# python command

## Syntax

    python mode keyword args ...

-   mode = *source* or name of Python function

    if mode is *source*:

        keyword = *here* or name of a *Python file*
          *here* arg = inline
            inline = one or more lines of Python code which defines func
                     must be a single argument, typically enclosed between triple quotes
          *Python file* = name of a file with Python code which will be executed immediately

-   if *mode* is the name of a Python function, one or more keywords
    with/without arguments must be appended

        keyword = *invoke* or *input* or *return* or *format* or *length* or *file* or *here* or *exists*
          *invoke* arg = none = invoke the previously defined Python function
          *input* args = N i1 i2 ... iN
            N = # of inputs to function
            i1,...,iN = value, SELF, or LAMMPS variable name
              value = integer number, floating point number, or string
              SELF = reference to LAMMPS itself which can be accessed by Python function
              variable = v_name, where name = name of LAMMPS variable, e.g. v_abc
          *return* arg = varReturn
            varReturn = v_name  = LAMMPS variable name which the return value of the Python function will be assigned to
          *format* arg = fstring with M characters
            M = N if no return value, where N = # of inputs
            M = N+1 if there is a return value
            fstring = each character (i,f,s,p) corresponds in order to an input or return value
            'i' = integer, 'f' = floating point, 's' = string, 'p' = SELF
          *length* arg = Nlen
            Nlen = max length of string returned from Python function
          *file* arg = filename
            filename = file of Python code, which defines func
          *here* arg = inline
            inline = one or more lines of Python code which defines func
                     must be a single argument, typically enclosed between triple quotes
          *exists* arg = none = Python code has been loaded by previous python command

## Examples

``` LAMMPS
python pForce input 2 v_x 20.0 return v_f format fff file force.py
python pForce invoke

python factorial input 1 myN return v_fac format ii here """
def factorial(n):
  if n == 1: return n
  return n * factorial(n-1)
 """

python loop input 1 SELF return v_value format pf here """
def loop(lmpptr,N,cut0):
  from lammps import lammps
  lmp = lammps(ptr=lmpptr)

  # loop N times, increasing cutoff each time

  for i in range(N):
    cut = cut0 + i*0.1
    lmp.set_variable("cut",cut)               # set a variable in LAMMPS
    lmp.command("pair_style lj/cut ${cut}")   # LAMMPS commands
    lmp.command("pair_coeff * * 1.0 1.0")
    lmp.command("run 100")
"""

python source funcdef.py

python source here "from lammps import lammps"
```

## Description

The *python* command allows interfacing LAMMPS with an embedded Python
interpreter and enables either executing arbitrary python code in that
interpreter, registering a Python function for future execution (as a
python style variable, from a fix interfaced with python, or for direct
invocation), or invoking such a previously registered function.

Arguments, including LAMMPS variables, can be passed to the function
from the LAMMPS input script and a value returned by the Python function
assigned to a LAMMPS variable. The Python code for the function can be
included directly in the input script or in a separate Python file. The
function can be standard Python code or it can make \"callbacks\" to
LAMMPS through its library interface to query or set internal values
within LAMMPS. This is a powerful mechanism for performing complex
operations in a LAMMPS input script that are not possible with the
simple input script and variable syntax which LAMMPS defines. Thus your
input script can operate more like a true programming language.

Use of this command requires building LAMMPS with the PYTHON package
which links to the Python library so that the Python interpreter is
embedded in LAMMPS. More details about this process are given below.

There are two ways to invoke a Python function once it has been
registered. One is using the *invoke* keyword. The other is to assign
the function to a [python-style variable](variable) defined in your
input script. Whenever the variable is evaluated, it will execute the
Python function to assign a value to the variable. Note that variables
can be evaluated in many different ways within LAMMPS. They can be
substituted with their result directly in an input script, or they can
be passed to various commands as arguments, so that the variable is
evaluated during a simulation run.

A broader overview of how Python can be used with LAMMPS is given in the
[Use Python with LAMMPS](Python_head) section of the documentation.
There also is an `examples/python` directory which illustrates use of
the python command.

------------------------------------------------------------------------

The first argument of the *python* command is either the *source*
keyword or the name of a Python function. This defines the mode of the
python command.

