8000 minor by writinwaters · Pull Request #1600 · infiniflow/infinity · GitHub
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Merged
merged 4 commits into from
Aug 6, 2024
Merged

minor #1600

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e50f817
minor
writinwaters Aug 6, 2024
e4d4d63
Output would not fail
writinwaters Aug 6, 2024
27c71eb
Update syntax
writinwaters Aug 6, 2024
4469ddc
vector update is available
writinwaters Aug 6, 2024
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73 changes: 29 additions & 44 deletions docs/references/pysdk_api_reference.md
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< 10000 td class="blob-code blob-code-context js-file-line">
Original file line number Diff line number Diff line change
Expand Up @@ -598,7 +598,7 @@ res.table_names # ['my_table, 'tensor_table', 'sparse_table']
## create_index

```python
Table.create_index(index_name, index_infos, conflict_type = ConflictType.Error)
table_obj.create_index(index_name, index_infos, conflict_type = ConflictType.Error)
```

Creates index on a specified column or on multiple columns.
Expand Down 8000 Expand Up @@ -972,7 +972,7 @@ table_obj.create_index(
## drop_index

```python
Table.drop_index(index_name, conflict_type = ConflictType.Error)
table_obj.drop_index(index_name, conflict_type = ConflictType.Error)
```

Deletes an index by its name.
Expand Down Expand Up @@ -1023,7 +1023,7 @@ table_obj.drop_index("my_index")
## show_index

```python
Table.show_index(index_name)
table_obj.show_index(index_name)
```

Retrieves the metadata of an specified index.
Expand Down Expand Up @@ -1212,7 +1212,7 @@ table_obj.insert([{"tensor_array_column": [[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0]
## import_data

```python
Table.import_data(filepath, import_options)
table_obj.import_data(filepath, import_options)
```

Imports data from a specified file into the current table.
Expand Down Expand Up @@ -1272,7 +1272,7 @@ table_obj.import_data(os.getcwd() + "/your_file.jsonl", {"file_type": "csv"})
## export_data

```python
Table.export_data(filepath, export_options, columns = None)
table_obj.export_data(filepath, export_options, columns = None)
```
Exports the current table to a specified file.
Expand Down Expand Up @@ -1344,10 +1344,10 @@ table_obj.export_data(os.getcwd() + "/export_data.jsonl", {"file_type": "jsonl",
## delete

```python
Table.delete(cond = None)
table_obj.delete(cond = None)
```

Deletes rows by condition.
Deletes rows from the table based on the specified condition.

### Parameters

Expand All @@ -1356,7 +1356,7 @@ Deletes rows by condition.
A condition or filter that determines which rows to delete from the table. The parameter can be an expression, a function, or any other form of conditional logic that evaluates to `True` for the rows that should be deleted. If `cond` is not specified or set to `None`, the method will delete all rows in the table.

:::tip NOTE
- The `cond` parameter currently supports 'and' and 'or' logical expressions only. Additional expressions like 'between' and 'in' will be available soon.
- The `cond` parameter currently supports 'and' and 'or' logical expressions only. Additional expressions like 'between' and 'in' will be available in future updates.
- `cond` must not be an empty string.
:::

Expand Down Expand Up @@ -1392,25 +1392,13 @@ table_obj.delete(None)
# - Vector column "vec"
table_obj = db_instance.create_table("my_table", {"c1": {"type": "integer"}, "vec": {"type": "vector,4,float"},})
# Insert two rows of data into the "my_table"
table_obj.insert(
[
{
"c1": 90,
"vec": [1.0, 1.2, 0.8, 0.9],
},
{
"c1": 80,
"vec": [4.0, 4.2, 4.3, 4.5],
},
]
)
table_obj.insert([{"c1": 90, "vec": [1.0, 1.2, 0.8, 0.9],}, {"c1": 80, "vec": [4.0, 4.2, 4.3, 4.5],},])
# Delete rows where "c1" equals 1
table_obj.delete("c1 = 90")
```

```python
# Create a table named "my_table" with one column:
# - Integer column "c1"
# Create a table named "my_table" with one integer column "c1"
table_obj = db_instance.create_table("my_table", {"c1": {"type": "integer"}})
# Insert three rows of data into the "my_table"
table_obj.insert([{"c1": 90}, {"c1": 80}, {"c1": 95}])
Expand All @@ -1423,22 +1411,20 @@ table_obj.delete("c1 >= 70 and c1 <= 90")
## update

```python
Table.update(cond = None)
table_obj.update(cond = None, data)
```

Searches for rows that match the specified condition and updates them accordingly.

