shengyudong/ai_wht_B
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

2026-1-6

Browse Source
This commit is contained in:
“shengyudong”
2026-01-06 14:18:39 +08:00
commit 5a384b694e
10345 changed files with 2050918 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

1
venv/Lib/site-packages/dashvector-1.0.22.dist-info/INSTALLER Normal file
View File

@@ -0,0 +1 @@
pip

217
venv/Lib/site-packages/dashvector-1.0.22.dist-info/LICENSE.txt Normal file
View File

@@ -0,0 +1,217 @@
Copyright 2023 Alibaba Inc. All rights reserved.
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
editorial revisions, annotations, elaborations, or other modifications
represent, as a whole, an original work of authorship. For the purposes
of this License, Derivative Works shall not include works that remain
separable from, or merely link (or bind by name) to the interfaces of,
the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
to that Work or Derivative Works thereof, that is intentionally
submitted to Licensor for inclusion in the Work by the copyright owner
or by an individual or Legal Entity authorized to submit on behalf of
the copyright owner. For the purposes of this definition, "submitted"
means any form of electronic, verbal, or written communication sent
to the Licensor or its representatives, including but not limited to
communication on electronic mailing lists, source code control systems,
and issue tracking systems that are managed by, or on behalf of, the
Licensor for the purpose of discussing and improving the Work, but
excluding communication that is conspicuously marked or otherwise
designated in writing by the copyright owner as "Not a Contribution."
"Contributor" shall mean Licensor and any individual or Legal Entity
on behalf of whom a Contribution has been received by Licensor and
subsequently incorporated within the Work.
2. Grant of Copyright License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
copyright license to reproduce, prepare Derivative Works of,
publicly display, publicly perform, sublicense, and distribute the
Work and such Derivative Works in Source or Object form.
3. Grant of Patent License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
(except as stated in this section) patent license to make, have made,
use, offer to sell, sell, import, and otherwise transfer the Work,
where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
institute patent litigation against any entity (including a
cross-claim or counterclaim in a lawsuit) alleging that the Work
or a Contribution incorporated within the Work constitutes direct
or contributory patent infringement, then any patent licenses
granted to You under this License for that Work shall terminate
as of the date such litigation is filed.
4. Redistribution. You may reproduce and distribute copies of the
Work or Derivative Works thereof in any medium, with or without
modifications, and in Source or Object form, provided that You
meet the following conditions:
(a) You must give any other recipients of the Work or
Derivative Works a copy of this License; and
(b) You must cause any modified files to carry prominent notices
stating that You changed the files; and
(c) You must retain, in the Source form of any Derivative Works
that You distribute, all copyright, patent, trademark, and
attribution notices from the Source form of the Work,
excluding those notices that do not pertain to any part of
the Derivative Works; and
(d) If the Work includes a "NOTICE" text file as part of its
distribution, then any Derivative Works that You distribute must
include a readable copy of the attribution notices contained
within such NOTICE file, excluding those notices that do not
pertain to any part of the Derivative Works, in at least one
of the following places: within a NOTICE text file distributed
as part of the Derivative Works; within the Source form or
documentation, if provided along with the Derivative Works; or,
within a display generated by the Derivative Works, if and
wherever such third-party notices normally appear. The contents
of the NOTICE file are for informational purposes only and
do not modify the License. You may add Your own attribution
notices within Derivative Works that You distribute, alongside
or as an addendum to the NOTICE text from the Work, provided
that such additional attribution notices cannot be construed
as modifying the License.
You may add Your own copyright statement to Your modifications and
may provide additional or different license terms and conditions
for use, reproduction, or distribution of Your modifications, or
for any such Derivative Works as a whole, provided Your use,
reproduction, and distribution of the Work otherwise complies with
the conditions stated in this License.
5. Submission of Contributions. Unless You explicitly state otherwise,
any Contribution intentionally submitted for inclusion in the Work
by You to the Licensor shall be under the terms and conditions of
this License, without any additional terms or conditions.
