ft-ps-tester 1.0.6

A Python tester for the 42 push_swap project with controlled disorder generation and performance grading.

ft_ps_tester

A Python-based tester for the 42 push_swap project. It generates controlled random sequences with specific disorder levels, runs your push_swap executable, validates the output, and grades performance against 42 thresholds.

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Features

• Controlled disorder generation — creates sequences with precise inversion percentages.
• Four test modes — simple, medium, complex, and adaptive.
• Output validation — simulates operations to verify sorting correctness.
• Performance grading — compares operation counts against 42 thresholds (excellent / good / pass / fail).
• Failure report — concise summary of timeouts, invalid operations, and limit exceedances.
• Big-O complexity analysis (--big-o) — measures algorithmic scaling across progressively larger inputs with per-mode expectations.

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Requirements

• Python 3
• A compiled push_swap executable that accepts arguments and prints operations to stdout

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Installation

Tip: If you run into installation errors, try updating pip first:

pip install --upgrade pip
# or
pip3 install --upgrade pip

Option 1: Install from PyPI (recommended)

Using pip:

pip install ft_ps_tester

Using pip3:

pip3 install ft_ps_tester

User-local install (no sudo required — pip):

pip install --user ft_ps_tester

User-local install (no sudo required — pip3):

pip3 install --user ft_ps_tester

Using python3 -m pip:

python3 -m pip install ft_ps_tester

Note: When using --user, the ft_ps_tester binary is installed to a user-local bin/ directory (e.g. ~/.local/bin on Linux/macOS, or %APPDATA%\Python\Python3x\Scripts on Windows). Make sure this directory is on your PATH, or use the python3 -m execution methods shown below.

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Option 2: Install from source

Clone this repository:

git clone https://github.com/italoalmeida0/ft_ps_tester.git
cd ft_ps_tester

Editable / development mode (pip):

pip install -e .

Editable / development mode (pip3):

pip3 install -e .

Editable / development mode (python3 -m pip):

python3 -m pip install -e .

Normal install (pip):

pip install .

Normal install (pip3):

pip3 install .

Normal install (python3 -m pip):

python3 -m pip install .

User-local install from source (pip --user):

pip install --user -e .

User-local install from source (pip3 --user):

pip3 install --user -e .

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Option 3: Run with pipx (isolated, no install required)

If you have pipx installed, you can run the tester directly without permanently installing it:

pipx run ft_ps_tester ./push_swap

Single test run:

pipx run ft_ps_tester ./push_swap 500 complex

Or install it into an isolated environment:

pipx install ft_ps_tester

Then run normally:

ft_ps_tester ./push_swap

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Make sure your push_swap binary is compiled and executable:

make
chmod +x push_swap

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Usage

Full test suite (recommended)

Tests 100 and 500 elements across all four modes (100 tests each).

If the ft_ps_tester command is on your PATH:

ft_ps_tester ./push_swap

If the command is not found (common with --user installs), run via the module:

python3 -m ft_ps_tester ./push_swap

Or using the .cli submodule directly:

python3 -m ft_ps_tester.cli ./push_swap

Or using python directly:

python -m ft_ps_tester ./push_swap

From the cloned source directory (no install required):

python3 ft_ps_tester/cli.py ./push_swap

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Single test run

Test a specific size and mode:

ft_ps_tester ./push_swap <size> <mode>

If ft_ps_tester is not on your PATH:

python3 -m ft_ps_tester ./push_swap <size> <mode>

Or via the .cli submodule:

python3 -m ft_ps_tester.cli ./push_swap <size> <mode>

Example:

ft_ps_tester ./push_swap 500 complex

Or:

python3 -m ft_ps_tester ./push_swap 500 complex

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Failure reports (--reports)

Enable automatic report generation when a test fails (invalid sort, operation limit exceeded, or timeout). Reports are saved in the same directory as the push_swap executable.

Two files are generated per failure:

File suffix	Content
_ops_N.txt	Raw output (operations) from push_swap
_nums_N.txt	Input numbers passed to push_swap

The numbering (_1, _2, …) is shared between both files: if either an _ops_N or _nums_N file already exists, the next number is used so both files always share the same suffix.

Example:

ft_ps_tester --reports ./push_swap

If a failure occurs in the 100_simple test, the following files are created next to ./push_swap:

report_100_simple_ops_1.txt
report_100_simple_nums_1.txt

If another failure occurs later (or if one of those files already existed), the next pair becomes:

report_100_simple_ops_2.txt
report_100_simple_nums_2.txt

You can also use --reports with single test runs:

ft_ps_tester --reports ./push_swap 500 complex

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Big-O Complexity Analysis (--big-o)

Run a dedicated complexity analysis that measures how your algorithm scales with input size. This mode runs 100 tests per size per mode across progressively larger sequences:

Sizes tested: 50, 100, 200, 400, 800

For each size, the tester:

1. Generates sequences with disorder appropriate to the mode
2. Runs 3 warm-up executions (not measured) to stabilize system caches
3. Runs 100 measured executions and tracks:
   • Average number of operations
   • Average execution time
   • Growth ratio between consecutive sizes
4. Validates that the output is correctly sorted

If any test fails to sort or times out, the failure is reported and that size/mode combination is marked.

