klipper-dgus/docs/Code_Overview.md

This document describes the overall code layout and major code flow of
Klipper.

Directory Layout
================

The **src/** directory contains the C source for the micro-controller
code. The **src/avr/** directory contains specific code for Atmel
ATmega micro-controllers. The **src/sam3x8e/** directory contains code
specific to the Arduino Due style ARM micro-controllers. The
**src/pru/** directory contains code specific to the Beaglebone's
on-board PRU micro-controller. The **src/simulator/** contains code
stubs that allow the micro-controller to be test compiled on other
architectures. The **src/generic/** directory contains helper code
that may be useful across different host architectures. The build
arranges for includes of "board/somefile.h" to first look in the
current architecture directory (eg, src/avr/somefile.h) and then in
the generic directory (eg, src/generic/somefile.h).

The **klippy/** directory contains the host software. Most of the host
software is written in Python, however the **klippy/chelper/**
directory contains some C code helpers. The **klippy/extras/**
directory contains the host code extensible "modules".

The **lib/** directory contains external 3rd-party library code that
is necessary to build some targets.

The **config/** directory contains example printer configuration
files.

The **scripts/** directory contains build-time scripts useful for
compiling the micro-controller code.

The **test/** directory contains automated test cases.

During compilation, the build may create an **out/** directory. This
contains temporary build time objects. The final micro-controller
object that is built is **out/klipper.elf.hex** on AVR and
**out/klipper.bin** on ARM.

Micro-controller code flow
==========================

Execution of the micro-controller code starts in architecture specific
code (eg, **src/avr/main.c**) which ultimately calls sched_main()
located in **src/sched.c**. The sched_main() code starts by running
all functions that have been tagged with the DECL_INIT() macro. It
then goes on to repeatedly run all functions tagged with the
DECL_TASK() macro.

One of the main task functions is command_dispatch() located in
**src/command.c**. This function is called from the board specific
input/output code (eg, **src/avr/serial.c**) and it runs the command
functions associated with the commands found in the input
stream. Command functions are declared using the DECL_COMMAND() macro
(see the [protocol](Protocol.md) document for more information).

Task, init, and command functions always run with interrupts enabled
(however, they can temporarily disable interrupts if needed). These
functions should never pause, delay, or do any work that lasts more
than a few micro-seconds. These functions schedule work at specific
times by scheduling timers.

Timer functions are scheduled by calling sched_add_timer() (located in
**src/sched.c**). The scheduler code will arrange for the given
function to be called at the requested clock time. Timer interrupts
are initially handled in an architecture specific interrupt handler
(eg, **src/avr/timer.c**) which calls sched_timer_dispatch() located
in **src/sched.c**. The timer interrupt leads to execution of schedule
timer functions. Timer functions always run with interrupts
disabled. The timer functions should always complete within a few
micro-seconds. At completion of the timer event, the function may
choose to reschedule itself.

In the event an error is detected the code can invoke shutdown() (a
macro which calls sched_shutdown() located in **src/sched.c**).
Invoking shutdown() causes all functions tagged with the
DECL_SHUTDOWN() macro to be run. Shutdown functions always run with
interrupts disabled.

Much of the functionality of the micro-controller involves working
with General-Purpose Input/Output pins (GPIO). In order to abstract
the low-level architecture specific code from the high-level task
code, all GPIO events are implemented in architecture specific
wrappers (eg, **src/avr/gpio.c**). The code is compiled with gcc's
"-flto -fwhole-program" optimization which does an excellent job of
inlining functions across compilation units, so most of these tiny
gpio functions are inlined into their callers, and there is no
run-time cost to using them.

Klippy code overview
====================

The host code (Klippy) is intended to run on a low-cost computer (such
as a Raspberry Pi) paired with the micro-controller. The code is
primarily written in Python, however it does use CFFI to implement
some functionality in C code.

