Troubleshooting Python Dateparser : Attribute Error

Python, a versatile and powerful programming language celebrated for its extensive libraries and packages, often sees programmers utilizing the “dateparser” library for parsing date and time strings. Nonetheless, some users might face issues like the “AttributeError: ‘safe_load()’ has removed.” This blog post delves into this error, its origins, and how to rectify it.

Understanding the Attribute Error:

To resolve ‘AttributeError: ‘safe_load()’ has been removed’ error when using dateparser, you need to update your PyYAML library to a version that employs the ‘load()’ method with the necessary security features.

Causes of the Error:

The error arises from changes made in in the PyYAML library. In older versions of PyYAML, the method “safe_load()” was used to parse YAML files safely. However, PyYAML deprecated this method in favor of using “load()” with additional security measures. Dateparser may rely on PyYAML internally, and if you have an older PyYAML version installed, you may encounter this error.

How to Resolve the AttributeError:

Follow these steps:

  1. Update PyYAML: Check your current PyYAML version using the following command:
   pip show pyyaml

To update PyYAML, use the following command:

   pip install --upgrade pyyaml
  1. Check for Dateparser Updates: Make sure you have the latest version of dateparser by running:
   pip install --upgrade dateparser
  1. Test Your Code: After updating both PyYAML and dateparser, test your code to ensure that the error no longer occurs.


Python’s dateparser is a valuable library for parsing date and time strings, but it can encounter issues related to its dependencies. By updating your PyYAML library and ensuring that dateparser is up-to-date, you can resolve this error and continue working with date and time parsing in Python.

In conclusion, staying updated with libraries and dependencies is crucial in the maintaining a smooth development experience. Troubleshooting errors like this one is an essential skill for Python programmers, ensuring that their Django projects run smoothly and without interruptions.