revision=commit_hash,
+            endpoint=endpoint,
+            cache_dir=cache_dir,
+            local_dir=local_dir,
+            local_dir_use_symlinks=local_dir_use_symlinks,
+            library_name=library_name,
+            library_version=library_version,
+            user_agent=user_agent,
+            proxies=proxies,
+            etag_timeout=etag_timeout,
+            resume_download=resume_download,
+            force_download=force_download,
+            token=token,
+            headers=headers,
+        )
+
+    if constants.HF_HUB_ENABLE_HF_TRANSFER:
+        # when using hf_transfer we don't want extra parallelism
+        # from the one hf_transfer provides
+        for file in filtered_repo_files:
+            _inner_hf_hub_download(file)
+    else:
+        thread_map(
+            _inner_hf_hub_download,
+            filtered_repo_files,
+            desc=tqdm_desc,
+            max_workers=max_workers,
+            # User can use its own tqdm class or the default one from `huggingface_hub.utils`
+            tqdm_class=tqdm_class or hf_tqdm,
+        )
+
+    if local_dir is not None:
+        return str(os.path.realpath(local_dir))
+    return snapshot_folder

.venv/lib/python3.13/site-packages/huggingface_hub/_tensorboard_logger.py

@@ -0,0 +1,194 @@
+# Copyright 2023 The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Contains a logger to push training logs to the Hub, using Tensorboard."""
+
+from pathlib import Path
+from typing import TYPE_CHECKING, List, Optional, Union
+
+from ._commit_scheduler import CommitScheduler
+from .errors import EntryNotFoundError
+from .repocard import ModelCard
+from .utils import experimental
+
+
+# Depending on user's setup, SummaryWriter can come either from 'tensorboardX'
+# or from 'torch.utils.tensorboard'. Both are compatible so let's try to load
+# from either of them.
+try:
+    from tensorboardX import SummaryWriter
+
+    is_summary_writer_available = True
+
+except ImportError:
+    try:
+        from torch.utils.tensorboard import SummaryWriter
+
+        is_summary_writer_available = False
+    except ImportError:
+        # Dummy class to avoid failing at import. Will raise on instance creation.
+        SummaryWriter = object
+        is_summary_writer_available = False
+
+if TYPE_CHECKING:
+    from tensorboardX import SummaryWriter
+
+
+class HFSummaryWriter(SummaryWriter):
+    """
+    Wrapper around the tensorboard's `SummaryWriter` to push training logs to the Hub.
+
+    Data is logged locally and then pushed to the Hub asynchronously. Pushing data to the Hub is done in a separate
+    thread to avoid blocking the training script. In particular, if the upload fails for any reason (e.g. a connection
+    issue), the main script will not be interrupted. Data is automatically pushed to the Hub every `commit_every`
+    minutes (default to every 5 minutes).
+
+    <Tip warning={true}>
+
+    `HFSummaryWriter` is experimental. Its API is subject to change in the future without prior notice.
+
+    </Tip>
+
+    Args:
+        repo_id (`str`):
+            The id of the repo to which the logs will be pushed.
+        logdir (`str`, *optional*):
+            The directory where the logs will be written. If not specified, a local directory will be created by the
+            underlying `SummaryWriter` object.
+        commit_every (`int` or `float`, *optional*):
+            The frequency (in minutes) at which the logs will be pushed to the Hub. Defaults to 5 minutes.
+        squash_history (`bool`, *optional*):
+            Whether to squash the history of the repo after each commit. Defaults to `False`. Squashing commits is
+            useful to avoid degraded performances on the repo when it grows too large.
+        repo_type (`str`, *optional*):
+            The type of the repo to which the logs will be pushed. Defaults to "model".
+        repo_revision (`str`, *optional*):
+            The revision of the repo to which the logs will be pushed. Defaults to "main".
+        repo_private (`bool`, *optional*):
+            Whether to make the repo private. If `None` (default), the repo will be public unless the organization's default is private. This value is ignored if the repo already exists.
+        path_in_repo (`str`, *optional*):
+            The path to the folder in the repo where the logs will be pushed. Defaults to "tensorboard/".
+        repo_allow_patterns (`List[str]` or `str`, *optional*):
+            A list of patterns to include in the upload. Defaults to `"*.tfevents.*"`. Check out the
+            [upload guide](https://huggingface.co/docs/huggingface_hub/guides/upload#upload-a-folder) for more details.
+        repo_ignore_patterns (`List[str]` or `str`, *optional*):
+            A list of patterns to exclude in the upload. Check out the
+            [upload guide](https://huggingface.co/docs/huggingface_hub/guides/upload#upload-a-folder) for more details.
+        token (`str`, *optional*):
+            Authentication token. Will default to the stored token. See https://huggingface.co/settings/token for more
+            details
+        kwargs:
+            Additional keyword arguments passed to `SummaryWriter`.
+
+    Examples:
+    ```diff
+    # Taken from https://pytorch.org/docs/stable/tensorboard.html
+    - from torch.utils.tensorboard import SummaryWriter
+    + from huggingface_hub import HFSummaryWriter
+
+    import numpy as np
+
+    - writer = SummaryWriter()
+    + writer = HFSummaryWriter(repo_id="username/my-trained-model")
+
+    for n_iter in range(100):
+        writer.add_scalar('Loss/train', np.random.random(), n_iter)
+        writer.add_scalar('Loss/test', np.random.random(), n_iter)
+        writer.add_scalar('Accuracy/train', np.random.random(), n_iter)
+        writer.add_scalar('Accuracy/test', np.random.random(), n_iter)
+    ```
+
+    ```py
+    >>> from huggingface_hub import HFSummaryWriter
+
+    # Logs are automatically pushed every 15 minutes (5 by default) + when exiting the context manager
+    >>> with HFSummaryWriter(repo_id="test_hf_logger", commit_every=15) as logger:
+    ...     logger.add_scalar("a", 1)
+    ...     logger.add_scalar("b", 2)
+    ```
+    """
+
+    @experimental
+    def __new__(cls, *args, **kwargs) -> "HFSummaryWriter":
+        if not is_summary_writer_available:
+            raise ImportError(
+                "You must have `tensorboard` installed to use `HFSummaryWriter`. Please run `pip install --upgrade"
+                " tensorboardX` first."
+            )
+        return super().__new__(cls)
+
+    def __init__(
+        self,
+        repo_id: str,
+        *,
+        logdir: Optional[str] = None,
+        commit_every: Union[int, float] = 5,
+        squash_history: bool = False,
+        repo_type: Optional[str] = None,
+        repo_revision: Optional[str] = None,
+        repo_private: Optional[bool] = None,
+        path_in_repo: Optional[str] = "tensorboard",
+        repo_allow_patterns: Optional[Union[List[str], str]] = "*.tfevents.*",
+        repo_ignore_patterns: Optional[Union[List[str], str]] = None,
+        token: Optional[str] = None,
+        **kwargs,
+    ):
+        # Initialize SummaryWriter
+        super().__init__(logdir=logdir, **kwargs)
+
+        # Check logdir has been correctly initialized and fail early otherwise. In practice, SummaryWriter takes care of it.
+        if not isinstance(self.logdir, str):
+            raise ValueError(f"`self.logdir` must be a string. Got '{self.logdir}' of type {type(self.logdir)}.")
+
+        # Append logdir name to `path_in_repo`
+        if path_in_repo is None or path_in_repo == "":
+            path_in_repo = Path(self.logdir).name
+        else:
+            path_in_repo = path_in_repo.strip("/") + "/" + Path(self.logdir).name
+
+        # Initialize scheduler
+        self.scheduler = CommitScheduler(
+            folder_path=self.logdir,
+            path_in_repo=path_in_repo,
+            repo_id=repo_id,
+            repo_type=repo_type,
+            revision=repo_revision,
+            private=repo_private,
+            token=token,
+            allow_patterns=repo_allow_patterns,
+            ignore_patterns=repo_ignore_patterns,
+            every=commit_every,
+            squash_history=squash_history,
+        )
+
+        # Exposing some high-level info at root level
+        self.repo_id = self.scheduler.repo_id
+        self.repo_type = self.scheduler.repo_type
+        self.repo_revision = self.scheduler.revision
+
+        # Add `hf-summary-writer` tag to the model card metadata
+        try:
+            card = ModelCard.load(repo_id_or_path=self.repo_id, repo_type=self.repo_type)
+        except EntryNotFoundError:
+            card = ModelCard("")
+        tags = card.data.get("tags", [])
+        if "hf-summary-writer" not in tags:
+            tags.append("hf-summary-writer")
+            card.data["tags"] = tags
+            card.push_to_hub(repo_id=self.repo_id, repo_type=self.repo_type)
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        """Push to hub in a non-blocking way when exiting the logger's context manager."""
+        super().__exit__(exc_type, exc_val, exc_tb)
+        future = self.scheduler.trigger()
+        future.result()

.venv/lib/python3.13/site-packages/huggingface_hub/_upload_large_folder.py

@@ -0,0 +1,625 @@
+# coding=utf-8
+# Copyright 2024-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import enum
+import logging
+import os
+import queue
+import shutil
+import sys
+import threading
+import time
+import traceback
+from datetime import datetime
+from pathlib import Path
+from threading import Lock
+from typing import TYPE_CHECKING, List, Optional, Tuple, Union
+from urllib.parse import quote
+
+from . import constants
+from ._commit_api import CommitOperationAdd, UploadInfo, _fetch_upload_modes
+from ._local_folder import LocalUploadFileMetadata, LocalUploadFilePaths, get_local_upload_paths, read_upload_metadata
+from .constants import DEFAULT_REVISION, REPO_TYPES
+from .utils import DEFAULT_IGNORE_PATTERNS, filter_repo_objects, tqdm
+from .utils._cache_manager import _format_size
+from .utils.sha import sha_fileobj
+
+
+if TYPE_CHECKING:
+    from .hf_api import HfApi
+
+logger = logging.getLogger(__name__)
+
+WAITING_TIME_IF_NO_TASKS = 10  # seconds
+MAX_NB_FILES_FETCH_UPLOAD_MODE = 100
+COMMIT_SIZE_SCALE: List[int] = [20, 50, 75, 100, 125, 200, 250, 400, 600, 1000]
+
+
+def upload_large_folder_internal(
+    api: "HfApi",
+    repo_id: str,
+    folder_path: Union[str, Path],
+    *,
+    repo_type: str,  # Repo type is required!
+    revision: Optional[str] = None,
+    private: Optional[bool] = None,
+    allow_patterns: Optional[Union[List[str], str]] = None,
+    ignore_patterns: Optional[Union[List[str], str]] = None,
+    num_workers: Optional[int] = None,
+    print_report: bool = True,
+    print_report_every: int = 60,
+):
+    """Upload a large folder to the Hub in the most resilient way possible.
+
+    See [`HfApi.upload_large_folder`] for the full documentation.
+    """
+    # 1. Check args and setup
+    if repo_type is None:
+        raise ValueError(
+            "For large uploads, `repo_type` is explicitly required. Please set it to `model`, `dataset` or `space`."
+            " If you are using the CLI, pass it as `--repo-type=model`."
+        )
+    if repo_type not in REPO_TYPES:
+        raise ValueError(f"Invalid repo type, must be one of {REPO_TYPES}")
+    if revision is None:
+        revision = DEFAULT_REVISION
+
+    folder_path = Path(folder_path).expanduser().resolve()
+    if not folder_path.is_dir():
+        raise ValueError(f"Provided path: '{folder_path}' is not a directory")
+
+    if ignore_patterns is None:
+        ignore_patterns = []
+    elif isinstance(ignore_patterns, str):
+        ignore_patterns = [ignore_patterns]
+    ignore_patterns += DEFAULT_IGNORE_PATTERNS
+
+    if num_workers is None:
+        nb_cores = os.cpu_count() or 1
+        num_workers = max(nb_cores - 2, 2)  # Use all but 2 cores, or at least 2 cores
+
+    # 2. Create repo if missing
+    repo_url = api.create_repo(repo_id=repo_id, repo_type=repo_type, private=private, exist_ok=True)
+    logger.info(f"Repo created: {repo_url}")
+    repo_id = repo_url.repo_id
+
+    # 3. List files to upload
+    filtered_paths_list = filter_repo_objects(
+        (path.relative_to(folder_path).as_posix() for path in folder_path.glob("**/*") if path.is_file()),
+        allow_patterns=allow_patterns,
+        ignore_patterns=ignore_patterns,
+    )
+    paths_list = [get_local_upload_paths(folder_path, relpath) for relpath in filtered_paths_list]
+    logger.info(f"Found {len(paths_list)} candidate files to upload")
+
+    # Read metadata for each file
+    items = [
+        (paths, read_upload_metadata(folder_path, paths.path_in_repo))
+        for paths in tqdm(paths_list, desc="Recovering from metadata files")
+    ]
+
+    # 4. Start workers
+    status = LargeUploadStatus(items)
+    threads = [
+        threading.Thread(
+            target=_worker_job,
+            kwargs={
+                "status": status,
+                "api": api,
+                "repo_id": repo_id,
+                "repo_type": repo_type,
+                "revision": revision,
+            },
+        )
+        for _ in range(num_workers)
+    ]
+
+    for thread in threads:
+        thread.start()
+
+    # 5. Print regular reports
+    if print_report:
+        print("\n\n" + status.current_report())
+    last_report_ts = time.time()
+    while True:
+        time.sleep(1)
+        if time.time() - last_report_ts >= print_report_every:
+            if print_report:
+                _print_overwrite(status.current_report())
+            last_report_ts = time.time()
+        if status.is_done():
+            logging.info("Is done: exiting main loop")
+            break
+
+    for thread in threads:
+        thread.join()
+
+    logger.info(status.current_report())
+    logging.info("Upload is complete!")
+
+
+####################
+# Logic to manage workers and synchronize tasks
+####################
+
+
+class WorkerJob(enum.Enum):
+    SHA256 = enum.auto()
+    GET_UPLOAD_MODE = enum.auto()
+    PREUPLOAD_LFS = enum.auto()
+    COMMIT = enum.auto()
+    WAIT = enum.auto()  # if no tasks are available but we don't want to exit
+
+
+JOB_ITEM_T = Tuple[LocalUploadFilePaths, LocalUploadFileMetadata]
+
+
+class LargeUploadStatus:
+    """Contains information, queues and tasks for a large upload process."""
+
+    def __init__(self, items: List[JOB_ITEM_T]):
+        self.items = items
+        self.queue_sha256: "queue.Queue[JOB_ITEM_T]" = queue.Queue()
+        self.queue_get_upload_mode: "queue.Queue[JOB_ITEM_T]" = queue.Queue()
+        self.queue_preupload_lfs: "queue.Queue[JOB_ITEM_T]" = queue.Queue()
+        self.queue_commit: "queue.Queue[JOB_ITEM_T]" = queue.Queue()
+        self.lock = Lock()
+
+        self.nb_workers_sha256: int = 0
+        self.nb_workers_get_upload_mode: int = 0
+        self.nb_workers_preupload_lfs: int = 0
+        self.nb_workers_commit: int = 0
+        self.nb_workers_waiting: int = 0
+        self.last_commit_attempt: Optional[float] = None
+
+        self._started_at = datetime.now()
+        self._chunk_idx: int = 1
+        self._chunk_lock: Lock = Lock()
+
+        # Setup queues
+        for item in self.items:
+            paths, metadata = item
+            if metadata.sha256 is None:
+                self.queue_sha256.put(item)
+            elif metadata.upload_mode is None:
+                self.queue_get_upload_mode.put(item)
+            elif metadata.upload_mode == "lfs" and not metadata.is_uploaded:
+                self.queue_preupload_lfs.put(item)
+            elif not metadata.is_committed:
+                self.queue_commit.put(item)
+            else:
+                logger.debug(f"Skipping file {paths.path_in_repo} (already uploaded and committed)")
+
+    def target_chunk(self) -> int:
+        with self._chunk_lock:
+            return COMMIT_SIZE_SCALE[self._chunk_idx]
+
+    def update_chunk(self, success: bool, nb_items: int, duration: float) -> None:
+        with self._chunk_lock:
+            if not success:
+                logger.warning(f"Failed to commit {nb_items} files at once. Will retry with less files in next batch.")
+                self._chunk_idx -= 1
+            elif nb_items >= COMMIT_SIZE_SCALE[self._chunk_idx] and duration < 40:
+                logger.info(f"Successfully committed {nb_items} at once. Increasing the limit for next batch.")
+                self._chunk_idx += 1
+
+            self._chunk_idx = max(0, min(self._chunk_idx, len(COMMIT_SIZE_SCALE) - 1))
+
+    def current_report(self) -> str:
+        """Generate a report of the current status of the large upload."""
+        nb_hashed = 0
+        size_hashed = 0
+        nb_preuploaded = 0
+        nb_lfs = 0
+        nb_lfs_unsure = 0
+        size_preuploaded = 0
+        nb_committed = 0
+        size_committed = 0
+        total_size = 0
+        ignored_files = 0
+        total_files = 0
+
+        with self.lock:
+            for _, metadata in self.items:
+                if metadata.should_ignore:
+                    ignored_files += 1
+                    continue
+                total_size += metadata.size
+                total_files += 1
+                if metadata.sha256 is not None:
+                    nb_hashed += 1
+                    size_hashed += metadata.size
+                if metadata.upload_mode == "lfs":
+                    nb_lfs += 1
+                if metadata.upload_mode is None:
+                    nb_lfs_unsure += 1
+                if metadata.is_uploaded:
+                    nb_preuploaded += 1
+                    size_preuploaded += metadata.size
+                if metadata.is_committed:
+                    nb_committed += 1
+                    size_committed += metadata.size
+            total_size_str = _format_size(total_size)
+
+            now = datetime.now()
+            now_str = now.strftime("%Y-%m-%d %H:%M:%S")
+            elapsed = now - self._started_at
+            elapsed_str = str(elapsed).split(".")[0]  # remove milliseconds
+
+            message = "\n" + "-" * 10
+            message += f" {now_str} ({elapsed_str}) "
+            message += "-" * 10 + "\n"
+
+            message += "Files:   "
+            message += f"hashed {nb_hashed}/{total_files} ({_format_size(size_hashed)}/{total_size_str}) | "
+            message += f"pre-uploaded: {nb_preuploaded}/{nb_lfs} ({_format_size(size_preuploaded)}/{total_size_str})"
+            if nb_lfs_unsure > 0:
+                message += f" (+{nb_lfs_unsure} unsure)"
+            message += f" | committed: {nb_committed}/{total_files} ({_format_size(size_committed)}/{total_size_str})"
+            message += f" | ignored: {ignored_files}\n"
+
+            message += "Workers: "
+            message += f"hashing: {self.nb_workers_sha256} | "
+            message += f"get upload mode: {self.nb_workers_get_upload_mode} | "
+            message += f"pre-uploading: {self.nb_workers_preupload_lfs} | "
+            message += f"committing: {self.nb_workers_commit} | "
+            message += f"waiting: {self.nb_workers_waiting}\n"
+            message += "-" * 51
+
+            return message
+
+    def is_done(self) -> bool:
+        with self.lock:
+            return all(metadata.is_committed or metadata.should_ignore for _, metadata in self.items)
+
+
+def _worker_job(
+    status: LargeUploadStatus,
+    api: "HfApi",
+    repo_id: str,
+    repo_type: str,
+    revision: str,
+):
+    """
+    Main process for a worker. The worker will perform tasks based on the priority list until all files are uploaded
+    and committed. If no tasks are available, the worker will wait for 10 seconds before checking again.
+
+    If a task fails for any reason, the item(s) are put back in the queue for another worker to pick up.
+
+    Read `upload_large_folder` docstring for more information on how tasks are prioritized.
+    """
+    while True:
+        next_job: Optional[Tuple[WorkerJob, List[JOB_ITEM_T]]] = None
+
+        # Determine next task
+        next_job = _determine_next_job(status)
+        if next_job is None:
+            return
+        job, items = next_job
+
+        # Perform task
+        if job == WorkerJob.SHA256:
+            item = items[0]  # single item
+            try:
+                _compute_sha256(item)
+                status.queue_get_upload_mode.put(item)
+            except KeyboardInterrupt:
+                raise
+            except Exception as e:
+                logger.error(f"Failed to compute sha256: {e}")
+                traceback.format_exc()
+                status.queue_sha256.put(item)
+
+            with status.lock:
+                status.nb_workers_sha256 -= 1
+
+        elif job == WorkerJob.GET_UPLOAD_MODE:
+            try:
+                _get_upload_mode(items, api=api, repo_id=repo_id, repo_type=repo_type, revision=revision)
+            except KeyboardInterrupt:
+                raise
+            except Exception as e:
+                logger.error(f"Failed to get upload mode: {e}")
+                traceback.format_exc()
+
+            # Items are either:
+            # - dropped (if should_ignore)
+            # - put in LFS queue (if LFS)
+            # - put in commit queue (if regular)
+            # - or put back (if error occurred).
+            for item in items:
+                _, metadata = item
+                if metadata.should_ignore:
+                    continue
+                if metadata.upload_mode == "lfs":
+                    status.queue_preupload_lfs.put(item)
+                elif metadata.upload_mode == "regular":
+                    status.queue_commit.put(item)
+                else:
+                    status.queue_get_upload_mode.put(item)
+
+            with status.lock:
+                status.nb_workers_get_upload_mode -= 1
+
+        elif job == WorkerJob.PREUPLOAD_LFS:
+            item = items[0]  # single item
+            try:
+                _preupload_lfs(item, api=api, repo_id=repo_id, repo_type=repo_type, revision=revision)
+                status.queue_commit.put(item)
+            except KeyboardInterrupt:
+                raise
+            except Exception as e:
+                logger.error(f"Failed to preupload LFS: {e}")
+                traceback.format_exc()
+                status.queue_preupload_lfs.put(item)
+
+            with status.lock:
+                status.nb_workers_preupload_lfs -= 1
+
+        elif job == WorkerJob.COMMIT:
+            start_ts = time.time()
+            success = True
+            try:
+                _commit(items, api=api, repo_id=repo_id, repo_type=repo_type, revision=revision)
+            except KeyboardInterrupt:
+                raise
+            except Exception as e:
+                logger.error(f"Failed to commit: {e}")
+                traceback.format_exc()
+                for item in items:
+                    status.queue_commit.put(item)
+                success = False
+            duration = time.time() - start_ts
+            status.update_chunk(success, len(items), duration)
+            with status.lock:
+                status.last_commit_attempt = time.time()
+                status.nb_workers_commit -= 1
+
+        elif job == WorkerJob.WAIT:
+            time.sleep(WAITING_TIME_IF_NO_TASKS)
+            with status.lock:
+                status.nb_workers_waiting -= 1
+
+
+def _determine_next_job(status: LargeUploadStatus) -> Optional[Tuple[WorkerJob, List[JOB_ITEM_T]]]:
+    with status.lock:
+        # 1. Commit if more than 5 minutes since last commit attempt (and at least 1 file)
+        if (
+            status.nb_workers_commit == 0
+            and status.queue_commit.qsize() > 0
+            and status.last_commit_attempt is not None
+            and time.time() - status.last_commit_attempt > 5 * 60
+        ):
+            status.nb_workers_commit += 1
+            logger.debug("Job: commit (more than 5 minutes since last commit attempt)")
+            return (WorkerJob.COMMIT, _get_n(status.queue_commit, status.target_chunk()))
+
+        # 2. Commit if at least 100 files are ready to commit
+        elif status.nb_workers_commit == 0 and status.queue_commit.qsize() >= 150:
+            status.nb_workers_commit += 1
+            logger.debug("Job: commit (>100 files ready)")
+            return (WorkerJob.COMMIT, _get_n(status.queue_commit, status.target_chunk()))
+
+        # 3. Get upload mode if at least 100 files
+        elif status.queue_get_upload_mode.qsize() >= MAX_NB_FILES_FETCH_UPLOAD_MODE:
+            status.nb_workers_get_upload_mode += 1
+            logger.debug(f"Job: get upload mode (>{MAX_NB_FILES_FETCH_UPLOAD_MODE} files ready)")
+            return (WorkerJob.GET_UPLOAD_MODE, _get_n(status.queue_get_upload_mode, MAX_NB_FILES_FETCH_UPLOAD_MODE))
+
+        # 4. Preupload LFS file if at least 1 file and no worker is preuploading LFS
+        elif status.queue_preupload_lfs.qsize() > 0 and status.nb_workers_preupload_lfs == 0:
+            status.nb_workers_preupload_lfs += 1
+            logger.debug("Job: preupload LFS (no other worker preuploading LFS)")
+            return (WorkerJob.PREUPLOAD_LFS, _get_one(status.queue_preupload_lfs))
+
+        # 5. Compute sha256 if at least 1 file and no worker is computing sha256
+        elif status.queue_sha256.qsize() > 0 and status.nb_workers_sha256 == 0:
+            status.nb_workers_sha256 += 1
+            logger.debug("Job: sha256 (no other worker computing sha256)")
+            return (WorkerJob.SHA256, _get_one(status.queue_sha256))
+
+        # 6. Get upload mode if at least 1 file and no worker is getting upload mode
+        elif status.queue_get_upload_mode.qsize() > 0 and status.nb_workers_get_upload_mode == 0:
+            status.nb_workers_get_upload_mode += 1
+            logger.debug("Job: get upload mode (no other worker getting upload mode)")
+            return (WorkerJob.GET_UPLOAD_MODE, _get_n(status.queue_get_upload_mode, MAX_NB_FILES_FETCH_UPLOAD_MODE))
+
+        # 7. Preupload LFS file if at least 1 file
+        #    Skip if hf_transfer is enabled and there is already a worker preuploading LFS
+        elif status.queue_preupload_lfs.qsize() > 0 and (
+            status.nb_workers_preupload_lfs == 0 or not constants.HF_HUB_ENABLE_HF_TRANSFER
+        ):
+            status.nb_workers_preupload_lfs += 1
+            logger.debug("Job: preupload LFS")
+            return (WorkerJob.PREUPLOAD_LFS, _get_one(status.queue_preupload_lfs))
+
+        # 8. Compute sha256 if at least 1 file
+        elif status.queue_sha256.qsize() > 0:
+            status.nb_workers_sha256 += 1
+            logger.debug("Job: sha256")
+            return (WorkerJob.SHA256, _get_one(status.queue_sha256))
+
+        # 9. Get upload mode if at least 1 file
+        elif status.queue_get_upload_mode.qsize() > 0:
+            status.nb_workers_get_upload_mode += 1
+            logger.debug("Job: get upload mode")
+            return (WorkerJob.GET_UPLOAD_MODE, _get_n(status.queue_get_upload_mode, MAX_NB_FILES_FETCH_UPLOAD_MODE))
+
+        # 10. Commit if at least 1 file and 1 min since last commit attempt
+        elif (
+            status.nb_workers_commit == 0
+            and status.queue_commit.qsize() > 0
+            and status.last_commit_attempt is not None
+            and time.time() - status.last_commit_attempt > 1 * 60
+        ):
+            status.nb_workers_commit += 1
+            logger.debug("Job: commit (1 min since last commit attempt)")
+            return (WorkerJob.COMMIT, _get_n(status.queue_commit, status.target_chunk()))
+
+        # 11. Commit if at least 1 file all other queues are empty and all workers are waiting
+        #     e.g. when it's the last commit
+        elif (
+            status.nb_workers_commit == 0
+            and status.queue_commit.qsize() > 0
+            and status.queue_sha256.qsize() == 0
+            and status.queue_get_upload_mode.qsize() == 0
+            and status.queue_preupload_lfs.qsize() == 0
+            and status.nb_workers_sha256 == 0
+            and status.nb_workers_get_upload_mode == 0
+            and status.nb_workers_preupload_lfs == 0
+        ):
+            status.nb_workers_commit += 1
+            logger.debug("Job: commit")
+            return (WorkerJob.COMMIT, _get_n(status.queue_commit, status.target_chunk()))
+
+        # 12. If all queues are empty, exit
+        elif all(metadata.is_committed or metadata.should_ignore for _, metadata in status.items):
+            logger.info("All files have been processed! Exiting worker.")
+            return None
+
+        # 13. If no task is available, wait
+        else:
+            status.nb_workers_waiting += 1
+            logger.debug(f"No task available, waiting... ({WAITING_TIME_IF_NO_TASKS}s)")
+            return (WorkerJob.WAIT, [])
+
+
+####################
+# Atomic jobs (sha256, get_upload_mode, preupload_lfs, commit)
+####################
+
+
+def _compute_sha256(item: JOB_ITEM_T) -> None:
+    """Compute sha256 of a file and save it in metadata."""
+    paths, metadata = item
+    if metadata.sha256 is None:
+        with paths.file_path.open("rb") as f:
+            metadata.sha256 = sha_fileobj(f).hex()
+    metadata.save(paths)
+
+
+def _get_upload_mode(items: List[JOB_ITEM_T], api: "HfApi", repo_id: str, repo_type: str, revision: str) -> None:
+    """Get upload mode for each file and update metadata.
+
+    Also receive info if the file should be ignored.
+    """
+    additions = [_build_hacky_operation(item) for item in items]
+    _fetch_upload_modes(
+        additions=additions,
+        repo_type=repo_type,
+        repo_id=repo_id,
+        headers=api._build_hf_headers(),
+        revision=quote(revision, safe=""),
+        endpoint=api.endpoint,
+    )
+    for item, addition in zip(items, additions):
+        paths, metadata = item
+        metadata.upload_mode = addition._upload_mode
+        metadata.should_ignore = addition._should_ignore
+        metadata.remote_oid = addition._remote_oid
+        metadata.save(paths)
+
+
+def _preupload_lfs(item: JOB_ITEM_T, api: "HfApi", repo_id: str, repo_type: str, revision: str) -> None:
+    """Preupload LFS file and update metadata."""
+    paths, metadata = item
+    addition = _build_hacky_operation(item)
+    api.preupload_lfs_files(
+        repo_id=repo_id,
+        repo_type=repo_type,
+        revision=revision,
+        additions=[addition],
+    )
+
+    metadata.is_uploaded = True
+    metadata.save(paths)
+
+
+def _commit(items: List[JOB_ITEM_T], api: "HfApi", repo_id: str, repo_type: str, revision: str) -> None:
+    """Commit files to the repo."""
+    additions = [_build_hacky_operation(item) for item in items]
+    api.create_commit(
+        repo_id=repo_id,
+        repo_type=repo_type,
+        revision=revision,
+        operations=additions,
+        commit_message="Add files using upload-large-folder tool",
+    )
+    for paths, metadata in items:
+        metadata.is_committed = True
+        metadata.save(paths)
+
+
+####################
+# Hacks with CommitOperationAdd to bypass checks/sha256 calculation
+####################
+
+
+class HackyCommitOperationAdd(CommitOperationAdd):
+    def __post_init__(self) -> None:
+        if isinstance(self.path_or_fileobj, Path):
+            self.path_or_fileobj = str(self.path_or_fileobj)
+
+
+def _build_hacky_operation(item: JOB_ITEM_T) -> HackyCommitOperationAdd:
+    paths, metadata = item
+    operation = HackyCommitOperationAdd(path_in_repo=paths.path_in_repo, path_or_fileobj=paths.file_path)
+    with paths.file_path.open("rb") as file:
+        sample = file.peek(512)[:512]
+    if metadata.sha256 is None:
+        raise ValueError("sha256 must have been computed by now!")
+    operation.upload_info = UploadInfo(sha256=bytes.fromhex(metadata.sha256), size=metadata.size, sample=sample)
+    operation._upload_mode = metadata.upload_mode  # type: ignore[assignment]
+    operation._should_ignore = metadata.should_ignore
+    operation._remote_oid = metadata.remote_oid
+    return operation
+
+
+####################
+# Misc helpers
+####################
+
+
+def _get_one(queue: "queue.Queue[JOB_ITEM_T]") -> List[JOB_ITEM_T]:
+    return [queue.get()]
+
+
+def _get_n(queue: "queue.Queue[JOB_ITEM_T]", n: int) -> List[JOB_ITEM_T]:
+    return [queue.get() for _ in range(min(queue.qsize(), n))]
+
+
+def _print_overwrite(report: str) -> None:
+    """Print a report, overwriting the previous lines.
+
+    Since tqdm in using `sys.stderr` to (re-)write progress bars, we need to use `sys.stdout`
+    to print the report.
+
+    Note: works well only if no other process is writing to `sys.stdout`!
+    """
+    report += "\n"
+    # Get terminal width
+    terminal_width = shutil.get_terminal_size().columns
+
+    # Count number of lines that should be cleared
+    nb_lines = sum(len(line) // terminal_width + 1 for line in report.splitlines())
+
+    # Clear previous lines based on the number of lines in the report
+    for _ in range(nb_lines):
+        sys.stdout.write("\r\033[K")  # Clear line
+        sys.stdout.write("\033[F")  # Move cursor up one line
+
+    # Print the new report, filling remaining space with whitespace
+    sys.stdout.write(report)
+    sys.stdout.write(" " * (terminal_width - len(report.splitlines()[-1])))
+    sys.stdout.flush()

