A simplified prototype for an as-built tracking database with API

Overview

Asbuilt_Trax

A simplified prototype for an as-built tracking database with API

The purpose of this project is to:

  1. Model a database that tracks construction as-builts, GIS contributers, GIS data, and construction crew leaders all in one place
  2. Publish an API that provides access to that data
  3. Use Jupyter Notebook to analyze and visualize the data

API Reference:

Endpoint path Method Parameter Description
http://localhost:5000/asbuilts/[ID] GET asbuilt.ID Returns data for specified as-built
http://localhost:5000/asbuilts/[ID] PUT asbuilt.ID Updates specified as-built
http://localhost:5000/asbuilts GET None Returns data for all as-builts
http://localhost:5000/asbuilts POST (JSON) gis_user_id, work_order, crew_leader_id, install_date Creates new record in asbuilts table
http://localhost:5000/asbuilts/[ID] DELETE asbuilt.ID Deletes specified as-built record

Project evolution

Asbuilt_Trax began as a way to practice PostgreSQL database design, construction, and maintenance by implementing a simplified records management database based on a utilities mapping workflow. What it provides is a solution to the problem of being able to lookup and manage records in an efficient way, leveraging the power of a database to serve the data up via API, and visualize the data in using Jupyter Notebook.

ORM

With a reasonable footing in SQL, I chose to build the API with Flask-SQLAlchemy in order to practice using the ORM and the framework it provides.

Future devlopments

Currently the API only provides for basic query and post/ delete operations. So I am looking forward to expanding those capabilities to return more comprehensive data from the database, including GIS records, creating and updating user tables, and SQL triggers to automate data management. I'd also like to implement more data visualization tools in the associated Jupyter Notebook.

Owner
Ryan Pemberton
Ryan Pemberton
Data processing with Pandas.

Processing-data-with-python This is a simple example showing how to use Pandas to create a dataframe and the processing data with python. The jupyter

1 Jan 23, 2022
📊 Python Flask game that consolidates data from Nasdaq, allowing the user to practice buying and selling stocks.

Web Trader Web Trader is a trading website that consolidates data from Nasdaq, allowing the user to search up the ticker symbol and price of any stock

Paulina Khew 21 Aug 30, 2022
Containerized Demo of Apache Spark MLlib on a Data Lakehouse (2022)

Spark-DeltaLake-Demo Reliable, Scalable Machine Learning (2022) This project was completed in an attempt to become better acquainted with the latest b

8 Mar 21, 2022
PLStream: A Framework for Fast Polarity Labelling of Massive Data Streams

PLStream: A Framework for Fast Polarity Labelling of Massive Data Streams Motivation When dataset freshness is critical, the annotating of high speed

4 Aug 02, 2022
Created covid data pipeline using PySpark and MySQL that collected data stream from API and do some processing and store it into MYSQL database.

Created covid data pipeline using PySpark and MySQL that collected data stream from API and do some processing and store it into MYSQL database.

2 Nov 20, 2021
Example Of Splunk Search Query With Python And Splunk Python SDK

SSQAuto (Splunk Search Query Automation) Example Of Splunk Search Query With Python And Splunk Python SDK installation: ➜ ~ git clone https://github.c

AmirHoseinTangsiriNET 1 Nov 14, 2021
PyEmits, a python package for easy manipulation in time-series data.

PyEmits, a python package for easy manipulation in time-series data. Time-series data is very common in real life. Engineering FSI industry (Financial

Thompson 5 Sep 23, 2022
Python beta calculator that retrieves stock and market data and provides linear regressions.

Stock and Index Beta Calculator Python script that calculates the beta (β) of a stock against the chosen index. The script retrieves the data and resa

sammuhrai 4 Jul 29, 2022
Find exposed data in Azure with this public blob scanner

BlobHunter A tool for scanning Azure blob storage accounts for publicly opened blobs. BlobHunter is a part of "Hunting Azure Blobs Exposes Millions of

CyberArk 250 Jan 03, 2023
A DSL for data-driven computational pipelines

"Dataflow variables are spectacularly expressive in concurrent programming" Henri E. Bal , Jennifer G. Steiner , Andrew S. Tanenbaum Quick overview Ne

1.9k Jan 03, 2023
Weather Image Recognition - Python weather application using series of data

Weather Image Recognition - Python weather application using series of data

Kushal Shingote 1 Feb 04, 2022
Data Competition: automated systems that can detect whether people are not wearing masks or are wearing masks incorrectly

Table of contents Introduction Dataset Model & Metrics How to Run Quickstart Install Training Evaluation Detection DATA COMPETITION The COVID-19 pande

Thanh Dat Vu 1 Feb 27, 2022
simple way to build the declarative and destributed data pipelines with python

unipipeline simple way to build the declarative and distributed data pipelines. Why you should use it Declarative strict config Scaffolding Fully type

aliaksandr-master 0 Jan 26, 2022
An Integrated Experimental Platform for time series data anomaly detection.

Curve Sorry to tell contributors and users. We decided to archive the project temporarily due to the employee work plan of collaborators. There are no

Baidu 486 Dec 21, 2022
A forecasting system dedicated to smart city data

smart-city-predictions System prognostyczny dedykowany dla danych inteligentnych miast Praca inżynierska realizowana przez Michała Stawikowskiego and

Kevin Lai 1 Nov 08, 2021
A Numba-based two-point correlation function calculator using a grid decomposition

A Numba-based two-point correlation function (2PCF) calculator using a grid decomposition. Like Corrfunc, but written in Numba, with simplicity and hackability in mind.

Lehman Garrison 3 Aug 24, 2022
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io

PyStan PyStan is a Python interface to Stan, a package for Bayesian inference. Stan® is a state-of-the-art platform for statistical modeling and high-

Stan 229 Dec 29, 2022
DaCe is a parallel programming framework that takes code in Python/NumPy and other programming languages

aCe - Data-Centric Parallel Programming Decoupling domain science from performance optimization. DaCe is a parallel programming framework that takes c

SPCL 330 Dec 30, 2022
A crude Hy handle on Pandas library

Quickstart Hyenas is a curde Hy handle written on top of Pandas API to allow for more elegant access to data-scientist's powerhouse that is Pandas. In

Peter Výboch 4 Sep 05, 2022
Hidden Markov Models in Python, with scikit-learn like API

hmmlearn hmmlearn is a set of algorithms for unsupervised learning and inference of Hidden Markov Models. For supervised learning learning of HMMs and

2.7k Jan 03, 2023