Mypy daemon (mypy server)¶
Instead of running mypy as a command-line tool, you can also run it as a long-running daemon (server) process and use a command-line client to send type-checking requests to the server. This way mypy can perform type checking much faster, since program state cached from previous runs is kept in memory and doesn’t have to be read from the file system on each run. The server also uses finer-grained dependency tracking to reduce the amount of work that needs to be done.
If you have a large codebase to check, running mypy using the mypy
daemon can be 10 or more times faster than the regular command-line
mypy tool, especially if your workflow involves running mypy
repeatedly after small edits – which is often a good idea, as this way
you’ll find errors sooner.
The mypy daemon is experimental. In particular, the command-line interface may change in future mypy releases.
The mypy daemon currently supports macOS and Linux only.
Each mypy daemon process supports one user and one set of source files, and it can only process one type checking request at a time. You can run multiple mypy daemon processes to type check multiple repositories.
The client utility
dmypy is used to control the mypy daemon.
dmypy run -- <flags> <files> to typecheck a set of files
(or directories). This will launch the daemon if it is not running.
You can use almost arbitrary mypy flags after
--. The daemon
will always run on the current host. Example:
dmypy run -- --follow-imports=error prog.py pkg1/ pkg2/
You’ll need to use either the
--follow-imports=error or the
--follow-imports=skip option with dmypy because the current
implementation can’t follow imports.
See Following imports or not? for details on how these work.
You can also define these using a
dmypy run will automatically restart the daemon if the
configuration or mypy version changes.
You need to provide all files or directories you want to type check
(other than stubs) as arguments. This is a result of the
--follow-imports restriction mentioned above.
The initial run will process all the code and may take a while to finish, but subsequent runs will be quick, especially if you’ve only changed a few files. You can use remote caching to speed up the initial run. The speedup can be significant if you have a large codebase.
dmypy run is sufficient for most uses, some workflows
(ones using remote caching, perhaps),
require more precise control over the lifetime of the daemon process:
dmypy stopstops the daemon.
dmypy start -- <flags>starts the daemon but does not check any files. You can use almost arbitrary mypy flags after
dmypy restart -- <flags>restarts the daemon. The flags are the same as with
dmypy start. This is equivalent to a stop command followed by a start.
dmypy run --timeout SECONDS -- <flags>(or
restart) to automatically shut down the daemon after inactivity. By default, the daemon runs until it’s explicitly stopped.
dmypy check <files>checks a set of files using an already running daemon.
dmypy statuschecks whether a daemon is running. It prints a diagnostic and exits with
0if there is a running daemon.
dmypy --help for help on additional commands and command-line
options not discussed here, and
dmypy <command> --help for help on