.venv/lib/python3.13/site-packages/huggingface_hub/dataclasses.py

@@ -0,0 +1,481 @@
+import inspect
+from dataclasses import _MISSING_TYPE, MISSING, Field, field, fields
+from functools import wraps
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    List,
+    Literal,
+    Optional,
+    Tuple,
+    Type,
+    TypeVar,
+    Union,
+    get_args,
+    get_origin,
+    overload,
+)
+
+from .errors import (
+    StrictDataclassClassValidationError,
+    StrictDataclassDefinitionError,
+    StrictDataclassFieldValidationError,
+)
+
+
+Validator_T = Callable[[Any], None]
+T = TypeVar("T")
+
+
+# The overload decorator helps type checkers understand the different return types
+@overload
+def strict(cls: Type[T]) -> Type[T]: ...
+
+
+@overload
+def strict(*, accept_kwargs: bool = False) -> Callable[[Type[T]], Type[T]]: ...
+
+
+def strict(
+    cls: Optional[Type[T]] = None, *, accept_kwargs: bool = False
+) -> Union[Type[T], Callable[[Type[T]], Type[T]]]:
+    """
+    Decorator to add strict validation to a dataclass.
+
+    This decorator must be used on top of `@dataclass` to ensure IDEs and static typing tools
+    recognize the class as a dataclass.
+
+    Can be used with or without arguments:
+    - `@strict`
+    - `@strict(accept_kwargs=True)`
+
+    Args:
+        cls:
+            The class to convert to a strict dataclass.
+        accept_kwargs (`bool`, *optional*):
+            If True, allows arbitrary keyword arguments in `__init__`. Defaults to False.
+
+    Returns:
+        The enhanced dataclass with strict validation on field assignment.
+
+    Example:
+    ```py
+    >>> from dataclasses import dataclass
+    >>> from huggingface_hub.dataclasses import as_validated_field, strict, validated_field
+
+    >>> @as_validated_field
+    >>> def positive_int(value: int):
+    ...     if not value >= 0:
+    ...         raise ValueError(f"Value must be positive, got {value}")
+
+    >>> @strict(accept_kwargs=True)
+    ... @dataclass
+    ... class User:
+    ...     name: str
+    ...     age: int = positive_int(default=10)
+
+    # Initialize
+    >>> User(name="John")
+    User(name='John', age=10)
+
+    # Extra kwargs are accepted
+    >>> User(name="John", age=30, lastname="Doe")
+    User(name='John', age=30, *lastname='Doe')
+
+    # Invalid type => raises
+    >>> User(name="John", age="30")
+    huggingface_hub.errors.StrictDataclassFieldValidationError: Validation error for field 'age':
+        TypeError: Field 'age' expected int, got str (value: '30')
+
+    # Invalid value => raises
+    >>> User(name="John", age=-1)
+    huggingface_hub.errors.StrictDataclassFieldValidationError: Validation error for field 'age':
+        ValueError: Value must be positive, got -1
+    ```
+    """
+
+    def wrap(cls: Type[T]) -> Type[T]:
+        if not hasattr(cls, "__dataclass_fields__"):
+            raise StrictDataclassDefinitionError(
+                f"Class '{cls.__name__}' must be a dataclass before applying @strict."
+            )
+
+        # List and store validators
+        field_validators: Dict[str, List[Validator_T]] = {}
+        for f in fields(cls):  # type: ignore [arg-type]
+            validators = []
+            validators.append(_create_type_validator(f))
+            custom_validator = f.metadata.get("validator")
+            if custom_validator is not None:
+                if not isinstance(custom_validator, list):
+                    custom_validator = [custom_validator]
+                for validator in custom_validator:
+                    if not _is_validator(validator):
+                        raise StrictDataclassDefinitionError(
+                            f"Invalid validator for field '{f.name}': {validator}. Must be a callable taking a single argument."
+                        )
+                validators.extend(custom_validator)
+            field_validators[f.name] = validators
+        cls.__validators__ = field_validators  # type: ignore
+
+        # Override __setattr__ to validate fields on assignment
+        original_setattr = cls.__setattr__
+
+        def __strict_setattr__(self: Any, name: str, value: Any) -> None:
+            """Custom __setattr__ method for strict dataclasses."""
+            # Run all validators
+            for validator in self.__validators__.get(name, []):
+                try:
+                    validator(value)
+                except (ValueError, TypeError) as e:
+                    raise StrictDataclassFieldValidationError(field=name, cause=e) from e
+
+            # If validation passed, set the attribute
+            original_setattr(self, name, value)
+
+        cls.__setattr__ = __strict_setattr__  # type: ignore[method-assign]
+
+        if accept_kwargs:
+            # (optional) Override __init__ to accept arbitrary keyword arguments
+            original_init = cls.__init__
+
+            @wraps(original_init)
+            def __init__(self, **kwargs: Any) -> None:
+                # Extract only the fields that are part of the dataclass
+                dataclass_fields = {f.name for f in fields(cls)}  # type: ignore [arg-type]
+                standard_kwargs = {k: v for k, v in kwargs.items() if k in dataclass_fields}
+
+                # Call the original __init__ with standard fields
+                original_init(self, **standard_kwargs)
+
+                # Add any additional kwargs as attributes
+                for name, value in kwargs.items():
+                    if name not in dataclass_fields:
+                        self.__setattr__(name, value)
+
+            cls.__init__ = __init__  # type: ignore[method-assign]
+
+            # (optional) Override __repr__ to include additional kwargs
+            original_repr = cls.__repr__
+
+            @wraps(original_repr)
+            def __repr__(self) -> str:
+                # Call the original __repr__ to get the standard fields
+                standard_repr = original_repr(self)
+
+                # Get additional kwargs
+                additional_kwargs = [
+                    # add a '*' in front of additional kwargs to let the user know they are not part of the dataclass
+                    f"*{k}={v!r}"
+                    for k, v in self.__dict__.items()
+                    if k not in cls.__dataclass_fields__  # type: ignore [attr-defined]
+                ]
+                additional_repr = ", ".join(additional_kwargs)
+
+                # Combine both representations
+                return f"{standard_repr[:-1]}, {additional_repr})" if additional_kwargs else standard_repr
+
+            cls.__repr__ = __repr__  # type: ignore [method-assign]
+
+        # List all public methods starting with `validate_` => class validators.
+        class_validators = []
+
+        for name in dir(cls):
+            if not name.startswith("validate_"):
+                continue
+            method = getattr(cls, name)
+            if not callable(method):
+                continue
+            if len(inspect.signature(method).parameters) != 1:
+                raise StrictDataclassDefinitionError(
+                    f"Class '{cls.__name__}' has a class validator '{name}' that takes more than one argument."
+                    " Class validators must take only 'self' as an argument. Methods starting with 'validate_'"
+                    " are considered to be class validators."
+                )
+            class_validators.append(method)
+
+        cls.__class_validators__ = class_validators  # type: ignore [attr-defined]
+
+        # Add `validate` method to the class, but first check if it already exists
+        def validate(self: T) -> None:
+            """Run class validators on the instance."""
+            for validator in cls.__class_validators__:  # type: ignore [attr-defined]
+                try:
+                    validator(self)
+                except (ValueError, TypeError) as e:
+                    raise StrictDataclassClassValidationError(validator=validator.__name__, cause=e) from e
+
+        # Hack to be able to raise if `.validate()` already exists except if it was created by this decorator on a parent class
+        # (in which case we just override it)
+        validate.__is_defined_by_strict_decorator__ = True  # type: ignore [attr-defined]
+
+        if hasattr(cls, "validate"):
+            if not getattr(cls.validate, "__is_defined_by_strict_decorator__", False):  # type: ignore [attr-defined]
+                raise StrictDataclassDefinitionError(
+                    f"Class '{cls.__name__}' already implements a method called 'validate'."
+                    " This method name is reserved when using the @strict decorator on a dataclass."
+                    " If you want to keep your own method, please rename it."
+                )
+
+        cls.validate = validate  # type: ignore
+
+        # Run class validators after initialization
+        initial_init = cls.__init__
+
+        @wraps(initial_init)
+        def init_with_validate(self, *args, **kwargs) -> None:
+            """Run class validators after initialization."""
+            initial_init(self, *args, **kwargs)  # type: ignore [call-arg]
+            cls.validate(self)  # type: ignore [attr-defined]
+
+        setattr(cls, "__init__", init_with_validate)
+
+        return cls
+
+    # Return wrapped class or the decorator itself
+    return wrap(cls) if cls is not None else wrap
+
+
+def validated_field(
+    validator: Union[List[Validator_T], Validator_T],
+    default: Union[Any, _MISSING_TYPE] = MISSING,
+    default_factory: Union[Callable[[], Any], _MISSING_TYPE] = MISSING,
+    init: bool = True,
+    repr: bool = True,
+    hash: Optional[bool] = None,
+    compare: bool = True,
+    metadata: Optional[Dict] = None,
+    **kwargs: Any,
+) -> Any:
+    """
+    Create a dataclass field with a custom validator.
+
+    Useful to apply several checks to a field. If only applying one rule, check out the [`as_validated_field`] decorator.
+
+    Args:
+        validator (`Callable` or `List[Callable]`):
+            A method that takes a value as input and raises ValueError/TypeError if the value is invalid.
+            Can be a list of validators to apply multiple checks.
+        **kwargs:
+            Additional arguments to pass to `dataclasses.field()`.
+
+    Returns:
+        A field with the validator attached in metadata
+    """
+    if not isinstance(validator, list):
+        validator = [validator]
+    if metadata is None:
+        metadata = {}
+    metadata["validator"] = validator
+    return field(  # type: ignore
+        default=default,  # type: ignore [arg-type]
+        default_factory=default_factory,  # type: ignore [arg-type]
+        init=init,
+        repr=repr,
+        hash=hash,
+        compare=compare,
+        metadata=metadata,
+        **kwargs,
+    )
+
+
+def as_validated_field(validator: Validator_T):
+    """
+    Decorates a validator function as a [`validated_field`] (i.e. a dataclass field with a custom validator).
+
+    Args:
+        validator (`Callable`):
+            A method that takes a value as input and raises ValueError/TypeError if the value is invalid.
+    """
+
+    def _inner(
+        default: Union[Any, _MISSING_TYPE] = MISSING,
+        default_factory: Union[Callable[[], Any], _MISSING_TYPE] = MISSING,
+        init: bool = True,
+        repr: bool = True,
+        hash: Optional[bool] = None,
+        compare: bool = True,
+        metadata: Optional[Dict] = None,
+        **kwargs: Any,
+    ):
+        return validated_field(
+            validator,
+            default=default,
+            default_factory=default_factory,
+            init=init,
+            repr=repr,
+            hash=hash,
+            compare=compare,
+            metadata=metadata,
+            **kwargs,
+        )
+
+    return _inner
+
+
+def type_validator(name: str, value: Any, expected_type: Any) -> None:
+    """Validate that 'value' matches 'expected_type'."""
+    origin = get_origin(expected_type)
+    args = get_args(expected_type)
+
+    if expected_type is Any:
+        return
+    elif validator := _BASIC_TYPE_VALIDATORS.get(origin):
+        validator(name, value, args)
+    elif isinstance(expected_type, type):  # simple types
+        _validate_simple_type(name, value, expected_type)
+    else:
+        raise TypeError(f"Unsupported type for field '{name}': {expected_type}")
+
+
+def _validate_union(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+    """Validate that value matches one of the types in a Union."""
+    errors = []
+    for t in args:
+        try:
+            type_validator(name, value, t)
+            return  # Valid if any type matches
+        except TypeError as e:
+            errors.append(str(e))
+
+    raise TypeError(
+        f"Field '{name}' with value {repr(value)} doesn't match any type in {args}. Errors: {'; '.join(errors)}"
+    )
+
+
+def _validate_literal(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+    """Validate Literal type."""
+    if value not in args:
+        raise TypeError(f"Field '{name}' expected one of {args}, got {value}")
+
+
+def _validate_list(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+    """Validate List[T] type."""
+    if not isinstance(value, list):
+        raise TypeError(f"Field '{name}' expected a list, got {type(value).__name__}")
+
+    # Validate each item in the list
+    item_type = args[0]
+    for i, item in enumerate(value):
+        try:
+            type_validator(f"{name}[{i}]", item, item_type)
+        except TypeError as e:
+            raise TypeError(f"Invalid item at index {i} in list '{name}'") from e
+
+
+def _validate_dict(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+    """Validate Dict[K, V] type."""
+    if not isinstance(value, dict):
+        raise TypeError(f"Field '{name}' expected a dict, got {type(value).__name__}")
+
+    # Validate keys and values
+    key_type, value_type = args
+    for k, v in value.items():
+        try:
+            type_validator(f"{name}.key", k, key_type)
+            type_validator(f"{name}[{k!r}]", v, value_type)
+        except TypeError as e:
+            raise TypeError(f"Invalid key or value in dict '{name}'") from e
+
+
+def _validate_tuple(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+    """Validate Tuple type."""
+    if not isinstance(value, tuple):
+        raise TypeError(f"Field '{name}' expected a tuple, got {type(value).__name__}")
+
+    # Handle variable-length tuples: Tuple[T, ...]
+    if len(args) == 2 and args[1] is Ellipsis:
+        for i, item in enumerate(value):
+            try:
+                type_validator(f"{name}[{i}]", item, args[0])
+            except TypeError as e:
+                raise TypeError(f"Invalid item at index {i} in tuple '{name}'") from e
+    # Handle fixed-length tuples: Tuple[T1, T2, ...]
+    elif len(args) != len(value):
+        raise TypeError(f"Field '{name}' expected a tuple of length {len(args)}, got {len(value)}")
+    else:
+        for i, (item, expected) in enumerate(zip(value, args)):
+            try:
+                type_validator(f"{name}[{i}]", item, expected)
+            except TypeError as e:
+                raise TypeError(f"Invalid item at index {i} in tuple '{name}'") from e
+
+
+def _validate_set(name: str, value: Any, args: Tuple[Any, ...]) -> None:
+    """Validate Set[T] type."""
+    if not isinstance(value, set):
+        raise TypeError(f"Field '{name}' expected a set, got {type(value).__name__}")
+
+    # Validate each item in the set
+    item_type = args[0]
+    for i, item in enumerate(value):
+        try:
+            type_validator(f"{name} item", item, item_type)
+        except TypeError as e:
+            raise TypeError(f"Invalid item in set '{name}'") from e
+
+
+def _validate_simple_type(name: str, value: Any, expected_type: type) -> None:
+    """Validate simple type (int, str, etc.)."""
+    if not isinstance(value, expected_type):
+        raise TypeError(
+            f"Field '{name}' expected {expected_type.__name__}, got {type(value).__name__} (value: {repr(value)})"
+        )
+
+
+def _create_type_validator(field: Field) -> Validator_T:
+    """Create a type validator function for a field."""
+    # Hacky: we cannot use a lambda here because of reference issues
+
+    def validator(value: Any) -> None:
+        type_validator(field.name, value, field.type)
+
+    return validator
+
+
+def _is_validator(validator: Any) -> bool:
+    """Check if a function is a validator.
+
+    A validator is a Callable that can be called with a single positional argument.
+    The validator can have more arguments with default values.
+
+    Basically, returns True if `validator(value)` is possible.
+    """
+    if not callable(validator):
+        return False
+
+    signature = inspect.signature(validator)
+    parameters = list(signature.parameters.values())
+    if len(parameters) == 0:
+        return False
+    if parameters[0].kind not in (
+        inspect.Parameter.POSITIONAL_OR_KEYWORD,
+        inspect.Parameter.POSITIONAL_ONLY,
+        inspect.Parameter.VAR_POSITIONAL,
+    ):
+        return False
+    for parameter in parameters[1:]:
+        if parameter.default == inspect.Parameter.empty:
+            return False
+    return True
+
+
+_BASIC_TYPE_VALIDATORS = {
+    Union: _validate_union,
+    Literal: _validate_literal,
+    list: _validate_list,
+    dict: _validate_dict,
+    tuple: _validate_tuple,
+    set: _validate_set,
+}
+
+
+__all__ = [
+    "strict",
+    "validated_field",
+    "Validator_T",
+    "StrictDataclassClassValidationError",
+    "StrictDataclassDefinitionError",
+    "StrictDataclassFieldValidationError",
+]

