To start building a distributed ledger, you will need to install Credits Core framework, lay out your dapp scaffold and bootstrap your development network.
The Credits Core framework is written in Python and going forwards we will be using standard Python tools to work with it.
Before installing the framework please make sure these external system dependencies are met:
- python pip
To install the framework run:
pip install git+ssh://firstname.lastname@example.org/CryptoCredits/credits-core.git
You may want to use virtualenv to contain all installed python packages instead of putting it into your global system space.
The framework contains
credits CLI tool that you will use to template
your dapps and bootstrap your local dev network.
Once Credits Core is installed you can run:
credits dapp create --name <dapp_name>
This will create a
./<dapp_name> folder and a scaffold of the Credits
dapp inside it. You will use it to develop your distributed ledger.
Your dapp is effectively a python package, and it needs to be made discoverable for Credits Core framework to allow it to be later included into the ledger. To achieve this run:
pip install -e ./<dapp_name>
network.yaml file is created as part of the dapp scaffold. It is
used in both the dapp configuration, and as a base for the next step –
You need a distributed ledger network to both run your dapp and integrate your client applications. To bootstrap a distributed ledger network run:
credits local create ./<dapp_name>/network.yaml
This will roll out configuration for a single node network in the
./node00 folder. It contains all you will need to run
the Credits Core network node.
You can also create multi-node network if needed by adding param
To run the network node you will need to start the nodes you have just created. You do this with:
credits local run ./node00/*.yaml
To start the node you need to provide it with both the network config,
which is copied to the node folder and the node config itself. Both
are located in the node folder as
This starts node process in the foreground and outputs the node logs into stdout.
loglevel in node config is set to
WARNING, you may want
to make it more verbose with
--log-level <LOG_LEVEL> option.
If you need to run a network of several nodes - you will need to run each node separately.