pyiron_base.jobs.job.core module
The JobCore the most fundamental pyiron job class.
- class pyiron_base.jobs.job.core.DatabaseProperties(job_dict=None)
Bases:
object
Access the database entry of the job
- class pyiron_base.jobs.job.core.HDF5Content(project_hdf5)
Bases:
object
Access the HDF5 file of the job
- class pyiron_base.jobs.job.core.JobCore(project, job_name)
Bases:
HasGroups
The JobCore the most fundamental pyiron job class. From this class the GenericJob as well as the reduced JobPath class are derived. While JobPath only provides access to the HDF5 file it is about one order faster.
Implements
HasGroups
. Groups are HDF groups in the HDF file associated with the job and any child jobs, nodes are HDF dataset in the HDF file.- Parameters:
project (ProjectHDFio) – ProjectHDFio instance which points to the HDF5 file the job is stored in
job_name (str) – name of the job, which has to be unique within the project
- .. attribute:: job_name
name of the job, which has to be unique within the project
- .. attribute:: status
- execution status of the job, can be one of the following [initialized, appended, created, submitted,
running, aborted, collect, suspended, refresh, busy, finished]
- .. attribute:: job_id
unique id to identify the job in the pyiron database
- .. attribute:: parent_id
job id of the predecessor job - the job which was executed before the current one in the current job series
- .. attribute:: master_id
- job id of the master job - a meta job which groups a series of jobs, which are executed either in parallel
or in serial.
- .. attribute:: child_ids
list of child job ids - only meta jobs have child jobs - jobs which list the meta job as their master
- .. attribute:: project
Project instance the jobs is located in
- .. attribute:: project_hdf5
ProjectHDFio instance which points to the HDF5 file the job is stored in
- .. attribute:: job_info_str
short string to describe the job by it is job_name and job ID - mainly used for logging
- .. attribute:: working_directory
working directory of the job is executed in - outside the HDF5 file
- .. attribute:: path
path to the job as a combination of absolute file system path and path within the HDF5 file.
- check_if_job_exists(job_name=None, project=None)
Check if a job already exists in an specific project.
- Parameters:
job_name (str) – Job name (optional)
project (ProjectHDFio, Project) – Project path (optional)
- Returns:
True / False
- Return type:
(bool)
- property child_ids
list of child job ids - only meta jobs have child jobs - jobs which list the meta job as their master
- Returns:
list of child job ids
- Return type:
list
- compress(files_to_compress=None, files_to_remove=None)
Compress the output files of a job object.
- Parameters:
files_to_compress (list)
- property content
- copy()
Copy the JobCore object which links to the HDF5 file
- Returns:
New FileHDFio object pointing to the same HDF5 file
- Return type:
- copy_to(project, new_job_name=None, input_only=False, new_database_entry=True, copy_files=True)
Copy the content of the job including the HDF5 file to a new location
- Parameters:
project (JobCore/ProjectHDFio/Project) – project to copy the job to
new_job_name (str) – The new name to assign the duplicate job. Required if the project is None or the same project as the copied job. (Default is None, try to keep the same name.)
input_only (bool) – [True/False] Whether to copy only the input. (Default is False.)
new_database_entry (bool) – [True/False] Whether to create a new database entry. If input_only is True then new_database_entry is False. (Default is True.)
copy_files (bool) – [True/False] copy the files inside the working directory - default True
- Returns:
JobCore object pointing to the new location.
- Return type:
- property database_entry
- decompress()
Decompress the output files of a compressed job object.
- property files
Allows to browse the files in a job directory.
By default this object prints itself as a listing of the job directory and the files inside.
>>> job.files /path/to/my/job: pyiron.log error.out
Access to the names of files is provided with
list()
>>> job.files.list() ['pyiron.log', 'error.out', 'INCAR']
Access to the contents of files is provided by indexing into this object, which returns a list of lines in the file
>>> job.files['error.out'] ["Oh no
“, “Something went wrong! “]
The
tail()
method prints the last lines of a file to stdout>>> job.files.tail('error.out', lines=1) Something went wrong!
For files that have valid python variable names can also be accessed by attribute notation
>>> job.files.INCAR File('INCAR')
- property files_to_compress
- property files_to_remove
- from_hdf(hdf=None, group_name='group')
Restore object from hdf5 format - The function has to be implemented by the derived classes - usually the GenericJob class
- Parameters:
hdf (ProjectHDFio) – Optional hdf5 file, otherwise self is used.
group_name (str) – Optional hdf5 group in the hdf5 file.
- get(name, default=None)
Internal wrapper function for __getitem__() - self[name]
- Parameters:
key (str, slice) – path to the data or key of the data object
default (any, optional) – return this if key cannot be found
- Returns:
data or data object
- Return type:
dict, list, float, int
- Raises:
ValueError – key cannot be found and default is not given
- get_from_table(path, name)
Get a specific value from a pandas.Dataframe
- Parameters:
path (str) – relative path to the data object
name (str) – parameter key
- Returns:
the value associated to the specific parameter key
- Return type:
dict, list, float, int
- get_job_id(job_specifier=None)
get the job_id for job named job_name in the local project path from database
- Parameters:
job_specifier (str, int) – name of the job or job ID
- Returns:
job ID of the job
- Return type:
int
- property id
Unique id to identify the job in the pyiron database - use self.job_id instead
- Returns:
job id
- Return type:
int
- inspect(job_specifier)
Inspect an existing pyiron object - most commonly a job - from the database
- Parameters:
job_specifier (str, int) – name of the job or job ID
- Returns:
Access to the HDF5 object - not a GenericJob object - use load() instead.
