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Startup
On startup, main creates a global Context object, then calls the
Context::initialize and Context::run methods.
Context is a large object that holds all task information, both in terms of
the task data, and intermediate run-time data. Having one global Context
object means we don't have 50 global variables. Context is therefore just a
big global bucket of data.
Context::initialize sets up all the data and processes the command line. The
initialization process is a big chicken-and-egg problem, because the command
line depends on configuration (aliases) and the command line can force a
reload of configuration (rc:foo). This is solved by look-ahead: the command
line is scanned for 'rc:xxx' and 'rc.data.location:xxx' arguments, then later
for overrides.
The Context::run method handles all the debug output and exceptions. Its
main purpose is to set up exception handling and call Context::dispatch.
Command Line Parsing
Command line parsing is difficult because of all the ambiguity. The solution
is to make multiple passes over the command line. For example, the command
determines whether subsequent arguments are interpreted as part of a filter or
set of modifications.
The CLI2 object is fed command line arguments, then through a succession of
calls builds and annotates a parse tree. To help with this, the Lexer is
used to break up strings into tokens.
Dispatch
Dispatch is simple: once the command line is parsed, the command is used to
look up a command object, then a call is made to the Command::execute method.
Context stores an associative map of command object pointers indexed by a
string. This means the 'done' string is an index to the CmdDone object that
implements the functionality.
Command Objects
Every task command is implemented by a command object. The command object
provides metadata, usage and one-line help in addition to the ::execute method
that implements the command. The Command base class implements common
functionality.
Column Objects
There is a 1:1 correspondence between attributes stored in the data files and
the columns that may be reported. These are represented by column objects,
which are responsible for validating input, measuring space needed according
to various formats, and for rendering data for reports. There is a
ColDescription object that inherits from a Column base class.
TDB2
The TDB2 object is a layered, transactioned I/O manager. Its purpose is to
isolate code from file I/O, locking and parsing details. It is also
responsible for minimizing reads, writes and parsing of data files.
All input is assumed to be UTF8. All stored data is UTF8.
GC
Garbage Collection is the process that moves tasks between the pending.data
and completed.data files. It is also responsible for waking tasks out of the
wait state.
Every command that displays task IDs will cause a GC to be run first, which
minimizes the number of changes necessary to the task IDs. This means that
when a report shows task IDs, those IDs will remain valid while subsequent
write commands are issued. The next report run may show different IDs.
Minimizing the size of pending.data is important for performance, because it
is the file that is accessed most.
Files
The data files used are all kept in the rc.data.location directory, which
defaults to ~/.task. The files are:
pending.data
completed.data
undo.data
backlog.data
The pending.data file aspires to contain only pending, waiting and recurring
tasks, but this is only correct after a GC, and before any tasks are modified.
This file tends to be relatively stable in size, reflecting the length of the
task list.
The completed.data file accumulates data over time, and grows unbounded.
The undo.data file accumulates changes over time, and grows unbounded. It
provides all the necessary metadata to support the 'undo' command.
The backlog.data file contains an accumulated set of changes that have not
been transmitted to Taskserver. It grows unbounded between 'sync' commands.
Filter
A filter is simply a set of command line arguments, but is only a subset of
the complete command line. These arguments are extracted from the parse tree
according to whether the command found is a read or write command.
There is a Filter::subset method for applying a filter to a set of tasks,
yielding a result set. It does this by creating an expression from the
parse tree using the Eval object, then evaluating the expression for each task,
such that the result set contains only tasks for which the expression evaluates
to Boolean true.
Eval & Variant
The Eval class evaluates expressions, provided in string form, using the
Variant class to represent data elements. Variant implements all operators
for all Variant types.
Sorting
Sorting is performed on a set of tasks. More specifically, the list that is
sorted is a set of numeric indexes to tasks that are stored in a separate
list. This minimizes the amount of data copying involved to just integers
rather than Task objects, but at the expense of one level of indirection.
Memory fragmentation is a bigger problem than the performance of vector
indexing.
The actual sorting is performed by std::stable_sort, but the compare function
is custom.
Render
There are two rendering objects, ViewTask and ViewText. These both have the
same tabular grid rendering capabilities. ViewText maintains a 2D vector of
strings to contain the data to be rendered, so it is used for things like the
help command output. ViewTask does not copy data, but assumes all data is
stored externally in a vector of Tasks, which minimizes data copying.
ViewTask contains projection data in the form of a set of Column objects that
represent the X axis. The Y axis is represented by a vector of tasks.
The rendering process is complex. It involves dynamically setting column
widths based on (1) available terminal width, (2) the columns to be included
in the output, (3) ability to wrap text for certain columns and (4) the size
of the data to be rendered, which involves added complexity when UTF8 is used.
The Column objects determine minimum width for a column and the maximum width
which then allows ViewT* to make choices.
Test Suite
A strong and diverse test suite is critical to the successful release of any
software. With the complex command set and its myriad permutations, a test
suite is the only way to ensure quality levels, and guarantee that big changes
are robust.
It is intended that the test suite continues growing, mostly feature tests.
The test are mostly written in Python. Some tests are written in C++ and all
tests generate TAP output.
There are currently about 8,000 unit tests, that take only a few seconds to
run on a multi-core machine.
Taskwarrior uses flod software to automate continuous integration across many
platforms. Code changes are automatically detected, propagated, built and
tested on a variety of participating platforms. Grid testing results are here:
http://central.tasktools.org/
When making code changes, it is important that the test suite be run to verify
that functionality was not broken.
Debugging
The 'rc.debug=on' override provides the following additional information which
is useful during debugging:
- Timing of various components (used to generate the data for the charts at
http://tasktools.org/performance).
- Data load times.
- Terminal size, color capabilities.
- Command line parse tree.
- TDB2 layer and I/O information.
Additionally, there are other settings (see 'man taskrc' for full details) that
may also be helpful: 'rc.hooks=on|off', 'rc.debug.parser=0|1|2|3',
'rc.debug.hooks=0|1|2', 'rc.debug.tls=0|1|2|3...'.
Patches
Patches are encouraged and welcomed. Either attach them to the appropriate
Jira issue, or send them to support@taskwarrior.org. A good patch:
- Maintains the MIT license, and does not contain code lifted from other
sources. You will have written 100% of the code in the patch, otherwise
we cannot maintain the license.
- Precisely addresses one issue only.
- Doesn't break unit tests.
- Doesn't introduce dependencies.
- Is accompanied by unit tests, where appropriate, written in Python.
- Is accompanied by documentation changes, where appropriate.
- Conforms to the prevailing coding standards - in other words, it should
fit right in with the existing code.
A patch may be rejected for violating any of the above rules, and more.
Bad patches may be accepted and modified depending on work load and mood. It
is possible that a patch may be rejected because it conflicts in some way with
plans or upcoming changes. Check with us first, before sinking time and effort
into a patch.
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