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There are several difficulties in accessing edge properties while developing functions with plpython3u in PostgreSQL:

1. Limited Documentation: There is limited documentation available for plpython3u in PostgreSQL, which makes it challenging to find resources and understand how to work with edge properties.

2. Data Type Mismatch: Edge properties can have different data types, and it's essential to match the data type used in your plpython3u function to avoid issues with storing and accessing data.

3. Limited Built-in Functions: Plpython3u has limited built-in functions available for working with graph edges, making it necessary to write custom functions to access and manipulate edge properties.

4. Performance Issues: With large graphs and many edges, accessing edge properties can be slow, leading to performance issues in the plpython3u function.

5. Security Issues: Plpython3u functions can be vulnerable to SQL injection attacks if not coded correctly, which can expose sensitive data in edge properties.