Skip to main content

Scripts and Jupyter notebooks for 4DN wrangling

Project description

DCIC-wrangling

This is a collection of scripts and Jupyter notebooks that can be helpful when performing many data wrangling tasks. Most of the tools are specific to 4DN Nucleome wrangling needs, however may be modified to be more generally useful for certain tasks.

Install

Packaged with poetry can be installed using make, poetry or pip.

From the dcicwrangling directory - make build

If you already have poetry installed - poetry install

Or to pip install from PyPi - pip install dcicwrangling

All dependencies are installed by default - if for some reason you don't want to install pytest packages or invoke (used to launch notebooks) you can do poetry install --no-dev - not recommended.

Usage

Jupyter notebooks

There are a collection of commonly used jupyter notebooks in the notebooks/useful_notebooks directory. You can start a jupyter notebook server locally using invoke notebook from the top level directory. This should launch the server and open a browser page where the notebooks can be accessed.

IMPORTANT! - You should create your own folder in the notebooks directory named Yourname_scripts. This folder is where you should create, access and run your notebooks. If you want to start with one of the notebooks in the useful_notebooks directory please create a copy and move it to your own folder. This keeps the repository clean and organized. Please DO NOT run notebooks in the useful_notebooks directory and commit the results to the repository.

Scripts

The scripts directory contains some useful command line scripts. They can be run from the top level directory using python scripts/script_name --options. Using --help shows available options. In general, modified versions and bespoke scripts should not be committed to the repository - or alternatively committed to a separate non-master branch.

As scripts are developed and refined tool.poetry.scripts directives can be added to facilitate script usage - see pyproject.toml file example.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dcicwrangling-2.0.0.tar.gz (57.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dcicwrangling-2.0.0-py3-none-any.whl (67.7 kB view details)

Uploaded Python 3

File details

Details for the file dcicwrangling-2.0.0.tar.gz.

File metadata

  • Download URL: dcicwrangling-2.0.0.tar.gz
  • Upload date:
  • Size: 57.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.3.2 CPython/3.7.15 Linux/5.4.0-1100-azure

File hashes

Hashes for dcicwrangling-2.0.0.tar.gz
Algorithm Hash digest
SHA256 f6fffb72278e449d6610911d35b6f19aa489fc73bb1ccd1271788d205afab921
MD5 15f5bf49ba16f966fd549640a661abba
BLAKE2b-256 bc073ce6506171fc5124896d7d71be787617c37efaeca6027ce7a54f4e34a89a

See more details on using hashes here.

File details

Details for the file dcicwrangling-2.0.0-py3-none-any.whl.

File metadata

  • Download URL: dcicwrangling-2.0.0-py3-none-any.whl
  • Upload date:
  • Size: 67.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.3.2 CPython/3.7.15 Linux/5.4.0-1100-azure

File hashes

Hashes for dcicwrangling-2.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 62790e31553fd52e86cb02701671c1166adaec3d98886177db50ac2e05f7937c
MD5 f5305da52e00052f3f238f29b948f1a5
BLAKE2b-256 8a61d25ad6868292f4698148aa81a80d0c1a12fa19399b55147affad0ef2e07d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page