The Tool Desk
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Choose the CLI or Python
Use the CLI if you want to run SQL interactively from a terminal. Choose Python if your query belongs in a script or notebook. Both routes can query the same CSV directly; the right choice depends on your workflow, not a blanket performance ranking.
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| Route | Setup | Good fit |
|---|---|---|
| CLI | Download and unzip DuckDB, then run the executable. | Quick interactive SQL in a terminal. |
| Python | Install the duckdb package with pip or conda. |
Queries in Python scripts and notebooks. |
DuckDB’s installation page lists 1.5.6 as the current stable release and 1.4.5 as LTS; these labels reflect the page at the time of writing and can change. See DuckDB installation options.
Install and start the CLI
The CLI is a single executable for Windows, macOS, and Linux. The official guide offers installation scripts, direct downloads, and Docker. For a direct download, choose the build for your operating system, unzip it, open a terminal in the extracted directory, and run the executable. In a POSIX shell, the command is ./duckdb; on Windows, run the downloaded executable from Command Prompt or PowerShell.
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Run duckdb without a database filename to open a temporary in-memory database. If you want queries or tables to use a database file, provide its filename when starting the CLI, for example duckdb analytics.db. Consult the CLI guide for platform-specific details.
Install the Python package
DuckDB’s Python overview documents Python 3.9 or newer. Install with either pip or conda:
pip install duckdbconda install python-duckdb -c conda-forgeThe Python overview labels its client version 1.5.5, while the installation page lists 1.5.6 as current stable; those page labels are not necessarily the same release snapshot. See the Python API overview.
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Query a CSV by its path
In the CLI, run SQL using the CSV filename as the relation:
SELECT * FROM 'data.csv';The equivalent explicit reader syntax is:
SELECT * FROM read_csv('data.csv');In Python, import the package and execute the query:
import duckdb
duckdb.sql("SELECT * FROM 'data.csv'").show()You can also read the CSV as a relation with duckdb.read_csv("data.csv"). These forms read the file directly; they do not create a persistent database table. Replace data.csv with a path relative to the process’s working directory or with an absolute path. If DuckDB cannot find the file, check the working directory and path spelling. The CSV import guide documents direct querying and loading options, and the Python data-ingestion guide covers Python reader usage.
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Check CSV inference if results look wrong
DuckDB attempts to detect a CSV’s delimiter, quoting and escaping rules, header presence, and column types. Its documented default type-inference sample is 20,480 rows (DuckDB documentation; publication year not stated). Because inference is sample-based, a column that changes type later in the file may not be interpreted as you expect.
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For regular files, DuckDB can sample from different positions. For non-seekable inputs such as gzip CSV or standard input, samples come from the beginning. If later rows may differ, inspect the inferred types rather than assuming the first rows represent the whole file.
- Run
sniff_csv('data.csv')to inspect the detected settings and a suggested reader prompt. - Set reader options explicitly when needed, such as
delimfor a nonstandard delimiter orheaderwhen header detection is wrong. - Specify column types when automatic type inference does not match the data.
- Use
sample_size = -1to sample the full file when that trade-off is appropriate; larger files may take longer to inspect.
The CSV auto-detection guide explains inference and its options.
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Use a persistent table only when you need one
Direct path queries are convenient for one-off analysis. To keep a table in a DuckDB database, create it from the CSV with:
CREATE TABLE my_table AS
SELECT * FROM 'data.csv';DuckDB also documents COPY and INSERT INTO ... SELECT for loading data into an existing table. The distinction is whether you want a reusable table in a database, not whether DuckDB is capable of importing the file. See Importing Data.
Read compressed or remote CSV files
Local gzip files
DuckDB documents direct reading of local gzip-compressed CSV files by filename. Use the compressed file path in a query as you would a local CSV path.
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HTTP(S) files
Reading a CSV over HTTP or HTTPS requires DuckDB’s httpfs extension. Install and load it in the CLI or SQL session, then query the remote path:
INSTALL httpfs;
LOAD httpfs;
SELECT * FROM read_csv('https://example.org/data.csv');Replace the example URL with the actual CSV address. The HTTP CSV import guide covers this setup.
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