Beispiel #1
0
    def create_job_file(self, job_num, branches):
        task = self.task
        config = self.job_file_factory.Config()

        # the file postfix is pythonic range made from branches, e.g. [0, 1, 2, 4] -> "_0To5"
        postfix = "_{}To{}".format(branches[0], branches[-1] + 1)
        config.postfix = postfix
        pf = lambda s: "postfix:{}".format(s)

        # get the actual wrapper file that will be executed by the remote job
        wrapper_file = get_path(task.arc_wrapper_file())
        config.executable = os.path.basename(wrapper_file)

        # collect task parameters
        task_params = task.as_branch(branches[0]).cli_args(exclude={"branch"})
        task_params += global_cmdline_args()
        # add and remove some arguments
        task_params = remove_cmdline_arg(task_params, "--workers", 2)
        if task.arc_use_local_scheduler():
            task_params = add_cmdline_arg(task_params, "--local-scheduler")
        for arg in task.arc_cmdline_args() or []:
            if isinstance(arg, tuple):
                task_params = add_cmdline_arg(task_params, *arg)
            else:
                task_params = add_cmdline_arg(task_params, arg)

        # job script arguments
        job_args = JobArguments(
            task_cls=task.__class__,
            task_params=task_params,
            branches=branches,
            auto_retry=False,
            dashboard_data=self.dashboard.remote_hook_data(
                job_num, self.submission_data.attempts.get(job_num, 0)),
        )
        config.arguments = job_args.join()

        # meta infos
        config.job_name = task.task_id
        config.output_uri = task.arc_output_uri()

        # prepare render variables
        config.render_variables = {}

        # input files
        config.input_files = [wrapper_file, law_src_path("job", "job.sh")]
        config.render_variables["job_file"] = pf("job.sh")

        # add the bootstrap file
        bootstrap_file = task.arc_bootstrap_file()
        config.input_files.append(bootstrap_file)
        config.render_variables["bootstrap_file"] = pf(
            os.path.basename(bootstrap_file))

        # add the stageout file
        stageout_file = task.arc_stageout_file()
        if stageout_file:
            config.input_files.append(stageout_file)
            config.render_variables["stageout_file"] = pf(
                os.path.basename(stageout_file))

        # does the dashboard have a hook file?
        dashboard_file = self.dashboard.remote_hook_file()
        if dashboard_file:
            config.input_files.append(dashboard_file)
            config.render_variables["dashboard_file"] = pf(
                os.path.basename(dashboard_file))

        # output files
        config.output_files = []

        # custom content
        config.custom_content = []

        # log files
        config.log = None
        if task.transfer_logs:
            log_file = "stdall.txt"
            config.stdout = log_file
            config.stderr = log_file
            config.output_files.append(log_file)
            config.render_variables["log_file"] = pf(log_file)
        else:
            config.stdout = None
            config.stderr = None

        # task hook
        config = task.arc_job_config(config, job_num, branches)

        # determine basenames of input files and add that list to the render data
        input_basenames = [
            pf(os.path.basename(path)) for path in config.input_files
        ]
        config.render_variables["input_files"] = " ".join(input_basenames)

        return self.job_file_factory(**config.__dict__)
Beispiel #2
0
    def create_job_file(self, job_num, branches):
        task = self.task
        config = self.job_file_factory.Config()

        # the file postfix is pythonic range made from branches, e.g. [0, 1, 2, 4] -> "_0To5"
        postfix = "_{}To{}".format(branches[0], branches[-1] + 1)
        config.postfix = postfix
        pf = lambda s: "postfix:{}".format(s)

        # get the actual wrapper file that will be executed by the remote job
        wrapper_file = get_path(task.htcondor_wrapper_file())
        config.executable = os.path.basename(wrapper_file)

        # collect task parameters
        task_params = task.as_branch(branches[0]).cli_args(exclude={"branch"})
        task_params += global_cmdline_args(
            exclude=[("--workers", 1), ("--local-scheduler", 1)])
        if task.htcondor_use_local_scheduler():
            task_params = add_cmdline_arg(task_params, "--local-scheduler",
                                          "True")
        for arg in task.htcondor_cmdline_args() or []:
            if isinstance(arg, tuple):
                task_params = add_cmdline_arg(task_params, *arg)
            else:
                task_params = add_cmdline_arg(task_params, arg)