Notwithstanding the above, nothing herein shall supersede or modify
the terms of any separate license agreement you may have executed
with Licensor regarding such Contributions.
6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
except as required for reasonable and customary use in describing the
origin of the Work and reproducing the content of the NOTICE file.
7. Disclaimer of Warranty. Unless required by applicable law or
agreed to in writing, Licensor provides the Work (and each
Contributor provides its Contributions) on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or conditions
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. You are solely responsible for determining the
appropriateness of using or redistributing the Work and assume any
risks associated with Your exercise of permissions under this License.
8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
or other liability obligations and/or rights consistent with this
License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
replaced with your own identifying information. (Don't include
the brackets!) The text should be enclosed in the appropriate
comment syntax for the file format. We also recommend that a
file or class name and description of purpose be included on the
same "printed page" as the copyright notice for easier
identification within third-party archives.
Copyright [yyyy] [name of copyright owner]
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
############################################################################
Open-Source Code Included in DashVector Python Library
3-clause BSD License (https://raw.githubusercontent.com/numpy/numpy/master/LICENSE.txt)
* Software: numpy - Version between 1.18.5 and 1.21.6 (https://pypi.org/project/numpy/)
* Software: protobuf - Version between 3.8.0 and 3.20.3 (https://pypi.org/project/protobuf/)
Apache License 2.0 (https://raw.githubusercontent.com/grpc/grpc/master/LICENSE)
* Software: grpcio - Version between 1.22.0 and 1.55.0 (https://pypi.org/project/grpcio/)
* Software: aiohttp - Version between 3.1.0 and 3.8.4 (https://pypi.org/project/aiohttp/)

540
venv/Lib/site-packages/dashvector-1.0.22.dist-info/METADATA Normal file
View File

@@ -0,0 +1,540 @@
Metadata-Version: 2.1
Name: dashvector
Version: 1.0.22
Summary: DashVector Client Python Sdk Library
Home-page: https://github.com/alibaba/proxima
License: Apache-2.0
Keywords: DashVector,vector,database,cloud
Author: Alibaba
Requires-Python: >=3.9,<4.0
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Database
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Application Frameworks
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Dist: aiohttp (>=3.1.0,<4.0.0)
Requires-Dist: certifi (>=2023.7.22,<2024.0.0)
Requires-Dist: grpcio (>=1.44.0) ; python_version >= "3.8" and python_version < "3.11"
Requires-Dist: grpcio (>=1.59.0) ; python_version >= "3.11" and python_version < "4.0"
Requires-Dist: importlib_metadata
Requires-Dist: numpy
Requires-Dist: protobuf (>=5.29,<6.0)
Project-URL: Documentation, https://help.aliyun.com/document_detail/2510225.html
Description-Content-Type: text/markdown
# DashVector Client Python Library
DashVector is a scalable and fully-managed vector-database service for building various machine learning applications. The DashVector client SDK is your gateway to access the DashVector service.
For more information about DashVector, please visit: https://help.aliyun.com/document_detail/2510225.html
## Installation
To install the DashVector client Python SDK, simply run:
```shell
pip install dashvector
```
## QuickStart
```python
import numpy as np
import dashvector
# Use DashVector `Client` api to communicate with the backend vectorDB service.
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
# Create a collection named "quickstart" with dimension of 4, using the default Cosine distance metric
rsp = client.create(name='quickstart', dimension=4)
assert rsp
# Get a collection by name
collection = client.get(name='quickstart')
# Operations on 'Collection' includes Inert/Query/Upsert/Update/Delete/Fetch of docs
# Here we insert sample data (4-dimensional vectors) in batches of 16
collection.insert(
[
dashvector.Doc(id=str(i), vector=np.random.rand(4), fields={'anykey': 'anyvalue'})
for i in range(16)
]
)
# Query a vector from the collection
docs = collection.query([0.1, 0.2, 0.3, 0.4], topk=5)
print(docs)
# Get statistics about collection
stats = collection.stats()
print(stats)
# Delete a collection by name
client.delete(name='quickstart')
```
## Reference
### Create a Client
`Client` host various APIs for interacting with DashVector `Collection`.
