Do you track your eating habits on MyFitnessPal? Have you ever wanted to analyze the information you're entering into MyFitnessPal programatically?
Although MyFitnessPal does have an API, it is private-access only; this creates an unnecessary barrier between you and your data that can be overcome using this library.
Having problems? Issues live on github. Have questions? Ask your questions in our gitter room.
You can either install from pip:
pip install myfitnesspal
or checkout and install the source from the github repository:
git clone https://github.com/coddingtonbear/python-myfitnesspal.git
cd python-myfitnesspal
python setup.py install
To access a single day's information:
import myfitnesspal
client = myfitnesspal.Client('my_username', 'my_password')
day = client.get_date(2013, 3, 2)
day
# >> <03/02/13 {'sodium': 3326, 'carbohydrates': 369, 'calories': 2001, 'fat': 22, 'sugar': 103, 'protein': 110}>To see all meals you can use the Day object's meals property:
day.meals
# >> [<Breakfast {}>,
# <Lunch {'sodium': 712, 'carbohydrates': 106, 'calories': 485, 'fat': 3, 'sugar': 0, 'protein': 17}>,
# <Dinner {'sodium': 2190, 'carbohydrates': 170, 'calories': 945, 'fat': 11, 'sugar': 17, 'protein': 53}>,
# <Snacks {'sodium': 424, 'carbohydrates': 93, 'calories': 571, 'fat': 8, 'sugar': 86, 'protein': 40}>]To access dinner, you can access it by its index in day.meals:
dinner = day.meals[2]
dinner
# >> <Dinner {'sodium': 2190, 'carbohydrates': 170, 'calories': 945, 'fat': 11, 'sugar': 17, 'protein': 53}>To get a list of things you ate for dinner, I can use the dinner Meal object's entries property:
dinner.entries
# >> [<Montebello - Spaghetti noodles, 6 oz. {'sodium': 0, 'carbohydrates': 132, 'calories': 630, 'fat': 3, 'sugar': 3, 'protein': 21}>,
# <Fresh Market - Arrabiatta Organic Pasta Sauce, 0.5 container (3 cups ea.) {'sodium': 1410, 'carbohydrates': 24, 'calories': 135, 'fat': 5, 'sugar': 12, 'protein': 6}>,
# <Quorn - Meatless and Soy-Free Meatballs, 6 -4 pieces (68g) {'sodium': 780, 'carbohydrates': 14, 'calories': 180, 'fat': 3, 'sugar': 2, 'protein': 26}>]To access one of the items, use the entries property as a list:
spaghetti = dinner.entries[0]
spaghetti.name
# >> Montebello - Spaghetti noodles, 6 oz.For a daily summary of your nutrition information, you can use a Day object's totals property:
day.totals
# >> {'calories': 2001,
# 'carbohydrates': 369,
# 'fat': 22,
# 'protein': 110,
# 'sodium': 3326,
# 'sugar': 103}Or, if you just want to see how many cups of water you've recorded, or the notes you've entered for a day:
day.water
# >> 1
day.notes
# >> "This is the note I entered for this day"For just one meal:
dinner.totals
# >> {'calories': 945,
# 'carbohydrates': 170,
# 'fat': 11,
# 'protein': 53,
# 'sodium': 2190,
# 'sugar': 17}For just one entry:
spaghetti.totals
# >> {'calories': 630,
# 'carbohydrates': 132,
# 'fat': 3,
# 'protein': 21,
# 'sodium': 0,
# 'sugar': 3}To access measurements from the past 30 days:
import myfitnesspal
client = myfitnesspal.Client('my_username', 'my_password')
weight = client.get_measurements('Weight')
weight
