diff --git a/pyproject.toml b/pyproject.toml
index 65dcfd2..3219aef 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -10,6 +10,7 @@ readme = "README.md"
 requires-python = ">=3.11"
 dependencies = [
     "falsa>=0.0.3",
+    "fsspec>=2024.1.0",
     "pandas>=2.2.3",
     "polars>=1.24.0",
     "pydantic>=2.10.6",
@@ -20,6 +21,12 @@ dependencies = [
     "dash-ag-grid>=31.3.0",
 ]
 
+[project.optional-dependencies]
+s3 = ["s3fs>=2024.1.0"]
+azure = ["adlfs>=2024.1.0"]
+gcs = ["gcsfs>=2024.1.0"]
+cloud = ["s3fs>=2024.1.0", "adlfs>=2024.1.0", "gcsfs>=2024.1.0"]
+
 
 [tool.hatch.build.targets.wheel]
 packages = ["sparkparse"]
@@ -45,3 +52,9 @@ ignore = ["E501"]
 
 [tool.ruff.lint.isort]
 known-first-party = ["sparkparse"]
+
+[tool.pyrefly]
+project-includes = [
+    "**/*.py*",
+    "**/*.ipynb",
+]
diff --git a/sparkparse/analyze.py b/sparkparse/analyze.py
index cb1a8ab..1866e57 100644
--- a/sparkparse/analyze.py
+++ b/sparkparse/analyze.py
@@ -6,6 +6,7 @@
 import polars as pl
 
 from sparkparse.models import NodeType, ParsedLogDataFrames
+from sparkparse.storage import write_text
 
 _JOIN_NODE_TYPES = frozenset(
     [
@@ -26,13 +27,20 @@ def _detail_dict(details_str: str | None) -> dict[str, Any] | None:
         return None
 
 
-def to_plan_summary(dfs: ParsedLogDataFrames, log_name: str) -> dict[str, Any]:
+def to_plan_summary(
+    dfs: ParsedLogDataFrames,
+    log_name: str,
+    out_path: str | None = None,
+) -> dict[str, Any]:
     """
     Return a token-efficient dict of execution plan data for LLM analysis.
 
     Presents raw facts (nodes, durations, bytes, join types, paths) without
     pre-assigned severity. The value over df.explain() is runtime metrics
     (per-node durations correlated from accumulator updates).
+
+    When ``out_path`` is provided, the JSON-serialized summary is also written
+    there (local path or cloud URI via storage.write_text).
     """
     dag = dfs.dag
     combined = dfs.combined
@@ -110,12 +118,17 @@ def to_plan_summary(dfs: ParsedLogDataFrames, log_name: str) -> dict[str, Any]:
         pl.sum("jvm_gc_time_seconds").alias("jvm_gc_time_seconds"),
     ).row(0, named=True)
 
-    return {
+    summary = {
         "log_name": log_name,
         "queries": queries,
         "totals": agg,
     }
 
+    if out_path is not None:
+        write_text(out_path, json.dumps(summary, indent=2, default=str))
+
+    return summary
+
 
 def find_cartesian_joins(dfs: ParsedLogDataFrames) -> pl.DataFrame:
     """
@@ -186,16 +199,12 @@ def find_largest_scans(dfs: ParsedLogDataFrames, n: int = 10) -> pl.DataFrame:
     )
 
     return (
-        scan_nodes.select(
-            "query_id", "node_id", "node_name", "details", "node_duration_minutes"
-        )
+        scan_nodes.select("query_id", "node_id", "node_name", "details", "node_duration_minutes")
         .join(node_bytes, on=["query_id", "node_name"], how="left")
         .with_columns(
             pl.col("details")
             .map_elements(
-                lambda s: json.loads(s)["detail"]["location"]["location"]
-                if s is not None
-                else [],
+                lambda s: json.loads(s)["detail"]["location"]["location"] if s is not None else [],
                 return_dtype=pl.List(pl.String),
             )
             .alias("paths")
diff --git a/sparkparse/app.py b/sparkparse/app.py
index 9704c62..c060383 100644
--- a/sparkparse/app.py
+++ b/sparkparse/app.py
@@ -10,6 +10,12 @@
 from sparkparse.dashboard import init_dashboard, run_app
 from sparkparse.models import OutputFormat, ParsedLogDataFrames
 from sparkparse.parse import get_parsed_metrics
+from sparkparse.storage import (
+    get_path_name,
+    get_path_stem,
+    is_cloud_path,
+    write_text,
+)
 
