ZSTD compresion with dictionary causes odd errors
- Lingua principale
- Python
- Stelle
- 211
- Fork
- 58
- Merge medio
- 1g 17h
- PR unite (30g)
- 6
Descrizione
When activating the "use_dict" flag in an SChunk instance, storing data leads to errors.
The following code does not execute on my system:
```
import blosc2
import numpy as np
CHUNKSIZE = int(2**12)
NCHUNKS = 5
coptions = blosc2.cparams_dflts.copy()
coptions["codec"] = blosc2.Codec.ZSTD # this is already the default
coptions["use_dict"] = 1
_rng = np.random.default_rng()
def _make_data() -> bytes:
return _rng.random(CHUNKSIZE // 4, dtype=np.float32).tobytes()
data = [_make_data() for x in range(NCHUNKS)]
storage = blosc2.SChunk(
chunksize=CHUNKSIZE, cparams=coptions, dparams=blosc2.dparams_dflts
)
for x in data:
storage.append_data(x)
for index, x in enumerate(data):
assert storage.decompress_chunk(index) == x
```
Instead, it leads to the following `RuntimeError`:
```
Traceback (most recent call last):
File "/home/user/minimal_bug.py", line 26, in
storage.append_data(x)
File "/home/user/env/lib/python3.9/site-packages/blosc2/schunk.py", line 298, in append_data
return super(SChunk, self).append_data(data)
File "blosc2_ext.pyx", line 1105, in blosc2.blosc2_ext.SChunk.append_data
RuntimeError: Could not append the buffer
```
If the above code is run with `coptions["use_dict"] = 0`, it executes successfully.
Do specific flags need to be set for shared dictionary compression to be successful, or does the sizing of stored data have different requirements?
python-blosc2 version: `blosc2==2.3.2`
python version: `3.9.18`
platform: arch linux, conda based python install
Guida per i contributori
Apri la guida per i contributori
Direzione di ricerca
Reproduce the provided minimal script with python-blosc2 2.3.2 and inspect SChunk.append_data in schunk.py together with the blosc2_ext.pyx traceback path. Determine why use_dict=1 rejects these chunks, then verify that appending all five buffers and decompressing each one succeeds with the dictionary enabled.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Valutazione
- Stack tecnologico
- python
- Ambito
- data
- Tipo di issue
- Bug
- Difficoltà
- 4/5
- Tempo stimato
- 3-5 giorni
- Stato di attività
- Ferma
- Chiarezza
- Abbastanza chiara
- Idoneità per principianti
- 28/100