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Quick Python Guide to Extracting Data from MyFantasyLeague.com API

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[开发(python) 所属分类 开发(python) | 发布者 店小二05 | 时间 2018 | 作者 红领巾 ] 0人收藏点击收藏

Introduction to API

Many organizations uses the Application Program Interface (API) to allow developer access some of their data. Access to data set via API is usually controlled by using the "API Key or client ID" which can be obtain by registering for free or at some cost.

A data set that changes quickly is better served through an API instead of a static database. To access the API data you have to send request to the remote server where the data lives. In most cases, an API data lives on the remote server in XML or JSON format.

To learn more about specific API structure make sure you take a look at it's documentation which is usually made available by the provider.

MyFantasyLeague.com API

In this post, we will take a look at the open data on MyFantasyLeague.com API. Specifically, we will send request to get the "players" data. The process discussed here will work for any request type with little or no modification.

First, before you continue I recommend you read the developer API page .

Step 1: Identify where the data lives and get its request url

From the request test page , you will that the players' data lives on this url below:-

XML =http://www03.myfantasyleague.com/2018/export?TYPE=players&DETAILS=&SINCE=&PLAYERS=&JSON=0


Quick Python Guide to Extracting Data from MyFantasyLeague.com API

JSON =http://www03.myfantasyleague.com/2018/export?TYPE=players&DETAILS=&SINCE=&PLAYERS=&JSON=1


Quick Python Guide to Extracting Data from MyFantasyLeague.com API

Step 2: Get the url and parse it into python

Now that we know where the data we needed is located, we parse it into python. I prefer using JSON, so I will use the JSON url to collect the data into pandas data frame for further processing.


Quick Python Guide to Extracting Data from MyFantasyLeague.com API

Note that you will need to identify the JSON element root and child to get hold of the data in pandas. To easily identify the element roots, use an online JSON reader such as this...


Quick Python Guide to Extracting Data from MyFantasyLeague.com API

If everything was successful, the above script should produce the dataframe table below:-


Quick Python Guide to Extracting Data from MyFantasyLeague.com API

Step 3: Do something useful with the dataframe data. You can save it to a database or CSV file.

That is it!

本文开发(python)相关术语:python基础教程 python多线程 web开发工程师 软件开发工程师 软件开发流程

tags: data,API,JSON,amp,will,request,com,url
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