        # job script arguments
        job_args = JobArguments(
            task_cls=task.__class__,
            task_params=task_params,
            branches=branches,
            auto_retry=False,
            dashboard_data=self.dashboard.remote_hook_data(
                job_num, self.submission_data.attempts.get(job_num, 0)),
        )
        config.arguments = job_args.join()

        # prepare render variables
        config.render_variables = {}

        # input files
        config.input_files = [wrapper_file, law_src_path("job", "job.sh")]
        config.render_variables["job_file"] = pf("job.sh")

        # add the bootstrap file
        bootstrap_file = task.htcondor_bootstrap_file()
        if bootstrap_file:
            config.input_files.append(bootstrap_file)
            config.render_variables["bootstrap_file"] = pf(
                os.path.basename(bootstrap_file))

        # add the stageout file
        stageout_file = task.htcondor_stageout_file()
        if stageout_file:
            config.input_files.append(stageout_file)
            config.render_variables["stageout_file"] = pf(
                os.path.basename(stageout_file))

        # does the dashboard have a hook file?
        dashboard_file = self.dashboard.remote_hook_file()
        if dashboard_file:
            config.input_files.append(dashboard_file)
            config.render_variables["dashboard_file"] = pf(
                os.path.basename(dashboard_file))

        # output files
        config.output_files = []

        # custom content
        config.custom_content = []

        # logging
        # we do not use condor's logging mechanism since it requires that the submission directory
        # is present when it retrieves logs, and therefore we rely on the job.sh script
        config.log = None
        config.stdout = None
        config.stderr = None
        if task.transfer_logs:
            log_file = "stdall.txt"
            config.output_files.append(log_file)
            config.render_variables["log_file"] = pf(log_file)

        # we can use condor's file stageout only when the output directory is local
        # otherwise, one should use the stageout_file and stageout manually
        output_dir = task.htcondor_output_directory()
        if isinstance(output_dir, LocalDirectoryTarget):
            config.absolute_paths = True
            config.custom_content.append(("initialdir", output_dir.path))
        else:
            del config.output_files[:]

        # task hook
        config = task.htcondor_job_config(config, job_num, branches)

        # determine basenames of input files and add that list to the render data
        input_basenames = [
            pf(os.path.basename(path)) for path in config.input_files[1:]
        ]
        config.render_variables["input_files"] = " ".join(input_basenames)

        return self.job_file_factory(**config.__dict__)
Beispiel #3
0
    def create_job_file(self, job_num, branches):
        task = self.task
        config = self.job_file_factory.Config()

        # the file postfix is pythonic range made from branches, e.g. [0, 1, 2, 4] -> "_0To5"
        postfix = "_{}To{}".format(branches[0], branches[-1] + 1)
        config.postfix = postfix
        _postfix = lambda path: self.job_file_factory.postfix_file(
            path, postfix)
        pf = lambda s: "__law_job_postfix__:{}".format(s)

        # collect task parameters
        proxy_cmd = ProxyCommand(
            task.as_branch(branches[0]),
            exclude_task_args={"branch"},
            exclude_global_args=["workers", "local-scheduler"])
        if task.lsf_use_local_scheduler():
            proxy_cmd.add_arg("--local-scheduler", "True", overwrite=True)
        for key, value in OrderedDict(task.lsf_cmdline_args()).items():
            proxy_cmd.add_arg(key, value, overwrite=True)

        # job script arguments
        job_args = JobArguments(
            task_cls=task.__class__,
            task_params=proxy_cmd.build(skip_run=True),
            branches=branches,
            auto_retry=False,
            dashboard_data=self.dashboard.remote_hook_data(
                job_num, self.submission_data.attempts.get(job_num, 0)),
        )

        # get the actual wrapper file that will be executed by the remote job
        wrapper_file = get_path(task.lsf_wrapper_file())
        config.command = "bash {} {}".format(
            _postfix(os.path.basename(wrapper_file)), job_args.join())

        # meta infos
        config.job_name = task.task_id
        config.emails = True

        # prepare render variables
        config.render_variables = {}

        # input files
        config.input_files = [wrapper_file, law_src_path("job", "job.sh")]

        # add the bootstrap file
        bootstrap_file = task.lsf_bootstrap_file()
        if bootstrap_file:
            config.input_files.append(bootstrap_file)
            config.render_variables["bootstrap_file"] = pf(
                os.path.basename(bootstrap_file))

