Lecture 1 Exercises — Command Line Foundations (1-week workload)

Goal: internalize shell fluency, scripting discipline, and reproducible environment setup. Submit a short report (Markdown or PDF) describing your approach, commands used, and lessons learned. Keep scripts in this repo under codes/lab01 or your personal fork.

Exercise 1 — Personal shell profile & prompt hygiene¶

1. Starting from the base image used in lecture (Zsh or Bash), craft a reproducible shell profile:

   • Define at least three aliases that speed up navigation and Git interactions.

   • Write one shell function mkproj <name> that creates a project folder with subdirs src/, data/, notes/ and initializes Git.

   • Configure a prompt that shows the current Git branch and changes color when the last command failed.

2. Store the profile snippets in ~/dotfiles/lecture01/ and provide a setup.sh that symlinks them into ~/.bashrc or ~/.zshrc.

3. Document testing steps: open a fresh shell to verify aliases, run mkproj demo and confirm structure + git init.

Exercise 2 — Portable log analyzer¶

1. Write a POSIX-compliant shell script bin/log_analyzer.sh that reads a glob of log files (e.g., logs/*.log) and prints:

   • Total number of lines, warnings ([WARNING]), and errors ([ERROR]).

   • Top five most frequent warning messages.

2. Support two flags:

   • -p pattern to filter lines before counting.

   • -o file to send the summary to a text file instead of stdout.

3. Add usage/help text and exit codes for bad inputs.

4. Prove portability: run under both Bash and dash (or BusyBox sh). Mention any differences observed.

Exercise 3 — Data pipeline with pipes & tools¶

1. Fetch the latest release list of this repository (use curl + GitHub API or the locally cloned repo if offline).

2. Build a pipeline that produces a table with columns tag, published_at, commit_sha (first 10 chars).

3. Save the command sequence in pipelines/releases.sh and ensure it accepts an optional --json path.json argument to read from a saved file instead of hitting the network.

4. Include shellcheck output (or a justification if unavailable) to show the script passes linting.

Submission checklist¶

• Provide paths to your scripts/profile files, plus sample invocations.

• Compress the working directory or push to a fork so the instructor can reproduce.

• Highlight one stumbling block and how you solved it.