Initial execution starts in **klippy/klippy.py**. This reads the
command-line arguments, opens the printer config file, instantiates
the main printer objects, and starts the serial connection. The main
execution of G-code commands is in the process_commands() method in
**klippy/gcode.py**. This code translates the G-code commands into
printer object calls, which frequently translate the actions to
commands to be executed on the micro-controller (as declared via the
DECL_COMMAND macro in the micro-controller code).

There are four threads in the Klippy host code. The main thread
handles incoming gcode commands. A second thread (which resides
entirely in the **klippy/chelper/serialqueue.c** C code) handles
low-level IO with the serial port. The third thread is used to process
response messages from the micro-controller in the Python code (see
**klippy/serialhdl.py**). The fourth thread writes debug messages to
the log (see **klippy/queuelogger.py**) so that the other threads
never block on log writes.

Code flow of a move command
===========================

A typical printer movement starts when a "G1" command is sent to the
Klippy host and it completes when the corresponding step pulses are
produced on the micro-controller. This section outlines the code flow
of a typical move command. The [kinematics](Kinematics.md) document
provides further information on the mechanics of moves.

* Processing for a move command starts in gcode.py. The goal of
  gcode.py is to translate G-code into internal calls. Changes in
  origin (eg, G92), changes in relative vs absolute positions (eg,
  G90), and unit changes (eg, F6000=100mm/s) are handled here. The
  code path for a move is: `process_data() -> process_commands() ->
  cmd_G1()`. Ultimately the ToolHead class is invoked to execute the
  actual request: `cmd_G1() -> ToolHead.move()`

* The ToolHead class (in toolhead.py) handles "look-ahead" and tracks
  the timing of printing actions. The codepath for a move is:
  `ToolHead.move() -> MoveQueue.add_move() -> MoveQueue.flush() ->
  Move.set_junction() -> Move.move()`.
  * ToolHead.move() creates a Move() object with the parameters of the
  move (in cartesian space and in units of seconds and millimeters).
  * MoveQueue.add_move() places the move object on the "look-ahead"
  queue.
  * MoveQueue.flush() determines the start and end velocities of each
  move.
  * Move.set_junction() implements the "trapezoid generator" on a
  move. The "trapezoid generator" breaks every move into three parts:
  a constant acceleration phase, followed by a constant velocity
  phase, followed by a constant deceleration phase. Every move
  contains these three phases in this order, but some phases may be of
  zero duration.
  * When Move.move() is called, everything about the move is known -
  its start location, its end location, its acceleration, its
  start/crusing/end velocity, and distance traveled during
  acceleration/cruising/deceleration. All the information is stored in
  the Move() class and is in cartesian space in units of millimeters
  and seconds.

  The move is then handed off to the kinematics classes: `Move.move()
  -> kin.move()`

* The goal of the kinematics classes is to translate the movement in
  cartesian space to movement on each stepper. The kinematics classes
  are in cartesian.py, corexy.py, delta.py, and extruder.py. The
  kinematic class is given a chance to audit the move
  (`ToolHead.move() -> kin.check_move()`) before it goes on the
  look-ahead queue, but once the move arrives in *kin*.move() the
  kinematic class is required to handle the move as specified. The
  kinematic classes translate the three parts of each move
  (acceleration, constant "cruising" velocity, and deceleration) to
  the associated movement on each stepper. Note that the extruder is
  handled in its own kinematic class. Since the Move() class specifies
  the exact movement time and since step pulses are sent to the
  micro-controller with specific timing, stepper movements produced by
  the extruder class will be in sync with head movement even though
  the code is kept separate.

* For efficiency reasons, the stepper pulse times are generated in C
  code. The code flow is: `kin.move() -> MCU_Stepper.step_const() ->
  stepcompress_push_const()`, or for delta kinematics:
  `DeltaKinematics.move() -> MCU_Stepper.step_delta() ->
  stepcompress_push_delta()`. The MCU_Stepper code just performs unit
  and axis transformation (millimeters to step distances), and calls
  the C code. The C code calculates the stepper step times for each
  movement and fills an array (struct stepcompress.queue) with the
  corresponding micro-controller clock counter times for every
  step. Here the "micro-controller clock counter" value directly
  corresponds to the micro-controller's hardware counter - it is
  relative to when the micro-controller was last powered up.

