GC3Libs programming API¶

gc3libs¶

GC3Libs is a python package for controlling the life-cycle of a Grid or batch computational job.

GC3Libs provides services for submitting computational jobs to Grids and batch systems, controlling their execution, persisting job information, and retrieving the final output.

GC3Libs takes an application-oriented approach to batch computing. A generic Application class provides the basic operations for controlling remote computations, but different Application subclasses can expose adapted interfaces, focusing on the most relevant aspects of the application being represented.

class gc3libs.Application(arguments, inputs, outputs, output_dir, **extra_args)¶

Support for running a generic application with the GC3Libs. The following parameters are required to create an Application instance:

arguments

List or sequence of program arguments. The program to execute is the first one.; any object in the list will be converted to string via Python’s str().

inputs

Files that will be copied to the remote execution node before execution starts.

There are two possible ways of specifying the inputs parameter:

It can be a Python dictionary: keys are local file paths or URLs, values are remote file names.
It can be a Python list: each item in the list should be a pair (source, remote_file_name): the source can be a local file or a URL; remote_file_name is the path (relative to the execution directory) where source will be downloaded. If remote_file_name is an absolute path, an InvalidArgument error is raised.

A single string file_name is allowed instead of the pair and results in the local file file_name being copied to file_name on the remote host.

outputs

Files and directories that will be copied from the remote execution node back to the local computer (or a network-accessible server) after execution has completed. Directories are copied recursively.

There are three possible ways of specifying the outputs parameter:

It can be a Python dictionary: keys are remote file or directory paths (relative to the execution directory), values are corresponding local names.
It can be a Python list: each item in the list should be a pair (remote_file_name, destination): the destination can be a local file or a URL; remote_file_name is the path (relative to the execution directory) that will be uploaded to destination. If remote_file_name is an absolute path, an InvalidArgument error is raised.

A single string file_name is allowed instead of the pair and results in the remote file file_name being copied to file_name on the local host.
The constant gc3libs.ANY_OUTPUT which instructs GC3Libs to copy every file in the remote execution directory back to the local output path (as specified by the output_dir attribute).

Note that no errors will be raised if an output file is not present. Override the terminated() method to raise errors for reacting on this kind of failures.

output_dir

Path to the base directory where output files will be downloaded. Output file names are interpreted relative to this base directory.

requested_cores,`requested_memory`,`requested_walltime`

specify resource requirements for the application: * the number of independent execution units (CPU cores), * amount of memory (as a gc3libs.quantity.Memory object), * amount of wall-clock time to allocate for the computational job (as a gc3libs.quantity.Duration object).

The following optional parameters may be additionally specified as keyword arguments and will be given special treatment by the Application class logic:

requested_architecture: specify that this application can only be executed on a certain processor architecture; see Run.Arch for a list of possible values. The default value None means that any architecture is valid, i.e., there are no requirements on the processor architecture.
environment: a list of pairs (name, value): the environment variable whose name is given by the contents of the string name will be defined as the content of string value (i.e., as if “export name=value” was executed prior to starting the application). Alternately, one can pass in a list of strings of the form “name=value”.
output_base_url: if not None, this is prefixed to all output files (except stdout and stderr, which are always retrieved), so, for instance, having output_base_url=”gsiftp://example.org/data” will upload output files into that remote directory.
stdin: file name of a file whose contents will be fed as standard input stream to the remote-executing process.
stdout: name of a file where the standard output stream of the remote executing process will be redirected to; will be automatically added to outputs.
stderr: name of a file where the standard error stream of the remote executing process will be redirected to; will be automatically added to outputs.
join: if this evaluates to True, then standard error is redirected to the file specified by stdout and stderr is ignored. (join has no effect if stdout is not given.)
tags: list of tag names (string) that must be present on a resource in order to be eligible for submission; in the ARC backend, tags are interpreted as run-time environments (RTE) to request.

Any other keyword arguments will be set as instance attributes, but otherwise ignored by the Application constructor.

After successful construction, an Application object is guaranteed to have the following instance attributes:

arguments

list of strings specifying command-line arguments for executable invocation. The first element must be the executable.

inputs

dictionary mapping source URL (a gc3libs.url.Url object) to a remote file name (a string); remote file names are relative paths (root directory is the remote job folder)

outputs

dictionary mapping remote file name (a string) to a destination (a gc3libs.url.Url); remote file names are relative paths (root directory is the remote job folder)

output_dir

Path to the base directory where output files will be downloaded. Output file names (those which are not URLs) are interpreted relative to this base directory.

execution

a Run instance; its state attribute is initially set to NEW (Actually inherited from the Task)

environment: dictionary mapping environment variable names to the requested value (string); possibly empty

stdin

None or a string specifying a (local) file name. If stdin is not None, then it matches a key name in inputs

stdout

None or a string specifying a (remote) file name. If stdout is not None, then it matches a key name in outputs

stderr

None or a string specifying a (remote) file name. If stdout is not None, then it matches a key name in outputs

join

boolean value, indicating whether stdout and stderr are collected into the same file

tags

list of strings specifying the tags to request in each resource for submission; possibly empty.

application_name = 'generic'¶

A name for applications of this class.

This string is used as a prefix for configuration items related to this application in configured resources. For example, if the application_name is foo, then the application interface code in GC3Pie might search for foo_cmd, foo_extra_args, etc. See qsub_sge() for an actual example.

bsub(resource, _suppress_warning=False, **extra_args)¶

Get an LSF qsub command-line invocation for submitting an instance of this application. Return a pair (cmd_argv, app_argv), where cmd_argv is a list containing the argv-vector of the command to run to submit an instance of this application to the LSF batch system, and app_argv is the argv-vector to use when invoking the application.

In the construction of the command-line invocation, one should assume that all the input files (as named in Application.inputs) have been copied to the current working directory, and that output files should be created in this same directory.

The default implementation just prefixes any output from the cmdline method with an LSF bsub invocation of the form bsub -cwd . -L /bin/sh + resource limits.

Override this method in application-specific classes to provide appropriate invocation templates and/or add resource-specific submission options.

cmdline(resource)¶

Return list of command-line arguments for invoking the application.

This is exactly the argv-vector of the application process: the application command name is included as first item (index 0) of the list, further items are command-line arguments.

Hence, to get a UNIX shell command-line, just concatenate the elements of the list, separating them with spaces.

compatible_resources(resources)¶: Return a list of compatible resources.

fetch_output(download_dir, overwrite, **extra_args)¶: Calls the corresponding method of the controller.

fetch_output_error(ex)¶

Invocation of Core.fetch_output() on this object failed; ex is the Exception that describes the error.

If this method returns an exception object, that is raised as a result of the Core.fetch_output(), otherwise the return value is ignored and Core.fetch_output returns None.

Default is to return ex unchanged; override in derived classes to change this behavior.

qsub_pbs(resource, _suppress_warning=False, **extra_args)¶: Similar to qsub_sge(), but for the PBS/TORQUE resource manager.

qsub_sge(resource, **extra_args)¶

Get an SGE qsub command-line invocation for submitting an instance of this application.

Return a pair (cmd_argv, app_argv). Both cmd_argv and app_argv are argv-lists: the command name is included as first item (index 0) of the list, further items are command-line arguments; cmd_argv is the argv-list for the submission command (excluding the actual application command part); app_argv is the argv-list for invoking the application. By overriding this method, one can add futher resource-specific options at the end of the cmd_argv argv-list.

In the construction of the command-line invocation, one should assume that all the input files (as named in Application.inputs) have been copied to the current working directory, and that output files should be created in this same directory.

The default implementation just prefixes any output from the cmdline method with an SGE qsub invocation of the form qsub -cwd -S /bin/sh + resource limits. Note that there is no generic way of requesting a certain number of cores in SGE: it all depends on the installed parallel environment, and these are totally under control of the local sysadmin; therefore, any request for cores is ignored and a warning is logged.

Override this method in application-specific classes to provide appropriate invocation templates and/or add different submission options.

rank_resources(resources)¶

Sort the given resources in order of preference.

By default, less-loaded resources come first; see _cmp_resources.

sbatch(resource, **extra_args)¶

Get a SLURM sbatch command-line invocation for submitting an instance of this application.

Return a pair (cmd_argv, app_argv). Both cmd_argv and app_argv are argv-lists: the command name is included as first item (index 0) of the list, further items are command-line arguments; cmd_argv is the argv-list for the submission command (excluding the actual application command part); app_argv is the argv-list for invoking the application. By overriding this method, one can add futher resource-specific options at the end of the cmd_argv argv-list.

In the construction of the command-line invocation, one should assume that all the input files (as named in Application.inputs) have been copied to the current working directory, and that output files should be created in this same directory.

Override this method in application-specific classes to provide appropriate invocation templates and/or add different submission options.

submit_error(exs)¶

Invocation of Core.submit() on this object failed; exs is a list of Exception objects, one for each attempted submission.

If this method returns an exception object, that is raised as a result of the Core.submit(), otherwise the return value is ignored and Core.submit returns None.

Default is to always return the first exception in the list (on the assumption that it is the root of all exceptions or that at least it refers to the preferred resource). Override in derived classes to change this behavior.

update_job_state_error(ex)¶

Handle exceptions that occurred during a Core.update_job_state call.

If this method returns an exception object, that exception is processed in Core.update_job_state() instead of the original one. Any other return value is ignored and Core.update_job_state proceeds as if no exception had happened.

Argument ex is the exception that was raised by the backend during job state update.

Default is to return ex unchanged; override in derived classes to change this behavior.

xrsl(resource)¶

Return a string containing an xRSL sequence, suitable for submitting an instance of this application through ARC’s ngsub command.

The default implementation produces XRSL content based on the construction parameters; you should override this method to produce XRSL tailored to your application.

Warning

WARNING: ARClib SWIG bindings cannot resolve the overloaded constructor if the xRSL string argument is a Python ‘unicode’ object; if you overload this method, force the result to be a ‘str’!

class gc3libs.Default¶

A namespace for all constants and default values used in the GC3Libs package.

ARC_CACHE_TIME = 30¶: only update ARC resources status every this seconds

ARC_LOST_JOB_TIMEOUT = 120¶: consider a submitted job lost if it does not show up in the information system after this duration

PROXY_VALIDITY_THRESHOLD = 600¶: Proxy validity threshold in seconds. If proxy is expiring before the thresold, it will be marked as to be renewed.

class gc3libs.Run(initializer=None, attach=None, **keywd)¶

A specialized dict-like object that keeps information about the execution state of an Application instance.

A Run object is guaranteed to have the following attributes:

log

A gc3libs.utils.History instance, recording human-readable text messages on events in this job’s history.

info

A simplified interface for reading/writing messages to Run.log. Reading from the info attribute returns the last message appended to log. Writing into info appends a message to log.

timestamp

Dictionary, recording the most recent timestamp when a certain state was reached. Timestamps are given as UNIX epochs.

For properties state, signal and returncode, see the respective documentation.

Run objects support attribute lookup by both the [...] and the . syntax; see gc3libs.utils.Struct for examples.

class Arch¶

Processor architectures, for use as values in the requested_architecture field of the Application class constructor.

The following values are currently defined:

X86_64: 64-bit Intel/AMD/VIA x86 processors in 64-bit mode.
X86_32: 32-bit Intel/AMD/VIA x86 processors in 32-bit mode.

Run.exitcode¶: The “exit code” part of a Run.returncode, see os.WEXITSTATUS. This is an 8-bit integer, whose meaning is entirely application-specific. (However, the value 255 is often used to mean that an error has occurred and the application could not end its execution normally.)

Run.in_state(*names)¶

Return True if the Run state matches any of the given names.

