https://github.com/southernmethodistuniversity/dhri_python
Python Tutorial for Text Mining
https://github.com/southernmethodistuniversity/dhri_python
Last synced: about 1 year ago
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Python Tutorial for Text Mining
- Host: GitHub
- URL: https://github.com/southernmethodistuniversity/dhri_python
- Owner: SouthernMethodistUniversity
- Created: 2020-01-29T16:11:31.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2022-08-10T18:24:31.000Z (almost 4 years ago)
- Last Synced: 2025-04-10T00:51:23.335Z (about 1 year ago)
- Language: Jupyter Notebook
- Size: 2.8 MB
- Stars: 2
- Watchers: 5
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
This repo is no longer being updated. Please see the [SMU@DHRI website](https://www.smu.edu/dhri) for the most current information.
# Text Mining With Python
The associated "Introduction to HPC and M2" slides can be found [here](https://smu.box.com/s/y54cbtazhe9enfaomvb8eaxoi99jq0cn).
## Running the Notebook via JupyterLab on M2
1. Go to [hpc.smu.edu](https://hpc.smu.edu/)
2. Sign in using your SMU ID and SMU password
3. Select "ManeFrame II Shell Access" from the "Clusters" drop-down menu. (Note: If you are a new user, you might be prompted for a password. It will capture your keystrokes even if nothing you're typing appears.)
5. In the "Shell" tab type `git clone https://github.com/SouthernMethodistUniversity/DHRI_python.git` to clone the GitHub repository.
6. In the same "Shell" tab type `cd DHRI_python` to change to repository's directory to verify that it has been clone properly. (Typing `ls` should show files that have been downloaded.)
7. In the "Dashboard" tab select "JupyterLab" from the "Interactive Apps" drop-down menu.
8. Set the "Additional environment modules to load" field to `environment`.
9. Set the "Custom module paths" field to `module use $HOME/DHRI_python`.
10. Select other options required for your Jupyter instance. These options are the
same as those requested via a standard Slurm script on M2. For this tutorial:
- Partition: `htc`
- Number of hours: 3
- Number of nodes: 1
- Cores per node: 1
- GPUs per node: 0
- Memory: 6
10. Select "Launch"
11. Wait for the job to start on M2. When the job starts a new button "Connect
to JupyterLab" button will appear.
12. Select "Connect to JupyterLab"
13. The JupyterLab graphical interface will be presented and running on the M2
resource requested.
14. Double click the appropriate notebook to open it.
15. When finished using the JupyterLab instance, return to the "My
Interactive Sessions" tab in your browser and select "Delete" and "Confirm",
when prompted, to cancel the job on M2.
**NOTE:** To be sure you have the latest version of the environment and code. Everytime you log-in, you should go to "ManeFrame II Shell Access" from the "Clusters" drop-down menu and paste this command `cd DHRI_python && git pull` then hit "Enter".
## Running the Notebook via JupyterLab via a Local Docker Installation
1. Install [Docker](https://docs.docker.com/get-docker/) and run commands below in terminal shell of your choice.
2. Clone repository, `git clone https://github.com/SouthernMethodistUniversity/DHRI_python.git`.
3. Change to repository directory, `cd DHRI_python`.
4. `docker run --rm -p 8888:8888 -e JUPYTER_ENABLE_LAB=yes -v $HOME:/home/jovyan rkalescky/text_mining_with_python:latest`
5. Copy and paste the last URL given into your web browser and the JupyterLab graphical interface will be presented.