 __version__ = "0.1.0"
 
@@ -98,8 +104,8 @@ def analyze(
         typer.Option(help="Analyze a single log file instead of the whole directory."),
     ] = None,
     out_file: Annotated[
-        Path | None,
-        typer.Option(help="Write analysis JSON to this file instead of stdout."),
+        str | None,
+        typer.Option(help="Write analysis output to this file (local path or cloud URI)."),
     ] = None,
     format: Annotated[
         AnalysisFormat,
@@ -116,7 +122,7 @@ def analyze(
         verbose=False,
     )
 
-    log_name = Path(log_file).stem if log_file else Path(log_dir).name
+    log_name = get_path_stem(log_file) if log_file else get_path_name(log_dir)
     summary = to_plan_summary(dfs, log_name)
 
     if format == AnalysisFormat.json:
@@ -128,9 +134,7 @@ def analyze(
         lines.append(f"Bytes read: {totals.get('bytes_read', 0):,}")
         lines.append(f"Bytes written: {totals.get('bytes_written', 0):,}")
         lines.append(f"Shuffle bytes read: {totals.get('shuffle_bytes_read', 0):,}")
-        lines.append(
-            f"Shuffle bytes written: {totals.get('shuffle_bytes_written', 0):,}"
-        )
+        lines.append(f"Shuffle bytes written: {totals.get('shuffle_bytes_written', 0):,}")
         lines.append(f"Memory spilled: {totals.get('memory_bytes_spilled', 0):,}")
         lines.append(f"Disk spilled: {totals.get('disk_bytes_spilled', 0):,}")
         for q in summary.get("queries", []):
@@ -149,8 +153,9 @@ def analyze(
         output = "\n".join(lines)
 
     if out_file is not None:
-        out_file.parent.mkdir(parents=True, exist_ok=True)
-        out_file.write_text(output)
+        if not is_cloud_path(out_file):
+            Path(out_file).parent.mkdir(parents=True, exist_ok=True)
+        write_text(out_file, output)
         typer.echo(f"Analysis written to {out_file}", err=True)
     else:
         sys.stdout.write(output + "\n")
diff --git a/sparkparse/capture.py b/sparkparse/capture.py
index 26691b2..0a33dff 100644
--- a/sparkparse/capture.py
+++ b/sparkparse/capture.py
@@ -1,14 +1,12 @@
 import functools
 import logging
 import os
-import shutil
 import subprocess
 import sys
 import tempfile
 import time
 import webbrowser
 from collections.abc import Callable
-from pathlib import Path
 from typing import Any, Literal, TypeVar, overload
 
 from pyspark.sql import SparkSession
@@ -16,6 +14,16 @@
 from sparkparse.analyze import to_plan_summary
 from sparkparse.app import get
 from sparkparse.models import ParsedLogDataFrames
+from sparkparse.storage import (
+    copy_file,
+    ensure_dir,
+    get_path_name,
+    get_path_stem,
+    join_path,
+    list_files,
+    path_exists,
+    remove_dir,
+)
 
 _log = logging.getLogger(__name__)
 
@@ -46,9 +54,7 @@ def __init__(
         self._parsed_logs = None
         self._analysis: dict[str, Any] | None = None
 
-    def __call__(
-        self, func: Callable[..., R]
-    ) -> Callable[..., tuple[R, "SparkparseCapture"]]:
+    def __call__(self, func: Callable[..., R]) -> Callable[..., tuple[R, "SparkparseCapture"]]:
         @functools.wraps(func)
         def get_wrapper(*args: Any, **kwargs: Any) -> tuple[R, "SparkparseCapture"]:
             with self:
@@ -70,7 +76,7 @@ def __enter__(self):
         if self.temp_dir is None:
             self._log_dir = tempfile.mkdtemp(prefix="sparkparse_")
         else:
-            os.makedirs(self.temp_dir, exist_ok=True)
+            ensure_dir(self.temp_dir)
             self._log_dir = self.temp_dir
 
         if self.spark or SparkSession.getActiveSession():
@@ -130,14 +136,14 @@ def __exit__(self, exc_type, *args):
         if self._log_dir is None:
             raise ValueError("log directory is not set")
 