        # add the stageout file
        stageout_file = task.lsf_stageout_file()
        if stageout_file:
            config.input_files.append(stageout_file)
            config.render_variables["stageout_file"] = pf(
                os.path.basename(stageout_file))

        # does the dashboard have a hook file?
        dashboard_file = self.dashboard.remote_hook_file()
        if dashboard_file:
            config.input_files.append(dashboard_file)
            config.render_variables["dashboard_file"] = pf(
                os.path.basename(dashboard_file))

        # output files
        config.output_files = []

        # custom content
        config.custom_content = []

        # logging
        # we do not use lsf's logging mechanism since it requires that the submission directory
        # is present when it retrieves logs, and therefore we rely on the job.sh script
        config.stdout = None
        config.stderr = None
        if task.transfer_logs:
            log_file = "stdall.txt"
            config.custom_log_file = log_file
            config.render_variables["log_file"] = pf(log_file)

        # we can use lsf's file stageout only when the output directory is local
        # otherwise, one should use the stageout_file and stageout manually
        output_dir = task.lsf_output_directory()
        if isinstance(output_dir, LocalDirectoryTarget):
            config.absolute_paths = True
            config.cwd = output_dir.path
        else:
            del config.output_files[:]

        # task hook
        config = task.lsf_job_config(config, job_num, branches)

        # determine basenames of input files and add that list to the render data
        input_basenames = [
            pf(os.path.basename(path)) for path in config.input_files
        ]
        config.render_variables["input_files"] = " ".join(input_basenames)

        # build the job file and get the sanitized config
        job_file, config = self.job_file_factory(**config.__dict__)

        # determine the absolute custom log file if set
        abs_log_file = None
        if config.custom_log_file and isinstance(output_dir,
                                                 LocalDirectoryTarget):
            abs_log_file = output_dir.child(config.custom_log_file,
                                            type="f").path

        # return job and log files
        return {"job": job_file, "log": abs_log_file}
Beispiel #4
0
    def create_job_file(self, job_num, branches):
        task = self.task
        config = self.job_file_factory.Config()

        # the file postfix is pythonic range made from branches, e.g. [0, 1, 2, 4] -> "_0To5"
        postfix = "_{}To{}".format(branches[0], branches[-1] + 1)
        config.postfix = postfix
        pf = lambda s: "postfix:{}".format(s)

        # executable
        config.executable = "bash_wrapper.sh"

        # collect task parameters
        task_params = task.as_branch(branches[0]).cli_args(exclude={"branch"})
        task_params += global_cmdline_args()
        # force the local scheduler?
        ls_flag = "--local-scheduler"
        if ls_flag not in task_params and task.glite_use_local_scheduler():
            task_params.append(ls_flag)

        # job script arguments
        job_args = JobArguments(
            task_module=task.__class__.__module__,
            task_family=task.task_family,
            task_params=task_params,
            branches=branches,
            auto_retry=False,
            dashboard_data=self.dashboard.remote_hook_data(
                job_num, self.attempts.get(job_num, 0)),
        )
        config.arguments = job_args.join()

        # meta infos
        config.output_uri = task.glite_output_uri()

        # prepare render variables
        config.render_variables = {}

        # input files
        config.input_files = [
            law_src_path("job", "bash_wrapper.sh"),
            law_src_path("job", "job.sh")
        ]
        config.render_variables["job_file"] = pf("job.sh")

        # add the bootstrap file
        bootstrap_file = task.glite_bootstrap_file()
        config.input_files.append(bootstrap_file)
        config.render_variables["bootstrap_file"] = pf(
            os.path.basename(bootstrap_file))

        # add the stageout file
        stageout_file = task.glite_stageout_file()
        if stageout_file:
            config.input_files.append(stageout_file)
            config.render_variables["stageout_file"] = pf(
                os.path.basename(stageout_file))

        # does the dashboard have a hook file?
        dashboard_file = self.dashboard.remote_hook_file()
        if dashboard_file:
            config.input_files.append(dashboard_file)
            config.render_variables["dashboard_file"] = pf(
                os.path.basename(dashboard_file))

        # determine basenames of input files and add that list to the render data
        input_basenames = [
            pf(os.path.basename(path)) for path in config.input_files
        ]
        config.render_variables["input_files"] = " ".join(input_basenames)

