I have a dictionary of values that I would like to write to GCS as a valid .CSV file using the Python SDK. I can write the dictionary out as newline separated text file, but I can't seem to find an example converting the dictionary to a valid .CSV. Can anybody suggest the best way to generate csv's within a dataflow pipeline? This answers to this question address Reading from CSV files, but don't really address writing to CSV files. I recognize that CSV files are just text files with rules, but I'm still struggling to convert the dictionary of data to a CSV that can be written using WriteToText.
Here is a simple example dictionary that I would like to turn into a CSV:
test_input = [{'label': 1, 'text': 'Here is a sentence'},
{'label': 2, 'text': 'Another sentence goes here'}]
test_input | beam.io.WriteToText(path_to_gcs)
The above would result in a text file that had each dictionary on a newline. Is there any functionality within Apache Beam that I can take advantage of (similar to csv.DictWriter)?
Generally you will want to write a function that can convert your original dict data elements into a csv-formatted string representation.
That function can be written as a DoFn that you can apply to your Beam PCollection of data, which would convert each collection element into the desired format; you can do this by applying the DoFn to your PCollection via ParDo. You can also wrap this DoFn in a more user-friendly PTransform.
You can learn more about this process in the Beam Programming Guide
Here is a simple, translatable non-Beam example:
# Our example list of dictionary elements
test_input = [{'label': 1, 'text': 'Here is a sentence'},
{'label': 2, 'text': 'Another sentence goes here'}]
def convert_my_dict_to_csv_record(input_dict):
""" Turns dictionary values into a comma-separated value formatted string """
return ','.join(map(str, input_dict.values()))
# Our converted list of elements
converted_test_input = [convert_my_dict_to_csv_record(element) for element in test_input]
The converted_test_input will look like the following:
['Here is a sentence,1', 'Another sentence goes here,2']
Beam DictToCSV DoFn and PTransform example using DictWriter
from csv import DictWriter
from csv import excel
from cStringIO import StringIO
...
def _dict_to_csv(element, column_order, missing_val='', discard_extras=True, dialect=excel):
""" Additional properties for delimiters, escape chars, etc via an instance of csv.Dialect
Note: This implementation does not support unicode
"""
buf = StringIO()
writer = DictWriter(buf,
fieldnames=column_order,
restval=missing_val,
extrasaction=('ignore' if discard_extras else 'raise'),
dialect=dialect)
writer.writerow(element)
return buf.getvalue().rstrip(dialect.lineterminator)
class _DictToCSVFn(DoFn):
""" Converts a Dictionary to a CSV-formatted String
column_order: A tuple or list specifying the name of fields to be formatted as csv, in order
missing_val: The value to be written when a named field from `column_order` is not found in the input element
discard_extras: (bool) Behavior when additional fields are found in the dictionary input element
dialect: Delimiters, escape-characters, etc can be controlled by providing an instance of csv.Dialect
"""
def __init__(self, column_order, missing_val='', discard_extras=True, dialect=excel):
self._column_order = column_order
self._missing_val = missing_val
self._discard_extras = discard_extras
self._dialect = dialect
def process(self, element, *args, **kwargs):
result = _dict_to_csv(element,
column_order=self._column_order,
missing_val=self._missing_val,
discard_extras=self._discard_extras,
dialect=self._dialect)
return [result,]
class DictToCSV(PTransform):
""" Transforms a PCollection of Dictionaries to a PCollection of CSV-formatted Strings
column_order: A tuple or list specifying the name of fields to be formatted as csv, in order
missing_val: The value to be written when a named field from `column_order` is not found in an input element
discard_extras: (bool) Behavior when additional fields are found in the dictionary input element
dialect: Delimiters, escape-characters, etc can be controlled by providing an instance of csv.Dialect
"""
def __init__(self, column_order, missing_val='', discard_extras=True, dialect=excel):
self._column_order = column_order
self._missing_val = missing_val
self._discard_extras = discard_extras
self._dialect = dialect
def expand(self, pcoll):
return pcoll | ParDo(_DictToCSVFn(column_order=self._column_order,
missing_val=self._missing_val,
discard_extras=self._discard_extras,
dialect=self._dialect)
)
To use the example, you would put your test_input into a PCollection, and apply the DictToCSV PTransform to the PCollection; you can take the resulting converted PCollection and use it as input for WriteToText. Note that you must provide a list or tuple of column names, via the column_order argument, corresponding to keys for your dictionary input elements; the resulting CSV-formatted string columns will be in the order of the column names provided. Also, the underlying implementation for the example does not support unicode.
Based on Andrew's suggestion, here is a ConvertDictToCSV function that I created:
def ConvertDictToCSV(input_dict, fieldnames, separator=",", quotechar='"'):
value_list = []
for field in fieldnames:
if input_dict[field]:
field_value = str(input_dict[field])
else:
field_value = ""
if separator in field_value:
field_value = quotechar + field_value + quotechar
value_list.append(field_value)
return separator.join(value_list)
This appears to be working well, but would certainly be safer to make use of csv.DictWriter if possible
