wjones127 commented on a change in pull request #12148:
URL: https://github.com/apache/arrow/pull/12148#discussion_r786980475
##########
File path: python/pyarrow/table.pxi
##########
@@ -1342,10 +1344,11 @@ cdef class Table(_PandasConvertible):
if preview_cols:
pieces.append('----')
for i in range(min(self.num_columns, preview_cols)):
- pieces.append('{}: {}'.format(
- self.field(i).name,
- self.column(i).to_string(indent=0, skip_new_lines=True)
- ))
+ col_string = self.column(i).to_string(
+ indent=0, skip_new_lines=True)
+ if len(col_string) > cols_char_limit:
+ col_string = col_string[:(cols_char_limit - 3)] + '...'
+ pieces.append('{}: {}'.format(self.field(i).name, col_string))
Review comment:
Thanks for the feedback. I implemented a very basic version of this for
now. This looks pretty good for this example:
```python
>>> from random import sample, choice
>>> import pyarrow as pa
>>> arr_int = pa.array(range(50))
>>> tree_parts = ["roots", "trunk", "crown", "seeds"]
>>> arr_list = pa.array([sample(tree_parts,
k=choice(range(len(tree_parts)))) for _ in range(50)])
>>> arr_struct = pa.StructArray.from_arrays([arr_int, arr_list],
names=['int_nested', 'list_nested'])
>>> arr_map = pa.array(
... [
... [(part, choice(range(10))) for part in sample(tree_parts,
k=choice(range(len(tree_parts))))]
... for _ in range(50)
... ],
... type=pa.map_(pa.utf8(), pa.int64())
... )
>>> table = pa.table({
... 'int': pa.chunked_array([arr_int] * 10),
... 'list': pa.chunked_array([arr_list] * 10),
... 'struct': pa.chunked_array([arr_struct] * 10),
... 'map': pa.chunked_array([arr_map] * 10),
... })
>>> print(table)
pyarrow.Table
int: int64
list: list<item: string>
child 0, item: string
struct: struct<int_nested: int64, list_nested: list<item: string>>
child 0, int_nested: int64
child 1, list_nested: list<item: string>
child 0, item: string
map: map<string, int64>
child 0, entries: struct<key: string not null, value: int64> not null
child 0, key: string not null
child 1, value: int64
----
int:
[[0,1,2,3,4,5,6,7,8,9,...,40,41,42,43,44,45,46,47,48,49],[0,1,2,3,4,5,6,7,8,9,...,40,41,42,43,44,45,46,47,48,49],[0,1,2,3,...]...]
list:
[[["seeds","trunk","roots"],["trunk","crown"],["crown"],["trunk"],["crown"],[],["roots","seeds"],["roots"],["trunk","roots"]...]...]
struct: [ -- is_valid: all not null -- child 0 type: int64
[
0,
1,
2,
3,
4,
5,
6,...]...]
map: [[ keys:["seeds","crown","trunk"]values:[7,8,7],
keys:["roots","crown"]values:[8,4], keys:["crown","roots","trunk"]...]...]
```
The unfortunate thing is it will have bad behavior in the case of string
columns containing `[`. For example,
```python
>>> pa.table({'x': pa.array(["[" * 100]* 500)})
x:
[["[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[","[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[",...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]...]
...]...]...]...]...]...]
```
I think that kind of behavior is pretty unavoidable until we push this limit
into the PrettyPrinter implementation itself.
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