bi_etl.components.csv_writer module

class bi_etl.components.csv_writer.CSVWriter(task: ETLTask | None, file_data: TextIO | str | Path, column_names: List[str], include_header: bool | None = True, append: bool = False, encoding: str | None = None, errors: str = 'strict', logical_name: str | None = None, **kwargs)[source]

Bases: ETLComponent

CSVWriter is similar to csv.DictWriter However, instead of a dict it uses our Row class as it’s return type. It uses csv.reader (in csv) to read the file.

Note the optional, but important, parameter delimiter.

Valid values for ``errors`` parameter:

Value

Meaning

'strict'

raise a ValueError error (or a subclass)

'ignore'

ignore the character and continue with the next

'replace'

replace with a suitable replacement character; Python will use the official U+FFFD REPLACEMENT CHARACTER for the builtin Unicode codecs on decoding and ‘?’ on encoding.

'surrogateescape'

replace with private code points U+DCnn.
Parameters:

  • task – The ETLTask instance to register in (if not None)

  • file_data – The file to parse as delimited. If str then it’s assumed to be a filename. Otherwise, it’s assumed to be a file object.

  • column_names – The names to use for columns

  • include_header – Should the first line of the output file be a header with the column names?

  • append – Should the file be appended to instead of overwritten (if it already exists)?

  • encoding – The encoding to use when opening the file, if it was a filename and not already opened. Default is None which becomes the Python default encoding

  • errors – The error handling to use when opening the file (if it was a filename and not already opened) Default is 'strict' See tabke above for valid errors values.

  • logical_name – The logical name of this source. Used for log messages.

  • kwargs – Optional Key word arguments. See below.

dialect

str or subclass of csv.Dialect Default “excel”. The dialect value to pass to csv

delimiter

str The delimiter used in the file. Default is comma ','.

doublequote

boolean Controls how instances of quotechar appearing inside a column should themselves be quoted. When True, the character is doubled. When False, the escapechar is used as a prefix to the quotechar. It defaults to True.

escapechar

str A one-character string used by the writer to escape the delimiter if quoting is set to QUOTE_NONE and the quotechar if doublequote is False. On reading, the escapechar removes any special meaning from the following character. It defaults to None, which disables escaping.

quotechar

str A one-character string used to quote columns containing special characters, such as the delimiter or quotechar, or which contain new-line characters. It defaults to ‘”’.

quoting

Controls when quotes should be generated by the writer and recognised by the reader. Can be either of the constants defined in this module. * QUOTE_NONE * QUOTE_MINIMAL Defaults to QUOTE_MINIMAL.

For more details see https://docs.python.org/3/library/csv.html#csv.QUOTE_ALL

skipinitialspace

boolean When True, whitespace immediately following the delimiter is ignored. The default is False.

strict

boolean When True, raise exception Error on bad CSV input. The default is False.

header_row

int The row to parse for headers

start_row

int The first row to parse for data

log_first_row

boolean Should we log progress on the first row read. Only applies if used as a source. (inherited from ETLComponent)

max_rows

int, optional The maximum number of rows to read. Only applies if Table is used as a source. (inherited from ETLComponent)

primary_key

list The name of the primary key column(s). Only impacts trace messages. Default=None. (inherited from ETLComponent)

progress_frequency

int How often (in seconds) to output progress messages. None for no progress messages. (inherited from ETLComponent)

progress_message

str The progress message to print. Default is "{logical_name} row # {row_number}". Note logical_name and row_number subs. (inherited from ETLComponent)

restkey

str Column name to catch long rows (extra values).

restval

str The value to put in columns that are in the column_names but not present in a given row (missing values).

large_field_support

boolean Enable support for csv columns bigger than 131,072 default limit.

DEFAULT_PROGRESS_FREQUENCY = 10

Default for number of seconds between progress messages when reading from this component. See ETLComponent.progress_frequency` to override.

DEFAULT_PROGRESS_MESSAGE = '{logical_name} current row # {row_number:,}'

Default progress message when reading from this component. See ETLComponent.progress_message` to override.

FULL_ITERATION_HEADER = 'full'

Constant value passed into ETLComponent.Row() to request all columns in the row. Deprecated: Please use ETLComponent.full_row_instance() to get a row with all columns.

Row(data: MutableMapping | Iterator | None = None, iteration_header: RowIterationHeader | str | None = None) → Row

Make a new empty row with this components structure.

__init__(task: ETLTask | None, file_data: TextIO | str | Path, column_names: List[str], include_header: bool | None = True, append: bool = False, encoding: str | None = None, errors: str = 'strict', logical_name: str | None = None, **kwargs)[source]
build_row(source_row: Row, source_excludes: frozenset | None = None, target_excludes: frozenset | None = None, stat_name: str = 'build_row_safe', parent_stats: Statistics | None = None) → Row

Use a source row to build a row with correct data types for this table.

