We no longer offer a standalone SAV-to-JSON converter.

Best if: you want a direct and simple SAV to JSON script.

1. Install dependencies.
2. Load your .sav file.
3. Export as JSON records.

pip install pyreadstat pandas

import pyreadstat

# Load SAV
df, meta = pyreadstat.read_sav("mydata.sav")

# Export JSON (array of records)
df.to_json("mydata.json", orient="records", force_ascii=False, indent=2)

Best if: you want a reproducible R workflow.

1. Install packages.
2. Read the .sav file.
3. Write JSON to disk.

install.packages(c("haven", "jsonlite"))
library(haven)
library(jsonlite)

df <- read_sav("mydata.sav")
write_json(df, "mydata.json", pretty = TRUE, auto_unbox = TRUE)

Best if: you want SQL-based filtering before JSON export.

1. Install and load read_stat.
2. Read SAV into DuckDB.
3. Copy query results to JSON.

INSTALL read_stat FROM community;
LOAD read_stat;

CREATE TABLE spss_data AS
FROM read_stat('mydata.sav');

COPY (
  SELECT *
  FROM spss_data
) TO 'mydata.json' (FORMAT JSON);

Best if: you need a free desktop path from SAV to structured output.

1. Open SAV in PSPP and export to CSV (SAVE TRANSLATE).
2. Convert the CSV to JSON using Python, R, or Node.
3. Validate field names and types in the output JSON.

SAVE TRANSLATE
  /OUTFILE='mydata.csv'
  /TYPE=CSV
  /FIELDNAMES
  /REPLACE.

Best if: you already use SPSS and want a familiar export flow.

1. Open your SAV file in SPSS.
2. Export to CSV via File -> Save As.
3. Convert CSV to JSON with your preferred script/tool.

Best if: your goal is insight, not just file format conversion.

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• Share findings as interactive dashboards, not static files.