.venv/lib/python3.13/site-packages/huggingface_hub/errors.py

@@ -0,0 +1,377 @@
+"""Contains all custom errors."""
+
+from pathlib import Path
+from typing import Optional, Union
+
+from requests import HTTPError, Response
+
+
+# CACHE ERRORS
+
+
+class CacheNotFound(Exception):
+    """Exception thrown when the Huggingface cache is not found."""
+
+    cache_dir: Union[str, Path]
+
+    def __init__(self, msg: str, cache_dir: Union[str, Path], *args, **kwargs):
+        super().__init__(msg, *args, **kwargs)
+        self.cache_dir = cache_dir
+
+
+class CorruptedCacheException(Exception):
+    """Exception for any unexpected structure in the Huggingface cache-system."""
+
+
+# HEADERS ERRORS
+
+
+class LocalTokenNotFoundError(EnvironmentError):
+    """Raised if local token is required but not found."""
+
+
+# HTTP ERRORS
+
+
+class OfflineModeIsEnabled(ConnectionError):
+    """Raised when a request is made but `HF_HUB_OFFLINE=1` is set as environment variable."""
+
+
+class HfHubHTTPError(HTTPError):
+    """
+    HTTPError to inherit from for any custom HTTP Error raised in HF Hub.
+
+    Any HTTPError is converted at least into a `HfHubHTTPError`. If some information is
+    sent back by the server, it will be added to the error message.
+
+    Added details:
+    - Request id from "X-Request-Id" header if exists. If not, fallback to "X-Amzn-Trace-Id" header if exists.
+    - Server error message from the header "X-Error-Message".
+    - Server error message if we can found one in the response body.
+
+    Example:
+    ```py
+        import requests
+        from huggingface_hub.utils import get_session, hf_raise_for_status, HfHubHTTPError
+
+        response = get_session().post(...)
+        try:
+            hf_raise_for_status(response)
+        except HfHubHTTPError as e:
+            print(str(e)) # formatted message
+            e.request_id, e.server_message # details returned by server
+
+            # Complete the error message with additional information once it's raised
+            e.append_to_message("\n`create_commit` expects the repository to exist.")
+            raise
+    ```
+    """
+
+    def __init__(self, message: str, response: Optional[Response] = None, *, server_message: Optional[str] = None):
+        self.request_id = (
+            response.headers.get("x-request-id") or response.headers.get("X-Amzn-Trace-Id")
+            if response is not None
+            else None
+        )
+        self.server_message = server_message
+
+        super().__init__(
+            message,
+            response=response,  # type: ignore [arg-type]
+            request=response.request if response is not None else None,  # type: ignore [arg-type]
+        )
+
+    def append_to_message(self, additional_message: str) -> None:
+        """Append additional information to the `HfHubHTTPError` initial message."""
+        self.args = (self.args[0] + additional_message,) + self.args[1:]
+
+
+# INFERENCE CLIENT ERRORS
+
+
+class InferenceTimeoutError(HTTPError, TimeoutError):
+    """Error raised when a model is unavailable or the request times out."""
+
+
+# INFERENCE ENDPOINT ERRORS
+
+
+class InferenceEndpointError(Exception):
+    """Generic exception when dealing with Inference Endpoints."""
+
+
+class InferenceEndpointTimeoutError(InferenceEndpointError, TimeoutError):
+    """Exception for timeouts while waiting for Inference Endpoint."""
+
+
+# SAFETENSORS ERRORS
+
+
+class SafetensorsParsingError(Exception):
+    """Raised when failing to parse a safetensors file metadata.
+
+    This can be the case if the file is not a safetensors file or does not respect the specification.
+    """
+
+
+class NotASafetensorsRepoError(Exception):
+    """Raised when a repo is not a Safetensors repo i.e. doesn't have either a `model.safetensors` or a
+    `model.safetensors.index.json` file.
+    """
+
+
+# TEXT GENERATION ERRORS
+
+
+class TextGenerationError(HTTPError):
+    """Generic error raised if text-generation went wrong."""
+
+
+# Text Generation Inference Errors
+class ValidationError(TextGenerationError):
+    """Server-side validation error."""
+
+
+class GenerationError(TextGenerationError):
+    pass
+
+
+class OverloadedError(TextGenerationError):
+    pass
+
+
+class IncompleteGenerationError(TextGenerationError):
+    pass
+
+
+class UnknownError(TextGenerationError):
+    pass
+
+
+# VALIDATION ERRORS
+
+
+class HFValidationError(ValueError):
+    """Generic exception thrown by `huggingface_hub` validators.
+
+    Inherits from [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError).
+    """
+
+
+# FILE METADATA ERRORS
+
+
+class FileMetadataError(OSError):
+    """Error triggered when the metadata of a file on the Hub cannot be retrieved (missing ETag or commit_hash).
+
+    Inherits from `OSError` for backward compatibility.
+    """
+
+
+# REPOSITORY ERRORS
+
+
+class RepositoryNotFoundError(HfHubHTTPError):
+    """
+    Raised when trying to access a hf.co URL with an invalid repository name, or
+    with a private repo name the user does not have access to.
+
+    Example:
+
+    ```py
+    >>> from huggingface_hub import model_info
+    >>> model_info("<non_existent_repository>")
+    (...)
+    huggingface_hub.utils._errors.RepositoryNotFoundError: 401 Client Error. (Request ID: PvMw_VjBMjVdMz53WKIzP)
+
+    Repository Not Found for url: https://huggingface.co/api/models/%3Cnon_existent_repository%3E.
+    Please make sure you specified the correct `repo_id` and `repo_type`.
+    If the repo is private, make sure you are authenticated.
+    Invalid username or password.
+    ```
+    """
+
+
+class GatedRepoError(RepositoryNotFoundError):
+    """
+    Raised when trying to access a gated repository for which the user is not on the
+    authorized list.
+
+    Note: derives from `RepositoryNotFoundError` to ensure backward compatibility.
+
+    Example:
+
+    ```py
+    >>> from huggingface_hub import model_info
+    >>> model_info("<gated_repository>")
+    (...)
+    huggingface_hub.utils._errors.GatedRepoError: 403 Client Error. (Request ID: ViT1Bf7O_026LGSQuVqfa)
+
+    Cannot access gated repo for url https://huggingface.co/api/models/ardent-figment/gated-model.
+    Access to model ardent-figment/gated-model is restricted and you are not in the authorized list.
+    Visit https://huggingface.co/ardent-figment/gated-model to ask for access.
+    ```
+    """
+
+
+class DisabledRepoError(HfHubHTTPError):
+    """
+    Raised when trying to access a repository that has been disabled by its author.
+
+    Example:
+
+    ```py
+    >>> from huggingface_hub import dataset_info
+    >>> dataset_info("laion/laion-art")
+    (...)
+    huggingface_hub.utils._errors.DisabledRepoError: 403 Client Error. (Request ID: Root=1-659fc3fa-3031673e0f92c71a2260dbe2;bc6f4dfb-b30a-4862-af0a-5cfe827610d8)
+
+    Cannot access repository for url https://huggingface.co/api/datasets/laion/laion-art.
+    Access to this resource is disabled.
+    ```
+    """
+
+
+# REVISION ERROR
+
+
+class RevisionNotFoundError(HfHubHTTPError):
+    """
+    Raised when trying to access a hf.co URL with a valid repository but an invalid
+    revision.
+
+    Example:
+
+    ```py
+    >>> from huggingface_hub import hf_hub_download
+    >>> hf_hub_download('bert-base-cased', 'config.json', revision='<non-existent-revision>')
+    (...)
+    huggingface_hub.utils._errors.RevisionNotFoundError: 404 Client Error. (Request ID: Mwhe_c3Kt650GcdKEFomX)
+
+    Revision Not Found for url: https://huggingface.co/bert-base-cased/resolve/%3Cnon-existent-revision%3E/config.json.
+    ```
+    """
+
+
+# ENTRY ERRORS
+class EntryNotFoundError(HfHubHTTPError):
+    """
+    Raised when trying to access a hf.co URL with a valid repository and revision
+    but an invalid filename.
+
+    Example:
+
+    ```py
+    >>> from huggingface_hub import hf_hub_download
+    >>> hf_hub_download('bert-base-cased', '<non-existent-file>')
+    (...)
+    huggingface_hub.utils._errors.EntryNotFoundError: 404 Client Error. (Request ID: 53pNl6M0MxsnG5Sw8JA6x)
+
+    Entry Not Found for url: https://huggingface.co/bert-base-cased/resolve/main/%3Cnon-existent-file%3E.
+    ```
+    """
+
+
+class LocalEntryNotFoundError(EntryNotFoundError, FileNotFoundError, ValueError):
+    """
+    Raised when trying to access a file or snapshot that is not on the disk when network is
+    disabled or unavailable (connection issue). The entry may exist on the Hub.
+
+    Note: `ValueError` type is to ensure backward compatibility.
+    Note: `LocalEntryNotFoundError` derives from `HTTPError` because of `EntryNotFoundError`
+          even when it is not a network issue.
+
+    Example:
+
+    ```py
+    >>> from huggingface_hub import hf_hub_download
+    >>> hf_hub_download('bert-base-cased', '<non-cached-file>',  local_files_only=True)
+    (...)
+    huggingface_hub.utils._errors.LocalEntryNotFoundError: Cannot find the requested files in the disk cache and outgoing traffic has been disabled. To enable hf.co look-ups and downloads online, set 'local_files_only' to False.
+    ```
+    """
+
+    def __init__(self, message: str):
+        super().__init__(message, response=None)
+
+
+# REQUEST ERROR
+class BadRequestError(HfHubHTTPError, ValueError):
+    """
+    Raised by `hf_raise_for_status` when the server returns a HTTP 400 error.
+
+    Example:
+
+    ```py
+    >>> resp = requests.post("hf.co/api/check", ...)
+    >>> hf_raise_for_status(resp, endpoint_name="check")
+    huggingface_hub.utils._errors.BadRequestError: Bad request for check endpoint: {details} (Request ID: XXX)
+    ```
+    """
+
+
+# DDUF file format ERROR
+
+
+class DDUFError(Exception):
+    """Base exception for errors related to the DDUF format."""
+
+
+class DDUFCorruptedFileError(DDUFError):
+    """Exception thrown when the DDUF file is corrupted."""
+
+
+class DDUFExportError(DDUFError):
+    """Base exception for errors during DDUF export."""
+
+
+class DDUFInvalidEntryNameError(DDUFExportError):
+    """Exception thrown when the entry name is invalid."""
+
+
+# STRICT DATACLASSES ERRORS
+
+
+class StrictDataclassError(Exception):
+    """Base exception for strict dataclasses."""
+
+
+class StrictDataclassDefinitionError(StrictDataclassError):
+    """Exception thrown when a strict dataclass is defined incorrectly."""
+
+
+class StrictDataclassFieldValidationError(StrictDataclassError):
+    """Exception thrown when a strict dataclass fails validation for a given field."""
+
+    def __init__(self, field: str, cause: Exception):
+        error_message = f"Validation error for field '{field}':"
+        error_message += f"\n    {cause.__class__.__name__}: {cause}"
+        super().__init__(error_message)
+
+
+class StrictDataclassClassValidationError(StrictDataclassError):
+    """Exception thrown when a strict dataclass fails validation on a class validator."""
+
+    def __init__(self, validator: str, cause: Exception):
+        error_message = f"Class validation error for validator '{validator}':"
+        error_message += f"\n    {cause.__class__.__name__}: {cause}"
+        super().__init__(error_message)
+
+
+# XET ERRORS
+
+
+class XetError(Exception):
+    """Base exception for errors related to Xet Storage."""
+
+
+class XetAuthorizationError(XetError):
+    """Exception thrown when the user does not have the right authorization to use Xet Storage."""
+
+
+class XetRefreshTokenError(XetError):
+    """Exception thrown when the refresh token is invalid."""
+
+
+class XetDownloadError(Exception):
+    """Exception thrown when the download from Xet Storage fails."""

.venv/lib/python3.13/site-packages/huggingface_hub/fastai_utils.py

@@ -0,0 +1,425 @@
+import json
+import os
+from pathlib import Path
+from pickle import DEFAULT_PROTOCOL, PicklingError
+from typing import Any, Dict, List, Optional, Union
+
+from packaging import version
+
+from huggingface_hub import constants, snapshot_download
+from huggingface_hub.hf_api import HfApi
+from huggingface_hub.utils import (
+    SoftTemporaryDirectory,
+    get_fastai_version,
+    get_fastcore_version,
+    get_python_version,
+)
+
+from .utils import logging, validate_hf_hub_args
+from .utils._runtime import _PY_VERSION  # noqa: F401 # for backward compatibility...
+
+
+logger = logging.get_logger(__name__)
+
+
+def _check_fastai_fastcore_versions(
+    fastai_min_version: str = "2.4",
+    fastcore_min_version: str = "1.3.27",
+):
+    """
+    Checks that the installed fastai and fastcore versions are compatible for pickle serialization.
+
+    Args:
+        fastai_min_version (`str`, *optional*):
+            The minimum fastai version supported.
+        fastcore_min_version (`str`, *optional*):
+            The minimum fastcore version supported.
+
+    <Tip>
+    Raises the following error:
+
+        - [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError)
+          if the fastai or fastcore libraries are not available or are of an invalid version.
+
+    </Tip>
+    """
+
+    if (get_fastcore_version() or get_fastai_version()) == "N/A":
+        raise ImportError(
+            f"fastai>={fastai_min_version} and fastcore>={fastcore_min_version} are"
+            f" required. Currently using fastai=={get_fastai_version()} and"
+            f" fastcore=={get_fastcore_version()}."
+        )
+
+    current_fastai_version = version.Version(get_fastai_version())
+    current_fastcore_version = version.Version(get_fastcore_version())
+
+    if current_fastai_version < version.Version(fastai_min_version):
+        raise ImportError(
+            "`push_to_hub_fastai` and `from_pretrained_fastai` require a"
+            f" fastai>={fastai_min_version} version, but you are using fastai version"
+            f" {get_fastai_version()} which is incompatible. Upgrade with `pip install"
+            " fastai==2.5.6`."
+        )
+
+    if current_fastcore_version < version.Version(fastcore_min_version):
+        raise ImportError(
+            "`push_to_hub_fastai` and `from_pretrained_fastai` require a"
+            f" fastcore>={fastcore_min_version} version, but you are using fastcore"
+            f" version {get_fastcore_version()} which is incompatible. Upgrade with"
+            " `pip install fastcore==1.3.27`."
+        )
+
+
+def _check_fastai_fastcore_pyproject_versions(
+    storage_folder: str,
+    fastai_min_version: str = "2.4",
+    fastcore_min_version: str = "1.3.27",
+):
+    """
+    Checks that the `pyproject.toml` file in the directory `storage_folder` has fastai and fastcore versions
+    that are compatible with `from_pretrained_fastai` and `push_to_hub_fastai`. If `pyproject.toml` does not exist
+    or does not contain versions for fastai and fastcore, then it logs a warning.
+
+    Args:
+        storage_folder (`str`):
+            Folder to look for the `pyproject.toml` file.
+        fastai_min_version (`str`, *optional*):
+            The minimum fastai version supported.
+        fastcore_min_version (`str`, *optional*):
+            The minimum fastcore version supported.
+
+    <Tip>
+    Raises the following errors:
+
+        - [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError)
+          if the `toml` module is not installed.
+        - [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError)
+          if the `pyproject.toml` indicates a lower than minimum supported version of fastai or fastcore.
+
+    </Tip>
+    """
+
+    try:
+        import toml
+    except ModuleNotFoundError:
+        raise ImportError(
+            "`push_to_hub_fastai` and `from_pretrained_fastai` require the toml module."
+            " Install it with `pip install toml`."
+        )
+
+    # Checks that a `pyproject.toml`, with `build-system` and `requires` sections, exists in the repository. If so, get a list of required packages.
+    if not os.path.isfile(f"{storage_folder}/pyproject.toml"):
+        logger.warning(
+            "There is no `pyproject.toml` in the repository that contains the fastai"
+            " `Learner`. The `pyproject.toml` would allow us to verify that your fastai"
+            " and fastcore versions are compatible with those of the model you want to"
+            " load."
+        )
+        return
+    pyproject_toml = toml.load(f"{storage_folder}/pyproject.toml")
+
+    if "build-system" not in pyproject_toml.keys():
+        logger.warning(
+            "There is no `build-system` section in the pyproject.toml of the repository"
+            " that contains the fastai `Learner`. The `build-system` would allow us to"
+            " verify that your fastai and fastcore versions are compatible with those"
+            " of the model you want to load."
+        )
+        return
+    build_system_toml = pyproject_toml["build-system"]
+
+    if "requires" not in build_system_toml.keys():
+        logger.warning(
+            "There is no `requires` section in the pyproject.toml of the repository"
+            " that contains the fastai `Learner`. The `requires` would allow us to"
+            " verify that your fastai and fastcore versions are compatible with those"
+            " of the model you want to load."
+        )
+        return
+    package_versions = build_system_toml["requires"]
+
+    # Extracts contains fastai and fastcore versions from `pyproject.toml` if available.
+    # If the package is specified but not the version (e.g. "fastai" instead of "fastai=2.4"), the default versions are the highest.
+    fastai_packages = [pck for pck in package_versions if pck.startswith("fastai")]
+    if len(fastai_packages) == 0:
+        logger.warning("The repository does not have a fastai version specified in the `pyproject.toml`.")
+    # fastai_version is an empty string if not specified
+    else:
+        fastai_version = str(fastai_packages[0]).partition("=")[2]
+        if fastai_version != "" and version.Version(fastai_version) < version.Version(fastai_min_version):
+            raise ImportError(
+                "`from_pretrained_fastai` requires"
+                f" fastai>={fastai_min_version} version but the model to load uses"
+                f" {fastai_version} which is incompatible."
+            )
+
+    fastcore_packages = [pck for pck in package_versions if pck.startswith("fastcore")]
+    if len(fastcore_packages) == 0:
+        logger.warning("The repository does not have a fastcore version specified in the `pyproject.toml`.")
+    # fastcore_version is an empty string if not specified
+    else:
+        fastcore_version = str(fastcore_packages[0]).partition("=")[2]
+        if fastcore_version != "" and version.Version(fastcore_version) < version.Version(fastcore_min_version):
+            raise ImportError(
+                "`from_pretrained_fastai` requires"
+                f" fastcore>={fastcore_min_version} version, but you are using fastcore"
+                f" version {fastcore_version} which is incompatible."
+            )
+
+
+README_TEMPLATE = """---
+tags:
+- fastai
+---
+
+# Amazing!
+
+🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
+
+# Some next steps
+1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
+
+2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([documentation here](https://huggingface.co/docs/hub/spaces)).
+
+3. Join the fastai community on the [Fastai Discord](https://discord.com/invite/YKrxeNn)!
+
+Greetings fellow fastlearner 🤝! Don't forget to delete this content from your model card.
+
+
+---
+
+
+# Model card
+
+## Model description
+More information needed
+
+## Intended uses & limitations
+More information needed
+
+## Training and evaluation data
+More information needed
+"""
+
+PYPROJECT_TEMPLATE = f"""[build-system]
+requires = ["setuptools>=40.8.0", "wheel", "python={get_python_version()}", "fastai={get_fastai_version()}", "fastcore={get_fastcore_version()}"]
+build-backend = "setuptools.build_meta:__legacy__"
+"""
+
+
+def _create_model_card(repo_dir: Path):
+    """
+    Creates a model card for the repository.
+
+    Args:
+        repo_dir (`Path`):
+            Directory where model card is created.
+    """
+    readme_path = repo_dir / "README.md"
+
+    if not readme_path.exists():
+        with readme_path.open("w", encoding="utf-8") as f:
+            f.write(README_TEMPLATE)
+
+
+def _create_model_pyproject(repo_dir: Path):
+    """
+    Creates a `pyproject.toml` for the repository.
+
+    Args:
+        repo_dir (`Path`):
+            Directory where `pyproject.toml` is created.
+    """
+    pyproject_path = repo_dir / "pyproject.toml"
+
+    if not pyproject_path.exists():
+        with pyproject_path.open("w", encoding="utf-8") as f:
+            f.write(PYPROJECT_TEMPLATE)
+
+
+def _save_pretrained_fastai(
+    learner,
+    save_directory: Union[str, Path],
+    config: Optional[Dict[str, Any]] = None,
+):
+    """
+    Saves a fastai learner to `save_directory` in pickle format using the default pickle protocol for the version of python used.
+
+    Args:
+        learner (`Learner`):
+            The `fastai.Learner` you'd like to save.
+        save_directory (`str` or `Path`):
+            Specific directory in which you want to save the fastai learner.
+        config (`dict`, *optional*):
+            Configuration object. Will be uploaded as a .json file. Example: 'https://huggingface.co/espejelomar/fastai-pet-breeds-classification/blob/main/config.json'.
+
+    <Tip>
+
+    Raises the following error:
+
+        - [`RuntimeError`](https://docs.python.org/3/library/exceptions.html#RuntimeError)
+          if the config file provided is not a dictionary.
+
+    </Tip>
+    """
+    _check_fastai_fastcore_versions()
+
+    os.makedirs(save_directory, exist_ok=True)
+
+    # if the user provides config then we update it with the fastai and fastcore versions in CONFIG_TEMPLATE.
+    if config is not None:
+        if not isinstance(config, dict):
+            raise RuntimeError(f"Provided config should be a dict. Got: '{type(config)}'")
+        path = os.path.join(save_directory, constants.CONFIG_NAME)
+        with open(path, "w") as f:
+            json.dump(config, f)
+
+    _create_model_card(Path(save_directory))
+    _create_model_pyproject(Path(save_directory))
+
+    # learner.export saves the model in `self.path`.
+    learner.path = Path(save_directory)
+    os.makedirs(save_directory, exist_ok=True)
+    try:
+        learner.export(
+            fname="model.pkl",
+            pickle_protocol=DEFAULT_PROTOCOL,
+        )
+    except PicklingError:
+        raise PicklingError(
+            "You are using a lambda function, i.e., an anonymous function. `pickle`"
+            " cannot pickle function objects and requires that all functions have"
+            " names. One possible solution is to name the function."
+        )
+
+
+@validate_hf_hub_args
+def from_pretrained_fastai(
+    repo_id: str,
+    revision: Optional[str] = None,
+):
+    """
+    Load pretrained fastai model from the Hub or from a local directory.
+
+    Args:
+        repo_id (`str`):
+            The location where the pickled fastai.Learner is. It can be either of the two:
+                - Hosted on the Hugging Face Hub. E.g.: 'espejelomar/fatai-pet-breeds-classification' or 'distilgpt2'.
+                  You can add a `revision` by appending `@` at the end of `repo_id`. E.g.: `dbmdz/bert-base-german-cased@main`.
+                  Revision is the specific model version to use. Since we use a git-based system for storing models and other
+                  artifacts on the Hugging Face Hub, it can be a branch name, a tag name, or a commit id.
+                - Hosted locally. `repo_id` would be a directory containing the pickle and a pyproject.toml
+                  indicating the fastai and fastcore versions used to build the `fastai.Learner`. E.g.: `./my_model_directory/`.
+        revision (`str`, *optional*):
+            Revision at which the repo's files are downloaded. See documentation of `snapshot_download`.
+
+    Returns:
+        The `fastai.Learner` model in the `repo_id` repo.
+    """
+    _check_fastai_fastcore_versions()
+
+    # Load the `repo_id` repo.
+    # `snapshot_download` returns the folder where the model was stored.
+    # `cache_dir` will be the default '/root/.cache/huggingface/hub'
+    if not os.path.isdir(repo_id):
+        storage_folder = snapshot_download(
+            repo_id=repo_id,
+            revision=revision,
+            library_name="fastai",
+            library_version=get_fastai_version(),
+        )
+    else:
+        storage_folder = repo_id
+
+    _check_fastai_fastcore_pyproject_versions(storage_folder)
+
+    from fastai.learner import load_learner  # type: ignore
+
+    return load_learner(os.path.join(storage_folder, "model.pkl"))
+
+
+@validate_hf_hub_args
+def push_to_hub_fastai(
+    learner,
+    *,
+    repo_id: str,
+    commit_message: str = "Push FastAI model using huggingface_hub.",
+    private: Optional[bool] = None,
+    token: Optional[str] = None,
+    config: Optional[dict] = None,
+    branch: Optional[str] = None,
+    create_pr: Optional[bool] = None,
+    allow_patterns: Optional[Union[List[str], str]] = None,
+    ignore_patterns: Optional[Union[List[str], str]] = None,
+    delete_patterns: Optional[Union[List[str], str]] = None,
+    api_endpoint: Optional[str] = None,
+):
+    """
+    Upload learner checkpoint files to the Hub.
+
+    Use `allow_patterns` and `ignore_patterns` to precisely filter which files should be pushed to the hub. Use
+    `delete_patterns` to delete existing remote files in the same commit. See [`upload_folder`] reference for more
+    details.
+
+    Args:
+        learner (`Learner`):
+            The `fastai.Learner' you'd like to push to the Hub.
+        repo_id (`str`):
+            The repository id for your model in Hub in the format of "namespace/repo_name". The namespace can be your individual account or an organization to which you have write access (for example, 'stanfordnlp/stanza-de').
+        commit_message (`str`, *optional*):
+            Message to commit while pushing. Will default to :obj:`"add model"`.
+        private (`bool`, *optional*):
+            Whether or not the repository created should be private.
+            If `None` (default), will default to been public except if the organization's default is private.
+        token (`str`, *optional*):
+            The Hugging Face account token to use as HTTP bearer authorization for remote files. If :obj:`None`, the token will be asked by a prompt.
+        config (`dict`, *optional*):
+            Configuration object to be saved alongside the model weights.
+        branch (`str`, *optional*):
+            The git branch on which to push the model. This defaults to
+            the default branch as specified in your repository, which
+            defaults to `"main"`.
+        create_pr (`boolean`, *optional*):
+            Whether or not to create a Pull Request from `branch` with that commit.
+            Defaults to `False`.
+        api_endpoint (`str`, *optional*):
+            The API endpoint to use when pushing the model to the hub.
+        allow_patterns (`List[str]` or `str`, *optional*):
+            If provided, only files matching at least one pattern are pushed.
+        ignore_patterns (`List[str]` or `str`, *optional*):
+            If provided, files matching any of the patterns are not pushed.
+        delete_patterns (`List[str]` or `str`, *optional*):
+            If provided, remote files matching any of the patterns will be deleted from the repo.
+
+    Returns:
+        The url of the commit of your model in the given repository.
+
+    <Tip>
+
+    Raises the following error:
+
+        - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+          if the user is not log on to the Hugging Face Hub.
+
+    </Tip>
+    """
+    _check_fastai_fastcore_versions()
+    api = HfApi(endpoint=api_endpoint)
+    repo_id = api.create_repo(repo_id=repo_id, token=token, private=private, exist_ok=True).repo_id
+
+    # Push the files to the repo in a single commit
+    with SoftTemporaryDirectory() as tmp:
+        saved_path = Path(tmp) / repo_id
+        _save_pretrained_fastai(learner, saved_path, config=config)
+        return api.upload_folder(
+            repo_id=repo_id,
+            token=token,
+            folder_path=saved_path,
+            commit_message=commit_message,
+            revision=branch,
+            create_pr=create_pr,
+            allow_patterns=allow_patterns,
+            ignore_patterns=ignore_patterns,
+            delete_patterns=delete_patterns,
+        )

