name: data-processing
kind: module
desc: Data aggregation and processing workflow with function steps, decision routing, and parallel execution

params:
  - name: input_dir
    value: "{{Output}}"
  - name: output_format
    value: "json"
  - name: max_entries
    value: "10000"
  - name: enable_dedup
    value: "true"

steps:
  # Step 1: function - Initialize processing context
  - name: initialize-context
    type: function
    script: |
      log_info("Data Processing Pipeline Started");
      log_info("Input Directory: {{input_dir}}");
      log_info("Output Format: {{output_format}}");

      // Create processing manifest
      var manifest = {
        start_time: timestamp(),
        input_dir: "{{input_dir}}",
        output_format: "{{output_format}}",
        files_processed: 0,
        total_entries: 0
      };

      writeFile("{{Output}}/processing/manifest.json", JSON.stringify(manifest, null, 2));
      return true;
    exports:
      processing_started: "{{Result}}"

  # Step 2: bash - Setup processing directories
  - name: setup-processing
    type: bash
    commands:
      - mkdir -p {{Output}}/processing
      - mkdir -p {{Output}}/aggregated
      - mkdir -p {{Output}}/reports
      - find {{input_dir}} -type f \( -name "*.txt" -o -name "*.json" -o -name "*.csv" \) > {{Output}}/processing/file-list.txt
    exports:
      file_list: "{{Output}}/processing/file-list.txt"
      processing_dir: "{{Output}}/processing"
      aggregated_dir: "{{Output}}/aggregated"

  # Step 3: function with decision - Determine processing strategy
  - name: determine-strategy
    type: function
    script: |
      var fileCount = fileLength("{{file_list}}");
      log_info("Files to process: " + fileCount);

      if (fileCount == 0) {
        log_warn("No files found to process");
        return "no_data";
      } else if (fileCount > 100) {
        log_info("Large dataset, using batch processing");
        return "batch";
      } else if (fileCount > 20) {
        log_info("Medium dataset, using parallel processing");
        return "parallel";
      }

      log_info("Small dataset, using sequential processing");
      return "sequential";
    exports:
      processing_strategy: "{{Result}}"
    decision:
      switch: "{{processing_strategy}}"
      cases:
        "no_data":
          goto: handle-no-data
        "batch":
          goto: batch-processing
        "parallel":
          goto: parallel-processing
        "sequential":
          goto: sequential-processing

  # Step 4a: foreach - Sequential processing for small datasets
  - name: sequential-processing
    type: foreach
    input: "{{file_list}}"
    variable: datafile
    threads: 1
    step:
      name: process-file
      type: bash
      command: |
        filename=$(basename "[[datafile]]")
        extension="${filename##*.}"
        if [ "$extension" = "json" ]; then
          cat "[[datafile]]" | jq -c '.' >> {{aggregated_dir}}/combined.jsonl 2>/dev/null || cat "[[datafile]]" >> {{aggregated_dir}}/combined.jsonl
        else
          cat "[[datafile]]" >> {{aggregated_dir}}/combined.txt
        fi
      on_error: continue
    exports:
      processing_mode: "sequential"

  # Step 4b: parallel-steps - Parallel processing for medium datasets
  - name: parallel-processing
    type: parallel-steps
    parallel_steps:
      - name: process-json-files
        type: bash
        command: "find {{input_dir}} -name '*.json' -exec cat {} \\; | jq -c '.' > {{aggregated_dir}}/all-json.jsonl 2>/dev/null || true"
        timeout: 600
        on_error: continue
      - name: process-txt-files
        type: bash
        command: "find {{input_dir}} -name '*.txt' -exec cat {} \\; | sort -u > {{aggregated_dir}}/all-txt.txt"
        timeout: 600
        on_error: continue
      - name: process-csv-files
        type: bash
        command: "find {{input_dir}} -name '*.csv' -exec tail -n +2 {} \\; > {{aggregated_dir}}/all-csv.csv"
        timeout: 600
        on_error: continue
    exports:
      processing_mode: "parallel"

