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Merge pull request #32 from lancedb/changhiskhan/doc-basic-ops
[DOC] basic operations
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# Basic LanceDB Functionality
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## How to connect to a database
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In local mode, LanceDB stores data in a directory on your local machine. To connect to a local database, you can use the following code:
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```python
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import lancedb
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uri = "~/.lancedb"
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db = lancedb.connect(uri)
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```
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LanceDB will create the directory if it doesn't exist (including parent directories).
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If you need a reminder of the uri, use the `db.uri` property.
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## How to create a table
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To create a table, you can use the following code:
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```python
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tbl = db.create_table("my_table",
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data=[{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
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{"vector": [5.9, 26.5], "item": "bar", "price": 20.0}])
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```
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Under the hood, LanceDB is converting the input data into an Apache Arrow table
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and persisting it to disk in [Lance format](github.com/eto-ai/lance).
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You can also pass in a pandas DataFrame directly:
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```python
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import pandas as pd
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df = pd.DataFrame([{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
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{"vector": [5.9, 26.5], "item": "bar", "price": 20.0}])
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tbl = db.create_table("table_from_df", data=df)
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```
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## How to open an existing table
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Once created, you can open a table using the following code:
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```python
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tbl = db.open_table("my_table")
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```
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If you forget the name of your table, you can always get a listing of all table names:
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```python
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db.table_names()
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```
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## How to add data to a table
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After a table has been created, you can always add more data to it using
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```python
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df = pd.DataFrame([{"vector": [1.3, 1.4], "item": "fizz", "price": 100.0},
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{"vector": [9.5, 56.2], "item": "buzz", "price": 200.0}])
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tbl.add(df)
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```
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## How to search for (approximate) nearest neighbors
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Once you've embedded the query, you can find its nearest neighbors using the following code:
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```python
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tbl.search([100, 100]).limit(2).to_df()
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```
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This returns a pandas DataFrame with the results.
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## What's next
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This section covered the very basics of the LanceDB API.
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LanceDB supports many additional features when creating indices to speed up search and options for search.
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These are contained in the next section of the documentation.
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@@ -35,5 +35,5 @@ result = table.search([100, 100]).limit(2).to_df()
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## Documentation Quick Links
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* [`Basic Operations`](basic.md) - basic functionality of LanceDB.
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* [`API Reference`](python.md) - detailed documentation for the LanceDB Python SDK.
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