.venv/lib/python3.13/site-packages/huggingface_hub/hf_file_system.py

@@ -0,0 +1,1142 @@
+import os
+import re
+import tempfile
+from collections import deque
+from dataclasses import dataclass, field
+from datetime import datetime
+from itertools import chain
+from pathlib import Path
+from typing import Any, Dict, Iterator, List, NoReturn, Optional, Tuple, Union
+from urllib.parse import quote, unquote
+
+import fsspec
+from fsspec.callbacks import _DEFAULT_CALLBACK, NoOpCallback, TqdmCallback
+from fsspec.utils import isfilelike
+from requests import Response
+
+from . import constants
+from ._commit_api import CommitOperationCopy, CommitOperationDelete
+from .errors import EntryNotFoundError, RepositoryNotFoundError, RevisionNotFoundError
+from .file_download import hf_hub_url, http_get
+from .hf_api import HfApi, LastCommitInfo, RepoFile
+from .utils import HFValidationError, hf_raise_for_status, http_backoff
+
+
+# Regex used to match special revisions with "/" in them (see #1710)
+SPECIAL_REFS_REVISION_REGEX = re.compile(
+    r"""
+    (^refs\/convert\/\w+)     # `refs/convert/parquet` revisions
+    |
+    (^refs\/pr\/\d+)          # PR revisions
+    """,
+    re.VERBOSE,
+)
+
+
+@dataclass
+class HfFileSystemResolvedPath:
+    """Data structure containing information about a resolved Hugging Face file system path."""
+
+    repo_type: str
+    repo_id: str
+    revision: str
+    path_in_repo: str
+    # The part placed after '@' in the initial path. It can be a quoted or unquoted refs revision.
+    # Used to reconstruct the unresolved path to return to the user.
+    _raw_revision: Optional[str] = field(default=None, repr=False)
+
+    def unresolve(self) -> str:
+        repo_path = constants.REPO_TYPES_URL_PREFIXES.get(self.repo_type, "") + self.repo_id
+        if self._raw_revision:
+            return f"{repo_path}@{self._raw_revision}/{self.path_in_repo}".rstrip("/")
+        elif self.revision != constants.DEFAULT_REVISION:
+            return f"{repo_path}@{safe_revision(self.revision)}/{self.path_in_repo}".rstrip("/")
+        else:
+            return f"{repo_path}/{self.path_in_repo}".rstrip("/")
+
+
+class HfFileSystem(fsspec.AbstractFileSystem):
+    """
+    Access a remote Hugging Face Hub repository as if were a local file system.
+
+    <Tip warning={true}>
+
+        [`HfFileSystem`] provides fsspec compatibility, which is useful for libraries that require it (e.g., reading
+        Hugging Face datasets directly with `pandas`). However, it introduces additional overhead due to this compatibility
+        layer. For better performance and reliability, it's recommended to use `HfApi` methods when possible.
+
+    </Tip>
+
+    Args:
+        token (`str` or `bool`, *optional*):
+            A valid user access token (string). Defaults to the locally saved
+            token, which is the recommended method for authentication (see
+            https://huggingface.co/docs/huggingface_hub/quick-start#authentication).
+            To disable authentication, pass `False`.
+        endpoint (`str`, *optional*):
+            Endpoint of the Hub. Defaults to <https://huggingface.co>.
+    Usage:
+
+    ```python
+    >>> from huggingface_hub import HfFileSystem
+
+    >>> fs = HfFileSystem()
+
+    >>> # List files
+    >>> fs.glob("my-username/my-model/*.bin")
+    ['my-username/my-model/pytorch_model.bin']
+    >>> fs.ls("datasets/my-username/my-dataset", detail=False)
+    ['datasets/my-username/my-dataset/.gitattributes', 'datasets/my-username/my-dataset/README.md', 'datasets/my-username/my-dataset/data.json']
+
+    >>> # Read/write files
+    >>> with fs.open("my-username/my-model/pytorch_model.bin") as f:
+    ...     data = f.read()
+    >>> with fs.open("my-username/my-model/pytorch_model.bin", "wb") as f:
+    ...     f.write(data)
+    ```
+    """
+
+    root_marker = ""
+    protocol = "hf"
+
+    def __init__(
+        self,
+        *args,
+        endpoint: Optional[str] = None,
+        token: Union[bool, str, None] = None,
+        **storage_options,
+    ):
+        super().__init__(*args, **storage_options)
+        self.endpoint = endpoint or constants.ENDPOINT
+        self.token = token
+        self._api = HfApi(endpoint=endpoint, token=token)
+        # Maps (repo_type, repo_id, revision) to a 2-tuple with:
+        #  * the 1st element indicating whether the repositoy and the revision exist
+        #  * the 2nd element being the exception raised if the repository or revision doesn't exist
+        self._repo_and_revision_exists_cache: Dict[
+            Tuple[str, str, Optional[str]], Tuple[bool, Optional[Exception]]
+        ] = {}
+
+    def _repo_and_revision_exist(
+        self, repo_type: str, repo_id: str, revision: Optional[str]
+    ) -> Tuple[bool, Optional[Exception]]:
+        if (repo_type, repo_id, revision) not in self._repo_and_revision_exists_cache:
+            try:
+                self._api.repo_info(
+                    repo_id, revision=revision, repo_type=repo_type, timeout=constants.HF_HUB_ETAG_TIMEOUT
+                )
+            except (RepositoryNotFoundError, HFValidationError) as e:
+                self._repo_and_revision_exists_cache[(repo_type, repo_id, revision)] = False, e
+                self._repo_and_revision_exists_cache[(repo_type, repo_id, None)] = False, e
+            except RevisionNotFoundError as e:
+                self._repo_and_revision_exists_cache[(repo_type, repo_id, revision)] = False, e
+                self._repo_and_revision_exists_cache[(repo_type, repo_id, None)] = True, None
+            else:
+                self._repo_and_revision_exists_cache[(repo_type, repo_id, revision)] = True, None
+                self._repo_and_revision_exists_cache[(repo_type, repo_id, None)] = True, None
+        return self._repo_and_revision_exists_cache[(repo_type, repo_id, revision)]
+
+    def resolve_path(self, path: str, revision: Optional[str] = None) -> HfFileSystemResolvedPath:
+        """
+        Resolve a Hugging Face file system path into its components.
+
+        Args:
+            path (`str`):
+                Path to resolve.
+            revision (`str`, *optional*):
+                The revision of the repo to resolve. Defaults to the revision specified in the path.
+
+        Returns:
+            [`HfFileSystemResolvedPath`]: Resolved path information containing `repo_type`, `repo_id`, `revision` and `path_in_repo`.
+
+        Raises:
+            `ValueError`:
+                If path contains conflicting revision information.
+            `NotImplementedError`:
+                If trying to list repositories.
+        """
+
+        def _align_revision_in_path_with_revision(
+            revision_in_path: Optional[str], revision: Optional[str]
+        ) -> Optional[str]:
+            if revision is not None:
+                if revision_in_path is not None and revision_in_path != revision:
+                    raise ValueError(
+                        f'Revision specified in path ("{revision_in_path}") and in `revision` argument ("{revision}")'
+                        " are not the same."
+                    )
+            else:
+                revision = revision_in_path
+            return revision
+
+        path = self._strip_protocol(path)
+        if not path:
+            # can't list repositories at root
+            raise NotImplementedError("Access to repositories lists is not implemented.")
+        elif path.split("/")[0] + "/" in constants.REPO_TYPES_URL_PREFIXES.values():
+            if "/" not in path:
+                # can't list repositories at the repository type level
+                raise NotImplementedError("Access to repositories lists is not implemented.")
+            repo_type, path = path.split("/", 1)
+            repo_type = constants.REPO_TYPES_MAPPING[repo_type]
+        else:
+            repo_type = constants.REPO_TYPE_MODEL
+        if path.count("/") > 0:
+            if "@" in path:
+                repo_id, revision_in_path = path.split("@", 1)
+                if "/" in revision_in_path:
+                    match = SPECIAL_REFS_REVISION_REGEX.search(revision_in_path)
+                    if match is not None and revision in (None, match.group()):
+                        # Handle `refs/convert/parquet` and PR revisions separately
+                        path_in_repo = SPECIAL_REFS_REVISION_REGEX.sub("", revision_in_path).lstrip("/")
+                        revision_in_path = match.group()
+                    else:
+                        revision_in_path, path_in_repo = revision_in_path.split("/", 1)
+                else:
+                    path_in_repo = ""
+                revision = _align_revision_in_path_with_revision(unquote(revision_in_path), revision)
+                repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
+                if not repo_and_revision_exist:
+                    _raise_file_not_found(path, err)
+            else:
+                revision_in_path = None
+                repo_id_with_namespace = "/".join(path.split("/")[:2])
+                path_in_repo_with_namespace = "/".join(path.split("/")[2:])
+                repo_id_without_namespace = path.split("/")[0]
+                path_in_repo_without_namespace = "/".join(path.split("/")[1:])
+                repo_id = repo_id_with_namespace
+                path_in_repo = path_in_repo_with_namespace
+                repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
+                if not repo_and_revision_exist:
+                    if isinstance(err, (RepositoryNotFoundError, HFValidationError)):
+                        repo_id = repo_id_without_namespace
+                        path_in_repo = path_in_repo_without_namespace
+                        repo_and_revision_exist, _ = self._repo_and_revision_exist(repo_type, repo_id, revision)
+                        if not repo_and_revision_exist:
+                            _raise_file_not_found(path, err)
+                    else:
+                        _raise_file_not_found(path, err)
+        else:
+            repo_id = path
+            path_in_repo = ""
+            if "@" in path:
+                repo_id, revision_in_path = path.split("@", 1)
+                revision = _align_revision_in_path_with_revision(unquote(revision_in_path), revision)
+            else:
+                revision_in_path = None
+            repo_and_revision_exist, _ = self._repo_and_revision_exist(repo_type, repo_id, revision)
+            if not repo_and_revision_exist:
+                raise NotImplementedError("Access to repositories lists is not implemented.")
+
+        revision = revision if revision is not None else constants.DEFAULT_REVISION
+        return HfFileSystemResolvedPath(repo_type, repo_id, revision, path_in_repo, _raw_revision=revision_in_path)
+
+    def invalidate_cache(self, path: Optional[str] = None) -> None:
+        """
+        Clear the cache for a given path.
+
+        For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.invalidate_cache).
+
+        Args:
+            path (`str`, *optional*):
+                Path to clear from cache. If not provided, clear the entire cache.
+
+        """
+        if not path:
+            self.dircache.clear()
+            self._repo_and_revision_exists_cache.clear()
+        else:
+            resolved_path = self.resolve_path(path)
+            path = resolved_path.unresolve()
+            while path:
+                self.dircache.pop(path, None)
+                path = self._parent(path)
+
+            # Only clear repo cache if path is to repo root
+            if not resolved_path.path_in_repo:
+                self._repo_and_revision_exists_cache.pop((resolved_path.repo_type, resolved_path.repo_id, None), None)
+                self._repo_and_revision_exists_cache.pop(
+                    (resolved_path.repo_type, resolved_path.repo_id, resolved_path.revision), None
+                )
+
+    def _open(
+        self,
+        path: str,
+        mode: str = "rb",
+        revision: Optional[str] = None,
+        block_size: Optional[int] = None,
+        **kwargs,
+    ) -> "HfFileSystemFile":
+        if "a" in mode:
+            raise NotImplementedError("Appending to remote files is not yet supported.")
+        if block_size == 0:
+            return HfFileSystemStreamFile(self, path, mode=mode, revision=revision, block_size=block_size, **kwargs)
+        else:
+            return HfFileSystemFile(self, path, mode=mode, revision=revision, block_size=block_size, **kwargs)
+
+    def _rm(self, path: str, revision: Optional[str] = None, **kwargs) -> None:
+        resolved_path = self.resolve_path(path, revision=revision)
+        self._api.delete_file(
+            path_in_repo=resolved_path.path_in_repo,
+            repo_id=resolved_path.repo_id,
+            token=self.token,
+            repo_type=resolved_path.repo_type,
+            revision=resolved_path.revision,
+            commit_message=kwargs.get("commit_message"),
+            commit_description=kwargs.get("commit_description"),
+        )
+        self.invalidate_cache(path=resolved_path.unresolve())
+
+    def rm(
+        self,
+        path: str,
+        recursive: bool = False,
+        maxdepth: Optional[int] = None,
+        revision: Optional[str] = None,
+        **kwargs,
+    ) -> None:
+        """
+        Delete files from a repository.
+
+        For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.rm).
+
+        <Tip warning={true}>
+
+            Note: When possible, use `HfApi.delete_file()` for better performance.
+
+        </Tip>
+
+        Args:
+            path (`str`):
+                Path to delete.
+            recursive (`bool`, *optional*):
+                If True, delete directory and all its contents. Defaults to False.
+            maxdepth (`int`, *optional*):
+                Maximum number of subdirectories to visit when deleting recursively.
+            revision (`str`, *optional*):
+                The git revision to delete from.
+
+        """
+        resolved_path = self.resolve_path(path, revision=revision)
+        paths = self.expand_path(path, recursive=recursive, maxdepth=maxdepth, revision=revision)
+        paths_in_repo = [self.resolve_path(path).path_in_repo for path in paths if not self.isdir(path)]
+        operations = [CommitOperationDelete(path_in_repo=path_in_repo) for path_in_repo in paths_in_repo]
+        commit_message = f"Delete {path} "
+        commit_message += "recursively " if recursive else ""
+        commit_message += f"up to depth {maxdepth} " if maxdepth is not None else ""
+        # TODO: use `commit_description` to list all the deleted paths?
+        self._api.create_commit(
+            repo_id=resolved_path.repo_id,
+            repo_type=resolved_path.repo_type,
+            token=self.token,
+            operations=operations,
+            revision=resolved_path.revision,
+            commit_message=kwargs.get("commit_message", commit_message),
+            commit_description=kwargs.get("commit_description"),
+        )
+        self.invalidate_cache(path=resolved_path.unresolve())
+
+    def ls(
+        self, path: str, detail: bool = True, refresh: bool = False, revision: Optional[str] = None, **kwargs
+    ) -> List[Union[str, Dict[str, Any]]]:
+        """
+        List the contents of a directory.
+
+        For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.ls).
+
+        <Tip warning={true}>
+
+            Note: When possible, use `HfApi.list_repo_tree()` for better performance.
+
+        </Tip>
+
+        Args:
+            path (`str`):
+                Path to the directory.
+            detail (`bool`, *optional*):
+                If True, returns a list of dictionaries containing file information. If False,
+                returns a list of file paths. Defaults to True.
+            refresh (`bool`, *optional*):
+                If True, bypass the cache and fetch the latest data. Defaults to False.
+            revision (`str`, *optional*):
+                The git revision to list from.
+
+        Returns:
+            `List[Union[str, Dict[str, Any]]]`: List of file paths (if detail=False) or list of file information
+            dictionaries (if detail=True).
+        """
+        resolved_path = self.resolve_path(path, revision=revision)
+        path = resolved_path.unresolve()
+        kwargs = {"expand_info": detail, **kwargs}
+        try:
+            out = self._ls_tree(path, refresh=refresh, revision=revision, **kwargs)
+        except EntryNotFoundError:
+            # Path could be a file
+            if not resolved_path.path_in_repo:
+                _raise_file_not_found(path, None)
+            out = self._ls_tree(self._parent(path), refresh=refresh, revision=revision, **kwargs)
+            out = [o for o in out if o["name"] == path]
+            if len(out) == 0:
+                _raise_file_not_found(path, None)
+        return out if detail else [o["name"] for o in out]
+
+    def _ls_tree(
+        self,
+        path: str,
+        recursive: bool = False,
+        refresh: bool = False,
+        revision: Optional[str] = None,
+        expand_info: bool = True,
+    ):
+        resolved_path = self.resolve_path(path, revision=revision)
+        path = resolved_path.unresolve()
+        root_path = HfFileSystemResolvedPath(
+            resolved_path.repo_type,
+            resolved_path.repo_id,
+            resolved_path.revision,
+            path_in_repo="",
+            _raw_revision=resolved_path._raw_revision,
+        ).unresolve()
+
+        out = []
+        if path in self.dircache and not refresh:
+            cached_path_infos = self.dircache[path]
+            out.extend(cached_path_infos)
+            dirs_not_in_dircache = []
+            if recursive:
+                # Use BFS to traverse the cache and build the "recursive "output
+                # (The Hub uses a so-called "tree first" strategy for the tree endpoint but we sort the output to follow the spec so the result is (eventually) the same)
+                dirs_to_visit = deque(
+                    [path_info for path_info in cached_path_infos if path_info["type"] == "directory"]
+                )
+                while dirs_to_visit:
+                    dir_info = dirs_to_visit.popleft()
+                    if dir_info["name"] not in self.dircache:
+                        dirs_not_in_dircache.append(dir_info["name"])
+                    else:
+                        cached_path_infos = self.dircache[dir_info["name"]]
+                        out.extend(cached_path_infos)
+                        dirs_to_visit.extend(
+                            [path_info for path_info in cached_path_infos if path_info["type"] == "directory"]
+                        )
+
+            dirs_not_expanded = []
+            if expand_info:
+                # Check if there are directories with non-expanded entries
+                dirs_not_expanded = [self._parent(o["name"]) for o in out if o["last_commit"] is None]
+
+            if (recursive and dirs_not_in_dircache) or (expand_info and dirs_not_expanded):
+                # If the dircache is incomplete, find the common path of the missing and non-expanded entries
+                # and extend the output with the result of `_ls_tree(common_path, recursive=True)`
+                common_prefix = os.path.commonprefix(dirs_not_in_dircache + dirs_not_expanded)
+                # Get the parent directory if the common prefix itself is not a directory
+                common_path = (
+                    common_prefix.rstrip("/")
+                    if common_prefix.endswith("/")
+                    or common_prefix == root_path
+                    or common_prefix in chain(dirs_not_in_dircache, dirs_not_expanded)
+                    else self._parent(common_prefix)
+                )
+                out = [o for o in out if not o["name"].startswith(common_path + "/")]
+                for cached_path in self.dircache:
+                    if cached_path.startswith(common_path + "/"):
+                        self.dircache.pop(cached_path, None)
+                self.dircache.pop(common_path, None)
+                out.extend(
+                    self._ls_tree(
+                        common_path,
+                        recursive=recursive,
+                        refresh=True,
+                        revision=revision,
+                        expand_info=expand_info,
+                    )
+                )
+        else:
+            tree = self._api.list_repo_tree(
+                resolved_path.repo_id,
+                resolved_path.path_in_repo,
+                recursive=recursive,
+                expand=expand_info,
+                revision=resolved_path.revision,
+                repo_type=resolved_path.repo_type,
+            )
+            for path_info in tree:
+                if isinstance(path_info, RepoFile):
+                    cache_path_info = {
+                        "name": root_path + "/" + path_info.path,
+                        "size": path_info.size,
+                        "type": "file",
+                        "blob_id": path_info.blob_id,
+                        "lfs": path_info.lfs,
+                        "last_commit": path_info.last_commit,
+                        "security": path_info.security,
+                    }
+                else:
+                    cache_path_info = {
+                        "name": root_path + "/" + path_info.path,
+                        "size": 0,
+                        "type": "directory",
+                        "tree_id": path_info.tree_id,
+                        "last_commit": path_info.last_commit,
+                    }
+                parent_path = self._parent(cache_path_info["name"])
+                self.dircache.setdefault(parent_path, []).append(cache_path_info)
+                out.append(cache_path_info)
+        return out
+
+    def walk(self, path: str, *args, **kwargs) -> Iterator[Tuple[str, List[str], List[str]]]:
+        """
+        Return all files below the given path.
+
+        For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.walk).
+
+        Args:
+            path (`str`):
+                Root path to list files from.
+
+        Returns:
+            `Iterator[Tuple[str, List[str], List[str]]]`: An iterator of (path, list of directory names, list of file names) tuples.
+        """
+        # Set expand_info=False by default to get a x10 speed boost
+        kwargs = {"expand_info": kwargs.get("detail", False), **kwargs}
+        path = self.resolve_path(path, revision=kwargs.get("revision")).unresolve()
+        yield from super().walk(path, *args, **kwargs)
+
+    def glob(self, path: str, **kwargs) -> List[str]:
+        """
+        Find files by glob-matching.
+
+        For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.glob).
+
+        Args:
+            path (`str`):
+                Path pattern to match.
+
+        Returns:
+            `List[str]`: List of paths matching the pattern.
+        """
+        # Set expand_info=False by default to get a x10 speed boost
+        kwargs = {"expand_info": kwargs.get("detail", False), **kwargs}
+        path = self.resolve_path(path, revision=kwargs.get("revision")).unresolve()
+        return super().glob(path, **kwargs)
+
+    def find(
+        self,
+        path: str,
+        maxdepth: Optional[int] = None,
+        withdirs: bool = False,
+        detail: bool = False,
+        refresh: bool = False,
+        revision: Optional[str] = None,
+        **kwargs,
+    ) -> Union[List[str], Dict[str, Dict[str, Any]]]:
+        """
+        List all files below path.
+
+        For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.find).
+
+        Args:
+            path (`str`):
+                Root path to list files from.
+            maxdepth (`int`, *optional*):
+                Maximum depth to descend into subdirectories.
+            withdirs (`bool`, *optional*):
+                Include directory paths in the output. Defaults to False.
+            detail (`bool`, *optional*):
+                If True, returns a dict mapping paths to file information. Defaults to False.
+            refresh (`bool`, *optional*):
+                If True, bypass the cache and fetch the latest data. Defaults to False.
+            revision (`str`, *optional*):
+                The git revision to list from.
+
+        Returns:
+            `Union[List[str], Dict[str, Dict[str, Any]]]`: List of paths or dict of file information.
+        """
+        if maxdepth:
+            return super().find(
+                path, maxdepth=maxdepth, withdirs=withdirs, detail=detail, refresh=refresh, revision=revision, **kwargs
+            )
+        resolved_path = self.resolve_path(path, revision=revision)
+        path = resolved_path.unresolve()
+        kwargs = {"expand_info": detail, **kwargs}
+        try:
+            out = self._ls_tree(path, recursive=True, refresh=refresh, revision=resolved_path.revision, **kwargs)
+        except EntryNotFoundError:
+            # Path could be a file
+            if self.info(path, revision=revision, **kwargs)["type"] == "file":
+                out = {path: {}}
+            else:
+                out = {}
+        else:
+            if not withdirs:
+                out = [o for o in out if o["type"] != "directory"]
+            else:
+                # If `withdirs=True`, include the directory itself to be consistent with the spec
+                path_info = self.info(path, revision=resolved_path.revision, **kwargs)
+                out = [path_info] + out if path_info["type"] == "directory" else out
+            out = {o["name"]: o for o in out}
+        names = sorted(out)
+        if not detail:
+            return names
+        else:
+            return {name: out[name] for name in names}
+
+    def cp_file(self, path1: str, path2: str, revision: Optional[str] = None, **kwargs) -> None:
+        """
+        Copy a file within or between repositories.
+
+        <Tip warning={true}>
+
+            Note: When possible, use `HfApi.upload_file()` for better performance.
+
+        </Tip>
+
+        Args:
+            path1 (`str`):
+                Source path to copy from.
+            path2 (`str`):
+                Destination path to copy to.
+            revision (`str`, *optional*):
+                The git revision to copy from.
+
+        """
+        resolved_path1 = self.resolve_path(path1, revision=revision)
+        resolved_path2 = self.resolve_path(path2, revision=revision)
+
+        same_repo = (
+            resolved_path1.repo_type == resolved_path2.repo_type and resolved_path1.repo_id == resolved_path2.repo_id
+        )
+
+        if same_repo:
+            commit_message = f"Copy {path1} to {path2}"
+            self._api.create_commit(
+                repo_id=resolved_path1.repo_id,
+                repo_type=resolved_path1.repo_type,
+                revision=resolved_path2.revision,
+                commit_message=kwargs.get("commit_message", commit_message),
+                commit_description=kwargs.get("commit_description", ""),
+                operations=[
+                    CommitOperationCopy(
+                        src_path_in_repo=resolved_path1.path_in_repo,
+                        path_in_repo=resolved_path2.path_in_repo,
+                        src_revision=resolved_path1.revision,
+                    )
+                ],
+            )
+        else:
+            with self.open(path1, "rb", revision=resolved_path1.revision) as f:
+                content = f.read()
+            commit_message = f"Copy {path1} to {path2}"
+            self._api.upload_file(
+                path_or_fileobj=content,
+                path_in_repo=resolved_path2.path_in_repo,
+                repo_id=resolved_path2.repo_id,
+                token=self.token,
+                repo_type=resolved_path2.repo_type,
+                revision=resolved_path2.revision,
+                commit_message=kwargs.get("commit_message", commit_message),
+                commit_description=kwargs.get("commit_description"),
+            )
+        self.invalidate_cache(path=resolved_path1.unresolve())
+        self.invalidate_cache(path=resolved_path2.unresolve())
+
+    def modified(self, path: str, **kwargs) -> datetime:
+        """
+        Get the last modified time of a file.
+
+        For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.modified).
+
+        Args:
+            path (`str`):
+                Path to the file.
+
+        Returns:
+            `datetime`: Last commit date of the file.
+        """
+        info = self.info(path, **kwargs)
+        return info["last_commit"]["date"]
+
+    def info(self, path: str, refresh: bool = False, revision: Optional[str] = None, **kwargs) -> Dict[str, Any]:
+        """
+        Get information about a file or directory.
+
+        For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.info).
+
+        <Tip warning={true}>
+
+            Note: When possible, use `HfApi.get_paths_info()` or `HfApi.repo_info()`  for better performance.
+
+        </Tip>
+
+        Args:
+            path (`str`):
+                Path to get info for.
+            refresh (`bool`, *optional*):
+                If True, bypass the cache and fetch the latest data. Defaults to False.
+            revision (`str`, *optional*):
+                The git revision to get info from.
+
+        Returns:
+            `Dict[str, Any]`: Dictionary containing file information (type, size, commit info, etc.).
+
+        """
+        resolved_path = self.resolve_path(path, revision=revision)
+        path = resolved_path.unresolve()
+        expand_info = kwargs.get(
+            "expand_info", True
+        )  # don't expose it as a parameter in the public API to follow the spec
+        if not resolved_path.path_in_repo:
+            # Path is the root directory
+            out = {
+                "name": path,
+                "size": 0,
+                "type": "directory",
+            }
+            if expand_info:
+                last_commit = self._api.list_repo_commits(
+                    resolved_path.repo_id, repo_type=resolved_path.repo_type, revision=resolved_path.revision
+                )[-1]
+                out = {
+                    **out,
+                    "tree_id": None,  # TODO: tree_id of the root directory?
+                    "last_commit": LastCommitInfo(
+                        oid=last_commit.commit_id, title=last_commit.title, date=last_commit.created_at
+                    ),
+                }
+        else:
+            out = None
+            parent_path = self._parent(path)
+            if not expand_info and parent_path not in self.dircache:
+                # Fill the cache with cheap call
+                self.ls(parent_path, expand_info=False)
+            if parent_path in self.dircache:
+                # Check if the path is in the cache
+                out1 = [o for o in self.dircache[parent_path] if o["name"] == path]
+                if not out1:
+                    _raise_file_not_found(path, None)
+                out = out1[0]
+            if refresh or out is None or (expand_info and out and out["last_commit"] is None):
+                paths_info = self._api.get_paths_info(
+                    resolved_path.repo_id,
+                    resolved_path.path_in_repo,
+                    expand=expand_info,
+                    revision=resolved_path.revision,
+                    repo_type=resolved_path.repo_type,
+                )
+                if not paths_info:
+                    _raise_file_not_found(path, None)
+                path_info = paths_info[0]
+                root_path = HfFileSystemResolvedPath(
+                    resolved_path.repo_type,
+                    resolved_path.repo_id,
+                    resolved_path.revision,
+                    path_in_repo="",
+                    _raw_revision=resolved_path._raw_revision,
+                ).unresolve()
+                if isinstance(path_info, RepoFile):
+                    out = {
+                        "name": root_path + "/" + path_info.path,
+                        "size": path_info.size,
+                        "type": "file",
+                        "blob_id": path_info.blob_id,
+                        "lfs": path_info.lfs,
+                        "last_commit": path_info.last_commit,
+                        "security": path_info.security,
+                    }
+                else:
+                    out = {
+                        "name": root_path + "/" + path_info.path,
+                        "size": 0,
+                        "type": "directory",
+                        "tree_id": path_info.tree_id,
+                        "last_commit": path_info.last_commit,
+                    }
+                if not expand_info:
+                    out = {k: out[k] for k in ["name", "size", "type"]}
+        assert out is not None
+        return out
+
+    def exists(self, path, **kwargs):
+        """
+        Check if a file exists.
+
+        For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.exists).
+
+        <Tip warning={true}>
+
+            Note: When possible, use `HfApi.file_exists()` for better performance.
+
+        </Tip>
+
+        Args:
+            path (`str`):
+                Path to check.
+
+        Returns:
+            `bool`: True if file exists, False otherwise.
+        """
+        try:
+            if kwargs.get("refresh", False):
+                self.invalidate_cache(path)
+
+            self.info(path, **{**kwargs, "expand_info": False})
+            return True
+        except:  # noqa: E722
+            return False
+
+    def isdir(self, path):
+        """
+        Check if a path is a directory.
+
+        For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.isdir).
+
+        Args:
+            path (`str`):
+                Path to check.
+
+        Returns:
+            `bool`: True if path is a directory, False otherwise.
+        """
+        try:
+            return self.info(path, expand_info=False)["type"] == "directory"
+        except OSError:
+            return False
+
+    def isfile(self, path):
+        """
+        Check if a path is a file.
+
+        For more details, refer to [fsspec documentation](https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.isfile).
+
+        Args:
+            path (`str`):
+                Path to check.
+
+        Returns:
+            `bool`: True if path is a file, False otherwise.
+        """
+        try:
+            return self.info(path, expand_info=False)["type"] == "file"
+        except:  # noqa: E722
+            return False
+
+    def url(self, path: str) -> str:
+        """
+        Get the HTTP URL of the given path.
+
+        Args:
+            path (`str`):
+                Path to get URL for.
+
+        Returns:
+            `str`: HTTP URL to access the file or directory on the Hub.
+        """
+        resolved_path = self.resolve_path(path)
+        url = hf_hub_url(
+            resolved_path.repo_id,
+            resolved_path.path_in_repo,
+            repo_type=resolved_path.repo_type,
+            revision=resolved_path.revision,
+            endpoint=self.endpoint,
+        )
+        if self.isdir(path):
+            url = url.replace("/resolve/", "/tree/", 1)
+        return url
+
+    def get_file(self, rpath, lpath, callback=_DEFAULT_CALLBACK, outfile=None, **kwargs) -> None:
+        """
+        Copy single remote file to local.
+
+        <Tip warning={true}>
+
+            Note: When possible, use `HfApi.hf_hub_download()` for better performance.
+
+        </Tip>
+
+        Args:
+            rpath (`str`):
+                Remote path to download from.
+            lpath (`str`):
+                Local path to download to.
+            callback (`Callback`, *optional*):
+                Optional callback to track download progress. Defaults to no callback.
+            outfile (`IO`, *optional*):
+                Optional file-like object to write to. If provided, `lpath` is ignored.
+
+        """
+        revision = kwargs.get("revision")
+        unhandled_kwargs = set(kwargs.keys()) - {"revision"}
+        if not isinstance(callback, (NoOpCallback, TqdmCallback)) or len(unhandled_kwargs) > 0:
+            # for now, let's not handle custom callbacks
+            # and let's not handle custom kwargs
+            return super().get_file(rpath, lpath, callback=callback, outfile=outfile, **kwargs)
+
+        # Taken from https://github.com/fsspec/filesystem_spec/blob/47b445ae4c284a82dd15e0287b1ffc410e8fc470/fsspec/spec.py#L883
+        if isfilelike(lpath):
+            outfile = lpath
+        elif self.isdir(rpath):
+            os.makedirs(lpath, exist_ok=True)
+            return None
+
+        if isinstance(lpath, (str, Path)):  # otherwise, let's assume it's a file-like object
+            os.makedirs(os.path.dirname(lpath), exist_ok=True)
+
+        # Open file if not already open
+        close_file = False
+        if outfile is None:
+            outfile = open(lpath, "wb")
+            close_file = True
+        initial_pos = outfile.tell()
+
+        # Custom implementation of `get_file` to use `http_get`.
+        resolve_remote_path = self.resolve_path(rpath, revision=revision)
+        expected_size = self.info(rpath, revision=revision)["size"]
+        callback.set_size(expected_size)
+        try:
+            http_get(
+                url=hf_hub_url(
+                    repo_id=resolve_remote_path.repo_id,
+                    revision=resolve_remote_path.revision,
+                    filename=resolve_remote_path.path_in_repo,
+                    repo_type=resolve_remote_path.repo_type,
+                    endpoint=self.endpoint,
+                ),
+                temp_file=outfile,
+                displayed_filename=rpath,
+                expected_size=expected_size,
+                resume_size=0,
+                headers=self._api._build_hf_headers(),
+                _tqdm_bar=callback.tqdm if isinstance(callback, TqdmCallback) else None,
+            )
+            outfile.seek(initial_pos)
+        finally:
+            # Close file only if we opened it ourselves
+            if close_file:
+                outfile.close()
+
+    @property
+    def transaction(self):
+        """A context within which files are committed together upon exit
+
+        Requires the file class to implement `.commit()` and `.discard()`
+        for the normal and exception cases.
+        """
+        # Taken from https://github.com/fsspec/filesystem_spec/blob/3fbb6fee33b46cccb015607630843dea049d3243/fsspec/spec.py#L231
+        # See https://github.com/huggingface/huggingface_hub/issues/1733
+        raise NotImplementedError("Transactional commits are not supported.")
+
+    def start_transaction(self):
+        """Begin write transaction for deferring files, non-context version"""
+        # Taken from https://github.com/fsspec/filesystem_spec/blob/3fbb6fee33b46cccb015607630843dea049d3243/fsspec/spec.py#L241
+        # See https://github.com/huggingface/huggingface_hub/issues/1733
+        raise NotImplementedError("Transactional commits are not supported.")
+
+
+class HfFileSystemFile(fsspec.spec.AbstractBufferedFile):
+    def __init__(self, fs: HfFileSystem, path: str, revision: Optional[str] = None, **kwargs):
+        try:
+            self.resolved_path = fs.resolve_path(path, revision=revision)
+        except FileNotFoundError as e:
+            if "w" in kwargs.get("mode", ""):
+                raise FileNotFoundError(
+                    f"{e}.\nMake sure the repository and revision exist before writing data."
+                ) from e
+            raise
+        # avoid an unnecessary .info() call with expensive expand_info=True to instantiate .details
+        if kwargs.get("mode", "rb") == "rb":
+            self.details = fs.info(self.resolved_path.unresolve(), expand_info=False)
+        super().__init__(fs, self.resolved_path.unresolve(), **kwargs)
+        self.fs: HfFileSystem
+
+    def __del__(self):
+        if not hasattr(self, "resolved_path"):
+            # Means that the constructor failed. Nothing to do.
+            return
+        return super().__del__()
+
+    def _fetch_range(self, start: int, end: int) -> bytes:
+        headers = {
+            "range": f"bytes={start}-{end - 1}",
+            **self.fs._api._build_hf_headers(),
+        }
+        url = hf_hub_url(
+            repo_id=self.resolved_path.repo_id,
+            revision=self.resolved_path.revision,
+            filename=self.resolved_path.path_in_repo,
+            repo_type=self.resolved_path.repo_type,
+            endpoint=self.fs.endpoint,
+        )
+        r = http_backoff(
+            "GET",
+            url,
+            headers=headers,
+            retry_on_status_codes=(500, 502, 503, 504),
+            timeout=constants.HF_HUB_DOWNLOAD_TIMEOUT,
+        )
+        hf_raise_for_status(r)
+        return r.content
+
+    def _initiate_upload(self) -> None:
+        self.temp_file = tempfile.NamedTemporaryFile(prefix="hffs-", delete=False)
+
+    def _upload_chunk(self, final: bool = False) -> None:
+        self.buffer.seek(0)
+        block = self.buffer.read()
+        self.temp_file.write(block)
+        if final:
+            self.temp_file.close()
+            self.fs._api.upload_file(
+                path_or_fileobj=self.temp_file.name,
+                path_in_repo=self.resolved_path.path_in_repo,
+                repo_id=self.resolved_path.repo_id,
+                token=self.fs.token,
+                repo_type=self.resolved_path.repo_type,
+                revision=self.resolved_path.revision,
+                commit_message=self.kwargs.get("commit_message"),
+                commit_description=self.kwargs.get("commit_description"),
+            )
+            os.remove(self.temp_file.name)
+            self.fs.invalidate_cache(
+                path=self.resolved_path.unresolve(),
+            )
+
+    def read(self, length=-1):
+        """Read remote file.
+
+        If `length` is not provided or is -1, the entire file is downloaded and read. On POSIX systems and if
+        `hf_transfer` is not enabled, the file is loaded in memory directly. Otherwise, the file is downloaded to a
+        temporary file and read from there.
+        """
+        if self.mode == "rb" and (length is None or length == -1) and self.loc == 0:
+            with self.fs.open(self.path, "rb", block_size=0) as f:  # block_size=0 enables fast streaming
+                out = f.read()
+                self.loc += len(out)
+                return out
+        return super().read(length)
+
+    def url(self) -> str:
+        return self.fs.url(self.path)
+
+
+class HfFileSystemStreamFile(fsspec.spec.AbstractBufferedFile):
+    def __init__(
+        self,
+        fs: HfFileSystem,
+        path: str,
+        mode: str = "rb",
+        revision: Optional[str] = None,
+        block_size: int = 0,
+        cache_type: str = "none",
+        **kwargs,
+    ):
+        if block_size != 0:
+            raise ValueError(f"HfFileSystemStreamFile only supports block_size=0 but got {block_size}")
+        if cache_type != "none":
+            raise ValueError(f"HfFileSystemStreamFile only supports cache_type='none' but got {cache_type}")
+        if "w" in mode:
+            raise ValueError(f"HfFileSystemStreamFile only supports reading but got mode='{mode}'")
+        try:
+            self.resolved_path = fs.resolve_path(path, revision=revision)
+        except FileNotFoundError as e:
+            if "w" in kwargs.get("mode", ""):
+                raise FileNotFoundError(
+                    f"{e}.\nMake sure the repository and revision exist before writing data."
+                ) from e
+        # avoid an unnecessary .info() call to instantiate .details
+        self.details = {"name": self.resolved_path.unresolve(), "size": None}
+        super().__init__(
+            fs, self.resolved_path.unresolve(), mode=mode, block_size=block_size, cache_type=cache_type, **kwargs
+        )
+        self.response: Optional[Response] = None
+        self.fs: HfFileSystem
+
+    def seek(self, loc: int, whence: int = 0):
+        if loc == 0 and whence == 1:
+            return
+        if loc == self.loc and whence == 0:
+            return
+        raise ValueError("Cannot seek streaming HF file")
+
+    def read(self, length: int = -1):
+        read_args = (length,) if length >= 0 else ()
+        if self.response is None:
+            url = hf_hub_url(
+                repo_id=self.resolved_path.repo_id,
+                revision=self.resolved_path.revision,
+                filename=self.resolved_path.path_in_repo,
+                repo_type=self.resolved_path.repo_type,
+                endpoint=self.fs.endpoint,
+            )
+            self.response = http_backoff(
+                "GET",
+                url,
+                headers=self.fs._api._build_hf_headers(),
+                retry_on_status_codes=(500, 502, 503, 504),
+                stream=True,
+                timeout=constants.HF_HUB_DOWNLOAD_TIMEOUT,
+            )
+            hf_raise_for_status(self.response)
+        try:
+            out = self.response.raw.read(*read_args)
+        except Exception:
+            self.response.close()
+
+            # Retry by recreating the connection
+            url = hf_hub_url(
+                repo_id=self.resolved_path.repo_id,
+                revision=self.resolved_path.revision,
+                filename=self.resolved_path.path_in_repo,
+                repo_type=self.resolved_path.repo_type,
+                endpoint=self.fs.endpoint,
+            )
+            self.response = http_backoff(
+                "GET",
+                url,
+                headers={"Range": "bytes=%d-" % self.loc, **self.fs._api._build_hf_headers()},
+                retry_on_status_codes=(500, 502, 503, 504),
+                stream=True,
+                timeout=constants.HF_HUB_DOWNLOAD_TIMEOUT,
+            )
+            hf_raise_for_status(self.response)
+            try:
+                out = self.response.raw.read(*read_args)
+            except Exception:
+                self.response.close()
+                raise
+        self.loc += len(out)
+        return out
+
+    def url(self) -> str:
+        return self.fs.url(self.path)
+
+    def __del__(self):
+        if not hasattr(self, "resolved_path"):
+            # Means that the constructor failed. Nothing to do.
+            return
+        return super().__del__()
+
+    def __reduce__(self):
+        return reopen, (self.fs, self.path, self.mode, self.blocksize, self.cache.name)
+
+
+def safe_revision(revision: str) -> str:
+    return revision if SPECIAL_REFS_REVISION_REGEX.match(revision) else safe_quote(revision)
+
+
+def safe_quote(s: str) -> str:
+    return quote(s, safe="")
+
+
+def _raise_file_not_found(path: str, err: Optional[Exception]) -> NoReturn:
+    msg = path
+    if isinstance(err, RepositoryNotFoundError):
+        msg = f"{path} (repository not found)"
+    elif isinstance(err, RevisionNotFoundError):
+        msg = f"{path} (revision not found)"
+    elif isinstance(err, HFValidationError):
+        msg = f"{path} (invalid repository id)"
+    raise FileNotFoundError(msg) from err
+
+
+def reopen(fs: HfFileSystem, path: str, mode: str, block_size: int, cache_type: str):
+    return fs.open(path, mode=mode, block_size=block_size, cache_type=cache_type)

