NanoEventsFactory

class coffea.nanoevents.NanoEventsFactory(schema, mapping, partition_key, cache=None, is_dask=False)

Bases: object

A factory class to build NanoEvents objects

Methods Summary

events()	Build events
from_parquet(file[, treepath, entry_start, ...])	Quickly build NanoEvents from a parquet file
from_preloaded(array_source[, entry_start, ...])	Quickly build NanoEvents from a pre-loaded array source
from_root(file[, treepath, entry_start, ...])	Quickly build NanoEvents from a root file

Methods Documentation

events()

Build events

classmethod from_parquet(file, treepath=uproot._util.unset, entry_start=None, entry_stop=None, runtime_cache=None, persistent_cache=None, schemaclass=<class 'coffea.nanoevents.schemas.nanoaod.NanoAODSchema'>, metadata=None, parquet_options={}, skyhook_options={}, access_log=None, delayed=True)

Quickly build NanoEvents from a parquet file

Parameters:

• file (str, pathlib.Path, pyarrow.NativeFile, or python file-like) – The filename or already opened file using e.g. uproot.open()

• treepath (str, optional) – Name of the tree to read in the file

• entry_start (int, optional) – Start at this entry offset in the tree (default 0)

• entry_stop (int, optional) – Stop at this entry offset in the tree (default end of tree)

• runtime_cache (dict, optional) – A dict-like interface to a cache object. This cache is expected to last the duration of the program only, and will be used to hold references to materialized awkward arrays, etc.

• persistent_cache (dict, optional) – A dict-like interface to a cache object. Only bare numpy arrays will be placed in this cache, using globally-unique keys.

• schemaclass (BaseSchema) – A schema class deriving from BaseSchema and implementing the desired view of the file

• metadata (dict, optional) – Arbitrary metadata to add to the base.NanoEvents object

• parquet_options (dict, optional) – Any options to pass to pyarrow.parquet.ParquetFile

• access_log (list, optional) – Pass a list instance to record which branches were lazily accessed by this instance

• delayed – Nanoevents will use dask as a backend to construct a delayed task graph representing your analysis.

classmethod from_preloaded(array_source, entry_start=None, entry_stop=None, runtime_cache=None, persistent_cache=None, schemaclass=<class 'coffea.nanoevents.schemas.nanoaod.NanoAODSchema'>, metadata=None, access_log=None)

Quickly build NanoEvents from a pre-loaded array source

Parameters:

• array_source (Mapping[str, awkward.Array]) – A mapping of names to awkward arrays, it must have a metadata attribute with uuid, num_rows, and path sub-items.

• entry_start (int, optional) – Start at this entry offset in the tree (default 0)

• entry_stop (int, optional) – Stop at this entry offset in the tree (default end of tree)

• runtime_cache (dict, optional) – A dict-like interface to a cache object. This cache is expected to last the duration of the program only, and will be used to hold references to materialized awkward arrays, etc.

• persistent_cache (dict, optional) – A dict-like interface to a cache object. Only bare numpy arrays will be placed in this cache, using globally-unique keys.

• schemaclass (BaseSchema) – A schema class deriving from BaseSchema and implementing the desired view of the file

• metadata (dict, optional) – Arbitrary metadata to add to the base.NanoEvents object

• access_log (list, optional) – Pass a list instance to record which branches were lazily accessed by this instance

classmethod from_root(file, treepath=uproot._util.unset, entry_start=None, entry_stop=None, steps_per_file=uproot._util.unset, runtime_cache=None, persistent_cache=None, schemaclass=<class 'coffea.nanoevents.schemas.nanoaod.NanoAODSchema'>, metadata=None, uproot_options={}, access_log=None, iteritems_options={}, use_ak_forth=True, delayed=True, known_base_form=None, decompression_executor=None, interpretation_executor=None)

Quickly build NanoEvents from a root file

Parameters:

• file (a string or dict input to uproot.open() or uproot.dask() or a uproot.reading.ReadOnlyDirectory) – The filename or dict of filenames including the treepath (as it would be passed directly to uproot.open() or uproot.dask()) already opened file using e.g. uproot.open().

• treepath (str, optional) – Name of the tree to read in the file. Used only if file is a uproot.reading.ReadOnlyDirectory.

• entry_start (int, optional (eager mode only)) – Start at this entry offset in the tree (default 0)

• entry_stop (int, optional (eager mode only)) – Stop at this entry offset in the tree (default end of tree)

• steps_per_file (int, optional) – Partition files into this many steps (previously “chunks”)

• runtime_cache (dict, optional) – A dict-like interface to a cache object. This cache is expected to last the duration of the program only, and will be used to hold references to materialized awkward arrays, etc.

• persistent_cache (dict, optional) – A dict-like interface to a cache object. Only bare numpy arrays will be placed in this cache, using globally-unique keys.

• schemaclass (BaseSchema) – A schema class deriving from BaseSchema and implementing the desired view of the file

• metadata (dict, optional) – Arbitrary metadata to add to the base.NanoEvents object

• uproot_options (dict, optional) – Any options to pass to uproot.open or uproot.dask

• access_log (list, optional) – Pass a list instance to record which branches were lazily accessed by this instance

• use_ak_forth – Toggle using awkward_forth to interpret branches in root file.

• delayed – Nanoevents will use dask as a backend to construct a delayed task graph representing your analysis.

• known_base_form – If the base form of the input file is known ahead of time we can skip opening a single file and parsing metadata.

• method) (interpretation_executor (None or Executor with a submit) – see: https://github.com/scikit-hep/uproot5/blob/main/src/uproot/_dask.py#L109

• method) – see: https://github.com/scikit-hep/uproot5/blob/main/src/uproot/_dask.py#L113