
In SQL: The Common Solvent for REST APIs we noticed how Steampipe’s suite of open-source plugins that translate REST API calls immediately into SQL tables. These plugins have been, till just lately, tightly certain to the open-source engine and to the occasion of Postgres that it launches and controls. That led members of the Steampipe neighborhood to ask: “Can we use the plugins in our personal Postgres databases?” Now the reply is sure—and extra—however let’s deal with Postgres first.
NOTE: Every Steampipe plugin ecosystem is now additionally a standalone foreign-data-wrapper extension for Postgres, a virtual-table extension for SQLite, and an export device.

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Utilizing a Steampipe Plugin as a Standalone Postgres International Information Wrapper (FDW)
Go to Steampipe downloads to search out the installer on your OS, and run it to accumulate the Postgres FDW distribution of a plugin—on this case, the GitHub plugin. It’s considered one of (at present) 140 plugins out there on the Steampipe hub. Every plugin supplies a set of tables that map API calls to database tables—within the case of the GitHub plugin, 55 such tables. Every desk can seem in a FROM
or JOIN
clause; right here’s a question to pick columns from the GitHub situation, filtering on a repository and writer.
choose
state,
updated_at,
title,
url
from
github_issue
the place
repository_full_name="turbot/steampipe"
and author_login = 'judell'
order by
updated_at desc
If you happen to’re utilizing Steampipe you’ll be able to set up the GitHub plugin like this:
steampipe plugin set up github
then run the question within the Steampipe CLI, or in any Postgres shopper that may hook up with Steampipe’s occasion of Postgres.
However if you wish to do the identical factor in your individual occasion of Postgres you’ll be able to set up the plugin another way.
$ sudo /bin/sh -c "$(
curl -fsSL https://steampipe.io/set up/postgres.sh)"
Enter the plugin identify: github
Enter the model (newest):
Found:
- PostgreSQL model: 14
- PostgreSQL location: /usr/lib/postgresql/14
- Working system: Linux
- System structure: x86_64
Based mostly on the above, steampipe_postgres_github.pg14.linux_amd64.tar.gz
might be downloaded, extracted and put in at: /usr/lib/postgresql/14
Proceed with putting in Steampipe PostgreSQL FDW for model 14 at
/usr/lib/postgresql/14?
- Press 'y' to proceed with the present model.
- Press 'n' to customise your PostgreSQL set up listing
and choose a unique model. (Y/n):
Downloading steampipe_postgres_github.pg14.linux_amd64.tar.gz...
###############################################################
############################ 100.0%
steampipe_postgres_github.pg14.linux_amd64/
steampipe_postgres_github.pg14.linux_amd64/steampipe_postgres_
github.so
steampipe_postgres_github.pg14.linux_amd64/steampipe_postgres_
github.management
steampipe_postgres_github.pg14.linux_amd64/steampipe_postgres_
github--1.0.sql
steampipe_postgres_github.pg14.linux_amd64/set up.sh
steampipe_postgres_github.pg14.linux_amd64/README.md
Obtain and extraction accomplished.
Putting in steampipe_postgres_github in /usr/lib/postgresql/14...
Efficiently put in steampipe_postgres_github extension!
Recordsdata have been copied to:
- Library listing: /usr/lib/postgresql/14/lib
- Extension listing: /usr/share/postgresql/14/extension/
Now hook up with your server as ordinary, utilizing psql
or one other shopper, most usually because the postgres
consumer. Then run these instructions that are typical for any Postgres overseas knowledge wrapper. As with all Postgres extensions, you begin like this:
CREATE EXTENSION steampipe_postgres_fdw_github;
To make use of a overseas knowledge wrapper, you first create a server:
CREATE SERVER steampipe_github FOREIGN DATA WRAPPER
steampipe_postgres_github OPTIONS (config 'token="ghp_..."');
Use OPTIONS to configure the extension to make use of your GitHub entry token. (Alternatively, the usual surroundings variables used to configure a Steampipe plugin—it’s simply GITHUB_TOKEN
on this case—will work when you set them earlier than beginning your occasion of Postgres.)
The tables supplied by the extension will stay in a schema, so outline one:
CREATE SCHEMA github;
Now import the schema outlined by the overseas server into the native schema you simply created:
IMPORT FOREIGN SCHEMA github FROM SERVER steampipe_github INTO github;
Now run a question!
