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Initialize FIX message parser and execution break simulator
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‎.github/workflows/ci.yml‎

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name: FIX Parser CI
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on:
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push:
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branches: ["main"]
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pull_request:
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branches: ["main"]
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jobs:
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test:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python-version: ["3.10", "3.11", "3.12"]
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steps:
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- name: Check out repository
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uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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cache: "pip"
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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python -m pip install -r requirements.txt
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- name: Run tests
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run: pytest
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- name: Run end-to-end sample pipeline
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run: make run

‎.gitignore‎

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.venv/
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__pycache__/
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*.pyc
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.pytest_cache/
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.coverage
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htmlcov/
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*.db
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*.sqlite
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.DS_Store

‎Makefile‎

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PYTHONPATH := src
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.PHONY: setup generate parse load reconcile test run clean
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setup:
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python -m pip install --upgrade pip
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python -m pip install -r requirements.txt
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generate:
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PYTHONPATH=$(PYTHONPATH) python -m fixops.generate_sample_data
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parse:
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PYTHONPATH=$(PYTHONPATH) python -m fixops.fix_parser
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load:
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PYTHONPATH=$(PYTHONPATH) python -m fixops.load_db
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reconcile:
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PYTHONPATH=$(PYTHONPATH) python -m fixops.reconcile
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test:
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pytest
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run: generate parse load reconcile
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clean:
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rm -f db/*.db
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rm -f data/generated/*.csv
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rm -f reports/exceptions/*.csv

‎PROJECT_SCOPE.md‎

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# Project Scope
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## Project Name
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FIX Message Parser & Execution Break Simulator
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## Goal
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Build a realistic, recruiter-ready project that demonstrates trading operations, FIX message review, execution support, SQL reconciliation, exception reporting, and production-support thinking using only simulated data.
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## What This Project Demonstrates
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- Parsing simulated FIX execution reports from tag-value messages.
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- Translating core FIX tags into structured columns.
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- Understanding basic order lifecycle states: New, Partially Filled, Filled, Rejected, and open/stale orders.
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- Comparing internal order records, FIX execution reports, broker drop-copy records, and expected order-state records.
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- Detecting execution breaks with SQL controls.
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- Producing CSV exception reports for investigation.
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- Documenting operational triage steps in a runbook.
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- Validating parser/reconciliation logic with pytest and GitHub Actions.
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## What This Project Does Not Claim
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This project does **not** claim professional experience with:
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- Real broker connectivity
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- Real FIX sessions
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- OMS or EMS administration
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- Hedge fund trading-desk systems
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- Proprietary trading data
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- Production trading infrastructure
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All messages and datasets are simulated for educational and portfolio use.
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## Intended Audience
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- Trading Operations Associate recruiters
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- Trade Support hiring managers
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- Production Support interviewers
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- Execution Operations teams
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- Entry-level systematic trading / hedge fund operations teams
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## Technical Stack
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- Python
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- pandas
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- SQL
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- SQLite
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- CSV
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- pytest
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- GitHub Actions
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## MVP Scope
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The MVP focuses on batch-style parsing and reconciliation. It does not implement live FIX connectivity, real-time streaming, message sequencing, or order routing.
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## Future Enhancements
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- Add resend / sequence-gap simulation.
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- Add cancel and cancel/replace workflows.
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- Add allocation-level reconciliation.
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- Add dashboard summary report.
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- Add severity classification and SLA aging.
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- Add CLI flags for report dates and threshold configuration.