        # output files
        config.output_files = []

        # custom content
        config.custom_content = []

        # log file
        if task.transfer_logs:
            log_file = "stdall.txt"
            config.stdout = log_file
            config.stderr = log_file
            config.output_files.append(log_file)
            config.render_variables["log_file"] = pf(log_file)
        else:
            config.stdout = None
            config.stderr = None

        # task hook
        config = task.glite_job_config(config, job_num, branches)

        return self.job_file_factory(**config.__dict__)
Beispiel #5
0
    def create_job_file(self, job_num, branches):
        task = self.task

        # the file postfix is pythonic range made from branches, e.g. [0, 1, 2, 4] -> "_0To5"
        postfix = "_{}To{}".format(branches[0], branches[-1] + 1)

        # create the config
        c = self.job_file_factory.Config()
        c.input_files = DeprecatedInputFiles()
        c.output_files = []
        c.render_variables = {}
        c.custom_content = []

        # get the actual wrapper file that will be executed by the remote job
        c.executable = get_path(task.glite_wrapper_file())
        c.input_files["executable_file"] = c.executable
        law_job_file = law_src_path("job", "law_job.sh")
        if c.executable != law_job_file:
            c.input_files["job_file"] = law_job_file

        # collect task parameters
        proxy_cmd = ProxyCommand(
            task.as_branch(branches[0]),
            exclude_task_args={"branch"},
            exclude_global_args=["workers", "local-scheduler"])
        if task.glite_use_local_scheduler():
            proxy_cmd.add_arg("--local-scheduler", "True", overwrite=True)
        for key, value in OrderedDict(task.glite_cmdline_args()).items():
            proxy_cmd.add_arg(key, value, overwrite=True)

        # job script arguments
        job_args = JobArguments(
            task_cls=task.__class__,
            task_params=proxy_cmd.build(skip_run=True),
            branches=branches,
            auto_retry=False,
            dashboard_data=self.dashboard.remote_hook_data(
                job_num, self.submission_data.attempts.get(job_num, 0)),
        )
        c.arguments = job_args.join()

        # add the bootstrap file
        bootstrap_file = task.glite_bootstrap_file()
        if bootstrap_file:
            c.input_files["bootstrap_file"] = bootstrap_file

        # add the stageout file
        stageout_file = task.glite_stageout_file()
        if stageout_file:
            c.input_files["stageout_file"] = stageout_file

        # does the dashboard have a hook file?
        dashboard_file = self.dashboard.remote_hook_file()
        if dashboard_file:
            c.input_files["dashboard_file"] = dashboard_file

        # log file
        c.stdout = None
        c.stderr = None
        if task.transfer_logs:
            log_file = "stdall.txt"
            c.stdout = log_file
            c.stderr = log_file
            c.custom_log_file = log_file

        # meta infos
        c.output_uri = task.glite_output_uri()

        # task hook
        c = task.glite_job_config(c, job_num, branches)

        # build the job file and get the sanitized config
        job_file, c = self.job_file_factory(postfix=postfix, **c.__dict__)

        # determine the custom log file uri if set
        abs_log_file = None
        if c.custom_log_file:
            abs_log_file = os.path.join(c.output_uri, c.custom_log_file)

        # return job and log files
        return {"job": job_file, "log": abs_log_file}
Beispiel #6
0
    def create_job_file(self, job_num, branches):
        task = self.task
        config = self.job_file_factory.Config()

        # the file postfix is pythonic range made from branches, e.g. [0, 1, 2, 4] -> "_0To5"
        postfix = "_{}To{}".format(branches[0], branches[-1] + 1)
        config.postfix = postfix
        pf = lambda s: "__law_job_postfix__:{}".format(s)

        # get the actual wrapper file that will be executed by the remote job
        wrapper_file = get_path(task.glite_wrapper_file())
        config.executable = os.path.basename(wrapper_file)

        # collect task parameters
        proxy_cmd = ProxyCommand(task.as_branch(branches[0]), exclude_task_args={"branch"},
            exclude_global_args=["workers", "local-scheduler"])
        if task.glite_use_local_scheduler():
            proxy_cmd.add_arg("--local-scheduler", "True", overwrite=True)
        for key, value in OrderedDict(task.glite_cmdline_args()).items():
            proxy_cmd.add_arg(key, value, overwrite=True)

