Airflow Provider XLSX

Apache Airflow operators for converting XLSX files from/to Parquet, CSV and JSON.

System Requirements

  • Airflow Versions
    • 2.0.0 or newer

Installation

pip install airflow-provider-xlsx

API documentation

xlsx_provider.operators.from_xlsx_operator

class xlsx_provider.operators.from_xlsx_operator.FromXLSXOperator(source, target, worksheet=0, skip_rows=0, limit=None, drop_columns=None, add_columns=None, types=None, column_names=None, file_format='parquet', csv_delimiter=',', csv_header='lower', *args, **kwargs)[source]

Convert an XLSX/XLS file into Parquet or CSV file

Read an XLSX or XLS file and convert it into Parquet, CSV, JSON, JSON Lines(one line per record) file.

Parameters
  • source (str) – Source filename (XLSX or XLS, templated)

  • target (str) – Target filename (templated)

  • worksheet (str or int) – Worksheet title or number (zero-based, templated)

  • skip_rows (int) – Number of input lines to skip (default: 0, templated)

  • limit (int) – Row limit (default: None, templated)

  • drop_columns (list of str) – List of columns to be dropped

  • add_columns (list of str or dictionary of string key/value pair) – Columns to be added (dict or list column=value)

  • types (str or dictionary of string key/value pair) – force Parquet column types (dict or list column=’str’, ‘d’, ‘datetime64[ns]’)

  • column_names (list of str) – force columns names (list)

  • file_format (str) – Output file format (parquet, csv, json, jsonl)

  • csv_delimiter (str) – CSV delimiter (default: ‘,’)

  • csv_header (str) – Convert CSV output header case (‘lower’, ‘upper’, ‘skip’)

class FileFormat(value)

File format enumerator (parquet/csv/json/jsonl)

classmethod lookup(file_format)
execute(context)[source]

This is the main method to derive when creating an operator. Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

write(names, columns, datatypes)[source]

Write data to file

write_csv(names, columns, datatypes)[source]

Write data to CSV file

write_json(names, columns, datatypes)[source]

Write data to JSON file

write_jsonl(names, columns, datatypes)[source]

Write data to JSON Lines file

write_parquet(names, columns, datatypes)[source]

Write the results in parquet format

xlsx_provider.operators.operators.from_xlsx_query_operator

class xlsx_provider.operators.from_xlsx_query_operator.FromXLSXQueryOperator(source, target, worksheet=0, skip_rows=0, types=None, file_format='parquet', csv_delimiter=',', csv_header='lower', query=None, table_name='xls', use_first_row_as_header=False, *args, **kwargs)[source]

Execute an SQL query an XLSX/XLS file and export the result into a Parquet or CSV file

This operators loads an XLSX or XLS file into an in-memory SQLite database, executes a query on the db and stores the result into a Parquet, CSV, JSON, JSON Lines(one line per record) file. The output columns names and types are determinated by the SQL query output.

Parameters
  • source (str) – Source filename (XLSX or XLS, templated)

  • target (str) – Target filename (templated)

  • worksheet (str or int) – Worksheet title or number (zero-based, templated)

  • skip_rows (int) – Number of input lines to skip (default: 0, templated)

  • types (str or dictionary of string key/value pair) – force Parquet column types (dict or list column=’str’, ‘d’, ‘datetime64[ns]’)

  • file_format (str) – Output file format (parquet, csv, json, jsonl)

  • csv_delimiter (str) – CSV delimiter (default: ‘,’)

  • csv_header (str) – Convert CSV output header case (‘lower’, ‘upper’, ‘skip’)

  • query (str) – SQL query (templated)

  • table_name – Table name (default: ‘xls’, templated)

  • use_first_row_as_header (bool) – if true, use the first row as column names otherwhise use A, B, C, … as colum names

class FileFormat(value)

File format enumerator (parquet/csv/json/jsonl)

classmethod lookup(file_format)
execute(context)[source]

This is the main method to derive when creating an operator. Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

write(result)[source]

Write data to file

write_csv(result)[source]

Write data to CSV file

write_json(result)[source]

Write data to JSON file

write_jsonl(result)[source]

Write data to JSON Lines file

write_parquet(result)[source]

Write the results in parquet format

xlsx_provider.operators.operators.to_xlsx_operator

class xlsx_provider.operators.to_xlsx_operator.ToXLSXOperator(source, target, worksheet=0, skip_rows=0, csv_delimiter=',', *args, **kwargs)[source]

Convert Parquest, CSV, JSON, JSON Lines into XLSX

Read a Parquest, CSV, JSON, JSON Lines(one line per record) file and convert it into XLSX

Parameters
  • source (str) – source filename (type is detected by the extension, templated)

  • target (str) – target filename (templated)

  • csv_delimiter (str) – CSV delimiter (default: ‘,’)

  • skip_rows (int) – Number of input lines to skip (default: 0, templated)

class FileFormat(value)

File format enumerator (parquet/csv/json/jsonl)

classmethod lookup(file_format)
execute(context)[source]

This is the main method to derive when creating an operator. Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

xlsx_provider.commons

xlsx_provider.commons.DEFAULT_CSV_DELIMITER = ','

Default CSV delimiter

xlsx_provider.commons.DEFAULT_CSV_HEADER = 'lower'

Default CSV header case

xlsx_provider.commons.DEFAULT_FORMAT = 'parquet'

Default output format

xlsx_provider.commons.DEFAULT_TABLE_NAME = 'xls'

Default Query Operator table name

class xlsx_provider.commons.FileFormat(value)[source]

File format enumerator (parquet/csv/json/jsonl)

xlsx_provider.commons.INDEX_COLUMN_NAME = '_index'

Index colummn name

xlsx_provider.commons.VERSION = '0.0.7'

Plugin Version

xlsx_provider.commons.XLSX_EPOC = datetime.datetime(1900, 1, 1, 0, 0)

XLSX Epoc

xlsx_provider.commons.XLS_EPOC = datetime.datetime(1899, 12, 30, 0, 0)

XLS Epoc - see https://support.microsoft.com/en-us/help/214326/excel-incorrectly-assumes-that-the-year-1900-is-a-leap-year

xlsx_provider.commons.col_number_to_name(col_number)[source]

Convert a column number to name (e.g. 0 -> ‘_index’, 0 -> A, 1 -> B)

Parameters

col_number (int) – column number

xlsx_provider.commons.copy_cells(source, target)[source]

Copy cells from source worksheet to target

xlsx_provider.commons.get_column_names(sheet, skip_rows=0)[source]

Extract the column names from the first row of the worksheet

Parameters
  • sheet (Worksheet) – worksheet

  • skip_rows (int) – Number of input lines to skip

xlsx_provider.commons.print_sheet(sheet, fileobj=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='UTF-8'>)[source]

Print a sheet on standard output as CSV

xlsx_provider.commons.rmdiacritics(char)[source]

Return the base character without diacritics (eg. accents)

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