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LBRY Chainquery

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OS Specifics


  • In order to use wget you will need brew install wget (used in
  • Chainquery is built for Linux by default in, so you will need to modify the cross compilation for an OSX build.
  • Be sure to give execute privileges to the scripts you plan to use.


Make sure you have Go 1.11+ (required for go-releaser)


  • Install and run mysql 8 (OSX: brew install mysql)
  • Create chainquery database.
  • Create user lbry with password lbry and grant it all permissions on chainquery db.


  • Install lbrycrdd (

  • Ensure ~/.lbrycrd/lbrycrd.conf file exists with username and password. If you don't have one, run:

    mkdir -p ~/.lbrycrd
    echo -e "rpcuser=lbryrpc\nrpcpassword=$(env LC_CTYPE=C LC_ALL=C tr -dc A-Za-z0-9 < /dev/urandom | head -c 16 | xargs)" >> ~/.lbrycrd/lbrycrd.conf
  • Run ./lbrycrdd -server -daemon -txindex -conf=$HOME/.lbrycrd/lbrycrd.conf. If you get an error about indexing, add the -reindex flag for one run. You will only need to reindex once.


Chainquery can be configured via toml file.

Running from Source

go get -u
cd "$(go env GOPATH)/src/"

Running from Release

This will likely eventually be the main supported method of running Chainquery in your environment but this sections documentation is a WIP so YMMV

Get a download link for your operating system specific release from the releases page then use the following command with your download link.

  wget -O ~/
  wget -O ~/

Unzip the package you just downloaded with the following.

cd ~/
unzip ~/

Your console should show you something similar to the following.

root@8fe4046b6d46:~# unzip
  inflating: LICENSE
  inflating: chainquery

Of course you don't have to extract all of this stuff to your machines home directory ~/ you must use whatever paths you prefer. One that could be beneficial is adding these executables into your systems $PATH this is out of the scope of this README.

The main Chainquery binary should be marked as Executable by default but if not you can run the following.

chmod +x ~/chainquery

Finally running chainquery should be as simple as.

~/chainquery serve

You can obtain information on the flags in Chainqueries main binary by running the following.

~/chainquery -help

The Model

The model of Chainquery at its foundation consists of the fundamental data types found in the block chain. This information is then expounded on with additional columns and tables that make querying the data much easier.

What does Chainquery consist of?

Chainquery consists of 4 main parts. The API Server, the Daemon, the Job Scheduler, and the upgrade manager.

API Server

The API Server services either structured queries via defined APIs or raw SQL against the Chainquery MySQL database. The APIs are documented via Chainquery APIs, a work in progress :) .


The Daemon is responsible for updating the Chainquery database to keep it in sync with lbrycrd data. The daemon runs periodically to check if there are newly created blocks that need to be processed. The Daemon simply processes the block and its transactions. It also handles blockchain reorganizations. It will remove the orphaned block data and processing the new blocks from that height it diverged. The entry points are daemon iterations(func daemonIteration()) block processing(func RunBlockProcessing(height *uint64)), transaction processing(func ProcessTx(jsonTx *lbrycrd.TxRawResult, blockTime uint64)).

Job Scheduler

The job scheduler schedules different types of jobs to update the Chainquery database example. These jobs synchronize different areas of the data either to make queries faster or ascertain information that is not directly part of the raw blockchain. The example provided is leveraged to handle the status of a claim which is actually stored in the ClaimTrie of LBRYcrd. So it runs periodically to make sure Chainquery has the most up to date status of claims in the trie. The table job_status stores the current state of a particular job, like when it last synced.

Upgrade Manager

The upgrade manager handles data upgrades between versions. The table application_status stores information about the state of the application as it relates to the data, api and app versions. This is all leveraged by the upgrade manager so it knows what scripts might need to be run to keep the data in sync across deployments. The scripts are foundation of the upgrade manager.


Contributions to this project are welcome, encouraged, and compensated. For more details, see

The master branch is regularly built and tested, but is not guaranteed to be completely stable. Releases are created regularly to indicate new official, stable release versions.

Developers are strongly encouraged to write unit tests for new code, and to submit new unit tests for old code. Unit tests can be compiled and run with: go test ./... from the source directory which should be $GOPATH/

All contributions should run the e2e test via ./e2e/ This requires Docker to be installed.

Updating the generated models

We use sqlboiler to generate our data models based on the db schema. If you make schema changes, run ./ to regenerate the models.

A note of caution: the models are generated by connecting to the MySQL server and inspecting the current schema. If you made any db schema changes by hand, then the schema may be out of sync with the migrations. Here's the safe way to ensure that the models match the migrations:

  • Put all the schema changes you want to make into a migration.
  • In mysql, drop and recreate the db you're using, so that it's empty.
  • Run ./ This will run all the migrations on the empty db.
  • Run ./ to update the models.

This process ensures that the generated models will match the updated schema exactly, so there are no surprises when the migrations are applied to the live db.


This project is MIT licensed. For the full license, see LICENSE.


We take security seriously. Please contact regarding any security issues. Our PGP key is here if you need it.


The primary contact for this project is @tiger5226 (beamer -at-