        # job script arguments
        job_args = JobArguments(
            task_cls=task.__class__,
            task_params=proxy_cmd.build(skip_run=True),
            branches=branches,
            auto_retry=False,
            dashboard_data=self.dashboard.remote_hook_data(
                job_num, self.submission_data.attempts.get(job_num, 0)),
        )
        config.arguments = job_args.join()

        # meta infos
        config.output_uri = task.glite_output_uri()

        # prepare render variables
        config.render_variables = {}

        # input files
        config.input_files = [wrapper_file, law_src_path("job", "job.sh")]
        config.render_variables["job_file"] = pf("job.sh")

        # add the bootstrap file
        bootstrap_file = task.glite_bootstrap_file()
        config.input_files.append(bootstrap_file)
        config.render_variables["bootstrap_file"] = pf(os.path.basename(bootstrap_file))

        # add the stageout file
        stageout_file = task.glite_stageout_file()
        if stageout_file:
            config.input_files.append(stageout_file)
            config.render_variables["stageout_file"] = pf(os.path.basename(stageout_file))

        # does the dashboard have a hook file?
        dashboard_file = self.dashboard.remote_hook_file()
        if dashboard_file:
            config.input_files.append(dashboard_file)
            config.render_variables["dashboard_file"] = pf(os.path.basename(dashboard_file))

        # output files
        config.output_files = []

        # custom content
        config.custom_content = []

        # log file
        if task.transfer_logs:
            log_file = "stdall.txt"
            config.stdout = log_file
            config.stderr = log_file
            config.custom_log_file = log_file
            config.render_variables["log_file"] = pf(log_file)
        else:
            config.stdout = None
            config.stderr = None

        # task hook
        config = task.glite_job_config(config, job_num, branches)

        # determine basenames of input files and add that list to the render data
        input_basenames = [pf(os.path.basename(path)) for path in config.input_files]
        config.render_variables["input_files"] = " ".join(input_basenames)

        # build the job file and get the sanitized config
        job_file, config = self.job_file_factory(**config.__dict__)

        # determine the custom log file uri if set
        abs_log_file = None
        if config.custom_log_file:
            abs_log_file = os.path.join(config.output_uri, config.custom_log_file)

        # return job and log files
        return {"job": job_file, "log": abs_log_file}
Beispiel #7
0
    def create_job_file(self, job_num, branches):
        task = self.task
        config = self.job_file_factory.Config()

        # the file postfix is pythonic range made from branches, e.g. [0, 1, 2] -> "_0To3"
        postfix = "_{}To{}".format(branches[0], branches[-1] + 1)
        config.postfix = postfix
        _postfix = lambda path: self.job_file_factory.postfix_file(
            path, postfix)
        pf = lambda s: "postfix:{}".format(s)

        # collect task parameters
        task_params = task.as_branch(branches[0]).cli_args(exclude={"branch"})
        task_params += global_cmdline_args()
        # force the local scheduler?
        ls_flag = "--local-scheduler"
        if ls_flag not in task_params and task.lsf_use_local_scheduler():
            task_params.append(ls_flag)

        # job script arguments
        job_args = JobArguments(
            task_module=task.__class__.__module__,
            task_family=task.task_family,
            task_params=task_params,
            start_branch=branches[0],
            end_branch=branches[-1] + 1,
            auto_retry=False,
            dashboard_data=self.dashboard.remote_hook_data(
                job_num, self.attempts.get(job_num, 0)),
        )
        config.command = "bash {} {}".format(_postfix("job.sh"),
                                             job_args.join())

        # meta infos
        config.job_name = task.task_id
        config.emails = True

        # prepare render variables
        config.render_variables = {}

        # input files
        config.input_files = [law_src_path("job", "job.sh")]

        # add the bootstrap file
        bootstrap_file = task.lsf_bootstrap_file()
        if bootstrap_file:
            config.input_files.append(bootstrap_file)
            config.render_variables["bootstrap_file"] = pf(
                os.path.basename(bootstrap_file))

        # add the stageout file
        stageout_file = task.lsf_stageout_file()
        if stageout_file:
            config.input_files.append(stageout_file)
            config.render_variables["stageout_file"] = pf(
                os.path.basename(stageout_file))

        # does the dashboard have a hook file?
        dashboard_file = self.dashboard.remote_hook_file()
        if dashboard_file:
            config.input_files.append(dashboard_file)
            config.render_variables["dashboard_file"] = pf(
                os.path.basename(dashboard_file))

