StellarDS 0.0.1.1

StellarDS.io SDK for Python

StellarDS Python SDK

Introduction

In the world of Python development, efficient database integration is crucial for building applications. We present the free StellarDS.io Python library to simplify database interactions. For developers looking to get started, you can easily access this on PyPI or on our Github repository, which includes a demo to help you get started with StellarDS.io.

Create a Python Application

Setup

1. Navigate to StellarDS.io and sign up for Stellar Datastore if not already done.
2. Go to Managa Database from the navigation bar.
3. Under Applications select to get access to your database via OAuth or via access tokens.
   1. When choosing OAuth, set a befitting name and set up the CallbackUrl as follows http://localhost:8080. Choose the required role for people to determine the access rights the application should have. Be sure to keep the client_secret and client_id for later.
   2. When choosing Access Tokens, set a befitting name and set up the duration of validity of the access token. Choose the required role for people to determine the access rights the application should have. Leave the domain empty.
4. In your Python environment execute the following command:

   pip install stellards requests cryptography
   

Initializing the SDK

To start using the StellarDS.io SDK you should first import the StellarDS class and create an instance of this class. When creating the instance you've got the option to either use OAuth or Access Token. And an option to save your tokens in a seperate file, so authenthication isn't required every time you start the script.

from StellarDS import StellarDS

stellar_ds = StellarDS(is_oauth=False, is_persistent=False)

When setting the boolean is_oauth to True, we should start the OAuth-flow with the required parameters.

stellar_ds.oauth('your_client_id', 'http://localhost:8080', 'your_client_secret')

When setting the boolean is_oauth to False, we can start using the SDK after an access_token was provided.

stellar_ds.access_token('your_access_token')

When setting the boolean is_persistent to True, when logging in a new file will be created with your encrypted tokens. This is so you don't have to keep logging in when restarting your application.

Test Connection

To check if everything is setup correctly you could use the ping() function.

stellar_ds.ping()

Project

When working with projects, it's recommended to import the Project class, since it can be used in some methods.

from StellarDS import Project

To get information on a specific project, you could use:

stellar_ds.project.get('project_id')

Or leave it empty to get the projects which you are a part of:

stellar_ds.project.get()

To update a project, you can use the built-in Project class.

project_data = Project('name', 'description', True)
stellar_ds.project.update('project_id', project_data)

Each call you make wil return a Project Response class which contains the following information:

• data
  • id
  • name
  • description
  • is_multitenant
• messages
  • code
  • message
  • type
• is_succes
• status_code

For example, if you want to get the name of one of your projects:

stellar_ds.project.get().data[0].name

Table

When working with tables it's recommended to import the Table class, since it can be used in some methods.

from StellarDS import Table

To get information on a specific table you could use:

stellar_ds.project.get('project_id', 'table_id')

You can also get all your tables.

stellar_ds.project.get('project_id')

To update an existing project you can use the built-in Table class.

table_data = Table('name', 'description', True)
stellar_ds.table.update('project_id', 'table_id' table_data)

It's also possible to add a table in the following way:

table_data = Table('name', 'description', True)
stellar_ds.table.add('project_id', table_data)

And deleting a table can be done as follows:

stellar_ds.table.delete('project_id', 'table_id')

Each call you make wil return a Table Response class which contains the following information:

• data
  • id
  • name
  • description
  • is_multitenant
• messages
  • code
  • message
  • type
• is_succes
• status_code

So for example, if you want to get the name of a specific table:

stellar_ds.table.get('project_id', 'table_id').data.name

Field

When working with fields it's recommended to import the Field class, since it can be used in some methods.

from StellarDS import Field

To get information on a specific field you could use:

stellar_ds.field.get('project_id', 'table_id', 'field_id')

You can also get all your fields from a specific table.

stellar_ds.field.get('project_id', 'table_id')

To update an existing project, you can use the build in Field class.

field_data = Field('name', 'type')
stellar_ds.field.update('project_id', 'table_id', 'field_id', field_data)

It's also possible to add a field to a table in the following way:

field_data = Field('name', 'type')
stellar_ds.field.add('project_id', 'table_id', field_data)

And deleting a field can be done as followed:

stellar_ds.field.delete('project_id', 'table_id', 'field_id')

When updating or adding a field, it's possible to specify a datatype. Here are all the possible types that can be used:

