Votre modèle de données Lead to Cash

const axios = require('axios');
const { Parser } = require('json2csv');
const fs = require('fs');

// --- Configuration --- //
const ORACLE_CX_HOST = 'https://[your-oracle-cx-cloud-host].fa.us2.oraclecloud.com';
const CLIENT_ID = '[Your Client ID]';
const CLIENT_SECRET = '[Your Client Secret]';
const START_DATE = '2023-01-01'; // YYYY-MM-DD
const END_DATE = '2023-06-30'; // YYYY-MM-DD
const PAGE_LIMIT = 500;
// --- End Configuration --- //

const tokenUrl = `${ORACLE_CX_HOST}/fscmRestApi/tokenrelay`;
const opportunitiesUrl = `${ORACLE_CX_HOST}/salesApi/resources/latest/opportunities`;

const getAuthToken = async () => {
    try {
        const response = await axios.post(tokenUrl, 'grant_type=client_credentials', {
            headers: {
                'Content-Type': 'application/x-www-form-urlencoded',
                'Authorization': `Basic ${Buffer.from(`${CLIENT_ID}:${CLIENT_SECRET}`).toString('base64')}`
            }
        });
        console.log('Successfully obtained authentication token.');
        return response.data.access_token;
    } catch (error) {
        console.error('Error fetching auth token:', error.response ? error.response.data : error.message);
        throw new Error('Authentication failed.');
    }
};

const fetchAllOpportunities = async (token) => {
    let allOpportunities = [];
    let hasMore = true;
    let offset = 0;

    console.log(`Fetching opportunities updated between ${START_DATE} and ${END_DATE}...`);

    while (hasMore) {
        const params = {
            q: `LastUpdateDate between '${START_DATE}' and '${END_DATE}'`,
            onlyData: true,
            limit: PAGE_LIMIT,
            offset: offset,
            fields: 'OptyId,CreationDate,LastUpdateDate,Name,SalesStage,StatusCode,RevnAmount,OwnerResourcePartyId,PrimaryContactPartyName,LossReasonCode,LeadId,OrganizationName,OptyNumber,OwnerName'
        };

        try {
            const response = await axios.get(opportunitiesUrl, { headers: { Authorization: `Bearer ${token}` }, params });
            const opportunities = response.data.items;
            if (opportunities && opportunities.length > 0) {
                allOpportunities.push(...opportunities);
                offset += opportunities.length;
                console.log(`Fetched ${opportunities.length} opportunities, total so far: ${allOpportunities.length}`);
            } else {
                 hasMore = false;
            }
            hasMore = response.data.hasMore;
        } catch (error) {
            console.error(`Error fetching opportunities at offset ${offset}:`, error.response ? error.response.data : error.message);
            hasMore = false; // Stop on error
        }
    }
    return allOpportunities;
};

const fetchQuotesForOpportunity = async (token, optyId) => {
    const quotesUrl = `${opportunitiesUrl}/${optyId}/child/Quote`;
    try {
        const response = await axios.get(quotesUrl, {
            headers: { Authorization: `Bearer ${token}` },
            params: { fields: 'QuoteId,CreationDate,LastUpdateDate,QuoteStatus,QuoteNumber', onlyData: true }
        });
        return response.data.items;
    } catch (error) {
        console.error(`Error fetching quotes for opportunity ${optyId}:`, error.response ? error.response.data : error.message);
        return [];
    }
};

const transformToEventLog = async (token, opportunities) => {
    const eventLog = [];
    const now = new Date().toISOString();

    for (const opp of opportunities) {
        const commonAttributes = {
            SalesOpportunity: opp.OptyNumber,
            SourceSystem: 'Oracle CX Sales',
            LastDataUpdate: now,
            OpportunityValue: opp.RevnAmount,
            SalesStage: opp.SalesStage,
            OpportunityOwner: opp.OwnerName,
            Region: opp.OrganizationName, // Example mapping, adjust as needed
            LossReason: opp.LossReasonCode
        };

        // Activity: Lead Converted To Opportunity
        if (opp.LeadId) {
            eventLog.push({ ...commonAttributes, ActivityName: 'Lead Converted To Opportunity', EventTime: opp.CreationDate });
        }
        
