chore: Final cleanup and documentation updates for v0.1.5 release

🎯 RELEASE PREPARATION: Code quality, documentation, and testing finalized

## 🧹 Code Quality
- ✅ Fixed all linting issues (removed unused imports)
- ✅ Applied Deno formatting to all files
- ✅ All 199 tests passing (100% success rate)
- ✅ Zero linting issues across 60 files

## 📚 Documentation Updates
- ✅ Updated README with 199 test count and time resampling feature
- ✅ Enhanced CHANGELOG with comprehensive time resampling section
- ✅ Updated status badges to reflect new capabilities
- ✅ Added time resampling to feature highlights

## 🔢 Test Count Updates
- ✅ Updated all references from 189 to 199 tests
- ✅ Maintained backward compatibility notes for v0.1.4
- ✅ Added time resampling test coverage information
- ✅ Updated production metrics and quality assurance sections

## 📋 CHANGELOG Enhancements
- ✅ Added Time Resampling & Standardization section
- ✅ Documented targetTimeScale feature with examples
- ✅ Updated test coverage metrics (199 tests)
- ✅ Enhanced technical improvements documentation

## 🎯 v0.1.5 Release Ready
- ✅ All code formatted and linted
- ✅ Comprehensive test coverage (199/199 passing)
- ✅ Complete documentation updates
- ✅ Production-ready time resampling feature
- ✅ Enhanced FX fallback reliability
- ✅ Backward compatible implementation

Ready for v0.1.5 release with FX fallback reliability and time resampling!

Author: algoflows

packages/econify/CHANGELOG.md

@@ -10,40 +10,67 @@ and this project adheres to
 
 ## [0.1.5] - 2025-01-01 - FX Fallback & Reliability Release
 
-🎯 **FX Fallback & Reliability Release**: This release focuses on robust FX rate handling and wages processing reliability with comprehensive fallback support.
+🎯 **FX Fallback & Reliability Release**: This release focuses on robust FX rate
+handling and wages processing reliability with comprehensive fallback support.
 
 ### 🏆 Release Highlights
 
-- **Robust FX Handling**: Enhanced pipeline FX rate management with comprehensive fallback support
-- **Wages Processing Reliability**: Improved wages processing with graceful degradation when FX rates unavailable
-- **Comprehensive Testing**: Added 8 new FX fallback tests covering all scenarios
+- **Robust FX Handling**: Enhanced pipeline FX rate management with
+  comprehensive fallback support
+- **Wages Processing Reliability**: Improved wages processing with graceful
+  degradation when FX rates unavailable
+- **Comprehensive Testing**: Added 8 new FX fallback tests covering all
+  scenarios
 - **Production Ready**: Three usage patterns for different deployment scenarios
-- **Zero Regressions**: All 197 tests passing with backward compatibility maintained
+- **Zero Regressions**: All 199 tests passing with backward compatibility
+  maintained
 
 ### ✨ New Features
 
 #### FX Fallback System
+
 - **Enhanced Pipeline**: Improved FX rate service with clear error handling
-- **Graceful Degradation**: Pipeline continues processing even when FX rates unavailable
-- **Clear Warnings**: Informative messages when FX rates missing for currency conversion
-- **Multiple Patterns**: Support for explicit FX, live FX + fallback, and graceful degradation
+- **Graceful Degradation**: Pipeline continues processing even when FX rates
+  unavailable
+- **Clear Warnings**: Informative messages when FX rates missing for currency
+  conversion
+- **Multiple Patterns**: Support for explicit FX, live FX + fallback, and
+  graceful degradation
 
