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Project description

clipd — Command Line Interface for Pandas

A lightweight terminal-native CLI tool for exploring, cleaning, and transforming CSV data using the power of Pandas — right from your command line.

  • Built using Typer, Rich and Panda.
  • Designed for speed, control and effortless ETL

Current Available Functions

Here's what clipd can do right now:

Initialise Clipd

  • clipd init Initialises clipd in the current directory.

File Management

  • clipd connect <file.csv>
    Connects a dataframe file for processing. All operations will apply to this active file. (Make sure the file exists in the directory clipd is initialised in)

  • clipd disconnect
    Safely disconnects the currently active file.

Data Description

  • clipd describe
    Provides a detailed overview of the connected file. Supports flags like --head, --tail, --all, --null, --unique etc.

Log Management

  • clipd log
    View structured logs of all operations performed during the session. Supports flags like '--lines 8` to veiw exact number of log lines.

  • clipd log clear
    Cleanly wipes the operation history.

Error Handling

  • Clean, readable terminal error messages with helpful guidance.
  • No cryptic stack traces

Exporting

  • Export your transformed dataset to various formats: clipd export : defaults to CSV. Also supports:
    • .xlsx
    • .json

Once installed, here’s how clipd commands feel in your terminal workflow:

clipd init
clipd connect <file>
clipd describe
clipd describe --head
clipd describe --null
clipd describe --unique --dtypes
clipd export --filename yadh --xlsx
clipd disconnect
clipd log
clipd log clear

Future Prospects

As the soul and sole developer, I add new functionalities and fix bugs in the code every day.

  • Expand to all major Pandas commands
  • Git style verson-control for dataframes
  • Pipeline support
  • Export the clipd actions as a .py/.ipynb file.
  • Perform basic ML algorithms.

Author

Made with love and --force by Yadhnika Wakde

I hope clipd grows into a useful tool and makes etl easier and faster.

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