The overseas tables supplied by the extension stay within the github schema
, so by default you’ll consult with tables like github.github_my_repository
. If you happen to set search_path="github"
, although, the schema turns into non-obligatory and you’ll write queries utilizing unqualified desk names. Right here’s a question we confirmed final time. It makes use of the github_search_repository which encapsulates the GitHub API for looking repositories.
Suppose you’re searching for repos associated to PySpark. Right here’s a question to search out repos whose names match pyspark, and report a couple of metrics that will help you gauge exercise and recognition.
choose
name_with_owner,
updated_at, -- how just lately up to date?
stargazer_count -- how many individuals starred the repo?
from
github_search_repository
the place
question = 'pyspark in:identify'
order by
stargazer_count desc
restrict 10;
+---------------------------------------+------------+---------------+
|name_with_owner |updated_at |stargazer_count|
+---------------------------------------+------------+---------------+
| AlexIoannides/pyspark-example-project | 2024-02-09 | 1324 |
| mahmoudparsian/pyspark-tutorial | 2024-02-11 | 1077 |
| spark-examples/pyspark-examples | 2024-02-11 | 1007 |
| palantir/pyspark-style-guide | 2024-02-12 | 924 |
| pyspark-ai/pyspark-ai | 2024-02-12 | 791 |
| lyhue1991/eat_pyspark_in_10_days | 2024-02-01 | 719 |
| UrbanInstitute/pyspark-tutorials | 2024-01-21 | 400 |
| krishnaik06/Pyspark-With-Python | 2024-02-11 | 400 |
| ekampf/PySpark-Boilerplate | 2024-02-11 | 388 |
| commoncrawl/cc-pyspark | 2024-02-12 | 361 |
+---------------------------------------+------------+---------------+
You probably have a number of repos, the primary run of that question will take a couple of seconds. The second run will return outcomes immediately, although, as a result of the extension features a highly effective and complicated cache.
And that’s all there may be to it! Each Steampipe plugin is now additionally a overseas knowledge wrapper that works precisely like this one. You possibly can load a number of extensions with a purpose to be a part of throughout APIs. In fact you’ll be able to be a part of any of those API-sourced overseas tables with your individual Postgres tables. And to avoid wasting the outcomes of any question, you’ll be able to prepend “create desk NAME as” or “create materialized view NAME as” to a question to persist outcomes as a desk or view.
Utilizing a Steampipe Plugin as a SQLite Extension that Offers Digital Tables
Go to Steampipe downloads to search out the installer on your OS and run it to accumulate the SQLite distribution of the identical plugin.
$ sudo /bin/sh -c "$(curl -fsSL https://steampipe.io/set up/sqlite.sh)"
Enter the plugin identify: github
Enter model (newest):
Enter location (present listing):
Downloading steampipe_sqlite_github.linux_amd64.tar.gz...
############################################################
################ 100.0%
steampipe_sqlite_github.so
steampipe_sqlite_github.linux_amd64.tar.gz downloaded and
extracted efficiently at /dwelling/jon/steampipe-sqlite.
Right here’s the setup, and you’ll place this code in ~/.sqliterc
if you wish to run it each time you begin sqlite
.
.load /dwelling/jon/steampipe-sqlite/steampipe_sqlite_github.so
choose steampipe_configure_github('
token="ghp_..."
');
Now you’ll be able to run the identical question as above. Right here, too, the outcomes are cached, so a second run of the question might be on the spot.
What in regards to the variations between Postgres-flavored and SQLite-flavored SQL? The Steampipe hub is your buddy! For instance, listed below are Postgres and SQLite variants of a question that accesses a area inside a JSON column with a purpose to tabulate the languages related along with your gists.
Postgres

SQLite

The github_my_gist desk reviews particulars about gists that belong to the GitHub consumer who’s authenticated to Steampipe. The language related to every gist lives in a JSONB column referred to as information, which comprises an inventory of objects like this.
"measurement": 24541,
"kind": "textual content/markdown",
"raw_url": "https://gist.githubusercontent.com/judell/49d66ca2a5d2a3b
"filename": "steampipe-readme-update.md",
"language": "Markdown"
The features wanted to undertaking that record as rows differ: in Postgres you utilize jsonb_array_elements
and in SQLite it’s json_each
.
As with Postgres extensions, you’ll be able to load a number of SQLite extensions with a purpose to be a part of throughout APIs. You possibly can be a part of any of those API-sourced overseas tables with your individual SQLite tables. And you’ll prepend create desk NAME as
to a question to persist outcomes as a desk.
