Official Python 3 client for SlicingDice - Data Warehouse and Analytics Database as a Service.
SlicingDice is a serverless, SQL & API-based, easy-to-use and really cost-effective alternative to Amazon Redshift and Google BigQuery.
If you are new to SlicingDice, check our quickstart guide and learn to use it in 15 minutes.
Please refer to the SlicingDice official documentation for more information on how to create a database, how to insert data, how to make queries, how to create columns, SlicingDice restrictions and API details.
Whether you want to test the client installation or simply check more examples on how the client works, take a look at the tests and examples directory.
In order to install the Python client, you only need to use pip
.
pip install pyslicer --extra-index-url=https://packagecloud.io/slicingdice/clients/pypi/simple
The following code snippet is an example of how to add and query data
using the SlicingDice python client. We entry data informing
user1@slicingdice.com
has age 22 and then query the database for
the number of users with age between 20 and 40 years old.
If this is the first register ever entered into the system,
the answer should be 1.
from pyslicer import SlicingDice
import asyncio
# Configure the client
client = SlicingDice(master_key='API_KEY')
loop = asyncio.get_event_loop()
# Inserting data
insert_data = {
"user1@slicingdice.com": {
"age": 22
},
"auto-create": ["dimension", "column"]
}
loop.run_until_complete(client.insert(insert_data))
# Querying data
query_data = {
"query-name": "users-between-20-and-40",
"query": [
{
"age": {
"range": [
20,
40
]
}
}
]
}
print(loop.run_until_complete(client.count_entity(query_data)))
SlicingDice
encapsulates logic for sending requests to the API. Its methods are thin layers around the API endpoints, so their parameters and return values are JSON-like dict
objects with the same syntax as the API endpoints
keys (str)
- API key to authenticate requests with the SlicingDice API.
__init__(self, write_key=None, read_key=None, master_key=None, custom_key=None, use_ssl=True, timeout=60)
write_key (str)
- API key to authenticate requests with the SlicingDice API Write Key.read_key (str)
- API key to authenticate requests with the SlicingDice API Read Key.master_key (str)
- API key to authenticate requests with the SlicingDice API Master Key.custom_key (str)
- API key to authenticate requests with the SlicingDice API Custom Key.use_ssl (bool)
- Define if the requests verify SSL for HTTPS requests.timeout (int)
- Amount of time, in seconds, to wait for results for each request.
Get information about current database(related to api keys informed on construction). This method corresponds to a GET
request at /database
.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_API_KEY')
loop = asyncio.get_event_loop()
print(loop.run_until_complete(client.get_database()))
{
"name": "Database 1",
"description": "My first database",
"dimensions": [
"default",
"users"
],
"updated-at": "2017-05-19T14:27:47.417415",
"created-at": "2017-05-12T02:23:34.231418"
}
Get all created columns, both active and inactive ones. This method corresponds to a GET request at /column.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_API_KEY')
loop = asyncio.get_event_loop()
print(loop.run_until_complete(client.get_columns()))
{
"active": [
{
"name": "Model",
"api-name": "car-model",
"description": "Car models from dealerships",
"type": "string",
"category": "general",
"cardinality": "high",
"storage": "latest-value"
}
],
"inactive": [
{
"name": "Year",
"api-name": "car-year",
"description": "Year of manufacture",
"type": "integer",
"category": "general",
"storage": "latest-value"
}
]
}
Create a new column. This method corresponds to a POST request at /column.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_API_KEY')
loop = asyncio.get_event_loop()
column = {
"name": "Year",
"api-name": "year",
"type": "integer",
"description": "Year of manufacturing",
"storage": "latest-value"
}
print(loop.run_until_complete(client.create_column(column)))
{
"status": "success",
"api-name": "year"
}
Insert data to existing entities or create new entities, if necessary. This method corresponds to a POST request at /insert.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_WRITE_API_KEY')
loop = asyncio.get_event_loop()
insert_data = {
"user1@slicingdice.com": {
"car-model": "Ford Ka",
"year": 2016
},
"user2@slicingdice.com": {
"car-model": "Honda Fit",
"year": 2016
},
"user3@slicingdice.com": {
"car-model": "Toyota Corolla",