.venv/lib/python3.13/site-packages/huggingface_hub/inference_api.py

@@ -0,0 +1,217 @@
+import io
+from typing import Any, Dict, List, Optional, Union
+
+from . import constants
+from .hf_api import HfApi
+from .utils import build_hf_headers, get_session, is_pillow_available, logging, validate_hf_hub_args
+from .utils._deprecation import _deprecate_method
+
+
+logger = logging.get_logger(__name__)
+
+
+ALL_TASKS = [
+    # NLP
+    "text-classification",
+    "token-classification",
+    "table-question-answering",
+    "question-answering",
+    "zero-shot-classification",
+    "translation",
+    "summarization",
+    "conversational",
+    "feature-extraction",
+    "text-generation",
+    "text2text-generation",
+    "fill-mask",
+    "sentence-similarity",
+    # Audio
+    "text-to-speech",
+    "automatic-speech-recognition",
+    "audio-to-audio",
+    "audio-classification",
+    "voice-activity-detection",
+    # Computer vision
+    "image-classification",
+    "object-detection",
+    "image-segmentation",
+    "text-to-image",
+    "image-to-image",
+    # Others
+    "tabular-classification",
+    "tabular-regression",
+]
+
+
+class InferenceApi:
+    """Client to configure requests and make calls to the HuggingFace Inference API.
+
+    Example:
+
+    ```python
+    >>> from huggingface_hub.inference_api import InferenceApi
+
+    >>> # Mask-fill example
+    >>> inference = InferenceApi("bert-base-uncased")
+    >>> inference(inputs="The goal of life is [MASK].")
+    [{'sequence': 'the goal of life is life.', 'score': 0.10933292657136917, 'token': 2166, 'token_str': 'life'}]
+
+    >>> # Question Answering example
+    >>> inference = InferenceApi("deepset/roberta-base-squad2")
+    >>> inputs = {
+    ...     "question": "What's my name?",
+    ...     "context": "My name is Clara and I live in Berkeley.",
+    ... }
+    >>> inference(inputs)
+    {'score': 0.9326569437980652, 'start': 11, 'end': 16, 'answer': 'Clara'}
+
+    >>> # Zero-shot example
+    >>> inference = InferenceApi("typeform/distilbert-base-uncased-mnli")
+    >>> inputs = "Hi, I recently bought a device from your company but it is not working as advertised and I would like to get reimbursed!"
+    >>> params = {"candidate_labels": ["refund", "legal", "faq"]}
+    >>> inference(inputs, params)
+    {'sequence': 'Hi, I recently bought a device from your company but it is not working as advertised and I would like to get reimbursed!', 'labels': ['refund', 'faq', 'legal'], 'scores': [0.9378499388694763, 0.04914155602455139, 0.013008488342165947]}
+
+    >>> # Overriding configured task
+    >>> inference = InferenceApi("bert-base-uncased", task="feature-extraction")
+
+    >>> # Text-to-image
+    >>> inference = InferenceApi("stabilityai/stable-diffusion-2-1")
+    >>> inference("cat")
+    <PIL.PngImagePlugin.PngImageFile image (...)>
+
+    >>> # Return as raw response to parse the output yourself
+    >>> inference = InferenceApi("mio/amadeus")
+    >>> response = inference("hello world", raw_response=True)
+    >>> response.headers
+    {"Content-Type": "audio/flac", ...}
+    >>> response.content # raw bytes from server
+    b'(...)'
+    ```
+    """
+
+    @validate_hf_hub_args
+    @_deprecate_method(
+        version="1.0",
+        message=(
+            "`InferenceApi` client is deprecated in favor of the more feature-complete `InferenceClient`. Check out"
+            " this guide to learn how to convert your script to use it:"
+            " https://huggingface.co/docs/huggingface_hub/guides/inference#legacy-inferenceapi-client."
+        ),
+    )
+    def __init__(
+        self,
+        repo_id: str,
+        task: Optional[str] = None,
+        token: Optional[str] = None,
+        gpu: bool = False,
+    ):
+        """Inits headers and API call information.
+
+        Args:
+            repo_id (``str``):
+                Id of repository (e.g. `user/bert-base-uncased`).
+            task (``str``, `optional`, defaults ``None``):
+                Whether to force a task instead of using task specified in the
+                repository.
+            token (`str`, `optional`):
+                The API token to use as HTTP bearer authorization. This is not
+                the authentication token. You can find the token in
+                https://huggingface.co/settings/token. Alternatively, you can
+                find both your organizations and personal API tokens using
+                `HfApi().whoami(token)`.
+            gpu (`bool`, `optional`, defaults `False`):
+                Whether to use GPU instead of CPU for inference(requires Startup
+                plan at least).
+        """
+        self.options = {"wait_for_model": True, "use_gpu": gpu}
+        self.headers = build_hf_headers(token=token)
+
+        # Configure task
+        model_info = HfApi(token=token).model_info(repo_id=repo_id)
+        if not model_info.pipeline_tag and not task:
+            raise ValueError(
+                "Task not specified in the repository. Please add it to the model card"
+                " using pipeline_tag"
+                " (https://huggingface.co/docs#how-is-a-models-type-of-inference-api-and-widget-determined)"
+            )
+
+        if task and task != model_info.pipeline_tag:
+            if task not in ALL_TASKS:
+                raise ValueError(f"Invalid task {task}. Make sure it's valid.")
+
+            logger.warning(
+                "You're using a different task than the one specified in the"
+                " repository. Be sure to know what you're doing :)"
+            )
+            self.task = task
+        else:
+            assert model_info.pipeline_tag is not None, "Pipeline tag cannot be None"
+            self.task = model_info.pipeline_tag
+
+        self.api_url = f"{constants.INFERENCE_ENDPOINT}/pipeline/{self.task}/{repo_id}"
+
+    def __repr__(self):
+        # Do not add headers to repr to avoid leaking token.
+        return f"InferenceAPI(api_url='{self.api_url}', task='{self.task}', options={self.options})"
+
+    def __call__(
+        self,
+        inputs: Optional[Union[str, Dict, List[str], List[List[str]]]] = None,
+        params: Optional[Dict] = None,
+        data: Optional[bytes] = None,
+        raw_response: bool = False,
+    ) -> Any:
+        """Make a call to the Inference API.
+
+        Args:
+            inputs (`str` or `Dict` or `List[str]` or `List[List[str]]`, *optional*):
+                Inputs for the prediction.
+            params (`Dict`, *optional*):
+                Additional parameters for the models. Will be sent as `parameters` in the
+                payload.
+            data (`bytes`, *optional*):
+                Bytes content of the request. In this case, leave `inputs` and `params` empty.
+            raw_response (`bool`, defaults to `False`):
+                If `True`, the raw `Response` object is returned. You can parse its content
+                as preferred. By default, the content is parsed into a more practical format
+                (json dictionary or PIL Image for example).
+        """
+        # Build payload
+        payload: Dict[str, Any] = {
+            "options": self.options,
+        }
+        if inputs:
+            payload["inputs"] = inputs
+        if params:
+            payload["parameters"] = params
+
+        # Make API call
+        response = get_session().post(self.api_url, headers=self.headers, json=payload, data=data)
+
+        # Let the user handle the response
+        if raw_response:
+            return response
+
+        # By default, parse the response for the user.
+        content_type = response.headers.get("Content-Type") or ""
+        if content_type.startswith("image"):
+            if not is_pillow_available():
+                raise ImportError(
+                    f"Task '{self.task}' returned as image but Pillow is not installed."
+                    " Please install it (`pip install Pillow`) or pass"
+                    " `raw_response=True` to get the raw `Response` object and parse"
+                    " the image by yourself."
+                )
+
+            from PIL import Image
+
+            return Image.open(io.BytesIO(response.content))
+        elif content_type == "application/json":
+            return response.json()
+        else:
+            raise NotImplementedError(
+                f"{content_type} output type is not implemented yet. You can pass"
+                " `raw_response=True` to get the raw `Response` object and parse the"
+                " output by yourself."
+            )