### Parameters

#### cond: `str` (not empty), *Required*

A condition that specifies which rows to update. This parameter should be a non-empty string representing a logical expression, a function, or any other form of conditional logic that evaluates to `True` for the rows that should be updated.
#### cond: `str` (not empty), *Required*

#### data: `list[dict[str, Union[str, int, float]]]`
A condition that specifies which rows to update. This parameter should be a non-empty string representing a logical expression, a function, or any other form of conditional logic that evaluates to `True` for the rows that should be updated.

A list of dict where key indicates column, value indicates new value. Must not be empty.
#### data: `list[dict[str, Any]]]` (not empty), *Required*

> Infinity does not support updating column with vector data type.
A list of dictionaries where each key indicates a column name and each value indicates the new value for the corresponding cell. This list must not be empty.

### Returns

Expand Down Expand Up @@ -1466,13 +1452,13 @@ table_obj.update("c1 > 2", [{"c2": 100, "c3": 1000}])
## output

```python
Table.output(columns)
table_obj.output(columns)
```
Specify the columns to display in the search output, or perform aggregation operations or arithmetic calculations.

### Parameters

#### columns: `list[str]`, *Required*
#### columns: `list[str]`, *Required*

Must not be empty. Supported aggragation functions:

Expand All @@ -1484,8 +1470,7 @@ Must not be empty. Supported aggragation functions:

### Returns

- Success: self `Table`
- Failure: `Exception`
An `infinity.local_infinity.table.LocalTable` object in Python module mode or an `infinity.remote_thrift.table.RemoteTable` object in client-server mode.

### Examples

Expand All @@ -1502,7 +1487,7 @@ table_obj.output(["c1+5"])
## filter

```python
Table.filter(cond)
table_obj.filter(cond)
```

Creates a filtering condition expression.
Expand All @@ -1528,10 +1513,10 @@ table_obj.filter("(-7 < c1 or 9 >= c1) and (c2 = 3)")
## knn

```python
Table.knn(vector_column_name, embedding_data, embedding_data_type, distance_type, topn, knn_params = None)
table_obj.knn(vector_column_name, embedding_data, embedding_data_type, distance_type, topn, knn_params = None)
```

Builds a KNN search expression. Find the top n closet rows to the given vector.
Conducts a KNN vector search, finding the top n closet rows to the given vector.

### Parameters

Expand Down Expand Up @@ -1572,7 +1557,7 @@ table_obj.knn('vec', [3.0] * 5, 'float', 'ip', 2)
## match sparse

```python
Table.match_sparse(vector_column_name, sparse_data, distance_type, topn, opt_params = None)
table_obj.match_sparse(vector_column_name, sparse_data, distance_type, topn, opt_params = None)
```

### Parameters
Expand Down Expand Up @@ -1645,7 +1630,7 @@ for question in questions:
## match tensor

```python
Table.match_tensor(vector_column_name, tensor_data, tensor_data_type, method_type, topn, extra_option)
table_obj.match_tensor(vector_column_name, tensor_data, tensor_data_type, method_type, topn, extra_option)
```

Builds a KNN tensor search expression. Find the top n closet rows to the given tensor according to chosen method.
Expand Down Expand Up @@ -1695,7 +1680,7 @@ match_tensor('t', [[1.0, 0.0, 0.0, 0.0], [1.0, 0.0, 0.0, 0.0]], 'float', 'maxsim
## fusion

```python
Table.fusion(method, options_text = '')
table_obj.fusion(method, options_text = '')
```

Builds a fusion expression.
Expand Down Expand Up @@ -1754,7 +1739,7 @@ table_obj.fusion('match_tensor', 'topn=2', make_match_tensor_expr('t', [[0.0, -1
## optimize

```python
Table.optimize(index_name, opt_params)
table_obj.optimize(index_name, opt_params)
```

### Parameters
Expand Down Expand Up @@ -1782,19 +1767,19 @@ table_obj.optimize('bmp_index_name', {'topk': '10'})
## get result

```python
Table.to_result()
table_obj.to_result()
```

```python
Table.to_df()
table_obj.to_df()
```

```python
Table.to_pl()
table_obj.to_pl()
```

```python
Table.to_arrow()
table_obj.to_arrow()
```

After querying, these four methods above can get result into specific type.
Expand Down
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