"year": 2010,
"test-drives": [
{
"value": "NY",
"date": "2016-08-17T13:23:47+00:00"
}, {
"value": "NY",
"date": "2016-08-17T13:23:47+00:00"
}, {
"value": "CA",
"date": "2016-04-05T10:20:30Z"
}
]
},
"user4@slicingdice.com": {
"car-model": "Ford Ka",
"year": 2005,
"test-drives": {
"value": "NY",
"date": "2016-08-17T13:23:47+00:00"
}
},
"auto-create": ["dimension", "column"]
}
print(loop.run_until_complete(client.insert(insert_data)))
{
"status": "success",
"inserted-entities": 4,
"inserted-columns": 12,
"took": 0.023
}
Verify which entities exist in a dimension (uses default
dimension if not provided) given a list of entity IDs. This method corresponds to a POST request at /query/exists/entity.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
ids = [
"user1@slicingdice.com",
"user2@slicingdice.com",
"user3@slicingdice.com"
]
print(loop.run_until_complete(client.exists_entity(ids)))
{
"status": "success",
"exists": [
"user1@slicingdice.com",
"user2@slicingdice.com"
],
"not-exists": [
"user3@slicingdice.com"
],
"took": 0.103
}
Count the number of inserted entities in the whole database. This method corresponds to a POST request at /query/count/entity/total.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
print(loop.run_until_complete(client.count_entity_total()))
{
"status": "success",
"result": {
"total": 42
},
"took": 0.103
}
Count the total number of inserted entities in the given dimensions. This method corresponds to a POST request at /query/count/entity/total.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
dimensions = ['default']
print(loop.run_until_complete(client.count_entity_total(dimensions)))
{
"status": "success",
"result": {
"total": 42
},
"took": 0.103
}
Count the number of entities matching the given query. This method corresponds to a POST request at /query/count/entity.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
query = [
{
"query-name": "corolla-or-fit",
"query": [
{
"car-model": {
"equals": "toyota corolla"
}
},
"or",
{
"car-model": {
"equals": "honda fit"
}
}
],
"bypass-cache": False
},
{
"query-name": "ford-ka",
"query": [
{
"car-model": {
"equals": "ford ka"
}
}
],
"bypass-cache": False
}
]
print(loop.run_until_complete(client.count_entity(query)))
{
"status": "success",
"result": {
"corolla-or-fit": 2,
"ford-ka": 2
},
"took": 0.049
}
Count the number of occurrences for time-series events matching the given query. This method corresponds to a POST request at /query/count/event.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
query = [
{
"query-name": "test-drives-in-ny",
"query": [
{
"test-drives": {
"equals": "NY",
"between": [
"2016-08-16T00:00:00Z",
"2016-08-18T00:00:00Z"
]
}
}
],
"bypass-cache": True
},
{
"query-name": "test-drives-in-ca",
"query": [
{
"test-drives": {
"equals": "CA",
"between": [
"2016-04-04T00:00:00Z",
"2016-04-06T00:00:00Z"
]
}
}
],
"bypass-cache": True
}
]
print(loop.run_until_complete(client.count_event(query)))
{
"status": "success",
"result": {
"test-drives-in-ny": 3,
"test-drives-in-ca": 1
},
"took": 0.046
}
Return the top values for entities matching the given query. This method corresponds to a POST request at /query/top_values.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
query = {
"car-year": {
"year": 2
},
"car models": {
"car-model": 3
}
}
print(loop.run_until_complete(client.top_values(query)))
{
"result": {
"car models": {
"car-model": [
{
"quantity": 2,
"value": "ford ka"
},
{
"quantity": 1,
"value": "honda fit"
},
{
"quantity": 1,
"value": "toyota corolla"
}
]
},
"car-year": {
"year": [
{
"quantity": 2,
"value": "2016"
},
{
"quantity": 1,
"value": "2010"
}
]
}
},
"took": 0.034,
"status": "success"
}
Return the aggregation of all columns in the given query. This method corresponds to a POST request at /query/aggregation.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
query = {
"query": [
{
"car-model": 2,
"equals": [
"honda fit",
"toyota corolla"
]
}
]
}
print(loop.run_until_complete(client.aggregation(query)))
{
"result": {
"year": [
{
"quantity": 2,
"value": "2016",
"car-model": [
{
"quantity": 1,
"value": "honda fit"
}
]
},
{
"quantity": 1,
"value": "2005"
}
]
},
"took":0.079,
"status":"success"
}
Get all saved queries. This method corresponds to a GET request at /query/saved.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_API_KEY')
loop = asyncio.get_event_loop()
print(loop.run_until_complete(client.get_saved_queries()))
{
"status": "success",
"saved-queries": [
{
"name": "users-in-ny-or-from-ca",
"type": "count/entity",
"query": [