.venv/lib/python3.13/site-packages/huggingface_hub/repocard.py

@@ -0,0 +1,830 @@
+import os
+import re
+from pathlib import Path
+from typing import Any, Dict, Literal, Optional, Type, Union
+
+import requests
+import yaml
+
+from huggingface_hub.file_download import hf_hub_download
+from huggingface_hub.hf_api import upload_file
+from huggingface_hub.repocard_data import (
+    CardData,
+    DatasetCardData,
+    EvalResult,
+    ModelCardData,
+    SpaceCardData,
+    eval_results_to_model_index,
+    model_index_to_eval_results,
+)
+from huggingface_hub.utils import get_session, is_jinja_available, yaml_dump
+
+from . import constants
+from .errors import EntryNotFoundError
+from .utils import SoftTemporaryDirectory, logging, validate_hf_hub_args
+
+
+logger = logging.get_logger(__name__)
+
+
+TEMPLATE_MODELCARD_PATH = Path(__file__).parent / "templates" / "modelcard_template.md"
+TEMPLATE_DATASETCARD_PATH = Path(__file__).parent / "templates" / "datasetcard_template.md"
+
+# exact same regex as in the Hub server. Please keep in sync.
+# See https://github.com/huggingface/moon-landing/blob/main/server/lib/ViewMarkdown.ts#L18
+REGEX_YAML_BLOCK = re.compile(r"^(\s*---[\r\n]+)([\S\s]*?)([\r\n]+---(\r\n|\n|$))")
+
+
+class RepoCard:
+    card_data_class = CardData
+    default_template_path = TEMPLATE_MODELCARD_PATH
+    repo_type = "model"
+
+    def __init__(self, content: str, ignore_metadata_errors: bool = False):
+        """Initialize a RepoCard from string content. The content should be a
+        Markdown file with a YAML block at the beginning and a Markdown body.
+
+        Args:
+            content (`str`): The content of the Markdown file.
+
+        Example:
+            ```python
+            >>> from huggingface_hub.repocard import RepoCard
+            >>> text = '''
+            ... ---
+            ... language: en
+            ... license: mit
+            ... ---
+            ...
+            ... # My repo
+            ... '''
+            >>> card = RepoCard(text)
+            >>> card.data.to_dict()
+            {'language': 'en', 'license': 'mit'}
+            >>> card.text
+            '\\n# My repo\\n'
+
+            ```
+        <Tip>
+        Raises the following error:
+
+            - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+              when the content of the repo card metadata is not a dictionary.
+
+        </Tip>
+        """
+
+        # Set the content of the RepoCard, as well as underlying .data and .text attributes.
+        # See the `content` property setter for more details.
+        self.ignore_metadata_errors = ignore_metadata_errors
+        self.content = content
+
+    @property
+    def content(self):
+        """The content of the RepoCard, including the YAML block and the Markdown body."""
+        line_break = _detect_line_ending(self._content) or "\n"
+        return f"---{line_break}{self.data.to_yaml(line_break=line_break, original_order=self._original_order)}{line_break}---{line_break}{self.text}"
+
+    @content.setter
+    def content(self, content: str):
+        """Set the content of the RepoCard."""
+        self._content = content
+
+        match = REGEX_YAML_BLOCK.search(content)
+        if match:
+            # Metadata found in the YAML block
+            yaml_block = match.group(2)
+            self.text = content[match.end() :]
+            data_dict = yaml.safe_load(yaml_block)
+
+            if data_dict is None:
+                data_dict = {}
+
+            # The YAML block's data should be a dictionary
+            if not isinstance(data_dict, dict):
+                raise ValueError("repo card metadata block should be a dict")
+        else:
+            # Model card without metadata... create empty metadata
+            logger.warning("Repo card metadata block was not found. Setting CardData to empty.")
+            data_dict = {}
+            self.text = content
+
+        self.data = self.card_data_class(**data_dict, ignore_metadata_errors=self.ignore_metadata_errors)
+        self._original_order = list(data_dict.keys())
+
+    def __str__(self):
+        return self.content
+
+    def save(self, filepath: Union[Path, str]):
+        r"""Save a RepoCard to a file.
+
+        Args:
+            filepath (`Union[Path, str]`): Filepath to the markdown file to save.
+
+        Example:
+            ```python
+            >>> from huggingface_hub.repocard import RepoCard
+            >>> card = RepoCard("---\nlanguage: en\n---\n# This is a test repo card")
+            >>> card.save("/tmp/test.md")
+
+            ```
+        """
+        filepath = Path(filepath)
+        filepath.parent.mkdir(parents=True, exist_ok=True)
+        # Preserve newlines as in the existing file.
+        with open(filepath, mode="w", newline="", encoding="utf-8") as f:
+            f.write(str(self))
+
+    @classmethod
+    def load(
+        cls,
+        repo_id_or_path: Union[str, Path],
+        repo_type: Optional[str] = None,
+        token: Optional[str] = None,
+        ignore_metadata_errors: bool = False,
+    ):
+        """Initialize a RepoCard from a Hugging Face Hub repo's README.md or a local filepath.
+
+        Args:
+            repo_id_or_path (`Union[str, Path]`):
+                The repo ID associated with a Hugging Face Hub repo or a local filepath.
+            repo_type (`str`, *optional*):
+                The type of Hugging Face repo to push to. Defaults to None, which will use use "model". Other options
+                are "dataset" and "space". Not used when loading from a local filepath. If this is called from a child
+                class, the default value will be the child class's `repo_type`.
+            token (`str`, *optional*):
+                Authentication token, obtained with `huggingface_hub.HfApi.login` method. Will default to the stored token.
+            ignore_metadata_errors (`str`):
+                If True, errors while parsing the metadata section will be ignored. Some information might be lost during
+                the process. Use it at your own risk.
+
+        Returns:
+            [`huggingface_hub.repocard.RepoCard`]: The RepoCard (or subclass) initialized from the repo's
+                README.md file or filepath.
+
+        Example:
+            ```python
+            >>> from huggingface_hub.repocard import RepoCard
+            >>> card = RepoCard.load("nateraw/food")
+            >>> assert card.data.tags == ["generated_from_trainer", "image-classification", "pytorch"]
+
+            ```
+        """
+
+        if Path(repo_id_or_path).is_file():
+            card_path = Path(repo_id_or_path)
+        elif isinstance(repo_id_or_path, str):
+            card_path = Path(
+                hf_hub_download(
+                    repo_id_or_path,
+                    constants.REPOCARD_NAME,
+                    repo_type=repo_type or cls.repo_type,
+                    token=token,
+                )
+            )
+        else:
+            raise ValueError(f"Cannot load RepoCard: path not found on disk ({repo_id_or_path}).")
+
+        # Preserve newlines in the existing file.
+        with card_path.open(mode="r", newline="", encoding="utf-8") as f:
+            return cls(f.read(), ignore_metadata_errors=ignore_metadata_errors)
+
+    def validate(self, repo_type: Optional[str] = None):
+        """Validates card against Hugging Face Hub's card validation logic.
+        Using this function requires access to the internet, so it is only called
+        internally by [`huggingface_hub.repocard.RepoCard.push_to_hub`].
+
+        Args:
+            repo_type (`str`, *optional*, defaults to "model"):
+                The type of Hugging Face repo to push to. Options are "model", "dataset", and "space".
+                If this function is called from a child class, the default will be the child class's `repo_type`.
+
+        <Tip>
+        Raises the following errors:
+
+            - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+              if the card fails validation checks.
+            - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
+              if the request to the Hub API fails for any other reason.
+
+        </Tip>
+        """
+
+        # If repo type is provided, otherwise, use the repo type of the card.
+        repo_type = repo_type or self.repo_type
+
+        body = {
+            "repoType": repo_type,
+            "content": str(self),
+        }
+        headers = {"Accept": "text/plain"}
+
+        try:
+            r = get_session().post("https://huggingface.co/api/validate-yaml", body, headers=headers)
+            r.raise_for_status()
+        except requests.exceptions.HTTPError as exc:
+            if r.status_code == 400:
+                raise ValueError(r.text)
+            else:
+                raise exc
+
+    def push_to_hub(
+        self,
+        repo_id: str,
+        token: Optional[str] = None,
+        repo_type: Optional[str] = None,
+        commit_message: Optional[str] = None,
+        commit_description: Optional[str] = None,
+        revision: Optional[str] = None,
+        create_pr: Optional[bool] = None,
+        parent_commit: Optional[str] = None,
+    ):
+        """Push a RepoCard to a Hugging Face Hub repo.
+
+        Args:
+            repo_id (`str`):
+                The repo ID of the Hugging Face Hub repo to push to. Example: "nateraw/food".
+            token (`str`, *optional*):
+                Authentication token, obtained with `huggingface_hub.HfApi.login` method. Will default to
+                the stored token.
+            repo_type (`str`, *optional*, defaults to "model"):
+                The type of Hugging Face repo to push to. Options are "model", "dataset", and "space". If this
+                function is called by a child class, it will default to the child class's `repo_type`.
+            commit_message (`str`, *optional*):
+                The summary / title / first line of the generated commit.
+            commit_description (`str`, *optional*)
+                The description of the generated commit.
+            revision (`str`, *optional*):
+                The git revision to commit from. Defaults to the head of the `"main"` branch.
+            create_pr (`bool`, *optional*):
+                Whether or not to create a Pull Request with this commit. Defaults to `False`.
+            parent_commit (`str`, *optional*):
+                The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
+                If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
+                If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
+                Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
+                especially useful if the repo is updated / committed to concurrently.
+        Returns:
+            `str`: URL of the commit which updated the card metadata.
+        """
+
+        # If repo type is provided, otherwise, use the repo type of the card.
+        repo_type = repo_type or self.repo_type
+
+        # Validate card before pushing to hub
+        self.validate(repo_type=repo_type)
+
+        with SoftTemporaryDirectory() as tmpdir:
+            tmp_path = Path(tmpdir) / constants.REPOCARD_NAME
+            tmp_path.write_text(str(self))
+            url = upload_file(
+                path_or_fileobj=str(tmp_path),
+                path_in_repo=constants.REPOCARD_NAME,
+                repo_id=repo_id,
+                token=token,
+                repo_type=repo_type,
+                commit_message=commit_message,
+                commit_description=commit_description,
+                create_pr=create_pr,
+                revision=revision,
+                parent_commit=parent_commit,
+            )
+        return url
+
+    @classmethod
+    def from_template(
+        cls,
+        card_data: CardData,
+        template_path: Optional[str] = None,
+        template_str: Optional[str] = None,
+        **template_kwargs,
+    ):
+        """Initialize a RepoCard from a template. By default, it uses the default template.
+
+        Templates are Jinja2 templates that can be customized by passing keyword arguments.
+
+        Args:
+            card_data (`huggingface_hub.CardData`):
+                A huggingface_hub.CardData instance containing the metadata you want to include in the YAML
+                header of the repo card on the Hugging Face Hub.
+            template_path (`str`, *optional*):
+                A path to a markdown file with optional Jinja template variables that can be filled
+                in with `template_kwargs`. Defaults to the default template.
+
+        Returns:
+            [`huggingface_hub.repocard.RepoCard`]: A RepoCard instance with the specified card data and content from the
+            template.
+        """
+        if is_jinja_available():
+            import jinja2
+        else:
+            raise ImportError(
+                "Using RepoCard.from_template requires Jinja2 to be installed. Please"
+                " install it with `pip install Jinja2`."
+            )
+
+        kwargs = card_data.to_dict().copy()
+        kwargs.update(template_kwargs)  # Template_kwargs have priority
+
+        if template_path is not None:
+            template_str = Path(template_path).read_text()
+        if template_str is None:
+            template_str = Path(cls.default_template_path).read_text()
+        template = jinja2.Template(template_str)
+        content = template.render(card_data=card_data.to_yaml(), **kwargs)
+        return cls(content)
+
+
+class ModelCard(RepoCard):
+    card_data_class = ModelCardData
+    default_template_path = TEMPLATE_MODELCARD_PATH
+    repo_type = "model"
+
+    @classmethod
+    def from_template(  # type: ignore # violates Liskov property but easier to use
+        cls,
+        card_data: ModelCardData,
+        template_path: Optional[str] = None,
+        template_str: Optional[str] = None,
+        **template_kwargs,
+    ):
+        """Initialize a ModelCard from a template. By default, it uses the default template, which can be found here:
+        https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md
+
+        Templates are Jinja2 templates that can be customized by passing keyword arguments.
+
+        Args:
+            card_data (`huggingface_hub.ModelCardData`):
+                A huggingface_hub.ModelCardData instance containing the metadata you want to include in the YAML
+                header of the model card on the Hugging Face Hub.
+            template_path (`str`, *optional*):
+                A path to a markdown file with optional Jinja template variables that can be filled
+                in with `template_kwargs`. Defaults to the default template.
+
+        Returns:
+            [`huggingface_hub.ModelCard`]: A ModelCard instance with the specified card data and content from the
+            template.
+
+        Example:
+            ```python
+            >>> from huggingface_hub import ModelCard, ModelCardData, EvalResult
+
+            >>> # Using the Default Template
+            >>> card_data = ModelCardData(
+            ...     language='en',
+            ...     license='mit',
+            ...     library_name='timm',
+            ...     tags=['image-classification', 'resnet'],
+            ...     datasets=['beans'],
+            ...     metrics=['accuracy'],
+            ... )
+            >>> card = ModelCard.from_template(
+            ...     card_data,
+            ...     model_description='This model does x + y...'
+            ... )
+
+            >>> # Including Evaluation Results
+            >>> card_data = ModelCardData(
+            ...     language='en',
+            ...     tags=['image-classification', 'resnet'],
+            ...     eval_results=[
+            ...         EvalResult(
+            ...             task_type='image-classification',
+            ...             dataset_type='beans',
+            ...             dataset_name='Beans',
+            ...             metric_type='accuracy',
+            ...             metric_value=0.9,
+            ...         ),
+            ...     ],
+            ...     model_name='my-cool-model',
+            ... )
+            >>> card = ModelCard.from_template(card_data)
+
+            >>> # Using a Custom Template
+            >>> card_data = ModelCardData(
+            ...     language='en',
+            ...     tags=['image-classification', 'resnet']
+            ... )
+            >>> card = ModelCard.from_template(
+            ...     card_data=card_data,
+            ...     template_path='./src/huggingface_hub/templates/modelcard_template.md',
+            ...     custom_template_var='custom value',  # will be replaced in template if it exists
+            ... )
+
+            ```
+        """
+        return super().from_template(card_data, template_path, template_str, **template_kwargs)
+
+
+class DatasetCard(RepoCard):
+    card_data_class = DatasetCardData
+    default_template_path = TEMPLATE_DATASETCARD_PATH
+    repo_type = "dataset"
+
+    @classmethod
+    def from_template(  # type: ignore # violates Liskov property but easier to use
+        cls,
+        card_data: DatasetCardData,
+        template_path: Optional[str] = None,
+        template_str: Optional[str] = None,
+        **template_kwargs,
+    ):
+        """Initialize a DatasetCard from a template. By default, it uses the default template, which can be found here:
+        https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md
+
+        Templates are Jinja2 templates that can be customized by passing keyword arguments.
+
+        Args:
+            card_data (`huggingface_hub.DatasetCardData`):
+                A huggingface_hub.DatasetCardData instance containing the metadata you want to include in the YAML
+                header of the dataset card on the Hugging Face Hub.
+            template_path (`str`, *optional*):
+                A path to a markdown file with optional Jinja template variables that can be filled
+                in with `template_kwargs`. Defaults to the default template.
+
+        Returns:
+            [`huggingface_hub.DatasetCard`]: A DatasetCard instance with the specified card data and content from the
+            template.
+
+        Example:
+            ```python
+            >>> from huggingface_hub import DatasetCard, DatasetCardData
+
+            >>> # Using the Default Template
+            >>> card_data = DatasetCardData(
+            ...     language='en',
+            ...     license='mit',
+            ...     annotations_creators='crowdsourced',
+            ...     task_categories=['text-classification'],
+            ...     task_ids=['sentiment-classification', 'text-scoring'],
+            ...     multilinguality='monolingual',
+            ...     pretty_name='My Text Classification Dataset',
+            ... )
+            >>> card = DatasetCard.from_template(
+            ...     card_data,
+            ...     pretty_name=card_data.pretty_name,
+            ... )
+
+            >>> # Using a Custom Template
+            >>> card_data = DatasetCardData(
+            ...     language='en',
+            ...     license='mit',
+            ... )
+            >>> card = DatasetCard.from_template(
+            ...     card_data=card_data,
+            ...     template_path='./src/huggingface_hub/templates/datasetcard_template.md',
+            ...     custom_template_var='custom value',  # will be replaced in template if it exists
+            ... )
+
+            ```
+        """
+        return super().from_template(card_data, template_path, template_str, **template_kwargs)
+
+
+class SpaceCard(RepoCard):
+    card_data_class = SpaceCardData
+    default_template_path = TEMPLATE_MODELCARD_PATH
+    repo_type = "space"
+
+
+def _detect_line_ending(content: str) -> Literal["\r", "\n", "\r\n", None]:  # noqa: F722
+    """Detect the line ending of a string. Used by RepoCard to avoid making huge diff on newlines.
+
+    Uses same implementation as in Hub server, keep it in sync.
+
+    Returns:
+        str: The detected line ending of the string.
+    """
+    cr = content.count("\r")
+    lf = content.count("\n")
+    crlf = content.count("\r\n")
+    if cr + lf == 0:
+        return None
+    if crlf == cr and crlf == lf:
+        return "\r\n"
+    if cr > lf:
+        return "\r"
+    else:
+        return "\n"
+
+
+def metadata_load(local_path: Union[str, Path]) -> Optional[Dict]:
+    content = Path(local_path).read_text()
+    match = REGEX_YAML_BLOCK.search(content)
+    if match:
+        yaml_block = match.group(2)
+        data = yaml.safe_load(yaml_block)
+        if data is None or isinstance(data, dict):
+            return data
+        raise ValueError("repo card metadata block should be a dict")
+    else:
+        return None
+
+
+def metadata_save(local_path: Union[str, Path], data: Dict) -> None:
+    """
+    Save the metadata dict in the upper YAML part Trying to preserve newlines as
+    in the existing file. Docs about open() with newline="" parameter:
+    https://docs.python.org/3/library/functions.html?highlight=open#open Does
+    not work with "^M" linebreaks, which are replaced by \n
+    """
+    line_break = "\n"
+    content = ""
+    # try to detect existing newline character
+    if os.path.exists(local_path):
+        with open(local_path, "r", newline="", encoding="utf8") as readme:
+            content = readme.read()
+            if isinstance(readme.newlines, tuple):
+                line_break = readme.newlines[0]
+            elif isinstance(readme.newlines, str):
+                line_break = readme.newlines
+
+    # creates a new file if it not
+    with open(local_path, "w", newline="", encoding="utf8") as readme:
+        data_yaml = yaml_dump(data, sort_keys=False, line_break=line_break)
+        # sort_keys: keep dict order
+        match = REGEX_YAML_BLOCK.search(content)
+        if match:
+            output = content[: match.start()] + f"---{line_break}{data_yaml}---{line_break}" + content[match.end() :]
+        else:
+            output = f"---{line_break}{data_yaml}---{line_break}{content}"
+
+        readme.write(output)
+        readme.close()
+
+
+def metadata_eval_result(
+    *,
+    model_pretty_name: str,
+    task_pretty_name: str,
+    task_id: str,
+    metrics_pretty_name: str,
+    metrics_id: str,
+    metrics_value: Any,
+    dataset_pretty_name: str,
+    dataset_id: str,
+    metrics_config: Optional[str] = None,
+    metrics_verified: bool = False,
+    dataset_config: Optional[str] = None,
+    dataset_split: Optional[str] = None,
+    dataset_revision: Optional[str] = None,
+    metrics_verification_token: Optional[str] = None,
+) -> Dict:
+    """
+    Creates a metadata dict with the result from a model evaluated on a dataset.
+
+    Args:
+        model_pretty_name (`str`):
+            The name of the model in natural language.
+        task_pretty_name (`str`):
+            The name of a task in natural language.
+        task_id (`str`):
+            Example: automatic-speech-recognition. A task id.
+        metrics_pretty_name (`str`):
+            A name for the metric in natural language. Example: Test WER.
+        metrics_id (`str`):
+            Example: wer. A metric id from https://hf.co/metrics.
+        metrics_value (`Any`):
+            The value from the metric. Example: 20.0 or "20.0 ± 1.2".
+        dataset_pretty_name (`str`):
+            The name of the dataset in natural language.
+        dataset_id (`str`):
+            Example: common_voice. A dataset id from https://hf.co/datasets.
+        metrics_config (`str`, *optional*):
+            The name of the metric configuration used in `load_metric()`.
+            Example: bleurt-large-512 in `load_metric("bleurt", "bleurt-large-512")`.
+        metrics_verified (`bool`, *optional*, defaults to `False`):
+            Indicates whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not. Automatically computed by Hugging Face, do not set.
+        dataset_config (`str`, *optional*):
+            Example: fr. The name of the dataset configuration used in `load_dataset()`.
+        dataset_split (`str`, *optional*):
+            Example: test. The name of the dataset split used in `load_dataset()`.
+        dataset_revision (`str`, *optional*):
+            Example: 5503434ddd753f426f4b38109466949a1217c2bb. The name of the dataset dataset revision
+            used in `load_dataset()`.
+        metrics_verification_token (`bool`, *optional*):
+            A JSON Web Token that is used to verify whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not.
+
+    Returns:
+        `dict`: a metadata dict with the result from a model evaluated on a dataset.
+
+    Example:
+        ```python
+        >>> from huggingface_hub import metadata_eval_result
+        >>> results = metadata_eval_result(
+        ...         model_pretty_name="RoBERTa fine-tuned on ReactionGIF",
+        ...         task_pretty_name="Text Classification",
+        ...         task_id="text-classification",
+        ...         metrics_pretty_name="Accuracy",
+        ...         metrics_id="accuracy",
+        ...         metrics_value=0.2662102282047272,
+        ...         dataset_pretty_name="ReactionJPEG",
+        ...         dataset_id="julien-c/reactionjpeg",
+        ...         dataset_config="default",
+        ...         dataset_split="test",
+        ... )
+        >>> results == {
+        ...     'model-index': [
+        ...         {
+        ...             'name': 'RoBERTa fine-tuned on ReactionGIF',
+        ...             'results': [
+        ...                 {
+        ...                     'task': {
+        ...                         'type': 'text-classification',
+        ...                         'name': 'Text Classification'
+        ...                     },
+        ...                     'dataset': {
+        ...                         'name': 'ReactionJPEG',
+        ...                         'type': 'julien-c/reactionjpeg',
+        ...                         'config': 'default',
+        ...                         'split': 'test'
+        ...                     },
+        ...                     'metrics': [
+        ...                         {
+        ...                             'type': 'accuracy',
+        ...                             'value': 0.2662102282047272,
+        ...                             'name': 'Accuracy',
+        ...                             'verified': False
+        ...                         }
+        ...                     ]
+        ...                 }
+        ...             ]
+        ...         }
+        ...     ]
+        ... }
+        True
+
+        ```
+    """
+
+    return {
+        "model-index": eval_results_to_model_index(
+            model_name=model_pretty_name,
+            eval_results=[
+                EvalResult(
+                    task_name=task_pretty_name,
+                    task_type=task_id,
+                    metric_name=metrics_pretty_name,
+                    metric_type=metrics_id,
+                    metric_value=metrics_value,
+                    dataset_name=dataset_pretty_name,
+                    dataset_type=dataset_id,
+                    metric_config=metrics_config,
+                    verified=metrics_verified,
+                    verify_token=metrics_verification_token,
+                    dataset_config=dataset_config,
+                    dataset_split=dataset_split,
+                    dataset_revision=dataset_revision,
+                )
+            ],
+        )
+    }
+
+
+@validate_hf_hub_args
+def metadata_update(
+    repo_id: str,
+    metadata: Dict,
+    *,
+    repo_type: Optional[str] = None,
+    overwrite: bool = False,
+    token: Optional[str] = None,
+    commit_message: Optional[str] = None,
+    commit_description: Optional[str] = None,
+    revision: Optional[str] = None,
+    create_pr: bool = False,
+    parent_commit: Optional[str] = None,
+) -> str:
+    """
+    Updates the metadata in the README.md of a repository on the Hugging Face Hub.
+    If the README.md file doesn't exist yet, a new one is created with metadata and an
+    the default ModelCard or DatasetCard template. For `space` repo, an error is thrown
+    as a Space cannot exist without a `README.md` file.
+
+    Args:
+        repo_id (`str`):
+            The name of the repository.
+        metadata (`dict`):
+            A dictionary containing the metadata to be updated.
+        repo_type (`str`, *optional*):
+            Set to `"dataset"` or `"space"` if updating to a dataset or space,
+            `None` or `"model"` if updating to a model. Default is `None`.
+        overwrite (`bool`, *optional*, defaults to `False`):
+            If set to `True` an existing field can be overwritten, otherwise
+            attempting to overwrite an existing field will cause an error.
+        token (`str`, *optional*):
+            The Hugging Face authentication token.
+        commit_message (`str`, *optional*):
+            The summary / title / first line of the generated commit. Defaults to
+            `f"Update metadata with huggingface_hub"`
+        commit_description (`str` *optional*)
+            The description of the generated commit
+        revision (`str`, *optional*):
+            The git revision to commit from. Defaults to the head of the
+            `"main"` branch.
+        create_pr (`boolean`, *optional*):
+            Whether or not to create a Pull Request from `revision` with that commit.
+            Defaults to `False`.
+        parent_commit (`str`, *optional*):
+            The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
+            If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
+            If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
+            Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
+            especially useful if the repo is updated / committed to concurrently.
+    Returns:
+        `str`: URL of the commit which updated the card metadata.
+
+    Example:
+        ```python
+        >>> from huggingface_hub import metadata_update
+        >>> metadata = {'model-index': [{'name': 'RoBERTa fine-tuned on ReactionGIF',
+        ...             'results': [{'dataset': {'name': 'ReactionGIF',
+        ...                                      'type': 'julien-c/reactiongif'},
+        ...                           'metrics': [{'name': 'Recall',
+        ...                                        'type': 'recall',
+        ...                                        'value': 0.7762102282047272}],
+        ...                          'task': {'name': 'Text Classification',
+        ...                                   'type': 'text-classification'}}]}]}
+        >>> url = metadata_update("hf-internal-testing/reactiongif-roberta-card", metadata)
+
+        ```
+    """
+    commit_message = commit_message if commit_message is not None else "Update metadata with huggingface_hub"
+
+    # Card class given repo_type
+    card_class: Type[RepoCard]
+    if repo_type is None or repo_type == "model":
+        card_class = ModelCard
+    elif repo_type == "dataset":
+        card_class = DatasetCard
+    elif repo_type == "space":
+        card_class = RepoCard
+    else:
+        raise ValueError(f"Unknown repo_type: {repo_type}")
+
+    # Either load repo_card from the Hub or create an empty one.
+    # NOTE: Will not create the repo if it doesn't exist.
+    try:
+        card = card_class.load(repo_id, token=token, repo_type=repo_type)
+    except EntryNotFoundError:
+        if repo_type == "space":
+            raise ValueError("Cannot update metadata on a Space that doesn't contain a `README.md` file.")
+
+        # Initialize a ModelCard or DatasetCard from default template and no data.
+        card = card_class.from_template(CardData())
+
+    for key, value in metadata.items():
+        if key == "model-index":
+            # if the new metadata doesn't include a name, either use existing one or repo name
+            if "name" not in value[0]:
+                value[0]["name"] = getattr(card, "model_name", repo_id)
+            model_name, new_results = model_index_to_eval_results(value)
+            if card.data.eval_results is None:
+                card.data.eval_results = new_results
+                card.data.model_name = model_name
+            else:
+                existing_results = card.data.eval_results
+
+                # Iterate over new results
+                #   Iterate over existing results
+                #       If both results describe the same metric but value is different:
+                #           If overwrite=True: overwrite the metric value
+                #           Else: raise ValueError
+                #       Else: append new result to existing ones.
+                for new_result in new_results:
+                    result_found = False
+                    for existing_result in existing_results:
+                        if new_result.is_equal_except_value(existing_result):
+                            if new_result != existing_result and not overwrite:
+                                raise ValueError(
+                                    "You passed a new value for the existing metric"
+                                    f" 'name: {new_result.metric_name}, type: "
+                                    f"{new_result.metric_type}'. Set `overwrite=True`"
+                                    " to overwrite existing metrics."
+                                )
+                            result_found = True
+                            existing_result.metric_value = new_result.metric_value
+                            if existing_result.verified is True:
+                                existing_result.verify_token = new_result.verify_token
+                    if not result_found:
+                        card.data.eval_results.append(new_result)
+        else:
+            # Any metadata that is not a result metric
+            if card.data.get(key) is not None and not overwrite and card.data.get(key) != value:
+                raise ValueError(
+                    f"You passed a new value for the existing meta data field '{key}'."
+                    " Set `overwrite=True` to overwrite existing metadata."
+                )
+            else:
+                card.data[key] = value
+
+    return card.push_to_hub(
+        repo_id,
+        token=token,
+        repo_type=repo_type,
+        commit_message=commit_message,
+        commit_description=commit_description,
+        create_pr=create_pr,
+        revision=revision,
+        parent_commit=parent_commit,
+    )

