leonoverweel / tz-canary Goto Github PK

Adding this metadata should enable linking from PyPI to GitHub. Need to figure out doing this in Poetry.

As of Python 3.9, timezone info is included in Python, so we should be able to get rid of this dependency.

Projects using Python 3.9 or later should be using the support now included as part of the standard library, and third party packages work with it such as tzdata. pytz offers no advantages beyond backwards compatibility with code written for earlier versions of Python.

In some places it's plural (TransitionsData, transitions_data); in other places it's singular transition_data.

Will be a breaking change.

Description:

While running the test suite, multiple warnings are triggered due to the use of 'T' as a frequency alias in pd.date_range(). According to the warnings, 'T' is deprecated and will be removed in a future version of pandas. The recommended alternative is to use 'min'.

Affected Code:

The warnings originate from the following lines in tests/fixtures/dt_index_fixtures.py:

1. Line 7:

   return pd.date_range(..., freq='<x>T')

   Warning:

   FutureWarning: 'T' is deprecated and will be removed in a future version, please use 'min' instead.
   

2. Line 14:

   return pd.date_range(..., freq='<x>T')

   Warning:

   FutureWarning: 'T' is deprecated and will be removed in a future version, please use 'min' instead.
   

3. Line 21:

   return pd.date_range(..., freq='<x>T')

   Warning:

   FutureWarning: 'T' is deprecated and will be removed in a future version, please use 'min' instead.
   

Steps to Reproduce:

1. Run the test suite using the command: python -m pytest.
2. Observe the warnings related to the use of pd.date_range.

Proposed Solution:

Replace all instances of freq='<x>T' with freq='<x>min' in tests/fixtures/dt_index_fixtures.py to address the deprecation warnings and future-proof the code.

Environment:

• OS: macOS
• Python version: 3.11.7
• pytest version: 7.4.0
• pandas version: 2.2.2

Additional Information:

All tests currently pass (16 passed), but the warnings suggest this issue will cause future failures when the deprecated functionality is removed from pandas.

Currently only supporting Python 3.11 because that's all I've tested on, but supporting 3.9+ should be easy enough.

To do:

• Set up testing matrix (tox or GitHub CI)
• Fix any potential issues with Python 3.9 and 3.10