‎README.md‎

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# FIX Message Parser & Execution Break Simulator
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![FIX Parser CI](https://github.com/YOUR_USERNAME/fix-message-parser-execution-break-simulator/actions/workflows/ci.yml/badge.svg)
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A recruiter-ready trading operations portfolio project that parses simulated FIX execution-report messages, reconciles them against internal order records and broker drop-copy-style records, and generates exception reports for trade support investigation.
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> **Important:** All data in this repository is simulated. This project does not use real broker, OMS, EMS, hedge fund, client, exchange, or proprietary trading data.
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## Why This Project Exists
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Trading Operations, Trade Support, and Production Support teams often investigate issues such as missing execution reports, stale orders, rejected orders, broker discrepancies, duplicate execution IDs, and order-state breaks.
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This project demonstrates those workflows in a student-accessible way using Python, SQL, SQLite, pandas, CSV files, pytest, and GitHub Actions.
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## What the Project Demonstrates
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- Parse simulated FIX tag-value execution reports.
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- Convert raw FIX messages into structured CSV rows.
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- Understand core order lifecycle states: New, Partially Filled, Filled, Rejected, and stale/open.
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- Reconcile internal orders, FIX reports, broker drop-copy records, and expected order states.
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- Detect common trade support exceptions using SQL.
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- Generate CSV exception reports for investigation.
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- Maintain a simple operational runbook.
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- Validate parser and reconciliation behavior with automated tests and CI.
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## Core FIX Concepts Used
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FIX messages are commonly represented as tag-value pairs. For readability, this project uses the pipe character `|` as the delimiter in sample files. Real FIX messages typically use the SOH delimiter.
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Example simulated execution report:
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```text
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8=FIX.4.2|35=8|49=BROKER1|56=CLIENT1|34=2|52=2026-06-14 09:30:07|37=B-1001|11=ORD-1001|17=E-1001-F1|150=1|39=1|55=AAPL|54=1|38=1000|32=400|31=190.2200|151=600|14=400|6=190.2200|10=002|
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```
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| Tag | Field | Meaning in this project |
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|---:|---|---|
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| 35 | MsgType | Message type. `35=8` means Execution Report. |
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| 11 | ClOrdID | Client order ID from the internal system. |
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| 37 | OrderID | Broker-assigned order ID. |
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| 17 | ExecID | Broker execution identifier. Should be unique per execution event. |
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| 150 | ExecType | Event type, such as New, Partial Fill, Fill, or Reject. |
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| 39 | OrdStatus | Current order status after the event. |
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| 55 | Symbol | Instrument ticker in this simulation. |
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| 54 | Side | `1=BUY`, `2=SELL`. |
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| 38 | OrderQty | Original order quantity. |
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| 32 | LastQty | Quantity executed on the current execution report. |
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| 31 | LastPx | Price for the current execution. |
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| 151 | LeavesQty | Remaining open quantity. |
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| 14 | CumQty | Cumulative executed quantity. |
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| 6 | AvgPx | Average execution price so far. |
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## Repository Structure
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```text
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.
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├── .github/workflows/ci.yml
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├── data/
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│ ├── raw/fix_messages.txt
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│ ├── input/internal_orders.csv
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│ ├── input/broker_drop_copy.csv
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│ ├── input/expected_order_states.csv
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│ └── generated/fix_execution_reports.csv
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├── db/
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├── reports/exceptions/
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├── sql/
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│ ├── schema.sql
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│ └── reconciliation_queries.sql
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├── src/fixops/
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│ ├── config.py
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│ ├── fix_parser.py
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│ ├── generate_sample_data.py
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│ ├── load_db.py
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│ └── reconcile.py
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├── tests/
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│ ├── test_parser.py
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│ └── test_reconciliation.py
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├── PROJECT_SCOPE.md
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├── RUNBOOK.md
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├── Makefile
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├── pyproject.toml
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└── requirements.txt
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```
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## Data Files
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| File | Purpose |
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|---|---|
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| `data/raw/fix_messages.txt` | Raw simulated FIX execution-report messages. |
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| `data/input/internal_orders.csv` | Internal order records from a simulated order-management source. |
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| `data/generated/fix_execution_reports.csv` | Parsed structured output from the FIX parser. |
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| `data/input/broker_drop_copy.csv` | Broker/drop-copy-style execution data. |
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| `data/input/expected_order_states.csv` | Expected final order states used for status reconciliation. |
