HF Buckets - Mirage

The HF Buckets resource mounts a Hugging Face Bucket at some prefix such as /hf/. Speaks HF’s HTTP API natively (async, streaming, no Python SDK dependency). For credential setup, see HF Buckets Setup.

Config

import os

from mirage import MountMode, Workspace
from mirage.resource.hf_buckets import HfBucketsConfig, HfBucketsResource

config = HfBucketsConfig(
    bucket=os.environ["HF_BUCKET_NAME"],  # "namespace/bucket-name"
    token=os.environ["HF_TOKEN"],
    # Optional:
    # endpoint="https://huggingface.co",
    # timeout=30,
    # key_prefix="data/",
)
resource = HfBucketsResource(config)
ws = Workspace({"/hf": resource}, mode=MountMode.READ)

HfBucketsResource(config) takes an HfBucketsConfig object with the bucket in namespace/bucket-name form plus an optional access token. Both READ and WRITE modes are supported out of the box.

Filesystem Layout

The HF Buckets resource maps bucket object keys to virtual paths under the mount prefix. For example, if bucket your-user/my-data contains:

data/file.txt
data/config.json
reports/q1.csv
reports/q2.csv

Then mounting at /hf/ exposes:

/hf/
  data/
    file.txt
    config.json
  reports/
    q1.csv
    q2.csv

Path mapping: virtual /hf/data/file.txt maps to bucket key data/file.txt.

Cache

The HF Buckets resource uses IndexCacheStore with index_ttl = 600 (10 minutes). Directory listings are cached and populate file-size/type entries that stat reads via a fast path, so a readdir followed by per-entry stat calls (which is what ls, FUSE getattr, and most shell commands trigger) costs one HTTP request instead of N.

Example

import asyncio
import os

from dotenv import load_dotenv

from mirage import MountMode, Workspace
from mirage.resource.hf_buckets import HfBucketsConfig, HfBucketsResource

load_dotenv(".env.development")

config = HfBucketsConfig(
    bucket=os.environ["HF_BUCKET_NAME"],
    token=os.environ["HF_TOKEN"],
)

resource = HfBucketsResource(config)


async def main() -> None:
    ws = Workspace({"/hf/": resource}, mode=MountMode.READ)

    r = await ws.execute("ls /hf/")
    print(await r.stdout_str())

    r = await ws.execute("cat /hf/data/file.txt")
    print(await r.stdout_str())

    r = await ws.execute("tree /hf/")
    print(await r.stdout_str())

    r = await ws.execute("find /hf/ -name '*.json'")
    print(await r.stdout_str())

    r = await ws.execute("grep example /hf/data/config.json")
    print(await r.stdout_str())

    r = await ws.execute("stat /hf/data/file.txt")
    print(await r.stdout_str())


if __name__ == "__main__":
    asyncio.run(main())

Shell Commands

The HF Buckets resource supports the full set of shell commands since it operates on real file content (text, binary, JSON, CSV, etc.). Large files benefit from range reads to avoid downloading entire objects.

Read Commands

Command	Notes
`cat`	Read file content
`head` / `tail`	First/last N lines
`grep` / `rg`	Pattern search (file or directory level)
`jq`	Query JSON fields
`wc`	Line/word/byte counts
`stat`	File metadata (name, size, type, modified)
`find`	Recursive search with `-name`, `-maxdepth`
`tree`	Directory tree view
`nl`	Number lines
`du`	Disk usage summary
`file`	Detect file type
`strings`	Extract printable strings from binary
`xxd`	Hex dump
`md5`	MD5 checksum
`sha256sum`	SHA-256 checksum

Text Processing

Command	Notes
`awk`	Pattern scanning and processing
`sed`	Stream editor
`tr`	Translate or delete characters
`sort`	Sort lines
`uniq`	Remove duplicate lines
`cut`	Extract fields/columns
`join`	Join lines on a common field
`paste`	Merge lines side by side
`column`	Columnate output
`fold`	Wrap lines to a specified width
`expand`	Convert tabs to spaces
`unexpand`	Convert spaces to tabs
`fmt`	Simple text formatter
`rev`	Reverse lines
`tac`	Concatenate and print in reverse
`look`	Display lines beginning with a given string
`shuf`	Shuffle lines
`tsort`	Topological sort
`comm`	Compare two sorted files
`cmp`	Compare two files byte by byte
`diff`	Compare files line by line
`patch`	Apply a diff patch
`iconv`	Character encoding conversion

File Operations

Command	Notes
`cp`	Copy files
`mv`	Move/rename files
`rm`	Remove files
`mkdir`	Create directories
`touch`	Create empty file or update timestamp
`ln`	Create symbolic links
`tee`	Write stdin to file and stdout
`mktemp`	Create temporary file
`split`	Split file into pieces
`csplit`	Split file by context

Path Utilities

Command	Notes
`basename`	Strip directory from path
`dirname`	Strip filename from path
`realpath`	Resolve path
`readlink`	Print symbolic link target
`ls`	List directory contents

Compression

Command	Notes
`gzip`	Compress files
`gunzip`	Decompress gzip files
`zip`	Create zip archives
`unzip`	Extract zip archives
`tar`	Archive files
`zcat`	Cat compressed files
`zgrep`	Grep compressed files

Encoding

Command	Notes
`base64`	Base64 encode/decode

Data Format Support

Commands with format-specific variants for structured data files:

Format	Extension	Variants
Parquet	`.parquet`	cat, head, tail, wc, stat, cut, grep, ls, file
Feather	`.feather`	cat, head, tail, wc, stat, cut, grep, ls, file
ORC	`.orc`	cat, head, tail, wc, stat, cut, grep, ls, file
HDF5	`.hdf5`	cat, head, tail, wc, stat, cut, grep, ls, file

These variants auto-detect the format by extension and convert to tabular text (CSV) for processing.

Use Cases

AI agents accessing HF datasets: Mount HF Buckets for agents to read and process datasets stored on the Hub
Data pipelines: Read and write HF bucket objects with shell-like commands
Sandboxed bucket access: Restrict agent operations to a specific bucket and prefix
FUSE mounting: Expose HF Buckets through a virtual FUSE mount for external tools

Scoping a resource to a key prefix

Pass key_prefix: str | None = None to HfBucketsConfig to transparently scope every operation to a subpath of the bucket:

HfBucketsResource(HfBucketsConfig(
    bucket="your-user/app-data",
    token=hf_token,
    key_prefix=f"users/{user_id}/",
))

When set, every read/write/list/stat operation is transparently scoped to that bucket subpath. Agents see clean paths like /data/notes.md; the underlying bucket key is users/{user_id}/data/notes.md. Useful for multi-tenant systems. Normalization: leading slashes are stripped and a trailing slash is added automatically. Both None and an empty string are treated as “no prefix.”

​Config

​Filesystem Layout

​Cache

​Example

​Shell Commands

​Read Commands

​Text Processing

​File Operations

​Path Utilities

​Compression

​Encoding

​Data Format Support

​Use Cases

​Scoping a resource to a key prefix