insight/backend/src/dashboard/services/json_reader.py

from pprint import pprint
from collections import defaultdict
import pandas as pd

from enum import Enum
from datetime import datetime

class ProductType(Enum):
    EMPTY_CAVITY_ECO_4 = "Empty Cavity - ECO4"



class jsonReader:
    def __init__(self, json_data):
        self.raw_data = json_data
        self.deals_by_line_item = defaultdict(list)
        self.line_item_names = list
        self.initial_setup()

    def to_date_only(self, timestamp: str) -> str:
        if timestamp is None:
            return None
        if timestamp.endswith("Z"):
            timestamp = timestamp[:-1]
        dt = datetime.strptime(timestamp, "%Y-%m-%dT%H:%M:%S")
        return dt.strftime("%Y-%m-%d")
    
    def initial_setup(self):
        """
        Build a dictionary mapping line item names -> list of deals
        """
        for deal in self.raw_data:
            line_items = deal.get("line_items", [])

            if not line_items:
                # Store empty deals under a special key
                self.deals_by_line_item["__empty__"].append(deal)
                continue

            # Add this deal under each line item name
            for item in line_items:
                name = item.get("name")
                if name:
                    self.deals_by_line_item[name].append(deal)
        self.line_item_names = list(self.deals_by_line_item.keys())

    def generate_df_via_product_type(self, product_type):
        rows = []
        for deals in self.deals_by_line_item[product_type]:
            row = self._return_df_from_deal_info(deals, product_type)
            rows.append(row)

        if rows:
            return pd.concat(rows, ignore_index=True)

    
    def _return_df_from_deal_info(self, deal, product_type):
        rows = []

        if "ECO" in product_type or "EPC" in product_type:
            if deal["attempts"]:
                # Multiple attempts => multiple rows
                for attempt in deal["attempts"]:
                    rows.append({
                        "submission_date": self.to_date_only(deal["deal_properties"].get("submission_date")),
                        "hubspot_id": deal["deal_properties"]["deal_id"],
                        "expected_commencement_date": deal["deal_properties"].get("expected_commencement_date"),
                        "work_type": product_type,
                        "price": next(
                            (item["price"] for item in deal["line_items"] if product_type in item["name"]),
                            None
                        )
                    })
            else:
                def historical_ecd_value_processes(timestamp): 
                    if timestamp is None or timestamp == '': 
                        return None 
                    dt = datetime.strptime(timestamp, "%Y-%m-%d") 
                    return dt.strftime("%Y-%m-%d")
                history = deal["deal_properties"]["expected_commencement_history"]

                # ---- SORT HISTORY: latest first ----
                history_sorted = sorted(
                    history,
                    key=lambda h: datetime.strptime(h["timestamp"].split("T")[0], "%Y-%m-%d"),
                    reverse=True
                )

                # Extract latest expected commencement date
                latest = history_sorted[0]
                latest_ecd = historical_ecd_value_processes(latest["value"])  # returns YYYY-MM-DD or None

                # Convert submission date
                raw_submission_date = deal["deal_properties"].get("last_submission_date")
                submission_date = self.to_date_only(raw_submission_date) if raw_submission_date else None

                # Convert both to datetime for comparison
                if submission_date and latest_ecd:
                    dt_sub = datetime.strptime(submission_date, "%Y-%m-%d")
                    dt_ecd = datetime.strptime(latest_ecd, "%Y-%m-%d")

                    # Only keep submission date if submission_date > latest ECD
                    if dt_sub <= dt_ecd:
                        submission_date = None
                else:
                    submission_date = None

                # 1️⃣ Add latest expected commencement date WITH conditional submission date
                rows.append({
                    "submission_date": submission_date,
                    "expected_commencement_date": latest_ecd,
                    "hubspot_id": deal["deal_properties"]["deal_id"],
                    "work_type": product_type,
                    "price": next(
                        (item["price"] for item in deal["line_items"] if product_type in item["name"]),
                        None
                    )
                })

                # 2️⃣ Add the remaining history WITHOUT submission date
                for attempt in history_sorted[1:]:
                    rows.append({
                        "submission_date": None,
                        "expected_commencement_date": historical_ecd_value_processes(attempt["value"]),
                        "hubspot_id": deal["deal_properties"]["deal_id"],
                        "work_type": product_type,
                        "price": next(
                            (item["price"] for item in deal["line_items"] if product_type in item["name"]),
                            None
                        )
                    })

        # Return a DataFrame or None
        return pd.DataFrame(rows) if rows else None
    
    def find_all_job_with_line_item(self):
        for i, deal in enumerate(self.raw_data):
            if len(deal["line_items"])>0:
                print(deal)
                print(i)
                break

    def print_raw_data(self):
        pprint(self.raw_data)