In addition to the states from Run.State, the two additional names ok and failed are also accepted, with the following meaning:

ok: state is TERMINATED and returncode is 0.
failed: state is TERMINATED and returncode is non-zero.

Run.info¶

A simplified interface for reading/writing entries into history.

Setting the info attribute appends a message to the log:

>>> j1 = Run()
>>> j1.info = 'a message'
>>> j1.info = 'a second message'

Getting the value of the info attribute returns the last message entered in the log:

>>> j1.info 
u'a second message ...'

Run.returncode¶

The returncode attribute of this job object encodes the Run termination status in a manner compatible with the POSIX termination status as implemented by os.WIFSIGNALED and os.WIFEXITED.

However, in contrast with POSIX usage, the exitcode and the signal part can both be significant: in case a Grid middleware error happened after the application has successfully completed its execution. In other words, os.WEXITSTATUS(returncode) is meaningful iff os.WTERMSIG(returncode) is 0 or one of the pseudo-signals listed in Run.Signals.

Run.exitcode and Run.signal are combined to form the return code 16-bit integer as follows (the convention appears to be obeyed on every known system):

Bit Encodes...

0..7 signal number

8 1 if program dumped core.

9..16 exit code

Note: the “core dump bit” is always 0 here.

Setting the returncode property sets exitcode and signal; you can either assign a (signal, exitcode) pair to returncode, or set returncode to an integer from which the correct exitcode and signal attribute values are extracted:

>>> j = Run()
>>> j.returncode = (42, 56)
>>> j.signal
42
>>> j.exitcode
56

>>> j.returncode = 137
>>> j.signal
9
>>> j.exitcode
0

gc3libs.cmdline¶

gc3libs.config¶

Deal with GC3Pie configuration files.

class gc3libs.config.Configuration(*locations, **extra_args)¶

In-memory representation of the GC3Pie configuration.

This class provides facilities for:

parsing configuration files (methods load() and merge_file());
validating the loaded values;
instanciating the internal GC3Pie objects resulting from the configuration (methods make_auth() and make_resource()).

The constructor takes a list of files to load (locations) and a list of key=value pairs to provide defaults for the configuration. Both lists are optional and can be omitted, resulting in a configuration containing only GC3Pie default values.

Example 1: initialization from config file:

>>> import os
>>> example_cfgfile = os.path.join(os.path.dirname(__file__), 'etc/gc3pie.conf.example')
>>> cfg = Configuration(example_cfgfile)
>>> cfg.debug
'0'

Example 2: initialization from key=value list:

>>> cfg = Configuration(auto_enable_auth=False, foo=1, bar='baz')
>>> cfg.auto_enable_auth
False
>>> cfg.foo
1
>>> cfg.bar
'baz'

When both a configuration file and a key=value list is present, values in the configuration files override those in the key=value list:

>>> cfg = Configuration(example_cfgfile, debug=1)
>>> cfg.debug
'0'

Example 3: default initialization:

>>> cfg = Configuration()
>>> cfg.auto_enable_auth
True

auth_factory¶

The instance of gc3libs.authentication.Auth used to manage auth access for the resources.

This is a read-only attribute, created upon first access with the values set in self.auths and self.auto_enabled.

load(*locations)¶

Merge settings from configuration files into this Configuration instance.

Environment variables and ~ references are expanded in the location file names.

If any of the specified files does not exist or cannot be read (for whatever reason), a message is logged but the error is ignored. However, a NoConfigurationFile exception is raised if none of the specified locations could be read.

Raises gc3libs.exceptions.NoConfigurationFile:
	if none of the specified files could be read.

make_auth(name)¶: Return factory for auth credentials configured in section [auth/name].

make_resources(ignore_errors=True)¶

Make backend objects corresponding to the configured resources.

Return a dictionary, mapping the resource name (string) into the corresponding backend object.

By default, errors in constructing backends (e.g., due to a bad configuration) are silently ignored: the offending configuration is just dropped. This can be changed by setting the optional argument ignore_errors to False: in this case, an exception is raised whenever we fail to construct a backend.

merge_file(filename)¶

Read configuration files and merge the settings into this Configuration object.

Contrary to load() (which see), the file name is taken literally and an error is raised if the file cannot be read for whatever reason.

Any parameter which is set in the configuration files [DEFAULT] section, and whose name does not start with underscore (_) defines an attribute in the current Configuration.

Warning

No type conversion is performed on values set this way - so they all end up being strings!

Raises gc3libs.exceptions.ConfigurationError:
	if the configuration file does not exist, cannot be read, is corrupt or has wrong format.

gc3libs.core¶

Top-level interface to Grid functionality.

class gc3libs.core.Core(cfg)¶

Core operations: submit, update state, retrieve (a snapshot of) output, cancel job.

Core operations are blocking, i.e., they return only after the operation has successfully completed, or an error has been detected.

Operations are always performed by a Core object. Core implements an overlay Grid on the resources specified in the configuration file.

add(task)¶: This method is here just to allow Core and Engine objects to be used interchangeably. It’s effectively a no-op, as it makes no sense in the synchronous/blocking semantics implemented by Core.

close()¶: Used to invoke explicitly the destructor on objects e.g. LRMS

fetch_output(app, download_dir=None, overwrite=False, **extra_args)¶

Retrieve output into local directory app.output_dir; optional argument download_dir overrides this.

The download directory is created if it does not exist. If it already exists, and the optional argument overwrite is False (default), it is renamed with a .NUMBER suffix and a new empty one is created in its place. Otherwise, if ‘overwrite` is True, files are downloaded over the ones already present.

If the task is in TERMINATING state, the state is changed to TERMINATED, attribute output_dir is set to the absolute path to the directory where files were downloaded, and the terminated transition method is called on the app object.

Task output cannot be retrieved when app.execution is in one of the states NEW or SUBMITTED; an OutputNotAvailableError exception is thrown in these cases.

Raise:	gc3libs.exceptions.OutputNotAvailableError if no output can be fetched from the remote job (e.g., the Application/Task object is in NEW or SUBMITTED state, indicating the remote job has not started running).

free(app, **extra_args)¶

Free up any remote resources used for the execution of app. In particular, this should delete any remote directories and files.

It is an error to call this method if app.execution.state is anything other than TERMINATED: an InvalidOperation exception will be raised in this case.

Raise:	gc3libs.exceptions.InvalidOperation if app.execution.state differs from Run.State.TERMINATED.

get_resources(**extra_args)¶: Return list of resources configured into this Core instance.

kill(app, **extra_args)¶

Terminate a job.

Terminating a job in RUNNING, SUBMITTED, or STOPPED state entails canceling the job with the remote execution system; terminating a job in the NEW or TERMINATED state is a no-op.

peek(app, what='stdout', offset=0, size=None, **extra_args)¶

Download size bytes (at offset bytes from the start) from the remote job standard output or error stream, and write them into a local file. Return file-like object from which the downloaded contents can be read.

If size is None (default), then snarf all available contents of the remote stream from offset unto the end.

The only allowed values for the what arguments are the strings ‘stdout’ and ‘stderr’, indicating that the relevant section of the job’s standard output resp. standard error should be downloaded.

remove(task)¶: This method is here just to allow Core and Engine objects to be used interchangeably. It’s effectively a no-op, as it makes no sense in the synchronous/blocking semantics implemented by Core.

select_resource(match)¶

Alter the configured list of resources, and retain only those that satisfy predicate match.

Argument match can be:

either a function (or a generic callable) that is passed each Resource object in turn, and should return a boolean indicating whether the resources should be kept (True) or not (False);

or it can be a string: only resources whose name matches (wildcards * and ? are allowed) are retained.

submit(app, resubmit=False, **extra_args)¶

Submit a job running an instance of the given app. Upon successful submission, call the submitted method on the app object.

At the beginning of the submission process, the app.execution state is reset to NEW; if submission is successfull, the task will be in SUBMITTED or RUNNING state when this call returns.

Raise:	gc3libs.exceptions.InputFileError if an input file does not exist or cannot otherwise be read.

update_job_state(*apps, **extra_args)¶

Update state of all applications passed in as arguments.

If keyword argument update_on_error is False (default), then application execution state is not changed in case a backend error happens; it is changed to UNKNOWN otherwise.

Note that if state of a job changes, the Run.state calls the appropriate handler method on the application/task object.

Raise:	gc3libs.exceptions.InvalidArgument in case one of the passed Application or Task objects is invalid. This can stop updating the state of other objects in the argument list.
Raise:	gc3libs.exceptions.ConfigurationError if the configuration of this Core object is invalid or otherwise inconsistent (e.g., a resource references a non-existing auth section).

update_resources(**extra_args)¶

Update the state of resources configured into this Core instance.

Each resource object in the returned list will have its updated attribute set to True if the update operation succeeded, or False if it failed.

class gc3libs.core.Engine(controller, tasks=[], store=None, can_submit=True, can_retrieve=True, max_in_flight=0, max_submitted=0, output_dir=None, fetch_output_overwrites=False)¶

Submit tasks in a collection, and update their state until a terminal state is reached. Specifically:

tasks in NEW state are submitted;

the state of tasks in SUBMITTED, RUNNING or STOPPED state is updated;

when a task reaches TERMINATED state, its output is downloaded.

The behavior of Engine instances can be further customized by setting the following instance attributes:

can_submit

Boolean value: if False, no task will be submitted.

can_retrieve

Boolean value: if False, no output will ever be retrieved.

max_in_flight

If >0, limit the number of tasks in SUBMITTED or RUNNING state: if the number of tasks in SUBMITTED, RUNNING or STOPPED state is greater than max_in_flight, then no new submissions will be attempted.

max_submitted

If >0, limit the number of tasks in SUBMITTED state: if the number of tasks in SUBMITTED, RUNNING or STOPPED state is greater than max_submitted, then no new submissions will be attempted.

output_dir

Base directory for job output; if not None, each task’s results will be downloaded in a subdirectory named after the task’s permanent_id.

fetch_output_overwrites

Default value to pass as the overwrite argument to Core.fetch_output() when retrieving results of a terminated task.

Any of the above can also be set by passing a keyword argument to the constructor (assume g is a Core instance):

| >>> e = Engine(g, can_submit=False)
| >>> e.can_submit
| False

add(task)¶: Add task to the list of tasks managed by this Engine. Adding a task that has already been added to this Engine instance results in a no-op.

close()¶: Call explicilty finalize methods on relevant objects e.g. LRMS

fetch_output(task, output_dir=None, overwrite=False, **extra_args)¶: Proxy for Core.fetch_output (which see).

free(task, **extra_args)¶: Proxy for Core.free, which see.

kill(task, **extra_args)¶: Schedule a task for killing on the next progress run.

peek(task, what='stdout', offset=0, size=None, **extra_args)¶: Proxy for Core.peek (which see).

progress()¶

Update state of all registered tasks and take appropriate action. Specifically:

tasks in NEW state are submitted;

the state of tasks in SUBMITTED, RUNNING, STOPPED or UNKNOWN state is updated;

when a task reaches TERMINATING state, its output is downloaded.

tasks in TERMINATED status are simply ignored.

The max_in_flight and max_submitted limits (if >0) are taken into account when attempting submission of tasks.

remove(task)¶: Remove a task from the list of tasks managed by this Engine.

stats(only=None)¶

Return a dictionary mapping each state name into the count of tasks in that state. In addition, the following keys are defined:

ok: count of TERMINATED tasks with return code 0
failed: count of TERMINATED tasks with nonzero return code
total: total count of managed tasks, whatever their state

If the optional argument only is not None, tasks whose whose class is not contained in only are ignored. : param tuple only: Restrict counting to tasks of these classes.

submit(task, resubmit=False, **extra_args)¶

Submit task at the next invocation of perform.