```python
dashvector.Client(
api_key: str,
endpoint: str = 'dashvector.cn-hangzhou.aliyuncs.com',
protocal: dashvector.DashVectorProtocol = dashvector.DashVectorProtocol.GRPC,
timeout: float = 10.0
) -> Client
```
| Parameters | Type | Required | Description |
|------------|--------------------|----------|----------------------------------------------------------------------------------------------|
| api_key | str | Yes | Your DashVector API-KEY |
| endpoint | str | No | Service Endpoint. <br/>Default value: `dashvector.cn-hangzhou.aliyuncs.com` |
| protocol | DashVectorProtocol | No | Communication protocol, support HTTP and GRPC. <br/>Default value: `DashVectorProtocol.GRPC` |
| timeout | float | No | Timeout period (in seconds), -1 means no timeout. <br/>Default value: `10.0` |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
assert client
```
### Create Collection
```python
Client.create(
name: str,
dimension: int,
dtype: Union[Type[int], Type[float]] = float,
fields_schema: Optional[Dict[str, Union[Type[str], Type[int], Type[float], Type[bool]]]] = None,
metric: str = 'cosine',
timeout: Optional[int] = None
) -> DashVectorResponse
```
| Parameters | Type | Required | Description |
|----------------|----------------------------------------------------------------------------|----------|------------------------------------------------------------------------------------------------------------------|
| name | str | Yes | The name of the Collection to create. |
| dimension | int | Yes | The dimensions of the Collection's vectors. Valid values: 1-20,000 |
| dtype | Union[Type[int], Type[float]] | No | The date type of the Collection's vectors.<br/>Default value: `Type[float]` |
| fields_schema | Optional[Dict[str, Union[Type[str], Type[int], Type[float], Type[bool]]]] | No | Fields schema of the Collection.<br/>Default value: `None`<br/>e.g. `{"name": str, "age": int}` |
| metric | str | No | Vector similarity metric. For `cosine`, dtype must be `float`.<br/>Valid values:<br/> 1. (Default)`cosine`<br/>2. `dotproduct`<br/>3. `euclidean` |
| timeout | Optional[int] | No | Timeout period (in seconds), -1 means asynchronous creation collection.<br/>Default value: `None` |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
rsp = client.create('YOUR-COLLECTION-NAME', dimension=4)
assert rsp
```
### List Collections
`Client.list() -> DashVectorResponse`
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collections = client.list()
for collection in collections:
print(collection)
# outputs:
# 'quickstart'
```
### Describe Collection
`Client.describe(name: str) -> DashVectorResponse`
| Parameters | Type | Required | Description |
|------------|-------|----------|-----------------------------------------|
| name | str | Yes | The name of the Collection to describe. |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
rsp = client.describe('YOUR-COLLECTION-NAME')
print(rsp)
# example output:
# {
# "request_id": "8d3ac14e-5382-4736-b77c-4318761ddfab",
# "code": 0,
# "message": "",
# "output": {
# "name": "quickstart",
# "dimension": 4,
# "dtype": "FLOAT",
# "metric": "dotproduct",
# "fields_schema": {
# "name": "STRING",
# "age": "INT",
# "height": "FLOAT"
# },
# "status": "SERVING",
# "partitions": {
# "default": "SERVING"
# }
# }
# }
```
### Delete Collection
`Client.delete(name: str) -> DashVectorResponse`
| Parameters | Type | Required | Description |
|------------|-------|----------|---------------------------------------|
| name | str | Yes | The name of the Collection to delete. |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
client.delete('YOUR-COLLECTION-NAME')
```
### Get a Collection Instance
`Collection` provides APIs for accessing `Doc` and `Partition`
`Client.get(name: str) -> Collection`
| Parameters | Type | Required | Description |
|------------|-------|----------|------------------------------------|
| name | str | Yes | The name of the Collection to get. |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collection = client.get('YOUR-COLLECTION-NAME')
assert collection
```
### Describe Collection Statistics
`Collection.stats() -> DashVectorResponse`
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collection = client.get('YOUR-COLLECTION-NAME')