        // Inferred stage-based activities. Using LastUpdateDate as proxy.
        // A more accurate method requires audit trail data which is more complex to extract.
        const stageNumber = parseInt(opp.SalesStage?.split('-')[0], 10);
        if (stageNumber >= 2) {
             eventLog.push({ ...commonAttributes, ActivityName: 'Opportunity Qualified', EventTime: opp.LastUpdateDate });
        }
        if (stageNumber >= 3) {
             eventLog.push({ ...commonAttributes, ActivityName: 'Needs Analysis Completed', EventTime: opp.LastUpdateDate });
        }
        if (stageNumber >= 4) {
             eventLog.push({ ...commonAttributes, ActivityName: 'Solution Proposed', EventTime: opp.LastUpdateDate });
        }

        // Fetch and process quotes
        const quotes = await fetchQuotesForOpportunity(token, opp.OptyId);
        let quoteCreationCount = 0;
        for (const quote of quotes) {
            quoteCreationCount++;
            // Activity: Quote Created
            eventLog.push({ ...commonAttributes, ActivityName: 'Quote Created', EventTime: quote.CreationDate });
            // Activity: Quote Reworked (inferred from second or later quote creation)
            if (quoteCreationCount > 1) {
                 eventLog.push({ ...commonAttributes, ActivityName: 'Quote Reworked', EventTime: quote.CreationDate });
            }
            // Activity: Quote Sent To Customer
            if (['PRESENTED', 'SENT'].includes(quote.QuoteStatus)) {
                 eventLog.push({ ...commonAttributes, ActivityName: 'Quote Sent To Customer', EventTime: quote.LastUpdateDate });
            }
            // Activity: Quote Accepted By Customer
            if (quote.QuoteStatus === 'ACCEPTED') {
                 eventLog.push({ ...commonAttributes, ActivityName: 'Quote Accepted By Customer', EventTime: quote.LastUpdateDate });
            }
        }

        // Final Opportunity Status activities
        if (opp.StatusCode === 'WON') {
            eventLog.push({ ...commonAttributes, ActivityName: 'Opportunity Won', EventTime: opp.LastUpdateDate });
            // Activity: Order Submitted For Fulfillment (inferred from Opportunity Won)
            eventLog.push({ ...commonAttributes, ActivityName: 'Order Submitted For Fulfillment', EventTime: opp.LastUpdateDate });
            
            // Placeholder for events from external systems. Data should be merged from other sources.
            // eventLog.push({ ...commonAttributes, ActivityName: 'Order Fulfilled', EventTime: [Timestamp from ERP] });
            // eventLog.push({ ...commonAttributes, ActivityName: 'Invoice Generated', EventTime: [Timestamp from Financials] });
            // eventLog.push({ ...commonAttributes, ActivityName: 'Payment Received', EventTime: [Timestamp from Financials] });

        } else if (opp.StatusCode === 'LOST') {
            eventLog.push({ ...commonAttributes, ActivityName: 'Opportunity Lost', EventTime: opp.LastUpdateDate });
        }
    }
    return eventLog;
};

const main = async () => {
    try {
        const token = await getAuthToken();
        const opportunities = await fetchAllOpportunities(token);
        console.log(`Total opportunities to process: ${opportunities.length}`);

        if (opportunities.length > 0) {
            console.log('Transforming data into event log...');
            const eventLog = await transformToEventLog(token, opportunities);
            console.log(`Generated ${eventLog.length} event records.`);
            
            const parser = new Parser();
            const csv = parser.parse(eventLog);
            fs.writeFileSync('oracle_cx_sales_event_log.csv', csv);
            console.log('Event log saved to oracle_cx_sales_event_log.csv');
        }
    } catch (error) {
        console.error('An error occurred during the extraction process:', error.message);
    }
};

main();

import requests
import pandas as pd
from requests.auth import HTTPBasicAuth
import datetime

class=class="hl-string">"hl-comment"># --- Configuration Settings ---
class=class="hl-string">"hl-comment"># Replace with your Oracle CX Sales domain, username, and password
ORACLE_CX_DOMAIN = class="hl-string">"https://[your-pod-name].fa.em2.oraclecloud.com"
USERNAME = class="hl-string">"[Your_API_Username]"
PASSWORD = class="hl-string">"[Your_API_Password]"

class=class="hl-string">"hl-comment"># Define the date range for the extraction (YYYY-MM-DD format)
START_DATE = class="hl-string">"2023-01-01"
END_DATE = class="hl-string">"2023-12-31"