The task state is reset to NEW and then added to the collection of managed tasks.

update_job_state(*tasks, **extra_args)¶: Return list of current states of the given tasks. States will only be updated at the next invocation of progress; in particular, no state-change handlers are called as a result of calling this method.

gc3libs.exceptions¶

Exceptions specific to the gc3libs package.

In addition to the exceptions listed here, gc3libs functions try to use Python builtin exceptions with the same meaning they have in core Python, namely:

TypeError is raised when an argument to a function or method has an incompatible type or does not implement the required protocol (e.g., a number is given where a sequence is expected).
ValueError`is raised when an argument to a function or method has the correct type, but fails to satisfy other constraints in the function contract (e.g., a positive number is required, and `-1 is passed instead).
AssertionError is raised when some internal assumption regarding state or function/method calling contract is violated. Informally, this indicates a bug in the software.

exception gc3libs.exceptions.ApplicationDescriptionError(msg, do_log=True)¶: Raised when the dumped description on a given Application produces something that the LRMS backend cannot process. As an example, for arc backends, this error is raised when the parsing of the Application’s XRSL fails

exception gc3libs.exceptions.AuthError(msg, do_log=False)¶

Base class for Auth-related errors.

Should never be instanciated: create a specific error class describing the actual error condition.

exception gc3libs.exceptions.ConfigurationError(msg, do_log=True)¶: Raised when the configuration file (or parts of it) could not be read/parsed. Also used to signal that a required parameter is missing or has an unknown/invalid value.

exception gc3libs.exceptions.DataStagingError(msg, do_log=False)¶

Base class for data staging and movement errors.

Should never be instanciated: create a specific error class describing the actual error condition.

exception gc3libs.exceptions.DetachedFromGridError(msg, do_log=False)¶: Raised when a method (other than attach()) is called on a detached Task instance.

exception gc3libs.exceptions.DuplicateEntryError(msg, do_log=False)¶: Raised by Application.__init__ if not all (local or remote) entries in the input or output files are distinct.

exception gc3libs.exceptions.Error(msg, do_log=False)¶

Base class for all error-level exceptions in GC3Pie.

Generally, this indicates a non-fatal error: depending on the nature of the task, steps could be taken to continue, but users must be aware that an error condition occurred, so the message is sent to the logs at the ERROR level.

Exceptions indicating an error condition after which the program cannot continue and should immediately stop, should use the FatalError base class.

exception gc3libs.exceptions.FatalError(msg, do_log=True)¶

A fatal error: execution cannot continue and program should report to user and then stop.

The message is sent to the logs at CRITICAL level when the exception is first constructed.

This is the base class for all fatal exceptions.

exception gc3libs.exceptions.InputFileError(msg, do_log=True)¶: Raised when an input file is specified, which does not exist or cannot be read.

exception gc3libs.exceptions.InternalError(msg, do_log=False)¶: Raised when some function cannot fulfill its duties, for reasons that do not depend on the library client code. For instance, when a response string gotten from an external command cannot be parsed as expected.

exception gc3libs.exceptions.InvalidArgument(msg, do_log=False)¶: Raised when the arguments passed to a function do not honor some required contract. For instance, either one of two optional arguments must be provided, but none of them was.

exception gc3libs.exceptions.InvalidOperation(msg, do_log=False)¶: Raised when an operation is attempted, that is not considered valid according to the system state. For instance, trying to retrieve the output of a job that has not yet been submitted.

exception gc3libs.exceptions.InvalidResourceName(msg, do_log=False)¶: Raised to signal that no computational resource with the given name is defined in the configuration file.

exception gc3libs.exceptions.InvalidType(msg, do_log=False)¶: A specialization of`InvalidArgument` for cases when the type of the passed argument does not match expectations.

exception gc3libs.exceptions.InvalidUsage(msg, do_log=True)¶

Raised when a command is not provided all required arguments on the command line, or the arguments do not match the expected syntax.

Since the exception message is the last thing a user will see, try to be specific about what is wrong on the command line.

exception gc3libs.exceptions.InvalidValue(msg, do_log=False)¶: A specialization of`InvalidArgument` for cases when the type of the passed argument does not match expectations.

exception gc3libs.exceptions.LoadError(msg, do_log=False)¶: Raised upon errors loading a job from the persistent storage.

exception gc3libs.exceptions.NoConfigurationFile(msg, do_log=True)¶: Raised when the configuration file cannot be read (e.g., does not exist or has wrong permissions), or cannot be parsed (e.g., is malformed).

exception gc3libs.exceptions.NoResources(msg, do_log=False)¶: Raised to signal that no resources are defined, or that none are compatible with the request.

exception gc3libs.exceptions.OutputNotAvailableError(msg, do_log=False)¶: Raised upon attempts to retrieve the output for jobs that are still in NEW or SUBMITTED state.

exception gc3libs.exceptions.RecoverableDataStagingError(msg, do_log=False)¶

Raised when transient problems with copying data to or from the remote execution site occurred.

This error is considered to be transient (e.g., network connectivity interruption), so trying again at a later time could solve the problem.

exception gc3libs.exceptions.RecoverableError(msg, do_log=False)¶

Used to mark transient errors: retrying the same action at a later time could succeed.

This exception should never be instanciated: it is only to be used in except clauses to catch “try again” situations.

exception gc3libs.exceptions.TaskError(msg, do_log=False)¶: Generic error condition in a Task object.

exception gc3libs.exceptions.UnexpectedStateError(msg, do_log=False)¶: Raised by Task.progress() when a job lands in STOPPED or TERMINATED state.

exception gc3libs.exceptions.UnknownJob(msg, do_log=False)¶: Raised when an operation is attempted on a task, which is unknown to the remote server or backend.

exception gc3libs.exceptions.UnknownJobState(msg, do_log=False)¶: Raised when a job state is gotten from the Grid middleware, that is not handled by the GC3Libs code. Might actually mean that there is a version mismatch between GC3Libs and the Grid middleware used.

exception gc3libs.exceptions.UnrecoverableDataStagingError(msg, do_log=False)¶: Raised when problems with copying data to or from the remote execution site occurred.

exception gc3libs.exceptions.UnrecoverableError(msg, do_log=False)¶

Used to mark permanent errors: there’s no point in retrying the same action at a later time, because it will yield the same error again.

This exception should never be instanciated: it is only to be used in except clauses to exclude “try again” situations.

gc3libs.persistence¶

Facade to store and retrieve Job information from permanent storage.

A usage warning¶

This module saves Python objects using the pickle framework: thus, the Application subclass corresponding to a job must be already loaded (or at least import-able) in the Python interpreter for pickle to be able to ‘undump’ the object from its on-disk representation.

In other words, if you create a custom Application subclass in some client code, GC3Utils won’t be able to read job files created by this code, because the class definition is not available in GC3Utils.

The recommended simple workaround is for a stand-alone script to ‘import self’ and then use the fully qualified name to run the script. In other words, start your script with this boilerplate code:

if __name__ == '__main__':
    import myscriptname
    myscriptname.MyScript().run()

The rest of the script now runs as the myscript module, which does the trick!

Note

Of course, the myscript.py file must be in the search path of the Python interpreter, or GC3Utils will still complain!

gc3libs.quantity¶

Manipulation of quantities with units attached with automated conversion among compatible units.

For details and the discussion leading up to this, see: <http://code.google.com/p/gc3pie/issues/detail?id=47>

class gc3libs.quantity.Duration¶

Represent the duration of a time lapse.

Construction of a duration can be done by parsing a string specification; several formats are accepted:

A duration is an aggregate of days, hours, minutes and seconds:

>>> l3 = Duration('1day 4hours 9minutes 16seconds')
>>> l3.amount(Duration.s) # convert to seconds
101356

Any of the terms can be omitted (in which case it defaults to zero):

>>> l4 = Duration('1day 4hours 16seconds')
>>> l4 == l3 - Duration('9 minutes')
True

The unit names can be singular or plural, and any amount of space can be added between the time unit name and the associated amount:

>>> l5 = Duration('3 hour 42 minute')
>>> l6 = Duration('3 hours 42 minutes')
>>> l7 = Duration('3hours 42minutes')
>>> l5 == l6 == l7
True

Unit names can also be abbreviated using just the leading letter:

>>> l8 = Duration('3h 42m')
>>> l9 = Duration('3h42m')
>>> l8 == l9
True

The abbreviated formats HH:MM:SS and DD:HH:MM:SS are also accepted:

>>> # 1 hour + 1 minute + 1 second
>>> l1 = Duration('01:01:01')
>>> l1 == Duration('3661 s')
True

>>> # 1 day, 2 hours, 3 minutes, 4 seconds
>>> l2 = Duration('01:02:03:04')
>>> l2.amount(Duration.s)
93784

However, the formats HH:MM and MM:SS are rejected as ambiguous:

>>> # is this hours:minutes or minutes:seconds ?
>>> l0 = Duration('01:02')
Traceback (most recent call last):
  ...
ValueError: Duration '01:02' is ambiguous: use '1m 2s' for 1 minutes and 2 seconds, or '1h 2m' for 1 hours and 2 minutes.

Finally, you can specify a duration like any other quantity, as an integral amount of a given time unit:
```
>>> l1 = Duration('1 day')
>>> l2 = Duration('86400 s')
>>> l1 == l2
True
```

A new quantity can also be defined as a multiple of an existing one:

>>> an_hour = Duration('1 hour')
>>> a_day = 24 * an_hour
>>> a_day.amount(Duration.h)
24

The quantities Duration.hours, Duration.minutes and Duration.seconds (and their single-letter abbreviations h, m, s) are pre-defined with their obvious meaning.

Also module-level aliases hours, minutes and seconds (and the one-letter forms) are available:

>>> a_day1 = 24*hours
>>> a_day2 = 1440*minutes
>>> a_day3 = 86400*seconds

This allows for yet another way of constructing duration objects, i.e., by passing the amount and the unit separately to the constructor:

>>> a_day4 = Duration(24, hours)

Two durations are equal if they indicate the exact same amount in seconds:

>>> a_day1 == a_day2
True
>>> a_day1.amount(s)
86400
>>> a_day2.amount(s)
86400

>>> a_day == an_hour
False
>>> a_day.amount(minutes)
1440
>>> an_hour.amount(minutes)
60

Basic arithmetic is possible with durations:

>>> two_hours = an_hour + an_hour
>>> two_hours == 2*an_hour
True

>>> one_hour = two_hours - an_hour
>>> one_hour.amount(seconds)
3600

It is also possible to add duration quantities defined with different units; the result is naturally expressed in the smaller unit of the two:

>>> one_hour_and_half = an_hour + 30*minutes
>>> one_hour_and_half
Duration(90, unit=m)

Note that the two unit class and numeric amount are accessible through the unit and amount() attributes:

>>> one_hour_and_half.unit
Duration(1, unit=m)
>>> one_hour_and_half.amount()
90

The amount() method accepts an optional specification of an alternate unit to express the amount into:

>>> one_hour_and_half.amount(Duration.hours)
1

An optional conv argument is available to specify a numerical domain for conversion, in case the default integer arithmetic is not precise enough:

>>> one_hour_and_half.amount(Duration.hours, conv=float)
1.5

The to_str() method allows representing a duration as a string, and provides choice of the output format and unit. The format string should contain exactly two %-specifiers: the first one is used to format the numerical amount, and the second one to format the measurement unit name.