rsp = collection.stats()
print(rsp)
# example output:
# {
# "request_id": "14448bcb-c9a3-49a8-9152-0de3990bce59",
# "code": 0,
# "message": "Success",
# "output": {
# "total_doc_count": "26",
# "index_completeness": 1.0,
# "partitions": {
# "default": {
# "total_doc_count": "26"
# }
# }
# }
# }
```
### Insert/Update/Upsert Docs
```python
Collection.insert(
docs: Union[Doc, List[Doc], Tuple, List[Tuple]],
partition: Optional[str] = None,
async_req: False
) -> DashVectorResponse
```
| Parameters | Type | Required | Description |
|------------|-------------------------------------------|----------|------------------------------------------------------------------------|
| docs | Union[Doc, List[Doc], Tuple, List[Tuple]] | Yes | The docs to Insert/Update/Upsert. |
| partition | Optional[str] | No | Name of the partition to Insert/Update/Upsert.<br/>Default value: `None` |
| async_req | bool | No | Enable async request or not.<br/>Default value: `False` |
Example:
```python
import dashvector
import numpy as np
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collection = client.get('YOUR-COLLECTION-NAME')
# insert a doc with Tuple
collection.insert(('YOUR-DOC-ID1', [0.1, 0.2, 0.3, 0.4]))
collection.insert(('YOUR-DOC-ID2', [0.2, 0.3, 0.4, 0.5], {'age': 30, 'name': 'alice', 'anykey': 'anyvalue'}))
# insert a doc with dashvector.Doc
collection.insert(
dashvector.Doc(
id='YOUR-DOC-ID3',
vector=[0.3, 0.4, 0.5, 0.6],
fields={'foo': 'bar'}
)
)
# insert in batches
ret = collection.insert(
[
('YOUR-DOC-ID4', [0.2, 0.7, 0.8, 1.3], {'age': 1}),
('YOUR-DOC-ID4', [0.3, 0.6, 0.9, 1.2], {'age': 2}),
('YOUR-DOC-ID6', [0.4, 0.5, 1.0, 1.1], {'age': 3})
]
)
# insert in batches
ret = collection.insert(
[
dashvector.Doc(id=str(i), vector=np.random.rand(4)) for i in range(10)
]
)
# async insert
ret_funture = collection.insert(
[
dashvector.Doc(id=str(i+10), vector=np.random.rand(4)) for i in range(10)
],
async_req=True
)
ret = ret_funture.get()
```
### Query a Collection
```python
Collection.query(
vector: Optional[Union[List[Union[int, float]], np.ndarray]] = None,
id: Optional[str] = None,
topk: int = 10,
filter: Optional[str] = None,
include_vector: bool = False,
partition: Optional[str] = None,
output_fields: Optional[List[str]] = None,
async_req: False
) -> DashVectorResponse
```
| Parameters | Type | Required | Description |
|-----------------|------------------------------------------------------|----------|--------------------------------------------------------------------------------------------------------------|
| vector | Optional[Union[List[Union[int, float]], np.ndarray]] | No | The vector to query |
| id | Optional[str] | No | The doc id to query.<br/>Setting `id` means searching by vector corresponding to the id |
| topk | Optional[str] | No | Number of similarity results to return.<br/>Default value: `10` |
| filter | Optional[str] | No | Expression used to filter results <br/>Default value: None <br/>e.g. `age>20` |
| include_vector | bool | No | Return vector details or not.<br/>Default value: `False` |
| partition | Optional[str] | No | Name of the partition to Query.<br/>Default value: `None` |
| output_fields | Optional[List[str]] | No | List of field names to return.<br/>Default value: `None`, means return all fields<br/>e.g. `['name', 'age']` |
| async_req | bool | No | Enable async request or not.<br/>Default value: `False` |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collection = client.get('YOUR-COLLECTION-NAME')
match_docs = collection.query([0.1, 0.2, 0.3, 0.4], topk=100, filter='age>20', include_vector=True, output_fields=['age','name','foo'])
if match_docs:
for doc in match_docs:
print(doc.id)
print(doc.vector)
print(doc.fields)
print(doc.score)
```
### Delete Docs
```python
collection.delete(
ids: Union[str, List[str]],
delete_all: bool = False,
partition: Optional[str] = None,
async_req: bool = False
) -> DashVectorResponse
```
| Parameters | Type | Required | Description |
|------------|-----------------------|----------|-----------------------------------------------------------------|
| ids | Union[str, List[str]] | Yes | The id (or list of ids) for the Doc(s) to Delete |
| delete_all | bool | No | Delete all vectors from partition.<br/>Default value: `False` |