.venv/lib/python3.13/site-packages/huggingface_hub/repository.py

@@ -0,0 +1,1477 @@
+import atexit
+import os
+import re
+import subprocess
+import threading
+import time
+from contextlib import contextmanager
+from pathlib import Path
+from typing import Callable, Dict, Iterator, List, Optional, Tuple, TypedDict, Union
+from urllib.parse import urlparse
+
+from huggingface_hub import constants
+from huggingface_hub.repocard import metadata_load, metadata_save
+
+from .hf_api import HfApi, repo_type_and_id_from_hf_id
+from .lfs import LFS_MULTIPART_UPLOAD_COMMAND
+from .utils import (
+    SoftTemporaryDirectory,
+    get_token,
+    logging,
+    run_subprocess,
+    tqdm,
+    validate_hf_hub_args,
+)
+from .utils._deprecation import _deprecate_method
+
+
+logger = logging.get_logger(__name__)
+
+
+class CommandInProgress:
+    """
+    Utility to follow commands launched asynchronously.
+    """
+
+    def __init__(
+        self,
+        title: str,
+        is_done_method: Callable,
+        status_method: Callable,
+        process: subprocess.Popen,
+        post_method: Optional[Callable] = None,
+    ):
+        self.title = title
+        self._is_done = is_done_method
+        self._status = status_method
+        self._process = process
+        self._stderr = ""
+        self._stdout = ""
+        self._post_method = post_method
+
+    @property
+    def is_done(self) -> bool:
+        """
+        Whether the process is done.
+        """
+        result = self._is_done()
+
+        if result and self._post_method is not None:
+            self._post_method()
+            self._post_method = None
+
+        return result
+
+    @property
+    def status(self) -> int:
+        """
+        The exit code/status of the current action. Will return `0` if the
+        command has completed successfully, and a number between 1 and 255 if
+        the process errored-out.
+
+        Will return -1 if the command is still ongoing.
+        """
+        return self._status()
+
+    @property
+    def failed(self) -> bool:
+        """
+        Whether the process errored-out.
+        """
+        return self.status > 0
+
+    @property
+    def stderr(self) -> str:
+        """
+        The current output message on the standard error.
+        """
+        if self._process.stderr is not None:
+            self._stderr += self._process.stderr.read()
+        return self._stderr
+
+    @property
+    def stdout(self) -> str:
+        """
+        The current output message on the standard output.
+        """
+        if self._process.stdout is not None:
+            self._stdout += self._process.stdout.read()
+        return self._stdout
+
+    def __repr__(self):
+        status = self.status
+
+        if status == -1:
+            status = "running"
+
+        return (
+            f"[{self.title} command, status code: {status},"
+            f" {'in progress.' if not self.is_done else 'finished.'} PID:"
+            f" {self._process.pid}]"
+        )
+
+
+def is_git_repo(folder: Union[str, Path]) -> bool:
+    """
+    Check if the folder is the root or part of a git repository
+
+    Args:
+        folder (`str`):
+            The folder in which to run the command.
+
+    Returns:
+        `bool`: `True` if the repository is part of a repository, `False`
+        otherwise.
+    """
+    folder_exists = os.path.exists(os.path.join(folder, ".git"))
+    git_branch = subprocess.run("git branch".split(), cwd=folder, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    return folder_exists and git_branch.returncode == 0
+
+
+def is_local_clone(folder: Union[str, Path], remote_url: str) -> bool:
+    """
+    Check if the folder is a local clone of the remote_url
+
+    Args:
+        folder (`str` or `Path`):
+            The folder in which to run the command.
+        remote_url (`str`):
+            The url of a git repository.
+
+    Returns:
+        `bool`: `True` if the repository is a local clone of the remote
+        repository specified, `False` otherwise.
+    """
+    if not is_git_repo(folder):
+        return False
+
+    remotes = run_subprocess("git remote -v", folder).stdout
+
+    # Remove token for the test with remotes.
+    remote_url = re.sub(r"https://.*@", "https://", remote_url)
+    remotes = [re.sub(r"https://.*@", "https://", remote) for remote in remotes.split()]
+    return remote_url in remotes
+
+
+def is_tracked_with_lfs(filename: Union[str, Path]) -> bool:
+    """
+    Check if the file passed is tracked with git-lfs.
+
+    Args:
+        filename (`str` or `Path`):
+            The filename to check.
+
+    Returns:
+        `bool`: `True` if the file passed is tracked with git-lfs, `False`
+        otherwise.
+    """
+    folder = Path(filename).parent
+    filename = Path(filename).name
+
+    try:
+        p = run_subprocess("git check-attr -a".split() + [filename], folder)
+        attributes = p.stdout.strip()
+    except subprocess.CalledProcessError as exc:
+        if not is_git_repo(folder):
+            return False
+        else:
+            raise OSError(exc.stderr)
+
+    if len(attributes) == 0:
+        return False
+
+    found_lfs_tag = {"diff": False, "merge": False, "filter": False}
+
+    for attribute in attributes.split("\n"):
+        for tag in found_lfs_tag.keys():
+            if tag in attribute and "lfs" in attribute:
+                found_lfs_tag[tag] = True
+
+    return all(found_lfs_tag.values())
+
+
+def is_git_ignored(filename: Union[str, Path]) -> bool:
+    """
+    Check if file is git-ignored. Supports nested .gitignore files.
+
+    Args:
+        filename (`str` or `Path`):
+            The filename to check.
+
+    Returns:
+        `bool`: `True` if the file passed is ignored by `git`, `False`
+        otherwise.
+    """
+    folder = Path(filename).parent
+    filename = Path(filename).name
+
+    try:
+        p = run_subprocess("git check-ignore".split() + [filename], folder, check=False)
+        # Will return exit code 1 if not gitignored
+        is_ignored = not bool(p.returncode)
+    except subprocess.CalledProcessError as exc:
+        raise OSError(exc.stderr)
+
+    return is_ignored
+
+
+def is_binary_file(filename: Union[str, Path]) -> bool:
+    """
+    Check if file is a binary file.
+
+    Args:
+        filename (`str` or `Path`):
+            The filename to check.
+
+    Returns:
+        `bool`: `True` if the file passed is a binary file, `False` otherwise.
+    """
+    try:
+        with open(filename, "rb") as f:
+            content = f.read(10 * (1024**2))  # Read a maximum of 10MB
+
+        # Code sample taken from the following stack overflow thread
+        # https://stackoverflow.com/questions/898669/how-can-i-detect-if-a-file-is-binary-non-text-in-python/7392391#7392391
+        text_chars = bytearray({7, 8, 9, 10, 12, 13, 27} | set(range(0x20, 0x100)) - {0x7F})
+        return bool(content.translate(None, text_chars))
+    except UnicodeDecodeError:
+        return True
+
+
+def files_to_be_staged(pattern: str = ".", folder: Union[str, Path, None] = None) -> List[str]:
+    """
+    Returns a list of filenames that are to be staged.
+
+    Args:
+        pattern (`str` or `Path`):
+            The pattern of filenames to check. Put `.` to get all files.
+        folder (`str` or `Path`):
+            The folder in which to run the command.
+
+    Returns:
+        `List[str]`: List of files that are to be staged.
+    """
+    try:
+        p = run_subprocess("git ls-files --exclude-standard -mo".split() + [pattern], folder)
+        if len(p.stdout.strip()):
+            files = p.stdout.strip().split("\n")
+        else:
+            files = []
+    except subprocess.CalledProcessError as exc:
+        raise EnvironmentError(exc.stderr)
+
+    return files
+
+
+def is_tracked_upstream(folder: Union[str, Path]) -> bool:
+    """
+    Check if the current checked-out branch is tracked upstream.
+
+    Args:
+        folder (`str` or `Path`):
+            The folder in which to run the command.
+
+    Returns:
+        `bool`: `True` if the current checked-out branch is tracked upstream,
+        `False` otherwise.
+    """
+    try:
+        run_subprocess("git rev-parse --symbolic-full-name --abbrev-ref @{u}", folder)
+        return True
+    except subprocess.CalledProcessError as exc:
+        if "HEAD" in exc.stderr:
+            raise OSError("No branch checked out")
+
+        return False
+
+
+def commits_to_push(folder: Union[str, Path], upstream: Optional[str] = None) -> int:
+    """
+        Check the number of commits that would be pushed upstream
+
+        Args:
+            folder (`str` or `Path`):
+                The folder in which to run the command.
+            upstream (`str`, *optional*):
+    The name of the upstream repository with which the comparison should be
+    made.
+
+        Returns:
+            `int`: Number of commits that would be pushed upstream were a `git
+            push` to proceed.
+    """
+    try:
+        result = run_subprocess(f"git cherry -v {upstream or ''}", folder)
+        return len(result.stdout.split("\n")) - 1
+    except subprocess.CalledProcessError as exc:
+        raise EnvironmentError(exc.stderr)
+
+
+class PbarT(TypedDict):
+    # Used to store an opened progress bar in `_lfs_log_progress`
+    bar: tqdm
+    past_bytes: int
+
+
+@contextmanager
+def _lfs_log_progress():
+    """
+    This is a context manager that will log the Git LFS progress of cleaning,
+    smudging, pulling and pushing.
+    """
+
+    if logger.getEffectiveLevel() >= logging.ERROR:
+        try:
+            yield
+        except Exception:
+            pass
+        return
+
+    def output_progress(stopping_event: threading.Event):
+        """
+        To be launched as a separate thread with an event meaning it should stop
+        the tail.
+        """
+        # Key is tuple(state, filename), value is a dict(tqdm bar and a previous value)
+        pbars: Dict[Tuple[str, str], PbarT] = {}
+
+        def close_pbars():
+            for pbar in pbars.values():
+                pbar["bar"].update(pbar["bar"].total - pbar["past_bytes"])
+                pbar["bar"].refresh()
+                pbar["bar"].close()
+
+        def tail_file(filename) -> Iterator[str]:
+            """
+            Creates a generator to be iterated through, which will return each
+            line one by one. Will stop tailing the file if the stopping_event is
+            set.
+            """
+            with open(filename, "r") as file:
+                current_line = ""
+                while True:
+                    if stopping_event.is_set():
+                        close_pbars()
+                        break
+
+                    line_bit = file.readline()
+                    if line_bit is not None and not len(line_bit.strip()) == 0:
+                        current_line += line_bit
+                        if current_line.endswith("\n"):
+                            yield current_line
+                            current_line = ""
+                    else:
+                        time.sleep(1)
+
+        # If the file isn't created yet, wait for a few seconds before trying again.
+        # Can be interrupted with the stopping_event.
+        while not os.path.exists(os.environ["GIT_LFS_PROGRESS"]):
+            if stopping_event.is_set():
+                close_pbars()
+                return
+
+            time.sleep(2)
+
+        for line in tail_file(os.environ["GIT_LFS_PROGRESS"]):
+            try:
+                state, file_progress, byte_progress, filename = line.split()
+            except ValueError as error:
+                # Try/except to ease debugging. See https://github.com/huggingface/huggingface_hub/issues/1373.
+                raise ValueError(f"Cannot unpack LFS progress line:\n{line}") from error
+            description = f"{state.capitalize()} file {filename}"
+
+            current_bytes, total_bytes = byte_progress.split("/")
+            current_bytes_int = int(current_bytes)
+            total_bytes_int = int(total_bytes)
+
+            pbar = pbars.get((state, filename))
+            if pbar is None:
+                # Initialize progress bar
+                pbars[(state, filename)] = {
+                    "bar": tqdm(
+                        desc=description,
+                        initial=current_bytes_int,
+                        total=total_bytes_int,
+                        unit="B",
+                        unit_scale=True,
+                        unit_divisor=1024,
+                        name="huggingface_hub.lfs_upload",
+                    ),
+                    "past_bytes": int(current_bytes),
+                }
+            else:
+                # Update progress bar
+                pbar["bar"].update(current_bytes_int - pbar["past_bytes"])
+                pbar["past_bytes"] = current_bytes_int
+
+    current_lfs_progress_value = os.environ.get("GIT_LFS_PROGRESS", "")
+
+    with SoftTemporaryDirectory() as tmpdir:
+        os.environ["GIT_LFS_PROGRESS"] = os.path.join(tmpdir, "lfs_progress")
+        logger.debug(f"Following progress in {os.environ['GIT_LFS_PROGRESS']}")
+
+        exit_event = threading.Event()
+        x = threading.Thread(target=output_progress, args=(exit_event,), daemon=True)
+        x.start()
+
+        try:
+            yield
+        finally:
+            exit_event.set()
+            x.join()
+
+            os.environ["GIT_LFS_PROGRESS"] = current_lfs_progress_value
+
+
+class Repository:
+    """
+    Helper class to wrap the git and git-lfs commands.
+
+    The aim is to facilitate interacting with huggingface.co hosted model or
+    dataset repos, though not a lot here (if any) is actually specific to
+    huggingface.co.
+
+    <Tip warning={true}>
+
+    [`Repository`] is deprecated in favor of the http-based alternatives implemented in
+    [`HfApi`]. Given its large adoption in legacy code, the complete removal of
+    [`Repository`] will only happen in release `v1.0`. For more details, please read
+    https://huggingface.co/docs/huggingface_hub/concepts/git_vs_http.
+
+    </Tip>
+    """
+
+    command_queue: List[CommandInProgress]
+
+    @validate_hf_hub_args
+    @_deprecate_method(
+        version="1.0",
+        message=(
+            "Please prefer the http-based alternatives instead. Given its large adoption in legacy code, the complete"
+            " removal is only planned on next major release.\nFor more details, please read"
+            " https://huggingface.co/docs/huggingface_hub/concepts/git_vs_http."
+        ),
+    )
+    def __init__(
+        self,
+        local_dir: Union[str, Path],
+        clone_from: Optional[str] = None,
+        repo_type: Optional[str] = None,
+        token: Union[bool, str] = True,
+        git_user: Optional[str] = None,
+        git_email: Optional[str] = None,
+        revision: Optional[str] = None,
+        skip_lfs_files: bool = False,
+        client: Optional[HfApi] = None,
+    ):
+        """
+        Instantiate a local clone of a git repo.
+
+        If `clone_from` is set, the repo will be cloned from an existing remote repository.
+        If the remote repo does not exist, a `EnvironmentError` exception will be thrown.
+        Please create the remote repo first using [`create_repo`].
+
+        `Repository` uses the local git credentials by default. If explicitly set, the `token`
+        or the `git_user`/`git_email` pair will be used instead.
+
+        Args:
+            local_dir (`str` or `Path`):
+                path (e.g. `'my_trained_model/'`) to the local directory, where
+                the `Repository` will be initialized.
+            clone_from (`str`, *optional*):
+                Either a repository url or `repo_id`.
+                Example:
+                - `"https://huggingface.co/philschmid/playground-tests"`
+                - `"philschmid/playground-tests"`
+            repo_type (`str`, *optional*):
+                To set when cloning a repo from a repo_id. Default is model.
+            token (`bool` or `str`, *optional*):
+                A valid authentication token (see https://huggingface.co/settings/token).
+                If `None` or `True` and machine is logged in (through `huggingface-cli login`
+                or [`~huggingface_hub.login`]), token will be retrieved from the cache.
+                If `False`, token is not sent in the request header.
+            git_user (`str`, *optional*):
+                will override the `git config user.name` for committing and
+                pushing files to the hub.
+            git_email (`str`, *optional*):
+                will override the `git config user.email` for committing and
+                pushing files to the hub.
+            revision (`str`, *optional*):
+                Revision to checkout after initializing the repository. If the
+                revision doesn't exist, a branch will be created with that
+                revision name from the default branch's current HEAD.
+            skip_lfs_files (`bool`, *optional*, defaults to `False`):
+                whether to skip git-LFS files or not.
+            client (`HfApi`, *optional*):
+                Instance of [`HfApi`] to use when calling the HF Hub API. A new
+                instance will be created if this is left to `None`.
+
+        Raises:
+            [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+                If the remote repository set in `clone_from` does not exist.
+        """
+        if isinstance(local_dir, Path):
+            local_dir = str(local_dir)
+        os.makedirs(local_dir, exist_ok=True)
+        self.local_dir = os.path.join(os.getcwd(), local_dir)
+        self._repo_type = repo_type
+        self.command_queue = []
+        self.skip_lfs_files = skip_lfs_files
+        self.client = client if client is not None else HfApi()
+
+        self.check_git_versions()
+
+        if isinstance(token, str):
+            self.huggingface_token: Optional[str] = token
+        elif token is False:
+            self.huggingface_token = None
+        else:
+            # if `True` -> explicit use of the cached token
+            # if `None` -> implicit use of the cached token
+            self.huggingface_token = get_token()
+
+        if clone_from is not None:
+            self.clone_from(repo_url=clone_from)
+        else:
+            if is_git_repo(self.local_dir):
+                logger.debug("[Repository] is a valid git repo")
+            else:
+                raise ValueError("If not specifying `clone_from`, you need to pass Repository a valid git clone.")
+
+        if self.huggingface_token is not None and (git_email is None or git_user is None):
+            user = self.client.whoami(self.huggingface_token)
+
+            if git_email is None:
+                git_email = user.get("email")
+
+            if git_user is None:
+                git_user = user.get("fullname")
+
+        if git_user is not None or git_email is not None:
+            self.git_config_username_and_email(git_user, git_email)
+
+        self.lfs_enable_largefiles()
+        self.git_credential_helper_store()
+
+        if revision is not None:
+            self.git_checkout(revision, create_branch_ok=True)
+
+        # This ensures that all commands exit before exiting the Python runtime.
+        # This will ensure all pushes register on the hub, even if other errors happen in subsequent operations.
+        atexit.register(self.wait_for_commands)
+
+    @property
+    def current_branch(self) -> str:
+        """
+        Returns the current checked out branch.
+
+        Returns:
+            `str`: Current checked out branch.
+        """
+        try:
+            result = run_subprocess("git rev-parse --abbrev-ref HEAD", self.local_dir).stdout.strip()
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+        return result
+
+    def check_git_versions(self):
+        """
+        Checks that `git` and `git-lfs` can be run.
+
+        Raises:
+            [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+                If `git` or `git-lfs` are not installed.
+        """
+        try:
+            git_version = run_subprocess("git --version", self.local_dir).stdout.strip()
+        except FileNotFoundError:
+            raise EnvironmentError("Looks like you do not have git installed, please install.")
+
+        try:
+            lfs_version = run_subprocess("git-lfs --version", self.local_dir).stdout.strip()
+        except FileNotFoundError:
+            raise EnvironmentError(
+                "Looks like you do not have git-lfs installed, please install."
+                " You can install from https://git-lfs.github.com/."
+                " Then run `git lfs install` (you only have to do this once)."
+            )
+        logger.info(git_version + "\n" + lfs_version)
+
+    @validate_hf_hub_args
+    def clone_from(self, repo_url: str, token: Union[bool, str, None] = None):
+        """
+        Clone from a remote. If the folder already exists, will try to clone the
+        repository within it.
+
+        If this folder is a git repository with linked history, will try to
+        update the repository.
+
+        Args:
+            repo_url (`str`):
+                The URL from which to clone the repository
+            token (`Union[str, bool]`, *optional*):
+                Whether to use the authentication token. It can be:
+                 - a string which is the token itself
+                 - `False`, which would not use the authentication token
+                 - `True`, which would fetch the authentication token from the
+                   local folder and use it (you should be logged in for this to
+                   work).
+                - `None`, which would retrieve the value of
+                  `self.huggingface_token`.
+
+        <Tip>
+
+        Raises the following error:
+
+            - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
+              if an organization token (starts with "api_org") is passed. Use must use
+              your own personal access token (see https://hf.co/settings/tokens).
+
+            - [`EnvironmentError`](https://docs.python.org/3/library/exceptions.html#EnvironmentError)
+              if you are trying to clone the repository in a non-empty folder, or if the
+              `git` operations raise errors.
+
+        </Tip>
+        """
+        token = (
+            token  # str -> use it
+            if isinstance(token, str)
+            else (
+                None  # `False` -> explicit no token
+                if token is False
+                else self.huggingface_token  # `None` or `True` -> use default
+            )
+        )
+        if token is not None and token.startswith("api_org"):
+            raise ValueError(
+                "You must use your personal access token, not an Organization token"
+                " (see https://hf.co/settings/tokens)."
+            )
+
+        hub_url = self.client.endpoint
+        if hub_url in repo_url or ("http" not in repo_url and len(repo_url.split("/")) <= 2):
+            repo_type, namespace, repo_name = repo_type_and_id_from_hf_id(repo_url, hub_url=hub_url)
+            repo_id = f"{namespace}/{repo_name}" if namespace is not None else repo_name
+
+            if repo_type is not None:
+                self._repo_type = repo_type
+
+            repo_url = hub_url + "/"
+
+            if self._repo_type in constants.REPO_TYPES_URL_PREFIXES:
+                repo_url += constants.REPO_TYPES_URL_PREFIXES[self._repo_type]
+
+            if token is not None:
+                # Add token in git url when provided
+                scheme = urlparse(repo_url).scheme
+                repo_url = repo_url.replace(f"{scheme}://", f"{scheme}://user:{token}@")
+
+            repo_url += repo_id
+
+        # For error messages, it's cleaner to show the repo url without the token.
+        clean_repo_url = re.sub(r"(https?)://.*@", r"\1://", repo_url)
+        try:
+            run_subprocess("git lfs install", self.local_dir)
+
+            # checks if repository is initialized in a empty repository or in one with files
+            if len(os.listdir(self.local_dir)) == 0:
+                logger.warning(f"Cloning {clean_repo_url} into local empty directory.")
+
+                with _lfs_log_progress():
+                    env = os.environ.copy()
+
+                    if self.skip_lfs_files:
+                        env.update({"GIT_LFS_SKIP_SMUDGE": "1"})
+
+                    run_subprocess(
+                        # 'git lfs clone' is deprecated (will display a warning in the terminal)
+                        # but we still use it as it provides a nicer UX when downloading large
+                        # files (shows progress).
+                        f"{'git clone' if self.skip_lfs_files else 'git lfs clone'} {repo_url} .",
+                        self.local_dir,
+                        env=env,
+                    )
+            else:
+                # Check if the folder is the root of a git repository
+                if not is_git_repo(self.local_dir):
+                    raise EnvironmentError(
+                        "Tried to clone a repository in a non-empty folder that isn't"
+                        f" a git repository ('{self.local_dir}'). If you really want to"
+                        f" do this, do it manually:\n cd {self.local_dir} && git init"
+                        " && git remote add origin && git pull origin main\n or clone"
+                        " repo to a new folder and move your existing files there"
+                        " afterwards."
+                    )
+
+                if is_local_clone(self.local_dir, repo_url):
+                    logger.warning(
+                        f"{self.local_dir} is already a clone of {clean_repo_url}."
+                        " Make sure you pull the latest changes with"
+                        " `repo.git_pull()`."
+                    )
+                else:
+                    output = run_subprocess("git remote get-url origin", self.local_dir, check=False)
+
+                    error_msg = (
+                        f"Tried to clone {clean_repo_url} in an unrelated git"
+                        " repository.\nIf you believe this is an error, please add"
+                        f" a remote with the following URL: {clean_repo_url}."
+                    )
+                    if output.returncode == 0:
+                        clean_local_remote_url = re.sub(r"https://.*@", "https://", output.stdout)
+                        error_msg += f"\nLocal path has its origin defined as: {clean_local_remote_url}"
+                    raise EnvironmentError(error_msg)
+
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+    def git_config_username_and_email(self, git_user: Optional[str] = None, git_email: Optional[str] = None):
+        """
+        Sets git username and email (only in the current repo).
+
+        Args:
+            git_user (`str`, *optional*):
+                The username to register through `git`.
+            git_email (`str`, *optional*):
+                The email to register through `git`.
+        """
+        try:
+            if git_user is not None:
+                run_subprocess("git config user.name".split() + [git_user], self.local_dir)
+
+            if git_email is not None:
+                run_subprocess(f"git config user.email {git_email}".split(), self.local_dir)
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+    def git_credential_helper_store(self):
+        """
+        Sets the git credential helper to `store`
+        """
+        try:
+            run_subprocess("git config credential.helper store", self.local_dir)
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+    def git_head_hash(self) -> str:
+        """
+        Get commit sha on top of HEAD.
+
+        Returns:
+            `str`: The current checked out commit SHA.
+        """
+        try:
+            p = run_subprocess("git rev-parse HEAD", self.local_dir)
+            return p.stdout.strip()
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+    def git_remote_url(self) -> str:
+        """
+        Get URL to origin remote.
+
+        Returns:
+            `str`: The URL of the `origin` remote.
+        """
+        try:
+            p = run_subprocess("git config --get remote.origin.url", self.local_dir)
+            url = p.stdout.strip()
+            # Strip basic auth info.
+            return re.sub(r"https://.*@", "https://", url)
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+    def git_head_commit_url(self) -> str:
+        """
+        Get URL to last commit on HEAD. We assume it's been pushed, and the url
+        scheme is the same one as for GitHub or HuggingFace.
+
+        Returns:
+            `str`: The URL to the current checked-out commit.
+        """
+        sha = self.git_head_hash()
+        url = self.git_remote_url()
+        if url.endswith("/"):
+            url = url[:-1]
+        return f"{url}/commit/{sha}"
+
+    def list_deleted_files(self) -> List[str]:
+        """
+        Returns a list of the files that are deleted in the working directory or
+        index.
+
+        Returns:
+            `List[str]`: A list of files that have been deleted in the working
+            directory or index.
+        """
+        try:
+            git_status = run_subprocess("git status -s", self.local_dir).stdout.strip()
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+        if len(git_status) == 0:
+            return []
+
+        # Receives a status like the following
+        #  D .gitignore
+        #  D new_file.json
+        # AD new_file1.json
+        # ?? new_file2.json
+        # ?? new_file4.json
+
+        # Strip each line of whitespaces
+        modified_files_statuses = [status.strip() for status in git_status.split("\n")]
+
+        # Only keep files that are deleted using the D prefix
+        deleted_files_statuses = [status for status in modified_files_statuses if "D" in status.split()[0]]
+
+        # Remove the D prefix and strip to keep only the relevant filename
+        deleted_files = [status.split()[-1].strip() for status in deleted_files_statuses]
+
+        return deleted_files
+
+    def lfs_track(self, patterns: Union[str, List[str]], filename: bool = False):
+        """
+        Tell git-lfs to track files according to a pattern.
+
+        Setting the `filename` argument to `True` will treat the arguments as
+        literal filenames, not as patterns. Any special glob characters in the
+        filename will be escaped when writing to the `.gitattributes` file.
+
+        Args:
+            patterns (`Union[str, List[str]]`):
+                The pattern, or list of patterns, to track with git-lfs.
+            filename (`bool`, *optional*, defaults to `False`):
+                Whether to use the patterns as literal filenames.
+        """
+        if isinstance(patterns, str):
+            patterns = [patterns]
+        try:
+            for pattern in patterns:
+                run_subprocess(
+                    f"git lfs track {'--filename' if filename else ''} {pattern}",
+                    self.local_dir,
+                )
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+    def lfs_untrack(self, patterns: Union[str, List[str]]):
+        """
+        Tell git-lfs to untrack those files.
+
+        Args:
+            patterns (`Union[str, List[str]]`):
+                The pattern, or list of patterns, to untrack with git-lfs.
+        """
+        if isinstance(patterns, str):
+            patterns = [patterns]
+        try:
+            for pattern in patterns:
+                run_subprocess("git lfs untrack".split() + [pattern], self.local_dir)
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+    def lfs_enable_largefiles(self):
+        """
+        HF-specific. This enables upload support of files >5GB.
+        """
+        try:
+            lfs_config = "git config lfs.customtransfer.multipart"
+            run_subprocess(f"{lfs_config}.path huggingface-cli", self.local_dir)
+            run_subprocess(
+                f"{lfs_config}.args {LFS_MULTIPART_UPLOAD_COMMAND}",
+                self.local_dir,
+            )
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+    def auto_track_binary_files(self, pattern: str = ".") -> List[str]:
+        """
+        Automatically track binary files with git-lfs.
+
+        Args:
+            pattern (`str`, *optional*, defaults to "."):
+                The pattern with which to track files that are binary.
+
+        Returns:
+            `List[str]`: List of filenames that are now tracked due to being
+            binary files
+        """
+        files_to_be_tracked_with_lfs = []
+
+        deleted_files = self.list_deleted_files()
+
+        for filename in files_to_be_staged(pattern, folder=self.local_dir):
+            if filename in deleted_files:
+                continue
+
+            path_to_file = os.path.join(os.getcwd(), self.local_dir, filename)
+
+            if not (is_tracked_with_lfs(path_to_file) or is_git_ignored(path_to_file)):
+                size_in_mb = os.path.getsize(path_to_file) / (1024 * 1024)
+
+                if size_in_mb >= 10:
+                    logger.warning(
+                        "Parsing a large file to check if binary or not. Tracking large"
+                        " files using `repository.auto_track_large_files` is"
+                        " recommended so as to not load the full file in memory."
+                    )
+
+                is_binary = is_binary_file(path_to_file)
+
+                if is_binary:
+                    self.lfs_track(filename)
+                    files_to_be_tracked_with_lfs.append(filename)
+
+        # Cleanup the .gitattributes if files were deleted
+        self.lfs_untrack(deleted_files)
+
+        return files_to_be_tracked_with_lfs
+
+    def auto_track_large_files(self, pattern: str = ".") -> List[str]:
+        """
+        Automatically track large files (files that weigh more than 10MBs) with
+        git-lfs.
+
+        Args:
+            pattern (`str`, *optional*, defaults to "."):
+                The pattern with which to track files that are above 10MBs.
+
+        Returns:
+            `List[str]`: List of filenames that are now tracked due to their
+            size.
+        """
+        files_to_be_tracked_with_lfs = []
+
+        deleted_files = self.list_deleted_files()
+
+        for filename in files_to_be_staged(pattern, folder=self.local_dir):
+            if filename in deleted_files:
+                continue
+
+            path_to_file = os.path.join(os.getcwd(), self.local_dir, filename)
+            size_in_mb = os.path.getsize(path_to_file) / (1024 * 1024)
+
+            if size_in_mb >= 10 and not is_tracked_with_lfs(path_to_file) and not is_git_ignored(path_to_file):
+                self.lfs_track(filename)
+                files_to_be_tracked_with_lfs.append(filename)
+
+        # Cleanup the .gitattributes if files were deleted
+        self.lfs_untrack(deleted_files)
+
+        return files_to_be_tracked_with_lfs
+
+    def lfs_prune(self, recent=False):
+        """
+        git lfs prune
+
+        Args:
+            recent (`bool`, *optional*, defaults to `False`):
+                Whether to prune files even if they were referenced by recent
+                commits. See the following
+                [link](https://github.com/git-lfs/git-lfs/blob/f3d43f0428a84fc4f1e5405b76b5a73ec2437e65/docs/man/git-lfs-prune.1.ronn#recent-files)
+                for more information.
+        """
+        try:
+            with _lfs_log_progress():
+                result = run_subprocess(f"git lfs prune {'--recent' if recent else ''}", self.local_dir)
+                logger.info(result.stdout)
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+    def git_pull(self, rebase: bool = False, lfs: bool = False):
+        """
+        git pull
+
+        Args:
+            rebase (`bool`, *optional*, defaults to `False`):
+                Whether to rebase the current branch on top of the upstream
+                branch after fetching.
+            lfs (`bool`, *optional*, defaults to `False`):
+                Whether to fetch the LFS files too. This option only changes the
+                behavior when a repository was cloned without fetching the LFS
+                files; calling `repo.git_pull(lfs=True)` will then fetch the LFS
+                file from the remote repository.
+        """
+        command = "git pull" if not lfs else "git lfs pull"
+        if rebase:
+            command += " --rebase"
+        try:
+            with _lfs_log_progress():
+                result = run_subprocess(command, self.local_dir)
+                logger.info(result.stdout)
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+    def git_add(self, pattern: str = ".", auto_lfs_track: bool = False):
+        """
+        git add
+
+        Setting the `auto_lfs_track` parameter to `True` will automatically
+        track files that are larger than 10MB with `git-lfs`.
+
+        Args:
+            pattern (`str`, *optional*, defaults to "."):
+                The pattern with which to add files to staging.
+            auto_lfs_track (`bool`, *optional*, defaults to `False`):
+                Whether to automatically track large and binary files with
+                git-lfs. Any file over 10MB in size, or in binary format, will
+                be automatically tracked.
+        """
+        if auto_lfs_track:
+            # Track files according to their size (>=10MB)
+            tracked_files = self.auto_track_large_files(pattern)
+
+            # Read the remaining files and track them if they're binary
+            tracked_files.extend(self.auto_track_binary_files(pattern))
+
+            if tracked_files:
+                logger.warning(
+                    f"Adding files tracked by Git LFS: {tracked_files}. This may take a"
+                    " bit of time if the files are large."
+                )
+
+        try:
+            result = run_subprocess("git add -v".split() + [pattern], self.local_dir)
+            logger.info(f"Adding to index:\n{result.stdout}\n")
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+    def git_commit(self, commit_message: str = "commit files to HF hub"):
+        """
+        git commit
+
+        Args:
+            commit_message (`str`, *optional*, defaults to "commit files to HF hub"):
+                The message attributed to the commit.
+        """
+        try:
+            result = run_subprocess("git commit -v -m".split() + [commit_message], self.local_dir)
+            logger.info(f"Committed:\n{result.stdout}\n")
+        except subprocess.CalledProcessError as exc:
+            if len(exc.stderr) > 0:
+                raise EnvironmentError(exc.stderr)
+            else:
+                raise EnvironmentError(exc.stdout)
+
+    def git_push(
+        self,
+        upstream: Optional[str] = None,
+        blocking: bool = True,
+        auto_lfs_prune: bool = False,
+    ) -> Union[str, Tuple[str, CommandInProgress]]:
+        """
+        git push
+
+        If used without setting `blocking`, will return url to commit on remote
+        repo. If used with `blocking=True`, will return a tuple containing the
+        url to commit and the command object to follow for information about the
+        process.
+
+        Args:
+            upstream (`str`, *optional*):
+                Upstream to which this should push. If not specified, will push
+                to the lastly defined upstream or to the default one (`origin
+                main`).
+            blocking (`bool`, *optional*, defaults to `True`):
+                Whether the function should return only when the push has
+                finished. Setting this to `False` will return an
+                `CommandInProgress` object which has an `is_done` property. This
+                property will be set to `True` when the push is finished.
+            auto_lfs_prune (`bool`, *optional*, defaults to `False`):
+                Whether to automatically prune files once they have been pushed
+                to the remote.
+        """
+        command = "git push"
+
+        if upstream:
+            command += f" --set-upstream {upstream}"
+
+        number_of_commits = commits_to_push(self.local_dir, upstream)
+
+        if number_of_commits > 1:
+            logger.warning(f"Several commits ({number_of_commits}) will be pushed upstream.")
+            if blocking:
+                logger.warning("The progress bars may be unreliable.")
+
+        try:
+            with _lfs_log_progress():
+                process = subprocess.Popen(
+                    command.split(),
+                    stderr=subprocess.PIPE,
+                    stdout=subprocess.PIPE,
+                    encoding="utf-8",
+                    cwd=self.local_dir,
+                )
+
+                if blocking:
+                    stdout, stderr = process.communicate()
+                    return_code = process.poll()
+                    process.kill()
+
+                    if len(stderr):
+                        logger.warning(stderr)
+
+                    if return_code:
+                        raise subprocess.CalledProcessError(return_code, process.args, output=stdout, stderr=stderr)
+
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+        if not blocking:
+
+            def status_method():
+                status = process.poll()
+                if status is None:
+                    return -1
+                else:
+                    return status
+
+            command_in_progress = CommandInProgress(
+                "push",
+                is_done_method=lambda: process.poll() is not None,
+                status_method=status_method,
+                process=process,
+                post_method=self.lfs_prune if auto_lfs_prune else None,
+            )
+
+            self.command_queue.append(command_in_progress)
+
+            return self.git_head_commit_url(), command_in_progress
+
+        if auto_lfs_prune:
+            self.lfs_prune()
+
+        return self.git_head_commit_url()
+
+    def git_checkout(self, revision: str, create_branch_ok: bool = False):
+        """
+        git checkout a given revision
+
+        Specifying `create_branch_ok` to `True` will create the branch to the
+        given revision if that revision doesn't exist.
+
+        Args:
+            revision (`str`):
+                The revision to checkout.
+            create_branch_ok (`str`, *optional*, defaults to `False`):
+                Whether creating a branch named with the `revision` passed at
+                the current checked-out reference if `revision` isn't an
+                existing revision is allowed.
+        """
+        try:
+            result = run_subprocess(f"git checkout {revision}", self.local_dir)
+            logger.warning(f"Checked out {revision} from {self.current_branch}.")
+            logger.warning(result.stdout)
+        except subprocess.CalledProcessError as exc:
+            if not create_branch_ok:
+                raise EnvironmentError(exc.stderr)
+            else:
+                try:
+                    result = run_subprocess(f"git checkout -b {revision}", self.local_dir)
+                    logger.warning(
+                        f"Revision `{revision}` does not exist. Created and checked out branch `{revision}`."
+                    )
+                    logger.warning(result.stdout)
+                except subprocess.CalledProcessError as exc:
+                    raise EnvironmentError(exc.stderr)
+
+    def tag_exists(self, tag_name: str, remote: Optional[str] = None) -> bool:
+        """
+        Check if a tag exists or not.
+
+        Args:
+            tag_name (`str`):
+                The name of the tag to check.
+            remote (`str`, *optional*):
+                Whether to check if the tag exists on a remote. This parameter
+                should be the identifier of the remote.
+
+        Returns:
+            `bool`: Whether the tag exists.
+        """
+        if remote:
+            try:
+                result = run_subprocess(f"git ls-remote origin refs/tags/{tag_name}", self.local_dir).stdout.strip()
+            except subprocess.CalledProcessError as exc:
+                raise EnvironmentError(exc.stderr)
+
+            return len(result) != 0
+        else:
+            try:
+                git_tags = run_subprocess("git tag", self.local_dir).stdout.strip()
+            except subprocess.CalledProcessError as exc:
+                raise EnvironmentError(exc.stderr)
+
+            git_tags = git_tags.split("\n")
+            return tag_name in git_tags
+
+    def delete_tag(self, tag_name: str, remote: Optional[str] = None) -> bool:
+        """
+        Delete a tag, both local and remote, if it exists
+
+        Args:
+            tag_name (`str`):
+                The tag name to delete.
+            remote (`str`, *optional*):
+                The remote on which to delete the tag.
+
+        Returns:
+             `bool`: `True` if deleted, `False` if the tag didn't exist.
+                If remote is not passed, will just be updated locally
+        """
+        delete_locally = True
+        delete_remotely = True
+
+        if not self.tag_exists(tag_name):
+            delete_locally = False
+
+        if not self.tag_exists(tag_name, remote=remote):
+            delete_remotely = False
+
+        if delete_locally:
+            try:
+                run_subprocess(["git", "tag", "-d", tag_name], self.local_dir).stdout.strip()
+            except subprocess.CalledProcessError as exc:
+                raise EnvironmentError(exc.stderr)
+
+        if remote and delete_remotely:
+            try:
+                run_subprocess(f"git push {remote} --delete {tag_name}", self.local_dir).stdout.strip()
+            except subprocess.CalledProcessError as exc:
+                raise EnvironmentError(exc.stderr)
+
+        return True
+
+    def add_tag(self, tag_name: str, message: Optional[str] = None, remote: Optional[str] = None):
+        """
+        Add a tag at the current head and push it
+
+        If remote is None, will just be updated locally
+
+        If no message is provided, the tag will be lightweight. if a message is
+        provided, the tag will be annotated.
+
+        Args:
+            tag_name (`str`):
+                The name of the tag to be added.
+            message (`str`, *optional*):
+                The message that accompanies the tag. The tag will turn into an
+                annotated tag if a message is passed.
+            remote (`str`, *optional*):
+                The remote on which to add the tag.
+        """
+        if message:
+            tag_args = ["git", "tag", "-a", tag_name, "-m", message]
+        else:
+            tag_args = ["git", "tag", tag_name]
+
+        try:
+            run_subprocess(tag_args, self.local_dir).stdout.strip()
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+        if remote:
+            try:
+                run_subprocess(f"git push {remote} {tag_name}", self.local_dir).stdout.strip()
+            except subprocess.CalledProcessError as exc:
+                raise EnvironmentError(exc.stderr)
+
+    def is_repo_clean(self) -> bool:
+        """
+        Return whether or not the git status is clean or not
+
+        Returns:
+            `bool`: `True` if the git status is clean, `False` otherwise.
+        """
+        try:
+            git_status = run_subprocess("git status --porcelain", self.local_dir).stdout.strip()
+        except subprocess.CalledProcessError as exc:
+            raise EnvironmentError(exc.stderr)
+
+        return len(git_status) == 0
+
+    def push_to_hub(
+        self,
+        commit_message: str = "commit files to HF hub",
+        blocking: bool = True,
+        clean_ok: bool = True,
+        auto_lfs_prune: bool = False,
+    ) -> Union[None, str, Tuple[str, CommandInProgress]]:
+        """
+        Helper to add, commit, and push files to remote repository on the
+        HuggingFace Hub. Will automatically track large files (>10MB).
+
+        Args:
+            commit_message (`str`):
+                Message to use for the commit.
+            blocking (`bool`, *optional*, defaults to `True`):
+                Whether the function should return only when the `git push` has
+                finished.
+            clean_ok (`bool`, *optional*, defaults to `True`):
+                If True, this function will return None if the repo is
+                untouched. Default behavior is to fail because the git command
+                fails.
+            auto_lfs_prune (`bool`, *optional*, defaults to `False`):
+                Whether to automatically prune files once they have been pushed
+                to the remote.
+        """
+        if clean_ok and self.is_repo_clean():
+            logger.info("Repo currently clean. Ignoring push_to_hub")
+            return None
+        self.git_add(auto_lfs_track=True)
+        self.git_commit(commit_message)
+        return self.git_push(
+            upstream=f"origin {self.current_branch}",
+            blocking=blocking,
+            auto_lfs_prune=auto_lfs_prune,
+        )
+
+    @contextmanager
+    def commit(
+        self,
+        commit_message: str,
+        branch: Optional[str] = None,
+        track_large_files: bool = True,
+        blocking: bool = True,
+        auto_lfs_prune: bool = False,
+    ):
+        """
+        Context manager utility to handle committing to a repository. This
+        automatically tracks large files (>10Mb) with git-lfs. Set the
+        `track_large_files` argument to `False` if you wish to ignore that
+        behavior.
+
+        Args:
+            commit_message (`str`):
+                Message to use for the commit.
+            branch (`str`, *optional*):
+                The branch on which the commit will appear. This branch will be
+                checked-out before any operation.
+            track_large_files (`bool`, *optional*, defaults to `True`):
+                Whether to automatically track large files or not. Will do so by
+                default.
+            blocking (`bool`, *optional*, defaults to `True`):
+                Whether the function should return only when the `git push` has
+                finished.
+            auto_lfs_prune (`bool`, defaults to `True`):
+                Whether to automatically prune files once they have been pushed
+                to the remote.
+
+        Examples:
+
+        ```python
+        >>> with Repository(
+        ...     "text-files",
+        ...     clone_from="<user>/text-files",
+        ...     token=True,
+        >>> ).commit("My first file :)"):
+        ...     with open("file.txt", "w+") as f:
+        ...         f.write(json.dumps({"hey": 8}))
+
+        >>> import torch
+
+        >>> model = torch.nn.Transformer()
+        >>> with Repository(
+        ...     "torch-model",
+        ...     clone_from="<user>/torch-model",
+        ...     token=True,
+        >>> ).commit("My cool model :)"):
+        ...     torch.save(model.state_dict(), "model.pt")
+        ```
+
+        """
+
+        files_to_stage = files_to_be_staged(".", folder=self.local_dir)
+
+        if len(files_to_stage):
+            files_in_msg = str(files_to_stage[:5])[:-1] + ", ...]" if len(files_to_stage) > 5 else str(files_to_stage)
+            logger.error(
+                "There exists some updated files in the local repository that are not"
+                f" committed: {files_in_msg}. This may lead to errors if checking out"
+                " a branch. These files and their modifications will be added to the"
+                " current commit."
+            )
+
+        if branch is not None:
+            self.git_checkout(branch, create_branch_ok=True)
+
+        if is_tracked_upstream(self.local_dir):
+            logger.warning("Pulling changes ...")
+            self.git_pull(rebase=True)
+        else:
+            logger.warning(f"The current branch has no upstream branch. Will push to 'origin {self.current_branch}'")
+
+        current_working_directory = os.getcwd()
+        os.chdir(os.path.join(current_working_directory, self.local_dir))
+
+        try:
+            yield self
+        finally:
+            self.git_add(auto_lfs_track=track_large_files)
+
+            try:
+                self.git_commit(commit_message)
+            except OSError as e:
+                # If no changes are detected, there is nothing to commit.
+                if "nothing to commit" not in str(e):
+                    raise e
+
+            try:
+                self.git_push(
+                    upstream=f"origin {self.current_branch}",
+                    blocking=blocking,
+                    auto_lfs_prune=auto_lfs_prune,
+                )
+            except OSError as e:
+                # If no changes are detected, there is nothing to commit.
+                if "could not read Username" in str(e):
+                    raise OSError("Couldn't authenticate user for push. Did you set `token` to `True`?") from e
+                else:
+                    raise e
+
+            os.chdir(current_working_directory)
+
+    def repocard_metadata_load(self) -> Optional[Dict]:
+        filepath = os.path.join(self.local_dir, constants.REPOCARD_NAME)
+        if os.path.isfile(filepath):
+            return metadata_load(filepath)
+        return None
+
+    def repocard_metadata_save(self, data: Dict) -> None:
+        return metadata_save(os.path.join(self.local_dir, constants.REPOCARD_NAME), data)
+
+    @property
+    def commands_failed(self):
+        """
+        Returns the asynchronous commands that failed.
+        """
+        return [c for c in self.command_queue if c.status > 0]
+
+    @property
+    def commands_in_progress(self):
+        """
+        Returns the asynchronous commands that are currently in progress.
+        """
+        return [c for c in self.command_queue if not c.is_done]
+
+    def wait_for_commands(self):
+        """
+        Blocking method: blocks all subsequent execution until all commands have
+        been processed.
+        """
+        index = 0
+        for command_failed in self.commands_failed:
+            logger.error(f"The {command_failed.title} command with PID {command_failed._process.pid} failed.")
+            logger.error(command_failed.stderr)
+
+        while self.commands_in_progress:
+            if index % 10 == 0:
+                logger.warning(
+                    f"Waiting for the following commands to finish before shutting down: {self.commands_in_progress}."
+                )
+
+            index += 1
+
+            time.sleep(1)