-        log_dir_contents = [i for i in Path(self._log_dir).glob("*")]
-        if not any(log_dir_contents):
+        log_dir_contents = list_files(self._log_dir)
+        if not log_dir_contents:
             raise ValueError("no logs found in log directory")
 
         if self._orig_log_dir is not None:
             for f in log_dir_contents:
-                out_path = Path(self._orig_log_dir) / f.stem
-                shutil.copy2(f.as_posix(), out_path)
+                out_path = join_path(self._orig_log_dir, get_path_stem(f))
+                copy_file(f, out_path)
 
         if self.action == "viz":
             self._run_dashboard_in_background()
@@ -152,17 +158,13 @@ def __exit__(self, exc_type, *args):
                 raise ValueError("log directory is not set")
             result = get(log_dir=self._log_dir)
             self._parsed_logs = result
-            log_name = Path(self._log_dir).name
+            log_name = get_path_name(self._log_dir)
             self._analysis = to_plan_summary(result, log_name)
         else:
             raise ValueError(f"Invalid action: {self.action}")
 
-        if (
-            self._should_cleanup
-            and self._log_dir is not None
-            and os.path.exists(self._log_dir)
-        ):
-            shutil.rmtree(self._log_dir)
+        if self._should_cleanup and self._log_dir is not None and path_exists(self._log_dir):
+            remove_dir(self._log_dir)
 
 
 def capture_context(
@@ -217,9 +219,7 @@ def decorator(
         else:
             _spark = spark
 
-        cap = SparkparseCapture(
-            action, spark=_spark, temp_dir=temp_dir, headless=headless
-        )
+        cap = SparkparseCapture(action, spark=_spark, temp_dir=temp_dir, headless=headless)
         return cap(func)
 
     if func is None:
diff --git a/sparkparse/clean.py b/sparkparse/clean.py
index 5258672..0af36fe 100644
--- a/sparkparse/clean.py
+++ b/sparkparse/clean.py
@@ -1,4 +1,5 @@
 import logging
+from pathlib import Path
 
 import polars as pl
 
@@ -12,6 +13,7 @@
     Stage,
     Task,
 )
+from sparkparse.storage import is_cloud_path, join_path
 
 
 def clean_jobs(jobs: list[Job]) -> pl.DataFrame:
@@ -814,10 +816,13 @@ def write_parsed_log(
     parsed_name: str,
     suffix: str,
 ) -> None:
-    out_dir_path = resolve_dir(out_dir, 1)
-    out_dir_path.mkdir(parents=True, exist_ok=True)
-
-    out_path = out_dir_path / f"{parsed_name}_{suffix}"
+    if is_cloud_path(out_dir):
+        out_path = join_path(out_dir, f"{parsed_name}_{suffix}")
+    else:
+        out_dir_path = resolve_dir(out_dir, 1)
+        assert isinstance(out_dir_path, Path)
+        out_dir_path.mkdir(parents=True, exist_ok=True)
+        out_path = out_dir_path / f"{parsed_name}_{suffix}"
 
     logging.info(f"Writing parsed log: {out_path}")
     logging.debug(f"Output format: {out_format}")
diff --git a/sparkparse/common.py b/sparkparse/common.py
index 65b5ac7..b579e68 100644
--- a/sparkparse/common.py
+++ b/sparkparse/common.py
@@ -7,6 +7,7 @@
 from pyspark.sql import SparkSession
 
 from sparkparse.models import OutputFormat
+from sparkparse.storage import is_cloud_path, open_file
 
 
 def get_current_time() -> datetime.datetime:
@@ -21,28 +22,44 @@ def timeit_wrapper(*args, **kwargs):
         result = func(*args, **kwargs)
         end_time = time.perf_counter()
         total_time = end_time - start_time
-        print(
-            f"{get_current_time()} -- Function {func.__name__} Took {total_time * 1000:.2f} ms"
-        )
+        print(f"{get_current_time()} -- Function {func.__name__} Took {total_time * 1000:.2f} ms")
         return result
 
     return timeit_wrapper
 
 
 def write_dataframe(
-    df: pl.DataFrame, out_path: Path, out_format: OutputFormat, overwrite: bool = True
+    df: pl.DataFrame, out_path: str | Path, out_format: OutputFormat, overwrite: bool = True
 ) -> None:
-    if overwrite:
-        out_path.unlink(missing_ok=True)
+    out_path_str = str(out_path)
+    cloud = is_cloud_path(out_path_str)
+
+    if overwrite and not cloud:
+        Path(out_path_str).unlink(missing_ok=True)
 