| partition | Optional[str] | No | Name of the partition to Delete from.<br/>Default value: `None` |
| async_req | bool | No | Enable async request or not.<br/>Default value: `False` |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collection = client.get('YOUR-COLLECTION-NAME')
collection.delete(['YOUR-DOC-ID1','YOUR-DOC-ID2'])
```
### Fetch Docs
```python
Collection.fetch(
ids: Union[str, List[str]],
partition: Optional[str] = None,
async_req: bool = False
) -> DashVectorResponse
```
| Parameters | Type | Required | Description |
|------------|-----------------------|----------|----------------------------------------------------------------|
| ids | Union[str, List[str]] | Yes | The id (or list of ids) for the Doc(s) to Fetch |
| partition | Optional[str] | No | Name of the partition to Fetch from.<br/>Default value: `None` |
| async_req | bool | No | Enable async request or not.<br/>Default value: `False` |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collection = client.get('YOUR-COLLECTION-NAME')
fetch_docs = collection.fetch(['YOUR-DOC-ID1', 'YOUR-DOC-ID2'])
if fetch_docs:
for doc_id in fetch_docs:
doc = fetch_docs[doc_id]
print(doc.id)
print(doc.vector)
print(doc.fields)
```
### Create Collection Partition
`Collection.create_partition(name: str) -> DashVectorResponse`
| Parameters | Type | Required | Description |
|------------|----------------|----------|-------------------------------------------------------------------------------------------------------|
| name | str | Yes | The name of the Partition to Create. |
| timeout | Optional[int] | No | Timeout period (in seconds), -1 means asynchronous creation partition.<br/>Default value: `None` |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collection = client.get('YOUR-COLLECTION-NAME')
rsp = collection.create_partition('YOUR-PARTITION-NAME')
assert rsp
```
### Delete Collection Partition
`Collection.delete_partition(name: str) -> DashVectorResponse`
| Parameters | Type | Required | Description |
|------------|-------|----------|--------------------------------------|
| name | str | Yes | The name of the Partition to Delete. |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collection = client.get('YOUR-COLLECTION-NAME')
rsp = collection.delete_partition('YOUR-PARTITION-NAME')
assert rsp
```
### List Collection Partitions
`Collection.list_partitions() -> DashVectorResponse`
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collection = client.get('YOUR-COLLECTION-NAME')
partitions = collection.list_partitions()
assert partitions
for pt in partitions:
print(pt)
```
### Describe Collection Partition
`Collection.describe_partition(name: str) -> DashVectorResponse`
| Parameters | Type | Required | Description |
|------------|-------|----------|----------------------------------------|
| name | str | Yes | The name of the Partition to Describe. |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collection = client.get('YOUR-COLLECTION-NAME')
rsp = collection.describe_partition('shoes')
print(rsp)
# example output:
# {"request_id":"296267a7-68e2-483a-87e6-5992d85a5806","code":0,"message":"","output":"SERVING"}
```
### Statistics for Collection Partition
`Collection.stats_partition(name: str) -> DashVectorResponse`
| Parameters | Type | Required | Description |
|------------|-------|----------|----------------------------------------------|
| name | str | Yes | The name of the Partition to get Statistics. |
Example:
```python
import dashvector
client = dashvector.Client(api_key='YOUR-DASHVECTOR-API-KEY')
collection = client.get('YOUR-COLLECTION-NAME')
rsp = collection.stats_partition('shoes')
print(rsp)
# example outptut:
# {
# "code":0,
# "message":"",
# "requests_id":"330a2bcb-e4a7-4fc6-a711-2fe5f8a24e8c",
# "output":{
# "total_doc_count":0
# }
# }
```
## Class
### dashvector.Doc
```python
@dataclass(frozen=True)
class Doc(object):
id: str
vector: Union[List[int], List[float], numpy.ndarray]
fields: Optional[Dict[str, Union[Type[str], Type[int], Type[float], Type[bool]]]] = None
score: float = 0.0
```
### dashvector.DashVectorResponse
```python
class DashVectorResponse(object):
code: DashVectorCode
message: str
request_id: str
output: Any
```
## License
This project is licensed under the Apache License (Version 2.0).