::: versionchanged
22Dec2022
:::

If the *source* keyword is used, it is followed by either a file name or
the *here* keyword. No other keywords can be used. The *here* keyword is
followed by a string with python commands, either on a single line
enclosed in quotes, or as multiple lines enclosed in triple quotes.
These Python commands will be passed to the python interpreter and
executed immediately without registering a Python function for future
execution. The code will be loaded into and run in the \"main\" module
of the Python interpreter. This allows running arbitrary Python code at
any time while processing the LAMMPS input file. This can be used to
pre-load Python modules, initialize global variables, define functions
or classes, or perform operations using the python programming language.
The Python code will be executed in parallel on all MPI processes. No
arguments can be passed.

In all other cases, the first argument is the name of a Python function
that will be registered with LAMMPS for future execution. The function
may already be defined (see *exists* keyword) or must be defined using
the *file* or *here* keywords as explained below.

If the *invoke* keyword is used, no other keywords can be used, and a
previous *python* command must have registered the Python function
referenced by this command. This invokes the Python function with the
previously defined arguments and the return value is processed as
explained below. You can invoke the function as many times as you wish
in your input script.

The *input* keyword defines how many arguments *N* the Python function
expects. If it takes no arguments, then the *input* keyword should not
be used. Each argument can be specified directly as a value, e.g. \'6\'
or \'3.14159\' or \'abc\' (a string of characters). The type of each
argument is specified by the *format* keyword as explained below, so
that Python will know how to interpret the value. If the word SELF is
used for an argument it has a special meaning. A pointer is passed to
the Python function which it can convert into a reference to LAMMPS
itself using the [LAMMPS Python module](Python_module). This enables the
function to call back to LAMMPS through its library interface as
explained below. This allows the Python function to query or set values
internal to LAMMPS which can affect the subsequent execution of the
input script. A LAMMPS variable can also be used as an argument,
specified as v_name, where \"name\" is the name of the variable. Any
style of LAMMPS variable returning a scalar or a string can be used, as
defined by the [variable](variable) command. The *format* keyword must
be used to set the type of data that is passed to Python. Each time the
Python function is invoked, the LAMMPS variable is evaluated and its
value is passed to the Python function.

The *return* keyword is only needed if the Python function returns a
value. The specified *varReturn* must be of the form v_name, where
\"name\" is the name of a python-style LAMMPS variable, defined by the
[variable](variable) command. The Python function can return a numeric
or string value, as specified by the *format* keyword.

As explained on the [variable](variable) doc page, the definition of a
python-style variable associates a Python function name with the
variable. This must match the *Python function name* first argument of
the *python* command. For example these two commands would be
consistent:

``` LAMMPS
variable foo python myMultiply
python myMultiply return v_foo format f file funcs.py
```

The two commands can appear in either order in the input script so long
as both are specified before the Python function is invoked for the
first time. Afterwards, the variable \'foo\' is associated with the
Python function \'myMultiply\'.

The *format* keyword must be used if the *input* or *return* keywords
are used. It defines an *fstring* with M characters, where M = sum of
number of inputs and outputs. The order of characters corresponds to the
N inputs, followed by the return value (if it exists). Each character
must be one of the following: \"i\" for integer, \"f\" for floating
point, \"s\" for string, or \"p\" for SELF. Each character defines the
type of the corresponding input or output value of the Python function
and affects the type conversion that is performed internally as data is
passed back and forth between LAMMPS and Python. Note that it is
permissible to use a [python-style variable](variable) in a LAMMPS
command that allows for an equal-style variable as an argument, but only
if the output of the Python function is flagged as a numeric value
(\"i\" or \"f\") via the *format* keyword.

If the *return* keyword is used and the *format* keyword specifies the
output as a string, then the default maximum length of that string is 63
characters (64-1 for the string terminator). If you want to return a
longer string, the *length* keyword can be specified with its *Nlen*
value set to a larger number (the code allocates space for Nlen+1 to
include the string terminator). If the Python function generates a
string longer than the default 63 or the specified *Nlen*, it will be
truncated.

