pyiron.base.job.path module¶

class pyiron.base.job.path.JobPath(db, job_id=None, db_entry=None, user=None)[source]¶

Bases: pyiron.base.job.path.JobPathBase

The JobPath class is derived from the JobCore and is used as a lean version of the GenericJob class. Instead of loading the full pyiron object the JobPath class only provides access to the HDF5 file, which should be enough for most analysis.

Parameters

db (DatabaseAccess) – database object
job_id (int) – Job ID - optional, but either a job ID or a database entry db_entry has to be provided.
db_entry (dict) – database entry {“job”:, “subjob”:, “projectpath”:, “project”:, “hamilton”:, “hamversion”:, “status”:} and optional entries are {“id”:, “masterid”:, “parentid”:}
user (str) – current unix/linux/windows user who is running pyiron

.. 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.

.. attribute:: is_root: boolean if the HDF5 object is located at the root level of the HDF5 file

.. attribute:: is_open: boolean if the HDF5 file is currently opened - if an active file handler exists

.. attribute:: is_empty: boolean if the HDF5 file is empty

.. attribute:: base_name: name of the HDF5 file but without any file extension

.. attribute:: file_path: directory where the HDF5 file is located

.. attribute:: h5_path: path inside the HDF5 file - also stored as absolute path

class pyiron.base.job.path.JobPathBase(job_path)[source]¶

Bases: pyiron.base.job.core.JobCore

The JobPath class is derived from the JobCore and is used as a lean version of the GenericJob class. Instead of loading the full pyiron object the JobPath class only provides access to the HDF5 file, which should be enough for most analysis.

Parameters

db (DatabaseAccess) – database object
job_id (int) – Job ID - optional, but either a job ID or a database entry db_entry has to be provided.
db_entry (dict) – database entry {“job”:, “subjob”:, “projectpath”:, “project”:, “hamilton”:, “hamversion”:, “status”:} and optional entries are {“id”:, “masterid”:, “parentid”:}
user (str) – current unix/linux/windows user who is running pyiron

.. 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.

.. attribute:: is_root: boolean if the HDF5 object is located at the root level of the HDF5 file

.. attribute:: is_open: boolean if the HDF5 file is currently opened - if an active file handler exists

.. attribute:: is_empty: boolean if the HDF5 file is empty

.. attribute:: base_name: name of the HDF5 file but without any file extension

.. attribute:: file_path: directory where the HDF5 file is located

.. attribute:: h5_path: path inside the HDF5 file - also stored as absolute path

property base_name¶

Name of the HDF5 file - but without the file extension .h5

Returns: file name without the file extension
Return type: str

close()[source]¶: Close the current HDF5 path and return to the path before the last open

create_group(name)[source]¶

Create an HDF5 group - similar to a folder in the filesystem - the HDF5 groups allow the users to structure their data.

Parameters: name (str) – name of the HDF5 group
Returns: FileHDFio object pointing to the new group
Return type: FileHDFio

property file_path¶

Path where the HDF5 file is located - posixpath.dirname()

Returns: HDF5 file location
Return type: str

groups()[source]¶

Filter HDF5 file by groups

Returns: an HDF5 file which is filtered by groups
Return type: FileHDFio

property h5_path¶

Get the path in the HDF5 file starting from the root group - meaning this path starts with ‘/’

Returns: HDF5 path
Return type: str

property is_empty¶

Check if the HDF5 file is empty

Returns: [True/False]
Return type: bool

property is_root¶

Check if the current h5_path is pointing to the HDF5 root group.

Returns: [True/False]
Return type: bool

items()[source]¶

List all keys and values as items of all groups and nodes of the HDF5 file

Returns: list of sets (key, value)
Return type: list

keys()[source]¶

List all groups and nodes of the HDF5 file - where groups are equivalent to directories and nodes to files.

Returns: all groups and nodes
Return type: list

list_dirs()[source]¶

equivalent to os.listdirs (consider groups as equivalent to dirs)

Returns: list of groups in pytables for the path self.h5_path
Return type: (list)

listdirs()[source]¶

equivalent to os.listdirs (consider groups as equivalent to dirs)

Returns: list of groups in pytables for the path self.h5_path
Return type: (list)

nodes()[source]¶

Filter HDF5 file by nodes

Returns: an HDF5 file which is filtered by nodes
Return type: FileHDFio

open(h5_rel_path)[source]¶

Create an HDF5 group and enter this specific group. If the group exists in the HDF5 path only the h5_path is set correspondingly otherwise the group is created first.

Parameters: h5_rel_path (str) – relative path from the current HDF5 path - h5_path - to the new group
Returns: FileHDFio object pointing to the new group
Return type: FileHDFio

put(key, value)[source]¶

Store data inside the HDF5 file

Parameters

key (str) – key to store the data
value (pandas.DataFrame, pandas.Series, dict, list, float, int) – basically any kind of data is supported

remove_file()[source]¶: Remove the HDF5 file with all the related content

values()[source]¶

List all values for all groups and nodes of the HDF5 file

Returns: list of all values
Return type: list