• BigInt
• Boolean
• Blob
• DateTime
• Float
• Int
• NvarChar(255)
• Real
• SmallInt
• TinyInt

Each call you make wil return a Field Response class which contains the following information:

• data
  • id
  • name
  • type
• messages
  • code
  • message
  • type
• is_succes
• status_code

As example, if you want to get the status_code of your request:

stellar_ds.field.get('project_id', 'table_id', 'field_id').status_code

Data

When working with data it's recommended to import the DataQueries and RecordList classes, since it can be used in some methods.

from StellarDS import DataQueries, RecordList

To get information on data in a table, you could use:

stellar_ds.data.get('project_id', 'table_id')

It's possible to add an extra parameter with different queries by using the DataQueries class.

• Offset

queries = DataQueries(Offset='number')
stellar_ds.data.get('project_id', 'table_id', queries)

• Take

queries = DataQueries(Take='number')
stellar_ds.data.get('project_id', 'table_id', queries)

• JoinQuery

queries = DataQueries(JoinQuery='table1;field1=table2;field2')
stellar_ds.data.get('project_id', 'table_id', queries)

• WhereQuery

queries = DataQueries(WhereQuery='field1;condition1;value1&field2;condition2;value2')
stellar_ds.data.get('project_id', 'table_id', queries)

• SortQuery

queries = DataQueries(SortQuery='field1;asc|desc&Field2;asc|desc')
stellar_ds.data.get('project_id', 'table_id', queries)

To update existing data, you can use the build in RecordList class to specify which data you want to change. The method also requires a class with your data you wish to change.

class Record:
    def __init__(self, field1 , field2):
        self.field1, self.field2 = field1, field2

record = Record('field1', 'field2')
recordList = RecordList(['record_id1', 'record_id2'])
stellar_ds.data.update('project_id', 'table_id', record, recordList, True)

It's also possible to add data in the following way:

record = Record('field1', 'field2')
stellar_ds.data.add('project_id', 'table_id', record)

And deleting data can be done as follows:

recordList = RecordList(['record_id1'])
stellar_ds.data.delete('project_id', 'table_id', recordList)

You could also immediately clear the full table.

data_clear_response = stellar_ds.data.clear('project_id', 'table_id')

When working with a Blob things are a little bit different. To fetch blob data, you could use:

stellar_ds.data.blob.get('project_id', 'table_id', 'record_id', 'field_name')

And adding would be done like follows:

data = 'record_bytes'
stellar_ds.data.blob.add('project_id', 'table_id', 'record_id', 'field_name', data)

Each normal call you make wil return a Data Response class which contains the following information:

• data
  • field1
  • field2
  • field3
• messages
  • code
  • message
  • type
• is_succes
• status_code
• count

When making a call for a Blob you will get a Blob Response class with this information:

• data
  • bytes
• messages
  • code
  • message
  • type
• is_succes
• status_code

For example, if you want to get the bytes from a blob of your request:

stellar_ds.data.blob.get('project_id', 'table_id', 'record_id', 'field_name').data.bytes

User

When working with users, it's recommended to import the User class, since it can be used in some methods.

from StellarDS import User

To get information on the user, you could use:

stellar_ds.user.get()

To update the current user, you can use the build in User class.

user = User(username='username', email='email')
stellar_ds.user.update(user)

Each call you make wil return a User Response class which contains the following information:

• data
  • username
  • email
• messages
  • code
  • message
  • type
• is_succes
• status_code

For instance, if you want to get the email of your user:

stellar_ds.user.get().data.email

Project Tier

To get information on the Project Tier you could use:

stellar_ds.projecttier.get('project_id')

To get the current used Project Tier statistics, you can use:

stellar_ds.projecttier.current.get('project_id')

Each call you make wil return a Project Tier Response class which contains the following information:

• data
  • name
  • users
  • tables
  • max_requests
• messages
  • code
  • message
  • type
• is_succes
• status_code

So if you want to get the current tables used in your Project Tier:

stellar_ds.projecttier.current.get('project_id').data.tables

Events

If you want to get notified when you got a new access_token, you could use:

stellar_ds.on_access_token('function')

If you want to get notified when a request is started, you could use:

stellar_ds.on_request_start('function')

If you want to get notified when a request is finished`, you could use:

stellar_ds.on_request_done('function')

So for example if you want to print() something when a request is finished:

def request_finished():
    print("text")

stellar_ds.on_request_done(request_finished)