------------------------------------------------------------------------

Either the *file*, *here*, or *exists* keyword must be used, but only
one of them. These keywords specify what Python code to load into the
Python interpreter. The *file* keyword gives the name of a file
containing Python code, which should end with a \".py\" suffix. The code
will be immediately loaded into and run in the \"main\" module of the
Python interpreter. The Python code will be executed in parallel on all
MPI processes. Note that Python code which contains a function
definition does not \"execute\" the function when it is run; it simply
defines the function so that it can be invoked later.

The *here* keyword does the same thing, except that the Python code
follows as a single argument to the *here* keyword. This can be done
using triple quotes as delimiters, as in the examples above. This allows
Python code to be listed verbatim in your input script, with proper
indentation, blank lines, and comments, as desired. See the [Commands
parse](Commands_parse) doc page, for an explanation of how triple quotes
can be used as part of input script syntax.

The *exists* keyword takes no argument. It means that Python code
containing the required Python function with the given name has already
been executed, for example by a *python source* command or in the same
file that was used previously with the *file* keyword.

Note that the Python code that is loaded and run must contain a function
with the specified function name. To operate properly when later
invoked, the function code must match the *input* and *return* and
*format* keywords specified by the python command. Otherwise Python will
generate an error.

------------------------------------------------------------------------

This section describes how Python code can be written to work with
LAMMPS.

Whether you load Python code from a file or directly from your input
script, via the *file* and *here* keywords, the code can be identical.
It must be indented properly as Python requires. It can contain comments
or blank lines. If the code is in your input script, it cannot however
contain triple-quoted Python strings, since that will conflict with the
triple-quote parsing that the LAMMPS input script performs.

All the Python code you specify via one or more python commands is
loaded into the Python \"main\" module, i.e. `__name__ == '__main__'`.
The code can define global variables, define global functions, define
classes or execute statements that are outside of function definitions.
It can contain multiple functions, only one of which matches the *func*
setting in the python command. This means you can use the *file* keyword
once to load several functions, and the *exists* keyword thereafter in
subsequent python commands to register the other functions that were
previously loaded with LAMMPS.

A Python function you define (or more generally, the code you load) can
import other Python modules or classes, it can make calls to other
system functions or functions you define, and it can access or modify
global variables (in the \"main\" module) which will persist between
successive function calls. The latter can be useful, for example, to
prevent a function from being invoke multiple times per timestep by
different commands in a LAMMPS input script that access the returned
python-style variable associated with the function. For example,
consider this function loaded with two global variables defined outside
the function:

``` python
nsteplast = -1
nvaluelast = 0

def expensive(nstep):
  global nsteplast,nvaluelast
  if nstep == nsteplast: return nvaluelast
  nsteplast = nstep
  # perform complicated calculation
  nvalue = ...
  nvaluelast = nvalue
  return nvalue
```

The variable \'nsteplast\' stores the previous timestep the function was
invoked (passed as an argument to the function). The variable
\'nvaluelast\' stores the return value computed on the last function
invocation. If the function is invoked again on the same timestep, the
previous value is simply returned, without re-computing it. The
\"global\" statement inside the Python function allows it to overwrite
the global variables from within the local context of the function.

Note that if you load Python code multiple times (via multiple python
commands), you can overwrite previously loaded variables and functions
if you are not careful. E.g. if the code above were loaded twice, the
global variables would be re-initialized, which might not be what you
want. Likewise, if a function with the same name exists in two chunks of
Python code you load, the function loaded second will override the
function loaded first.

It\'s important to realize that if you are running LAMMPS in parallel,
each MPI task will load the Python interpreter and execute a local copy
of the Python function(s) you define. There is no connection between the
Python interpreters running on different processors. This implies three
important things.

First, if you put a print or other statement creating output to the
screen in your Python function, you will see P copies of the output,
when running on P processors. If the prints occur at (nearly) the same
time, the P copies of the output may be mixed together. When loading the
LAMMPS Python module into the embedded Python interpreter, it is
possible to pass the pointer to the current LAMMPS class instance and
via the Python interface to the LAMMPS library interface, it is possible
to determine the MPI rank of the current process and thus adapt the
Python code so that output will only appear on MPI rank 0. The following
LAMMPS input demonstrates how this could be done. The text \'Hello,
LAMMPS!\' should be printed only once, even when running LAMMPS in
parallel.

``` LAMMPS
python python_hello input 1 SELF format p here """
def python_hello(handle):
    from lammps import lammps
    lmp = lammps(ptr=handle)
    me = lmp.extract_setting('world_rank')
    if me == 0:
        print('Hello, LAMMPS!')
"""

python python_hello invoke
```

If your Python code loads Python modules that are not pre-loaded by the
Python library, then it will load the module from disk. This may be a
bottleneck if 1000s of processors try to load a module at the same time.
On some large supercomputers, loading of modules from disk by Python may
be disabled. In this case you would need to pre-build a Python library
that has the required modules pre-loaded and link LAMMPS with that
library.

