> Source: https://txtfetch.com/extract/xlsx
> Plain-text twin — every page on txtfetch.com has one. https://txtfetch.com/text

---

# Spreadsheets, resolved not raw.

Cell values are indices into a shared string table. Formulas store their formula, not their answer. Tika resolves both before you ever see the response.

the-problem

A spreadsheet's cells don't hold their own text. In .xlsx, string cell values are indices into xl/sharedStrings.xml, a dedup table shared across the whole workbook, not inline text. So reading cells in isolation just gets you numbers pointing at other numbers. Formula cells store the formula itself, like =SUM(A1:A10). The number a human sees is a separately cached result value, and plenty of naive readers grab the wrong one, or the formula string, instead. Number formats add another layer of indirection. A cell can be stored as 0.42 and displayed as 42%. Or it can be stored as a serial integer and displayed as a date. So 'the value' and 'what's on screen' genuinely differ. Hidden sheets, hidden rows, and merged cells still carry meaning that a flat text dump can drop entirely.

one-request-solution

txtfetch resolves the indirection for you. Shared-string references become their actual text, and formula cells return Tika's cached computed value rather than the =SUM() source. That means the numbers in your response match what a person looking at the sheet would see. For table structure, with rows and columns kept intact instead of flattened into a wall of numbers, request ?format=markdown.

curl

```curl
curl -X POST https://api.txtfetch.com/v1/extract \
  -H "Authorization: Bearer $TXTFETCH_KEY" \
  -F file=@q1-revenue-workbook.xlsx
```

Python

```python
import os
import requests

with open("q1-revenue-workbook.xlsx", "rb") as f:
    r = requests.post(
        "https://api.txtfetch.com/v1/extract",
        headers={"Authorization": f"Bearer {os.environ['TXTFETCH_KEY']}"},
        files={"file": f},
    )

print(r.json()["extracted_text"])
```

JavaScript

```javascript
import { readFile } from "node:fs/promises";

const file = new Blob([await readFile("q1-revenue-workbook.xlsx")]);
const form = new FormData();
form.append("file", file, "q1-revenue-workbook.xlsx");

const res = await fetch("https://api.txtfetch.com/v1/extract", {
  method: "POST",
  headers: { Authorization: `Bearer ${process.env.TXTFETCH_KEY}` },
  body: form,
});

const { extracted_text } = await res.json();
console.log(extracted_text);
```

Go

```go
package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"io"
	"mime/multipart"
	"net/http"
	"os"
)

type extractResponse struct {
	Status        string `json:"status"`
	ExtractedText string `json:"extracted_text"`
}

func main() {
	f, err := os.Open("q1-revenue-workbook.xlsx")
	if err != nil {
		panic(err)
	}
	defer f.Close()

	var body bytes.Buffer
	writer := multipart.NewWriter(&body)
	part, err := writer.CreateFormFile("file", "q1-revenue-workbook.xlsx")
	if err != nil {
		panic(err)
	}
	if _, err := io.Copy(part, f); err != nil {
		panic(err)
	}
	writer.Close()

	req, err := http.NewRequest("POST", "https://api.txtfetch.com/v1/extract", &body)
	if err != nil {
		panic(err)
	}
	req.Header.Set("Authorization", "Bearer "+os.Getenv("TXTFETCH_KEY"))
	req.Header.Set("Content-Type", writer.FormDataContentType())

	resp, err := http.DefaultClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer resp.Body.Close()

	var result extractResponse
	if err := json.NewDecoder(resp.Body).Decode(&result); err != nil {
		panic(err)
	}
	fmt.Println(result.ExtractedText)
}
```

Or skip the download. Pass a `url` parameter and txtfetch fetches the document server-side:

curl

```curl
curl -X POST "https://api.txtfetch.com/v1/extract?url=https://example.com/reports/regional-sales.xlsx" \
  -H "Authorization: Bearer $TXTFETCH_KEY"
```

Python

```python
import os
import requests

r = requests.post(
    "https://api.txtfetch.com/v1/extract",
    headers={"Authorization": f"Bearer {os.environ['TXTFETCH_KEY']}"},
    params={"url": "https://example.com/reports/regional-sales.xlsx"},
)

print(r.json()["extracted_text"])
```

JavaScript

```javascript
const endpoint = new URL("https://api.txtfetch.com/v1/extract");
endpoint.searchParams.set("url", "https://example.com/reports/regional-sales.xlsx");

const res = await fetch(endpoint, {
  method: "POST",
  headers: { Authorization: `Bearer ${process.env.TXTFETCH_KEY}` },
});

const { extracted_text } = await res.json();
console.log(extracted_text);
```

