`flow.record`¶

Submodules¶

Package Contents¶

Classes¶

`FieldType`
`GroupedRecord`	GroupedRecord acts like a normal Record, but can contain multiple records.
`Record`
`RecordDescriptor`	Record Descriptor class for defining a Record type and its fields.
`RecordField`
`JsonRecordPacker`

Functions¶

`DynamicDescriptor`
`RecordAdapter`
`RecordReader`
`RecordWriter`
`extend_record`	Extend `record` with fields and values from `other_records`.
`ignore_fields_for_comparison`	Context manager to temporarily ignore fields for comparison.
`iter_timestamped_records`	Yields timestamped annotated records for each datetime fieldtype in record.
`open_path`	Open `path` using `mode` and returns a file object.
`open_path_or_stream`
`open_stream`
`set_ignored_fields_for_comparison`	Can be used to update the IGNORE_FIELDS_FOR_COMPARISON from outside the flow.record package scope
`stream`

Attributes¶

`IGNORE_FIELDS_FOR_COMPARISON`
`RECORD_VERSION`
`RECORDSTREAM_MAGIC`
`dynamic_fieldtype`

flow.record.IGNORE_FIELDS_FOR_COMPARISON¶

flow.record.RECORD_VERSION = 1¶

flow.record.RECORDSTREAM_MAGIC = b'RECORDSTREAM\n'¶

flow.record.DynamicDescriptor(name, fields)¶

class flow.record.FieldType¶

classmethod default()¶: Return the default value for the field in the Record template.

class flow.record.GroupedRecord(name, records)¶

Bases: Record

GroupedRecord acts like a normal Record, but can contain multiple records.

See it as a flat Record view on top of multiple Records. If two Records have the same fieldname, the first one will prevail.

name¶

records = []¶

descriptors = []¶

flat_fields = []¶

get_record_by_type(type_name)¶

Get record in a GroupedRecord by type_name.

Parameters:: type_name (str) – The record type name (for example wq/meta).
Returns:: None or the record

__repr__()¶

__setattr__(attr, val)¶: Enforce setting the fields to their respective types.

__getattr__(attr)¶

class flow.record.Record¶

__slots__ = ()¶

__eq__(other)¶

__setattr__(k, v)¶: Enforce setting the fields to their respective types.

__hash__() → int¶

__repr__()¶

flow.record.RecordAdapter(url: str | None = None, out: bool = False, selector: str | None = None, clobber: bool = True, fileobj: BinaryIO | None = None, **kwargs) → flow.record.adapter.AbstractWriter | flow.record.adapter.AbstractReader¶

class flow.record.RecordDescriptor(name: str, fields: Sequence[tuple[str, str]] | None = None)¶

Record Descriptor class for defining a Record type and its fields.

name: str = None¶

recordType: type = None¶

static get_required_fields() → Mapping[str, RecordField]¶

Get required fields mapping. eg:

{: “_source”: RecordField(“_source”, “string”), “_classification”: RecordField(“_classification”, “datetime”), “_generated”: RecordField(“_generated”, “datetime”), “_version”: RecordField(“_version”, “vaeint”),

}

Returns:: Mapping of required fields

property fields: Mapping[str, RecordField]¶

Get fields mapping (without required fields). eg:

{: “foo”: RecordField(“foo”, “string”), “bar”: RecordField(“bar”, “varint”),

}

Returns:: Mapping of Record fields

get_all_fields() → Mapping[str, RecordField]¶

Get all fields including required meta fields. eg:

{: “ts”: RecordField(“ts”, “datetime”), “foo”: RecordField(“foo”, “string”), “bar”: RecordField(“bar”, “varint”), “_source”: RecordField(“_source”, “string”), “_classification”: RecordField(“_classification”, “datetime”), “_generated”: RecordField(“_generated”, “datetime”), “_version”: RecordField(“_version”, “varint”),

}

Returns:: Mapping of all Record fields

getfields(typename: str) → RecordFieldSet¶

Get fields of a given type.

