Symplify usage

README.md

@@ -18,23 +18,23 @@ You can establish a connection to the MindsDB server using the SDK. Here are som
 
 ```python
 import mindsdb_sdk
-server = mindsdb_sdk.connect()
-server = mindsdb_sdk.connect('http://127.0.0.1:47334')
+con = mindsdb_sdk.connect()
+con = mindsdb_sdk.connect('http://127.0.0.1:47334')
 ```
 
 #### Connect to the MindsDB Cloud
 
 ```python
 import mindsdb_sdk
-server = mindsdb_sdk.connect(login='[email protected]', password='-')
-server = mindsdb_sdk.connect('https://cloud.mindsdb.com', login='[email protected]', password='-')
+con = mindsdb_sdk.connect(login='[email protected]', password='-')
+con = mindsdb_sdk.connect('https://cloud.mindsdb.com', login='[email protected]', password='-')
 ```
 
 ####  Connect to a MindsDB Pro server
 
 ```python
 import mindsdb_sdk
-server = mindsdb_sdk.connect('http://<YOUR_INSTANCE_IP>', login='[email protected]', password='-', is_managed=True)
+con = mindsdb_sdk.connect('http://<YOUR_INSTANCE_IP>', login='[email protected]', password='-', is_managed=True)
 ```
 
