A commandline utility to search across Slack for messages that were reacted to with a specific emoji.
The simplest way to install this package is to use pip to install the package from the Python Package Index:
$ pip install slack-emoji-search
Ensure Python, pip, virtualenv and virtualenvwrapper are set up. If you've run the laptop script, you're all good.
Assuming you are using Python 2.7.9+ or 3.4+ the following steps should work:
$ python -m ensurepip
$ pip install virtualenv virtualenvwrapper
Clone the repo, set up a python virtualenvironment, and install requirements:
$ git clone https://github.com/18F/emoji_search.git ~/emoji_search
$ cd ~/emoji_search
$ mkvirtualenv emoji_search
$ pip install -r requirements.txt
If you always plan on running the script with the virtualenv activated, you can skip this step.
Activate virtualenv if necessary:
$ workon emoji_search && cd ~/emoji_search
Make script executable:
$ echo '#!'`which python`|cat - emoji_search.py > /tmp/out && mv /tmp/out emoji_search.py
$ chmod 755 emoji_search.py
You will need a Slack API key. You can get this from the Slack website. The script expects the token to be in a file in the same directory, which will not be checked in to Github. To create it, run the following from the ~/emoji_search directory, subbing in your token and making sure to keep the quotes:
echo "API_TOKEN = '<MY-API-TOKEN>'" > api_token.py
If you did not make the script executable in the optional step above use python ~/emoji_search/emoji_search.py
in place of ~/emoji_search/emoji_search.py
below:
To query for messages reacted to with the 🌲 emoji between Nov 2, 2015 and Oct 31, 2015 and write the output to a file called evergreen.txt in the current directory, run:
~/emoji_search/emoji_search.py --emoji evergreen_tree \
--startdate 10-31-2015 \
--enddate 11-02-2015 \
--outfile evergreen.txt
All flags are optional except for --emoji. If no destination file is provided, results will be written to the terminal.
18F's work on this project is in the worldwide public domain.
This project is in the public domain within the United States, and copyright and related rights in the work worldwide are waived through the CC0 1.0 Universal public domain dedication.
All contributions to this project will be released under the CC0 dedication. By submitting a pull request, you are agreeing to comply with this waiver of copyright interest.