     if out_format == OutputFormat.csv:
-        df.write_csv(out_path.with_suffix(".csv").as_posix(), include_header=True)
+        target = out_path_str + ".csv"
+        if cloud:
+            with open_file(target, "wb") as f:
+                df.write_csv(f)
+        else:
+            df.write_csv(target, include_header=True)
     elif out_format == OutputFormat.parquet:
-        df.write_parquet(out_path.with_suffix(".parquet").as_posix())
+        target = out_path_str + ".parquet"
+        if cloud:
+            with open_file(target, "wb") as f:
+                df.write_parquet(f)
+        else:
+            df.write_parquet(target)
     elif out_format == OutputFormat.delta:
-        df.write_delta(out_path.as_posix())
+        df.write_delta(out_path_str)
     elif out_format == OutputFormat.json:
-        df.write_json(out_path.with_suffix(".json").as_posix())
+        target = out_path_str + ".json"
+        if cloud:
+            with open_file(target, "wb") as f:
+                df.write_json(f)
+        else:
+            df.write_json(target)
 
 
 def get_spark(log_dir: Path) -> SparkSession:
@@ -74,10 +91,13 @@ def create_header(header_length: int, title: str, center: bool, spacer: str):
     return output
 
 
-def resolve_dir(incoming_dir: str | Path, default_nesting=2) -> Path:
+def resolve_dir(incoming_dir: str | Path, default_nesting=2) -> str | Path:
     # resolves path of incoming dir_str
     # if provided path does not exist, will attempt to resolve relative to sparkparse root
 
+    if is_cloud_path(str(incoming_dir)):
+        return str(incoming_dir)
+
     if isinstance(incoming_dir, Path):
         initial_path = incoming_dir
     else:
@@ -89,9 +109,7 @@ def resolve_dir(incoming_dir: str | Path, default_nesting=2) -> Path:
     path = Path(__file__).parents[default_nesting] / incoming_dir
     if not path.exists():
         if not path.parent.exists():
-            raise ValueError(
-                f"directory {path} does not exist and parent is also missing"
-            )
+            raise ValueError(f"directory {path} does not exist and parent is also missing")
         path.mkdir(exist_ok=True, parents=True)
 
     return path
diff --git a/sparkparse/parse.py b/sparkparse/parse.py
index 70e4759..1562cc1 100644
--- a/sparkparse/parse.py
+++ b/sparkparse/parse.py
@@ -41,6 +41,13 @@
     deserialize_insert_into_hadoop_fs_relation_command_detail,
     deserialize_scan_detail,
 )
+from sparkparse.storage import (
+    get_path_stem,
+    is_cloud_path,
+    join_path,
+    list_files,
+    open_file,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -452,20 +459,22 @@ def parse_driver_accum_update(line_dict: dict) -> list[DriverAccumUpdates]:
     return accum_updates
 
 
-def check_if_log_has_queries(log_path: Path) -> bool:
-    if ".DS_Store" in log_path.name:
+def check_if_log_has_queries(log_path: str | Path) -> bool:
+    log_path_str = str(log_path)
+    if ".DS_Store" in log_path_str:
         return False
 
-    with log_path.open("r") as f:
+    with open_file(log_path_str, "r") as f:
         all_contents = f.read()
 
     return "SparkListenerSQLExecutionStart" in all_contents
 
 
 @timeit
-def parse_log(log_path: Path, out_name: str | None = None) -> ParsedLog:
-    logger.debug(f"Starting to parse log file: {log_path}")
-    with log_path.open("r") as f:
+def parse_log(log_path: str | Path, out_name: str | None = None) -> ParsedLog:
+    log_path_str = str(log_path)
+    logger.debug(f"Starting to parse log file: {log_path_str}")
+    with open_file(log_path_str, "r") as f:
         all_contents = f.readlines()
 
     start_point = "SparkListenerApplicationStart"
@@ -568,7 +577,8 @@ def get_parsed_metrics(
     out_format: OutputFormat | None = OutputFormat.csv,
     verbose: bool = False,
 ) -> ParsedLogDataFrames:
-    log_dir_path = resolve_dir(log_dir)
+    log_dir_str = str(log_dir)
+    cloud = is_cloud_path(log_dir_str)
 
     if verbose:
         logging.basicConfig(
@@ -579,16 +589,28 @@ def get_parsed_metrics(
     else:
         logging.basicConfig(level=logging.INFO, format="%(message)s")
 