95
venv/Lib/site-packages/dashvector-1.0.22.dist-info/RECORD Normal file
View File

@@ -0,0 +1,95 @@
dashvector-1.0.22.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
dashvector-1.0.22.dist-info/LICENSE.txt,sha256=GYJChq297x8HRI7yfGLcHdK-evsn6Sv7k68UCeGTu9w,12090
dashvector-1.0.22.dist-info/METADATA,sha256=tyf5PadbzNCsh5hBO1aXJOcCV6f1fylKzgMdE62RHDk,19949
dashvector-1.0.22.dist-info/RECORD,,
dashvector-1.0.22.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
dashvector-1.0.22.dist-info/WHEEL,sha256=sP946D7jFCHeNz5Iq4fL4Lu-PrWrFsgfLXbbkciIZwg,88
dashvector/__init__.py,sha256=d51J0TVujpnGSZsMIK7pEWeFob82CeT4VjDPAFr8djw,1433
dashvector/__pycache__/__init__.cpython-312.pyc,,
dashvector/__pycache__/version.cpython-312.pyc,,
dashvector/common/__init__.py,sha256=ZiiWcXjS5x0Ov_ATOcVUgW2pH1dqRUbNdZl2MLXKJGg,671
dashvector/common/__pycache__/__init__.cpython-312.pyc,,
dashvector/common/__pycache__/common_validator.cpython-312.pyc,,
dashvector/common/__pycache__/constants.cpython-312.pyc,,
dashvector/common/__pycache__/error.cpython-312.pyc,,
dashvector/common/__pycache__/handler.cpython-312.pyc,,
dashvector/common/__pycache__/logging.cpython-312.pyc,,
dashvector/common/__pycache__/status.cpython-312.pyc,,
dashvector/common/__pycache__/types.cpython-312.pyc,,
dashvector/common/__pycache__/vector_validator.cpython-312.pyc,,
dashvector/common/common_validator.py,sha256=x9RzNI0CUn-tGiMyVctImxF1LW9MUPV2m8KNHMGAptw,20160
dashvector/common/constants.py,sha256=v5qeBhOftgrHB8VJSz2frbRPejWYO-B66ijY5XuIpDU,1372
dashvector/common/error.py,sha256=dV5Nfct6S1r7B_0VfSXWIC6Rr2UDnbtmEIV4FIqjU1o,3987
dashvector/common/handler.py,sha256=lIS1QHEoeLt9dDbScRFm9hfLsDAPO29J5ZIrdetNBD0,6271
dashvector/common/logging.py,sha256=9_G-pkPpk0KtwBDSbYPyYajSW7EKcCQLIAEuDuaHlSs,1671
dashvector/common/status.py,sha256=hC5-nY0zUow1SNTc5IxvX2jDSdhUOgj_J1VtojRR26Y,2007
dashvector/common/types.py,sha256=qMmYtdm2xWIxtZj2Wri9QhPEpm_VmKZSIm4swk9dAr4,28818
dashvector/common/vector_validator.py,sha256=G6S1_kTQcIMYXcXhlpolHgS9z4mir1Om2UmeP_SFuLo,11476
dashvector/core/__init__.py,sha256=ZiiWcXjS5x0Ov_ATOcVUgW2pH1dqRUbNdZl2MLXKJGg,671
dashvector/core/__pycache__/__init__.cpython-312.pyc,,
dashvector/core/__pycache__/client.cpython-312.pyc,,
dashvector/core/__pycache__/collection.cpython-312.pyc,,
dashvector/core/__pycache__/doc.cpython-312.pyc,,
dashvector/core/__pycache__/group.cpython-312.pyc,,
dashvector/core/client.py,sha256=i-g7A_slYq1m-dds6YkMrWTh3eglqHas3CWwTDYtQv0,15331
dashvector/core/collection.py,sha256=2h_iFzwuyMpGILc8rjahkYBSID1yPgen2jGdIk1CsFM,32712
dashvector/core/doc.py,sha256=xVhh9DenHHVJqF6DR6zP2GbX9JzHTlsUf0jqNQQAUbA,11479
