A module for visualization of a nested python data structure
a nested python objects including list, tuple, dictionary, tensor, ndarray to data-tree, and make a quick peek out of its structure
data = a list of 10 lists of 3 dicts of 2 keys : list of 2 strings
dv.viz(data)
$ list of 10
$ └── list of 3
$ └── dict of 2
$ ├── train : ['data1', 'data2']
$ └── test : ['data3', 'data4']
How to use
install
$ pip install dstree
import and quick_start
import dstree as dst
data = dst.get_example_data()
tree = dst.viz(data)
usage in detail
import dstree as dst
dst.quick_start() # Copy & Paste console output to set up the tutorial codes
Note
This package is built based on treelib & graphviz syntax.
Supports int, str, float, list, tuple, dict, Tensor, ndarray, Series, DataFrame datatype.
And also custom data classes are supported.
Metadata
Release files for dstree 3.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| dstree-3.4.tar.gz | 4.1 MB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dstree-3.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.3 MB
Release files / dstree-3.4.tar.gz
| Download URL | dstree-3.4.tar.gz |
|---|---|
| Size | 4.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
b8e10af9e7aab5537263e45040171f9222848c2b1516fe5a25877d18f8d06fb6
|
|
BLAKE2b-256 checksum How to use checksums |
35989e46fe5344bc319402722ff1fc5c7d3a478667a13de750c9fe5fe85719d4
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.8.9
|
Release files / dstree-3.4-py3-none-any.whl
| Download URL | dstree-3.4-py3-none-any.whl |
|---|---|
| Size | 4.2 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
562a9378628572104c68b8b0e794186be845c24960b1d0186fd3440c7416ba65
|
|
BLAKE2b-256 checksum How to use checksums |
47d5ec6ee89486edcea28060e98b08a27daa1a7f38c43b653c48d905ac172822
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.8.9
|
Security for dstree 3.4
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.