Is pip gaining on conda for python libs?

I’ve been leaning towards pip a lot lately for my data science work. Generally, I’ve been having more dependency issues for the standard ML libraries when using conda install/ forge xyz than pip install xyz. Also, pip seems to be much faster. This has really become apparent to me over the past year or so. Anyone with me?

Curious for opinions.

Using mostly standard libs..numpy/ pd, pyspark, pyarrow sklearn, statsmodels, randomforest, lgbm, xgb. Not so much keras tensorflow etc.

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