We have a type similar to this (a typed list) internally in pandas, although it is restricted to a single dimension and far from feature complete -- it only has .append and a .to_array() method for converting to a 1d numpy array. Our version is written in Cython, and we use it for performance reasons when we would otherwise need to create a list of unknown length:
https://github.com/pydata/pandas/blob/v0.17.1/pandas/hashtable.pyx#L99

In my experience, it's several times faster than using a builtin list from Cython, which makes sense given that it needs to copy about 1/3 the data (no type or reference count for individual elements). Obviously, it uses 1/3 the space to store the data, too. We currently don't expose this object externally, but it could be an interesting project to adapt this code into a standalone project that could be more broadly useful.

Cheers,
Stephan

On Tue, Dec 22, 2015 at 8:20 PM, Chris Barker wrote:

sorry for being so lazy as to not go look at the project pages, but....

This sounds like it could be really useful, and maybe supercise a coupl eof half-baked projects of mine. But -- what does "dynamic" mean?

- can you append to these arrays?
- can it support "ragged arrrays" -- it looks like it does.

```>>> L = ArrayList( [[0], [1,2], [3,4,5], [6,7,8,9]] )
>>> print(L)
[[0], [1 2], [3 4 5], [6 7 8 9]]
```
so this looks like a ragged array -- but what do you get when you do:

for row in L:
print row

```>>> print(L.data)
[0 1 2 3 4 5 6 7 8 ```
is .data a regular old 1-d numpy array?

```>>> L = ArrayList( np.arange(10), [3,3,4])
>>> print(L)
[[0 1 2], [3 4 5], [6 7 8 9]]
>>> print(L.data)
[0 1 2 3 4 5 6 7 8 9]
```

does an ArrayList act like a numpy array in other ways:

L * 5

L* some_array

in which case, how does it do broadcasting???

Thanks,

-CHB

```>>> L = ArrayList(["Hello", "world", "!"])
>>> print(L[0])
'Hello'
>>> L[1] = "brave new world"
>>> print(L)
['Hello', 'brave new world', '!']```

Nicolas

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