.venv/lib/python3.13/site-packages/inquirerpy-0.3.4.dist-info/INSTALLER

@@ -0,0 +1 @@
+uv

.venv/lib/python3.13/site-packages/inquirerpy-0.3.4.dist-info/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2020 Kevin Zhuang
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

.venv/lib/python3.13/site-packages/inquirerpy-0.3.4.dist-info/METADATA

@@ -0,0 +1,191 @@
+Metadata-Version: 2.1
+Name: inquirerpy
+Version: 0.3.4
+Summary: Python port of Inquirer.js (A collection of common interactive command-line user interfaces)
+Home-page: https://github.com/kazhala/InquirerPy
+License: MIT
+Keywords: cli,prompt-toolkit,commandline,inquirer,development
+Author: Kevin Zhuang
+Author-email: kevin7441@gmail.com
+Maintainer: Kevin Zhuang
+Maintainer-email: kevin7441@gmail.com
+Requires-Python: >=3.7,<4.0
+Classifier: Development Status :: 2 - Pre-Alpha
+Classifier: Environment :: Console
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Operating System :: Microsoft
+Classifier: Operating System :: Unix
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Topic :: Software Development
+Classifier: Topic :: Software Development :: Libraries
+Classifier: Topic :: Software Development :: Libraries :: Application Frameworks
+Classifier: Topic :: Software Development :: User Interfaces
+Provides-Extra: docs
+Requires-Dist: Sphinx (>=4.1.2,<5.0.0); extra == "docs"
+Requires-Dist: furo (>=2021.8.17-beta.43,<2022.0.0); extra == "docs"
+Requires-Dist: myst-parser (>=0.15.1,<0.16.0); extra == "docs"
+Requires-Dist: pfzy (>=0.3.1,<0.4.0)
+Requires-Dist: prompt-toolkit (>=3.0.1,<4.0.0)
+Requires-Dist: sphinx-autobuild (>=2021.3.14,<2022.0.0); extra == "docs"
+Requires-Dist: sphinx-copybutton (>=0.4.0,<0.5.0); extra == "docs"
+Project-URL: Documentation, https://inquirerpy.readthedocs.io
+Project-URL: Repository, https://github.com/kazhala/InquirerPy
+Description-Content-Type: text/markdown
+
+# InquirerPy
+
+[![Test](https://github.com/kazhala/InquirerPy/workflows/Test/badge.svg)](https://github.com/kazhala/InquirerPy/actions?query=workflow%3ATest)
+[![Lint](https://github.com/kazhala/InquirerPy/workflows/Lint/badge.svg)](https://github.com/kazhala/InquirerPy/actions?query=workflow%3ALint)
+[![Build](https://codebuild.ap-southeast-2.amazonaws.com/badges?uuid=eyJlbmNyeXB0ZWREYXRhIjoiUUYyRUIxOXBWZ0hKcUhrbXplQklMemRsTVBxbUk3bFlTdldnRGpxeEpQSXJidEtmVEVzbVNCTE1UR3VoRSt2N0NQV0VaUXlCUzNackFBNzRVUFBBS1FnPSIsIml2UGFyYW1ldGVyU3BlYyI6IloxREtFeWY4WkhxV0NFWU0iLCJtYXRlcmlhbFNldFNlcmlhbCI6MX0%3D&branch=master)](https://ap-southeast-2.console.aws.amazon.com/codesuite/codebuild/378756445655/projects/InquirerPy/history?region=ap-southeast-2&builds-meta=eyJmIjp7InRleHQiOiIifSwicyI6e30sIm4iOjIwLCJpIjowfQ)
+[![Coverage](https://img.shields.io/coveralls/github/kazhala/InquirerPy?logo=coveralls)](https://coveralls.io/github/kazhala/InquirerPy?branch=master)
+[![Version](https://img.shields.io/pypi/pyversions/InquirerPy)](https://pypi.org/project/InquirerPy/)
+[![PyPi](https://img.shields.io/pypi/v/InquirerPy)](https://pypi.org/project/InquirerPy/)
+
+Documentation: [inquirerpy.readthedocs.io](https://inquirerpy.readthedocs.io/)
+
+<!-- start intro -->
+
+## Introduction
+
+`InquirerPy` is a Python port of the famous [Inquirer.js](https://github.com/SBoudrias/Inquirer.js/) (A collection of common interactive command line user interfaces).
+This project is a re-implementation of the [PyInquirer](https://github.com/CITGuru/PyInquirer) project, with bug fixes of known issues, new prompts, backward compatible APIs
+as well as more customisation options.
+
+<!-- end intro -->
+
+![Demo](https://github.com/kazhala/gif/blob/master/InquirerPy-demo.gif)
+
+## Motivation
+
+[PyInquirer](https://github.com/CITGuru/PyInquirer) is a great Python port of [Inquirer.js](https://github.com/SBoudrias/Inquirer.js/), however, the project is slowly reaching
+to an unmaintained state with various issues left behind and no intention to implement more feature requests. I was heavily relying on this library for other projects but
+could not proceed due to the limitations.
+
+Some noticeable ones that bother me the most:
+
+- hard limit on `prompt_toolkit` version 1.0.3
+- various color issues
+- various cursor issues
+- No options for VI/Emacs navigation key bindings
+- Pagination option doesn't work
+
+This project uses python3.7+ type hinting with focus on resolving above issues while providing greater customisation options.
+
+## Requirements
+
+### OS
+
+Leveraging [prompt_toolkit](https://github.com/prompt-toolkit/python-prompt-toolkit), `InquirerPy` works cross platform for all OS. Although Unix platform may have a better experience than Windows.
+
+### Python
+
+```
+python >= 3.7
+```
+
+## Getting Started
+
+Checkout full documentation **[here](https://inquirerpy.readthedocs.io/)**.
+
+### Install
+
+```sh
+pip3 install InquirerPy
+```
+
+### Quick Start
+
+#### Classic Syntax (PyInquirer)
+
+```python
+from InquirerPy import prompt
+
+questions = [
+    {"type": "input", "message": "What's your name:", "name": "name"},
+    {"type": "confirm", "message": "Confirm?", "name": "confirm"},
+]
+result = prompt(questions)
+name = result["name"]
+confirm = result["confirm"]
+```
+
+#### Alternate Syntax
+
+```python
+from InquirerPy import inquirer
+
+name = inquirer.text(message="What's your name:").execute()
+confirm = inquirer.confirm(message="Confirm?").execute()
+```
+
+<!-- start migration -->
+
+## Migrating from PyInquirer
+
+Most APIs from [PyInquirer](https://github.com/CITGuru/PyInquirer) should be compatible with `InquirerPy`. If you have discovered more incompatible APIs, please
+create an issue or directly update README via a pull request.
+
+### EditorPrompt
+
+`InquirerPy` does not support [editor](https://github.com/CITGuru/PyInquirer#editor---type-editor) prompt as of now.
+
+### CheckboxPrompt
+
+The following table contains the mapping of incompatible parameters.
+
+| PyInquirer      | InquirerPy      |
+| --------------- | --------------- |
+| pointer_sign    | pointer         |
+| selected_sign   | enabled_symbol  |
+| unselected_sign | disabled_symbol |
+
+### Style
+
+Every style keys from [PyInquirer](https://github.com/CITGuru/PyInquirer) is present in `InquirerPy` except the ones in the following table.
+
+| PyInquirer | InquirerPy |
+| ---------- | ---------- |
+| selected   | pointer    |
+
+Although `InquirerPy` support all the keys from [PyInquirer](https://github.com/CITGuru/PyInquirer), the styling works slightly different.
+Please refer to the [Style](https://inquirerpy.readthedocs.io/en/latest/pages/style.html) documentation for detailed information.
+
+<!-- end migration -->
+
+## Similar projects
+
+### questionary
+
+[questionary](https://github.com/tmbo/questionary) is a fantastic fork which supports `prompt_toolkit` 3.0.0+ with performance improvement and more customisation options.
+It's already a well established and stable library.
+
+Comparing with [questionary](https://github.com/tmbo/questionary), `InquirerPy` offers even more customisation options in styles, UI as well as key bindings. `InquirerPy` also provides a new
+and powerful [fuzzy](https://inquirerpy.readthedocs.io/en/latest/pages/prompts/fuzzy.html) prompt.
+
+### python-inquirer
+
+[python-inquirer](https://github.com/magmax/python-inquirer) is another great Python port of [Inquirer.js](https://github.com/SBoudrias/Inquirer.js/). Instead of using `prompt_toolkit`, it
+leverages the library `blessed` to implement the UI.
+
+Before implementing `InquirerPy`, this library came up as an alternative. It's a more stable library comparing to the original [PyInquirer](https://github.com/CITGuru/PyInquirer), however
+it has a rather limited customisation options and an older UI which did not solve the issues I was facing described in the [Motivation](#Motivation) section.
+
+Comparing with [python-inquirer](https://github.com/magmax/python-inquirer), `InquirerPy` offers a slightly better UI,
+more customisation options in key bindings and styles, providing pagination as well as more prompts.
+
+## Credit
+
+This project is based on the great work done by the following projects & their authors.
+
+- [PyInquirer](https://github.com/CITGuru/PyInquirer)
+- [prompt_toolkit](https://github.com/prompt-toolkit/python-prompt-toolkit)
+
+## License
+
+This project is licensed under [MIT](https://github.com/kazhala/InquirerPy/blob/master/LICENSE).
+

.venv/lib/python3.13/site-packages/inquirerpy-0.3.4.dist-info/RECORD

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+InquirerPy/resolver.py,sha256=L2PnXpp7HwM4Vp4mvNXjZ_CiX-BFgQ4KgnMTjXDMihI,8396
+InquirerPy/separator.py,sha256=Om-lhbj9kOGocwhKdQ2Wex6CTJH69CKar72wPZRETQY,693
+InquirerPy/utils.py,sha256=Lf0nYT1xNJobjQrNR5Z0vDIR4jJeITFLeI0EfEuYAm8,11224
+InquirerPy/validator.py,sha256=exRQ0dEdfaVScVYuSsPfLNuhwWIVueHHw1kUYAjGr2w,5907
+inquirerpy-0.3.4.dist-info/INSTALLER,sha256=5hhM4Q4mYTT9z6QB6PGpUAW81PGNFrYrdXMj4oM_6ak,2
+inquirerpy-0.3.4.dist-info/LICENSE,sha256=f_X1vlC7GWiYmTHt2_p9ESxTHEj_V3y4xAbsCRGCx6I,1069
+inquirerpy-0.3.4.dist-info/METADATA,sha256=E6RR6q3qbYpH4eVeNPppbd1UV18ywnN7jjuxtJQnis8,8145
+inquirerpy-0.3.4.dist-info/RECORD,,
+inquirerpy-0.3.4.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
+inquirerpy-0.3.4.dist-info/WHEEL,sha256=y3eDiaFVSNTPbgzfNn0nYn5tEn1cX6WrdetDlQM4xWw,83

.venv/lib/python3.13/site-packages/inquirerpy-0.3.4.dist-info/WHEEL

@@ -0,0 +1,4 @@
+Wheel-Version: 1.0
+Generator: poetry 1.0.7
+Root-Is-Purelib: true
+Tag: py3-none-any