Go

```go
package main

import (
	"encoding/json"
	"fmt"
	"net/http"
	"net/url"
	"os"
)

type extractResponse struct {
	Status        string `json:"status"`
	ExtractedText string `json:"extracted_text"`
}

func main() {
	endpoint, err := url.Parse("https://api.txtfetch.com/v1/extract")
	if err != nil {
		panic(err)
	}
	q := endpoint.Query()
	q.Set("url", "https://example.com/reports/regional-sales.xlsx")
	endpoint.RawQuery = q.Encode()

	req, err := http.NewRequest("POST", endpoint.String(), nil)
	if err != nil {
		panic(err)
	}
	req.Header.Set("Authorization", "Bearer "+os.Getenv("TXTFETCH_KEY"))

	resp, err := http.DefaultClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer resp.Body.Close()

	var result extractResponse
	if err := json.NewDecoder(resp.Body).Decode(&result); err != nil {
		panic(err)
	}
	fmt.Println(result.ExtractedText)
}
```

```
{
  "status": "success",
  "extracted_text": "..."
}
```

what-comes-back

That is the shape. This is the text. A real .xlsx from the benchmark corpus, word-diffed against the raw parser output. Nothing here was written for this page. Every character comes from a committed fixture.

FY2026 Budget Forecast (XLSX)

`fy2026-budget-forecast.xlsx` · application/vnd.openxmlformats-officedocument.spreadsheetml.sheet · left pane read via Apache Tika, **right pane: the human-checked expected.json**

raw parser output

```
Opex

Line item	Q1	Q2
Cloud hosting	4200	4600
Payroll	61000	64500

Summary

Total	65200	69100
```

the human-checked ideal

```
Opex

Line item	Q1	Q2
Cloud hosting	4200	4600
Payroll	61000	64500

Summary

Total	65200	69100
```

[See all ten documents, with the full explanation →](https://txtfetch.com/diff)

formats-covered

-   `.xlsx`
-   `.xls`
-   `.xlsm`
-   `.csv`
-   `.ods`

response-options

Need rows and columns, not a flat wall of numbers? ?format=markdown returns each sheet as a proper markdown table.

faq

**Does extraction return the formula or the calculated value?**: The calculated value. Tika reads the cached formula result that Excel stores alongside the formula, so you get 18200 instead of the literal string =SUM(A1:A10).

**Do percentages and dates come back as raw numbers?**: No. The cell's number format is applied before the text is returned. A cell stored as 0.42 with a percent format comes back as 42%. A date stored as the serial number 46229 comes back as 2026-07-26. A cell with no format applied returns its stored value unchanged, which is what you want for a plain number.

**Are hidden sheets and hidden rows included?**: Yes. txtfetch extracts hidden sheets and rows along with visible ones, since hiding a sheet in Excel doesn't remove its data.

**Can I get real table structure instead of a flat text dump?**: Yes. Pass ?format=markdown, and rows and columns come back as a markdown table per sheet instead of space-separated cell values.

go-further

-   [Read the .xlsx guide →](https://txtfetch.com/blog/extract-tables-for-rag)
-   [Drop a real .xlsx and see the exact text every sheet extracts to, free →](https://txtfetch.com/tools/xlsx-to-text)
-   [The wider Office-family parsing story (DOCX/PPTX/XLSX) →](https://txtfetch.com/blog/parse-office-docs-docx-pptx-xlsx-for-llms)
-   [Charset detection for plain .csv and other delimited exports →](https://txtfetch.com/extract/csv)
-   [API quickstart →](https://txtfetch.com/docs)
-   [How the pipeline works →](https://txtfetch.com/how-it-works)
-   [Extract it from your language →](https://txtfetch.com/for)
-   [Get an API key →](https://app.txtfetch.com/signup)

Office

-   [`.docx`](https://txtfetch.com/extract/docx)
-   [`.pptx`](https://txtfetch.com/extract/pptx)
-   [`.doc`](https://txtfetch.com/extract/legacy-office)
-   [`.rtf`](https://txtfetch.com/extract/rtf)
-   [All formats →](https://txtfetch.com/extract)

## Send a real .xlsx through it.

One HTTP call returns the text. Read one in your browser first, for free.

[Get an API key →](https://app.txtfetch.com/signup)

[Open the free .xlsx reader →](https://txtfetch.com/tools/xlsx-to-text)