duckgate
Interactive SQL shell over S3 data (Parquet, Iceberg, CSV) using DuckDB.
What duckgate adds on top of DuckDB
The SQL engine is unmodified DuckDB — every query, join, and function runs exactly as it
would in the duckdb CLI. duckgate is a thin orchestration layer that solves a narrower
problem: querying an AWS Glue Data Catalog full of S3 tables without hand-writing paths.
| Plain DuckDB | duckgate | |
|---|---|---|
| Discover tables | Write read_parquet('s3://...') per path, by hand |
duckgate tables lists everything from Glue + local config |
| AWS credentials | SET s3_access_key_id=... or CREATE SECRET, manually |
Resolved automatically from an AWS profile (SSO or static) |
| Hyphenated names | You quote the identifier yourself | Quoted automatically (CREATE VIEW "name-with-hyphens") |
| Glue location with no wildcard | read_parquet won't expand it — "no files found" |
**/*.<format> appended automatically |
| Point at another environment | Rewrite the query with a different path | [[tables]] overrides a Glue table by name, no catalog edits |
| Registering many tables | N/A — you only use what you write | Lazy, on-demand, once per session |
| One broken table (bad perms, empty) | You just don't query what you don't know about | Rest of the catalog keeps working, warning printed |
Query with no LIMIT |
No warning | Warned on stderr (-q and the shell) |
Where plain DuckDB already holds its own: the duckdb CLI has its own polished interactive
shell (history, autocomplete, .mode) and a -c "query" one-shot flag. duckgate's shell is
simpler — its value is coming with the Glue catalog already wired in, not out-shelling DuckDB.
Install
duckgate is a CLI tool, so an isolated install is recommended over a bare pip install:
uv tool install duckgate
# or
pipx install duckgate
Quick start
duckgate init # prompts for a config path (default: ~/.duckgate/config.toml)
duckgate tables # list available tables
duckgate describe my_table # show a table's schema, no registration
duckgate # open interactive shell
duckgate -q "SELECT COUNT(*) FROM my_table" # one-shot query
duckgate init accepts Enter to take the suggested default, or a path you type (e.g. a local
duckgate.toml for a per-project override). Pass -p/--path to skip the prompt entirely —
handy in scripts: duckgate init --path duckgate.toml.
Configuration
duckgate.toml in the current directory, falling back to ~/.duckgate/config.toml:
[aws]
profile = "my-aws-profile"
region = "eu-central-1"
[glue]
enabled = true
databases = [] # empty = all databases
[[tables]]
name = "fis_location"
path = "s3://my-bucket/structured/sqlserver/dev/fis/location/**/*.parquet"
format = "parquet" # parquet | iceberg | csv
Table resolution
- Glue tables are discovered automatically from the configured databases. A bare Glue
table location (no wildcard) is read as
location/**/*.<format>. - Local
[[tables]]entries override Glue tables with the same name — use this to point to a specific environment prefix. - If two Glue tables from different databases share a name, they are registered as
database__table_name. duckgate tableslists what the catalog discovers (what Glue/your config advertises), not just tables that are actually queryable. A table with no matching files or bad permissions will still show up in the list and only fails when you query it.- Tables are registered lazily: a table's DuckDB view is created only the first time a query
references it in a session (
-qruns once per process; the shell keeps this per session, so a repeated reference to the same table costs nothing).
Query safety
-q and the shell print a warning to stderr when a query has no LIMIT clause. This only
flags the risk — it doesn't rewrite the query, and it can't help an aggregate
(COUNT(*), GROUP BY) that has to scan the whole table regardless of any LIMIT.
AWS credentials
Uses the AWS profile from [aws] profile, resolved via boto3.Session(profile_name=...).
Works with aws sso login and static credentials directly. Tools that only export temporary
credentials into your shell's environment (e.g. Granted assume) are not picked up,
since a named profile lookup ignores ambient environment variables — configure the profile's
credential_process if you want a tool like that to work transparently.
Supported formats
| Format | How |
|---|---|
| Parquet | read_parquet('s3://...') via httpfs |
| Iceberg | iceberg_scan('s3://...') via the iceberg extension |
| CSV | read_csv('s3://...') via httpfs |
Development
make sync # uv sync
make test # run the test suite
make lint # ruff check --fix
make format # ruff format
make check # lint + format + test + clean (run before every commit)
Release
Pushing a v* tag (e.g. v0.1.0) builds and publishes to PyPI via GitHub Actions, using
PyPI Trusted Publishing (see .github/workflows/publish.yml). Bump __version__ in
duckgate/__init__.py to match before tagging.
License
Apache License 2.0 — see LICENSE.
Metadata
Release files for duckgate 0.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| duckgate-0.3.1.tar.gz | 144.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| duckgate-0.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 157.9 kB
Release files / duckgate-0.3.1.tar.gz
| Download URL | duckgate-0.3.1.tar.gz |
|---|---|
| Size | 144.5 kB |
| Tags | Source |
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| Download URL | duckgate-0.3.1-py3-none-any.whl |
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| Size | 13.4 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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| Uploaded via |
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