* The next major step is to compress the steps: `stepcompress_flush()
  -> compress_bisect_add()` (in klippy/chelper/stepcompress.c). This
  code generates and encodes a series of micro-controller "queue_step"
  commands that correspond to the list of stepper step times built in
  the previous stage. These "queue_step" commands are then queued,
  prioritized, and sent to the micro-controller (via
  stepcompress.c:steppersync and serialqueue.c:serialqueue).

* Processing of the queue_step commands on the micro-controller starts
  in src/command.c which parses the command and calls
  `command_queue_step()`. The command_queue_step() code (in
  src/stepper.c) just appends the parameters of each queue_step
  command to a per stepper queue. Under normal operation the
  queue_step command is parsed and queued at least 100ms before the
  time of its first step. Finally, the generation of stepper events is
  done in `stepper_event()`. It's called from the hardware timer
  interrupt at the scheduled time of the first step. The
  stepper_event() code generates a step pulse and then reschedules
  itself to run at the time of the next step pulse for the given
  queue_step parameters. The parameters for each queue_step command
  are "interval", "count", and "add". At a high-level, stepper_event()
  runs the following, 'count' times: `do_step(); next_wake_time =
  last_wake_time + interval; interval += add;`

The above may seem like a lot of complexity to execute a
movement. However, the only really interesting parts are in the
ToolHead and kinematic classes. It's this part of the code which
specifies the movements and their timings. The remaining parts of the
processing is mostly just communication and plumbing.

Adding a host module
====================

The Klippy host code has a dynamic module loading capability. If a
config section named "[my_module]" is found in the printer config file
then the software will automatically attempt to load the python module
klippy/extras/my_module.py . This module system is the preferred
method for adding new functionality to Klipper.

The easiest way to add a new module is to use an existing module as a
reference - see **klippy/extras/servo.py** as an example.

The following may also be useful:
* Execution of the module starts in the module level `load_config()`
  function (for config sections of the form [my_module]) or in
  `load_config_prefix()` (for config sections of the form
  [my_module my_name]). This function is passed a "config" object and
  it must return a new "printer object" associated with the given
  config section.
* During the process of instantiating a new printer object, the config
  object can be used to read parameters from the given config
  section. This is done using `config.get()`, `config.getfloat()`,
  `config.getint()`, etc. methods. Be sure to read all values from the
  config during the construction of the printer object - if the user
  specifies a config parameter that is not read during this phase then
  it will be assumed it is a typo in the config and an error will be
  raised.
* Use the `config.get_printer()` method to obtain a reference to the
  main "printer" class. This "printer" class stores references to all
  the "printer objects" that have been instantiated. Use the
  `printer.lookup_object()` method to find references to other printer
  objects. Almost all functionality (even core kinematic modules) are
  encapsulated in one of these printer objects. Note, though, that
  when a new module is instantiated, not all other printer objects
  will have been instantiated. The "gcode" and "pins" modules will
  always be available, but for other modules it is a good idea to
  defer the lookup.
* Define a `printer_state()` method if the code needs to be called
  during printer setup and/or shutdown. This method is called twice
  during setup (with "connect" and then "ready") and may also be
  called at run-time (with "shutdown" or "disconnect"). It is common
  to perform "printer object" lookup during the "connect" and "ready"
  phases.
* If there is an error in the user's config, be sure to raise it
  during the `load_config()` or `printer_state("connect")` phases. Use
  either `raise config.error("my error")` or `raise
  printer.config_error("my error")` to report the error.
* Use the "pins" module to configure a pin on a micro-controller. This
  is typically done with something similar to
  `printer.lookup_object("pins").setup_pin("pwm",
  config.get("my_pin"))`. The returned object can then be commanded at
  run-time.
* If the module needs access to system timing or external file
  descriptors then use `printer.get_reactor()` to obtain access to the
  global "event reactor" class. This reactor class allows one to
  schedule timers, wait for input on file descriptors, and to "sleep"
  the host code.
* Do not use global variables. All state should be stored in the
  printer object returned from the `load_config()` function. This is
  important as otherwise the RESTART command may not perform as
  expected. Also, for similar reasons, if any external files (or
  sockets) are opened then be sure to close them from the
  `printer_state("disconnect")` callback.
* Avoid accessing the internal member variables (or calling methods
  that start with an underscore) of other printer objects. Observing
  this convention makes it easier to manage future changes.
* If submitting the module for inclusion in the main Klipper code, be
  sure to place a copyright notice at the top of the module. See the
  existing modules for the preferred format.

