Access Object Store on Local Install

Yes, it is possible to access the Object Store from a local install. The Object Store is an organization-specific key-value storage location to save and retrieve data. It is shared across the entire organization, and you can access data across all projects in an organization using the same key.

Here are the steps to access the Object Store:

1. Log in to your account and set up your first organization workspace. You can follow the instructions provided in the QuantConnect documentation.

2. After setting up your workspace, you can use the lean object-store get command to open the local storage directory in the file explorer. This command is part of the Lean CLI API.

3. To access the data you store in the Object Store from backtests, the Research Environment, and live algorithms, you can iterate through the ObjectStore object. Here is an example in Python:

for kvp in qb.ObjectStore:
    key = kvp.Key
    value = kvp.Value

1. To store an object that is in a different format, you need to encode it to one of the supported data types. For instance, if you train a machine learning model and it is in binary format, encode it into base 64 before saving it. Here is an example in Python:

self.ObjectStore.Save(string_key, string_value)
self.ObjectStore.SaveBytes(bytes_key, bytes_value)

1. To retrieve the stored objects, you can use the Read or ReadBytes methods. Here is an example in Python:

string_value = self.ObjectStore.Read(string_key)
bytes_value = self.ObjectStore.ReadBytes(bytes_key)

Remember, the Object Store is organization-specific. When you save data in the Object Store, it creates a new file in the organization workspace / storage / projectName directory and names the file with the key you provide. To access the storage data of project A from project B, include the project id of project A to the key.

For complete examples of using the Object Store, see the Object Store documentation.

If you access something locally from the Object Store, can you use your local computer CPU and GPU to analyze it?

Yes, once you have accessed data from the Object Store locally, you can use your local computer's CPU and GPU to analyze it. The data you retrieve from the Object Store is just like any other data you would process on your local machine.

However, it's important to note that while you can use your local CPU for any kind of data processing, using your local GPU might require specific setup depending on the kind of analysis you want to perform. For instance, if you want to use your GPU for machine learning tasks, you might need to have specific libraries installed, such as TensorFlow or PyTorch, and these libraries should be configured to use your GPU.

As for QuantConnect's LEAN engine, it supports running backtests on local hardware, but it's not explicitly mentioned in the extracts whether it can utilize local GPU for acceleration. However, QuantConnect's cloud platform does support GPU for backtesting and research computations, which might require additional subscription fees.

If you want to use your local GPU for backtesting, you might need to modify LEAN's source code to support GPU acceleration. This might require some programming knowledge and understanding of how LEAN works internally. You can check out QuantConnect's documentation for more information about running backtests locally.