Python API

This is the API documentation for Hail, and provides detailed information on the Python programming interface.

Use import hail as hl to access this functionality.

Classes

hail.Table

Hail’s distributed implementation of a dataframe or SQL table.

hail.GroupedTable

Table grouped by row that can be aggregated into a new table.

hail.MatrixTable

Hail’s distributed implementation of a structured matrix.

hail.GroupedMatrixTable

Matrix table grouped by row or column that can be aggregated into a new matrix table.

Top-Level Functions

hail.init(sc=None, app_name='Hail', master=None, local='local[*]', log=None, quiet=False, append=False, min_block_size=0, branching_factor=50, tmp_dir='/tmp', default_reference='GRCh37', idempotent=False, global_seed=6348563392232659379, _optimizer_iterations=None, _backend=None)[source]

Initialize Hail and Spark.

Examples

Import and initialize Hail using GRCh38 as the default reference genome:

>>> import hail as hl
>>> hl.init(default_reference='GRCh38')  # doctest: +SKIP

Notes

Hail is not only a Python library; most of Hail is written in Java/Scala and runs together with Apache Spark in the Java Virtual Machine (JVM). In order to use Hail, a JVM needs to run as well. The init() function is used to initialize Hail and Spark.

This function also sets global configuration parameters used for the Hail session, like the default reference genome and log file location.

This function will be called automatically (with default parameters) if any Hail functionality requiring the backend (most of the libary!) is used. To initialize Hail explicitly with non-default arguments, be sure to do so directly after importing the module, as in the above example.

Note

If a pyspark.SparkContext is already running, then Hail must be initialized with it as an argument:

>>> hl.init(sc=sc)  # doctest: +SKIP

See also

stop()

Parameters
  • sc (pyspark.SparkContext, optional) – Spark context. By default, a Spark context will be created.

  • app_name (str) – Spark application name.

  • master (str, optional) – Spark master.

  • local (str) – Local-mode master, used if master is not defined here or in the Spark configuration.

  • log (str) – Local path for Hail log file. Does not currently support distributed file systems like Google Storage, S3, or HDFS.

  • quiet (bool) – Print fewer log messages.

  • append (bool) – Append to the end of the log file.

  • min_block_size (int) – Minimum file block size in MB.

  • branching_factor (int) – Branching factor for tree aggregation.

  • tmp_dir (str) – Temporary directory for Hail files. Must be a network-visible file path.

  • default_reference (str) – Default reference genome. Either 'GRCh37', 'GRCh38', or 'GRCm38'.

  • idempotent (bool) – If True, calling this function is a no-op if Hail has already been initialized.

  • global_seed (int, optional) – Global random seed.

hail.stop()[source]

Stop the currently running Hail session.

hail.spark_context()[source]

Returns the active Spark context.

Returns

pyspark.SparkContext

hail.default_reference()[source]

Returns the default reference genome 'GRCh37'.

Returns

ReferenceGenome

hail.get_reference(name) → hail.genetics.reference_genome.ReferenceGenome[source]

Returns the reference genome corresponding to name.

Notes

Hail’s built-in references are 'GRCh37', GRCh38', and 'GRCm38'. The contig names and lengths come from the GATK resource bundle: human_g1k_v37.dict and Homo_sapiens_assembly38.dict.

If name='default', the value of default_reference() is returned.

Parameters

name (str) – Name of a previously loaded reference genome or one of Hail’s built-in references: 'GRCh37', 'GRCh38', 'GRCm38', and 'default'.

Returns

ReferenceGenome

hail.set_global_seed(seed)[source]

Sets Hail’s global seed to seed.

Parameters

seed (int) – Integer used to seed Hail’s random number generator