tk-apis 0.3.1

Wrappers for some common SERP ingestion APIs we use at TK

TK APIs

This is a collection of the wrapper functions used to call various third-party, SERP-related data sources. The implementation returns things as Pandas DataFrames, because this package was written by a data scientist for data science use.

Code examples

The package contains modules for each of the APIs. You'll need to provide your own API keys; an easy way to do this is a .env file.

My examples below assume you have defined a .env and use the python-dotenv package to load in this information:

from dotenv import load_dotenv
import os

load_dotenv()

Once the credentials are in, you can load the desired module(s) and execute queries accordingly:

Moz

Note: All values of params must be lists. Strings are not accepted.

from tk_apis import moz_calls as moz

moz.get_url_data(url='https://www.terakeet.com',
                 api_key=os.environ['MOZ_AUTH'],
                 params='monthly_history_deltas': ['domain_authority'],
                 'daily_history_deltas': ['domain_authority'])

SemRush

from tk_apis import semrush_calls as sr

sr.get_related_keywords(keyword='babylonian empire', 
                        api_key=os.environ['SEMRUSH_KEY'])
sr.get_top_related_keyword(keyword='babylonian empire', 
                           api_key=os.environ['SEMRUSH_KEY'])

sr.get_keyword_data(keyword='babylonian empire', 
                    api_key=os.environ['SEMRUSH_KEY'])
sr.get_search_volume(keyword='sumerians', 
                     api_key=os.environ['SEMRUSH_KEY'])

sr.get_organic_results(keyword='babylonian empire',
                       api_key=os.environ['SEMRUSH_KEY'],
                       n=10)

sr.get_url_organic_kws(u='https://www.nordstrom.com',
                       api_key=os.environ['SEMRUSH_KEY'])

SerpApi

from tk_apis import serpapi_calls as sa

serp = sa.get_serp_result(keyword='arnold schwarzenegger', 
                          api_key=os.environ['SERPAPI_KEY'])

sa.extract_organic_df(result_set=serp)
sa.extract_knowledge_graph(result_set=serp)
sa.extract_top_stories(result_set=serp)
sa.extract_related_searches(result_set=serp)
sa.extract_related_questions(result_set=serp)