CSV Data Processor which evaluates and process data faster by using OpenMP

csv-data-processor

A lightweight CLI tool to query, aggregate, and update numeric CSV files directly from the terminal.

• Automatically loads file.csv from the working directory
• First row = column names
• Remaining rows = numeric data (double)
• Commands can be chained using | (pipe operator)
• Uses OpenMP for fast execution

When started, it prints the list of columns and shows a prompt:

Welcome to csv-data-processor
csv-data-processor>>>

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Supported Commands

Aggregate Range — a(...)

a(<column>, <start>, <end>)

Sums values in a column from row start to end. Use * to mean full coverage.

Examples:

a(SALARY,0,99)
a(PRICE,*,*)

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Conditional Aggregate — ca(...)

ca(<column>, <condition>)

Filters cells based on a condition and sums the matching ones. x refers to the current cell value.

Examples:

ca(SALARY, x>50000)
ca(AGE, x>=18 && x<=60)

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Update Range — u(...)

u(<column>, <start>, <end>, <expression-or-value>)

Updates values in a given range.

• Expression uses x as the old value
• Or assign constant values

Examples:

u(SALARY,0,*, 50000)
u(AGE,*,*, x+1)

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Conditional Update — cu(...)

cu(<column>, <condition>, <expression-or-value>)

Only updates rows where the condition evaluates true.

Examples:

cu(SALARY, x<30000, x*1.2)
cu(AGE, x<18, 18)

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Show Columns — s(...)

s(<col1 col2 col3>, <start>, <end>)

Displays selected columns in table format.

Example:

s(ID NAME SALARY,*,*)

Note: Current version prints entire dataset ignoring range args.

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Save and Exit — commit

commit

Saves data back to file.csv and ends program.

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Exit Without Saving — exit

exit

Quits and discards unsaved changes.

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Result Output + Timer

After running commands (single or chained), tool prints:

• Execution Time (in seconds)

• Compact result table:

  • 1st row: commands executed
  • 2nd row: result per command (sum, Null for update, Error if failed)

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Build & Run

Ensure a C++ compiler with OpenMP is available.

Run:

./parallel.sh

Your file.csv must be placed in the executable directory.

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Example CSV Format

ID,AGE,SALARY
1,22,40000
2,35,65000
3,29,52000

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Feature Summary

Feature	Status
Range aggregation
Conditional aggregation
Range update
Conditional update
Parallel execution
Save back to CSV
Table output
Command chaining

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Purpose

Provides a fast and simple way to manipulate numeric CSV datasets without needing SQL or heavy spreadsheet tools — ideal for bulk analytics and quick data experiments.

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