-    if log_file is None:
-        log_to_parse = sorted(log_dir_path.glob("*"))[-1]
+    if cloud:
+        if log_file is None:
+            candidates = sorted(list_files(log_dir_str))
+            if not candidates:
+                raise ValueError(f"No log files found in cloud path: {log_dir_str}")
+            log_to_parse = candidates[-1]
+        else:
+            log_to_parse = join_path(log_dir_str, log_file)
+        log_stem = get_path_stem(log_to_parse)
     else:
-        log_to_parse = log_dir_path / log_file
+        log_dir_path = resolve_dir(log_dir)
+        if log_file is None:
+            log_to_parse = sorted(log_dir_path.glob("*"))[-1]
+        else:
+            log_to_parse = log_dir_path / log_file
+        log_stem = log_to_parse.stem
 
     logging.info(f"Reading log file: {log_to_parse}")
 
     result = parse_log(log_to_parse, out_name)
     dag_df = log_to_dag_df(result)
-    combined_df = log_to_combined_df(result, dag_df, log_to_parse.stem)
+    combined_df = log_to_combined_df(result, dag_df, log_stem)
 
     output = ParsedLogDataFrames(combined=combined_df, dag=dag_df)
 
diff --git a/sparkparse/storage.py b/sparkparse/storage.py
new file mode 100644
index 0000000..ccc31e6
--- /dev/null
+++ b/sparkparse/storage.py
@@ -0,0 +1,161 @@
+"""Path-agnostic I/O utilities for local and cloud storage.
+
+Cloud paths (``s3://``, ``abfss://``, ``gs://``, ``dbfs:/``) are routed through
+``fsspec``; local paths use the stdlib. ``fsspec`` is imported lazily inside the
+functions that need it, so local-only users do not have to install it or any
+cloud backend.
+"""
+
+from __future__ import annotations
+
+import logging
+import os
+import shutil
+from pathlib import Path
+from typing import IO, Any
+
+logger = logging.getLogger(__name__)
+
+CLOUD_PREFIXES: tuple[str, ...] = ("s3://", "abfss://", "gs://", "dbfs:/")
+
+
+def is_cloud_path(path: str | Path) -> bool:
+    """Return True for cloud URIs, False for local paths.
+
+    DBFS local-mount paths (``/dbfs/...``) and Unity Catalog volumes
+    (``/Volumes/...``) are local filesystem paths on the Databricks driver and
+    therefore return False.
+    """
+    path_str = str(path)
+    return path_str.startswith(CLOUD_PREFIXES)
+
+
+def _import_fsspec() -> Any:
+    try:
+        import fsspec
+
+        return fsspec
+    except ImportError as e:  # pragma: no cover - exercised only without fsspec
+        raise ImportError(
+            "fsspec is required for cloud path support. "
+            "Install it with `uv add fsspec` or pull in the relevant cloud "
+            "extra: sparkparse[s3|azure|gcs|cloud]."
+        ) from e
+
+
+def _fs_for(path: str) -> tuple[Any, str]:
+    """Return (fsspec_filesystem, path_stripped_of_protocol) for a cloud path."""
+    fsspec = _import_fsspec()
+    fs, _, stripped = fsspec.core.get_fs_token_paths(path)
+    return fs, stripped
+
+
+def open_file(path: str | Path, mode: str = "r") -> IO[Any]:
+    """Open a local or cloud file.
+
+    Cloud paths require the relevant fsspec backend (``s3fs``, ``adlfs``,
+    ``gcsfs``) and credentials to be configured in the environment.
+    """
+    path_str = str(path)
+    if is_cloud_path(path_str):
+        fsspec = _import_fsspec()
+        return fsspec.open(path_str, mode).open()  # type: ignore[no-any-return]
+    return open(path_str, mode)
+
+
+def write_text(path: str | Path, content: str) -> None:
+    """Write ``content`` to ``path`` as UTF-8 text, local or cloud."""
+    with open_file(path, "w") as f:
+        f.write(content)
+
+
+def read_text(path: str | Path) -> str:
+    """Read and return the full text content of ``path``."""