By default, the unit used originally for defining the quantity is used:

>>> an_hour.to_str('%d [%s]')
'1 [hour]'

This can be overridden by specifying an optional second argument unit:

>>> an_hour.to_str('%d [%s]', unit=Duration.m)
'60 [m]'

A third optional argument conv can set the numerical type to be used for conversion computations:

>>> an_hour.to_str('%.1f [%s]', unit=Duration.m, conv=float)
'60.0 [m]'

The default numerical type is int, which in particular implies that you get a null amount if the requested unit is larger than the quantity:

>>> an_hour.to_str('%d [%s]', unit=Duration.days)
'0 [days]'

Conversion to string uses the unit originally used for defining the quantity and the %g%s format:

>>> str(an_hour)
'1hour'

to_timedelta(duration)¶

Convert a duration into a Python datetime.timedelta object.

This is useful to operate on Python’s datetime.time and datetime.date objects, which can be added or subtracted to datetime.timedelta.

class gc3libs.quantity.Memory¶

Represent an amount of RAM.

Construction of a memory quantity can be done by parsing a string specification (amount followed by unit):

>>> byte = Memory('1 B')
>>> kilobyte = Memory('1 kB')

A new quantity can also be defined as a multiple of an existing one:

>>> a_thousand_kB = 1000*kilobyte

The base-10 units (up to TB, Terabytes) and base-2 (up to TiB, TiBiBytes) are available as attributes of the Memory class. This allows for a third way of constructing quantity objects, i.e., by passing the amount and the unit separately to the constructor:

>>> a_megabyte = Memory(1, Memory.MB)
>>> a_mibibyte = Memory(1, Memory.MiB)

>>> a_gigabyte = 1*Memory.GB
>>> a_gibibyte = 1*Memory.GiB

>>> two_terabytes = 2*Memory.TB
>>> two_tibibytes = 2*Memory.TiB

Two memory quantities are equal if they indicate the exact same amount in bytes:

>>> kilobyte == 1000*byte
True
>>> a_megabyte == a_mibibyte
False
>>> a_megabyte < a_mibibyte
True
>>> a_megabyte > a_gigabyte
False

Basic arithmetic is possible with memory quantities:

>>> two_bytes = byte + byte
>>> two_bytes == 2*byte
True
>>> half_gigabyte = a_gigabyte / 2
>>> half_gigabyte
Memory(476.837, unit=MiB)

The ratio of two memory quantities is correctly computed as a pure (floating-point) number:

>>> a_gigabyte / a_megabyte
1000.0

It is also possible to add memory quantities defined with different units; the result is naturally expressed in the smaller unit of the two:

>>> one_gigabyte_and_half = 1*Memory.GB + 500*Memory.MB
>>> one_gigabyte_and_half
Memory(1500, unit=MB)

Note that the two unit class and numeric amount are accessible through the unit and amount() attributes:

>>> one_gigabyte_and_half.unit
Memory(1, unit=MB)
>>> one_gigabyte_and_half.amount()
1500

The amount() method accepts an optional specification of an alternate unit to express the amount into:

>>> one_gigabyte_and_half.amount(Memory.GB)
1

An optional conv argument is available to specify a numerical domain for conversion, in case the default integer arithmetic is not precise enough:

>>> one_gigabyte_and_half.amount(Memory.GB, conv=float)
1.5

The to_str() method allows representing a quantity as a string, and provides choice of the output format and unit. The format string should contain exactly two %-specifiers: the first one is used to format the numerical amount, and the second one to format the measurement unit name.

By default, the unit used originally for defining the quantity is used:

>>> a_megabyte.to_str('%d [%s]')
'1 [MB]'

This can be overridden by specifying an optional second argument unit:

>>> a_megabyte.to_str('%d [%s]', unit=Memory.kB)
'1000 [kB]'

A third optional argument conv can set the numerical type to be used for conversion computations:

>>> a_megabyte.to_str('%g%s', unit=Memory.GB, conv=float)
'0.001GB'

The default numerical type is int, which in particular implies that you get a null amount if the requested unit is larger than the quantity:

>>> a_megabyte.to_str('%g%s', unit=Memory.GB, conv=int)
'0GB'

Conversion to string uses the unit originally used for defining the quantity and the %g%s format:

>>> str(a_megabyte)
'1MB'

class gc3libs.quantity.Quantity(base_unit_name, **other_units)¶

Metaclass for creating quantity classes.

This factory creates subclasses of _Quantity and bootstraps the base unit.

The name of the base unit is given as argument to the metaclass instance:

>>> class Memory1(object):
...   __metaclass__ = Quantity('B')
...
>>> B = Memory1('1 B')
>>> print (2*B)
2B

Optional keyword arguments create additional units; the argument key gives the unit name, and its value gives the ratio of the new unit to the base unit. For example:

>>> class Memory2(object):
...   __metaclass__ = Quantity('B', kB=1000, MB=1000*1000)
...
>>> a_thousand_kB = Memory2('1000kB')
>>> MB = Memory2('1   MB')
>>> a_thousand_kB == MB
True

Note that the units (base and additional) are also available as class attributes for easier referencing in Python code:

>>> a_thousand_kB == Memory2.MB
True

gc3libs.session¶

class gc3libs.session.Session(path, store_url=None, create=True, **extra_args)¶

A ‘session’ is a persistent collection of tasks.

Tasks added to the session are persistently recorded using an instance of gc3libs.persistence.Store. Stores can be shared among different sessions: each session knows wich jobs it ‘owns’.

A session is associated to a directory, which holds all the data releated to that session. Specifically, two files are always created in the session directory andused internally by this class:

index.txt: contains a list of all job IDs associated with this session;
store.url: its contents are the URL of the store to create (as would be passed to the gc3libs.persistence.make_store factory).

To only argument needed to instantiate a session is the path of the directory; the directory name will be used as the identifier of the session itself. For example, the following code creates a temporary directory and the two files mentioned above inside it:

>>> import tempfile; tmpdir = tempfile.mktemp(dir='.')
>>> session = Session(tmpdir)
>>> sorted(os.listdir(tmpdir))
['created', 'session_ids.txt', 'store.url']

When a Session object is created with a path argument pointing to an existing valid session, the index of jobs is automatically loaded into memory, and the store pointed to by the store.url file in the session directory will be used, disregarding the contents of the `store_url` argument.

In other words, the store_url argument is only used when creating a new session. If no store_url argument is passed (i.e., it has its default value), a Session object will instantiate and use a FileSystemStore store, keeping data in the jobs subdirectory of the session directory.

Methods add and remove are provided to manage the collection; the len() operator returns the number of tasks in the session; iteration over a session returns the tasks one by one:

>>> task1 = gc3libs.Task()
>>> id1 = session.add(task1)
>>> task2 = gc3libs.Task()
>>> id2 = session.add(task2)
>>> len(session)
2
>>> for t in session:
...     print(type(t))
<class 'gc3libs.Task'>
<class 'gc3libs.Task'>
>>> session.remove(id1)
>>> len(session)
1

When passed the flush=False optional argument, methods add and remove do not update the session metadata: i.e., the tasks are added or removed from the store and the in-memory task list, but the updated task list is not saved back to disk. This is useful when making many changes in a row; call Session.flush to persist the full set of changes.

The Store object is anyway accessible in the store attribute of each Session instance:

>>> type(session.store)
<class 'gc3libs.persistence.filesystem.FilesystemStore'>

However, Session defines methods save and load as a convenient proxy to the corresponding Store methods:

>>> obj = gc3libs.persistence.Persistable()
>>> oid = session.save(obj)
>>> obj2 = session.load(oid)
>>> obj.persistent_id == obj2.persistent_id
True

The whole session data can be removed by using method destroy:

>>> session.destroy()
>>> os.path.exists(session.path)
False

add(task, flush=True)¶

Add a Task to the current session, save it to the associated persistent storage, and return the assigned persistent_id:

>>> # create new, empty session
>>> import tempfile; tmpdir = tempfile.mktemp(dir='.')
>>> session = Session(tmpdir)
>>> len(session)
0

>>> # add a task to it
>>> task = gc3libs.Task()
>>> tid1 = session.add(task)
>>> len(session)
1

Duplicates are silently ignored: the same object can be added many times to the session, but gets the same ID each time:

>>> # add a different task
>>> tid2 = session.add(task)
>>> len(session)
1
>>> tid1 == tid2
True

>>> # do cleanup
>>> session.destroy()
>>> os.path.exists(session.path)
False

destroy()¶: Remove the session directory and all the tasks it contains from the store which are associated to this session.

Note

This will remove the associated task storage if and only if the storage is contained in the session directory!

flush()¶

Update session metadata.

Should be used after a save/remove operations, to ensure that the session state and metadata is correctly persisted.

forget(task_id, flush=True)¶: Remove task identified by task_id from the current session but not from the associated storage.

list_ids()¶: Return set of all task IDs belonging to this session.

list_names()¶: Return set of names of tasks belonging to this session.

load(obj_id)¶

Load an object from persistent storage and return it.

This is just a convenience proxy for calling method load on the Store instance associated with this session.

remove(task_id, flush=True)¶: Remove task identified by task_id from the current session and from the associated storage.

save(obj)¶

Save an object to the persistent storage and return persistent_id of the saved object.

This is just a convenience proxy for calling method save on the Store instance associated with this session.

The object is not added to the session, nor is session meta-data updated:

# create an empty session
>>> import tempfile; tmpdir = tempfile.mktemp(dir='.')
>>> session = Session(tmpdir)
>>> 0 == len(session)
True

# use `save` on an object
>>> obj = gc3libs.persistence.Persistable()
>>> oid = session.save(obj)

# session is still empty
>>> 0 == len(session)
True

# do cleanup
>>> session.destroy()
>>> os.path.exists(session.path)
False

save_all(flush=True)¶: Save all modified tasks to persistent storage.

set_end_timestamp(time=None)¶

Create a file named finished in the session directory. It’s creation/modification time will be used to know when the session has finished.

Please note that Session does not know when a session is finished, so this method should be called by a SessionBasedScript class.

set_start_timestamp(time=None)¶: Create a file named created in the session directory. It’s creation/modification time will be used to know when the session has sarted.

gc3libs.template¶

Support and expansion of programmatic templates.

The module gc3libs.template allows creation of textual templates with a simple object-oriented programming interface: given a string with a list of substitutions (using the syntax of Python’s standard substitute module), a set of replacements can be specified, and the gc3libs.template.expansions function will generate all possible texts coming from the same template. Templates can be nested, and expansions generated recursviely.

class gc3libs.template.Template(template, validator=<function <lambda>>, **extra_args)¶

A template object is a pair (obj, keywords). Methods are provided to substitute the keyword values into obj, and to iterate over expansions of the given keywords (optionally filtering the allowed combination of keyword values).

Second optional argument validator must be a function that accepts a set of keyword arguments, and returns True if the keyword combination is valid (can be expanded/substituted back into the template) or False if it should be discarded. The default validator passes any combination of keywords/values.

expansions(**keywords)¶: Iterate over all valid expansions of the templated object and the template keywords. Returned items are Template instances constucted with the expanded template object and a valid combination of keyword values.

substitute(**extra_args)¶

Return result of interpolating the value of keywords into the template. Keyword arguments extra_args can be used to override keyword values passed to the constructor.

If the templated object provides a substitute method, then return the result of invoking it with the template keywords as keyword arguments. Otherwise, return the result of applying Python standard library’s string.Template.safe_substitute() on the string representation of the templated object.

Raise ValueError if the set of keywords/values is not valid according to the validator specified in the constructor.

gc3libs.template.expansions(obj, **extra_args)¶

Iterate over all expansions of a given object, recursively expanding all templates found. How the expansions are actually computed, depends on the type of object being passed in the first argument obj:

If obj is a list, iterate over expansions of items in obj. (In particular, this flattens out nested lists.)

Example:
```
>>> L = [0, [2, 3]]
>>> list(expansions(L))
[0, 2, 3]
```
If obj is a dictionary, return dictionary formed by all combinations of a key k in obj with an expansion of the corresponding value obj[k]. Expansions are computed by recursively calling expansions(obj[k], **extra_args).

