#ResBaz2019 Workshop - Accessing APIs using R

Transcript

1. ACCESSING APIS USING R Manish Kukreja https://datamak.ml #ResBaz2019 https://resbaz.auckland.ac.nz/schedule/#session-018

2. BACKGROUND ON APIS • API stands for Application Programming Interface

   • GUI or CLI is for human-computer interaction • API is for program-program interaction • Some examples • Get data and plot it • Add a node to a computing cluster • Recognize faces as soon as an image is uploaded • APIs used on the web are mostly HTTP RESTful APIs or REST APIs

3. REST API path to the endpoint http://example.com/api/v2/fetch/data URL to a

   domain

4. HTTP VERBS • POST – used to create a record,

   data is passed using JSON or XML • GET – read single or list of records, response can be JSON or XML • PUT – update/replace single or entire list of records • PATCH – update/modify single or entire list of records • DELETE – delete the whole collection

5. STEPS TO ACCESS API 1. Obtain the key for using

   the web service 2. Find the URL and endpoint path of the API 3. Convert input data to JSON format using toJSON() in the jsonlite package [optional] 4. Send input data to the API service using the appropriate HTTP VERB function in the httr package. Include API key in the function call. 5. Extract your results from the API response using the fromJSON() function

6. JOIN THE WORKSPACE IN RSTUDIO.CLOUD https://tiny.cc/resbaz-api

7. JOIN THE WORKSPACE IN RSTUDIO.CLOUD

8. JOIN THE WORKSPACE IN RSTUDIO.CLOUD

9. JOIN THE WORKSPACE IN RSTUDIO.CLOUD

10. JOIN THE WORKSPACE IN RSTUDIO.CLOUD

11. JOIN THE WORKSPACE IN RSTUDIO.CLOUD

12. 1. OBTAIN THE SECRET KEY https://darksky.net/dev/register

13. 2. FIND URL AND ENDPOINT PATH https://darksky.net/dev/docs#forecast-request

14. 3. CONVERT INPUT DATA TO JSON SKIPPED

15. 4. SEND REQUEST •Send GET request •Check response

16. 5. EXTRACT RESULTS FROM RESPONSE •Use httr::content() to extract data

    from response object •Transform it for easy manipulation •Visualize, merge or analyse it

17. WORKSHOP CODE • Darksky weather forecast API notebook • https://datamak.ml/projects/data-analysis/Darksky-API

    • Microsoft sentiment analysis API notebook • https://datamak.ml/projects/data-analysis/Sentiment-API

18. THANK YOU