motion-lake-client 0.0.9

Motion Lake Client, a client for the Motion Lake API (a Mobility Data Lake)

MotionLake Client

MotionLake Client is a Python client library for interacting with a storage server designed for a new mobility data lake solution. It provides functionalities to create collections, store data, query data, and retrieve collections.

Installation

You can install the library via pip:

pip install motion-lake-client

Usage

Here's a brief overview of how to use the library:

from motion_lake_client import BaseClient

# Initialize the client with the base URL of the storage server
client = BaseClient(lake_url="http://localhost:8000")

# Create a new collection
client.create_collection("my_collection")

# Store data in a collection
data = b"example_data"
timestamp = int(datetime.now().timestamp())
client.store("my_collection", data, timestamp)

# Query data from a collection
results = client.query(
    "my_collection", min_timestamp=0, max_timestamp=timestamp, ascending=True
)

# Retrieve last item from a collection
last_item = client.get_last_item("my_collection")

# Retrieve first item from a collection
first_item = client.get_first_item("my_collection")

# Get items between two timestamps
items_between = client.get_items_between(
    "my_collection", min_timestamp=0, max_timestamp=timestamp
)

# Get items before a timestamp
items_before = client.get_items_before("my_collection", timestamp, limit=10)

# Get items after a timestamp
items_after = client.get_items_after("my_collection", timestamp, limit=10)

# Get all collections
collections = client.get_collections()

Documentation

The library provides a series of classes and methods for storing, querying, and managing collections of data items. Each item is timestamped and can be stored in various formats. Below is a detailed usage guide for each component provided by the API.

Prerequisites

Before using the API, make sure you have the requests library installed:

pip install requests

Initializing the Client

To start interacting with the data storage server, instantiate the BaseClient with the URL of the storage server:

from datetime import datetime
from my_module import BaseClient, ContentType

# Initialize the client; replace 'http://localhost:8000' with your server's URL
client = BaseClient('http://localhost:8000')

Creating a Data Collection

Create a new data collection by specifying its name:

response = client.create_collection("weather_data")
print(response)

Storing Data

Store data in a specified collection:

data = b"Example data"
timestamp = datetime.now()

# Store data as raw bytes
response = client.store("weather_data", data, timestamp, ContentType.RAW)
print(response)

You can also specify whether to create the collection if it doesn't exist:

response = client.store("weather_data", data, timestamp, ContentType.JSON, create_collection=True)
print(response)

Querying Data

Retrieve items from a collection based on various criteria:

• Query by Timestamp Range:

  from datetime import datetime, timedelta
  
  start_date = datetime.now() - timedelta(days=1)
  end_date = datetime.now()
  
  items = client.get_items_between("weather_data", start_date, end_date)
  for item in items:
      print("Timestamp:", item.timestamp, "Data:", item.data)
  

• Get Last N Items:

  last_items = client.get_last_items("weather_data", 5)
  for item in last_items:
      print("Timestamp:", item.timestamp, "Data:", item.data)
  

• Get First N Items:

  first_items = client.get_first_items("weather_data", 5)
  for item in first_items:
      print("Timestamp:", item.timestamp, "Data:", item.data)
  

Advanced Queries

Perform an advanced SQL-like query (make sure your query string contains the placeholder [table]):

query = "SELECT * FROM [table] WHERE data LIKE '%sample%'"
min_timestamp = datetime(2023, 1, 1)
max_timestamp = datetime(2023, 1, 31)

response = client.advanced_query("weather_data", query, min_timestamp, max_timestamp)
print(response)

Managing Collections

• List All Collections:

  collections = client.get_collections()
  for collection in collections:
      print(f"Collection: {collection.name}, Items: {collection.count}")
  

• Delete a Collection:

  response = client.delete_collection("weather_data")
  print(response)
  

Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue for any bugs or feature requests.

License

All rights reserved.