Example:
```
>>> D = {'a':1, 'b':[2,3]}
>>> list(expansions(D))
[{'a': 1, 'b': 2}, {'a': 1, 'b': 3}]
```
If obj is a tuple, iterate over all tuples formed by the expansion of every item in obj. (Each item t[i] is expanded by calling expansions(t[i], **extra_args).)

Example:
```
>>> T = (1, [2, 3])
>>> list(expansions(T))
[(1, 2), (1, 3)]
```

If obj is a Template class instance, then the returned values are the result of applying the template to the expansion of each of its keywords.

Example:

>>> T1 = Template("a=${n}", n=[0,1])
>>> list(expansions(T1))
[Template('a=${n}', n=0), Template('a=${n}', n=1)]

Note that keywords passed to the expand invocation override the ones used in template construction:

>>> T2 = Template("a=${n}")
>>> list(expansions(T2, n=[1,3]))
[Template('a=${n}', n=1), Template('a=${n}', n=3)]

>>> T3 = Template("a=${n}", n=[0,1])
>>> list(expansions(T3, n=[2,3]))
[Template('a=${n}', n=2), Template('a=${n}', n=3)]

Any other value is returned unchanged.

Example:

>>> V = 42
>>> list(expansions(V))
[42]

gc3libs.url¶

Utility classes and methods for dealing with URLs.

class gc3libs.url.Url¶

Represent a URL as a named-tuple object. This is an immutable object that cannot be changed after creation.

The following read-only attributes are defined on objects of class Url.

Attribute	Index	Value	Value if not present
scheme	0	URL scheme specifier	empty string
netloc	1	Network location part	empty string
path	2	Hierarchical path	empty string
query	3	Query component	empty string
hostname	4	Host name (lower case)	None
port	5	Port number as integer (if present)	None
username	6	User name	None
password	7	Password	None

There are two ways of constructing Url objects:

By passing a string urlstring:

>>> u = Url('http://www.example.org/data')

>>> u.scheme
'http'
>>> u.netloc
'www.example.org'
>>> u.path
'/data'

The default URL scheme is file:

>>> u = Url('/tmp/foo')
>>> u.scheme
'file'
>>> u.path
'/tmp/foo'

Please note that extra leading slashes ‘/’ are interpreted as the begining of a network location:

>>> u = Url('//foo/bar')
>>> u.path
'/bar'
>>> u.netloc
'foo'
>>> Url('///foo/bar').path
'/foo/bar'

Check RFC 3986 http://tools.ietf.org/html/rfc3986

If force_abs is True (default), then the path attribute is made absolute, by calling os.path.abspath if necessary:

>>> u = Url('foo/bar', force_abs=True)
>>> os.path.isabs(u.path)
True

Otherwise, if force_abs is False, then the path attribute stores the passed string unchanged:

>>> u = Url('foo', force_abs=False)
>>> os.path.isabs(u.path)
False
>>> u.path
'foo'

Other keyword arguments can specify defaults for missing parts of the URL:

>>> u = Url('/tmp/foo', scheme='file', netloc='localhost')
>>> u.scheme
'file'
>>> u.netloc
'localhost'
>>> u.path
'/tmp/foo'

By passing keyword arguments only, to construct an Url object with exactly those values for the named fields:
```
>>> u = Url(scheme='http', netloc='www.example.org', path='/data')
```
In this form, the force_abs parameter is ignored.

adjoin(relpath)¶

Return a new Url, constructed by appending relpath to the path section of this URL.

Example:

>>> u0 = Url('http://www.example.org')
>>> u1 = u0.adjoin('data')
>>> str(u1)
'http://www.example.org/data'

>>> u2 = u1.adjoin('moredata')
>>> str(u2)
'http://www.example.org/data/moredata'

Even if relpath starts with /, it is still appended to the path in the base URL:

>>> u3 = u2.adjoin('/evenmore')
>>> str(u3)
'http://www.example.org/data/moredata/evenmore'

class gc3libs.url.UrlKeyDict(iter_or_dict=None, force_abs=False)¶

A dictionary class enforcing that all keys are URLs.

Strings and/or objects returned by urlparse can be used as keys. Setting a string key automatically translates it to a URL:

>>> d = UrlKeyDict()
>>> d['/tmp/foo'] = 1
>>> for k in d.keys(): print (type(k), k.path) 
(<class '....Url'>, '/tmp/foo')

Retrieving the value associated with a key works with both the string or the url value of the key:

>>> d['/tmp/foo']
1
>>> d[Url('/tmp/foo')]
1

Key lookup can use both the string or the Url value as well:

>>> '/tmp/foo' in d
True
>>> Url('/tmp/foo') in d
True
>>> 'file:///tmp/foo' in d
True
>>> 'http://example.org' in d
False

Class UrlKeyDict supports initialization by copying items from another dict instance or from an iterable of (key, value) pairs:

>>> d1 = UrlKeyDict({ '/tmp/foo':'foo', '/tmp/bar':'bar' })
>>> d2 = UrlKeyDict([ ('/tmp/foo', 'foo'), ('/tmp/bar', 'bar') ])
>>> d1 == d2
True

Differently from dict, initialization from keyword arguments alone is not supported:

>>> d3 = UrlKeyDict(foo='foo', bar='bar') 
Traceback (most recent call last):
    ...
TypeError: __init__() got an unexpected keyword argument 'foo'

An empty UrlKeyDict instance is returned by the constructor when called with no parameters:

>>> d0 = UrlKeyDict()
>>> len(d0)
0

If force_abs is True, then all paths are converted to absolute ones in the dictionary keys.

>>> d = UrlKeyDict(force_abs=True)
>>> d['foo'] = 1
>>> for k in d.keys(): print os.path.isabs(k.path)
True

>>> d = UrlKeyDict(force_abs=False)
>>> d['foo'] = 2
>>> for k in d.keys(): print os.path.isabs(k.path)
False

class gc3libs.url.UrlValueDict(iter_or_dict=None, force_abs=False, **extra_args)¶

A dictionary class enforcing that all values are URLs.

Strings and/or objects returned by urlparse can be used as values. Setting a string value automatically translates it to a URL:

>>> d = UrlValueDict()
>>> d[1] = '/tmp/foo'
>>> d[2] = Url('file:///tmp/bar')
>>> for v in d.values(): print (type(v), v.path) 
(<class '....Url'>, '/tmp/foo')
(<class '....Url'>, '/tmp/bar')

Retrieving the value associated with a key always returns the URL-type value, regardless of how it was set:

>>> repr(d[1])
"Url(scheme='file', netloc='', path='/tmp/foo', hostname=None, port=None, username=None, password=None)"

Class UrlValueDict supports initialization by any of the methods that work with a plain dict instance:

>>> d1 = UrlValueDict({ 'foo':'/tmp/foo', 'bar':'/tmp/bar' })
>>> d2 = UrlValueDict([ ('foo', '/tmp/foo'), ('bar', '/tmp/bar') ])
>>> d3 = UrlValueDict(foo='/tmp/foo', bar='/tmp/bar')

>>> d1 == d2
True
>>> d2 == d3
True

In particular, an empty UrlDict instance is returned by the constructor when called with no parameters:

>>> d0 = UrlValueDict()
>>> len(d0)
0

If force_abs is True, then all paths are converted to absolute ones in the dictionary values.

>>> d = UrlValueDict(force_abs=True)
>>> d[1] = 'foo'
>>> for v in d.values(): print os.path.isabs(v.path)
True

>>> d = UrlValueDict(force_abs=False)
>>> d[2] = 'foo'
>>> for v in d.values(): print os.path.isabs(v.path)
False

gc3libs.utils¶

Generic Python programming utility functions.

This module collects general utility functions, not specifically related to GC3Libs. A good rule of thumb for determining if a function or class belongs in here is the following: place a function or class in this module if you could copy its code into the sources of a different project and it would not stop working.

class gc3libs.utils.Enum¶

A generic enumeration class. Inspired by: http://stackoverflow.com/questions/36932/whats-the-best-way-to-implement-an-enum-in-python/2182437#2182437 with some more syntactic sugar added.

An Enum class must be instanciated with a list of strings, that make the enumeration “label”:

>>> Animal = Enum('CAT', 'DOG')

Each label is available as an instance attribute, evaluating to itself:

>>> Animal.DOG
'DOG'

>>> Animal.CAT == 'CAT'
True

As a consequence, you can test for presence of an enumeration label by string value:

>>> 'DOG' in Animal
True

Finally, enumeration labels can also be iterated upon:

>>> for a in Animal: print a
DOG
CAT

class gc3libs.utils.History¶

A list of messages with timestamps and (optional) tags.

The append method should be used to add a message to the History:

>>> L = History()
>>> L.append('first message')
>>> L.append('second one')

The last method returns the text of the last message appended, with its timestamp:

>>> L.last().startswith('second one at')
True

Iterating over a History instance returns message texts in the temporal order they were added to the list, with their timestamp:

>>> for msg in L: print(msg) 
first message ...

append(message, *tags)¶

Append a message to this History.

The message is timestamped with the time at the moment of the call.

The optional tags argument is a sequence of strings. Tags are recorded together with the message and may be used to filter log messages given a set of labels. (This feature is not yet implemented.)

format_message(message)¶: Return a formatted message, appending to the message its timestamp in human readable format.

last()¶: Return text of last message appended. If log is empty, return empty string.

gc3libs.utils.Log¶: alias of History

class gc3libs.utils.PlusInfinity¶

An object that is greater-than any other object.

>>> x = PlusInfinity()

>>> x > 1
True
>>> 1 < x
True
>>> 1245632479102509834570124871023487235987634518745 < x
True

>>> x > sys.maxint
True
>>> x < sys.maxint
False
>>> sys.maxint < x
True

PlusInfinity objects are actually larger than any given Python object:

>>> x > 'azz'
True
>>> x > object()
True

Note that PlusInfinity is a singleton, therefore you always get the same instance when calling the class constructor:

>>> x = PlusInfinity()
>>> y = PlusInfinity()
>>> x is y
True

Relational operators try to return the correct value when comparing PlusInfinity to itself:

>>> x < y
False
>>> x <= y
True
>>> x == y
True
>>> x >= y
True
>>> x > y
False

class gc3libs.utils.Singleton¶

Derived classes of Singleton can have only one instance in the running Python interpreter.

>>> x = Singleton()
>>> y = Singleton()
>>> x is y
True

class gc3libs.utils.Struct(initializer=None, **extra_args)¶

A dict-like object, whose keys can be accessed with the usual ‘[...]’ lookup syntax, or with the ‘.’ get attribute syntax.

Examples:

>>> a = Struct()
>>> a['x'] = 1
>>> a.x
1
>>> a.y = 2
>>> a['y']
2

Values can also be initially set by specifying them as keyword arguments to the constructor:

>>> a = Struct(z=3)
>>> a['z']
3
>>> a.z
3

Like dict instances, Struct`s have a `copy method to get a shallow copy of the instance:

>>> b = a.copy()
>>> b.z
3

copy()¶: Return a (shallow) copy of this Struct instance.

gc3libs.utils.backup(path)¶

Rename the filesystem entry at path by appending a unique numerical suffix; return new name.

For example,

create a test file:

>>> import tempfile
>>> path = tempfile.mkstemp()[1]

then make a backup of it; the backup will end in .~1~:

>>> path1 = backup(path)
>>> os.path.exists(path + '.~1~')
True

3. re-create the file, and make a second backup: this time the file will be renamed with a .~2~ extension:

>>> open(path, 'w').close()
>>> path2 = backup(path)
>>> os.path.exists(path + '.~2~')
True

cleaning up tests

>>> os.remove(path+'.~1~')
>>> os.remove(path+'.~2~')

gc3libs.utils.basename_sans(path)¶: Return base name without the extension.

gc3libs.utils.cache_for(lapse)¶

Cache the result of a (nullary) method invocation for a given amount of time. Use as a decorator on object methods whose results are to be cached.

