fitdata


Namefitdata JSON
Version 1.3.0 PyPI version JSON
download
home_pagehttps://gitlab.com/misternobody01/fitdata.git
SummaryA Python package for managing fitness-related data and goals.
upload_time2025-01-10 12:06:00
maintainerNone
docs_urlNone
authorMonsieur Nobody
requires_python>=3.6
licenseMIT
keywords fitness health bmi bmr tdee macros python
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            ## Overview

The **FitData** package provides tools for analyzing and managing health-related data and fitness goals. It offers features for validating user data, calculating essential metrics (e.g., BMI, BMR, TDEE), managing macronutrient distributions, and tracking weekly progress.

Designed for developers, this package simplifies the process of integrating fitness calculations and data analysis into applications.

---

## Features

1. **Data Validation**
   - Ensures user-provided data is complete, consistent, and properly formatted.

2. **Core Calculations**
   - **BMI (Body Mass Index)**: Calculates BMI and determines the corresponding category.
   - **BMR (Basal Metabolic Rate)**: Computes the minimum calories required to maintain basic physiological functions.
   - **TDEE (Total Daily Energy Expenditure)**: Estimates daily calorie burn based on activity levels.

3. **Advanced Calculations**
   - **Caloric Adjustments**: Calculates the caloric surplus/deficit required for fitness goals.
   - **Duration Estimation**: Estimates the time required to achieve a target weight.
   - **Macronutrient Management**: Distributes protein, carbs, fat, and other macros across meals.

4. **Progress Tracking**
   - Tracks weekly progression and provides feedback on weight changes.

---

            

Raw data

            {
    "_id": null,
    "home_page": "https://gitlab.com/misternobody01/fitdata.git",
    "name": "fitdata",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.6",
    "maintainer_email": null,
    "keywords": "fitness health bmi bmr tdee macros python",
    "author": "Monsieur Nobody",
    "author_email": "monsieurnobody01@gmail.com",
    "download_url": "https://files.pythonhosted.org/packages/b1/4c/6f42f42b39e00e4cbd8b8dba840f580a6b56f68bfb163be333e73e30d821/fitdata-1.3.0.tar.gz",
    "platform": null,
    "description": "## Overview\n\nThe **FitData** package provides tools for analyzing and managing health-related data and fitness goals. It offers features for validating user data, calculating essential metrics (e.g., BMI, BMR, TDEE), managing macronutrient distributions, and tracking weekly progress.\n\nDesigned for developers, this package simplifies the process of integrating fitness calculations and data analysis into applications.\n\n---\n\n## Features\n\n1. **Data Validation**\n   - Ensures user-provided data is complete, consistent, and properly formatted.\n\n2. **Core Calculations**\n   - **BMI (Body Mass Index)**: Calculates BMI and determines the corresponding category.\n   - **BMR (Basal Metabolic Rate)**: Computes the minimum calories required to maintain basic physiological functions.\n   - **TDEE (Total Daily Energy Expenditure)**: Estimates daily calorie burn based on activity levels.\n\n3. **Advanced Calculations**\n   - **Caloric Adjustments**: Calculates the caloric surplus/deficit required for fitness goals.\n   - **Duration Estimation**: Estimates the time required to achieve a target weight.\n   - **Macronutrient Management**: Distributes protein, carbs, fat, and other macros across meals.\n\n4. **Progress Tracking**\n   - Tracks weekly progression and provides feedback on weight changes.\n\n---\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "A Python package for managing fitness-related data and goals.",
    "version": "1.3.0",
    "project_urls": {
        "Homepage": "https://gitlab.com/misternobody01/fitdata.git"
    },
    "split_keywords": [
        "fitness",
        "health",
        "bmi",
        "bmr",
        "tdee",
        "macros",
        "python"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "d35507a718e47611124f2b74d5bc2d0d56b453a98eccfc04fc88e58b0c197455",
                "md5": "7eaea2b7dc53b217ac771e36a9e32ef6",
                "sha256": "d844d55fe17a60c677c576f33920ce65f4894754c1058265510e6713307c9be3"
            },
            "downloads": -1,
            "filename": "fitdata-1.3.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "7eaea2b7dc53b217ac771e36a9e32ef6",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.6",
            "size": 12278,
            "upload_time": "2025-01-10T12:05:58",
            "upload_time_iso_8601": "2025-01-10T12:05:58.677164Z",
            "url": "https://files.pythonhosted.org/packages/d3/55/07a718e47611124f2b74d5bc2d0d56b453a98eccfc04fc88e58b0c197455/fitdata-1.3.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "b14c6f42f42b39e00e4cbd8b8dba840f580a6b56f68bfb163be333e73e30d821",
                "md5": "b855302995e053ec35c458e864168eb1",
                "sha256": "8c872cba850c49bcbf78a179c2658f784997873934cf7e5a9b81f8710ad4e585"
            },
            "downloads": -1,
            "filename": "fitdata-1.3.0.tar.gz",
            "has_sig": false,
            "md5_digest": "b855302995e053ec35c458e864168eb1",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.6",
            "size": 10057,
            "upload_time": "2025-01-10T12:06:00",
            "upload_time_iso_8601": "2025-01-10T12:06:00.976442Z",
            "url": "https://files.pythonhosted.org/packages/b1/4c/6f42f42b39e00e4cbd8b8dba840f580a6b56f68bfb163be333e73e30d821/fitdata-1.3.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-01-10 12:06:00",
    "github": false,
    "gitlab": true,
    "bitbucket": false,
    "codeberg": false,
    "gitlab_user": "misternobody01",
    "gitlab_project": "fitdata",
    "lcname": "fitdata"
}
        
Elapsed time: 0.48920s