Parameters:

  • source_row –

  • source_excludes –

  • target_excludes –

  • stat_name – Name of this step for the ETLTask statistics. Default = ‘build rows’

  • parent_stats –

Return type:

Row

build_row_dynamic_source(source_row: Row, source_excludes: frozenset | None = None, target_excludes: frozenset | None = None, stat_name: str = 'build_row_dynamic_source', parent_stats: Statistics | None = None) → Row

Use a source row to build a row with correct data types for this table. This version expects dynamically changing source rows, so it sanity checks all rows.

Parameters:

  • source_row –

  • source_excludes –

  • target_excludes –

  • stat_name – Name of this step for the ETLTask statistics. Default = ‘build rows’

  • parent_stats –

Return type:

Row

cache_commit()
cache_row(row: Row, allow_update: bool = False, allow_insert: bool = True)
property check_row_limit
clear_cache()

Clear all lookup caches. Sets to un-cached state (unknown state v.s. empty state which is what init_cache gives)

clear_statistics()
close(error: bool = False)[source]

Close the file

property column_names: List[str]

The list of column names for this component.

property column_names_set: set

A set containing the column names for this component. Usable to quickly check if the component contains a certain column.

commit()[source]
debug_log(state: bool = True)
define_lookup(lookup_name: str, lookup_keys: list, lookup_class: Type[Lookup] = None, lookup_class_kwargs: dict | None = None)

Define a new lookup.

Parameters:

  • lookup_name – Name for the lookup. Used to refer to it later.

  • lookup_keys – list of lookup key columns

  • lookup_class – Optional python class to use for the lookup. Defaults to value of default_lookup_class attribute.

  • lookup_class_kwargs – Optional dict of additional parameters to pass to lookup constructor. Defaults to empty dict.

property empty_iteration_header: RowIterationHeader
fill_cache(progress_frequency: float = 10, progress_message='{component} fill_cache current row # {row_number:,}', criteria_list: list = None, criteria_dict: dict = None, column_list: list = None, exclude_cols: frozenset = None, order_by: list = None, assume_lookup_complete: bool = None, allow_duplicates_in_src: bool = False, row_limit: int = None, parent_stats: Statistics = None)

Fill all lookup caches from the table.

Parameters:

  • progress_frequency – How often (in seconds) to output progress messages. Default 10. None for no progress messages.

  • progress_message – The progress message to print. Default is "{component} fill_cache current row # {row_number:,}". Note logical_name and row_number substitutions applied via format().

  • criteria_list – Each string value will be passed to sqlalchemy.sql.expression.Select.where(). https://goo.gl/JlY9us

  • criteria_dict – Dict keys should be columns, values are set using = or in

  • column_list – List of columns to include

  • exclude_cols (frozenset) – Optional. Columns to exclude when filling the cache

  • order_by – list of columns to sort by when filling the cache (helps range caches)

  • assume_lookup_complete – Should later lookup calls assume the cache is complete? If so, lookups will raise an Exception if a key combination is not found. Default to False if filtering criteria was used, otherwise defaults to True.

  • allow_duplicates_in_src – Should we quietly let the source provide multiple rows with the same key values? Default = False

  • row_limit – limit on number of rows to cache.

  • row_limit – limit on number of rows to cache.

  • parent_stats – Optional Statistics object to nest this steps statistics in. Default is to place statistics in the ETLTask level statistics.

fill_cache_from_source(source: ETLComponent, progress_frequency: float = 10, progress_message='{component} fill_cache current row # {row_number:,}', criteria_list: list = None, criteria_dict: dict = None, column_list: list = None, exclude_cols: frozenset = None, order_by: list = None, assume_lookup_complete: bool = None, allow_duplicates_in_src: bool = False, row_limit: int = None, parent_stats: Statistics = None)

Fill all lookup caches from the database table. Note that filtering criteria can be specified so that the resulting cache is not the entire current contents. See assume_lookup_complete for how the lookup will handle cache misses – note only database table backed components have the ability to fall back to querying the existing data on cache misses.

Parameters:

  • source – Source component to get rows from.

  • progress_frequency – How often (in seconds) to output progress messages. Default 10. None for no progress messages.

  • progress_message – The progress message to print. Default is "{component} fill_cache current row # {row_number:,}". Note logical_name and row_number substitutions applied via format().

  • criteria_list – Each string value will be passed to sqlalchemy.sql.expression.Select.where(). https://goo.gl/JlY9us

  • criteria_dict – Dict keys should be columns, values are set using = or in

  • column_list – List of columns to include

  • exclude_cols – Optional. Columns to exclude when filling the cache

  • order_by – list of columns to sort by when filling the cache (helps range caches)

  • assume_lookup_complete – Should later lookup calls assume the cache is complete? If so, lookups will raise an Exception if a key combination is not found. Default to False if filtering criteria was used, otherwise defaults to True.

