withopen 6.0.0

A structured and backup-friendly way to manage `.txt` files with multi-console and debugging support.

🧾 WithOpen — "Your code's .txt guide"

A Zero Dependency and Robust structured .txt files file manager for automation, pipelines, and bot-friendly data with confidence.
Replacing 20+ lines of code and logic with a single one-liner.

This project started from a simple frustration:
After writing hundreds of with open(file) as .. lines, building backups, validating structures, and hacking delete filters... I realized I was reinventing the same patterns over and over.

So I made withopen:
A zero-dependency Python utility that treats plain .txt files like structured datasets — safely and scalably.

It’s not a database. It’s a reliable, structured backend for:

• Automations
• Bots
• CLI tools
• Low-overhead microservices

🎯 Key Capabilities

• Structure Enforcement: First write or append defines whether data is 1D or 2D; future data must match.
• CRUD Operations: w() (write), r() (read), a() (append), d() (delete/trim/filter).
• Multi-console safe: Handles concurrent processes to avoid corruption.
• Backups & Snapshots: Automatic and manual backups, plus time-based snapshots.
• Auto Folder Organization: All files, backups, and snapshots are kept in structured folders — no clutter.
• Anti-Tamper Safe Mode: Hidden files and structure-locking help protect against manual edits or file corruption.
• Debug & Recovery: Scan for structural errors and selectively repair.
• Hide / Unhide: Protect files from accidental user tampering.
• Zero dependencies, intuitive API, and minimal setup.

🔑 Core Functions

✅ w() — Write / Overwrite

w(txt_name, write_list, is2d=None)

Parameter	Type	Description
txt_name	str	Name of the file (without extension).
write_list	list	Data to write (1D or 2D list). Overwrites existing content.
is2d	bool or None	Specify structure type on first write or when resetting. Only required if the file is new or empty.

📝 Use [] to reset file structure.

📖 r() — Read

r(txt_name, index=None, set_new=[], notify_new=True)

Parameter	Type	Description
txt_name	str	Name of the file.
index	int, list, or None	Return only data from specific index/column(s).
set_new	list	If file doesn’t exist, create it using this list.
notify_new	bool	Print a message if the file was auto-created. Default: True.

➕ a() — Append

a(txt_name, append_list, is2d=None)

Parameter	Type	Description
txt_name	str	Name of the file.
append_list	list	Data to append (must match existing structure).
is2d	bool or None	Required only for new or empty files.

❌ d() — Delete / Filter / Trim

d(txt_name, del_list=[], index=None, cutoff=None, keep=None, reverse=False, size=None)

Parameter	Type	Description
txt_name	str	Name of the file.
del_list	list or str	Values to match for deletion.
index	int, list, "*" or None	Column(s) to match values in. "*" matches whole row.
cutoff	int	Maximum number of deletions per value.
keep	int	Retain only N matching rows.
reverse	bool	Delete from end instead of top.
size	int	Trim the file to only last N rows.

🧠 You can mix-and-match these for precise cleanup strategies.

⚙️ Installation

pip install withopen

🏃 Example Workflow

import withopen as f

# Write 2D data (first write locks structure)
f.w("tasks", [["Name", "Status"], ["Ping", "Done"], ["Build", "Pending"]])

# Append new row (must match shape)
f.a("tasks", [["Test", "Pending"]])

# Read all rows
print(f.r("tasks"))

# Read specific column or row
print(f.r("tasks", index=1))      # second column across all rows
print(f.r("tasks", index=[0, 2])) # columns 0 and 2

# Delete by matching value
f.d("tasks", del_list=["Done"], index=1)

# Trim to last N rows
f.d("tasks", size=3)

# Backup & snapshot
wo.backup("tasks")
f.snapshot("tasks", unit="h", gap=4)

# Debug / fix structure errors
f.debug("tasks", is2d=True, length=2)

# Hide / unhide
f.hide("tasks")
f.unhide("tasks")

📋 Data Models: 1D & 2D

Mode	Example	Notes
1D	["apple", "banana", "pear"]	Use is2d=False on first write/append
2D	[["user","score"], ["alice",10], ["bob",8]]	Use is2d=True on first write/append