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## Reconciliation Controls
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The project generates separate CSV reports for:
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1. Missing execution report
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2. Missing broker drop copy
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3. Rejected order
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4. Stale open order
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5. Quantity mismatch
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6. Price mismatch
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7. Side mismatch
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8. Symbol mismatch
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9. Order status mismatch
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10. Duplicate ExecID
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11. Unexpected fill
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12. CumQty / LeavesQty inconsistency
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Reports are written to:
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```text
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reports/exceptions/
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```
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## Quickstart
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```bash
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python -m venv .venv
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source .venv/bin/activate # Windows PowerShell: .venv\Scripts\Activate.ps1
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python -m pip install -r requirements.txt
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make run
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```
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Or run each step manually:
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```bash
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python -m fixops.generate_sample_data
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python -m fixops.fix_parser
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python -m fixops.load_db
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python -m fixops.reconcile
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```
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Expected terminal output from reconciliation:
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```text
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Reconciliation complete. Exception report counts:
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- missing_execution_report: 1
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- missing_broker_drop_copy: 1
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- rejected_order: 1
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- stale_open_order: 3
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- quantity_mismatch: 1
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- price_mismatch: 1
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- side_mismatch: 1
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- symbol_mismatch: 1
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- order_status_mismatch: 2
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- duplicate_exec_id: 1
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- unexpected_fill: 1
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- cumqty_leavesqty_inconsistency: 1
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```
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## Run Tests
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```bash
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pytest
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```
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GitHub Actions runs tests on Python 3.10, 3.11, and 3.12 and also runs the end-to-end sample pipeline.
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## Example Exception Report
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`reports/exceptions/duplicate_exec_id.csv`
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| exec_id | duplicate_count | cl_ord_ids | exception_reason |
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|---|---:|---|---|
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| E-DUP-900 | 2 | ORD-1009, ORD-1009 | Same ExecID appears multiple times in the FIX execution-report stream |
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## How I Would Explain This in an Interview
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I built a simulated trade-support workflow that parses FIX-style execution reports, normalizes important tags like `ClOrdID`, `OrderID`, `ExecID`, `ExecType`, `OrdStatus`, `LastQty`, `LeavesQty`, `CumQty`, and `AvgPx`, and reconciles the parsed messages against internal order records, broker drop-copy records, and expected order states.
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The goal was to demonstrate how a trading operations or production support analyst investigates execution breaks: missing acknowledgements, rejected orders, stale open orders, broker mismatches, duplicate execution IDs, unexpected fills, and invalid order-state math. I intentionally used simulated data and lightweight tools—Python, pandas, SQLite, SQL, pytest, and GitHub Actions—so the logic is transparent and easy to validate.
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## Truthful Resume Bullets
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- Built a simulated FIX execution-report parser in Python to normalize tag-value messages into structured CSV records for order lifecycle analysis.
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- Designed SQLite reconciliation controls to compare internal orders, parsed FIX reports, broker drop-copy-style data, and expected order states.
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- Implemented exception detection for missing execution reports, missing broker drop copies, rejects, stale open orders, field mismatches, duplicate ExecIDs, unexpected fills, and invalid `CumQty` / `LeavesQty` states.
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- Created pytest coverage and GitHub Actions CI to validate parser behavior and run an end-to-end reconciliation pipeline.
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- Wrote operational runbook documentation explaining investigation steps, severity classification, and escalation logic for simulated trade-support breaks.
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## Suggested Commit Sequence
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1. `Initialize project structure and documentation`
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2. `Add simulated order and broker datasets`
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3. `Implement FIX execution report parser`
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4. `Add SQLite schema and database loader`
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5. `Implement reconciliation controls and exception exports`
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6. `Add parser and reconciliation tests`
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7. `Add GitHub Actions CI workflow`
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8. `Expand README with runbook, interview notes, and resume bullets`
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## Disclaimer
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This repository is a portfolio simulation. It does not connect to a live FIX session, broker, OMS, EMS, execution venue, hedge fund system, or trading database.

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