^{created by @zudsniper with various LLM & Chat Agent Models}

calcsv.py - Classify and analyze CSV transactions.

• Fix the MarkDown table formatting for stat_log.md

• Add more classifiers (AI, Hybrid)

• Support 'export to Google Sheets, Excel'

• Sort transactions by amount, date ⭐

  • Add --sort|-s <date|amount> <+-> flag to specify sort order & direction

• Add 'learning' mode to allow user to classify transactions and save to static_classes.json

• Add 'interactive' mode to allow user to classify transactions and save to static_classes.json

  • Add -y flag to skip all interactivity

• GENERATE A BUDGET FROM TRANSACTION STATISTICAL ANALYSIS & GUIDED USER INPUT WORKFLOW ⭐⭐⭐

python calcsv-pre41.py <filepath> [-f <format> | --format <format>] [-c <classifier> | --classifier <classifier>]

calcsv.py is a tool to parse, classify, and analyze transactions from a CSV file. It supports various CSV formats and classification methods.

• filepath
  Path to the CSV file. (Required)

• -f, --format format
  Specifies the format of the CSV file. Default is "date,amount,*,,description".

• -c, --classifier classifier
  Specifies the classification method. Choices are "normal", "ai", and "hybrid". Default is "normal".

1. Default Usage

   python calcsv-pre41.py transactions.csv

2. Specify CSV Format

   python calcsv-pre41.py transactions.csv --format "date,amount,description"

3. Using AI Classifier

   python calcsv-pre41.py transactions.csv --classifier ai

• static_classes.json
  JSON file containing static classification rules.

• stat_log.md
  Markdown file where statistics are optionally appended.

+----------------+
|                |
|     WINDOW     |
|                |
+----------------+

• AI Classifier: Implement a machine learning model to classify transactions based on patterns and historical data.
• Hybrid Classifier: Combine the rules-based approach of the "normal" classifier with the predictive power of the AI classifier to achieve more accurate classifications.
• Enhanced UI: Develop a graphical user interface for easier interaction and visualization of transaction data.
• Integration with Financial Platforms: Allow direct import of transaction data from popular financial platforms and banks.

Written by @zudsniper.

Report bugs to [email protected].

Copyright © 2023 Jason McElhenney. All rights reserved.