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Run a full node in testnet

This tutorial shows you how to run a full node and meet the requirements to apply to becoming a masternode candidate on Shifu, you have to run the Tao client, which is our Tao implementation written in Go.

General hardware notice

The Tao team has extensively tested performances and come up with those minimal requirements for any Tao masternode host.

Testnet

  • Must be facing internet directly (no NAT, public IP)
  • Must have at least 2 cores
  • Must have at least 8GB of RAM
  • Must use an IaaS ("cloud") provider of your choice (AWS, Digital Ocean, Google Cloud, etc.).
  • Storage must be SSD

Mainnet

  • Must be facing internet directly (no NAT, public IP)
  • Must have at least 16 cores
  • Must have at least 32GB of RAM
  • Must use an IaaS ("cloud") provider of your choice (AWS, Digital Ocean, Google Cloud, etc.)
  • Storage must be SSD

We recommand prioritizing CPU. For example with Digital Ocean, pick a CPU optimized droplet. On AWS EC2, an C5 type instance would be a perfect match.

The full node will serve on port 20202 udp and tcp for p2p communication with other nodes, 8545 tcp for RPC api and 8546 tcp for websocket api. You may need to edit your firewall configuration accordingly.

If you have other production grade environment than cloud provider at your displosal, please tell us more about on our Gitter.

taomn

We made a simple command line interface called taomn to easily and quickly start a Tao full node. It takes care of starting the necessary docker containers with the proper settings for you. It will really suit you if you don't already have a big infrastructure running. Spin up a machine in your favorite cloud and get your full node running in a few minutes!

Prerequisites

To use taomn, you should meet these requirements in addition to the hardware ones:

Installation

Simply install it from pip.

pip3 install --user taomn

Update

Update it from pip.

pip3 install -U taomn

First start

When you first start your full node with taomn, you need to give some informations.

--name: The name of your full node. It should be formatted as a slug string. Slug format authorize all letters and numbers, dashes ("-") and underscores ("_"). You can name it to reflect your identity, company name, etc.

--net: The network your full node will connect to. You can choose here to connect it to the Tao Testnet or Mainnet (once launched).

--pkey: The private key of the account that your full node will use. A Tao full node uses an account to be uniquely identified and to receive transaction fee.

Important note: we advise for security measures to use a fresh new account for your masternode. This is not the account who will receive the rewards. The rewards are sent to the account who will make the 50k TAO initial deposit.

It could look like this:

taomn start --name [YOUR_NODE_NAME] \
    --net testnet \
    --pkey [YOUR_COINBASE_PRIVATE_KEY]

Once started, you should see your node on the testnet stats page or the mainnet stats page, depending on which net you are connecting to!

Note: it can take up to one hour or more (depending on the blockchain data size) to properly sync the entire blockchain.

Usage

You can now interact with it via the other commands:

stop: Stop your full node.

start: Start your full node if it is stopped.

status: The current status of your full node.

inspect: Display the details related to your full node. Useful for applying your full node as a masternode.

remove: Completely remove your masternode, unique identity and data.

Troubleshooting

taomn: command not found

It might happen that your PATH is not set by default to include the default user binary directory. You can add it by adding it to your shell $PATH:

On GNU/Linux:

echo 'export PATH=$PATH:~/.local/bin' >> ~/.bashrc

On MacOS: Replace [VERSION] by your version of python (3.5, 3.6, 3.7)

echo 'export PATH=$PATH:~/Library/Python/[VERSION]/bin' >> ~/.bashrc

error: could not access the docker daemon

If you have installed Docker, you probably forgot to add your user to the docker group. Please run this, close your session and open it again.

usermod -aG docker $your_user_name