pymilvus-test 0.2.32

Python Sdk for Milvus

Milvus Python SDK -- pymilvus

Using Milvus python sdk for Milvus Download

Pymilvus only supports python >= 3.5, is fully tested under 3.5, 3.6, 3.7.

Pymilvus can be downloaded via pip. If no use, try pip3

$ pip install pymilvus

Different versions of Milvus and lowest/highest pymilvus version supported accordingly

Milvus version	Lowest pymilvus version supported	Highest pymivus version supported
0.3.0	-	0.1.13
0.3.1	0.1.14	0.1.25
0.4.0	0.2.0	0.2.2
0.5.0	0.2.3	-

You can download a specific version by:

$ pip install pymilvus==0.2.3

If you want to upgrade pymilvus to newest version

$ pip install --upgrade pymilvus

Import

from milvus import Milvus, IndexType, MetricType, Status

Getting started

Initial a Milvus instance and connect to the sever

>>> milvus = Milvus()

>>> milvus.connect(host='localhost', port='19530')
Status(code=0, message='Successfully connected! localhost:19530')

Once successfully connected, you can get the version of server

>>> milvus.server_version()
(Status(code=0, message='Success'), '0.5.0')  # this is example version, the real version may vary

---

Add a new table

First set param

>>> dim = 32  # Dimension of the vector
>>> param = {'table_name':'test01', 'dimension':dim, 'index_file_size':1024, 'metric_type':MetricType.L2}

Then create table

>>> milvus.create_table(param)
Status(code=0, message='Create table successfully!')

Describe the table we just created

>>> milvus.describe_table('test01')
(Status(code=0, message='Describe table successfully!'), TableSchema(table_name='test01', dimension=32, index_file_size=1024, metric_type=<MetricType: L2>))

---

Add vectors into table test01

First create 20 vectors of 256-dimension.

• Note that random and pprint we used here is for creating fake vectors data and pretty print, you may not need them in your project

>>> import random
>>> from pprint import pprint

# Initialize 20 vectors of 256-dimension
>>> vectors = [[random.random() for _ in range(dim)] for _ in range(20)]

Then add vectors into table test01

>>> status, ids = milvus.add_vectors(table_name='test01', records=vectors)
>>> print(status)
Status(code=0, message='Add vectors successfully!')
>>> pprint(ids) # List of ids returned
[1571123848227800000,
 1571123848227800001,
    ...........
 1571123848227800018,
 1571123848227800019]

You can also specify vectors id

>>> vector_ids = [i for i in range(20)]
>>> status, ids = milvus.add_vectors(table_name='test01', records=vectors, ids=vector_ids)
>>> pprint(ids)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]

Get vectors num

>>> milvus.get_table_row_count('test01')
(Status(code=0, message='Success!'), 20)

---

Load vectors into memory

>>> milvus.preload_table('test01')
Status(code=0, message='')

---

Create index

>>> index_param = {'index_type': IndexType.FLAT, 'nlist': 128}
>>> milvus.create_index('test01', index_param)
Status(code=0, message='Build index successfully!')

Then show index information

>>> milvus.describe_index('test01')
(Status(code=0, message='Successfully'), IndexParam(_table_name='test01', _index_type=<IndexType: FLAT>, _nlist=128))

---

Search vectors

# create 5 vectors of 256-dimension
>>> q_records = [[random.random() for _ in range(dim)] for _ in range(5)]

Then get results

>>> status, results = milvus.search_vectors(table_name='test01', query_records=q_records, top_k=1, nprobe=16)
>>> print(status)
Status(code=0, message='Search vectors successfully!')
>>> pprint(results) # Searched top_k vectors
[
[(id:15, distance:2.855304718017578),
 (id:16, distance:3.040700674057007)],
[(id:11, distance:3.673950433731079),
 (id:15, distance:4.183730602264404)],
      ........
[(id:6, distance:4.065953254699707),
 (id:1, distance:4.149323463439941)]
]

---

Drop index

>>> milvus.drop_index('test01')
Status(code=0, message='')

---

Delete the table we just created

>>> milvus.delete_table(table_name='test01')
Status(code=0, message='Delete table successfully!')

Disconnect with the server

>>> milvus.disconnect()
Status(code=0, message='Disconnect successfully')

---

Example python

There are some small examples in examples/, you can find more guide there.

Build docs

$ sphinx-build -b html doc/en/ doc/en/build

If you encounter any problems or bugs, please open new issues