{"id":50508876,"url":"https://github.com/denisecase/nlp-01-getting-started","last_synced_at":"2026-06-02T18:31:14.424Z","repository":{"id":343155405,"uuid":"1176329430","full_name":"denisecase/nlp-01-getting-started","owner":"denisecase","description":"Professional Python project for Web Mining and Applied NLP.","archived":false,"fork":false,"pushed_at":"2026-03-09T05:16:03.000Z","size":463,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-03-09T09:58:10.349Z","etag":null,"topics":["data-analytics","github-actions","natural-language-processing","nlp","professional-python","python","reproducible-workflows","src-layout"],"latest_commit_sha":null,"homepage":"https://denisecase.github.io/nlp-01-getting-started/","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# nlp-01-getting-started\n\n[![Python 3.14+](https://img.shields.io/badge/python-3.14%2B-blue?logo=python)](#)\n[![MIT](https://img.shields.io/badge/license-see%20LICENSE-yellow.svg)](./LICENSE)\n\n\u003e Professional Python project for Web Mining and Applied NLP.\n\nWeb Mining and Applied NLP focus on retrieving, processing, and analyzing text from the web and other digital sources.\nThis course builds those capabilities through working projects.\n\nIn the age of generative AI, durable skills are grounded in real work:\nsetting up a professional environment,\nreading and running code,\nunderstanding the logic,\nand pushing work to a shared repository.\nEach project follows a similar structure based on professional Python projects.\nThese projects are **hands-on textbooks** for learning Web Mining and Applied NLP.\n\n## This Project\n\nThis is the **getting started** project.\nThe goal is to copy this repository, set up your environment, run the example script and notebook, and push your work to GitHub.\nThen, you'll change the authorship to make the project yours and explore the structure.\nNo major code changes are required.\n\nYou'll work with just these areas:\n\n- **notebooks/** - Jupyter notebooks for exploration\n- **src/nlp/** - Python code (verifies .venv/)\n- **pyproject.toml** - update authorship, links, and dependencies\n- **zensical.toml** - update authorship and links\n\nThe goal is just to confirm you can run projects on your machine.\nOnce you get the first project running successfully,\nthe rest of the course is much easier.\n\n## First: Follow These Instructions\n\nFollow the [step-by-step workflow guide](https://denisecase.github.io/pro-analytics-02/workflow-b-apply-example-project/) to complete:\n\n1. Phase 1. **Start \u0026 Run**\n2. Phase 2. **Change Authorship**\n3. Phase 3. **Read \u0026 Understand**\n\n## Challenges\n\nChallenges are expected.\nSometimes instructions may not quite match your operating system.\nWhen issues occur, share screenshots, error messages, and details about what you tried.\nWorking through issues is an important part of implementing professional projects.\n\n## Success\n\nAfter completing Phase 1. **Start \u0026 Run**, you'll have your own GitHub project,\nrunning on your machine, and running the example will print out:\n\n```shell\n========================\nPipeline executed successfully!\n========================\n```\n\nAnd a new file named `project.log` will appear in the project folder.\n\nOnce you see it, you're 90% of the way there.\nAfter that, you'll just make the project yours and get started exploring.\n\n## Command Reference\n\nThe commands below are used in the workflow guide above.\nThey are provided here for convenience.\n\nFollow the guide for the **full instructions**.\n\n\u003cdetails\u003e\n\u003csummary\u003eShow command reference\u003c/summary\u003e\n\n### In a machine terminal (open in your `Repos` folder)\n\nAfter you get a copy of this repo in your own GitHub account,\nopen a machine terminal in your `Repos` folder:\n\n```shell\n# Replace username with YOUR GitHub username.\ngit clone https://github.com/username/nlp-01-getting-started\ncd nlp-01-getting-started\ncode .\n```\n\n### In a VS Code terminal\n\n```shell\nuv self update\nuv python pin 3.14\nuv sync --extra dev --extra docs --upgrade\n\nuvx pre-commit install\ngit add -A\nuvx pre-commit run --all-files\n\n# Later, we install spacy data model and\n# en_core_web_sm = english, core, web, small\n# It's big: spacy+data ~200+ MB w/ model installed\n#           ~350–450 MB for .venv is normal for NLP\n# uv run python -m spacy download en_core_web_sm\n\n# First, run the module\n# IMPORTANT: Close each figure after viewing so execution continues\nuv run python -m nlp.web_words_case\n\n# Then, open the notebook.\n# IMPORTANT: Select the kernel and Run All:\n# notebooks/web_words_case.ipynb\n\nuv run ruff format .\nuv run ruff check . --fix\nuv run zensical build\n\ngit add -A\ngit commit -m \"update\"\ngit push -u origin main\n```\n\n\u003c/details\u003e\n\n## Notes\n\n- Use the **UP ARROW** and **DOWN ARROW** in the terminal to scroll through past commands.\n- Use `CTRL+f` to find (and replace) text within a file.\n\n## Example Artifact (Output)\n\n![Word Cloud Example](docs/images/word_cloud_example.png)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdenisecase%2Fnlp-01-getting-started","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdenisecase%2Fnlp-01-getting-started","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdenisecase%2Fnlp-01-getting-started/lists"}