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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 will be executed immediately
               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 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 = logreturn (optional)
      invoke the previously-defined Python function
      if logreturn is specified, print the return value of the invoked function to the screen and logfile
    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 then be accessed by Python function
        variable = v_name, where name = name of a LAMMPS variable, e.g. v_abc
        internal variable = iv_name, where name = name of a LAMMPS internal-style variable, e.g. iv_xyz
    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 the Python function
    here arg = inline
      inline = one or more lines of Python code which defines the Python function
               must be a single argument, typically enclosed between triple quotes
    exists arg = none = Python code has been loaded by previous python command

Examples

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

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 interfaces LAMMPS with an embedded Python interpreter and enables executing arbitrary python code in that interpreter. This can be done immediately, by using mode = source. Or execution can be deferred, by registering a Python function for later execution, by using mode = name of a Python function.

Later execution can be triggered in one of two ways. One is to use the python command again with its invoke keyword. The other is to trigger the evaluation of a python-style, equal-style, vector-style, or atom-style variable. A python-style variable invokes its associated Python function; its return value becomes the value of the python-style variable. Equal-, vector-, and atom-style variables can use a Python function wrapper in their formulas which encodes the python-style variable name, and specifies arguments (which themselves can be numeric formulas) to pass to the Python function associated with the python-style variable.

As explained on the variable doc page, the definition of a python-style variable associates a Python function name with the variable. Its specification must match the mode argument of the python command for the Python function name. For example these two commands would be consistent:

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.

Note that python-style, equal-style, vector-style, and atom-style variables can be used in many different ways within LAMMPS. They can be evaluated directly in an input script, effectively replacing the variable with its value. Or they can be passed to various commands as arguments, so that the variable is evaluated multiple times during a simulation run. See the variable command doc page for more details on variable styles which enable Python function evaluation.

The Python code for a Python 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.

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

---

The first argument to the python command is the mode setting, which is either source or the name of a Python function.

Changed in version 22Dec2022.

If source is used, it is followed by either the here keyword or a file name containing Python code. The here keyword is followed by a single inline argument which is a string containing one or more python commands. The string can either be on the same line as the python command, enclosed in quotes, or it can be multiple lines enclosed in triple quotes.

In either case, the in-line code or the file contents are passed to the python interpreter and executed immediately. 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 the MPI processes being used to run LAMMPS. Note that no arguments can be passed to the executed Python code.

If the mode setting is the name of a Python function, then it will be registered with LAMMPS for future execution (or can already be defined, see the exists keyword). One or more keywords must follow the mode function name. One of the keywords must be invoke, file, here, or exists, which specifies what Python code to load into the Python interpreter. Note that only one of those 4 keywords is allowed since their operations are mutually exclusive.

---

If the invoke keyword is used, no other keywords can be used. A previous python command must have registered the Python function referenced by this command, which can then be invoked multiple times in an input script via the invoke keyword. Each invocation passes current values for arguments to the Python function. A return value of the Python function will be ignored unless the Python function is linked to a python style variable with the return keyword. This return value can be logged to the screen and logfile by adding the optional logreturn argument to the invoke keyword. In that case a message with the name of the python command and the return value is printed. Note that return values of python functions are otherwise only accessible when the function is invoked indirectly by evaluating its associated python style variable, as described below.

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 and below. 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 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 simply means that Python code containing the needed Python function has already been loaded into the LAMMPS Python interpreter, for example by previous python source command or in a file that was loaded previously with the file keyword. This allows use of a single file of Python code which contains multiple functions, any of which can be used in the same (or different) input scripts (see below).

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

---

The other keywords which can be used with the python command are input, return, format, and length.

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. 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 input argument, specified as v_name, where “name” is the name of the variable defined in the input script. Any style of LAMMPS variable returning a scalar or a string can be used, as defined by the variable command. The style of variable must be consistent with the format keyword specification for 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 as an argument to the Python function. Note that a python-style variable can be used as an argument, which means that the a Python function can use arguments which invoke other Python functions.

A LAMMPS internal-style variable can also be used as an input argument, specified as iv_name, where “name” is the name of the internal-style variable. The internal-style variable does not have to be defined in the input script (though it can be); if it is not defined, this command creates an internal-style variable with the specified name.

An internal-style variable must be used when an equal-style, vector-style, or atom-style variable triggers the invocation of the Python function defined by this command, by including a Python function wrapper with arguments in its formula. Each of the arguments must be specified as an internal-style variable via the input keyword.

In brief, the syntax for a Python function wrapper in a variable formula is py_varname(arg1,arg2,...argN), where “varname” is the name of a python-style variable associated with a Python function defined by this command. One or more arguments to the function wrapper can themselves be sub-formulas which the variable command will evaluate and pass as arguments to the Python function. This is done by assigning the numeric result for each argument to an internal-style variable; thus the input keyword must specify the arguments as internal-style variables and their format (see below) as “f” for floating point. This is because LAMMPS variable formulas are calculated with floating point arithmetic (any integer values are converted to floating point). Note that the Python function can also have additional inputs, also specified by the input keyword, which are NOT arguments in the Python function wrapper. See the example below for the mixedargs Python function.

See the variable command doc page for full details on formula syntax including for Python function wrappers. Examples using Python function wrappers are shown below. Note that as explained above with python-style variables, Python function wrappers can be nested; a sub-formula for an argument can contain its own Python function wrapper which invokes another Python function.

