Metadata Portal is a self-hosted web page that shows you the latest metadata for a given network.
This is an important addition to Signer, which can update the metadata inside only through a special video QR code without going online. Parity will host its own version of the page for all chains for which we sign the metadata. External users (chain owners) will be able to deploy their versions of metadata portal if they want.
It all starts with the Github repository. Any user can clone it and run their Metadata Portal. We also host our own version, so let’s break down the principles of working on it.
Metadata Portal supports two metadata sources in parallel. Both are equally important for different types of users.
This flow is important for all users who want to always have the latest metadata in their signing devices to parse and sign their transactions right away.
make signer
locally to sign new metadata using his signing air-gapped deviceThis flow is for security-oriented users and Parity itself. It allows chain owners to sign their metadata updates and host QR codes for their users.
You can use Github Pages to host the metadata-portal for your set of chains
config.toml
gh-pages
branch (Settings
-> Pages
-> Source
)homepage
field in package.json
public/CNAME
fileNOTIFY_MATRIX: false
in .github/workflows/update.yml
MATRIX_SERVER
, MATRIX_ROOM_ID
, MATRIX_ACCESS_TOKEN
values to project Actions secretsThe main requirement is the OpenCV. You can check this manual: https://crates.io/crates/opencv
OpenCV package in Arch is suitable for this.
pacman -S clang qt5-base opencv
sudo apt install libopencv-dev clang libclang-dev
You have several options of getting the OpenCV library:
install it from the repository, make sure to install -dev
packages because they contain headers necessary
for the crate build (also check that your package contains pkg_config
or cmake
files).
build OpenCV manually and set up the following environment variables prior to building the project with
opencv
crate:
PKG_CONFIG_PATH
for the location of *.pc
files or OpenCV_DIR
for the location of *.cmake
filesLD_LIBRARY_PATH
for where to look for the installed *.so
files during runtimeAdditionally, please make sure to install clang
package or its derivative that contains libclang.so
and
clang
binary.
clang
clang
and libclang-dev
brew install opencv
If you’re getting dyld: Library not loaded: @rpath/libclang.dylib
:
OS can’t find libclang.dylib dynamic library because it resides in a non-standard path, set up the DYLD_FALLBACK_LIBRARY_PATH environment variable to point to the path where libclang.dylib can be found, e.g. for XCode:
export DYLD_FALLBACK_LIBRARY_PATH="$(xcode-select --print-path)/Toolchains/XcodeDefault.xctoolchain/usr/lib/"
Before running the frontend locally, you need to generate a data file:
make collector
And then run the app in the development mode
yarn start