Store the result of the first invocation of the decorated method; if another invocation happens before lapse seconds have passed, return the cached value instead of calling the real function again. If a new call happens after the grace period has expired, call the real function and store the result in the cache.

Note: Do not use with methods that take keyword arguments, as they will be discarded! In addition, arguments are compared to elements in the cache by identity, so that invoking the same method with equal but distinct object will result in two separate copies of the result being computed and stored in the cache.

Cache results and timestamps are stored into the objects’ _cache_value and _cache_last_updated attributes, so the caches are destroyed with the object when it goes out of scope.

The working of the cached method can be demonstrated by the following simple code:

>>> class X(object):
...     def __init__(self):
...         self.times = 0
...     @cache_for(2)
...     def foo(self):
...             self.times += 1
...             return ("times effectively run: %d" % self.times)
>>> x = X()
>>> x.foo()
'times effectively run: 1'
>>> x.foo()
'times effectively run: 1'
>>> time.sleep(3)
>>> x.foo()
'times effectively run: 2'

gc3libs.utils.cat(*args, **extra_args)¶

Concatenate the contents of all args into output. Both output and each of the args can be a file-like object or a string (indicating the path of a file to open).

If append is True, then output is opened in append-only mode; otherwise it is overwritten.

gc3libs.utils.copy_recursively(src, dst, overwrite=False)¶: Copy src to dst, descending it recursively if necessary.

gc3libs.utils.copyfile(src, dst, overwrite=False, link=False)¶

Copy a file from src to dst; return True if the copy was actually made. If overwrite is False (default), an existing destination entry is left unchanged and False is returned.

If link is True, an attempt at hard-linking is done first; failing that, we copy the source file onto the destination one. Permission bits and modification times are copied as well.

If dst is a directory, a file with the same basename as src is created (or overwritten) in the directory specified.

gc3libs.utils.copytree(src, dst, overwrite=False)¶

Recursively copy an entire directory tree rooted at src. If overwrite is False (default), entries that already exist in the destination tree are left unchanged and not overwritten.

gc3libs.workflow¶

Implementation of task collections.

Tasks can be grouped into collections, which are tasks themselves, therefore can be controlled (started/stopped/cancelled) like a single whole. Collection classes provided in this module implement the basic patterns of job group execution; they can be combined to form more complex workflows. Hook methods are provided so that derived classes can implement problem-specific job control policies.

class gc3libs.workflow.ParallelTaskCollection(tasks=None, **extra_args)¶

A ParallelTaskCollection runs all of its tasks concurrently.

The collection state is set to TERMINATED once all tasks have reached the same terminal status.

add(task)¶: Add a task to the collection.

attach(controller)¶: Use the given Controller interface for operations on the job associated with this task.

kill(**extra_args)¶: Terminate all tasks in the collection, and set collection state to TERMINATED.

progress()¶: Try to advance all jobs in the collection to the next state in a normal lifecycle. Return list of task execution states.

submit(resubmit=False, **extra_args)¶: Start all tasks in the collection.

update_state(**extra_args)¶: Update state of all tasks in the collection.

class gc3libs.workflow.RetryableTask(task, max_retries=0, **extra_args)¶

Wrap a Task instance and re-submit it until a specified termination condition is met.

By default, the re-submission upon failure happens iff execution terminated with nonzero return code; the failed task is retried up to self.max_retries times (indefinitely if self.max_retries is 0).

Override the retry method to implement a different retryal policy.

Note: The resubmission code is implemented in the terminated(), so be sure to call it if you override in derived classes.

retry()¶

Return True or False, depending on whether the failed task should be re-submitted or not.

The default behavior is to retry a task iff its execution terminated with nonzero returncode and the maximum retry limit has not been reached. If self.max_retries is 0, then the dependent task is retried indefinitely.

Override this method in subclasses to implement a different policy.

update_state()¶: Update the state of the dependent task, then resubmit it if it’s TERMINATED and self.retry() is True.

class gc3libs.workflow.SequentialTaskCollection(tasks, **extra_args)¶

A SequentialTaskCollection runs its tasks one at a time.

After a task has completed, the next method is called with the index of the finished task in the self.tasks list; the return value of the next method is then made the collection execution.state. If the returned state is RUNNING, then the subsequent task is started, otherwise no action is performed.

The default next implementation just runs the tasks in the order they were given to the constructor, and sets the state to TERMINATED when all tasks have been run.

attach(controller)¶: Use the given Controller interface for operations on the job associated with this task.

kill(**extra_args)¶: Stop execution of this sequence. Kill currently-running task (if any), then set collection state to TERMINATED.

next(done)¶

Return the state or task to run when step number done is completed.

This method is called when a task is finished; the done argument contains the index number of the just-finished task into the self.tasks list. In other words, the task that just completed is available as self.tasks[done].

The return value from next can be either a task state (i.e., an instance of Run.State), or a valid index number for self.tasks. In the first case:

if the return value is Run.State.TERMINATED, then no other jobs will be run;
otherwise, the return value is assigned to execution.state and the next job in the self.tasks list is executed.

If instead the return value is a (nonnegative) number, then tasks in the sequence will be re-run starting from that index.

The default implementation runs tasks in the order they were given to the constructor, and sets the state to TERMINATED when all tasks have been run. This method can (and should) be overridden in derived classes to implement policies for serial job execution.

submit(resubmit=False, **extra_args)¶: Start the current task in the collection.

update_state(**extra_args)¶: Update state of the collection, based on the jobs’ statuses.

class gc3libs.workflow.StagedTaskCollection(**extra_args)¶

Simplified interface for creating a sequence of Tasks. This can be used when the number of Tasks to run is fixed and known at program writing time.

A StagedTaskCollection subclass should define methods stage0, stage1, ... up to stageN (for some arbitrary value of N positive integer). Each of these stageN must return a Task instance; the task returned by the stage0 method will be executed first, followed by the task returned by stage1, and so on. The sequence stops at the first N such that stageN is not defined.

The exit status of the whole sequence is the exit status of the last Task instance run. However, if any of the stageX methods returns an integer value instead of a Task instance, then the sequence stops and that number is used as the sequence exit code.

class gc3libs.workflow.TaskCollection(tasks=None, **extra_args)¶

Base class for all task collections. A “task collection” is a group of tasks, that can be managed collectively as a single one.

A task collection implements the same interface as the Task class, so you can use a TaskCollection everywhere a Task is required. A task collection has a state attribute, which is an instance of gc3libs.Run.State; each concrete collection class decides how to deduce a collective state based on the individual task states.

add(task)¶: Add a task to the collection.

attach(controller)¶: Use the given Controller interface for operations on the job associated with this task.

peek(what, offset=0, size=None, **extra_args)¶: Raise a gc3libs.exceptions.InvalidOperation error, as there is no meaningful semantics that can be defined for peek into a generic collection of tasks.

remove(task)¶: Remove a task from the collection.

stats(only=None)¶

Return a dictionary mapping each state name into the count of tasks in that state. In addition, the following keys are defined:

ok: count of TERMINATED tasks with return code 0
failed: count of TERMINATED tasks with nonzero return code
total: count of managed tasks, whatever their state

If the optional argument only is not None, tasks whose class is not contained in only are ignored.

Parameters:	only (tuple) – Restrict counting to tasks of these classes.

terminated()¶

Called when the job state transitions to TERMINATED, i.e., the job has finished execution (with whatever exit status, see returncode) and the final output has been retrieved.

Default implementation for TaskCollection is to set the exitcode to the maximum of the exit codes of its tasks.

update_state(**extra_args)¶: Update the running state of all managed tasks.

gc3libs.application¶

Support for running a generic application with the GC3Libs.

gc3libs.application.apppot¶

Support for AppPot-hosted applications.

For more details about AppPot, visit: <http://apppot.googlecode.com>

class gc3libs.application.apppot.AppPotApplication(arguments, inputs, outputs, output_dir, apppot_img=None, apppot_changes=None, apppot_tag='ENV/APPPOT-0.21', apppot_extra=[], **extra_args)¶

Base class for AppPot-hosted applications. Provides the same interface as the base Application and runs the specified command in an AppPot instance.

In addition to the standard Application keyword arguments, the following ones can be given to steer the AppPot execution:

apppot_img: Path or URL to the AppPot system image to use. If None (default), then the default AppPot system image on the remote system is used.
apppot_changes: Path or URL to an AppPot changes file to be merged at system startup.
apppot_tag: ARC RTE to use for submission of this AppPot job.
apppot_extra: List of additional UML boot command-line arguments. (Passed to the AppPot instance via apppot-start‘s --extra option.)

gc3libs.application.gamess¶

Specialized support for computational jobs running GAMESS-US.

class gc3libs.application.gamess.GamessAppPotApplication(inp_file_path, *other_input_files, **extra_args)¶

Specialized AppPotApplication object to submit computational jobs running GAMESS-US.

This class makes no check or guarantee that a GAMESS-US executable will be available in the executing AppPot instance: the apppot_img and apppot_tag keyword arguments can be used to select the AppPot system image to run this application; see the AppPotApplication for information.

The __init__ construction interface is compatible with the one used in GamessApplication. The only required parameter for construction is the input file name; any other argument names an additional input file, that is added to the Application.inputs list, but not otherwise treated specially.

Any other keyword parameter that is valid in the Application class can be used here as well, with the exception of input and output. Note that a GAMESS-US job is always submitted with join = True, therefore any stderr setting is ignored.

class gc3libs.application.gamess.GamessApplication(inp_file_path, *other_input_files, **extra_args)¶

Specialized Application object to submit computational jobs running GAMESS-US.

The only required parameter for construction is the input file name; subsequent positional arguments are additional input files, that are added to the Application.inputs list, but not otherwise treated specially.

The verno parameter is used to request a specific version of GAMESS-US; if the default value None is used, the default version of GAMESS-US at the executing site is run.

Any other keyword parameter that is valid in the Application class can be used here as well, with the exception of input and output. Note that a GAMESS-US job is always submitted with join = True, therefore any stderr setting is ignored.

terminated()¶

Append to log the termination status line as extracted from the GAMESS ‘.out’ file.

The job exit code .execution.exitcode is (re)set according to the following table:

Exit code	Meaning
0	the output file contains the string `EXECUTION OF GAMESS TERMINATED normally`
1	the output file contains the string `EXECUTION OF GAMESS TERMINATED -ABNORMALLY-`
2	the output file contains the string `ddikick exited unexpectedly`
70 (os.EX_SOFTWARE)	the output file cannot be read or does not match any of the above patterns

gc3libs.application.rosetta¶

Specialized support for computational jobs running programs in the Rosetta suite.

class gc3libs.application.rosetta.RosettaApplication(application, application_release, inputs, outputs=[], flags_file=None, database=None, arguments=[], **extra_args)¶

Specialized Application object to submit one run of a single application in the Rosetta suite.

Required parameters for construction:

application: name of the Rosetta application to call (e.g., “docking_protocol” or “relax”)

inputs: a dict instance, keys are Rosetta -in:file:* options, values are the (local) path names of the corresponding files. (Example: inputs={"-in:file:s":"1brs.pdb"})

outputs: list of output file names to fetch after Rosetta has finished running.