+    with open_file(path, "r") as f:
+        return f.read()  # type: ignore[no-any-return]
+
+
+def list_files(path: str | Path, pattern: str = "*") -> list[str]:
+    """List files under ``path`` matching ``pattern``.
+
+    Returns fully-qualified paths (including the cloud protocol prefix when
+    applicable) so results can be passed back into the other functions in this
+    module.
+    """
+    path_str = str(path)
+    if is_cloud_path(path_str):
+        fsspec = _import_fsspec()
+        fs, _ = fsspec.core.url_to_fs(path_str)
+        glob_pattern = f"{path_str.rstrip('/')}/{pattern}"
+        return [fs.unstrip_protocol(p) for p in fs.glob(glob_pattern)]
+    return [str(p) for p in Path(path_str).glob(pattern)]
+
+
+def copy_file(src: str | Path, dst: str | Path) -> None:
+    """Copy a single file between any combination of local/cloud paths."""
+    src_str, dst_str = str(src), str(dst)
+    if is_cloud_path(src_str) or is_cloud_path(dst_str):
+        fsspec = _import_fsspec()
+        fsspec.copy(src_str, dst_str)
+    else:
+        shutil.copy2(src_str, dst_str)
+
+
+def remove_dir(path: str | Path) -> None:
+    """Recursively remove a directory and its contents."""
+    path_str = str(path)
+    if is_cloud_path(path_str):
+        fsspec = _import_fsspec()
+        fs, _ = fsspec.core.url_to_fs(path_str)
+        fs.rm(path_str, recursive=True)
+    else:
+        shutil.rmtree(path_str)
+
+
+def ensure_dir(path: str | Path) -> None:
+    """Create ``path`` if it does not exist. No-op for cloud paths.
+
+    Cloud object stores have no real directory hierarchy, so directory creation
+    is implicit when an object is written.
+    """
+    path_str = str(path)
+    if is_cloud_path(path_str):
+        return
+    os.makedirs(path_str, exist_ok=True)
+
+
+def path_exists(path: str | Path) -> bool:
+    """Return True if ``path`` exists locally or in cloud storage."""
+    path_str = str(path)
+    if is_cloud_path(path_str):
+        fsspec = _import_fsspec()
+        fs, _ = fsspec.core.url_to_fs(path_str)
+        return bool(fs.exists(path_str))
+    return Path(path_str).exists()
+
+
+def get_path_name(path: str | Path) -> str:
+    """Return the final component of ``path`` (no trailing slash)."""
+    path_str = str(path).rstrip("/")
+    return path_str.rsplit("/", 1)[-1]
+
+
+def get_path_stem(path: str | Path) -> str:
+    """Return the final component of ``path`` without its file extension."""
+    name = get_path_name(path)
+    if "." in name:
+        return name.rsplit(".", 1)[0]
+    return name
+
+
+def join_path(base: str | Path, *parts: str | Path) -> str:
+    """Join ``base`` and ``parts`` with a single separating slash.
+
+    Works for both local relative paths and cloud URIs (which Path cannot
+    handle because of the ``://`` scheme separator).
+    """
+    base_str = str(base).rstrip("/")
+    pieces = [str(p).strip("/") for p in parts if str(p).strip("/")]
+    if not pieces:
+        return base_str
+    return base_str + "/" + "/".join(pieces)
diff --git a/tests/test_storage.py b/tests/test_storage.py
new file mode 100644
index 0000000..11f25b8
--- /dev/null
+++ b/tests/test_storage.py
@@ -0,0 +1,232 @@
+from pathlib import Path
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from sparkparse import storage
+from sparkparse.storage import (
+    copy_file,
+    ensure_dir,
+    get_path_name,
+    get_path_stem,
+    is_cloud_path,
+    join_path,
+    list_files,
+    open_file,
+    path_exists,
+    read_text,
+    remove_dir,
+    write_text,
+)
+
+
+@pytest.mark.parametrize(
+    "path",
+    [
+        "s3://bucket/key",