Utilizing a Steampipe Plugin as a Standalone Export Instrument
Go to Steampipe downloads to search out the installer on your OS, and run it to accumulate the export distribution of a plugin—once more, we’ll illustrate utilizing the GitHub plugin.
$ sudo /bin/sh -c "$(curl -fsSL https://steampipe.io/set up/export.sh)"
Enter the plugin identify: github
Enter the model (newest):
Enter location (/usr/native/bin):
Created non permanent listing at /tmp/tmp.48QsUo6CLF.
Downloading steampipe_export_github.linux_amd64.tar.gz...
##########################################################
#################### 100.0%
Deflating downloaded archive
steampipe_export_github
Putting in
Making use of mandatory permissions
Eradicating downloaded archive
steampipe_export_github was put in efficiently to
/usr/native/bin
$ steampipe_export_github -h
Export knowledge utilizing the github plugin.
Discover detailed utilization info together with desk names,
column names, and examples on the Steampipe Hub:
https://hub.steampipe.io/plugins/turbot/github
Utilization:
steampipe_export_github TABLE_NAME [flags]
Flags:
--config string Config file knowledge
-h, --help assist for steampipe_export_github
--limit int Restrict knowledge
--output string Output format: csv, json or jsonl
(default "csv")
--select strings Column knowledge to show
--where stringArray the place clause knowledge
There’s no SQL engine within the image right here, this device is solely an exporter. To export all of your gists to a JSON file:
steampipe_export_github github_my_gist --output json > gists.json
To pick out just some columns and export to a CSV file:
steampipe_export_github github_my_gist --output csv --select
"description,created_at,html_url" > gists.csv
You should use --limit
to restrict the rows returned, and --where
to filter them, however largely you’ll use this device to shortly and simply seize knowledge that you just’ll therapeutic massage elsewhere, for instance, in a spreadsheet.
Faucet into the Steampipe Plugin Ecosystem
Steampipe plugins aren’t simply uncooked interfaces to underlying APIs. They use tables to mannequin these APIs in helpful methods. For instance, the github_my_repository
desk exemplifies a design sample that applies persistently throughout the suite of plugins. From the GitHub plugin’s documentation:
You possibly can personal repositories individually, or you’ll be able to share possession of repositories with different individuals in a company. The
github_my_repository
desk will record repos that you just personal, that you just collaborate on, or that belong to your organizations. To question ANY repository, together with public repos, use thegithub_repository
desk.
Different plugins observe the identical sample. For instance, the Microsoft 365 plugin supplies each microsoft_my_mail_message
and microsoft_mail_message
, and the plugin supplies googleworkspace_my_gmail_message
and googleworkspace_gmail
. The place doable, plugins consolidate views of sources from the attitude of an authenticated consumer.
Whereas plugins usually present tables with mounted schemas, that’s not at all times the case. Dynamic schemas, carried out by the Airtable, CSV, Kubernetes, and Salesforce plugins (amongst others) are one other key sample. Right here’s a CSV instance utilizing a standalone Postgres FDW.
IMPORT FOREIGN SCHEMA csv FROM SERVER steampipe_csv INTO csv
OPTIONS(config 'paths=["/home/jon/csv"]');
Now all of the .csv
information in /dwelling/jon/csv
will automagically be Postgres overseas tables. Suppose you retain monitor of legitimate house owners of EC2 cases in a file referred to as ec2_owner_tags
. Right here’s a question in opposition to the corresponding desk.
choose * from csv.ec2_owner_tags;
proprietor | _ctx
----------------+----------------------------
Pam Beesly | "connection_name": "csv"
Dwight Schrute | "connection_name": "csv"
You may be a part of that desk with the AWS plugin’s aws_ec2_instance
desk to report proprietor tags on EC2 cases which can be (or are usually not) listed within the CSV file.
choose
ec2.proprietor,
case
when csv.proprietor is null then 'false'
else 'true'
finish as is_listed
from
(choose distinct tags ->> 'proprietor' as proprietor
from aws.aws_ec2_instance) ec2
left be a part of
csv.ec2_owner_tags csv on ec2.proprietor = csv.proprietor;
proprietor | is_listed
----------------+-----------
Dwight Schrute | true
Michael Scott | false
Throughout the suite of plugins there are greater than 2,300 pre-defined fixed-schema tables that you need to use in these methods, plus a limiteless variety of dynamic tables. And new plugins are continually being added by Turbot and by Steampipe’s open-source neighborhood. You possibly can faucet into this ecosystem utilizing Steampipe or Turbot Pipes, from your individual Postgres or SQLite database, or immediately from the command line.