Optional parameters:

flags_file: path to a local file containing additional flags for controlling Rosetta invocation; if None, a local configuration file will be used.

database: (local) path to the Rosetta DB; if this is not specified, then it is assumed that the correct location will be available at the remote execution site as environment variable ROSETTA_DB_LOCATION

arguments: If present, they will be appended to the Rosetta application command line.

terminated()¶: Extract output files from the tar archive created by the ‘rosetta.sh’ script.

class gc3libs.application.rosetta.RosettaDockingApplication(pdb_file_path, native_file_path=None, number_of_decoys_to_create=1, flags_file=None, application_release='3.1', **extra_args)¶

Specialized Application class for executing a single run of the Rosetta “docking_protocol” application.

Currently used in the gdocking app.

gc3libs.authentication¶

Authentication support for the GC3Libs.

class gc3libs.authentication.Auth(config, auto_enable)¶

A mish-mash of authorization functions.

This class actually serves the purposes of:

a registry of authorization ‘types’, mapping internally-assigned names to Python classes;
storage for the configuration information (which can be arbitrary, but should probably be read off a configuration file);
a factory, returning a ‘SomeAuth’ object through which clients can deal with actual authorization issues (like checking if the authorization credentials are valid and getting/renewing them).
a cache, that tries to avoid expensive re-initializations of Auth objects by allowing only one live instance per type, and returning it when requested.

FIXME

There are several problems with this approach:

the configuration is assumed static and cannot be changed after the Auth instance is constructed.
there is no communication between the client class and the Auth classes.
there is no control over the lifetime of the cache; at a minimum, it should be settable per-auth-type.
I’m unsure whether the mapping of ‘type names’ (as in the type=... keyword in the config file) to Python classes belongs in a generic factory method or in the configuration file reader. (Probably the former, so the code here would actually be right.)
The whole auto_enable stuff really belongs to the user-interface part, which is also hard-coded in the auth classes, and should not be.

add_params(**params)¶

Add the specified keyword arguments as initialization parameters to all the configured auth classes.

Parameters that have already been specified are silently overwritten.

get(auth_name, **kwargs)¶

Return an instance of the Auth class corresponding to the given auth_name, or raise an exception if instanciating the same class has given an unrecoverable exception in past calls.

Additional keyword arguments are passed unchanged to the class constructor and can override values specified at configuration time.

Instances are remembered for the lifetime of the program; if an instance of the given class is already present in the cache, that one is returned; otherwise, an instance is contructed with the given parameters.

Caution

The params keyword arguments are only used if a new instance is constructed and are silently ignored if the cached instance is returned.

class gc3libs.authentication.NoneAuth(**auth)¶: Auth proxy to use when no auth is needed.

gc3libs.authentication.ssh¶

Authentication support for accessing resources through the SSH protocol.

gc3libs.authentication.grid¶

Authentication support with Grid proxy certificates.

gc3libs.backends¶

Interface to different resource management systems for the GC3Libs.

class gc3libs.backends.LRMS(name, architecture, max_cores, max_cores_per_job, max_memory_per_core, max_walltime, auth=None, **extra_args)¶

Base class for interfacing with a computing resource.

The following construction parameters are also set as instance attributes. All of them are mandatory, except auth.

Attribute name	Expected Type	Meaning
name	string	A unique identifier for this resource, used for generating error message.
architecture	set of Run.Arch values	Should contain one entry per each architecture supported. Valid architecture values are constants in the gc3libs.Run.Arch class.
auth	string	A gc3libs.authentication.Auth instance that will be used to access the computational resource associated with this backend. The default value None is used to mean that no authentication credentials are needed (e.g., access to the resource has been pre-authenticated) or is managed outside of GC3Pie).
max_cores	int	Maximum number of CPU cores that GC3Pie can allocate on this resource.
max_cores_per_job	int	Maximum number of CPU cores that GC3Pie can allocate on this resource for a single job.
max_memory_per_core	Memory	Maximum memory that GC3Pie can allocate to jobs on this resource. The value is per core, so the actual amount allocated to a single job is the value of this entry multiplied by the number of cores requested by the job.
max_walltime	Duration	Maximum wall-clock time that can be allotted to a single job running on this resource.

The above should be considered immutable attributes: they are specified at construction time and changed never after.

The following attributes are instead dynamically provided (i.e., defined by the get_resource_status() method or similar), thus can change over the lifetime of the object:

Attribute name	Type
free_slots	int
user_run	int
user_queued	int
queued	int

static authenticated(fn)¶

Decorator: mark a function as requiring authentication.

Each invocation of the decorated function causes a call to the get method of the authentication object (configured with the auth parameter to the class constructor).

cancel_job(app)¶: Cancel a running job. If app is associated to a queued or running remote job, tell the execution middleware to cancel it.

close()¶: Implement gracefully close on LRMS dependent resources e.g. transport

free(app)¶

Free up any remote resources used for the execution of app. In particular, this should delete any remote directories and files.

Call this method when app.execution.state is anything other than TERMINATED results in undefined behavior and will likely be the cause of errors later on. Be cautious.

get_resource_status()¶: Update the status of the resource associated with this LRMS instance in-place. Return updated Resource object.

get_results(job, download_dir, overwrite=False)¶: Retrieve job output files into local directory download_dir (which must already exists). Will not overwrite existing files, unless the optional argument overwrite is True.

peek(app, remote_filename, local_file, offset=0, size=None)¶

Download size bytes (at offset offset from the start) from remote file remote_filename and write them into local_file. If size is None (default), then snarf contents of remote file from offset unto the end.

Argument local_file is either a local path name (string), or a file-like object supporting a .write() method. If local_file is a path name, it is created if not existent, otherwise overwritten.

Argument remote_filename is the name of a file in the remote job “sandbox”.

Any exception raised by operations will be passed through.

submit_job(application, job)¶

Submit an Application instance to the configured computational resource; return a gc3libs.Job instance for controlling the submitted job.

This method only returns if the job is successfully submitted; upon any failure, an exception is raised.

Note:

job.state is not altered; it is the caller’s responsibility to update it.

the job object may be updated with any information that is necessary for this LRMS to perform further operations on it.

update_job_state(app)¶: Query the state of the remote job associated with app and update app.execution.state accordingly. Return the corresponding Run.State; see Run.State for more details.

validate_data(data_file_list=None)¶: Return True if the list of files is expressed in one of the file transfer protocols the LRMS supports. Return False otherwise

gc3libs.backends.batch¶

This module provides a generic BatchSystem class from which all batch-like backends should inherit.

class gc3libs.backends.batch.BatchSystem(name, architecture, max_cores, max_cores_per_job, max_memory_per_core, max_walltime, auth, frontend, transport, accounting_delay=15, **extra_args)¶

Base class for backends dealing with a batch-queue system (e.g., PBS/TORQUE, Grid Engine, etc.)

This is an abstract class, that you should subclass in order to interface with a given batch queuing system. (Remember to call this class’ constructor in the derived class __init__ method.)

cancel_job(*args, **kwargs)¶: Cancel a running job. If app is associated to a queued or running remote job, tell the execution middleware to cancel it.

close(*args, **kwargs)¶: Return True if the list of files is expressed in one of the file transfer protocols the LRMS supports. Return False otherwise

free(*args, **kwargs)¶

Free up any remote resources used for the execution of app. In particular, this should delete any remote directories and files.

Call this method when app.execution.state is anything other than TERMINATED results in undefined behavior and will likely be the cause of errors later on. Be cautious.

get_epilogue_script(app)¶: This method will get the epilogue script(s) for the app application and will return a string which contains the contents of the script(s) merged together.

get_jobid_from_submit_output(output, regexp)¶: Parse the output of the submission command. Regexp is provided by the caller.

get_prologue_script(app)¶: This method will get the prologue script(s) for the app application and will return a string which contains the contents of the script(s) merged together.

get_results(*args, **kwargs)¶: Retrieve job output files into local directory download_dir (which must already exists). Will not overwrite existing files, unless the optional argument overwrite is True.

peek(*args, **kwargs)¶

Download size bytes (at offset offset from the start) from remote file remote_filename and write them into local_file. If size is None (default), then snarf contents of remote file from offset unto the end.

Argument local_file is either a local path name (string), or a file-like object supporting a .write() method. If local_file is a path name, it is created if not existent, otherwise overwritten.

Argument remote_filename is the name of a file in the remote job “sandbox”.

Any exception raised by operations will be passed through.

submit_job(*args, **kwargs)¶: This method will create a remote directory to store job’s sandbox, and will copy the sandbox in there.

update_job_state(*args, **kwargs)¶: Query the state of the remote job associated with app and update app.execution.state accordingly. Return the corresponding Run.State; see Run.State for more details.

validate_data(data_file_list)¶: Return True if the list of files is expressed in one of the file transfer protocols the LRMS supports. Return False otherwise

gc3libs.backends.batch.generic_filename_mapping(jobname, jobid, file_name)¶: Map STDOUT/STDERR filenames (as recorded in Application.outputs) to commonly used default STDOUT/STDERR file names (e.g., <jobname>.o<jobid>).

gc3libs.backends.arc0¶

Job control on ARC0 resources.

class gc3libs.backends.arc0.ArcLrms(name, architecture, max_cores, max_cores_per_job, max_memory_per_core, max_walltime, auth, arc_ldap=None, frontend=None, lost_job_timeout=120, **extra_args)¶

Manage jobs through the ARC middleware.

In addition to attributes

Attribute name Type Required?

arc_ldap string

frontend string yes

cancel_job(*args, **kwargs)¶: Cancel a running job. If app is associated to a queued or running remote job, tell the execution middleware to cancel it.

close()¶: Return True if the list of files is expressed in one of the file transfer protocols the LRMS supports. Return False otherwise

free(*args, **kwargs)¶

Free up any remote resources used for the execution of app. In particular, this should delete any remote directories and files.

Call this method when app.execution.state is anything other than TERMINATED results in undefined behavior and will likely be the cause of errors later on. Be cautious.

get_resource_status(obj, *args)¶

Get dynamic information from the ARC infosystem and set attributes on the current object accordingly.

The following attributes are set:

total_queued
free_slots
user_running
user_queued

get_results(*args, **kwargs)¶: Retrieve job output files into local directory download_dir (which must already exists). Will not overwrite existing files, unless the optional argument overwrite is True.

peek(*args, **kwargs)¶

Download size bytes (at offset offset from the start) from remote file remote_filename and write them into local_file. If size is None (default), then snarf contents of remote file from offset unto the end.

Argument local_file is either a local path name (string), or a file-like object supporting a .write() method. If local_file is a path name, it is created if not existent, otherwise overwritten.

Argument remote_filename is the name of a file in the remote job “sandbox”.

Any exception raised by operations will be passed through.

submit_job(*args, **kwargs)¶

Submit an Application instance to the configured computational resource; return a gc3libs.Job instance for controlling the submitted job.

This method only returns if the job is successfully submitted; upon any failure, an exception is raised.

Note:

job.state is not altered; it is the caller’s responsibility to update it.

the job object may be updated with any information that is necessary for this LRMS to perform further operations on it.

update_job_state(obj, *args)¶

Query the state of the ARC0 job associated with app and update app.execution.state accordingly. Return the corresponding Run.State; see Run.State for more details.

