transcriptic.jupyter

Project

class transcriptic.jupyter.Project(project_id, attributes=None, connection=None)[source]

A Project object contains helper methods for managing your runs. You can view the runs associated with this project as well as submit runs to the project.

Example Usage:

myProject = Project("My Project")
projectRuns = myProject.runs()
myRunId = projectRuns.query("title == 'myRun'").id.item()
myRun = Run(myRunId)
id

Project id

Type

str

name

Project name

Type

str

attributes

Master attributes dictionary

Type

dict

connection

Transcriptic Connection object associated with this specific object

Type

transcriptic.config.Connection

Project.runs()

Project.runs(use_cache=True)[source]

Get the list of runs belonging to the project

Parameters

use_cache (Boolean) – Determines whether the cached list of runs is returned

Returns

Returns a DataFrame of runs, with the id and title as columns

Return type

DataFrame

Project.submit()

Project.submit(protocol, title, test_mode=False)[source]

Submit a run to this project

Parameters
  • protocol (dict) – Autoprotocol Protocol in dictionary form, can be generated using Protocol.as_dict()

  • title (Optional[str]) – Title of run. Run-id will automatically be used as name if field is not provided

  • test_mode (Optional[boolean]) – Determines if run will be submitted will be treated as a test run or a run that is meant for execution

Returns

Returns a run object if run is successfully submitted

Return type

Run

Run

class transcriptic.jupyter.Run(run_id, attributes=None, connection=None, timeout=30.0)[source]

Bases: transcriptic.jupyter.common._BaseObject

A Run object contains helper methods for accessing Run-related information such as Instructions, Datasets and monitoring data.

Example Usage:

myRun = Run('r12345')
myRun.data
myRun.instructions
myRun.containers
myRun.Instructions[0]
id

Run id

Type

str

name

Run name

Type

str

data

DataFrame summary of all datasets which belong to this run

Type

DataFrame

instructions

DataFrame summary of all Instruction objects which belong to this run

Type

DataFrame

containers

DataFrame summary of all Container objects which belong to this run

Type

DataFrame

project_id

Project id which run belongs to

Type

str

attributes

Master attributes dictionary

Type

dict

connection

Transcriptic Connection object associated with this specific object

Type

transcriptic.config.Connection

property Containers

Helper for allowing direct access of Container objects

Returns

Returns a Series of Container objects

Return type

Series

property Datasets

Helper for allowing direct access of Dataset objects

Returns

Returns a Series of Dataset objects

Return type

Series

property Instructions

Helper for allowing direct access of Instruction objects

Returns

Returns a Series of Instruction objects

Return type

Series

property containers
property data

Find and generate a list of Dataset objects which are associated with this run

Returns

Returns a DataFrame of datasets, with Name, Dataset and DataType as columns

Return type

DataFrame

property data_ids

Find and generate a list of datarefs and data_ids associated with this run.

Returns

Returns a DataFrame of data ids, with datarefs and data_ids as columns

Return type

DataFrame

property instructions

Dataset

class transcriptic.jupyter.Dataset(data_id, attributes=None, connection=None)[source]

Bases: transcriptic.jupyter.common._BaseObject

A Dataset object contains helper methods for accessing data related information

id

Dataset id

Type

str

name

Dataset name

Type

str

data
DataFrame of well-indexed data values. Note that associated metadata is found in

attributes dictionary

Type

DataFrame

data_objects[source]

List of DataObject type

Type

list(DataObject)

attachments

names and data of all attachments for the dataset

Type

dict(str, bytes)

container

Container object that was used for this dataset

Type

Container

operation

Operation used for generating the dataset

Type

str

data_type

Data type of this dataset

Type

str

attributes

Master attributes dictionary

Type

dict

connection

Transcriptic Connection object associated with this specific object

Type

transcriptic.config.Connection

property attachments
cross_ref_aliquots()[source]
property data
data_objects()[source]
property raw_data

Instruction

class transcriptic.jupyter.Instruction(attributes, connection=None)[source]

Bases: object

An Instruction object contains information related to the current instruction such as the start, completed time as well as warps associated with the instruction.

Note that Instruction objects are usually created as part of a run and not created explicitly.

Additionally, if diagnostic information is available, one can click on the Show Diagnostics Data button to view relevant diagnostic information.

Example Usage:

myRun = Run('r12345')
myRun.instructions

# Access instruction object
myRun.Instructions[1]
myRun.Instructions[1].warps
id

Instruction id

Type

str

name

Instruction name

Type

str

warps

DataFrame of warps in the instruction

Type

DataFrame

started_at

Time where instruction begun

Type

str

completed_at

Time where instruction ended

Type

str

device_id

Id of device which instruction was executed on

Type

str

attributes

Master attributes dictionary

Type

dict

connection

Transcriptic Connection object associated with this specific object

Type

transcriptic.config.Connection

monitoring(data_type='pressure', grouping=None)[source]

View monitoring data of a given instruction

Parameters
  • data_type (Optional[str]) – Monitoring data type, defaults to ‘pressure’

  • grouping (Optional[str]) – Determines whether the values will be grouped, defaults to None. E.g. “5:ms”

Returns

Returns a pandas dataframe of the monitoring data if present. Returns an empty dataframe if no data can be found due to errors.

Return type

DataFrame

property warp_events

Warp events include discrete monitoring events such as liquid sensing events for a particular instruction.

property warps

Container

class transcriptic.jupyter.Container(container_id, attributes=None, connection=None)[source]

Bases: transcriptic.jupyter.common._BaseObject

A Container object represents a container from the Transcriptic LIMS and contains relevant information on the container type as well as the aliquots present in the container.

Example Usage:
my_container = container("ct186apgz6a374")
my_container.well_map
my_container.aliquots

my_container.container_type.col_count
my_container.container_type.robotize("B1")
my_container.container_type.humanize(12)
name

Name of container

Type

str

well_map

Well mapping with well indices for keys and well names as values

Type

dict

aliquots

DataFrame of aliquots present in the container. DataFrame index now corresponds to the Well Index.

Type

DataFrame

container_type

Autoprotocol ContainerType object with many useful container type information and functions.

Type

autoprotocol.container_type.ContainerType

cover

Cover type of container

Type

str

storage

Storage condition of container

Example Usage:

my_container = container("ct186apgz6a374")

my_container.well_map

my_container.container_type.col_count
my_container.container_type.robotize("B1")
my_container.container_type.humanize(12)
Type

str

__repr__()[source]

Return a string representation of a Container using the specified name. (ex. Container(‘my_plate’))

property aliquots

Return a DataFrame of aliquots in the container, along with aliquot name, volume, and properties. Row index for the DataFrame corresponds to the well index of the aliquot.