Getting Started

Install as a library

go get github.com/Gaurav-Gosain/golars@latest

Install the CLI

go install github.com/Gaurav-Gosain/golars/cmd/golars@latest

Type golars help to see every subcommand:

golars                       start interactive REPL
golars run SCRIPT            execute a .glr script
golars fmt [-w] FILE         canonicalize a .glr script
golars lint FILE             report common .glr mistakes
golars schema FILE           print column names + dtypes
golars stats FILE            print describe() stats
golars head FILE [N]         print first N rows (default 10)
golars diff A B              show row-level diff between two files
golars sql QUERY [FILE...]   run a SQL query against files
golars browse FILE           interactive TUI table viewer
golars explain SCRIPT        print the lazy plan

Your first query

Programmatically:

package main

import (
    "context"
    "fmt"
    "log"

    "github.com/Gaurav-Gosain/golars/dataframe"
    "github.com/Gaurav-Gosain/golars/expr"
    "github.com/Gaurav-Gosain/golars/lazy"
    "github.com/Gaurav-Gosain/golars/series"
)

func main() {
    ctx := context.Background()

    dept, _ := series.FromString("dept", []string{"eng", "eng", "sales", "ops"}, nil)
    salary, _ := series.FromInt64("salary", []int64{100, 120, 80, 70}, nil)
    df, _ := dataframe.New(dept, salary)
    defer df.Release()

    plan := lazy.FromDataFrame(df).
        Filter(expr.Col("salary").Gt(expr.Lit(int64(75)))).
        GroupBy("dept").
        Agg(expr.Col("salary").Sum().Alias("total")).
        Sort("total", true)

    out, err := plan.Collect(ctx)
    if err != nil {
        log.Fatal(err)
    }
    defer out.Release()
    fmt.Println(out)
}

From the shell:

# Read a CSV, describe it
golars stats trades.csv

# Run SQL against it
golars sql "SELECT symbol, SUM(volume) AS vol FROM trades GROUP BY symbol ORDER BY vol DESC LIMIT 5" trades.csv

# Interactively browse it
golars browse trades.csv

The REPL

Run golars with no arguments to open the interactive REPL:

golars » load trades.csv
ok  loaded trades.csv (1,234,567 × 6)

golars » filter volume > 100
ok  added FILTER to pipeline: col("volume") > 100

golars » groupby symbol amount:sum:vol
ok  added GROUP BY [symbol] with 1 aggs

golars » sort vol desc
ok  added SORT vol desc to pipeline

golars » head 10

The REPL ships with inline ghost-text completions, command history, and tab completion for paths and column names.

Cookbook

End-to-end recipes.

.glr scripting

Automate from a script.