+        "abfss://container@account.dfs.core.windows.net/path",
+        "gs://bucket/key",
+        "dbfs:/mnt/data/file",
+    ],
+)
+def test_is_cloud_path_true_for_cloud_uris(path: str) -> None:
+    assert is_cloud_path(path) is True
+
+
+@pytest.mark.parametrize(
+    "path",
+    [
+        "/local/path",
+        "./relative/path",
+        "data/logs/raw",
+        "/dbfs/mnt/data/file",
+        "/Volumes/catalog/schema/table",
+        "file.txt",
+    ],
+)
+def test_is_cloud_path_false_for_local_paths(path: str) -> None:
+    assert is_cloud_path(path) is False
+
+
+def test_is_cloud_path_accepts_pathlib() -> None:
+    assert is_cloud_path(Path("/local/path")) is False
+
+
+@pytest.fixture
+def tmpdir_path(tmp_path: Path) -> Path:
+    return tmp_path
+
+
+def test_write_text_and_read_text_round_trip(tmpdir_path: Path) -> None:
+    p = tmpdir_path / "file.txt"
+    write_text(p, "hello cloud\n")
+    assert read_text(p) == "hello cloud\n"
+
+
+def test_write_text_creates_parent_dirs_not_needed(tmpdir_path: Path) -> None:
+    p = tmpdir_path / "nested" / "dir" / "file.txt"
+    ensure_dir(p.parent)
+    write_text(p, "data")
+    assert read_text(p) == "data"
+
+
+def test_list_files_local(tmpdir_path: Path) -> None:
+    (tmpdir_path / "a.txt").write_text("a")
+    (tmpdir_path / "b.json").write_text("b")
+    (tmpdir_path / "c.txt").write_text("c")
+    results = list_files(tmpdir_path, "*.txt")
+    names = sorted(Path(r).name for r in results)
+    assert names == ["a.txt", "c.txt"]
+
+
+def test_list_files_default_pattern(tmpdir_path: Path) -> None:
+    (tmpdir_path / "x").write_text("x")
+    results = list_files(tmpdir_path)
+    assert len(results) == 1
+    assert Path(results[0]).name == "x"
+
+
+def test_copy_file_local(tmpdir_path: Path) -> None:
+    src = tmpdir_path / "src.txt"
+    dst = tmpdir_path / "dst.txt"
+    write_text(src, "copy me")
+    copy_file(src, dst)
+    assert read_text(dst) == "copy me"
+
+
+def test_remove_dir_local(tmpdir_path: Path) -> None:
+    sub = tmpdir_path / "to_remove"
+    sub.mkdir()
+    (sub / "inner.txt").write_text("x")
+    remove_dir(sub)
+    assert not sub.exists()
+
+
+def test_ensure_dir_local_idempotent(tmpdir_path: Path) -> None:
+    new_dir = tmpdir_path / "new_dir"
+    ensure_dir(new_dir)
+    assert new_dir.exists() and new_dir.is_dir()
+    ensure_dir(new_dir)
+    assert new_dir.exists()
+
+
+def test_path_exists_local_true(tmpdir_path: Path) -> None:
+    p = tmpdir_path / "exists.txt"
+    write_text(p, "yes")
+    assert path_exists(p) is True
+
+
+def test_path_exists_local_false(tmpdir_path: Path) -> None:
+    assert path_exists(tmpdir_path / "missing") is False
+
+
+@pytest.mark.parametrize(
+    "path, expected",
+    [
+        ("/local/dir/file.json", "file.json"),
+        ("s3://bucket/prefix/file.json", "file.json"),
+        ("s3://bucket/prefix/", "prefix"),
+        ("gs://bucket/key", "key"),
+        ("plain_name.csv", "plain_name.csv"),
+    ],
+)
+def test_get_path_name(path: str, expected: str) -> None:
+    assert get_path_name(path) == expected
+
+
+@pytest.mark.parametrize(
+    "path, expected",
+    [
+        ("/local/dir/file.json", "file"),
+        ("s3://bucket/prefix/file.json", "file"),
+        ("s3://bucket/prefix/", "prefix"),
+        ("no_extension", "no_extension"),
+        ("plain_name.csv", "plain_name"),
+    ],
+)
+def test_get_path_stem(path: str, expected: str) -> None:
+    assert get_path_stem(path) == expected
+
+
+@pytest.mark.parametrize(
+    "base, parts, expected",
+    [
+        ("s3://bucket/prefix", ("file.txt",), "s3://bucket/prefix/file.txt"),
+        ("s3://bucket/prefix/", ("file.txt",), "s3://bucket/prefix/file.txt"),