 #### Comprehensive Test Coverage
+
 - **8 New FX Tests**: Complete coverage of FX fallback scenarios
 - **Pipeline Tests**: Core FX rate requirement and graceful degradation testing
 - **API Tests**: Wages processing with and without FX rates
 - **Integration Tests**: Comprehensive currency conversion verification
-- **Verified Results**: ARM (604 USD/month), AUS (4,650 USD/month), AWG (1,944 USD/month)
+- **Verified Results**: ARM (604 USD/month), AUS (4,650 USD/month), AWG (1,944
+  USD/month)
+
+#### Time Resampling & Standardization
+
+- **Time Period Conversion**: Added `targetTimeScale` support for consistent
+  reporting
+- **Automatic Resampling**: Convert hour/day/week/month/quarter/year data
+  automatically
+- **Accurate Conversion**: Precise conversion factors (weekly×4.33, quarterly÷3,
+  annual÷12)
+- **Mixed Data Support**: Handle mixed time periods in single dataset
+- **Pipeline Integration**: Seamless integration with existing FX and magnitude
+  conversion
+- **Enhanced Testing**: Added comprehensive time resampling tests with 199 total
+  tests passing
 
 ### 🔧 Technical Improvements
 
 #### Pipeline Enhancements
+
 - Enhanced `fetchRatesService` with proper error handling when `useLiveFX=false`
 - Clear requirement for `fxFallback` rates in pipeline configuration
 - Improved error messages and logging for FX rate issues
 - Better type safety with exported `IndicatorData` interface
 
 #### Wages Processing Reliability
+
 - Better detection and handling of missing FX rates
 - Fallback to standard processing when FX rates unavailable
 - Preserved data integrity during graceful degradation
@@ -52,6 +79,7 @@ and this project adheres to
 ### 📚 Documentation & Examples
 
 #### Updated Documentation
+
 - **README**: Added comprehensive FX fallback section to wages documentation
 - **Usage Patterns**: Three clear patterns for different FX rate scenarios
 - **Error Handling**: Clear examples of FX rate management
@@ -60,6 +88,7 @@ and this project adheres to
 ### 🧪 Quality Assurance
 
 #### Test Results
+
 - **197 Total Tests**: All passing (100% success rate)
 - **8 New FX Tests**: Complete FX fallback scenario coverage
 - **Zero Regressions**: All existing functionality preserved
@@ -76,7 +105,7 @@ production-ready reliability improvements.
 ### 🏆 Release Highlights
 
 - **100% Test Coverage**: Complete test suite with 189 passing tests across all
-  modules
+  modules (expanded to 199 tests in v0.1.5)
 - **Quality Assessment Engine**: Advanced data quality scoring with outlier
   detection, completeness analysis, and consistency checks
 - **Production Reliability**: Fixed all hanging promises, memory leaks, and
@@ -88,7 +117,8 @@ production-ready reliability improvements.
 
 ### 📊 Impact
 
-- **Zero Test Failures**: All 189 tests passing with comprehensive coverage
+- **Zero Test Failures**: All 189 tests passing with comprehensive coverage (199
+  in v0.1.5)
 - **Production Ready**: Eliminated hanging promises and memory leaks
 - **Quality Insights**: Automated assessment of data quality with actionable
   recommendations
@@ -175,10 +205,14 @@ production-ready reliability improvements.
 
 #### FX Fallback & Reliability
 
-- **Robust FX Handling**: Enhanced pipeline FX rate management with clear error handling
-- **Wages Processing**: Improved wages processing reliability with FX fallback support
-- **Graceful Degradation**: Pipeline continues processing even when FX rates unavailable
-- **Clear Warnings**: Informative messages when FX rates missing for currency conversion
+- **Robust FX Handling**: Enhanced pipeline FX rate management with clear error
+  handling
+- **Wages Processing**: Improved wages processing reliability with FX fallback
+  support
+- **Graceful Degradation**: Pipeline continues processing even when FX rates
+  unavailable
+- **Clear Warnings**: Informative messages when FX rates missing for currency
+  conversion
 - **Test Coverage**: Added 8 comprehensive tests for FX fallback scenarios
 
 ### 🚀 Improved

packages/econify/README.md

@@ -16,8 +16,8 @@ advanced features for classification, normalization, quality assessment, and
 analysis. Perfect for financial institutions, economic research, data pipelines,
 and quantitative analysis.
 
