To use the new JSON mode in the OpenAI API with Python, you would modify your API call to specify the response_format parameter with the value { type: "json_object" }. This is how you tell the API that you want the response in JSON mode.

When you make a request, Requests makes educated guesses about the encoding ofthe response based on the HTTP headers. The text encoding guessed by Requestsis used when you access r.text. You can find out what encoding Requests isusing, and change it, using the r.encoding property:

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If you change the encoding, Requests will use the new value of r.encodingwhenever you call r.text. You might want to do this in any situation whereyou can apply special logic to work out what the encoding of the content willbe. For example, HTML and XML have the ability to specify their encoding intheir body. In situations like this, you should use r.content to find theencoding, and then set r.encoding. This will let you use r.text withthe correct encoding.

Requests will also use custom encodings in the event that you need them. Ifyou have created your own encoding and registered it with the codecsmodule, you can simply use the codec name as the value of r.encoding andRequests will handle the decoding for you.

In case the JSON decoding fails, r.json() raises an exception. For example, ifthe response gets a 204 (No Content), or if the response contains invalid JSON,attempting r.json() raises requests.exceptions.JSONDecodeError. This wrapper exceptionprovides interoperability for multiple exceptions that may be thrown by differentpython versions and json serialization libraries.

It should be noted that the success of the call to r.json() does notindicate the success of the response. Some servers may return a JSON object in afailed response (e.g. error details with HTTP 500). Such JSON will be decodedand returned. To check that a request is successful, user.raise_for_status() or check r.status_code is what you expect.

Using Response.iter_content will handle a lot of what you would otherwisehave to handle when using Response.raw directly. When streaming adownload, the above is the preferred and recommended way to retrieve thecontent. Note that chunk_size can be freely adjusted to a number thatmay better fit your use cases.

The data argument can also have multiple values for each key. This can bedone by making data either a list of tuples or a dictionary with listsas values. This is particularly useful when the form has multiple elements thatuse the same key:

It is strongly recommended that you open files in binarymode. This is because Requests may attempt to providethe Content-Length header for you, and if it does this valuewill be set to the number of bytes in the file. Errors may occurif you open the file in text mode.

It is also special in that the server could have sent the same header multipletimes with different values, but requests combines them so they can berepresented in the dictionary within a single mapping, as perRFC 7230:

Cookies are returned in a RequestsCookieJar,which acts like a dict but also offers a more complete interface,suitable for use over multiple domains or paths. Cookie jars canalso be passed in to requests:

You can tell Requests to stop waiting for a response after a given number ofseconds with the timeout parameter. Nearly all production code should usethis parameter in nearly all requests. Failure to do so can cause your programto hang indefinitely:

timeout is not a time limit on the entire response download;rather, an exception is raised if the server has not issued aresponse for timeout seconds (more precisely, if no bytes have beenreceived on the underlying socket for timeout seconds). If no timeout is specified explicitly, requests donot time out.

Because if i looped it from object to json or csv to json in python, it will be overhead for the application. Im building a restapi in flux which only return json will be use in our IOT platform where milisec. latency will cause trouble.

The response of the GET request contains information we called it as a payload. We can find this information in the message body. Use attributes and methods of Response to view payload in the different formats.

In the case of HTTP 500 error, some servers may return a JSON object in a failed response (e.g., error details with HTTP 500). So you should execute response.json() after checking response.raise_for_status() or check response.status_code.

In this example, I am using httpbin.org to execute a GET call. httpbin.org is a web service that allows test requests and responds with data about the request. You can use this service to test your code.

Hi, I'm getting an error when I try to use the json library to properly read a REST API response. I checked the response and it was 200 (successful). Any idea why the json library can't "find" a json object to decode?

I am using Python's json and requests libraries. The pageId variable is a stand-in for retrieving information on the page, including its id (it's also to get familiar with the format of the json object).

I know to_dict() method. What I am using now is json.dumps(response.to_dict()). I supposed it's a bit verbose, which packed es json response into py dict and by next turn it back into json. Why can't I get the json response directly?

We don't keep the json around in python. If you just want the json back what you'd need to do is use the low-level API (elasticsearch-py) and supply your own serializer that doesn't actually deserialize the json and just passes it through. To still get the benefits of the dsl library you can always serialize the Search object (by calling to_dict on it) and passing it into search method manually like .execute does.

can you append a file that has a response in it - might be easier to give you hints seeing the actual data.

Not sure if this is the case, just make sure to sanitize the json from any personal data if any.

I have a use case where the output dataset of the code recipe should be a json data. I am making an API call where the data extracted is in Json format. I don't want to convert that Json data into a pandas dataframe but want to keep the JSON data same as it is. Can you please help me know on the way how we can achieve this.

I have a data extracted from the API call and the data (call it as X) is in Json format. In a normal python recipe template the the output dataset has to be converted into a pandas data frame which is a structured format. But in my use case, I don't want to convert the data extracted which is X (in json) but yet want to be the same as the same X in Json.

I believe I understand this better now. However, is it possible for you to provide an example of "API -> Json data (X) -> output dataset (X) in json only" so I can understand more visually just to make sure?

If I am understanding this correctly, I don't believe the Flow has the ability to just show the JSON data as an output type of the python code recipe unless the JSON data is stored inside of a managed folder. In other words, DSS only allows a dataset object to represent data tabularly. To represent what I mean in a visual way:

1. Contact a DSS administrator and let them know your issue or limitations. They may be able to help you to successfully create and store the data inside of a managed folder by changing some of the permissions of DSS and/or your project settings and or group settings.

is it possible to store request json in some variable and set the variable in response Body for mock responses with example

i have req the that req or few of params i want to send in response(mocking response with example)

Using this approach, first, the environment will be updated by the Postman API in the cloud before the request is actually executed, and after that when the request is executed and hits the mock server of Postman in the cloud, the mock server will be able to resolve the updated environment value and thus return you the expected response.

This part of the documentation covers all the interfaces of Flask. Forparts where Flask depends on external libraries, we document the mostimportant right here and provide links to the canonical documentation.

The flask object implements a WSGI application and acts as the centralobject. It is passed the name of the module or package of theapplication. Once it is created it will act as a central registry forthe view functions, the URL rules, template configuration and much more.

The name of the package is used to resolve resources from inside thepackage or the folder the module is contained in depending on if thepackage parameter resolves to an actual python package (a folder withan __init__.py file inside) or a standard module (just a .py file).

The idea of the first parameter is to give Flask an idea of whatbelongs to your application. This name is used to find resourceson the filesystem, can be used by extensions to improve debugginginformation and a lot more.

Why is that? The application will work even with __name__, thanksto how resources are looked up. However it will make debugging morepainful. Certain extensions can make assumptions based on theimport name of your application. For example the Flask-SQLAlchemyextension will look for the code in your application that triggeredan SQL query in debug mode. If the import name is not properly setup, that debugging information is lost. (For example it would onlypick up SQL queries in yourapplication.app and notyourapplication.views.frontend)

By default, this returns SEND_FILE_MAX_AGE_DEFAULT fromthe configuration of current_app. This defaultsto None, which tells the browser to use conditional requestsinstead of a timed cache, which is usually preferable.

Create the Jinja environment based on jinja_optionsand the various Jinja-related methods of the app. Changingjinja_options after this will have no effect. Also addsFlask-related globals and filters to the environment.

Update the template context with some commonly used variables.This injects request, session, config and g into the templatecontext as well as everything template context processors wantto inject. Note that the as of Flask 0.6, the original valuesin the context will not be overridden if a context processordecides to return a value with the same key. 152ee80cbc

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