Parameters:: typename – The typename of the fields to return. eg: “string” or “datetime”
Returns:: RecordFieldSet of fields with the given typename

__call__(*args, **kwargs) → Record¶: Create a new Record initialized with args and kwargs.

init_from_dict(rdict: dict[str, Any], raise_unknown=False) → Record¶

Create a new Record initialized with key, value pairs from rdict.

If raise_unknown=True then fields on rdict that are unknown to this RecordDescriptor will raise a TypeError exception due to initializing with unknown keyword arguments. (default: False)

Returns:: Record with data from rdict

init_from_record(record: Record, raise_unknown=False) → Record¶

Create a new Record initialized with data from another record.

If raise_unknown=True then fields on record that are unknown to this RecordDescriptor will raise a TypeError exception due to initializing with unknown keyword arguments. (default: False)

Returns:: Record with data from record

extend(fields: Sequence[tuple[str, str]]) → RecordDescriptor¶

Returns a new RecordDescriptor with the extended fields

Returns:: RecordDescriptor with extended fields

get_field_tuples() → tuple[tuple[str, str]]¶

Returns a tuple containing the (typename, name) tuples, eg:

((‘boolean’, ‘foo’), (‘string’, ‘bar’))

Returns:: Tuple of (typename, name) tuples

static calc_descriptor_hash(name, fields: Sequence[tuple[str, str]]) → int¶

Calculate and return the (cached) descriptor hash as a 32 bit integer.

The descriptor hash is the first 4 bytes of the sha256sum of the descriptor name and field names and types.

property descriptor_hash: int¶: Returns the (cached) descriptor hash

property identifier: tuple[str, int]¶: Returns a tuple containing the descriptor name and hash

__hash__() → int¶

__eq__(other: RecordDescriptor) → bool¶

__repr__() → str¶

definition(reserved: bool = True) → str¶

Return the RecordDescriptor as Python definition string.

If reserved is True it will also return the reserved fields.

Returns:: Descriptor definition string

base(**kwargs_sink)¶

exception flow.record.RecordDescriptorError¶

Bases: Exception

Raised when there is an error constructing a record descriptor

class flow.record.RecordField(name: str, typename: str)¶

name = None¶

typename = None¶

type = None¶

__repr__()¶

flow.record.RecordReader(url: str | None = None, selector: str | None = None, fileobj: BinaryIO | None = None, **kwargs) → flow.record.adapter.AbstractReader¶

flow.record.RecordWriter(url: str | None = None, clobber: bool = True, **kwargs) → flow.record.adapter.AbstractWriter¶

flow.record.dynamic_fieldtype¶

flow.record.extend_record(record: Record, other_records: list[Record], replace: bool = False, name: str | None = None) → Record¶

Extend record with fields and values from other_records.

Duplicate fields are ignored in other_records unless replace=True.

Parameters:

record – Initial Record to extend.
other_records – List of Records to use for extending/replacing.
replace – if True, it will replace existing fields and values in record from fields and values from other_records. Last record always wins.
name – rename the RecordDescriptor name to name. Otherwise, use name from initial record.

Returns:

Extended Record

flow.record.ignore_fields_for_comparison(ignored_fields: Iterable[str])¶: Context manager to temporarily ignore fields for comparison.

flow.record.iter_timestamped_records(record: Record) → Iterator[Record]¶

Yields timestamped annotated records for each datetime fieldtype in record. If record does not have any datetime fields the original record is returned.

Parameters:: record – Record to add timestamp fields for.
Yields:: Record annotated with ts and ts_description fields for each datetime fieldtype.

flow.record.open_path(path: str, mode: str, clobber: bool = True) → IO¶

Open path using mode and returns a file object.

It handles special cases if path is meant to be stdin or stdout. And also supports compression based on extension or file header of stream.