Introduction¶

What you will find here¶

Welcome to the documentation of Gerber tooling within PyGerber library. This part of documentation will cover most of the features of PyGerber which have to do with consuming and changing Gerber files.

In particular, you can learn here how to:

Generation of Gerber files is covered separately by Gerber code generation guide.

Adding rendering backends is covered by documentation of Virtual Machines.

Design overview¶

In this section we will cover the general design of Gerber tooling within PyGerber. Let's start with basic stages of Gerber processing which have to be performed to create PNG image out of Gerber file.

Parser¶

First of all, Gerber files have to be loaded into memory and parsed into Abstract Syntax Tree (AST). This is done by a parser, currently PyGerber has only one Gerber parser, based on pyparsing library, available as pygerber.gerber.parser.pyparsing.Parser class. Currently work is being done to provide plugin interface which would allow to use parsers implemented as separate packages. Alongside that initiative, a C++ based Gerber parser is being implemented.

Compiler¶

After obtaining AST it is converted to a special assembly like format called Rendering Virtual Machine Commands (RVMC). This conversion is handled by a Compiler class. RVMC representation is much simpler, it does not differentiate between rectangles, obrounds, circles and other Gerber constructs, but rather represents everything as shapes built out of lines and arcs. This simplification allows it to be very generic and quite easy to implement.

Virtual Machine¶

Once RVMC is obtained, it is passed to one of the classes inheriting from VirtualMachine class, which are responsible for "executing" the RVMC (nomenclature based on analogy to executing assembly code). Depending on the VM chosen, there are different configuration options available and different type of image will be obtained. Since at the begging we assumed we want to walk through the process of rendering PNG image, we would have to choose PillowVirtualMachine, which is capable of rendering raster images with Pillow library and exporting them in different raster formats.

flowchart TD
  src@{ shape: st-rect, label: "Gerber source" }
  parser@{ shape: proc, label: "Parser" }
  ast@{ shape: st-rect, label: "Abstract Syntax Tree" }
  compiler@{ shape: proc, label: "Compiler" }
  rvmc@{ shape: st-rect, label: "RVMC" }
  vm@{ shape: proc, label: "Virtual Machine" }
  image@{ shape: st-rect, label: "Image" }

src --> parser

subgraph Parsing
    parser --> ast
end

subgraph Translation
    ast --> compiler
    compiler --> rvmc
end

subgraph Rendering
    rvmc --> vm
    vm --> image
end

Additional processing¶

Although rendering is probably the most useful feature of PyGerber, it is not the only one. PyGerber is capable of performing analysis, formatting and modification of existing Gerber files. This is done by different classes, which are not part of the rendering pipeline. All those tools require AST as input, so you have to first parse Gerber file before you can use them. For example here is processing flow for formatting:

flowchart TD
  src@{ shape: st-rect, label: "Gerber source" }
  parser@{ shape: proc, label: "Parser" }
  ast@{ shape: st-rect, label: "Abstract Syntax Tree" }
  formatter@{ shape: proc, label: "Formatter" }
  formatted@{ shape: st-rect, label: "Formatted Gerber source" }

src --> parser

subgraph Parsing
    parser --> ast
end

subgraph Formatting
    ast --> formatter
end

formatter --> formatted