dashvector/core/group.py,sha256=xt9OnnAEB_P5xKG5TZmwqu38hbA3DJwGrzPAa4NFLA0,3595
dashvector/core/handler/__init__.py,sha256=ZiiWcXjS5x0Ov_ATOcVUgW2pH1dqRUbNdZl2MLXKJGg,671
dashvector/core/handler/__pycache__/__init__.cpython-312.pyc,,
dashvector/core/handler/__pycache__/grpc_handler.cpython-312.pyc,,
dashvector/core/handler/__pycache__/http_handler.cpython-312.pyc,,
dashvector/core/handler/grpc_handler.py,sha256=S0TH4tKsgTzK8RXFZJjpBcCcRpac3Dd9OGUKzBuWZ-I,18540
dashvector/core/handler/http_handler.py,sha256=cdc_Na6vQ-oeZ8tly3UwFVZj41Scu8aVS_gnmPjEUXo,19913
dashvector/core/models/__init__.py,sha256=ZiiWcXjS5x0Ov_ATOcVUgW2pH1dqRUbNdZl2MLXKJGg,671
dashvector/core/models/__pycache__/__init__.cpython-312.pyc,,
dashvector/core/models/__pycache__/collection_meta_status.cpython-312.pyc,,
dashvector/core/models/__pycache__/create_collection_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/create_partition_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/delete_collection_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/delete_doc_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/delete_partition_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/describe_collection_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/describe_partition_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/fetch_doc_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/get_version_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/list_collections_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/list_partitions_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/partition_meta_status.cpython-312.pyc,,
dashvector/core/models/__pycache__/query_doc_group_by_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/query_doc_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/stats_collection_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/stats_partition_request.cpython-312.pyc,,
dashvector/core/models/__pycache__/upsert_doc_request.cpython-312.pyc,,
dashvector/core/models/collection_meta_status.py,sha256=Ym7gH-Pr3W_OD60zP9fZsU6oRrHJZ4rurEfDn6Ux6ok,10376
dashvector/core/models/create_collection_request.py,sha256=xrX3iOV_zQAdOiRnS7WpHB2qfv51Xc1oZSeAL7ZlyJg,3782
dashvector/core/models/create_partition_request.py,sha256=K0A4KvF30MSodL6JdYfwtZgHWIHmg2B0L-8rQwg3q_4,1778
dashvector/core/models/delete_collection_request.py,sha256=T5A2wPyR6byhcB6BU7nsE4AVOL3ODpJ7Rzthvzt3rRk,1439
dashvector/core/models/delete_doc_request.py,sha256=j5MxSIYiZXXp3Upl_eXz_H0G715LimATCo7PV2mfHW4,5058
dashvector/core/models/delete_partition_request.py,sha256=ysj_2nGkn4p913gHqkPOEsmLcsw55ZaiY6Xuuf_Fe3o,1705
