PyScience Lab Downloads & RevenuePyScience Lab · App Store
Not in any tracked top chart right now.
Updated 9 Nov 2026 · rankings refresh through the day
DeveloperSimTeCon GmbH
CategoryEducation
Price11,000 KRW
Released
Rating★ 0.0 (0)
Version2.5
Age rating4+
First seen by us
28 Oct 2026
📈Dropped out of every chart we track🆕First spotted by AppInsider📦Version 2.5🆕Released on the App Store
Full timeline · 4 events
- 📈PyScience Lab dropped out of every chart we trackLast seen 31 Oct
- 🆕PyScience Lab first spotted by AppInsider#9 in Top Paid · Education · South Korea
- 📦PyScience Lab version 2.5* Updated UI for improved accessibility and usability.
* Fixed minor bugs and optimized performance. - 🆕PyScience Lab released on the App Store
Collected from the stores by AppInsider since we first spotted the app. Dates are when we saw each change.
Rating
0.0 ★
0 ratings
Measured
PyScience Lab on the App Store
App details
App ID
6737474386
Publisher
SimTeCon GmbH
On the store since
Oct 2024
2 years on the store
Minimum OS
iOS 16.4+
iPhone 8 and later
Devices
iPhone · iPad
Universal purchase
Content rating
4+
Languages
1
EN
Size
103 MB
Where it ranks now
Every top chart it appears in across 30 countries.
| Country | Charts | Rank |
|---|---|---|
| Not charting right now. | ||
Ratings
App Store, worldwide.
Rating
0.0 ★
0 ratings
Measured
Ratings
0
Measured
About PyScience Lab
PyScience Lab is the ultimate mobile environment to master Python for scientific computing, data work, and algorithmic thinking. Built for students, researchers, data analysts, and self-taught developers, PyScience Lab combines guided lessons, comprehensive reference guides, active recall flashcards, and an extensive problem bank into one focused study app.
Accelerate your coding skills with 1,400 coding tasks and 200 coding challenges designed to transform theory into practical programming confidence.
1,400 CODING TASKS & 200 CODING CHALLENGES
Stop passive reading and start building code. PyScience Lab features an active learning flow that reinforces every concept through targeted practice:
- 1,400 Guided Coding Tasks: Step-by-step coding exercises covering Python fundamentals, array operations, math functions, data structures, and numerical workflows.
- 200 Real-World Coding Challenges: Scenario-based problems designed to sharpen your algorithmic thinking, test edge cases, and build interview-ready problem-solving skills.
NUMPY & SCIPY REFERENCE LIBRARIES
Get concise explanations and clean code examples for essential scientific libraries:
- NumPy: Master array creation, multi-dimensional slicing, indexing, broadcasting, vectorization, linear algebra, statistics, and random sampling.
- SciPy: Review numerical integration, optimization, signal processing, interpolation, spatial transformations, and statistical distributions.
- Data Visualization: Look up practical data plotting concepts to visualize complex scientific data clearly.
ALGORITHMS & DATA STRUCTURES PATTERNS
Strengthen your technical foundation with structured modules on core computer science patterns:
- Core Patterns: Hash maps, sets, counters, array sorting, two pointers, sliding windows, and prefix sums.
- Data Structures: Binary search, min/max heaps, tries, segment trees, and Fenwick trees.
- Graph & Search Algorithms: DFS, BFS, shortest path, backtracking, dynamic programming, and bit manipulation.
- Pythonic Solutions: Understand when and why to use each pattern with clean, efficient implementation examples.
ACTIVE RECALL WITH SMART FLASHCARDS
Lock in knowledge faster with an integrated flashcard review system:
- Review definitions, syntax rules, function signatures, and algorithm logic one card at a time.
- Reveal answers, self-assess comprehension, and mark progress as you study.
- Perfect for quick 5-minute daily reviews or deep study sessions.
DISTRACTION-FREE & OPTIMIZED FOR STUDY
- Clean, High-Contrast UI: Readable typography, syntax-highlighted code blocks, and visual unit guides.
- Offline Access: Look up Python syntax and study algorithm patterns anywhere without an internet connection.
- Ad-Free Environment: Zero ads, zero pop-ups, and zero interruptions.
WHO IS PYSCIENCE LAB FOR?
- Students mastering coursework in computer science, linear algebra, and data science.
- Researchers and scientists needing quick reference guides for NumPy and SciPy s
Accelerate your coding skills with 1,400 coding tasks and 200 coding challenges designed to transform theory into practical programming confidence.
1,400 CODING TASKS & 200 CODING CHALLENGES
Stop passive reading and start building code. PyScience Lab features an active learning flow that reinforces every concept through targeted practice:
- 1,400 Guided Coding Tasks: Step-by-step coding exercises covering Python fundamentals, array operations, math functions, data structures, and numerical workflows.
- 200 Real-World Coding Challenges: Scenario-based problems designed to sharpen your algorithmic thinking, test edge cases, and build interview-ready problem-solving skills.
NUMPY & SCIPY REFERENCE LIBRARIES
Get concise explanations and clean code examples for essential scientific libraries:
- NumPy: Master array creation, multi-dimensional slicing, indexing, broadcasting, vectorization, linear algebra, statistics, and random sampling.
- SciPy: Review numerical integration, optimization, signal processing, interpolation, spatial transformations, and statistical distributions.
- Data Visualization: Look up practical data plotting concepts to visualize complex scientific data clearly.
ALGORITHMS & DATA STRUCTURES PATTERNS
Strengthen your technical foundation with structured modules on core computer science patterns:
- Core Patterns: Hash maps, sets, counters, array sorting, two pointers, sliding windows, and prefix sums.
- Data Structures: Binary search, min/max heaps, tries, segment trees, and Fenwick trees.
- Graph & Search Algorithms: DFS, BFS, shortest path, backtracking, dynamic programming, and bit manipulation.
- Pythonic Solutions: Understand when and why to use each pattern with clean, efficient implementation examples.
ACTIVE RECALL WITH SMART FLASHCARDS
Lock in knowledge faster with an integrated flashcard review system:
- Review definitions, syntax rules, function signatures, and algorithm logic one card at a time.
- Reveal answers, self-assess comprehension, and mark progress as you study.
- Perfect for quick 5-minute daily reviews or deep study sessions.
DISTRACTION-FREE & OPTIMIZED FOR STUDY
- Clean, High-Contrast UI: Readable typography, syntax-highlighted code blocks, and visual unit guides.
- Offline Access: Look up Python syntax and study algorithm patterns anywhere without an internet connection.
- Ad-Free Environment: Zero ads, zero pop-ups, and zero interruptions.
WHO IS PYSCIENCE LAB FOR?
- Students mastering coursework in computer science, linear algebra, and data science.
- Researchers and scientists needing quick reference guides for NumPy and SciPy s
Latest updates
2.5
* Updated UI for improved accessibility and usability.
* Fixed minor bugs and optimized performance.