The mapping of ARC0 job statuses to Run.State is as follows:

ARC job status Run.State

ACCEPTED SUBMITTED

ACCEPTING SUBMITTED

SUBMITTING SUBMITTED

PREPARING SUBMITTED

PREPARED SUBMITTED

INLRMS:Q SUBMITTED

INLRMS:R RUNNING

INLRMS:O STOPPED

INLRMS:E STOPPED

INLRMS:S STOPPED

INLRMS:H STOPPED

FINISHING RUNNING

EXECUTED RUNNING

FINISHED TERMINATING

CANCELING TERMINATING

FINISHED TERMINATING

FAILED TERMINATING

KILLED TERMINATED

DELETED TERMINATED

Any other ARC job status is mapped to Run.State.UNKNOWN. In particular, querying a job ID that is not found in the ARC information system will result in UNKNOWN state, as will querying a job that has just been submitted and has not yet found its way to the infosys.

validate_data(data_file_list)¶: Return True if the list of files is expressed in one of the file transfer protocols the LRMS supports. Return False otherwise

gc3libs.backends.arc1¶

Job control using libarcclient. (Which can submit to all EMI-supported resources.)

class gc3libs.backends.arc1.Arc1Lrms(name, architecture, max_cores, max_cores_per_job, max_memory_per_core, max_walltime, auth, arc_ldap, frontend=None, lost_job_timeout=120, **extra_args)¶

Manage jobs through ARC’s libarcclient.

cancel_job(*args, **kwargs)¶: Cancel a running job. If app is associated to a queued or running remote job, tell the execution middleware to cancel it.

close()¶: Return True if the list of files is expressed in one of the file transfer protocols the LRMS supports. Return False otherwise

free(*args, **kwargs)¶

Free up any remote resources used for the execution of app. In particular, this should delete any remote directories and files.

Call this method when app.execution.state is anything other than TERMINATED results in undefined behavior and will likely be the cause of errors later on. Be cautious.

get_resource_status(obj, *args)¶

Get dynamic information from the ARC infosystem and set attributes on the current object accordingly.

The following attributes are set:

total_queued
free_slots
user_running
user_queued

get_results(*args, **kwargs)¶: Retrieve job output files into local directory download_dir (which must already exists). Will not overwrite existing files, unless the optional argument overwrite is True.

peek(*args, **kwargs)¶

Download size bytes (at offset offset from the start) from remote file remote_filename and write them into local_file. If size is None (default), then snarf contents of remote file from offset unto the end.

Argument local_file is either a local path name (string), or a file-like object supporting a .write() method. If local_file is a path name, it is created if not existent, otherwise overwritten.

Argument remote_filename is the name of a file in the remote job “sandbox”.

Any exception raised by operations will be passed through.

submit_job(*args, **kwargs)¶

Submit an Application instance to the configured computational resource; return a gc3libs.Job instance for controlling the submitted job.

This method only returns if the job is successfully submitted; upon any failure, an exception is raised.

Note:

job.state is not altered; it is the caller’s responsibility to update it.

the job object may be updated with any information that is necessary for this LRMS to perform further operations on it.

update_job_state(obj, *args)¶

Query the state of the ARC job associated with app and update app.execution.state accordingly. Return the corresponding Run.State; see Run.State for more details.

The mapping of ARC job statuses to Run.State is as follows:

ARC job status Run.State

ACCEPTED SUBMITTED

SUBMITTING SUBMITTED

PREPARING SUBMITTED

QUEUING SUBMITTED

RUNNING RUNNING

FINISHING RUNNING

FINISHED TERMINATING

FAILED TERMINATING

KILLED TERMINATED

DELETED TERMINATED

HOLD STOPPED

OTHER UNKNOWN

Any other ARC job status is mapped to Run.State.UNKNOWN.

validate_data(data_file_list)¶: Return True if the list of files is expressed in one of the file transfer protocols the LRMS supports. Return False otherwise

gc3libs.backends.lsf¶

Job control on SGE clusters (possibly connecting to the front-end via SSH).

class gc3libs.backends.lsf.LsfLrms(name, architecture, max_cores, max_cores_per_job, max_memory_per_core, max_walltime, auth, frontend, transport, accounting_delay=15, **extra_args)¶

Job control on LSF clusters (possibly by connecting via SSH to a submit node).

get_resource_status(obj, *args)¶

Get dynamic information out of the LSF subsystem.

return self

dynamic information required (at least those): total_queued free_slots user_running user_queued

gc3libs.backends.sge¶

Job control on SGE clusters (possibly connecting to the front-end via SSH).

class gc3libs.backends.sge.SgeLrms(name, architecture, max_cores, max_cores_per_job, max_memory_per_core, max_walltime, auth, frontend, transport, accounting_delay=15, default_pe=None, **extra_args)¶

Job control on SGE clusters (possibly by connecting via SSH to a submit node).

get_resource_status(*args, **kwargs)¶: Update the status of the resource associated with this LRMS instance in-place. Return updated Resource object.

gc3libs.backends.sge.compute_nr_of_slots(qstat_output)¶

Compute the number of total, free, and used/reserved slots from the output of SGE’s qstat -F.

Return a dictionary instance, mapping each host name into a dictionary instance, mapping the strings total, available, and unavailable to (respectively) the the total number of slots on the host, the number of free slots on the host, and the number of used+reserved slots on the host.

Cluster-wide totals are associated with key global.

Note: The ‘available slots’ computation carried out by this function is unreliable: there is indeed no notion of a ‘global’ or even ‘per-host’ number of ‘free’ slots in SGE. Slot numbers can be computed per-queue, but a host can belong in different queues at the same time; therefore the number of ‘free’ slots available to a job actually depends on the queue it is submitted to. Since SGE does not force users to submit explicitly to a queue, rather encourages use of a sort of ‘implicit’ routing queue, there is no way to compute the number of free slots, as this entirely depends on how local policies will map a job to the available queues.

gc3libs.backends.sge.count_jobs(qstat_output, whoami)¶

Parse SGE’s qstat output (as contained in string qstat_output) and return a quadruple (R, Q, r, q) where:

R is the total number of running jobs in the SGE cell (from any user);

Q is the total number of queued jobs in the SGE cell (from any user);

r is the number of running jobs submitted by user whoami;

q is the number of queued jobs submitted by user whoami

gc3libs.backends.sge.parse_qhost_f(qhost_output)¶: Parse SGE’s qhost -F output (as contained in string qhost_output) and return a dict instance, mapping each host name to its attributes.

gc3libs.backends.sge.parse_qstat_f(qstat_output)¶: Parse SGE’s qstat -F output (as contained in string qstat_output) and return a dict instance, mapping each queue name to its attributes.

gc3libs.backends.pbs¶

Job control on PBS/Torque clusters (possibly connecting to the front-end via SSH).

class gc3libs.backends.pbs.PbsLrms(name, architecture, max_cores, max_cores_per_job, max_memory_per_core, max_walltime, auth, frontend, transport, accounting_delay=15, queue=None, **extra_args)¶

Job control on PBS/Torque clusters (possibly by connecting via SSH to a submit node).

get_resource_status(*args, **kwargs)¶: Update the status of the resource associated with this LRMS instance in-place. Return updated Resource object.

gc3libs.backends.pbs.count_jobs(qstat_output, whoami)¶

Parse PBS/Torque’s qstat output (as contained in string qstat_output) and return a quadruple (R, Q, r, q) where:

R is the total number of running jobs in the PBS/Torque cell (from any user);

Q is the total number of queued jobs in the PBS/Torque cell (from any user);

r is the number of running jobs submitted by user whoami;

q is the number of queued jobs submitted by user whoami

gc3libs.backends.shellcmd¶

Run applications as local processes.

class gc3libs.backends.shellcmd.ShellcmdLrms(name, architecture, max_cores, max_cores_per_job, max_memory_per_core, max_walltime, auth=None, time_cmd='/usr/bin/time', spooldir=None, **extra_args)¶

Execute an Application instance as a local process.

Construction of an instance of ShellcmdLrms takes the following optional parameters (in addition to any parameters taken by the base class LRMS):

Parameters:

time_cmd (str) –
Path to the GNU time command. Default is /usr/bin/time which is correct on all known Linux distributions.

This backend uses many of the extended features of GNU time, so the shell-builtins or the BSD time will not work.
spooldir (str) – Path to a filesystem location where to create temporary working directories for processes executed through this backend. The default value None means to use $TMPDIR or /tmp (see tempfile.mkftemp for details).

cancel_job(app)¶: Cancel a running job. If app is associated to a queued or running remote job, tell the execution middleware to cancel it.

close()¶: Implement gracefully close on LRMS dependent resources e.g. transport

free(app)¶

Delete the temporary directory where a child process has run.

The temporary directory is removed with all its content, recursively.

get_resource_status()¶: Update the status of the resource associated with this LRMS instance in-place. Return updated Resource object.

get_results(app, download_dir, overwrite=False)¶: Retrieve job output files into local directory download_dir (which must already exists). Will not overwrite existing files, unless the optional argument overwrite is True.

peek(app, remote_filename, local_file, offset=0, size=None)¶

Download size bytes (at offset offset from the start) from remote file remote_filename and write them into local_file. If size is None (default), then snarf contents of remote file from offset unto the end.

Argument local_file is either a local path name (string), or a file-like object supporting a .write() method. If local_file is a path name, it is created if not existent, otherwise overwritten.

Argument remote_filename is the name of a file in the remote job “sandbox”.

Any exception raised by operations will be passed through.

submit_job(app)¶

Run an Application instance as a local process.

See:	LRMS.submit_job

update_job_state(app)¶: Query the running status of the local process whose PID is stored into app.execution.lrms_jobid, and map the POSIX process status to GC3Libs Run.State.

validate_data(data_file_list=[])¶

Return False if any of the URLs in data_file_list cannot be handled by this backend.

The shellcmd backend can only handle file URLs.

gc3libs.backends.transport¶

The Transport class hierarchy provides an abstraction layer to execute commands and copy/move files irrespective of whether the destination is the local computer or a remote front-end that we access via SSH.

GC3Utils modules¶

gc3utils¶

gc3utils.frontend¶

This is the main entry point for command gc3utils – a simple command-line frontend to distributed resources

This is a generic front-end code; actual implementation of commands can be found in gc3utils.commands

gc3utils.frontend.main()¶: Generic front-end function to invoke the commands in gc3utils/commands.py

Run.State value	purpose	can change to
NEW	Job has not yet been submitted/started (i.e., gsub not called)	SUBMITTED (by gsub)
SUBMITTED	Job has been sent to execution resource	RUNNING, STOPPED
STOPPED	Trap state: job needs manual intervention (either user- or sysadmin-level) to resume normal execution	TERMINATING(by gkill), SUBMITTED (by miracle)
RUNNING	Job is executing on remote resource	TERMINATING
TERMINATING	Job has finished execution on remote resource; output not yet retrieved	TERMINATED
TERMINATED	Job execution is finished (correctly or not) and will not be resumed; output has been retrieved	None: final state

Raises:	exception `UnexpectedStateError` if the associated job goes into state STOPPED or UNKNOWN
Returns:	final returncode, or None if the execution state is not TERMINATED.

Raise:	LockTimeout, IOError, OSError
Returns:	A positive integer number, monotonically increasing with every call. A list of such numbers if argument qty is a positive integer.

GC3Libs programming API¶

gc3libs¶

gc3libs.cmdline¶

gc3libs.config¶

gc3libs.core¶

gc3libs.exceptions¶

gc3libs.persistence¶

A usage warning¶

gc3libs.quantity¶

gc3libs.session¶

gc3libs.template¶

gc3libs.url¶

gc3libs.utils¶

gc3libs.workflow¶

gc3libs.application¶

gc3libs.application.apppot¶

gc3libs.application.gamess¶

gc3libs.application.rosetta¶

gc3libs.authentication¶

gc3libs.authentication.ssh¶

gc3libs.authentication.grid¶

gc3libs.backends¶

gc3libs.backends.batch¶

gc3libs.backends.arc0¶

gc3libs.backends.arc1¶

gc3libs.backends.lsf¶

gc3libs.backends.sge¶

gc3libs.backends.pbs¶

gc3libs.backends.shellcmd¶

gc3libs.backends.transport¶

GC3Utils modules¶

gc3utils¶

gc3utils.frontend¶

gc3utils.commands¶