Data Enrichment templates

Lazy templates help developing apps for Data Enrichment. Lazy is a revolutionary software tool that turns the traditional Data Enrichment application development process on its head. Using Lazy AI, developers can create Data Enrichment apps using just prompts, freeing themselves from the complex and time-consuming coding processes.

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Generate Scatter Plot from CSV

An app for editing raw data, uploading CSV files, and handling errors.

Streamlit
Python

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Create Repository from Template using Github API

This app creates a GitHub repository using a template repository with user-defined environment variables. The user can add the template repository name and repository owner details as environment variables. They can also add the custom name they would like to give the new repository created from the template. The app uses FastAPI for making the api call to Github endpoints.

Discord Activity Monitor Bot

This Discord bot monitors member activity within a server. It allows administrators to rank inactivity criteria in days or minutes using command !setinactivity x minutes or !setinactivity x days. Inactive users can be kicked based on the criteria set by the administrators using command !kickinactive. App requires 'DISCORD_BOT_TOKEN' environment secret. And you need to give the bot following permissions on discord website. Read Message History: To fetch past messages and determine member activity. Kick Members: To remove inactive members from the server. Read Messages / View channels: To read latest message of user.

GitHub Webhook Example

This is a Python Flask API application that handles GitHub webhooks that have been setup for a GitHub repository. The app listens to and receives incoming JSON data from GitHub on it's endpoint `github/webhook/`, and prints it for the user to see. The JSON data can then be stored or further processed as required. The app URL will be used in the webhook setup on GitHub.

Gmail Organization Invitation API

This app is an API that sends an invitation email from a Gmail account with 2FA enabled. It accepts various inputs to generate a personalized invitation email based on the name of the email of the person being invited, the email who invited the person and the name of the organisation and an invitation link.

Context Aware Chat API

A simple chat API for user interaction with a large language model.

FALLBACK LATEST 1 THEME | Flask, HTML, JS and Tailwind Based Website

This is a good starting point for styled website. It has a header, footer. Has Tailwind and Flowbite loaded so you can build nice looking pages from here.

Lazy apps can be helpful in the Data Enrichment category by automating and streamlining the process of gathering and enhancing data. Here are a few ways lazy apps can assist in data enrichment:

  1. Automated data collection: Lazy apps can automatically collect data from various sources, such as websites, APIs, or databases. This eliminates the need for manual data entry and saves time and effort.
  2. Data validation and cleansing: Lazy apps can perform data validation checks to ensure the accuracy and integrity of the collected data. They can also clean and standardize the data by removing duplicates, correcting errors, and formatting it consistently.
  3. Data enrichment through external sources: Lazy apps can integrate with external data sources, such as social media platforms, public databases, or third-party APIs, to enrich the collected data. This can include adding demographic information, geolocation data, or additional details about individuals or companies.
  4. Data enrichment through machine learning: Lazy apps can leverage machine learning algorithms to analyze and extract insights from the collected data. This can include sentiment analysis, categorization, or predictive modeling, which can provide valuable information for decision-making.
  5. Seamless integration with existing systems: Lazy apps can integrate with existing data management systems, such as customer relationship management (CRM) or marketing automation platforms, to ensure a smooth flow of enriched data. This allows organizations to leverage the enriched data in their existing workflows and processes.

Overall, lazy apps in the Data Enrichment category can significantly reduce manual effort, improve data quality, and provide valuable insights for businesses and organizations.

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