A command-line tool that provides an SQL-like query language for reading, updating, and deleting CSV records.
Csvq is a command-line tool that provides an SQL-like query language for operating on CSV files. It allows users to read, update, delete, and manipulate CSV records using familiar SQL syntax, eliminating the need for complex database setups or spreadsheet software for simple data tasks. The tool supports transactions, multiple file formats, and an interactive shell for streamlined data processing.
Developers, data analysts, and system administrators who need to quickly query and manipulate CSV data without installing a full database system. It's ideal for those working with small to medium-sized datasets typically handled in spreadsheet applications.
Csvq offers a lightweight, dependency-free solution for SQL-like operations on CSV files, with support for transactions, variables, and multiple formats. Its single binary distribution and interactive shell make it easy to adopt and use across platforms for ad-hoc data tasks.
SQL-like query language for csv
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Available as a single executable binary with no external dependencies, making setup trivial across platforms, as highlighted in the README's philosophy section.
Handles CSV, TSV, JSON, fixed-length formats, and more, allowing flexible data input without conversion, based on the features list in the README.
Supports managed transactions with COMMIT and ROLLBACK, ensuring safe updates to CSV files during multi-step workflows, as described in the transaction management feature.
Includes a REPL interface for real-time data exploration and manipulation, similar to database consoles, demonstrated in the interactive shell usage examples.
Loads entire datasets into RAM during execution, limiting it to files that fit in memory, as the README explicitly states it's not suitable for very large data.
Lacks indexing and query optimization mechanisms, resulting in slower execution compared to dedicated databases, admitted in the README's intended use section.
SQL-like but may not support all standard SQL features; for example, the reference manual doesn't emphasize advanced joins or subqueries, and JSON support is restricted to UTF-8 encoding.