- Return type:
- is_compressed()
Check if the job is already compressed or not.
- Returns:
[True/False]
- Return type:
bool
- is_master_id(job_id)
Check if the job ID job_id is the master ID for any child job
- Parameters:
job_id (int) – job ID of the master job
- Returns:
[True/False]
- Return type:
bool
- is_self_archived()
Check if the HDF5 file of the Job is compressed as tar-archive
- Returns:
[True/False]
- Return type:
bool
- property job_id
Unique id to identify the job in the pyiron database
- Returns:
job id
- Return type:
int
- property job_info_str
Short string to describe the job by it is job_name and job ID - mainly used for logging
- Returns:
job info string
- Return type:
str
- property job_name
Get name of the job, which has to be unique within the project
- Returns:
job name
- Return type:
str
- list_childs()
List child jobs as JobPath objects - not loading the full GenericJob objects for each child
- Returns:
list of child jobs
- Return type:
list
- list_files()
List files inside the working directory
- Parameters:
extension (str) – filter by a specific extension
- Returns:
list of file names
- Return type:
list
- load(job_specifier, convert_to_object=True)
Load an existing pyiron object - most commonly a job - from the database
- Parameters:
job_specifier (str, int) – name of the job or job ID
convert_to_object (bool) – convert the object to an pyiron object or only access the HDF5 file - default=True accessing only the HDF5 file is about an order of magnitude faster, but only provides limited functionality. Compare the GenericJob object to JobCore object.
- Returns:
Either the full GenericJob object or just a reduced JobCore object
- Return type:
- property master_id
Get job id of the master job - a meta job which groups a series of jobs, which are executed either in parallel or in serial.
- Returns:
master id
- Return type:
int
- move_to(project)
Move the content of the job including the HDF5 file to a new location
- Parameters:
project (ProjectHDFio) – project to move the job to
- Returns:
JobCore object pointing to the new location.
- Return type:
- property name
Get name of the job, which has to be unique within the project
- Returns:
job name
- Return type:
str
- property parent_id
Get job id of the predecessor job - the job which was executed before the current one in the current job series
- Returns:
parent id
- Return type:
int
- property path
Absolute path of the HDF5 group starting from the system root - combination of the absolute system path plus the absolute path inside the HDF5 file starting from the root group.
- Returns:
absolute path
- Return type:
str
- property project
Project instance the jobs is located in
- Returns:
project the job is located in
- Return type:
- property project_hdf5
Get the ProjectHDFio instance which points to the HDF5 file the job is stored in
- Returns:
HDF5 project
- Return type:
- relocate_hdf5(h5_path=None)
Relocate the hdf file. This function is needed when the child job is spawned by a parent job (cf. pyiron_base.jobs.master.generic)
- remove(_protect_childs=True)
Remove the job - this removes the HDF5 file, all data stored in the HDF5 file an the corresponding database entry.
- Parameters:
_protect_childs (bool) – [True/False] by default child jobs can not be deleted, to maintain the consistency - default=True
- remove_child()
internal function to remove command that removes also child jobs. Do never use this command, since it will destroy the integrity of your project.
- rename(new_job_name)
Rename the job - by changing the job name
- Parameters:
new_job_name (str) – new job name
- reset_job_id(job_id=None)
The reset_job_id function has to be implemented by the derived classes - usually the GenericJob class
- Parameters:
job_id (int/ None)
- save()
The save function has to be implemented by the derived classes - usually the GenericJob class
- self_archive()
Compress HDF5 file of the job object to tar-archive
- self_unarchive()
Decompress HDF5 file of the job object from tar-archive
- show_hdf()
Iterating over the HDF5 datastructure and generating a human readable graph.
- property status
- Execution status of the job, can be one of the following [initialized, appended, created, submitted, running,
aborted, collect, suspended, refresh, busy, finished]
- Returns:
status
- Return type:
(str/pyiron_base.job.jobstatus.JobStatus)
- to_hdf(hdf=None, group_name='group')
Store object in hdf5 format - The function has to be implemented by the derived classes - usually the GenericJob class
- Parameters:
hdf (ProjectHDFio) – Optional hdf5 file, otherwise self is used.
group_name (str) – Optional hdf5 group in the hdf5 file.
- to_object(object_type=None, **qwargs)
Load the full pyiron object from an HDF5 file
- Parameters:
object_type – if the ‘TYPE’ node is not available in the HDF5 file a manual object type can be set - optional
**qwargs – optional parameters [‘job_name’, ‘project’] - to specify the location of the HDF5 path
- Returns:
pyiron object
- Return type:
- property working_directory
working directory of the job is executed in - outside the HDF5 file
- Returns:
working directory
- Return type:
str
- pyiron_base.jobs.job.core.recursive_load_from_hdf(project_hdf5: ProjectHDFio, item: str)
Load given item from HDF, but check also for DataContainer along the way.
If item exists as is in HDF, return it, otherwise break it up along every slash and try to load a
DataContainer
and then try to index with the remainder of the path, i.e.>>> recursive_load_from_hdf(hdf, 'my/path/to/value')
is equivalent to one of (in this order)
>>> hdf['my/path/to'].to_object()['value'] >>> hdf['my/path'].to_object()['to/value'] >>> hdf['my'].to_object()['path/to/value']
in case
>>> hdf['/my/path/to/value']
doesn’t exist.
- Parameters:
project_hdf5 (ProjectHDFio) – HDF file to access
item (str) – path to value, may contain /
- Returns:
whatever was found in the HDF file None: if nothing was found in the HDF file
- Return type:
object