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The TakeBestPricedOfferTo*Btc needed to be split up so they are specific to fiat offers, and this change adds new TakeBestPricedOfferTo*Xmr bots just for XMR. This simplifies the the non-bsq-swap bots; documenting, coding, configuring, and logging the taking of both fiat and xmr (altcoin) offers in the same bots was getting confusing, and that's going to turn away potential users. This refactoring means there are six bots now, and it forced considerable refactoring in all of them. This commit is the bulk of the work for the PR, but there will be more changes after everything is tested again, and comments are adjusted.
Bisq API Reference Doc Generator
Generates content for the Bisq API Reference site.
What is bisq-api-reference?
This project's main purpose is to generate the Markdown text for the API Reference. It also provides a Java and Python workarea for running API client example code, and developing new Java and Python clients and bots.
It contains four subprojects:
- reference-doc-builder -- The Java application that produces the API Reference content, from Bisq protobuf definition files.
- cli-examples -- A folder of bash scripts demonstrating how to run API CLI commands. Each script is named for the RPC method call being demonstrated.
- java-examples -- A Java project demonstrating how to call the API from Java gRPC clients. Each class in the bisq.rpccalls package is named for the RPC method call being demonstrated.
- python-examples -- A Python3 project demonstrating how to call the API from Python3 gRPC clients. Each class in the bisq.rpccalls package is named for the RPC method call being demonstrated. There are also some simple bot examples in the bisq.bots package.
The RPC method examples are also displayed in the API Reference. While navigating the RPC method links in the reference's table of contents on the left side of the page, they appear in the dark, right side of the page. There is also a copy-to-clipboard icon at the top right of each example.
More details about the subprojects can be found in each subproject's README.
Languages
Java
81.5%
Python
15.6%
Shell
2.9%