{
"state": {
"equals": "NY"
}
},
"or",
{
"state-origin": {
"equals": "CA"
}
}
],
"cache-period": 100
}, {
"name": "users-from-ca",
"type": "count/entity",
"query": [
{
"state": {
"equals": "NY"
}
}
],
"cache-period": 60
}
],
"took": 0.103
}
Create a saved query at SlicingDice. This method corresponds to a POST request at /query/saved.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_API_KEY')
loop = asyncio.get_event_loop()
query = {
"name": "my-saved-query",
"type": "count/entity",
"query": [
{
"car-model": {
"equals": "honda fit"
}
},
"or",
{
"car-model": {
"equals": "toyota corolla"
}
}
],
"cache-period": 100
}
print(loop.run_until_complete(client.create_saved_query(query)))
{
"status": "success",
"name": "my-saved-query",
"type": "count/entity",
"query": [
{
"car-model": {
"equals": "honda fit"
}
},
"or",
{
"car-model": {
"equals": "toyota corolla"
}
}
],
"cache-period": 100,
"took": 0.103
}
Update an existing saved query at SlicingDice. This method corresponds to a PUT request at /query/saved/QUERY_NAME.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_API_KEY')
loop = asyncio.get_event_loop()
new_query = {
"type": "count/entity",
"query": [
{
"car-model": {
"equals": "honda fit"
}
},
"or",
{
"car-model": {
"equals": "toyota corolla"
}
}
],
"cache-period": 100
}
print(loop.run_until_complete(client.update_saved_query('my-saved-query', new_query)))
{
"status": "success",
"name": "my-saved-query",
"type": "count/entity",
"query": [
{
"car-model": {
"equals": "honda fit"
}
},
"or",
{
"car-model": {
"equals": "toyota corolla"
}
}
],
"cache-period": 100,
"took": 0.103
}
Executed a saved query at SlicingDice. This method corresponds to a GET request at /query/saved/QUERY_NAME.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
print(loop.run_until_complete(client.get_saved_query('my-saved-query')))
{
"status": "success",
"type": "count/entity",
"query": [
{
"car-model": {
"equals": "honda fit"
}
},
"or",
{
"car-model": {
"equals": "toyota corolla"
}
}
],
"result": {
"my-saved-query": 2
},
"took": 0.043
}
Delete a saved query at SlicingDice. This method corresponds to a DELETE request at /query/saved/QUERY_NAME.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_API_KEY')
loop = asyncio.get_event_loop()
print(loop.run_until_complete(client.delete_saved_query('my-saved-query')))
{
"status": "success",
"deleted-query": "my-saved-query",
"type": "count/entity",
"query": [
{
"car-model": {
"equals": "honda fit"
}
},
"or",
{
"car-model": {
"equals": "toyota corolla"
}
}
],
"took": 0.043
}
Retrieve inserted values for entities matching the given query. This method corresponds to a POST request at /data_extraction/result.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
query = {
"query": [
{
"car-model": {
"equals": "ford ka"
}
},
"or",
{
"car-model": {
"equals": "honda fit"
}
}
],
"columns": ["car-model", "year"],
"limit": 2
}
print(loop.run_until_complete(client.result(query)))
{
"status": "success",
"data": {
"customer5@mycustomer.com": {
"year": "2005",
"car-model": "ford ka"
},
"user1@slicingdice.com": {
"year":"2016",
"car-model": "ford ka"
}
},
"page": 1,
"took": 0.053
}
Retrieve inserted values as well as their relevance for entities matching the given query. This method corresponds to a POST request at /data_extraction/score.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
query = {
"query": [
{
"car-model": {
"equals": "toyota corolla"
}
},
"or",
{
"car-model": {
"equals": "honda fit"
}
}
],
"columns": ["car-model", "year"],
"limit": 2
}
print(loop.run_until_complete(client.score(query)))
{
"status": "success",
"data": {
"user3@slicingdice.com": {
"score": 1,
"year": "2010",
"car-model": "toyota corolla"
},
"user2@slicingdice.com": {
"score": 1,
"year": "2016",
"car-model": "honda fit"
}
},
"page": 1,
"next-page": null,
"took": 0.063
}
Retrieve inserted values using a SQL syntax. This method corresponds to a POST request at /query/sql.
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
query = "SELECT COUNT(*) FROM default WHERE age BETWEEN 0 AND 49"
print(loop.run_until_complete(client.sql(query)))
from pyslicer import SlicingDice
import asyncio
client = SlicingDice('MASTER_OR_READ_API_KEY')
loop = asyncio.get_event_loop()
query = "INSERT INTO default([entity-id], name, age) VALUES(1, 'john', 10)"
print(loop.run_until_complete(client.sql(query)))
{
"took":0.063,
"result":[
{"COUNT": 3}
],
"count":1,
"status":"success"
}
Official Python 3 client for SlicingDice, Data Warehouse and Analytics Database as a Service.