        # determine basenames of input files and add that list to the render data
        input_basenames = [
            pf(os.path.basename(path)) for path in config.input_files
        ]
        config.render_variables["input_files"] = " ".join(input_basenames)

        # output files
        config.output_files = []

        # logging
        # we do not use lsf's logging mechanism since it requires that the submission directory
        # is present when it retrieves logs, and therefore we rely on the job.sh script
        config.stdout = None
        config.stderr = None
        if task.transfer_logs:
            log_file = "stdall.txt"
            config.output_files.append(log_file)
            config.render_variables["log_file"] = pf(log_file)

        # we can use lsf's file stageout only when the output directory is local
        # otherwise, one should use the stageout_file and stageout manually
        output_dir = task.lsf_output_directory()
        if not isinstance(output_dir, LocalDirectoryTarget):
            del config.output_files[:]
        else:
            config.absolute_paths = True
            config.cwd = output_dir.path

        # task hook
        config = task.lsf_job_config(config, job_num, branches)

        return self.job_file_factory(**config.__dict__)
Beispiel #8
0
    def create_job_file(self, job_num, branches):
        task = self.task

        # the file postfix is pythonic range made from branches, e.g. [0, 1, 2, 4] -> "_0To5"
        postfix = "_{}To{}".format(branches[0], branches[-1] + 1)

        # create the config
        c = self.job_file_factory.Config()
        c.input_files = DeprecatedInputFiles()
        c.output_files = []
        c.render_variables = {}
        c.custom_content = []

        # get the actual wrapper file that will be executed by the remote job
        c.executable = get_path(task.htcondor_wrapper_file())
        c.input_files["executable_file"] = c.executable
        law_job_file = law_src_path("job", "law_job.sh")
        if c.executable != law_job_file:
            c.input_files["job_file"] = law_job_file

        # collect task parameters
        proxy_cmd = ProxyCommand(
            task.as_branch(branches[0]),
            exclude_task_args={"branch"},
            exclude_global_args=["workers", "local-scheduler"])
        if task.htcondor_use_local_scheduler():
            proxy_cmd.add_arg("--local-scheduler", "True", overwrite=True)
        for key, value in OrderedDict(task.htcondor_cmdline_args()).items():
            proxy_cmd.add_arg(key, value, overwrite=True)

        # job script arguments
        job_args = JobArguments(
            task_cls=task.__class__,
            task_params=proxy_cmd.build(skip_run=True),
            branches=branches,
            auto_retry=False,
            dashboard_data=self.dashboard.remote_hook_data(
                job_num, self.submission_data.attempts.get(job_num, 0)),
        )
        c.arguments = job_args.join()

        # add the bootstrap file
        bootstrap_file = task.htcondor_bootstrap_file()
        if bootstrap_file:
            c.input_files["bootstrap_file"] = bootstrap_file

        # add the stageout file
        stageout_file = task.htcondor_stageout_file()
        if stageout_file:
            c.input_files["stageout_file"] = stageout_file

        # does the dashboard have a hook file?
        dashboard_file = self.dashboard.remote_hook_file()
        if dashboard_file:
            c.input_files["dashboard_file"] = dashboard_file

        # logging
        # we do not use htcondor's logging mechanism since it might require that the submission
        # directory is present when it retrieves logs, and therefore we use a custom log file
        c.log = None
        c.stdout = None
        c.stderr = None
        if task.transfer_logs:
            c.custom_log_file = "stdall.txt"

        # when the output dir is local, we can run within this directory for easier output file
        # handling and use absolute paths for input files
        output_dir = task.htcondor_output_directory()
        output_dir_is_local = isinstance(output_dir, LocalDirectoryTarget)
        if output_dir_is_local:
            c.absolute_paths = True
            c.custom_content.append(("initialdir", output_dir.path))

        # task hook
        c = task.htcondor_job_config(c, job_num, branches)

        # when the output dir is not local, direct output files are not possible
        if not output_dir_is_local:
            del c.output_files[:]

        # build the job file and get the sanitized config
        job_file, c = self.job_file_factory(postfix=postfix, **c.__dict__)

        # get the location of the custom local log file if any
        abs_log_file = None
        if output_dir_is_local and c.custom_log_file:
            abs_log_file = os.path.join(output_dir.path, c.custom_log_file)

        # return job and log files
        return {"job": job_file, "log": abs_log_file}