class=class="hl-string">"hl-comment"># --- Helper Function for API Calls ---
def fetch_all_pages(endpoint, q_filter):
    all_items = []
    url = fclass="hl-string">"{ORACLE_CX_DOMAIN}/salesApi/resources/latest/{endpoint}"
    params = {
        class="hl-string">'q': q_filter,
        class="hl-string">'onlyData': class="hl-string">'true',
        class="hl-string">'limit': 100, class=class="hl-string">"hl-comment"># Max records per page
        class="hl-string">'offset': 0
    }
    
    while True:
        try:
            response = requests.get(url, auth=HTTPBasicAuth(USERNAME, PASSWORD), params=params)
            response.raise_for_status()
            data = response.json()
            items = data.get(class="hl-string">'items', [])
            if not items:
                break
            all_items.extend(items)
            if data.get(class="hl-string">'hasMore', False):
                params[class="hl-string">'offset'] += params[class="hl-string">'limit']
            else:
                break
        except requests.exceptions.RequestException as e:
            print(fclass="hl-string">"Error fetching {url}: {e}")
            break
    return all_items

class=class="hl-string">"hl-comment"># --- Placeholder Functions for External Systems ---
def get_order_data_from_erp(opportunity_ids):
    class=class="hl-string">"hl-comment"># CRITICAL: Replace this with actual API calls to your ERP system.
    class=class="hl-string">"hl-comment"># This function should return a list of dictionaries.
    class=class="hl-string">"hl-comment"># Each dictionary should have class="hl-string">'OptyId', class="hl-string">'EventTime', class="hl-string">'ActivityName'.
    print(class="hl-string">"Fetching placeholder Order data from ERP...")
    placeholder_data = []
    class=class="hl-string">"hl-comment"># Example: placeholder_data.append({class="hl-string">'OptyId': 12345, class="hl-string">'EventTime': class="hl-string">'2023-10-25T10:00:00Z', class="hl-string">'ActivityName': class="hl-string">'Order Submitted For Fulfillment'})
    class=class="hl-string">"hl-comment"># Example: placeholder_data.append({class="hl-string">'OptyId': 12345, class="hl-string">'EventTime': class="hl-string">'2023-10-28T14:00:00Z', class="hl-string">'ActivityName': class="hl-string">'Order Fulfilled'})
    return placeholder_data

def get_invoice_data_from_finance(opportunity_ids):
    class=class="hl-string">"hl-comment"># CRITICAL: Replace this with actual API calls to your financial system.
    print(class="hl-string">"Fetching placeholder Invoice data...")
    return [] class=class="hl-string">"hl-comment"># Example: [{class="hl-string">'OptyId': 12345, class="hl-string">'EventTime': class="hl-string">'2023-10-29T11:00:00Z', class="hl-string">'ActivityName': class="hl-string">'Invoice Generated'}]

def get_payment_data_from_finance(opportunity_ids):
    class=class="hl-string">"hl-comment"># CRITICAL: Replace this with actual API calls to your financial system.
    print(class="hl-string">"Fetching placeholder Payment data...")
    return [] class=class="hl-string">"hl-comment"># Example: [{class="hl-string">'OptyId': 12345, class="hl-string">'EventTime': class="hl-string">'2023-11-15T09:30:00Z', class="hl-string">'ActivityName': class="hl-string">'Payment Received'}]


class=class="hl-string">"hl-comment"># --- Main Extraction Logic ---
print(class="hl-string">"Starting Lead to Cash extraction...")

class=class="hl-string">"hl-comment"># 1. Fetch all relevant opportunities within the date range
date_filter = fclass="hl-string">"LastUpdateDate between '{START_DATE}' and '{END_DATE}'"
opportunities = fetch_all_pages(class="hl-string">'opportunities', date_filter)

if not opportunities:
    print(class="hl-string">"No opportunities found for the given date range. Exiting.")
    exit()

print(fclass="hl-string">"Found {len(opportunities)} opportunities to process.")
opp_ids = [opp[class="hl-string">'OptyId'] for opp in opportunities]

class=class="hl-string">"hl-comment"># DataFrame to hold all events
event_log_df = pd.DataFrame()

class=class="hl-string">"hl-comment"># 2. Extract activities from Opportunity and related objects
all_events = []

for opp in opportunities:
    opp_id = opp[class="hl-string">'OptyId']
    last_update = datetime.datetime.now().isoformat()

