Fast columnar dataframe library for Python, powered by a zero-dependency C17 engine with lazy fusion execution.
pip install teideNote: v0.1.0 supports Linux and macOS only. Windows support is planned.
from teide import Context, col
with Context() as ctx:
df = ctx.read_csv("data.csv")
result = (
df.filter(col("price") > 0)
.group_by("category")
.agg(col("price").sum(), col("price").mean())
.sort("price_sum", descending=True)
.collect()
)
print(result)- Lazy evaluation with automatic query optimization (predicate pushdown, CSE, operator fusion)
- Morsel-driven parallel execution across all cores
- Zero-copy NumPy interop for numeric columns
- Fast CSV reader — parallel parsing, mmap I/O
- Columnar storage — splayed tables, date-partitioned datasets
- Pure C17 engine — no external dependencies, minimal memory overhead
MIT