dashvector/core/models/describe_collection_request.py,sha256=eK94qr-UIwFF1_coH78RlilSQojXKTKki818G0HA0Ow,1451
dashvector/core/models/describe_partition_request.py,sha256=s74-nN68v5mJkoc4VjPOaVQv9MrFE9CrOUSHcA_E0UM,1724
dashvector/core/models/fetch_doc_request.py,sha256=Ng-lC6104LTjb2DOB6LBwboc3tQGB3pW6u0IglcDKg4,2433
dashvector/core/models/get_version_request.py,sha256=O1qsriTI20hE2Xz9W0hwuy5ZA2FkcApgnACbB9QSAvQ,1020
dashvector/core/models/list_collections_request.py,sha256=nKchTHSOvACL3fuJ2A7ZTKxlKmHdxkOncoVsYPBLC9A,1029
dashvector/core/models/list_partitions_request.py,sha256=PHQLeYz1fSxDsvjbXQSl8NYoe1zkXISEbaqiLCR-Buk,1477
dashvector/core/models/partition_meta_status.py,sha256=RG8WjBVW5eU_YPTiq_BSN4TEKy7Oo6v_ALmaHwkFtiw,1662
dashvector/core/models/query_doc_group_by_request.py,sha256=8KKauNmdu2g0cqPlxSrHsB_50hD4rJ93jFQWzHcq8dg,8649
dashvector/core/models/query_doc_request.py,sha256=Wq7ouh-6ODQqgYcgtPB4LnkPdIjumN7yb6njAMqr-eI,8854
dashvector/core/models/stats_collection_request.py,sha256=g5TRqsYxD3T-6F3IxWy8qfeC_fWadBmD30i17gXgY84,1418
dashvector/core/models/stats_partition_request.py,sha256=ywP8PPKd9RIbavC-TpKV1pKn-syCTjuc2-a0SR-BcrQ,1708
dashvector/core/models/upsert_doc_request.py,sha256=pMwR6iKhLnCLtgUbu3w5qyyts6JT4KNG6ob8DMLWlOY,22570
dashvector/core/proto/__init__.py,sha256=ZiiWcXjS5x0Ov_ATOcVUgW2pH1dqRUbNdZl2MLXKJGg,671
dashvector/core/proto/__pycache__/__init__.cpython-312.pyc,,
dashvector/core/proto/__pycache__/dashvector_pb2.cpython-312.pyc,,
dashvector/core/proto/__pycache__/dashvector_pb2_grpc.cpython-312.pyc,,
dashvector/core/proto/dashvector_pb2.py,sha256=sO-oxeiB1juxZaN6rz5qF3fnld3ASO_pJD45ye753u4,31890
dashvector/core/proto/dashvector_pb2.pyi,sha256=LVHOUH4XBJp9Wogb9t9Q3dVl_hRCzFGCt8VkH8iwu9w,88531
dashvector/core/proto/dashvector_pb2_grpc.py,sha256=WSvhrBt38pfXe9OrZwlV3P1xLd5c_KeraFba8Npysl0,33811
dashvector/util/__init__.py,sha256=ZiiWcXjS5x0Ov_ATOcVUgW2pH1dqRUbNdZl2MLXKJGg,671
dashvector/util/__pycache__/__init__.cpython-312.pyc,,
dashvector/util/__pycache__/convertor.cpython-312.pyc,,
dashvector/util/__pycache__/validator.cpython-312.pyc,,
dashvector/util/convertor.py,sha256=C9brkgn-nufst7B-PP77IJHYVWPOUGlXkceuUMVzRbM,1557
dashvector/util/validator.py,sha256=kGGcWPupMA-M08J7VoxOeSkpCILNtPi1NxLFzB4A0kY,2769
dashvector/version.py,sha256=MbZJUWjlP-w6sLfx1x_AKSxiseuYZVdIOvZmqlq2dAc,747

0
venv/Lib/site-packages/dashvector-1.0.22.dist-info/REQUESTED Normal file
View File

4
venv/Lib/site-packages/dashvector-1.0.22.dist-info/WHEEL Normal file
View File

@@ -0,0 +1,4 @@
Wheel-Version: 1.0
Generator: poetry-core 1.9.0
Root-Is-Purelib: true
Tag: py3-none-any