MaxCleanerDB 3.0.5

easy to set up alternative to SQl, bugs and leak proof by design and also support multiple console interactions

A Bug/Leakage Prevention and File Management System.

A lightweight, dependency-free Python module for managing structured text-based data with validation, backup, and recovery features. Ideal for small-scale data storage, prototypes, or personal tools that need structure without the overhead of a full database.

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🚀 Features

• ✅ Safe read/write with structure validation (1D & 2D lists)
• ➕ Append support with consistency checks
• ❌ Granular delete with filters (cutoff, keep, reverse, size)
• 💾 Backup and 📸 Snapshot support
• 🧹 Debug and auto-clean corrupted files
• 📚 Built-in mini-guide
• 🎗️ Supports Multiple Console usage
• 🗂️ Clean folder/files organization.
• 💪 Strong anti-corruption and Tamper mechanism

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Why Use This Package?

• a data tool for web-scraping and real-time dashboard.
• perfect for quick prototyping, automation, or lightweight apps.
• Zero setup overhead — no SQL, no migrations, just plain text files.
• Built-in concurrency and validation — reduce bugs and data corruption.
• Auto-debugging — self-healing files to avoid downtime.
• Ideal for web scraping, automation pipelines, and small apps where a full database is overkill.

📦 Core Functions

w(txt_name: str, write_list: list) -> None

Write (or reset) the contents of a file, validating structure before saving to all backup locations.

r(txt_name: str, set_new: list | None = [], notify_new: bool = True) -> list | None

Read file contents. If the file is missing, return set_new and optionally notify user of new file creation.

a(txt_name: str, append_list: list) -> list

Append new rows to an existing file after validating structure. Returns the updated list.

d(txt_name: str, ...) -> tuple[int, list]

Delete matching rows with flexible options:

• del_list: values to delete
• index: column index for 2D deletion
• cutoff: max deletions per value
• keep: retain only N per value
• reverse: delete from end
• size: trim to max N items

backup(txt_name: str, display=True)

Create a manual backup of a file or all (txt_name="*").

snapshot(txt_name: str, unit, gap, begin=0, display=True)

Take time-based snapshots if eligible. Supports:

• unit: 'minute', 'hour', 'day', 'month', etc.
• gap: how much time must pass
• begin: used for daily-based triggers

debug(txt_name, is_2D=None, clean=None, length=None, display=True)

Scan and optionally auto-clean a file that fails validation. Great for corrupted data recovery.

help()

Opens the interactive mini-guide documentation tool.

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📁 File Organization

Each file is saved as a .txt in a structured folder. All backups and snapshots are handled automatically.

Other folders:

• Backup 💾/ – Manual backups
• Snapshot 📸/ – A timed backup

Validation files:

• *_validation.txt – Schema registry per file

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Usage Examples

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Write (w): Overwrite data

• w("students", ["Alice", "Bob"]) Overwrites the file "students" with a 1D list.

• w("scores", [[1, "Math", 80], [2, "Science", 90]]) Overwrites the file "scores" with a 2D list.

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Read (r): Read data, or set new if missing

• r("students") Reads the content of "students".

• r("new_file", [], notify_new=True) If "new_file" doesn't exist, sets it with an empty list and optionally notifies.

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Append (a): Add new entries

• a("students", ["Charlie"]) Appends "Charlie" to the 1D list "students".

• a("scores", [[3, "English", 85], [4, "Math", 75]]) Appends rows to the 2D list "scores".

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Delete (d): Various modes

Delete by value in 1D:

• d("students", ["Bob"]) Deletes "Bob" from the list.

Multi-row delete in 1D:

• d("students", ["Bob", "Charlie"]) Deletes both "Bob" and "Charlie" if found.

Delete by value in 2D:

• d("scores", [2], index=0) Deletes rows where the first element (ID) is 2.

• d("scores", ["Math"], index=1, cutoff=1) Deletes only the first occurrence where subject is "Math".

• d("scores", ["Math"], index=1, keep=1) Keeps only one row with subject "Math", deletes the rest.

• d("scores", size=2) Trims the list to the last 2 entries.

• d("scores", ["English"], index=1, reverse=True) Deletes rows with "English" in reverse order (from last to first).

Multi-index delete (like SQL WHERE conditions):

• d("scores", [[2, "Science"]], index=[0, 1]) Deletes rows where ID is 2 and subject is "Science".

• d("scores", [[1, "Math", 80]], index=[0, 1, 2]) or index="*" Deletes the exact row [1, "Math", 80].

OR condition with multi-index matching:

• d("scores", [[1, 80], [4, 75]], index=[0, 2]) Deletes rows where (ID is 1 and score is 80) OR (ID is 4 and score is 75).

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Backup and Snapshot

• backup("students") Manually backs up the "students" file.

• backup("*") Backs up all files.

• snapshot("students", "day", 1) Creates a snapshot of "students" if a day has passed.

• snapshot("*", "hour", 6) Snapshots all files every 6 hours.

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Debugging

• debug("students", is_2D=False, clean=True) Cleans and checks 1D data in "students".

• debug("scores", is_2D=True, length=3) Checks 2D data in "scores" for correct 3-column format.

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Help

• help() Displays the usage guide.

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