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https://github.com/wassname/greater_tables_project.git
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Stephen Mildenhall
38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
"""
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A massively over-engineered hash function for DataFrames. Output
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varies with time. From GTP. Blake2b - who knew?
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"""
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import hashlib
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import time
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import base64
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import pandas as pd
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def df_short_hash(df, length=12):
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"""Generate a short, time-dependent hash for a DataFrame (safe for HTML IDs)."""
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hasher = hashlib.blake2b(digest_size=8) # Smaller output
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# Hash DataFrame content (values, index, columns)
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hasher.update(df.to_numpy().tobytes())
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hasher.update(pd.util.hash_pandas_object(df.index, index=True).values.tobytes())
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hasher.update(pd.util.hash_pandas_object(df.columns, index=True).values.tobytes())
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# Time component for uniqueness
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timestamp = str(time.time_ns()).encode()
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hasher.update(timestamp)
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# Encode as base32 (safe for HTML IDs, removes special characters)
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hash_bytes = hasher.digest()
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hash_str = base64.b32encode(hash_bytes).decode("utf-8").rstrip("=") # Trim padding
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return f"T{hash_str[:length]}" # Prefix with 'T' to ensure a valid ID
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def txt_short_hash(txt):
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hasher = hashlib.md5()
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hasher.update(txt.encode('utf-8'))
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hash_bytes = hasher.digest()
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hash_str = base64.b32encode(hash_bytes).decode("utf-8").rstrip("=") # Trim padding
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return hash_str[::2]
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