casanova 0.1.0

Specialized & performant CSV readers, writers and enrichers for python.

Casanova

If you often find yourself reading CSV files using python, you will quickly notice that, while being more comfortable, csv.DictReader remains way slower than csv.reader:

# To read a 1.5G CSV file:
csv.reader: 24s
csv.DictReader: 84s

Casanova is therefore an attempt to stick to csv.reader performance while still keeping a comfortable interface, still able to consider headers etc.

Casanova is thus a good fit for you if you need to:

• Stream large CSV files without running out of memory
• Enrich the same CSV files by outputing a similar file, all while adding, filtering and editing cells.
• Have the possibility to resume said enrichment if your process exited
• Do so in a threadsafe fashion, and be able to resume even if your output does not have the same order as the input

Installation

You can install casanova with pip with the following command:

pip install casanova

Usage

• reader

reader

import casanova

with open('./file.csv') as f:

  # Interested in a single column?
  for url in casanova.reader(f, column='url'):
    print(url)

  # No headers?
  for url in casanova.reader(f, column=0, no_headers=True):
    print(url)

  # Interested in several columns
  for title, url in casanova.reader(f, columns=('title', 'url')):
    print(title, url)

  # Working on records
  for record in casanova.reader(f, columns=('title', 'url')):
    # record is a namedtuple based on your columns
    print(record[0], record.url)

  # Records slow you down? Need to go faster?
  # You can iterate directly on rows and use the reader's recorded positions
  reader = casanova.reader(f, columns=('title', 'url'))
  url_pos = reader.pos.url

  for row in reader.rows():
    print(row[url_pos])

Arguments

• file file: file object to read.
• column ?str|int: name or index of target column.
• colums ?iterable<str|int>: iterable of name or index of target columns.

Attributes

• pos int|namedtuple: index of target column or named tuple of target columns.

Methods

iter

Lets you iterate on a single value or on a namedtuple record.

rows

Lets you iterate over the original csv.reader.