Hashing Pandas dataframe breaks

First import:

import pandas as pd
import numpy as np
import hashlib

Next, consider the following:

np.random.seed(42)
arr = np.random.choice([41, 43, 42], size=(3,3))
df = pd.DataFrame(arr)
print(arr)
print(df)
print(hashlib.sha256(arr.tobytes()).hexdigest())
print(hashlib.sha256(df.values.tobytes()).hexdigest())

Multiple executions of this snippet yield the same hash twice all the time: ddfee4572d380bef86d3ebe3cb7bfa7c68b7744f55f67f4e1ca5f6872c2c9ba1.

However, if we consider the following:

np.random.seed(42)
arr = np.random.choice(['foo', 'bar', 42], size=(3,3))
df = pd.DataFrame(arr)
print(arr)
print(df)
print(hashlib.sha256(arr.tobytes()).hexdigest())
print(hashlib.sha256(df.values.tobytes()).hexdigest())

Note that there are strings in the data now. The hash of the arr is fixed (52db9328682317c44370b8186a5c6bae75f2a94c9d0d5b24d61f602857acd3de) for different evaluations, but the one of the pandas.DataFrame changes each time.

Any pythonic way around it? No Pythonic?

Edit: Related links:

• Hashable DataFrames