The return keyword is only needed if the Python function returns a value. The specified varReturn is of the form v_name, where “name” is the name of a python-style LAMMPS variable, defined by the variable command. The Python function can return a numeric or string value, as specified by the format keyword. This return value is only accessible when its associated python-style variable is evaluated. When the invoke keyword is used, the return value of the python function is ignored unless the optional logreturn argument is specified.

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 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. LAMMPS will then allocate Nlen+1 space 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.

---

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:

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.

Also 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.

It is possible to avoid this issue, by passing the pointer to the current LAMMPS class instance to the Python function via the {input} SELF argument described above. The Python function can then use the Python interface to the LAMMPS library interface, and determine the MPI rank of the current process. The Python code can then ensure output will only appear on MPI rank 0. The following LAMMPS input demonstrates how this could be done. The text ‘Hello, LAMPS!’ should be printed only once, even when running LAMMPS in parallel.

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

Second, 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.

---

As mentioned above, a Python function can “call back” to LAMMPS through its library interface, if the SELF input is used to pass Python a pointer to LAMMPS. The mechanism for doing this is as follows:

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. 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 Use Python with LAMMPS 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:

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)  # alternate form of LAMMPS command

    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:

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 and 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 “alternate form of LAMMPS command” line could be used in place of the 2 preceding lines, to have Python insert the value into the LAMMPS command string.

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.

---

As noted above, a Python function can be invoked during a run, whenever an associated python-style variable it is assigned to is evaluated.

If the variable is an input argument to another LAMMPS command (e.g. fix setforce), then the Python function will be invoked inside the class for that command, possibly 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 constraints apply to Python functions called during a simulation run at each time step using the fix python/invoke command.

---

As noted above, a Python function can also be invoked within the formula for an equal-style, vector-style, or atom-style variable. This means the Python function will be invoked whenever that variable is invoked. In the case of a vector-style variable, the Python function can be invoked once per element of the global vector. In the case of an atom-style variable, the Python function can be invoked once per atom.

Here are three simple examples using equal-, vector-, and atom-style variables to trigger execution of a Python function:

variable        foo python truncate
python          truncate return v_foo input 1 iv_arg format fi here """
def truncate(x):
  return int(x)
"""
variable        ptrunc equal py_foo(press)
print           "TRUNCATED pressure = ${ptrunc}"

The Python truncate function simply converts a floating-point value to an integer value. When the LAMMPS print command evaluates the equal-style ptrunc variable, the current thermodynamic pressure is passed to the Python function. The truncated value is output to the screen and logfile by the print command. Note that the input keyword for the python command, specifies an internal-style variable named “arg” as iv_arg which is required to invoke the Python function from a Python function wrapper.

The last 2 lines can be replaced by these to define a vector-style variable which invokes the same Python truncate function:

compute         ke all temp
variable        ke vector c_ke
variable        ketrunc vector py_foo(v_ke)
thermo_style    custom step temp epair v_ketrunc[*6]

The vector-style variable ketrunc invokes the Python truncate function on each of the 6 components of the global kinetic energy tensor calculated by the compute ke command. The 6 truncated values will be printed with thermo output to the screen and log file.

Or the last 2 lines of the equal-style variable example can be replaced by these to define atom-style variables which invoke the same Python truncate function:

variable        xtrunc atom py_foo(x)
variable        ytrunc atom py_foo(y)
variable        ztrunc atom py_foo(z)
dump            1 all custom 100 tmp.dump id x y z v_xtrunc v_ytrunc v_ztrunc

When the dump command invokes the 3 atom-style variables, their arguments x,y,z to the Python function wrapper are the current per-atom coordinates of each atom. The Python truncate function is thus invoked 3 times for each atom, and the truncated coordinate values for each atom are written to the dump file.

Note that when using a Python function wrapper in a variable, arguments can be passed to the Python function either from the variable formula or by input keyword to the python command. For example, consider these (made up) commands:

variable        foo python mixedargs
python          mixedargs return v_foo input 6 7.5 v_myValue iv_arg1 iv_argy iv_argz v_flag &
                format fffffsf here """
def mixedargs(a,b,x,y,z,flag):
  ...
  return result
"""
variable        flag string optionABC
variable        myValue equal "2.0*temp*c_pe"
compute         pe all pe
compute         peatom all pe/atom
variable        field atom py_foo(x+3.0,sqrt(y),(z-zlo)*c_peatom)

They define a Python mixedargs function with 6 arguments. Three of them are internal-style variables, which the variable formula calculates as numeric values for each atom and passes to the function. In this example, these arguments are themselves small formulas containing the x,y,z coordinates of each atom as well as a per-atom compute (c_peratom) and thermodynamic keyword (zlo).

The other three arguments (7.5,v_myValue,v_flag) are defined by the python command. The first and last are constant values (“7.5” and the optionABC string). The second argument (myValue) is the result of an equal-style variable formula which accesses the system temperature and potential energy.

The “result” returned by each invocation of the Python mixedargs function becomes the per-atom value in the atom-style “field” variable, which could be output to a dump file or used elsewhere in the input script.

---

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:

foo += 1

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

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 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 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 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, variable, fix python/invoke

Default

none