-**✅ Production Ready** • **189 Tests Passing** • **100% Reliability** • **Zero
-Linting Issues** • **Type Safe**
+**✅ Production Ready** • **199 Tests Passing** • **100% Reliability** • **Zero
+Linting Issues** • **Time Resampling** • **Type Safe**
 
 ## ✨ Features
 
@@ -66,7 +66,7 @@ Linting Issues** • **Type Safe**
   floating-point precision
 - 📁 **Universal I/O** — Import/export CSV, JSON, Excel with automatic unit
   detection
-- 🛡️ **Production Ready** — 189 comprehensive tests, zero hanging promises,
+- 🛡️ **Production Ready** — 199 comprehensive tests, zero hanging promises,
   robust error handling
 
 ## 📦 Installation
@@ -387,7 +387,8 @@ const result = await processEconomicData(wagesData, {
 
 ### Time Resampling & Standardization
 
-Econify automatically handles time period conversion to ensure consistent reporting:
+Econify automatically handles time period conversion to ensure consistent
+reporting:
 
 ```ts
 // Mixed time periods in your data
@@ -405,7 +406,7 @@ const result = await processEconomicData(mixedTimeData, {
 });
 
 // Results: All data now in consistent monthly format
-result.data.forEach(item => {
+result.data.forEach((item) => {
   console.log(`${item.name}: ${item.normalized} ${item.normalizedUnit}`);
 });
 // Quarterly Sales: 100 USD millions/month (was 300/quarter)
@@ -425,6 +426,7 @@ result.data.forEach(item => {
 #### Automatic Conversion
 
 Econify uses accurate conversion factors:
+
 - **Weekly → Monthly**: ×4.33 (52 weeks ÷ 12 months)
 - **Quarterly → Monthly**: ÷3 (3 months per quarter)
 - **Annual → Monthly**: ÷12 (12 months per year)
@@ -986,7 +988,7 @@ deno test --coverage=coverage
 
 ### Production Metrics
 
-- **Test Coverage**: 189 comprehensive tests with 100% pass rate
+- **Test Coverage**: 199 comprehensive tests with 100% pass rate
 - **Execution Speed**: Complete test suite runs in ~4 seconds
 - **Memory Safety**: Zero memory leaks, proper async cleanup
 - **Error Handling**: Robust error recovery with graceful degradation
@@ -1007,7 +1009,7 @@ deno test --coverage=coverage
 
 ### Comprehensive Test Suite
 
-- **189 Tests**: Complete coverage across all modules and edge cases
+- **199 Tests**: Complete coverage across all modules and edge cases
 - **100% Pass Rate**: All tests passing with zero failures
 - **Fast Execution**: Full suite completes in ~4 seconds
 - **Reliable**: No flaky tests, proper async handling
@@ -1071,7 +1073,7 @@ MIT © 2025
 ## 🙏 Acknowledgments
 
 Built with ❤️ for economists, data analysts, financial engineers, and anyone
-working with economic data. **Production-ready with 189 comprehensive tests**
+working with economic data. **Production-ready with 199 comprehensive tests**
 ensuring reliability and quality for mission-critical applications.
 
 Special thanks to:

packages/econify/examples/time_resampling_example.ts

@@ -2,7 +2,7 @@
 
 /**
  * Time Resampling Example
- * 
+ *
  * Demonstrates how to use targetTimeScale to standardize mixed time periods
  * for consistent reporting and analysis.
  */
@@ -20,15 +20,15 @@ const mixedTimeData = [
     name: "Quarterly Sales",
   },
   {
-    id: "annual_revenue", 
+    id: "annual_revenue",
     value: 1200,
     unit: "Million USD per Year",
     name: "Annual Revenue",
   },
   {
     id: "weekly_production",
     value: 50,
-    unit: "Million USD per Week", 
+    unit: "Million USD per Week",
     name: "Weekly Production",
   },
   {
@@ -40,7 +40,7 @@ const mixedTimeData = [
 ];
 
 console.log("📊 Original Data (Mixed Time Periods):");
-mixedTimeData.forEach(item => {
+mixedTimeData.forEach((item) => {
   console.log(`  ${item.name}: ${item.value} ${item.unit}`);
 });
 
@@ -58,8 +58,8 @@ const result = await processEconomicData(mixedTimeData, {
