SSI Validation Automation Project (Python + SQL)

What this project does:
This project reads trade data and Standing Settlement Instructions (SSIs), validates them for missing or incorrect records, and outputs a clean report showing any mismatches or format issues.

This is my first Python + SQL automation project.

It is designed to show: How trade and SSI data can be read, validated, and reported How Python and SQL can be used together to automate real-world data checks A basic simulation of how actual securities operations handle instruction mismatches

Clone-and-run tested: This project has been tested by cloning the repository and running all scripts in sequence from a clean environment. Employers can reproduce the results by running the scripts in the listed order, no additional setup required.

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Technologies Used

• Python
• pandas (for data analysis)
• SQLite (for database storage and SQL queries)
• VS Code + Terminal (to run the scripts)

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File Structure

 ``` scripts/ ├── validate_ssi.py # Reads CSVs, merges, validates, outputs issues ├── load_to_db.py # Loads CSVs into SQLite database ├── read_from_db.py # Reads from DB using SQL ├── validate_from_db.py # Full validation using SQL + Python ├── save_validated_to_db.py # Saves validated results back to DB ├── query_invalid_ssis.py # SQL query for only invalid SSIs ├── trades.csv # Sample trade data ├── ssi_master.csv # Reference SSI data ├── validated_trades.csv # Output file with results ssi_data.db # SQLite database file (auto-created) LICENSE # License file README.md # You are here ``` 

How to Run the Scripts

You can run each file in the terminal like this:

python scripts/validate_ssi.py
python scripts/load_to_db.py
python scripts/read_from_db.py
python scripts/validate_from_db.py
python scripts/save_validated_to_db.py
python scripts/query_invalid_ssis.py
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How to Test the Output

python scripts/query_invalid_ssis.py

  TradeID   Security  Amount   SSI  Valid_SSI_Format
0    T3       TSLA     3000  None                 0

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## SQL automation project.

This is my first Python + SQL automation project.

It is designed to show:
- How trade and SSI data can be read, validated, and reported
- How Python and SQL can be used together to automate real-world data checks
- A basic simulation of how actual securities operations handle instruction mismatches

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