Package: comma
Comma: A Python CSV Library for HumansThis library tries to make manipulating CSV files a great experience.FeaturesHere are some of the features thatcommasupports:Robust autodetection of CSV parameters
(thanks toclevercsv) and
encoding (thanks tochardet).Single-line usage,comma.load(...), no syntax to remember or parameters to tweak.Simple, Pythonic interface to access/modify the rows using standardlistanddictoperations, i.e.row[0]androw["street"]are equivalent.Column slices using the header name, i.e.table["street"].In-place editing of the dataset, including multiple lines.Opening files directly from an URL.InstallationIf you use pip:pipinstall'comma[autodetect,net]'or if you use pipenv:pipenvinstall'comma[autodetect,net]'Why?Although Python, fortuitously, is
"batteries included",
on occasion, some of the libraries end up being designed with APIs
that don't map well to what turns out to be the most common usage
patterns. This is what happened with the variousurlliblibraries,
incredibly powerful, but limiting users by its complexity---it was
not straightforward, for instance, to use cookies: One of several
problems thatrequestsby@ken-reitzaddressed. Indeed,requestsabstracts power beneath simplicity, smart defaults, and
discoverability.For the CSV format, we are confronted with a similar situation. While
both the JSON and YAML formats have packages that provide, one-command
means to load content from files in those respective formats to a
nested Python object, for the CSV format,the standard libraryhas
you use an iterator to access the data. Many details require significant
syntax change (for instance the difference between having lists or
dictionaries depends on the class that is used to read the file).Since then, we also have several excellent libraries that, by providing
great auto-detection (of dialect, file format, encoding, etc.) allow
for hiding many details from the end user.All this to say,commawill try to do exactly what you want
when you do:importcommadata=comma.load("file.csv")data[0]["field"]="changed value"comma.dump(data,filename="file_modified.csv")AlternativesPython is fortunate to have a lot of very good libraries to read/write
CSV and tabular files in general. (Some of these were discovered through
the excellentAwesome Pythonlist.)clevercsv: An
exceptional library by@GjjvdBurg,
builds on statistical and empirical
to provide powerful and reliable CSV dialect detection. However, it
strives to be a drop-in replacement for the original Pythoncsvmodule, and as such does not improve on the complex syntax. This
library isthe culmination of serious peer-reviewed
research, andcommauses it
internally to improve auto-detection.csvkit: This is a set of
command-line tools (rather than a module/package) written in Python,
to make it easier to manipulate CSV files. One of the highlights is
a tool calledcsvpy <file.csv>to open a Python shell with the CSV
data loaded into a Python object calledreader, to quickly run
some Python logic on the data. While it is technically possible to
usecsvkit's internals in a project, this is not documented.pandas: An advanced data
science package for Python, this certainly provides a powerful CSV
(and more generally, table file) reader and parser. The API of the
table object is very powerful, but you need to take the time to learn
how to use it. This library is perhaps not ideal for file manipulations.pyexcel: This library provides
access to Excel and other tabular formats, including CSV, and various
data sources (stream, database, file, ...). It emphasizes one common
format-agnostic API, that instead has the user choose the data format
(list, matrix, dictionary, ...).tablib: This library was
originally written byKenneth Reitz,
the creator who broughtrequests,pipenvand many other goodies to
Python---and then included in theJazzbandcollective. The focus of this library is on interoperating between many
different file formats (such as XLS, CSV, JSON, YAML, DF, etc., ...,
even LaTeXbooktabs!). It seems to have a very high adoption rate
because it is a dependency for many Jazzband libraries. The API is
class-based rather than method-based. A companion library,prettytablefocuses on
pretty printing tabular data (including from a CSV file).tabulator: This
library provides a single interface to manipulate extremely large
tabular data---and useful for files so large that they need to be
streamed line-by-line; the library supports a broad array of formats
including reading data directly from Google Spreadsheets. However
this power means that reading a CSV file requires several operations.Although not specifically restricted to Python, theAwesomeCSVresource is also
interesting.MiscellaneousAlthough not specifically a Python library, nor designed to read/write CSV
files (but instead to compare them),daffis a really cool project: It provides adiffof tabular datawith cell-level
awareness.Another unrelated project isGrist, a spreadsheet
PaaS, which among other useful features, allowsthe use of Python within
formulas.AcknowledgementsThanks to@zbanksfor the name of the package!
Thanks to@rfreling,@adamfinkelsteinfor discussing ideas
before I got started on this. Thanks to@GjjvdBurgand collaborators for awesome, awesome contribution to text processing science
and our Python community withclevercsv.LicenseThis project is licensed under the LGPLv3 license, with the understanding
that importing a Python modular is similar in spirit to dynamically linking
against it.You can use the librarycommain any project, for any purpose, as long
as you provide some acknowledgement to this original project for use of
the library.If you make improvements tocomma, you are required to make those
changes publicly available.