# swegym / pandas-dev__pandas-49078

- taskset: [swegym](https://harnessreport.com/tasks/swegym.md)
- difficulty: hard
- category: debugging
- language: 
- runnable from the site: no
- agent timeout: 3000s

## Results by harness

_none yet_

## Instruction

```
ENH: Serialize view of ArrowStringArray
Currently Pandas serializes views of ArrowStringArrays by serailizing the whole thing, rather than a subset.  Here is an example:

```python
In [1]: import pandas as pd

In [2]: s = pd.Series([c * 1000 for c in "abcdefghijklmnopqrstuvwxyz"])

In [3]: s
Out[3]: 
0     aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa...
1     bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb...
2     cccccccccccccccccccccccccccccccccccccccccccccc...
3     dddddddddddddddddddddddddddddddddddddddddddddd...
4     eeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee...
5     ffffffffffffffffffffffffffffffffffffffffffffff...
6     gggggggggggggggggggggggggggggggggggggggggggggg...
7     hhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh...
8     iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii...
9     jjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj...
10    kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk...
11    llllllllllllllllllllllllllllllllllllllllllllll...
12    mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm...
13    nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn...
14    oooooooooooooooooooooooooooooooooooooooooooooo...
15    pppppppppppppppppppppppppppppppppppppppppppppp...
16    qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq...
17    rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr...
18    ssssssssssssssssssssssssssssssssssssssssssssss...
19    tttttttttttttttttttttttttttttttttttttttttttttt...
20    uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu...
21    vvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvv...
22    wwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwww...
23    xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx...
24    yyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyy...
25    zzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz...
dtype: object

In [4]: import pickle

In [5]: len(pickle.dumps(s))
Out[5]: 26758

In [6]: len(pickle.dumps(s.astype("string[pyarrow]")))
Out[6]: 26891

In [7]: len(pickle.dumps(s.head(5)))
Out[7]: 5632

In [8]: len(pickle.dumps(s.astype("string[pyarrow]").head(5)))
Out[8]: 26891
```

This negatively affects dask dataframe operations that cut up pandas dataframes into small pieces, moves them around to different computers, and then pieces them back together again.
```
---
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