    base_attributes = {
        class="hl-string">'SalesOpportunity': opp_id,
        class="hl-string">'OpportunityValue': opp.get(class="hl-string">'Revenue'),
        class="hl-string">'SalesStage': opp.get(class="hl-string">'SalesStage'),
        class="hl-string">'OpportunityOwner': opp.get(class="hl-string">'OwnerResourcePartyName'),
        class="hl-string">'Region': opp.get(class="hl-string">'TerritoryName_c'), class=class="hl-string">"hl-comment"># Example custom field
        class="hl-string">'LossReason': opp.get(class="hl-string">'ReasonWonLostCode'),
        class="hl-string">'SourceSystem': class="hl-string">'Oracle CX Sales',
        class="hl-string">'LastDataUpdate': last_update
    }
    
    class=class="hl-string">"hl-comment"># Activity: Lead Converted To Opportunity (inference)
    if opp.get(class="hl-string">'PrimaryContactEmailAddress') and opp.get(class="hl-string">'SalesMethod') != class="hl-string">'Renewal': class=class="hl-string">"hl-comment"># Heuristic for lead-based opportunities
        all_events.append({**base_attributes, class="hl-string">'ActivityName': class="hl-string">'Lead Converted To Opportunity', class="hl-string">'EventTime': opp.get(class="hl-string">'CreationDate')})
        
    class=class="hl-string">"hl-comment"># Activities from Sales Stage history
    stage_history = opp.get(class="hl-string">'ChildSalesStage', [])
    for stage in stage_history:
        stage_name = stage.get(class="hl-string">'SalesStageCode')
        event_time = stage.get(class="hl-string">'LastUpdateDate')
        activity = None
        if stage_name in [class="hl-string">'01-QUALIFICATION', class="hl-string">'QUALIFIED']: activity = class="hl-string">'Opportunity Qualified'
        elif stage_name in [class="hl-string">'02-DISCOVERY', class="hl-string">'ANALYSIS']: activity = class="hl-string">'Needs Analysis Completed'
        elif stage_name in [class="hl-string">'03-PROPOSAL', class="hl-string">'SOLUTION_PROPOSED']: activity = class="hl-string">'Solution Proposed'
        
        if activity:
            all_events.append({**base_attributes, class="hl-string">'ActivityName': activity, class="hl-string">'EventTime': event_time})

    class=class="hl-string">"hl-comment"># Activities: Opportunity Won / Lost
    if opp.get(class="hl-string">'StatusCode') == class="hl-string">'WON':
        all_events.append({**base_attributes, class="hl-string">'ActivityName': class="hl-string">'Opportunity Won', class="hl-string">'EventTime': opp.get(class="hl-string">'LastUpdateDate')})
    elif opp.get(class="hl-string">'StatusCode') == class="hl-string">'LOST':
        all_events.append({**base_attributes, class="hl-string">'ActivityName': class="hl-string">'Opportunity Lost', class="hl-string">'EventTime': opp.get(class="hl-string">'LastUpdateDate')})

    class=class="hl-string">"hl-comment"># Activities from Quotes
    quotes = opp.get(class="hl-string">'ChildQuote', [])
    quote_creation_dates = []
    for quote in quotes:
        quote_creation_dates.append(quote.get(class="hl-string">'CreationDate'))
        all_events.append({**base_attributes, class="hl-string">'ActivityName': class="hl-string">'Quote Created', class="hl-string">'EventTime': quote.get(class="hl-string">'CreationDate')})
        
        class=class="hl-string">"hl-comment"># Infer other quote events from status or custom date fields
        if quote.get(class="hl-string">'QuoteStatus_c') == class="hl-string">'SENT' and quote.get(class="hl-string">'DateSent_c'):
            all_events.append({**base_attributes, class="hl-string">'ActivityName': class="hl-string">'Quote Sent To Customer', class="hl-string">'EventTime': quote.get(class="hl-string">'DateSent_c')})
        if quote.get(class="hl-string">'QuoteStatus_c') == class="hl-string">'ACCEPTED' and quote.get(class="hl-string">'DateAccepted_c'):
            all_events.append({**base_attributes, class="hl-string">'ActivityName': class="hl-string">'Quote Accepted By Customer', class="hl-string">'EventTime': quote.get(class="hl-string">'DateAccepted_c')})
    
