|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Go Dork||677||6 months ago||4||April 03, 2021||4||mit||Go|
|The fastest dork scanner written in Go.|
|Nboost||439||3 years ago||26||June 12, 2020||18||apache-2.0||Python|
|NBoost is a scalable, search-api-boosting platform for deploying transformer models to improve the relevance of search results on different platforms (i.e. Elasticsearch)|
|Alfred Web Search Suggest||330||3 months ago||1||mit||PHP|
|Alfred search suggest workflow for various popular websites.|
|Gmusicproxy||317||2 years ago||15||gpl-3.0||Python|
|Google Play Music Proxy - "Let's stream Google Play Music using any media-player"|
|Cloudbunny||279||2 years ago||2||mit||Python|
|CloudBunny is a tool to capture the real IP of the server that uses a WAF as a proxy or protection. In this tool we used three search engines to search domain information: Shodan, Censys and Zoomeye.|
|Pallas||240||1||2 years ago||4||August 06, 2019||113||Java|
|Curator is to Zookeeper what Pallas is to Elasticsearch|
|Guppy Proxy||111||4 years ago||1||mit||Python|
|The Guppy Proxy (GUI Pappy)|
|Google Places||81||3||5 years ago||3||February 02, 2018||7||other||PHP|
|PHP wrapper class for the Google Places API|
|Google Search SERP Scraper|
|Wp Json Scraper||60||a year ago||2||mit||Python|
|Scrapes WordPress data using the WP-JSON API activated by default since WordPress 4.7|
The Amundsen project moved to a monorepo. This repository will be kept up temporarily to allow users to transition gracefully, but new PRs won't be accepted.
Amundsen Search service serves a Restful API and is responsible for searching metadata. The service leverages Elasticsearch for most of it's search capabilites.
For information about Amundsen and our other services, visit the main repository
README.md. Please also see our instructions for a quick start setup of Amundsen with dummy data, and an overview of the architecture.
$ venv_path=[path_for_virtual_environment] $ python3 -m venv $venv_path $ source $venv_path/bin/activate $ pip3 install amundsen-search $ python3 search_service/search_wsgi.py # In a different terminal, verify the service is up by running $ curl -v http://localhost:5001/healthcheck
$ git clone https://github.com/amundsen-io/amundsensearchlibrary.git $ cd amundsensearchlibrary $ venv_path=[path_for_virtual_environment] $ python3 -m venv $venv_path $ source $venv_path/bin/activate $ pip3 install -r requirements.txt $ python3 setup.py install $ python3 search_service/search_wsgi.py # In a different terminal, verify the service is up by running $ curl -v http://localhost:5001/healthcheck
$ docker pull amundsendev/amundsen-search:latest $ docker run -p 5001:5001 amundsendev/amundsen-search # - alternative, for production environment with Gunicorn (see its homepage link below) $ ## docker run -p 5001:5001 amundsendev/amundsen-search gunicorn --bind 0.0.0.0:5001 search_service.search_wsgi # In a different terminal, verify the service is up by running $ curl -v http://localhost:5001/healthcheck
By default, Flask comes with a Werkzeug webserver, which is used for development. For production environments a production grade web server such as Gunicorn should be used.
$ pip3 install gunicorn $ gunicorn search_service.search_wsgi # In a different terminal, verify the service is up by running $ curl -v http://localhost:8000/healthcheck
For more imformation see the Gunicorn configuration documentation.
By default, Search service uses LocalConfig that looks for Elasticsearch running in localhost.
In order to use different end point, you need to create a Config suitable for your use case. Once a config class has been created, it can be referenced by an environment variable:
For example, in order to have different config for production, you can inherit Config class, create Production config and passing production config class into environment variable. Let's say class name is ProdConfig and it's in search_service.config module. then you can set as below:
This way Search service will use production config in production environment. For more information on how the configuration is being loaded and used, here's reference from Flask doc.
We have Swagger documentation setup with OpenApi 3.0.2. This documentation is generated via Flasgger.
When adding or updating an API please make sure to update the documentation. To see the documentation run the application locally and go to
Currently the documentation only works with local configuration.
Amundsen Search service consists of three packages, API, Models, and Proxy.
A package that contains Flask Restful resources that serves Restful API request. The routing of API is being registered here.
Proxy package contains proxy modules that talks dependencies of Search service. There are currently two modules in Proxy package, Elasticsearch and Statsd.
Elasticsearch proxy module serves various use case of searching metadata from Elasticsearch. It uses Query DSL for the use case, execute the search query and transform into model.
Apache Atlas proxy module uses Atlas to serve the Atlas requests. At the moment the Basic Search REST API is used via the Python Client.
Statsd utilities module has methods / functions to support statsd to publish metrics. By default, statsd integration is disabled and you can turn in on from Search service configuration. For specific configuration related to statsd, you can configure it through environment variable.
Models package contains many modules where each module has many Python classes in it. These Python classes are being used as a schema and a data holder. All data exchange within Amundsen Search service use classes in Models to ensure validity of itself and improve readability and maintainability.