fitbit-data:使用Python代码下载Fitbit数据并将其插入PostgreSQL数据库

# fitbit https://python-fitbit.readthedocs.io/en/latest/ ## Description: This repository contains two python files, data_pull.py and make_plots.py. data_pull.py hooks into the Fitbit API (with a given client ID and secret) and pulls Fitbit statistics. ## Plot Example:  ## Methods: **hr()** for minute-by-minute heart rate data, given a date **sleep()** for all sleep logs, including time slept, start and end times, nap / main sleep, restless count, etc., given a date **water()** for how much water was logged, given a date **basicactivity()** for data on steps, active minutes, sedentary minutes, etc., given a date **hrzones()** for data on how long was spent in each heart rate zone (peak, cardio, fat burn, other), given a date **fill_missing_data()** will call all five above methods for a specified date range, and is meant to be run if the program doesn't execute on some day or set of days **date_check()** ensures no duplicates in the database **daterange()** is a helper method to yield a range of dates (analogous to the range() function, but for dates) All date parameters for each method defaults to the previous day. All methods (except for daterange() and date_check()) do not return. If date_check() returns -1, then the method that called it returns None and nothing is uploaded to the SQL database. Otherwise, new rows are appended to a SQL table in database fitbit with the specified name. ## Setup and Use: This project **not** runnable or useful (unless you want my Fitbit data) without registering an application with the Fitbit API and getting your own client ID and secret. Steps to get set up: 1. First, [**go here**](https://towardsdatascience.com/collect-your-own-fitbit-data-with-python-ff145fa10873) and follow the instructions to authorize yourself to use the API. 2. **SAVE YOUR CLIENT ID AND CLIENT SECRET!** You'll need them in the next step. 3. Then, in data_pull.py, change the database parameters (username, ip, name) to whatever PostreSQL database you want to use for storing the data if you don't want to use localhost. 4. Run data_pull.py and give it a test run! ## Command Line Arguments: --p YOUR_POSTGRES_PASSWORD (mandatory) --s (start date for fill in format %Y-%m-%d without quotation marks. If not set, defaults to one week ago.) --id YOUR_CLIENT_ID (from step 2) -- code will fail without a client ID --sec YOUR_CLIENT_SECRET (from step 2) -- code will fail without a secret