How to separate data in a Restful API?

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I am working on a program that reads the content of a Restful API from ImportIO. The connection works, and data is returned, but it's a jumbled mess. I'm trying to clean it to only return Asins.

I have tried using the split keyword and delimiter to no success.

stuff = requests.get('***')


I get the content, but I want to extract only Asins.


While .content gives you access to the raw bytes of the response payload, you will often want to convert them into a string using a character encoding such as UTF-8. the response will do that for you when you access .text.


Because the decoding of bytes to str requires an encoding scheme, requests will try to guess the encoding based on the response’s headers if you do not specify one. You can provide an explicit encoding by setting .encoding before accessing .text:

If you take a look at the response, you’ll see that it is actually serialized JSON content. To get a dictionary, you could take the str you retrieved from .text and deserialize it using json.loads(). However, a simpler way to accomplish this task is to use .json():


The type of the return value of .json() is a dictionary, so you can access values in the object by key.

You can do a lot with status codes and message bodies. But, if you need more information, like metadata about the response itself, you’ll need to look at the response’s headers.

For More Info:

Bulk Split Data with the API – Appen Success Center, Automating with Figure Eight REST API. Bulk Split Data with the API Calling split on this column will let Appen know that the contents of this  Resources are a higher level representation, unrelated with your data. Operating on a resource can have significant side effects, like firing an alert to a user, updating other related data, initiating a long lived process, etc. For example, we could map a file system or even the unix ps command as a REST API.

What format is the return information in? Typically Restful API's will return the data as json, you will likely have luck parsing the it as a json object.

stuff_dictionary = stuff.json()

With that, you can load the content is returned as a dictionary and you will have a much easier time.


Since I don't have the full URL to test, I can't give an exact answer. Given the content type is CSV, using a pandas DataFrame is pretty easy. With a quick StackOverflow search, I found the following answer:

So I tried the following in the terminal and got a dataframe from it

from io import StringIO
import pandas as pd

So you should be able to perform the following

from io import StringIO
import pandas as pd
df = pd.read_csv(StringIO(stuff.content))

If that doesn't work, consider dropping the first three bytes you have in your response: b'\xef\xbb\xf'. Check the answer from Mark Tolonen to get parse this.

After that, selecting the ASIN (your second column) from your dataframe should be easy.

asins = df.loc[:, 'ASIN']
asins_arr = asins.array

Should you divide a rest API into several smaller APIs (services) to , The latter would require only one request but the client might not need all the data that the request provides all the time. An example of this is for a  But as repurposing for web-forms shows, it can also be used for different types of parameters. A RESTful API could use a POST or PUT request with a body to send form data to a server. One example would be a parameter for nested representations. By default, we return a plain representation of an article.

The response is the byte string of CSV content encoded in UTF-8. The first three escaped byte codes are a UTF-8-encoded BOM signature. So stuff.content.decode('utf-8-sig') should decode it. stuff.text may also work if the encoding was returned correctly in the response headers.

Best practices for REST API design, Best practices on how to design REST APIs to be easy to understand, We can't manipulate this data as easily on the client-side, especially in  Your REST API is server code whose job it is to provide access to your data and to enforce rules like who can see what. Then other programs use your REST API to interact with your data. This high-level diagram shows how you might organize your code: you’d have a database (or multiple databases), and your REST API would sit on top of that.

RESTful API Design Tips from Experience - Peter Boyer,; ⭐️ Feel free to read it there, PATCH for updating data (with partial information for the object). may refer to a non-colliding error key separate from the body of a response. Apache Nifi is an important and powerful tool for automating data flow between systems. Importing data from a REST API in Apache Nifi is extremely useful, but can involve a significant amount of time writing, testing and maintaining a custom plugin.

Which is better solution, Conceptually, you're probably coupling data model and REST resources too much. Create separate models for all three APIs. Regardless of the REST resources, I would choose option 2, not "for all 3 API's" but because Person, Contact and  We demonstrate how to build a RESTful API on top of CQRS systems. The result joins HTTP semantics and REST style with distributed computing concerns such as eventual consistency and concurrency. BT

What is REST – Learn to create timeless REST APIs, Guiding Principles of REST. Client–server – By separating the user interface concerns from the data storage concerns, we improve the portability of the user  How to Parse JSON Data From a REST API Using a Simple JSON Library This quick tutorial will show you how you can use JAVA to leverage JSON data from a REST API and parse it as a JSON object. by