semvec/pypi-packages huggingface dataset:
batch-traceability-mock-recall 0.1.1
Batch traceability and mock recall CLI tool (one step back / one step forward)
License: MIT
Requires Python: >=3.10

\## Author \& Acknowledgment

This project was developed by the repository owner.



An AI-based assistant was used as a learning and productivity support tool

to refine the project structure, improve code quality, and align the solution

with regulatory and audit-oriented best practices.



\## Integration with Data Integrity (ALCOA+)



This project is designed to operate \*\*after data integrity validation\*\*.



Before executing any traceability analysis or mock recall, datasets

(e.g. production, batches, shipments) should be validated against

\*\*ALCOA+ data integrity principles\*\* to ensure they are:



\- Attributable

\- Legible

\- Contemporaneous

\- Original

\- Accurate

\- Complete

\- Consistent

\- Enduring

\- Available



An external \*\*ALCOA+ Checker\*\* can be used as a validation gate.

If critical data integrity violations are detected, the mock recall

should not be executed, as traceability results would not be reliable.



This separation reflects real-world QA system design, where data

integrity validation and operational analytics are independent but

logically connected processes.



\## Example Workflow



1\. Execute ALCOA+ data integrity checks on operational datasets

2\. Review and resolve any critical violations

3\. Approve datasets for operational use

4\. Execute batch traceability and mock recall

5\. Generate recall evidence and KPIs





#
master-of-secrets 0.1.1
Cryptographically secure Password Generator
License: MIT
Requires Python: >=3.9
Keywords: cli, cryptography, generator, password, security

# The Master of Secrets - Password Generator

A Python-based secure password generator that creates strong 20-character passwords and calculates their cryptographic strength.

## Features

- Uses Python's `secrets` module for cryptographically strong random passwords
- Passwords include uppercase letters, lowercase letters, digits, and special characters
- Computes the Shannon entropy of generated passwords to measure randomness
- Estimates how long it would take to crack the password (assuming 1 billion guesses per second)

## Requirements

- Python 3.9 (minimum)
- NumPy
- SciPy

## Installation

Install the required dependencies:

```bash
pip install master-of-secrets
```

## Usage

Run the script:

```bash
secure-me
```

When prompted, type "Yes" to generate a password or "No" to exit:

```
Greetings, The Master of Secrets is at your service!
Would you like to know a secret? (Yes/No): Yes
```

Example output:

```
Password: K9#mP$2xL@4rT&8vN!1q
Estimated crack time: 3.27e+02 years
```

## How It Works

1. Creates a 20-character password using a combination of ASCII letters, digits, and punctuation marks
2. Analyzes the character distribution in the password to calculate its Shannon entropy
3. Estimates the time required to crack the password based on the entropy, assuming an attacker can make 1 billion guesses per second

## Note

The crack time estimation is based on the character distribution entropy of the specific generated password, not the theoretical password space. For a truly random 20-character password from the full character set, the theoretical entropy would be higher.

## Author

Monish Giani (thelazybastard)


## License

MIT Licence