Sci REPL

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SciREPL Help

Quick Start — Python

# Basic math
2 + 2

# NumPy
import numpy as np
np.linspace(0, 10, 5)

# Plotly chart (interactive)
x = np.linspace(0, 2*np.pi, 50)
plot(x, np.sin(x))

# Matplotlib (install once, then use)
%pip install matplotlib
import matplotlib.pyplot as plt
plt.plot([1, 4, 2, 3])
plt.title("Matplotlib")
plt.show()

# SymPy (LaTeX rendering)
from sympy import symbols, sqrt, solve
a, b, c, x = symbols('a b c x')
solve(a*x**2 + b*x + c, x)

# Suppress output with ;
big_array = np.arange(1000);

Installing Packages

Install pure-Python packages from PyPI with %pip install:

%pip install requests

# Then use it
import requests
r = requests.get('https://api.github.com')
print(r.status_code)

Note: Only pure-Python packages are supported. Packages with C extensions (e.g. psutil) require pre-compiled WASM wheels.

Install R packages with install.packages() or %install:

# Standard R syntax (works out of the box)
install.packages("jsonlite")
library(jsonlite)

# Or use the %install shortcut
%install dplyr

Note: Only R packages compiled to WebAssembly are available. See repo.r-wasm.org for the package list.

Quick Start — R

Switch to R using the language selector. The webR runtime (~50 MB) downloads on first use and is cached.

# Basic math
mean(c(10, 20, 30))

# Vectors and stats
x <- rnorm(100)
summary(x)

# Static plot (PNG)
plot(1:10, (1:10)^2, main = "Quadratic")

# Interactive Plotly chart
plotly(1:50, sin(1:50 / 5), title = "Sine Wave")

# Multi-trace interactive chart
mplotly(
  traces = list(
    list(x = 1:10, y = (1:10)^2, name = "x²"),
    list(x = 1:10, y = (1:10)^3, name = "x³")
  ),
  title = "Power Functions"
)

# Cross-kernel file sharing
sharedfs_write("/shared/data/from_r.txt", "Hello from R!")
sharedfs_list("/shared/data")

Quick Start — Prolog

Switch to Prolog using the language selector (Py → PL).

% Assert facts
assert(parent(tom, bob)).
assert(parent(bob, ann)).

% Query
parent(tom, X).

% Rules
assert((grandparent(X,Z) :-
    parent(X,Y), parent(Y,Z))).
grandparent(tom, Z).

Shared Filesystem

SciREPL has a SharedVFS (shared virtual filesystem) that lets all kernels read and write to the same files. Files under /shared/ and /tmp/ are accessible from every language.

Directory layout:

• /shared/data/ — Datasets (CSV, JSON, etc.)
• /shared/lib/python/ — Python modules (auto-added to sys.path)
• /shared/lib/prolog/ — Prolog modules
• /shared/lib/wasm/ — WebAssembly modules
• /shared/bin/, /shared/config/ — Utilities and config files
• /tmp/ — Temporary files (shared, not persisted)

Per-kernel behavior:

• Python — Use standard open() with /shared/ paths. Files are synced to SharedVFS automatically after each cell execution.
• R — Use sharedfs_write() and sharedfs_read() helpers to access shared files.
• Prolog — Consult files from /shared/ paths directly.
• Bash — The brush-wasm shell has a built-in bridge to SharedVFS.

# Python — write a CSV to the shared folder
with open("/shared/data/results.csv", "w") as f:
    f.write("x,y\n1,2\n3,4\n")

# R — read it back
sharedfs_read("/shared/data/results.csv")

% Prolog — consult a shared knowledge base
:- consult('/shared/lib/prolog/kb.pl').

Packages & workbooks: When you install a package or workbook from Browse Packages & Workbooks, files with /shared/ destination paths are written to SharedVFS automatically. Package files targeting a specific kernel (e.g., Prolog modules at /user/) go to that kernel's own filesystem.

Browsing files: Open Menu → Files & Storage to browse. Select SharedVFS from the dropdown to see shared files, or select a kernel (Python, Prolog) to see its internal filesystem. Use the Show empty folders checkbox to toggle visibility of empty directories.

Uploading: Use the "Upload File" button at the top of Files & Storage to upload files directly into SharedVFS. Set the destination path (default: /shared/data/) before uploading.

Export Formats

Use Export in the Menu to choose a format and image handling:

• HTML — Self-contained file with dark theme, code, and output. Choose "Separate files" for a .html.zip with an images/ folder.
• Markdown — Fenced code blocks, LaTeX math, and markdown tables. "Separate files" uses GitHub-compatible ![alt](images/X.png) references in a .md.zip.
• PDF — Opens the browser print dialog. Choose "Save as PDF" for a light-themed document.
• DOCX — Word document with code blocks, tables, images, and native Word equations (LaTeX math converted to editable OOXML formulas). Requires internet (library loaded on demand from CDN).
• LaTeX — .tex file for academic papers. Uses listings, amsmath, booktabs, graphicx. Exports as .tex.zip if images are present.
• .ipynb — Includes cell outputs (text, LaTeX, images, tables). Viewable in Jupyter and GitHub without re-execution.

Syntax highlighting: Code cells display with syntax highlighting for Python, JavaScript, R, Bash, and Prolog. Exports (HTML, DOCX) also include highlighted code.

.ipynb import with outputs: When importing a .ipynb file that already contains outputs, they are displayed directly without re-executing the code. This allows fast viewing of notebooks from Jupyter, Colab, or previous SciREPL exports.

Cell Language

Each cell remembers its language. To change a cell's language, click ✎ to edit, then use the language dropdown. Click All→ to apply the language to all code cells in the notebook.

Keyboard Shortcuts

• Shift+Enter or Ctrl+Enter — Run code
• Ctrl+F / Cmd+F or 🔍 button — Find in notebook (with replace)
• Tab — Insert 4 spaces
• ; at end of line — Suppress output

Documentation

Full documentation: GitHub README

Version

SciREPL Pro v0.9.0

Includes: Multi-language (Python + Prolog), editable cells, markdown cells, session persistence with auto-save and crash recovery, Math Mode palette, .ipynb import/export with output preservation, rich export (HTML, Markdown, PDF, DOCX with native equations, LaTeX) with syntax highlighting, virtual filesystem, search paths, URL file fetching, multi-notebook support, package format (.zip/.tar.gz)

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