Skip to main content

FK-Graph

Visualise the graphs hidden within relational databases.

Schemas can sometimes fail to reflect the full complexity of the relationships in a populated database, especially when the data has been added manually over a period of time.

This application creates a graph of foreign key relations in a populated database and can be used to generate a plotly figure, or interactive dash app, showing these relations.

To install:

pip install fk-graph

Development:

Clone the repo and cd in to the project directory. Create a virtual env, then install the requirements with

pip install -r requirements.txt

Finally, to be able to run tests while developing, install the package as an editable install.

pip install --editable .

Metadata

Release files for fk-graph 0.0.15

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for fk-graph 0.0.15
File Size Uploaded
fk_graph-0.0.15.tar.gz 12.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for fk-graph 0.0.15
File Interpreter ABI Platform
fk_graph-0.0.15-py3-none-any.whl Python 3 none any Details

Total release size: 23.2 kB

Release files / fk_graph-0.0.15.tar.gz

Download URL fk_graph-0.0.15.tar.gz
Size 12.3 kB
Tags Source
SHA-256 checksum
How to use checksums
99393d3c4b49fa128654cc8abcc8f46f4a6df801493c2ae9a9b055cc3c4e85af
BLAKE2b-256 checksum
How to use checksums
7ec10dc166adbbeceb050f0abadbc2040422330846f4e6c073ae6e8991edf9a6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/4.0.2 CPython/3.11.7

Release files / fk_graph-0.0.15-py3-none-any.whl

Download URL fk_graph-0.0.15-py3-none-any.whl
Size 10.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
60ab11806165aa235e1a2265d3d833cb0a80f9a017837a66eaf5e6cecfad60d8
BLAKE2b-256 checksum
How to use checksums
06d0620810683ef39ffeda7ac9fa568806a149af5158f278eac5ef7f22b2e442
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/4.0.2 CPython/3.11.7

Release history Release notifications | RSS feed

This release

0.0.15 This release

2 release files

0.0.13

2 release files

0.0.12

2 release files

0.0.11

2 release files

0.0.10

2 release files

0.0.9

2 release files

0.0.8

2 release files

0.0.7

2 release files

0.0.5

2 release files

0.0.4

2 release files

0.0.3

2 release files

0.0.2

2 release files

0.0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page