  • allow_duplicates_in_src – Should we quietly let the source provide multiple rows with the same key values? Default = False

  • row_limit – limit on number of rows to cache.

  • parent_stats – Optional Statistics object to nest this steps statistics in. Default is to place statistics in the ETLTask level statistics.

property full_iteration_header: RowIterationHeader
full_row_instance(data: MutableMapping | Iterator | None = None) → Row

Build a full row (all columns) using the source data.

Note: If data is passed here, it uses bi_etl.components.row.row.Row.update() to map the data into the columns. That is nicely automatic, but slower since it has to try various ways to read the data container object.

Consider using the appropriate one of the more specific update methods based on the source data container.

generate_iteration_header(logical_name: str | None = None, columns_in_order: list | None = None, result_primary_key: list | None = None) → RowIterationHeader
get_by_lookup(lookup_name: str, source_row: Row, stats_id: str = 'get_by_lookup', parent_stats: Statistics | None = None, fallback_to_db: bool = False) → Row

Get by an alternate key. Returns a Row

Throws:

NoResultFound

get_column_name(column: str)
get_lookup(lookup_name: str) → Lookup
get_lookup_keys(lookup_name: str) → list
get_lookup_tuple(lookup_name: str, row: Row) → tuple
get_qualified_lookup_name(base_lookup_name: str) → str
get_stats_entry(stats_id: str, parent_stats: Statistics | None = None, print_start_stop_times: bool | None = None)
get_unique_stats_entry(stats_id: str, parent_stats: Statistics | None = None, print_start_stop_times: bool | None = None)
get_writer() → writer[source]

Build or get the csv.DictWriter object.

init_cache()

Initialize all lookup caches as empty.

insert(source: Row | list, additional_insert_values: dict = None, parent_stats: Statistics = None, **kwargs)[source]

Insert a row or list of rows in the table.

Parameters:

  • source (Row or list thereof) – Row(s) to insert

  • additional_insert_values (dict) – Additional values to set on each row.

  • parent_stats (bi_etl.statistics.Statistics) – Optional Statistics object to nest this steps statistics in. Default is to place statistics in the ETLTask level statistics.

insert_row(source_row: Row, additional_insert_values: dict = None, stat_name: str = 'insert', parent_stats: Statistics = None) → Row[source]

Inserts a row into the target file.

Parameters:

  • source_row – The row with values to insert

  • additional_insert_values – Values to add / override in the row before inserting.

  • stat_name – Name of this step for the ETLTask statistics.

  • parent_stats – Optional Statistics object to nest this steps statistics in. Default is to place statistics in the ETLTask level statistics.

Return type:

new_row

property is_closed
iter_result(result_list: object, columns_in_order: list | None = None, criteria_dict: dict | None = None, logical_name: str | None = None, progress_frequency: int | None = None, stats_id: str | None = None, parent_stats: Statistics | None = None) → Iterable[Row]
Yields:

row (Row) – next row

static kwattrs_order() → Dict[str, int]

Certain values need to be set before others in order to work correctly. This method should return a dict mapping those key values = arg name to a value less than the default of 9999, which will be used for any arg not explicitly listed here.

log_progress(row: Row, stats: Statistics)
logging_level_reported = False

Has the logging level of this component been reported (logged) yet? Stored at class level so that it can be logged only once.

property lookups
property primary_key: list

The name of the primary key column(s). Only impacts trace messages. Default=Empty list.

property primary_key_tuple: tuple

The name of the primary key column(s) in a tuple. Used when a hashable PK definition is needed.

property progress_frequency: int

How often (in seconds) to output progress messages. None for no progress messages.

property row_name: str
property rows_read: int

int The number of rows read and returned.

sanity_check_example_row(example_source_row, source_excludes=None, target_excludes=None, ignore_source_not_in_target=None, ignore_target_not_in_source=None)
sanity_check_source_mapping(source_definition: ETLComponent, source_name: str = None, source_excludes: frozenset = None, target_excludes: frozenset = None, ignore_source_not_in_target: bool = None, ignore_target_not_in_source: bool = None, raise_on_source_not_in_target: bool = None, raise_on_target_not_in_source: bool = None)
set_kwattrs(**kwargs)
property statistics
property trace_data: bool

boolean Should a debug message be printed with the parsed contents (as columns) of each row.

uncache_row(row)
uncache_where(key_names, key_values_dict)
where(criteria_list: list | None = None, criteria_dict: dict | None = None, order_by: list | None = None, column_list: List[Column | str] = None, exclude_cols: FrozenSet[Column | str] = None, use_cache_as_source: bool | None = None, progress_frequency: int | None = None, stats_id: str | None = None, parent_stats: Statistics | None = None) → Iterable[Row]
Parameters:
Return type:

rows

write_header()[source]

Write the header row.