Singer tap that extracts data from LinkedIn Sales Navigator and produces JSON-formatted data following the Singer spec.
To make this Tap work with a Target, clone both projects and follow these instructions:
This section dives into basic usage of tap-linkedin
by walking through extracting
data from a table. It assumes that you have access to LinkedIn Sales Navigator.
python3 -m venv ~/.virtualenvs/tap-linkedin
source ~/.virtualenvs/tap-linkedin/bin/activate
pip install -e .
Configuration Key | Description |
---|---|
keyword | The keyword to search for in Sales Navigator. |
cookie | Your LinkedIn cookie |
x_li_identity | Your LinkedIn x-li-identity |
csrf_token | Your LinkedIn csrf-token |
{
"keyword": "keywork",
"cookie": "cookie",
"x_li_identity": "x_li_identity",
"csrf_token": "csrf_token"
}
The tap can be invoked in discovery mode to find the available tables and columns in the database:
$ tap-linkedin --config config.json --discover >> catalog.json
A discovered catalog is output, with a JSON-schema description of each table. A source table directly corresponds to a Singer stream.
The selected-by-default
fields is used to enable the sync of the tables. If set to 'true', all of the tables will be
selected in the catalog.json
git clone https://github.com/datamill-co/target-postgres
cd target-postgres
python3 -m venv ~/.virtualenvs/target-postgres
source ~/.virtualenvs/target-postgres/bin/activate
pip install target-postgres
From the home directory of the project
tap-linkedin -c config.json --catalog catalog.json | ~/.virtualenvs/target-postgres/bin/target-postgres