finta-local-dev-loop

# Finta Local Dev Loop ## Overview Finta is primarily UI-driven without a public API. For local automation, use CSV exports from Finta combined with Python scripts for analysis, reporting, and integration with other tools. ## Instructions ### Export Pipeline Data 1. In Finta, go to **Pipeline** > **Export** > **CSV** 2. Save as `pipeline-export.csv` ### Analyze Fundraise Pipeline ```python import pandas as pd from datetime import datetime # Load Finta export df = pd.read_csv("pipeline-export.csv") # Pipeline summary summary = df.groupby("Stage").agg( count=("Name", "count"), avg_check=("Check Size", "mean"), ).reset_index() print("Pipeline Summary:") print(summary.to_string(index=False)) # Conversion rates stages = ["Researching", "Reaching Out", "Intro Meeting", "Follow-up", "Due Diligence", "Term Sheet", "Closed"] for i in range(len(stages) - 1): current = len(df[df["Stage"] == stages[i]]) next_stage = len(df[df["Stage"] == stages[i+1]]) rate = (next_stage / current * 100) if current > 0 else 0 print(f" {stages[i]} -> {stages[i+1]}: {rate:.0f}%") ``` ### Weekly Pipeline Report ```python def generate_weekly_report(df: pd.DataFrame) -> str: total = len(df) active = len(df[df["Stage"].isin(["Intro Meeting", "Follow-up", "Due Diligence"])]) term_sheets = len(df[df["Stage"] == "Term Sheet"]) closed = len(df[df["Stage"] == "Closed"]) return f""" Fundraise Pipeline Report ({datetime.now().strftime('%Y-%m-%d')}) ===========...