 ## Basic usage
@@ -43,7 +43,7 @@ Once connected to the server, you can perform various operations. Here are some
 
 ```python
 # Get a list of databases
-databases = server.list_databases()
+databases = con.databases.list()
 
 # Get a specific database
 database = databases[0]  # Database type object
@@ -53,24 +53,27 @@ query = database.query('select * from table1')
 print(query.fetch())
 
 # Create a table
-table = database.create_table('table2', query)
+table = database.tables.create('table2', query)
 
 # Get a project
-project = server.get_project('proj')
+project = con.projects.proj
+
+# or use mindsdb project
+project = con
 
 # Perform an SQL query within a project
 query = project.query('select * from database.table join model1')
 
 # Create a view
-view = project.create_view('view1', query=query)
+view = project.views.create('view1', query=query)
 
 # Get a list of views
-views = project.list_views()
+views = project.views.list()
 view = views[0]
 df = view.fetch()
 
 # Get a list of models
-models = project.list_models()
+models = project.models.list()
 model = models[0]
 
 # Use a model for prediction
@@ -83,7 +86,7 @@ timeseries_options = {
     'window': 5,
     'horizon': 1
 }
-model = project.create_model(
+model = project.models.create(
     'rentals_model',
     predict='price',
     query=query,
@@ -98,6 +101,10 @@ You can find more examples in this [Google colab notebook](
 https://colab.research.google.com/drive/1QouwAR3saFb9ffthrIs1LSH5COzyQa11#scrollTo=k6IbwsKRPQCR
 )
 
+## Examples
+
+https://github.com/mindsdb/mindsdb_python_sdk/tree/staging/examples
+
 ## API Documentation
 
 The API documentation for the MindsDB SDK can be found at https://mindsdb.github.io/mindsdb_python_sdk/. You can generate the API documentation locally by following these steps:

docs/requirements.txt

@@ -1,6 +1,6 @@
 requests
-pandas == 1.3.5
-mindsdb-sql >= 0.5.0, < 0.6.0
+pandas >= 1.3.5
+mindsdb-sql >= 0.7.0, < 0.8.0
 
 sphinx
 sphinx-rtd-theme

docs/source/database.rst

@@ -1,7 +1,7 @@
-Database
+Databases
 ----------------------------
 
-.. automodule:: mindsdb_sdk.database
+.. automodule:: mindsdb_sdk.databases
    :members:
    :undoc-members:
    :show-inheritance:

docs/source/handlers.rst

@@ -0,0 +1,7 @@
+Handlers
+-------------------------
+
+.. automodule:: mindsdb_sdk.handlers
+   :members:
+   :undoc-members:
+   :show-inheritance:

docs/source/index.rst

@@ -87,7 +87,12 @@ Base usage
           query=query,
     )
 
+    More
 
+More examples
+-----------
+
+`<https://github.com/mindsdb/mindsdb_python_sdk/examples>`_
 
 API documentation
 =================
@@ -105,9 +110,15 @@ API documentation
 
    server
    database
+   handlers
+   ml_engines
    project
    model
+   tables
+   views
    query
+   jobs
+
 
 Indices and tables
 ------------------

docs/source/jobs.rst

@@ -0,0 +1,7 @@
+Jobs
+-------------------------
+
+.. automodule:: mindsdb_sdk.jobs
+   :members:
+   :undoc-members:
+   :show-inheritance:

docs/source/ml_engines.rst

@@ -0,0 +1,7 @@
+ML Engines
+-------------------------
+
+.. automodule:: mindsdb_sdk.ml_engines
+   :members:
+   :undoc-members:
+   :show-inheritance:

docs/source/model.rst

@@ -1,7 +1,7 @@
-Model
+Models
 -------------------------
 
-.. automodule:: mindsdb_sdk.model
+.. automodule:: mindsdb_sdk.models
    :members:
    :undoc-members:
    :show-inheritance:

docs/source/project.rst

@@ -1,7 +1,7 @@
-Project
+Projects
 ---------------------------
 
-.. automodule:: mindsdb_sdk.project
+.. automodule:: mindsdb_sdk.projects
    :members:
    :undoc-members:
    :show-inheritance:

docs/source/tables.rst

@@ -0,0 +1,7 @@
+Tables
+-------------------------
+
+.. automodule:: mindsdb_sdk.tables
+   :members:
+   :undoc-members:
+   :show-inheritance:

docs/source/views.rst

@@ -0,0 +1,7 @@
+Views
+-------------------------
+
+.. automodule:: mindsdb_sdk.views
+   :members:
+   :undoc-members:
+   :show-inheritance:

examples/home_rentals.py

@@ -0,0 +1,37 @@
+
+import mindsdb_sdk
+
+con = mindsdb_sdk.connect()
+
+# connect to database
+db = con.databases.create(
+    'example_db',
+    engine='postgres',
+    connection_args={
+        "user": "demo_user",
+        "password": "demo_password",
+        "host": "3.220.66.106",
+        "port": "5432",
+        "database": "demo"
+    }
+)
+
+# get table
+# because table with schema we are using .get
+tbl = db.tables.get('demo_data.home_rentals')
+
+# create model
+model = con.models.create(
+    'home_rentals_model',
+    predict='rental_price',
+    query=tbl
+)
+
+# wait till training complete
+model.wait_complete()
+
+# make prediction for first 3 rows
+result = model.predict(tbl.limit(3))
+
+
+

examples/using_openai.py

@@ -0,0 +1,25 @@
+
+import mindsdb_sdk
+
+con = mindsdb_sdk.connect()
+
+openai_handler = con.ml_handlers.openai
+
+# create ml engine
+openai = con.ml_engines.create(
+    'openai',
+    handler=openai_handler,
+    # handler='openai', # <-- another option to define handler
+    connection_data={'api_key': ''}
+)
+
+# create model
+model = con.models.create(
+    'open1',
+    predict='answer',
+    engine=openai,  # created ml engine
+    prompt_template='answer question: {{q}}'
+)
+
+# use model
+model.predict({'q': 'size of the sun'})

examples/working_with_tables.py

@@ -0,0 +1,43 @@
+import mindsdb_sdk
+import pandas as pd
+
+con = mindsdb_sdk.connect()
+
+# get user's database (connected to mindsdb as rental_db)
+db = con.databases.rental_db
+
+# get table
+table1 = db.tables.house_sales
+
+
+# ---- create new table ----
+
+# copy create table house_sales and fill it with rows with type=house
+table2 = db.tables.create('house_sales2', table1.filter(type='house'))
+
+# create table from csv file
+df = pd.read_csv('my_data.csv')
+table3 = db.tables.create('my_table', df)
+
+
+# ---- insert into table ----
+
+# insert to table2 first 10 rows from table1
+table2.insert(table1.limit(10))
+
+
+# ---- update data in table ----
+
+# get all rows with type=house from table1 and update values in table2 using key ('saledate', 'type', 'bedrooms')
+table2.update(
+    table1.filter(type='house'),
+    on=['saledate', 'type', 'bedrooms']
+)
+
+
+# ---- delete rows from table ----
+
+# delete all rows where bedrooms=2
+table2.delete(bedrooms=2)
+
+

mindsdb_sdk/connect.py

@@ -1,5 +1,7 @@
 from mindsdb_sdk.server import Server
 
+from mindsdb_sdk.connectors.rest_api import RestAPI
+
 
 def connect(url: str = None, login: str = None, password: str = None, is_managed: bool = False) -> Server:
     """
@@ -39,4 +41,6 @@ def connect(url: str = None, login: str = None, password: str = None, is_managed
             # is local
             url = 'http://127.0.0.1:47334'
 
-    return Server(url=url, login=login, password=password, is_managed=is_managed)
+    api = RestAPI(url, login, password, is_managed)
+
+    return Server(api)