# >> OrderedDict([(datetime.date(2015, 5, 14), 171.0), (datetime.date(2015, 5, 13), 173.8), (datetime.date(2015, 5,12), 171.8),
# (datetime.date(2015, 5, 11), 171.6), (datetime.date(2015, 5, 10), 172.4), (datetime.date(2015, 5, 9), 170.2),
# (datetime.date(2015, 5, 8), 171.0), (datetime.date(2015, 5, 7), 171.2), (datetime.date(2015, 5, 6), 170.8),
# (datetime.date(2015, 5, 5), 171.8), (datetime.date(2015, 5, 4), 174.2), (datetime.date(2015, 5, 3), 172.2),
# (datetime.date(2015, 5, 2), 171.0), (datetime.date(2015, 5, 1), 171.2), (datetime.date(2015, 4, 30), 171.6),
# (datetime.date(2015, 4, 29), 172.4), (datetime.date(2015, 4, 28), 172.2), (datetime.date(2015, 4, 27), 173.2),
# (datetime.date(2015, 4, 26), 171.8), (datetime.date(2015, 4, 25), 170.8), (datetime.date(2015, 4, 24), 171.2),
# (datetime.date(2015, 4, 23), 171.6), (datetime.date(2015, 4, 22), 173.2), (datetime.date(2015, 4, 21), 174.2),
# (datetime.date(2015, 4, 20), 173.6), (datetime.date(2015, 4, 19), 171.8), (datetime.date(2015, 4, 18), 170.4),
# (datetime.date(2015, 4, 17), 169.8), (datetime.date(2015, 4, 16), 170.4), (datetime.date(2015, 4, 15), 170.8),
# (datetime.date(2015, 4, 14), 171.6)])To access measurements since a given date:
import datetime
may = datetime.date(2015, 5, 1)
body_fat = client.get_measurements('Body Fat', may)
body_fat
# >> OrderedDict([(datetime.date(2015, 5, 14), 12.8), (datetime.date(2015, 5, 13), 13.1), (datetime.date(2015, 5, 12), 12.7),
# (datetime.date(2015, 5, 11), 12.7), (datetime.date(2015, 5, 10), 12.8), (datetime.date(2015, 5, 9), 12.4),
# (datetime.date(2015, 5, 8), 12.6), (datetime.date(2015, 5, 7), 12.7), (datetime.date(2015, 5, 6), 12.6),
# (datetime.date(2015, 5, 5), 12.9), (datetime.date(2015, 5, 4), 13.0), (datetime.date(2015, 5, 3), 12.6),
# (datetime.date(2015, 5, 2), 12.6), (datetime.date(2015, 5, 1), 12.7)])To access measurements within a date range:
thisweek = datetime.date(2015, 5, 11)
lastweek = datetime.date(2015, 5, 4)
weight = client.get_measurements('Weight', thisweek, lastweek)
weight
# >> OrderedDict([(datetime.date(2015, 5, 11), 171.6), (datetime.date(2015, 5, 10), 172.4), (datetime.date(2015, 5,9), 170.2),
# (datetime.date(2015, 5, 8), 171.0), (datetime.date(2015, 5, 7), 171.2), (datetime.date(2015, 5, 6), 170.8),
# (datetime.date(2015, 5, 5), 171.8), (datetime.date(2015, 5, 4), 174.2)])Measurements are returned as ordered dictionaries. The first argument specifies the measurement name, which can be any name listed in the MyFitnessPal Check-In page. When specifying a date range, the order of the date arguments does not matter.
Day objects act as dictionaries:
day.keys()
# >> ['Breakfast', 'Lunch', 'Dinner', 'Snack']
lunch = day['Lunch']
print lunch
# >> [<Generic - Ethiopian - Miser Wat (Red Lentils), 2 cup {'sodium': 508, 'carbohydrates': 76, 'calories': 346, 'fat': 2, 'sugar': 0, 'protein': 12}>,
# <Injera - Ethiopian Flatbread, 18 " diameter {'sodium': 204, 'carbohydrates': 30, 'calories': 139, 'fat': 1, 'sugar': 0, 'protein': 5}>]Meal objects act as lists:
len(lunch)
# >> 2
miser_wat = lunch[0]
print miser_wat
# >> <Generic - Ethiopian - Miser Wat (Red Lentils), 2 cup {'sodium': 508, 'carbohydrates': 76, 'calories': 346, 'fat': 2, 'sugar': 0, 'protein': 12}>and Entry objects act as dictionaries:
print miser_wat['calories']
# >> 346and, since the measurement units returned are not necessarily very intuitive,
you can enable or disable unit awareness using the unit_aware keyword
argument.
client = myfitnesspal.Client('my_username', 'my_password', unit_aware=True)
day = client.get_date(2013, 3, 2)
lunch = day['lunch']
print lunch
# >> [<Generic - Ethiopian - Miser Wat (Red Lentils), 2 cup {'sodium': Weight(mg=508), 'carbohydrates': Weight(g=76), 'calories': Energy(Calorie=346), 'fat': Weight(g=2), 'sugar': Weight(g=0), 'protein': Weight(g=12)}>,
miser_wat = lunch[0]
print miser_wat['calories']
# >> Energy(Calorie=346)