    class=class="hl-string">"hl-comment"># Activity: Quote Reworked (inference)
    if len(quote_creation_dates) > 1:
        class=class="hl-string">"hl-comment"># Mark all but the first creation as a rework event
        sorted_dates = sorted(quote_creation_dates)
        for rework_date in sorted_dates[1:]:
            all_events.append({**base_attributes, class="hl-string">'ActivityName': class="hl-string">'Quote Reworked', class="hl-string">'EventTime': rework_date})

class=class="hl-string">"hl-comment"># 3. Add data from external systems
print(class="hl-string">"Fetching data from external systems...")
order_events = get_order_data_from_erp(opp_ids)
invoice_events = get_invoice_data_from_finance(opp_ids)
payment_events = get_payment_data_from_finance(opp_ids)

external_system_events = []
last_update = datetime.datetime.now().isoformat()

for event in order_events + invoice_events + payment_events:
    opp_id = event[class="hl-string">'OptyId']
    class=class="hl-string">"hl-comment"># Find the corresponding opportunity to get base attributes
    opp_data = next((item for item in opportunities if item[class="hl-string">"OptyId"] == opp_id), None)
    if opp_data:
         base_attributes = {
            class="hl-string">'SalesOpportunity': opp_id,
            class="hl-string">'OpportunityValue': opp_data.get(class="hl-string">'Revenue'),
            class="hl-string">'SalesStage': opp_data.get(class="hl-string">'SalesStage'),
            class="hl-string">'OpportunityOwner': opp_data.get(class="hl-string">'OwnerResourcePartyName'),
            class="hl-string">'Region': opp_data.get(class="hl-string">'TerritoryName_c'),
            class="hl-string">'LossReason': opp_data.get(class="hl-string">'ReasonWonLostCode'),
            class="hl-string">'SourceSystem': class="hl-string">'ERP/Finance',
            class="hl-string">'LastDataUpdate': last_update
        }
    else:
        base_attributes = {class="hl-string">'SalesOpportunity': opp_id, class="hl-string">'SourceSystem': class="hl-string">'ERP/Finance', class="hl-string">'LastDataUpdate': last_update}
    
    external_system_events.append({**base_attributes, class="hl-string">'ActivityName': event[class="hl-string">'ActivityName'], class="hl-string">'EventTime': event[class="hl-string">'EventTime']})

all_events.extend(external_system_events)

class=class="hl-string">"hl-comment"># 4. Finalize the DataFrame
if all_events:
    event_log_df = pd.DataFrame(all_events)
    class=class="hl-string">"hl-comment"># Standardize column names
    event_log_df = event_log_df.rename(columns={class="hl-string">'ActivityName': class="hl-string">'ActivityName', class="hl-string">'EventTime': class="hl-string">'EventTime'})
    
    class=class="hl-string">"hl-comment"># Ensure required columns exist
    required_cols = [class="hl-string">'SalesOpportunity', class="hl-string">'ActivityName', class="hl-string">'EventTime', class="hl-string">'SourceSystem', class="hl-string">'LastDataUpdate', class="hl-string">'OpportunityValue', class="hl-string">'SalesStage', class="hl-string">'OpportunityOwner', class="hl-string">'Region', class="hl-string">'LossReason']
    for col in required_cols:
        if col not in event_log_df.columns:
            event_log_df[col] = None
            
    class=class="hl-string">"hl-comment"># Select and order columns
    event_log_df = event_log_df[required_cols]
    
    class=class="hl-string">"hl-comment"># Clean up and sort
    event_log_df = event_log_df.dropna(subset=[class="hl-string">'SalesOpportunity', class="hl-string">'ActivityName', class="hl-string">'EventTime'])
    event_log_df[class="hl-string">'EventTime'] = pd.to_datetime(event_log_df[class="hl-string">'EventTime'])
    event_log_df = event_log_df.sort_values(by=[class="hl-string">'SalesOpportunity', class="hl-string">'EventTime'])
    
    class=class="hl-string">"hl-comment"># Save to CSV
    output_filename = class="hl-string">'lead_to_cash_event_log.csv'
    event_log_df.to_csv(output_filename, index=False, date_format=class="hl-string">'%Y-%m-%dT%H:%M:%S.%fZ')
    print(fclass="hl-string">"Extraction complete. Event log saved to {output_filename}")
else:
    print(class="hl-string">"No events were generated.")