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Json.Decoder.Jsondecodeerror: Expecting Value: Line 1 Column 1 (Char 0)

Json.Decoder.Jsondecodeerror: Expecting Value: Line 1 Column 1 (Char 0)

Json.Decoder.Jsondecodeerror: Expecting Value: Line 1 Column 1 (Char 0): When working with the JSON (JavaScript Object Notation) format, the error JSONDecodeError: Expecting value: line 1 column 1 (char 0) occurs.

You might be trying to retrieve JSON data from an API (application programming interface) or storing some JSON data. We will go over potential entry points and solutions in this article.

How can JSONDecodeError: Expecting value: line 1 column 1 (char 0) occur?

JSONDecodeError indicates that the JSON format is being used incorrectly. A curly bracket might need to be included, a key might not have a value, data might not be encased in double quotes, or there could be another syntax issue in the JSON data.

Generally, the error expecting value: line 1 column 1 (char 0) error can occur for the following reasons.

  • Non-JSON conforming quoting
  • Empty JSON file
  • XML output (that is, a string starting with <)

Let’s elaborate on the points stated above:

1. Non-JSON conforming quoting

The format of the Python dictionary datatype is similar to that of JSON, or JavaScript Object Notation. A dictionary requires a key or value to be wrapped in quotes if a key or value is a string. The JSON standard stipulates that keys do not have to be strings.

Keys, however, must always be encapsulated in double quotations. A problem may arise if this criteria is not followed.

2. Empty JSON file

We’ve used a file that is empty and a second file that has the code listed below for this example. We open the JSON file in reading mode using context manager and load it with the load method. However, since the JSON file is empty, an error is raised.

3. XML output (that is, a string starting with <)

A straightforward text-based format called XML, also known as Extensible Markup Language, is used to represent structured data, including documents, data, configuration, books, transactions, invoices, and much more.

It is an older method of storing data, much like JSON. While earlier APIs returned data in XML format, JSON is currently the preference standard. Let’s look at how to handle the anticipated value in this scenario, which is line 1 column 1 (char 0).

Let’s break down what is happening here.

  • For ease of example, suppose API returns an XML format data, as shown above.
  • Now, when we try to load that response from API, we will get a type error.

Resolving JSONDecodeError: Expecting value: line 1 column 1 (char 0)

1. Solution for Non-JSON conforming quoting

It would be best if you made sure that the keys and values are encapsulated within the double quotes in order to fix the type problem in this situation.

Because it is a requirement of the JSON syntax, this is necessary. It’s crucial to understand that JSON only use double quotes and never single ones.

2. Solution for empty JSON file

The name alone should provide the answer. Verify that the JSON file or the API response is not empty in order to fix the type issue in this situation.

If the file is empty, fill it with content and, for an API response, use try-except to handle the error, which could, for example, be empty JSON or a 404 error.

The function mentioned above accepts a term and outputs all associated data in JSON format. Now we have changed the URL to demonstrate how we can deal with the Expecting value: line 1 column 1 (char 0) type error. Enties have replaced entries.

As a result, we will not receive a proper response in JSON format. However, the purpose of this is merely to simulate the error that could occur if an API returns an invalid response.

  • Now, if you try to run the code above, you will be prompted to enter a word. The response is saved into the data variable and later converted to a string.
  • However, in the try block json.loads method, which parses JSON string to python dictionary raises an error.
  • This is because the response sent by API is not of JSON format, hence can’t be parsed, resulting in JSONDecodeError.
  • JSONDecodeError gets handled by the try-except block, and a “Response content is not valid JSON”gets printed as an outcome.

3. Solution for XML output(that is, a string starting with <)

To avoid type errors resulting from an XML format, we will convert it to a JSON format. However, firstly install this library.

Let’s elaborate on the code above:

  • We have imported two libraries, namely JSON and xmltodict.
  • Using the context manager with, XML file test.xml is opened in read mode. Thereafter using the xmltodict parse method, it is converted to a dictionary type, and the file is closed.
  • dumps() takes in a JSON object and returns a string of that object.
  • Again using context manager with, a JSON file is created, XML data that was converted to a JSON string is written on it, and the file is closed.

JSONDecodeError: Expecting value: line 1 column 1 (char 0) Django

The failure of Pipenv 2018.10.9 causes this issue. To resolve this issue, use Pipenv 2018.5.18. For more, read here.

Are you facing this error in Flask?

The data from HTTP requests is frequently fetched as bytes when you get it. Therefore, you can be dealing with a JSON in bytes if you see a JSONDecodeError.

First, you must use response.decode(‘utf-8’) to decode the JSON. You can parse the string that is produced as a result of this.


How to parse JSON in python?

json.loads() method can be used to parse JSON in python. For instance:
import json
json_string = ‘{“a”:”1″, “b”:”2″, “c”:”3″}’
json_to_dict = json.loads(json_string)

How to detect empty file/string before parsing JSON?

import os
file_path = “/home/nikhilomkar/Desktop/test.json”
print(“File is empty!” if os.stat(file_path).st_size == 0 else “File isn’t empty!”)
The following code checks, if the file is empty and prints the File, is empty! If true, else, the File isn’t empty!

Conclusion JSONDecodeError: Expecting value: line 1 column 1 (char 0)

The JSONDecodeError was covered in the article below: Expecting value: char 0 on line 1 of column 1. Numerous decoding and formatting mistakes are to blame for this problem. We examined possible scenarios where it might happen and solutions.

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