スキル一覧に戻る
edoannunziata

ftpc-storage

by edoannunziata

TUI client for remote flat-file storage.

0🍴 0📅 2026年1月1日
GitHubで見るManusで実行

SKILL.md


name: ftpc-storage description: Read files from remote storage backends (local, FTP, SFTP, S3, Azure). List directories, download files, inspect metadata. Use for reading data from cloud storage, FTP servers, or remote filesystems without making changes. allowed-tools: Read, Grep, Glob, Bash(python3:*)

FTPC Storage (Read-Only)

Use the ftpc library to read files from various storage backends.

Supported Backends

ProtocolURL FormatExample
Localfile:///path or /path/home/user/data
FTPftp://[user:pass@]host[:port]/pathftp://ftp.example.com/pub
FTPSftps://[user:pass@]host[:port]/pathftps://secure.example.com
SFTPsftp://[user:pass@]host[:port]/pathsftp://user:pass@host/data
S3s3://bucket/paths3://my-bucket/folder
Azure Data Lakeazure://account.dfs.core.windows.net/fs/pathazure://myacct.dfs.core.windows.net/data
Azure Blobblob://account.blob.core.windows.net/container/pathblob://myacct.blob.core.windows.net/files

Quick Start

from ftpc import connect_sync

# Connect using URL and list files
with connect_sync("s3://my-bucket") as store:
    files = store.list("/")
    for f in files:
        print(f"{f.name}  {'DIR' if f.is_directory else f.size}")

Available Operations

List Directory

from ftpc import connect_sync

with connect_sync("ftp://ftp.example.com") as store:
    # List root (base path from URL)
    files = store.list()

    # List specific path
    files = store.list("/documents")

    # Each file is a FileDescriptor with:
    # - name: str (filename only)
    # - path: PurePath (full path)
    # - is_file: bool
    # - is_directory: bool
    # - size: Optional[int] (bytes, None for directories)
    # - modified_time: Optional[datetime]

Download File

from ftpc import connect_sync

with connect_sync("sftp://user:pass@host") as store:
    # Download to local path
    store.download("/remote/file.csv", "local_file.csv")

    # With progress tracking
    def progress(bytes_done: int) -> bool:
        print(f"Downloaded {bytes_done} bytes")
        return True  # Return False to cancel

    store.download("/large_file.zip", "output.zip", progress)

Using Named Remotes from Config

If ~/.ftpcconf.toml exists with configured remotes:

# ~/.ftpcconf.toml
[my-s3]
type = "s3"
bucket = "my-bucket"
region = "us-east-1"

[work-ftp]
type = "ftp"
url = "ftp.company.com"
username = "user"
password = "secret"

Load config and create client:

from ftpc.config import Config
from ftpc.clients.s3client import S3Client

config = Config.from_file()  # Loads ~/.ftpcconf.toml
remote = config.remotes["my-s3"]

# Create client from config (varies by type)
with S3Client(bucket_name=remote.bucket, region_name=remote.region) as client:
    files = client.ls("/")

Async Usage

import asyncio
from ftpc import Storage

async def main():
    async with Storage.connect("s3://bucket") as store:
        files = await store.list("/")
        await store.download("/data.csv", "local.csv")

asyncio.run(main())

Named Constructors (Explicit Configuration)

from ftpc import Storage

# S3 with explicit credentials
with Storage.s3(
    bucket="my-bucket",
    region="us-east-1",
    access_key_id="AKIAIOSFODNN7EXAMPLE",
    secret_access_key="wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY"
).sync() as store:
    files = store.list("/")

# FTP with explicit config
with Storage.ftp(
    host="ftp.example.com",
    username="user",
    password="pass",
    tls=True  # Use FTPS
).sync() as store:
    store.download("/file.txt", "local.txt")

# SFTP with key file
with Storage.sftp(
    host="server.example.com",
    username="deploy",
    key_filename="/home/user/.ssh/id_rsa"
).sync() as store:
    files = store.list("/var/data")

Dependencies

Install required backends:

pip install ftpc            # Core (local + FTP)
pip install ftpc[sftp]      # + SFTP (paramiko)
pip install ftpc[s3]        # + S3 (boto3)
pip install ftpc[azure]     # + Azure (azure-storage-*)
pip install ftpc[all]       # All backends

スコア

総合スコア

60/100

リポジトリの品質指標に基づく評価

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

+10
説明文

100文字以上の説明がある

0/10
人気

GitHub Stars 100以上

0/15
最近の活動

3ヶ月以内に更新がある

0/10
フォーク

10回以上フォークされている

0/5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

0/5

レビュー

💬

レビュー機能は近日公開予定です