  # Step 4c: bash - Batch processing for large datasets
  - name: batch-processing
    type: bash
    command: |
      # Process in batches of 50 files
      split -l 50 {{file_list}} {{processing_dir}}/batch_
      for batch in {{processing_dir}}/batch_*; do
        while read -r file; do
          cat "$file" >> {{aggregated_dir}}/batch-output.txt 2>/dev/null
        done < "$batch"
      done
    timeout: 3600
    exports:
      processing_mode: "batch"

  # Step 4d: function - Handle no data case
  - name: handle-no-data
    type: function
    script: |
      log_warn("No data files found for processing");
      writeFile("{{Output}}/reports/no-data.txt", "No data files found in " + "{{input_dir}}");
      return false;
    exports:
      processing_mode: "skipped"

  # Step 5: function - Deduplicate and clean data
  - name: deduplicate-data
    type: function
    pre_condition: "'{{enable_dedup}}' == 'true'"
    script: |
      log_info("Deduplicating aggregated data");

      var txtFile = "{{aggregated_dir}}/all-txt.txt";
      if (fileExists(txtFile)) {
        var lineCount = fileLength(txtFile);
        log_info("Text entries before dedup: " + lineCount);
        sortUnix(txtFile);
        var newCount = fileLength(txtFile);
        log_info("Text entries after dedup: " + newCount);
      }

      return true;
    exports:
      dedup_complete: "{{Result}}"

  # Step 6: parallel-steps - Generate multiple report formats
  - name: generate-reports
    type: parallel-steps
    parallel_steps:
      - name: json-report
        type: bash
        command: |
          cat {{aggregated_dir}}/*.jsonl 2>/dev/null | head -{{max_entries}} > {{Output}}/reports/data.json
          echo '{"total": '$(wc -l < {{Output}}/reports/data.json 2>/dev/null || echo 0)'}' > {{Output}}/reports/summary.json
        on_error: continue
      - name: csv-report
        type: bash
        command: |
          echo "source,data" > {{Output}}/reports/data.csv
          cat {{aggregated_dir}}/*.txt 2>/dev/null | head -{{max_entries}} | while read line; do
            echo "aggregated,\"$line\"" >> {{Output}}/reports/data.csv
          done
        on_error: continue
      - name: markdown-report
        type: bash
        command: |
          cat > {{Output}}/reports/report.md << EOF
          # Data Processing Report

          **Target:** {{Target}}
          **Processing Mode:** {{processing_mode}}
          **Generated:** $(date)

          ## Statistics
          - Input Directory: {{input_dir}}
          - Files Processed: $(wc -l < {{file_list}})
          - Output Format: {{output_format}}

          ## Files Generated
          - data.json
          - data.csv
          - summary.json
          EOF

  # Step 7: function - Calculate final statistics
  - name: calculate-statistics
    type: function
    script: |
      var stats = {
        processing_mode: "{{processing_mode}}",
        files_processed: fileLength("{{file_list}}"),
        dedup_enabled: "{{enable_dedup}}" === "true",
        output_format: "{{output_format}}",
        completion_time: timestamp()
      };

      log_info("Processing Complete:");
      log_info("  Mode: " + stats.processing_mode);
      log_info("  Files: " + stats.files_processed);

      writeFile("{{Output}}/reports/stats.json", JSON.stringify(stats, null, 2));
      return JSON.stringify(stats);
    exports:
      final_stats: "{{Result}}"

  # Step 8: bash - Archive and cleanup
  - name: archive-results
    type: bash
    parallel_commands:
      - "tar -czf {{Output}}/data-archive.tar.gz -C {{Output}} reports aggregated 2>/dev/null || true"
      - "rm -rf {{processing_dir}}/batch_* 2>/dev/null || true"
      - "echo 'Processing pipeline completed at:' $(date) > {{Output}}/COMPLETED.txt"
    exports:
      archive_file: "{{Output}}/data-archive.tar.gz"
      pipeline_complete: "true"