If you add timezone information in the Field annotation for a datetime
then that will now be passed to the pyarrow data type.
I'm not sure how pyarrow enforces timezones, right now, it silently
coerces to the timezone given in the column regardless of whether the
input had the matching timezone or not. This is probably not the right
behavior. Though we could just make it so the user has to make the
pydantic model do the validation instead of doing that at the pyarrow
conversion layer.
Closes#721
fts will return results as a pyarrow table. Pyarrow tables has a
`filter` method but it does not take sql filter strings (only pyarrow
compute expressions). Instead, we do one of two things to support
`tbl.search("keywords").where("foo=5").limit(10).to_arrow()`:
Default path: If duckdb is available then use duckdb to execute the sql
filter string on the pyarrow table.
Backup path: Otherwise, write the pyarrow table to a lance dataset and
then do `to_table(filter=<filter>)`
Neither is ideal.
Default path has two issues:
1. requires installing an extra library (duckdb)
2. duckdb mangles some fields (like fixed size list => list)
Backup path incurs a latency penalty (~20ms on ssd) to write the
resultset to disk.
In the short term, once #676 is addressed, we can write the dataset to
"memory://" instead of disk, this makes the post filter evaluate much
quicker (ETA next week).
In the longer term, we'd like to be able to evaluate the filter string
on the pyarrow Table directly, one possibility being that we use
Substrait to generate pyarrow compute expressions from sql string. Or if
there's enough progress on pyarrow, it could support Substrait
expressions directly (no ETA)
---------
Co-authored-by: Will Jones <willjones127@gmail.com>
Closes https://github.com/lancedb/lance/issues/1738
We add a `flatten` parameter to the signature of `to_pandas`. By default
this is None and does nothing.
If set to True or -1, then LanceDB will flatten structs before
converting to a pandas dataframe. All nested structs are also flattened.
If set to any positive integer, then LanceDB will flatten structs up to
the specified level of nesting.
---------
Co-authored-by: Weston Pace <weston.pace@gmail.com>
* Filename typo
* Remove rick_morty csv as users won't really be able to use it.. We can
create a an executable colab and download it from a bucket or smth.
Fix broken link to embedding functions
testing: broken link was verified after local docs build to have been
repaired
---------
Co-authored-by: Chang She <chang@lancedb.com>
This PR adds an overview of embeddings docs:
- 2 ways to vectorize your data using lancedb - explicit & implicit
- explicit - manually vectorize your data using `wit_embedding` function
- Implicit - automatically vectorize your data as it comes by ingesting
your embedding function details as table metadata
- Multi-modal example w/ disappearing embedding function
Add `to_list` to return query results as list of python dict (so we're
not too pandas-centric). Closes#555
Add `to_pandas` API and add deprecation warning on `to_df`. Closes#545
Co-authored-by: Chang She <chang@lancedb.com>
I only modified those docs pages that are untouched in existing unmerged
PRs, so hopefully there are no merge conflicts!
1. The `tantivy-py` version specified in the docs doesn't work (pip
install fails), but with the latest version of pip and wheel installed
on my Mac, I was able to just `pip install tantivy` and FTS works great
for me. I updated the docs page to include this in
7ca4b757ce but can always modify to
another specific version in case this breaks any tests.
2. The `.add()` method for Python should take in a list of dicts as the
first option (to also align with the JS API), and additionally, users
can pass an existing pandas DataFrame to add to a table. Hope this makes
sense.
3. I've had multiple conversations with users who are unclear that the
terms "exhaustive", "flat" and "KNN" are all the same kind of search, so
I've updated the verbiage of this section to clarify this.
4. Fixed typos and improved clarity in the ANN indexes page.
BREAKING CHANGE: The `score` column has been renamed to `_distance` to
more accurately describe the semantics (smaller means closer / better).
---------
Co-authored-by: Lei Xu <lei@lancedb.com>
Saves users from having to explicitly call
`LanceModel.to_arrow_schema()` when creating an empty table.
See new docs for full details.
---------
Co-authored-by: Chang She <chang@lancedb.com>
* Rename "Reference" -> "Guides" to create distinction b/w api reference
and user facing docs
* Add all the various ways to create, add and delete from table
Related - https://github.com/lancedb/lancedb/pull/391
