Rodrigo Rodriguez (Pragmatismo)
50eae38d36
update and code refactoring focused on: 1. Adding new documentation pages to the table of contents 2. Restructuring the bot templates documentation 3. Changing keyword syntax from underscore format to space format (e.g., `SET_BOT_MEMORY` → `SET BOT MEMORY`) 4. Updating compiler and keyword registration to support the new space-based syntax 5. Adding new keyword modules (social media, lead scoring, templates, etc.) Refactor BASIC keywords to use spaces instead of underscores Change keyword syntax from underscore format (SET_BOT_MEMORY) to more natural space-separated format (SET BOT MEMORY) throughout the codebase. Key changes: - Update Rhai custom syntax registration to use space tokens - Simplify compiler preprocessing (fewer replacements needed) - Update all template .bas files to use new syntax - Expand documentation with consolidated examples and new sections - Add new keyword modules: social_media, lead_scoring, send_template, core_functions, qrcode, sms, procedures, import_export, llm_macros, on_form_submit
195 lines
6.8 KiB
QBasic
195 lines
6.8 KiB
QBasic
' Data Sync Bot - Demonstrates new data operations keywords
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' This template shows how to use MERGE, FILTER, AGGREGATE, JOIN, and other data keywords
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' ============================================================================
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' WEBHOOK: External systems can trigger this sync via HTTP POST
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' Endpoint: /api/office/webhook/data-sync
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' ============================================================================
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WEBHOOK "data-sync"
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TALK "Starting data synchronization..."
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' ============================================================================
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' EXAMPLE 1: Fetch and merge external data
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' ============================================================================
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' Fetch customers from external CRM API
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SET HEADER "Authorization", "Bearer " + GET BOT MEMORY("crm_api_key")
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SET HEADER "Content-Type", "application/json"
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external_customers = GET "https://api.crm.example.com/customers"
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' Merge external data with local database using email as the key
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merge_result = MERGE "customers", external_customers, "email"
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TALK "Customer sync complete: " + merge_result.inserted + " new, " + merge_result.updated + " updated"
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CLEAR HEADERS
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' ============================================================================
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' EXAMPLE 2: Data transformation with MAP and FILL
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' ============================================================================
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' Read raw order data
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orders = FIND "orders.xlsx", "status=pending"
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' Map field names to match our internal format
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mapped_orders = MAP orders, "customerName->customer, orderDate->date, totalAmount->amount"
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' Fill a report template with the data
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report_template = #{
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"title": "Order Report for {{customer}}",
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"summary": "Order placed on {{date}} for ${{amount}}",
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"processed_at": NOW()
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}
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report_data = FILL mapped_orders, report_template
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' ============================================================================
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' EXAMPLE 3: Filtering and aggregation
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' ============================================================================
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' Get all sales data
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sales = FIND "sales.xlsx"
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' Filter for this month's sales
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this_month = FILTER sales, "date>=" + FORMAT(DATEADD(TODAY(), "month", -1), "yyyy-MM-dd")
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' Filter high-value transactions
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high_value = FILTER this_month, "amount>1000"
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' Calculate aggregates
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total_sales = AGGREGATE "SUM", this_month, "amount"
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average_sale = AGGREGATE "AVG", this_month, "amount"
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sale_count = AGGREGATE "COUNT", this_month, "id"
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max_sale = AGGREGATE "MAX", this_month, "amount"
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min_sale = AGGREGATE "MIN", this_month, "amount"
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TALK "This month's statistics:"
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TALK "- Total sales: $" + total_sales
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TALK "- Average sale: $" + average_sale
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TALK "- Number of sales: " + sale_count
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TALK "- Largest sale: $" + max_sale
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TALK "- Smallest sale: $" + min_sale
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' ============================================================================
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' EXAMPLE 4: Joining datasets
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' ============================================================================
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' Load related data
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customers = FIND "customers.xlsx"
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orders = FIND "orders.xlsx"
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products = FIND "products.xlsx"
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' Join orders with customer information
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orders_with_customers = JOIN orders, customers, "customer_id"
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' Now join with product data
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complete_orders = JOIN orders_with_customers, products, "product_id"
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' ============================================================================
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' EXAMPLE 5: Grouping and pivoting
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' ============================================================================
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' Group sales by salesperson
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sales_by_rep = GROUP_BY sales, "salesperson"
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' Create pivot table: sales by month
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monthly_pivot = PIVOT sales, "month", "amount"
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TALK "Monthly sales pivot created with " + UBOUND(monthly_pivot) + " rows"
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' ============================================================================
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' EXAMPLE 6: Database CRUD operations
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' ============================================================================
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' Insert a new sync log entry
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log_entry = #{
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"sync_type": "full",
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"started_at": NOW(),
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"records_processed": sale_count,
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"status": "completed"
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}
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insert_result = INSERT "sync_logs", log_entry
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TALK "Created sync log: " + insert_result.id
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' Update existing records
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rows_updated = UPDATE "customers", "last_sync<" + FORMAT(DATEADD(TODAY(), "day", -7), "yyyy-MM-dd"), #{
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"needs_refresh": true,
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"updated_at": NOW()
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}
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TALK "Marked " + rows_updated + " customers for refresh"
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' Save with upsert (insert or update)
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summary = #{
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"date": TODAY(),
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"total_sales": total_sales,
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"order_count": sale_count,
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"sync_status": "complete"
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}
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SAVE "daily_summaries", FORMAT(TODAY(), "yyyy-MM-dd"), summary
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' ============================================================================
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' EXAMPLE 7: File operations for reporting
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' ============================================================================
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' Generate a report
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report_content = "Daily Sales Report - " + TODAY() + "\n\n"
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report_content = report_content + "Total Sales: $" + total_sales + "\n"
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report_content = report_content + "Transactions: " + sale_count + "\n"
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report_content = report_content + "Average: $" + average_sale + "\n"
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' Write report to file
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WRITE "reports/daily/" + FORMAT(TODAY(), "yyyy-MM-dd") + ".txt", report_content
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' List all reports
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all_reports = LIST "reports/daily/"
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TALK "Total reports in archive: " + UBOUND(all_reports)
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' ============================================================================
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' EXAMPLE 8: HTTP POST to external system
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' ============================================================================
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' Send summary to analytics platform
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analytics_payload = #{
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"event": "daily_sync_complete",
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"data": #{
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"date": TODAY(),
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"total_sales": total_sales,
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"transaction_count": sale_count,
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"new_customers": merge_result.inserted
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}
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}
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SET HEADER "X-API-Key", GET BOT MEMORY("analytics_api_key")
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analytics_response = POST "https://analytics.example.com/events", analytics_payload
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CLEAR HEADERS
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' ============================================================================
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' EXAMPLE 9: Cleanup old data
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' ============================================================================
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' Delete old sync logs (older than 30 days)
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cutoff_date = FORMAT(DATEADD(TODAY(), "day", -30), "yyyy-MM-dd")
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deleted_logs = DELETE "sync_logs", "created_at<" + cutoff_date
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IF deleted_logs > 0 THEN
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TALK "Cleaned up " + deleted_logs + " old sync log entries"
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END IF
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' ============================================================================
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' Return webhook response
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' ============================================================================
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result = #{
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"status": "success",
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"timestamp": NOW(),
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"summary": #{
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"customers_synced": merge_result.inserted + merge_result.updated,
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"sales_processed": sale_count,
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"total_revenue": total_sales,
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"logs_cleaned": deleted_logs
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}
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}
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TALK "Data synchronization complete!"
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