fitbit-analyzer | statistics generator for fitbit data like sleep

by 5agado Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | fitbit-analyzer Summary

fitbit-analyzer is a Python library. fitbit-analyzer has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. However fitbit-analyzer has 1 bugs. You can download it from GitHub.

Analyzer and statistics generator for Fitbit data like sleep, steps count and heart rate. Check out also my related introductory article. Includes OAuth 2.0 scraper to download personal Fitbit data using the Fitbit API Python Client Implementation.

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Quality

Security

License

Reuse

Support

fitbit-analyzer has a low active ecosystem.

It has 52 star(s) with 16 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 3 have been closed. On average issues are closed in 10 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of fitbit-analyzer is current.

Quality

fitbit-analyzer has 1 bugs (0 blocker, 0 critical, 0 major, 1 minor) and 182 code smells.

Security

fitbit-analyzer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

fitbit-analyzer code analysis shows 0 unresolved vulnerabilities.

There are 1 security hotspots that need review.

License

fitbit-analyzer is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

fitbit-analyzer releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

fitbit-analyzer saves you 314 person hours of effort in developing the same functionality from scratch.

It has 756 lines of code, 80 functions and 17 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed fitbit-analyzer and discovered the below as its top functions. This is intended to give you an instant insight into fitbit-analyzer implemented functionality, and help decide if they suit your requirements.

Load sleep data
Load data from the dump directory
Returns a list of all subDirs of a main directory
Load heart data from the home directory
Generates statistics for a given data type
Generates basic statistics for each file
Generates a dataframe with the basic statistics for each file
Get sleep date
Plots sleep time
Prepare the main dataframe
Get axes and axes
Returns a DataFrame containing the heart beat heart data
Loads the steps data from the json file
Loads the total steps data for each activity
Scrape data from the current directory
Dump activities to a directory
Dump data to a JSON file
Plot sleep efficiency
Prepare yearly stats for year and month
Scrape from a given date range
Start the authorization token URL
Calculate the center of intradayCountStats
Return HTML response
Format a failure message
Plot monthly sleep times
Plot the sleep efficiency of week sleep

Get all kandi verified functions for this library.

fitbit-analyzer Key Features

No Key Features are available at this moment for fitbit-analyzer.

fitbit-analyzer Examples and Code Snippets

No Code Snippets are available at this moment for fitbit-analyzer.

Community Discussions

No Community Discussions are available at this moment for fitbit-analyzer.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install fitbit-analyzer

You can download it from GitHub.
You can use fitbit-analyzer like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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