To reset structure (clear file):

f.w("filename", [], is2d=None)

🧹 Deletion & Filtering

d() is versatile. Combine arguments:

• del_list (values or rows)
• index (column index, list of indices, or "*" for full row)
• cutoff (max deletes per value)
• keep (retain only N matches)
• reverse (delete from end)
• size (keep only last N rows)

Examples

Delete rows where status == “Done”:

f.d("tasks", del_list=["Done"], index=1)

Delete a full exact row:

f.d("tasks", del_list=[["Ping","Done"]], index="*")

Trim to last 5 rows:

f.d("tasks", size=5)

Keep only N occurrences of a value:

f.d("tasks", del_list=["Pending"], index=1, keep=2)

🔢 Index Matching Patterns

1. Match by Single Index (Column)

f.d("tasks", del_list=["Pending"], index=1)

Deletes all rows where column 1 (status) is "Pending".

2. Match by Multiple Indexes (Multi-Column Logic)

f.d("tasks", del_list=[["Fix Bug", "High"]], index=[0, 2])

Deletes rows where column 0 = "Fix Bug" and column 2 = "High".

3. Match Entire Row

f.d("tasks", del_list=[["Fix Bug", "Done", "Low"]], index="*")

Deletes exact row match across all columns.

4. Match Multiple Rows by Value in a Column

f.d("tasks", del_list=[["Deploy"], ["Write Docs"]], index=0)

Deletes any row where column 0 (task name) matches "Deploy" or "Write Docs".

5. Selective Cutoff Deletes

f.d("tasks", del_list=["Pending"], index=1, cutoff=2)

Deletes only the first 2 rows where column 1 = "Pending".

6. Reverse Delete

f.d("tasks", del_list=["Done"], index=1, reverse=True)

Deletes from the bottom up, not top-down.

7. Trim by Row Count (No index)

f.d("tasks", size=5)

Keeps only the last 5 rows — trims the rest.

🛠 Debugging & Recovery

When a file's structure is compromised:

debug("tasks", is2d=True, length=2)

• Flags bad rows and optionally cleans them.
• Use majority-vote backups to restore

when corruption occurs.

📁 Backups & Snapshots

• backup("tasks") → manual backup

• snapshot("tasks", unit, gap, trim=None, begin=0) → time-based backup

  • Units: 's', 'm', 'h', 'd', 'mo', 'y'
  • gap: minimum time between snapshots
  • trim: max rows in snapshot

Backups and snapshots are stored in structured subfolders.

🔐 Hide / Unhide Files

• hide("tasks"): prevents accidental edits or reads
• unhide("tasks"): makes file visible again
• Use "*" to hide/unhide all files

🧠 Best Practices

1. Always use the API (w, a, r, d) — avoid manual edits.
2. Run debug() periodically for long-lived files.
3. Use snapshot() in scripts that run continuously.
4. Use hide() when bundling scripts to protect internal files.
5. Reset structure if your shape definition changes (with w("file", [])).

🔧 Utility Functions

🖥️ consoles() — Console Mode Config

f.consoles(txt_name, multiple=True, alert=True)

Sets console interaction mode for:

• Multiple scripts
• Multiple tabs
• Bots and automation tools

Ensures safe concurrent access by coordinating file locks per console context.
Use this when your files are read/written by multiple parallel environments.

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🔕 warning() — Enable or Disable Read Alerts

f.warning(alert=False)

Turns on or off the warning that appears when reading a file outside of console-safe mode.

Useful for bots or CI/CD logs where alerts aren’t needed.

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🗑️ remove(txt_name, display=True)

Deletes the target file along with all backups and snapshots.
⚠️ Use with caution — irreversible.

ℹ️ info(txt_name, display=True)

Returns metadata such as structure type, total rows, shape, and last modified time.

🧪 debug(txt_name, is2d=None, length=None, display=True)

Scans for structure issues like row length mismatches or corrupted lines.
Can auto-fix when used with length or is2d.

📂 listdir(display=True)

Lists all structured text files currently being tracked.

🆘 help()

Prints a quick-reference summary of all available functions and parameters.
Great for in-terminal use.

📄 License

This project is licensed under the MIT License.
Use freely, modify, share — no warranties.