Adding new kinematics
=====================

This section provides some tips on adding support to Klipper for
additional types of printer kinematics. This type of activity requires
excellent understanding of the math formulas for the target
kinematics. It also requires software development skills - though one
should only need to update the host software (which is written in
Python).

Useful steps:
1. Start by studying the
   "[code flow of a move](#code-flow-of-a-move-command)" section and
   the [Kinematics document](Kinematics.md).
2. Review the existing kinematic classes in cartesian.py, corexy.py,
   and delta.py. The kinematic classes are tasked with converting a
   move in cartesian coordinates to the movement on each stepper. One
   should be able to copy one of these files as a starting point.
3. Implement the `get_postion()` method in the new kinematics
   class. This method converts the current stepper position of each
   stepper axis (stored in millimeters) to a position in cartesian
   space (also in millimeters).
4. Implement the `set_postion()` method. This is the inverse of
   get_position() - it sets each axis position (in millimeters) given
   a position in cartesian coordinates.
5. Implement the `move()` method. The goal of the move() method is to
   convert a move defined in cartesian space to a series of stepper
   step times that implement the requested movement.
   * The `move()` method is passed a "print_time" parameter (which
     stores a time in seconds) and a "move" class instance that fully
     defines the movement. The goal is to repeatedly invoke the
     `stepper.step()` method with the time (relative to print_time)
     that each stepper should step at to obtain the desired motion.
   * One "trick" to help with the movement calculations is to imagine
     there is a physical rail between `move.start_pos` and
     `move.end_pos` that confines the print head so that it can only
     move along this straight line of motion. Then, if the head is
     confined to that imaginary rail, the head is at `move.start_pos`,
     only one stepper is enabled (all other steppers can move freely),
     and the given stepper is stepped a single step, then one can
     imagine that the head will move along the line of movement some
     distance. Determine the formula converting this step distance to
     distance along the line of movement. Once one has the distance
     along the line of movement, one can figure out the time that the
     head should be at that position (using the standard formulas for
     velocity and acceleration). This time is the ideal step time for
     the given stepper and it can be passed to the `stepper.step()`
     method.
   * The `stepper.step()` method must always be called with an
     increasing time for a given stepper (steps must be scheduled in
     the order they are to be executed). A common error during
     kinematic development is to receive an "Internal error in
     stepcompress" failure - this is generally due to the step()
     method being invoked with a time earlier than the last scheduled
     step. For example, if the last step in move1 is scheduled at a
     time greater than the first step in move2 it will generally
     result in the above error.
   * Fractional steps. Be aware that a move request is given in
     cartesian space and it is not confined to discreet
     locations. Thus a move's start and end locations may translate to
     a location on a stepper axis that is between two steps (a
     fractional step). The code must handle this. The preferred
     approach is to schedule the next step at the time a move would
     position the stepper axis at least half way towards the next
     possible step location. Incorrect handling of fractional steps is
     a common cause of "Internal error in stepcompress" failures.
6. Other methods. The `home()`, `check_move()`, and other methods
   should also be implemented. However, at the start of development
   one can use empty code here.
7. Implement test cases. Create a g-code file with a series of moves
   that can test important cases for the given kinematics. Follow the
   [debugging documentation](Debugging.md) to convert this g-code file
   to micro-controller commands. This is useful to exercise corner
   cases and to check for regressions.
8. Optimize if needed. One may notice that the existing kinematic
   classes do not call `stepper.step()`. This is purely an
   optimization - the inner loop of the kinematic calculations were
   moved to C to reduce load on the host cpu. All of the existing
   kinematic classes started development using `stepper.step()` and
   then were later optimized. The g-code to mcu command translation
   (described in the previous step) is a useful tool during
   optimization - if a code change is purely an optimization then it
   should not impact the resulting text representation of the mcu
   commands (though minor changes in output due to floating point
   rounding are possible). So, one can use this system to detect
   regressions.