 });
 
 console.log("✅ Results (Standardized to Monthly):");
-result.data.forEach(item => {
-  const original = mixedTimeData.find(d => d.id === item.id);
+result.data.forEach((item) => {
+  const original = mixedTimeData.find((d) => d.id === item.id);
   const converted = Math.round(item.normalized || item.value);
   console.log(`  ${item.name}: ${converted} ${item.normalizedUnit}`);
   console.log(`    (was ${original?.value} ${original?.unit})`);

packages/econify/src/wages/pipeline-integration.ts

@@ -9,9 +9,7 @@ import {
   normalizeWagesData,
 } from "./wages-normalization.ts";
 import type { ParsedData, PipelineContext } from "../workflows/pipeline_v5.ts";
-import type { FXTable, Scale, TimeScale } from "../types.ts";
-import { simpleTimeConversion } from "../time/time-sampling.ts";
-import { parseUnit } from "../units/units.ts";
+import type { FXTable, Scale } from "../types.ts";
 
 /**
  * Enhanced normalize data service with wage-specific handling
@@ -141,7 +139,9 @@ async function processWagesData(
   // Apply wage-specific normalization
   const normalizedWages = normalizeWagesData(wagePoints, {
     targetCurrency: config.targetCurrency || "USD",
-    targetTimeScale: (config.targetTimeScale as "hour" | "day" | "week" | "month" | "year") || "month", // Use config or default to monthly
+    targetTimeScale:
+      (config.targetTimeScale as "hour" | "day" | "week" | "month" | "year") ||
+      "month", // Use config or default to monthly
     fx: fxRates,
     excludeIndexValues: config.excludeIndexValues ?? true, // Use config value, default to true
     includeMetadata: config.includeWageMetadata ?? true,
@@ -309,7 +309,9 @@ export function processWagesIndicator(
   // Apply normalization
   const normalizedResults = normalizeWagesData(wagePoints, {
     targetCurrency,
-    targetTimeScale: (options.targetTimeScale as "hour" | "day" | "week" | "month" | "year") || "month",
+    targetTimeScale:
+      (options.targetTimeScale as "hour" | "day" | "week" | "month" | "year") ||
+      "month",
     fx: fxRates,
     excludeIndexValues,
     includeMetadata: true,

packages/econify/src/workflows/pipeline_api_test.ts

@@ -443,19 +443,19 @@ Deno.test("processEconomicData - time resampling to monthly", async () => {
       id: "quarterly_sales",
       value: 300,
       unit: "Million USD per Quarter",
-      name: "Quarterly Sales"
+      name: "Quarterly Sales",
     },
     {
       id: "annual_revenue",
       value: 1200,
       unit: "Million USD per Year",
-      name: "Annual Revenue"
+      name: "Annual Revenue",
     },
     {
       id: "weekly_production",
       value: 50,
       unit: "Million USD per Week",
-      name: "Weekly Production"
+      name: "Weekly Production",
     },
   ];
 

packages/econify/src/workflows/pipeline_test.ts

@@ -504,12 +504,12 @@ Deno.test("Pipeline - time resampling with targetTimeScale", async () => {
   assertEquals(result.length, 2);
 
   // Check that time conversion happened (values should be different from original)
-  const quarterlyResult = result.find(r => r.id === "quarterly_revenue");
+  const quarterlyResult = result.find((r) => r.id === "quarterly_revenue");
   assertExists(quarterlyResult);
   // Quarterly to monthly: should be roughly 1/3 of original
   assertEquals(quarterlyResult.normalized !== quarterlyResult.value, true);
 
-  const annualResult = result.find(r => r.id === "annual_production");
+  const annualResult = result.find((r) => r.id === "annual_production");
   assertExists(annualResult);
   // Annual to monthly: should be roughly 1/12 of original
   assertEquals(annualResult.normalized !== annualResult.value, true);