feat: much faster file name resolution using ListFiles

[sg-s]

problem description

api.get_dataframe (and therefore DataFrame.from_deeporigin) can take extremely long because:

1. 2 calls to list_database_rows and describe_row take place in series when they could take place in parallel (this is a problem of 700ms vs 300ms)
2. (more serious problem). there is a place where N DescriebFile calls are made in series, where N is the number of files in the database. this means that the time it takes to fetch data grows with the number of files linearly, and the time for each file resolution is ~350ms.

proposed solution in this PR

using a new ListFiles endpoint that allows us to resolve all file IDs and names in a single API call (which typically takes 300ms no matter how many files)

screenshot

from cold start, this is how long it takes to display a dataframe. in the old version, this took ~10s

rejected alternative

using async methods. this approach was tried in this PR: #73

it was rejected because it's much slower, and complicates testing dramatically

[jonrkarr]

Looks good. Nice job identifying a bottleneck and finding a way to speed it up.

Using async to execute many queries in parallel is a good thought. In some cases, we can get even higher performance with specialized bulk or composite methods.