Time
====

Fundamental to the operation of Klipper is the handling of clocks,
times, and timestamps. Klipper executes actions on the printer by
scheduling events to occur in the near future. For example, to turn on
a fan, the code might schedule a change to a GPIO pin in a 100ms. It
is rare for the code to attempt to take an instantaneous action. Thus,
the handling of time within Klipper is critical to correct operation.

There are three types of times tracked internally in the Klipper host
software:
* System time. The system time uses the system's monotonic clock - it
  is a floating point number stored as seconds and it is (generally)
  relative to when the host computer was last started. System times
  have limited use in the software - they are primarily used when
  interacting with the operating system. Within the host code, system
  times are frequently stored in variables named *eventtime* or
  *curtime*.
* Print time. The print time is synchronized to the main
  micro-controller clock (the micro-controller defined in the "[mcu]"
  config section). It is a floating point number stored as seconds and
  is relative to when the main mcu was last restarted. It is possible
  to convert from a "print time" to the main micro-controller's
  hardware clock by multiplying the print time by the mcu's statically
  configured frequency rate. The high-level host code uses print times
  to calculates almost all physical actions (eg, head movement, heater
  changes, etc.). Within the host code, print times are generally
  stored in variables named *print_time* or *move_time*.
* MCU clock. This is the hardware clock counter on each
  micro-controller. It is stored as an integer and its update rate is
  relative to the frequency of the given micro-controller. The host
  software translates its internal times to clocks before transmission
  to the mcu. The mcu code only ever tracks time in clock
  ticks. Within the host code, clock values are tracked as 64bit
  integers, while the mcu code uses 32bit integers. Within the host
  code, clocks are generally stored in variables with names containing
  *clock* or *ticks*.

Conversion between the different time formats is primarily implemented
in the **klippy/clocksync.py** code.

Some things to be aware of when reviewing the code:
* 32bit and 64bit clocks: To reduce bandwidth and to improve
  micro-controller efficiency, clocks on the micro-controller are
  tracked as 32bit integers. When comparing two clocks in the mcu
  code, the `timer_is_before()` function must always be used to ensure
  integer rollovers are handled properly. The host software converts
  32bit clocks to 64bit clocks by appending the high-order bits from
  the last mcu timestamp it has received - no message from the mcu is
  ever more than 2^31 clock ticks in the future or past so this
  conversion is never ambiguous. The host converts from 64bit clocks
  to 32bit clocks by simply truncating the high-order bits. To ensure
  there is no ambiguity in this conversion, the
  **klippy/chelper/serialqueue.c** code will buffer messages until
  they are within 2^31 clock ticks of their target time.
* Multiple micro-controllers: The host software supports using
  multiple micro-controllers on a single printer. In this case, the
  "MCU clock" of each micro-controller is tracked separately. The
  clocksync.py code handles clock drift between micro-controllers by
  modifying the way it converts from "print time" to "MCU clock". On
  secondary mcus, the mcu frequency that is used in this conversion is
  regularly updated to account for measured drift.