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Home and office nutrient tracking software

Project description

Command line tools for interacting with government food database, and analyzing your health trends. The SR28 database includes data for ~8500 foods and ~180 nutrients. Customizable with extensions and mapping rules built on top.

Requires:

  • Python 3.4.3 or later (lzma, ssl & sqlite3 modules) [WinXP, Ubuntu14.04, or later].

  • Packages: see setup.py, and requirements.txt files.

  • Internet connection, to download food database & package dependencies.

See nt database: https://github.com/nutratech/nt-sqlite

See usda database: https://github.com/nutratech/usda-sqlite

Details

Category

Install / Linux

Test status unknown (Linux)

Install / Windows

Test status unknown (Windows)

Other checks

Coverage unknown Lint status unknown

PyPI Release

Latest version unknown Monthly downloads unknown

Supported Runtime

Python3 (3.4 - 3.10)

Code Style

Code style: black

License

License GPL-3

Linux / macOS requirements (for development)

You will need make and gcc to build the Levenshtein extension.

sudo apt install make gcc direnv python3-dev python3-venv

# on macOS
brew install make gcc direnv python@3.10

Using direnv

Install with,

sudo apt install direnv || brew install direnv

# Need to add hook, too
# See: https://direnv.net/docs/hook.html
DEFAULT_SHELL=$(basename $SHELL)
SHELL_RC_FILE=~/.${DEFAULT_SHELL}rc
HOOK='eval "$(direnv hook '$DEFAULT_SHELL')"'

# Install the hook, if not already
grep "$HOOK" $SHELL_RC_FILE || echo "$HOOK" >>$SHELL_RC_FILE
source $SHELL_RC_FILE

This is what the .envrc file is for. It automatically activates venv.

Notes

On Windows you should check the box during the Python installer to include Scripts directory in your %PATH%. This can be done manually after installation too.

Main program works 100% on older OSes, but test and lint may break.

Levenshtein speedup [extras]

Install the Levenshtein speedup with this.

pip install nutra[extras]

Linux may need to install python-dev package as well as gcc.

Windows may fail if missing the Visual Studio build tools are missing.

Install PyPi release (from pip)

pip install -U nutra

(Specify: flag -U to upgrade, or --pre for development releases)

Using the source code directly

Clone down, initialize nt-sqlite submodule, and install requirements:

git clone https://github.com/nutratech/cli.git
cd cli
make init || source .venv/bin/activate
make deps

./nutra -h

Initialize the DBs (nt and usda).

# source .venv/bin/activate  # uncomment if NOT using direnv
./nutra init

# Or install and run as package script
make install
n init

If installed (or inside cli) folder, the program can also run with python -m ntclient.

You may need to set the PY_SYS_INTERPRETER value for the Makefile if trying to install other than with /usr/bin/python3.

Building the PyPi release (sdist)

make build  # python3 setup.py --quiet sdist
twine upload dist/nutra-X.X.X.tar.gz

Linting & Tests

Install the dependencies (make deps). Now you can lint & test.

# source .venv/bin/activate  # uncomment if NOT using direnv
make format lint test

ArgComplete (tab completion / autocomplete)

The argcomplete package will be installed alongside.

Linux, macOS, and Linux Subsystem for Windows

Simply run the following out of a bash shell. Check their page for more specifics on using other shells, e.g. zsh, fish, or tsh.

activate-global-python-argcomplete --user

Then you can press tab to fill in or complete sub-commands and to list argument flags.

Windows (Git Bash)

This can work with git bash too. I followed the instructions on their README.

I’ve run the command to seed the autocomplete script.

mkdir -p $HOME/.bash_completion.d
activate-global-python-argcomplete --user

And my ~/.bashrc file looks like this.

export ARGCOMPLETE_USE_TEMPFILES=1

# python bash completion
if [ -f ~/.bash_completion.d/python-argcomplete ]; then
    source ~/.bash_completion.d/python-argcomplete
fi

On older versions it may be python-argcomplete.sh instead.

NOTE: Standard autocomplete is fully functional, we are adding customized completions.

Currently Supported Data

USDA Stock database

  • Standard reference database (SR28) [7794 foods]

USDA Extensions (Relational)

  • Flavonoid, Isoflavonoids, and Proanthocyanidins [1352 foods]

Usage

Requires internet connection to download initial datasets. Run nutra init for this step.

Run n or nutra to output usage (-h flag is optional and defaulted).

Project details


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This version

0.2.7

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