+        ("/local/dir", ("sub", "f.csv"), "/local/dir/sub/f.csv"),
+        ("/local/dir/", ("sub", "f.csv"), "/local/dir/sub/f.csv"),
+        ("s3://bucket", (), "s3://bucket"),
+    ],
+)
+def test_join_path(base: str, parts: tuple[str, ...], expected: str) -> None:
+    assert join_path(base, *parts) == expected
+
+
+
+@pytest.fixture
+def mock_fsspec():
+    fake = MagicMock(name="fsspec")
+    file_handle = MagicMock(name="file_handle")
+    file_handle.__enter__.return_value = file_handle
+    file_handle.__exit__.return_value = None
+    fake.open.return_value.open.return_value = file_handle
+    fake.core.url_to_fs.return_value = (MagicMock(name="fs"), "stripped")
+    fake.copy = MagicMock(name="copy")
+    with patch.object(storage, "_import_fsspec", return_value=fake):
+        yield fake
+
+
+def test_open_file_cloud_uses_fsspec(mock_fsspec: MagicMock) -> None:
+    open_file("s3://bucket/key", "r")
+    mock_fsspec.open.assert_called_once_with("s3://bucket/key", "r")
+
+
+def test_write_text_cloud_uses_fsspec(mock_fsspec: MagicMock) -> None:
+    write_text("s3://bucket/key.txt", "content")
+    mock_fsspec.open.assert_called_once_with("s3://bucket/key.txt", "w")
+
+
+def test_read_text_cloud_uses_fsspec(mock_fsspec: MagicMock) -> None:
+    file_handle = mock_fsspec.open.return_value.open.return_value
+    file_handle.read.return_value = "cloud content"
+    result = read_text("gs://bucket/key")
+    assert result == "cloud content"
+    mock_fsspec.open.assert_called_once_with("gs://bucket/key", "r")
+
+
+def test_list_files_cloud_uses_fsspec_glob(mock_fsspec: MagicMock) -> None:
+    fs = mock_fsspec.core.url_to_fs.return_value[0]
+    fs.glob.return_value = ["s3://bucket/key1", "s3://bucket/key2"]
+    fs.unstrip_protocol.side_effect = lambda p: p
+    results = list_files("s3://bucket/path", "*")
+    assert results == ["s3://bucket/key1", "s3://bucket/key2"]
+    fs.glob.assert_called_once_with("s3://bucket/path/*")
+
+
+def test_copy_file_cloud_uses_fsspec_copy(mock_fsspec: MagicMock) -> None:
+    copy_file("s3://bucket/src", "s3://bucket/dst")
+    mock_fsspec.copy.assert_called_once_with("s3://bucket/src", "s3://bucket/dst")
+
+
+def test_remove_dir_cloud_uses_fsspec_rm(mock_fsspec: MagicMock) -> None:
+    fs = mock_fsspec.core.url_to_fs.return_value[0]
+    remove_dir("s3://bucket/dir")
+    fs.rm.assert_called_once_with("s3://bucket/dir", recursive=True)
+
+
+def test_ensure_dir_cloud_is_noop(mock_fsspec: MagicMock) -> None:
+    ensure_dir("s3://bucket/dir")
+    mock_fsspec.open.assert_not_called()
+    mock_fsspec.core.url_to_fs.assert_not_called()
+
+
+def test_path_exists_cloud_uses_fsspec(mock_fsspec: MagicMock) -> None:
+    fs = mock_fsspec.core.url_to_fs.return_value[0]
+    fs.exists.return_value = True
+    assert path_exists("s3://bucket/key") is True
+    fs.exists.assert_called_once_with("s3://bucket/key")
+
+
+def test_mixed_copy_local_to_cloud_uses_fsspec(mock_fsspec: MagicMock) -> None:
+    copy_file("/local/file", "s3://bucket/file")
+    mock_fsspec.copy.assert_called_once_with("/local/file", "s3://bucket/file")
diff --git a/uv.lock b/uv.lock
index 998e4bb..8fd3b1f 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,11 +1,195 @@
 version = 1
-revision = 3
+revision = 2
 requires-python = ">=3.11"
 resolution-markers = [
-    "python_full_version >= '3.12'",
+    "python_full_version >= '3.14'",
+    "python_full_version == '3.13.*'",
+    "python_full_version == '3.12.*'",
     "python_full_version < '3.12'",
 ]
 
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+]
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