Third, if your Python code calls back to LAMMPS (discussed in the next
section) and causes LAMMPS to perform an MPI operation requires global
communication (e.g. via MPI_Allreduce), such as computing the global
temperature of the system, then you must ensure all your Python
functions (running independently on different processors) call back to
LAMMPS. Otherwise the code may hang.

------------------------------------------------------------------------

Your Python function can \"call back\" to LAMMPS through its library
interface, if you use the SELF input to pass Python a pointer to LAMMPS.
The mechanism for doing this in your Python function is as follows:

``` python
def foo(handle,...):
  from lammps import lammps
  lmp = lammps(ptr=handle)
  lmp.command('print "Hello from inside Python"')
  ...
```

The function definition must include a variable (\'handle\' in this
case) which corresponds to SELF in the *python* command. The first line
of the function imports the [\"lammps\" Python module](Python_module).
The second line creates a Python object `lmp` which wraps the instance
of LAMMPS that called the function. The \'ptr=handle\' argument is what
makes that happen. The third line invokes the command() function in the
LAMMPS library interface. It takes a single string argument which is a
LAMMPS input script command for LAMMPS to execute, the same as if it
appeared in your input script. In this case, LAMMPS should output

    Hello from inside Python

to the screen and log file. Note that since the LAMMPS print command
itself takes a string in quotes as its argument, the Python string must
be delimited with a different style of quotes.

The [Python_head]{.title-ref} page describes the syntax for how Python
wraps the various functions included in the LAMMPS library interface.

A more interesting example is in the `examples/python/in.python` script
which loads and runs the following function from
`examples/python/funcs.py`:

``` python
def loop(N,cut0,thresh,lmpptr):
  print("LOOP ARGS", N, cut0, thresh, lmpptr)
  from lammps import lammps
  lmp = lammps(ptr=lmpptr)
  natoms = lmp.get_natoms()

  for i in range(N):
    cut = cut0 + i*0.1

    lmp.set_variable("cut",cut)                 # set a variable in LAMMPS
    lmp.command("pair_style lj/cut ${cut}")     # LAMMPS command
    #lmp.command("pair_style lj/cut %d" % cut)  # LAMMPS command option

    lmp.command("pair_coeff * * 1.0 1.0")       # ditto
    lmp.command("run 10")                       # ditto
    pe = lmp.extract_compute("thermo_pe",0,0)   # extract total PE from LAMMPS
    print("PE", pe/natoms, thresh)
    if pe/natoms < thresh: return
```

with these input script commands:

``` LAMMPS
python          loop input 4 10 1.0 -4.0 SELF format iffp file funcs.py
python          loop invoke
```

This has the effect of looping over a series of 10 short runs (10
timesteps each) where the pair style cutoff is increased from a value of
1.0 in distance units, in increments of 0.1. The looping stops when the
per-atom potential energy falls below a threshold of -4.0 in energy
units. More generally, Python can be used to implement a loop with
complex logic, much more so than can be created using the LAMMPS
[jump](jump) and [if](if) commands.

Several LAMMPS library functions are called from the loop function.
Get_natoms() returns the number of atoms in the simulation, so that it
can be used to normalize the potential energy that is returned by
extract_compute() for the \"thermo_pe\" compute that is defined by
default for LAMMPS thermodynamic output. Set_variable() sets the value
of a string variable defined in LAMMPS. This library function is a
useful way for a Python function to return multiple values to LAMMPS,
more than the single value that can be passed back via a return
statement. This cutoff value in the \"cut\" variable is then substituted
(by LAMMPS) in the pair_style command that is executed next.
Alternatively, the \"LAMMPS command option\" line could be used in place
of the 2 preceding lines, to have Python insert the value into the
LAMMPS command string.

