Data sources¶

Pandas & Polars DataFrames¶

import pandas as pd
import polars as pl
from rustpy_xlsxwriter import FastExcel

# Pandas — Arrow zero-copy, dtype-aware
df_pd = pd.DataFrame({"Name": ["Alice", "Bob"], "Score": [88.5, 92.3]})
FastExcel("pandas.xlsx").sheet("Data", df_pd).save()

# Polars — native support, no .to_pandas() needed
df_pl = pl.DataFrame({"Name": ["Alice", "Bob"], "Score": [88.5, 92.3]})
FastExcel("polars.xlsx").sheet("Data", df_pl).save()

Generator Streaming¶

def rows():
    for i in range(1_000_000):
        yield {"id": i, "value": f"row_{i}"}

FastExcel("streamed.xlsx").sheet("Data", rows()).save()

Note: dedupe_strings=True buffers the sheet, so it defeats the point of generator streaming. Leave it off for very large streamed exports.

In-Memory Buffer (Web Frameworks)¶

import io
from rustpy_xlsxwriter import FastExcel

buf = io.BytesIO()
FastExcel(buf).sheet("Sheet1", records).save()
xlsx_bytes = buf.getvalue()  # send as HTTP response

String Deduplication¶

By default every sheet is written in constant-memory mode: strings go inline into the sheet XML and nothing is buffered. Passing dedupe_strings=True takes that sheet out of constant-memory mode and stores each distinct string once in the workbook's shared-string table instead.

(
    FastExcel("report.xlsx")
    .sheet("Events", events, dedupe_strings=True)   # lots of repeated text
    .sheet("Raw", raw_rows)                         # default: streamed
    .save()
)

Measured on 50k rows — the uncompressed XML shrinks a lot, but .xlsx is a zip and deflate already collapses repetition, so the on-disk win is modest and can even be negative:

Data	Uncompressed	On disk	Write time
Short repeats (4 distinct values)	−11%	+2%	1.7x
Long repeats (20 distinct, 120 chars)	−56%	−5%	1.1x
All-unique strings	+11%	−1%	1.5x
20 repeated text columns	−39%	−9%	1.1x

Worth enabling for sheets with many repeated long strings, or when the consumer parses the uncompressed XML. Not worth it for short categorical values. Off by default because it buffers the whole sheet in memory — measure on your own data before turning it on for a large export.

For write_worksheets, pass dedupe_strings as a dict keyed by sheet name (with a "general" fallback key).