Packages may contain data of any size or type. A given package instance--specified by a hash, tag, or version--is immutable for reproducibility.
$ quilt install uciml/iris
Note: most Quilt commands are available both on the command line and in Python.
You can install a package as follows:
$ python>>> from quilt.data.uciml import iris>>> iris<PackageNode 'Users/YOU/quilt_packages/uciml/iris'>raw/tables/README>>> iris.tables.bezdek_iris() # this is a pandas DataFramesepal_length sepal_width petal_length petal_width label0 5.1 3.5 1.4 0.2 Iris-setosa1 4.9 3.0 1.4 0.2 Iris-setosa2 4.7 3.2 1.3 0.2 Iris-setosa...
Start by installing and importing the package you wish to modify:
import quiltquilt.install("uciml/wine")from quilt.data.uciml import wine
Alternatively, you can build an empty package and import it for editing:
import quiltquilt.build("USER/FOO")from quilt.data.USER import FOO
Update: As of version 2.9.9, easiest method to edit a package is to use subpackage build and push.
Use the Pandas API to edit existing dataframes:
df = wine.tables.wine()hue = df['Hue']df['HueNormalized'] = (hue - hue.min())/(hue.max() - hue.min())
_set helper method on the top-level package node to create new groups and data nodes:
import pandas as pddf = pd.DataFrame(dict(x=[1, 2, 3]))# insert a dataframe at wine.mygroup.data()wine._set(["mygroup", "data"], df)# insert a file at wine.mygroup.anothergroup.blob()wine._set(["mygroup", "anothergroup", "blob"], "localpath/file.txt") #
del to delete attributes:
_meta attribute to attach any JSON-serializable dictionary of metadata to a group or a data node:
wine.mygroup._meta['foo'] = 'bar'wine.mygroup._meta['created'] = time.time()
Data nodes contain a built-in key
_meta['_system'] with information such as the original file path. You may access it, but any modifications to it may be lost.
At this point, your changes only exist in memory. To persist your changes, read on to learn about
Building a package creates a local bundle of serialized data.
$ quilt ls displays your local packages and their location on disk.
There are three ways to build data packages with Quilt:
quilt build USR/PKG DIRECTORY. Implicit builds are good for taking quick snapshots of unstructured data like images or text files. Quilt serializes columnar formats formats (xls, csv, tsv, etc.) to data frames; all other files will be copied "as is".
quilt build USR/PKG FILE.YML. Explicit builds allow fine-grained control over package names, types, and contents.
One the fly, in Python
To implicitly build a package of unserialized data:
quilt build USR/PKG DIRECTORY
DIR and it's subdirectories will be packaged into
To publish your package:
quilt push USR/PKG --public
Users on Individual and Business plans can omit the
--public flag to create private packages.
Explicit builds cue from a YAML file, conventionally called
quilt build USR/PKG BUILD.YML
build.yml specifies the structure and contents of a package.
An easy way to create a
build.yml file is as follows:
quilt generate DIR
The above command creates
README.md files that you can modify to your liking. A
README.md file is highly recommended as it populates your package landing page with documentation. See the API section for more on how README markdown is converted to HTML.
build.yml syntax for more.
Directory and file naming in quilt generate
Directories and files that start with a numeric character or underscore will be prefixed with the letter
n. If a name collision results, the build will fail with an error.
If two files have the same path and root name, but different file extensions (
foo.csv), the extensions will be appended as follows:
foo_csv. If, after appending, there remains a name collision, the build will fail with an error.
# start with an empty packagequilt.build("akarve/foo")# put some data in itimport pandas as pdfrom quilt.data.akarve import foodf = pd.DataFrame(data=[1,2,3])foo._set(['bar'], df)foo.bar()# Output:# 0# 0 1# 1 2# 2 3
Package handles take the form
USER_NAME/PACKAGE_NAME. The package name and all of its children must be valid Python identifiers:
Start with a letter
Contain only alphanumerics and underscore
The above criteria ensure that packages can be accessed with Python's dot operator.
Pushing a package stores a built package in a server-side registry. Push a package to back up changes or share your package with others.
$ quilt login # requires free account$ quilt push USR/PKG --public
Or, in Python:
# log in to the registry (requires a free account)quilt.login()# push it to the registryquilt.push("USR/PKG", is_public=True)
Users on Individual and Business plans can omit
is_public=True to create private packages.