:::: note
::: title
Note
:::

When using the callback mechanism just described, recognize that there
are some operations you should not attempt because LAMMPS cannot execute
them correctly. If the Python function is invoked between runs in the
LAMMPS input script, then it should be OK to invoke any LAMMPS input
script command via the library interface command() or file() functions,
so long as the command would work if it were executed in the LAMMPS
input script directly at the same point.
::::

However, a Python function can also be invoked during a run, whenever an
associated LAMMPS variable it is assigned to is evaluated. If the
variable is an input argument to another LAMMPS command (e.g. [fix
setforce](fix_setforce)), then the Python function will be invoked
inside the class for that command, in one of its methods that is invoked
in the middle of a timestep. You cannot execute arbitrary input script
commands from the Python function (again, via the command() or file()
functions) at that point in the run and expect it to work. Other library
functions such as those that invoke computes or other variables may have
hidden side effects as well. In these cases, LAMMPS has no simple way to
check that something illogical is being attempted.

The same applies to Python functions called during a simulation run at
each time step using [fix python/invoke](fix_python_invoke).

------------------------------------------------------------------------

If you run Python code directly on your workstation, either
interactively or by using Python to launch a Python script stored in a
file, and your code has an error, you will typically see informative
error messages. That is not the case when you run Python code from
LAMMPS using an embedded Python interpreter. The code will typically
fail silently. LAMMPS will catch some errors but cannot tell you where
in the Python code the problem occurred. For example, if the Python code
cannot be loaded and run because it has syntax or other logic errors,
you may get an error from Python pointing to the offending line, or you
may get one of these generic errors from LAMMPS:

    Could not process Python file
    Could not process Python string

When the Python function is invoked, if it does not return properly, you
will typically get this generic error from LAMMPS:

    Python function evaluation failed

Here are three suggestions for debugging your Python code while running
it under LAMMPS.

First, don\'t run it under LAMMPS, at least to start with! Debug it
using plain Python. Load and invoke your function, pass it arguments,
check return values, etc.

Second, add Python print statements to the function to check how far it
gets and intermediate values it calculates. See the discussion above
about printing from Python when running in parallel.

Third, use Python exception handling. For example, say this statement in
your Python function is failing, because you have not initialized the
variable foo:

``` python
foo += 1
```

If you put one (or more) statements inside a \"try\" statement, like
this:

``` python
import exceptions
print("Inside simple function")
try:
  foo += 1      # one or more statements here
except Exception as e:
  print("FOO error:", e)
```

then you will get this message printed to the screen:

    FOO error: local variable 'foo' referenced before assignment

If there is no error in the try statements, then nothing is printed.
Either way the function continues on (unless you put a return or
sys.exit() in the except clause).

------------------------------------------------------------------------

## Restrictions

This command is part of the PYTHON package. It is only enabled if LAMMPS
was built with that package. See the [Build package](Build_package) page
for more info.

Building LAMMPS with the PYTHON package will link LAMMPS with the Python
library on your system. Settings to enable this are in the
lib/python/Makefile.lammps file. See the lib/python/README file for
information on those settings.

If you use Python code which calls back to LAMMPS, via the SELF input
argument explained above, there is an extra step required when building
LAMMPS. LAMMPS must also be built as a shared library and your Python
function must be able to load the [\"lammps\" Python
module](Python_module) that wraps the LAMMPS library interface. These
are the same steps required to use Python by itself to wrap LAMMPS.
Details on these steps are explained on the [Python](Python_head) doc
page. Note that it is important that the stand-alone LAMMPS executable
and the LAMMPS shared library be consistent (built from the same source
code files) in order for this to work. If the two have been built at
different times using different source files, problems may occur.

Another limitation of calling back to Python from the LAMMPS module
using the *python* command in a LAMMPS input is that both, the Python
interpreter and LAMMPS, must be linked to the same Python runtime as a
shared library. If the Python interpreter is linked to Python statically
(which seems to happen with Conda) then loading the shared LAMMPS
library will create a second python \"main\" module that hides the one
from the Python interpreter and all previous defined function and global
variables will become invisible.

## Related commands

[shell](shell), [variable](variable), [fix
python/invoke](fix_python_invoke)

## Default

none