Classification criteria:

Both operations and time are classified independently using dynamic formulas based on input size n:

Operations:

Complexity	Formula (max ops)	Avg growth ratio
O(n)	1.0 * n	≤ 2.2x
O(n log n)	1.14 * n * log₂(n)	≤ 3.0x
O(n sqrt(n))	1.09 * n * sqrt(n)	≤ 3.5x
O(n²)	0.152 * n²	≤ 4.0x
O(n³)	0.00095 * n³	≤ 8.0x
O(>n³)	> 0.00095 * n³	> 8.0x

Time (ms):

Complexity	Formula (max ms)	Avg growth ratio
O(n)	0.05 * n	≤ 2.2x
O(n log n)	0.08 * n * log₂(n)	≤ 3.0x
O(n sqrt(n))	0.12 * n * sqrt(n)	≤ 3.5x
O(n²)	0.25 * n²	≤ 4.0x
O(n³)	1.0 * n³	≤ 8.0x

Example: At n=800, O(n²) max ops = 0.152 * 800² ≈ 97,280. The coefficients are calibrated for push_swap output patterns.

Expected complexity per mode:

Mode	Expected complexity	Description
simple	≤ O(n²)	Nearly sorted — should stay within n²
medium	≤ O(n sqrt(n))	Moderate disorder — better than n²
complex	O(n log n)	Heavily shuffled — optimal sort expected
adaptive	O(n²) down to O(n log n)	Should adapt based on disorder level

Usage:

ft_ps_tester --big-o ./push_swap

Or via module:

python3 -m ft_ps_tester --big-o ./push_swap

Example output:

================================================================================
  BIG-O COMPLEXITY ANALYSIS
================================================================================

>> Big-O Analysis | Mode: SIMPLE
  Size |  Tests |    Avg Ops |  Ops Ratio | Avg Time(ms) | Time Ratio | Status
----------------------------------------------------------------------------------
    50 |    100 |        450 |        N/A |         2.10 |        N/A | PASS
   100 |    100 |        980 |      2.18x |         4.50 |      2.14x | PASS
   ...
----------------------------------------------------------------------------------
Ops Complexity:  O(n^2) (Avg ratio: 3.29x, Max ops at n=800: 75000)
Time Complexity: O(n log n) (Avg ratio: 2.15x, Max time(ms) at n=800: 35.20)

================================================================================
  BIG-O SUMMARY
================================================================================

Mode       | Ops Big-O    | Ops Status | Time Big-O   | Time Status | Overall | Expected
-------------------------------------------------------------------------------------------------------------------
SIMPLE     | O(n log n)   | OK         | O(n^2)       | OK          | PASS    | <= O(n^2)
MEDIUM     | O(n log n)   | OK         | O(n^2)       | FAIL        | FAIL    | <= O(n sqrt(n))
COMPLEX    | O(n log n)   | OK         | O(n^2)       | FAIL        | FAIL    | O(n log n)
ADAPTIVE   | O(n log n)   | OK         | O(n^2)       | OK          | PASS    | O(n^2) down to O(n log n)

Details by mode:
  SIMPLE   | Ops:  Avg ratio: 2.40x, Max ops at n=800: 7732
           | Time: Avg ratio: 3.90x, Max time(ms) at n=800: 206.76
  MEDIUM   | Ops:  Avg ratio: 2.40x, Max ops at n=800: 7732
           | Time: Avg ratio: 3.90x, Max time(ms) at n=800: 206.76
  COMPLEX  | Ops:  Avg ratio: 2.40x, Max ops at n=800: 7732
           | Time: Avg ratio: 3.90x, Max time(ms) at n=800: 206.76
  ADAPTIVE | Ops:  Avg ratio: 2.40x, Max ops at n=800: 7732
           | Time: Avg ratio: 3.90x, Max time(ms) at n=800: 206.76

Reference (Operations & Time):
  Simple  : Expected <= O(n^2)  (nearly sorted)
  Medium  : Expected <= O(n sqrt(n))
  Complex : Expected O(n log n) (optimal comparison sort)
  Adaptive: Expected O(n^2) down to O(n log n) (should adapt to disorder)

Note: Overall PASS requires both Ops and Time to meet expectations.

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Modes / Flags

Your push_swap must support the following flags (passed as --<mode> before the numbers):

Mode	Disorder range	Description
simple	15.0% – 19.9%	Nearly sorted sequences
medium	20.0% – 49.9%	Moderately shuffled sequences
complex	50.0% – 55.0%	Heavily shuffled sequences
adaptive	15.0% – 55.0%	Random disorder across the full spectrum

Note: If your push_swap does not implement these flags, the tester will still work if your program ignores unknown flags and simply sorts the provided numbers. However, for accurate mode-based testing, your push_swap should parse and use the flag to adjust its algorithm.

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Grading Thresholds

Size	Excellent	Good	Pass
100	< 700	< 1500	≤ 2000
500	< 5500	< 8000	≤ 12000

Results are shown with color-coded grades:

• EXCELLENT — green
• GOOD — blue
• PASS — yellow
• FAIL — red

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Example Output

Running FULL TEST SUITE for ./push_swap

>> Testing Size: 100 | Mode: SIMPLE  ..................................................
>> Testing Size: 100 | Mode: MEDIUM  ..................................................
>> Testing Size: 100 | Mode: COMPLEX ..................................................
>> Testing Size: 100 | Mode: ADAPTIVE..................................................
>> Testing Size: 500 | Mode: SIMPLE  ..................................................
>> Testing Size: 500 | Mode: MEDIUM  ..................................................
>> Testing Size: 500 | Mode: COMPLEX ..................................................
>> Testing Size: 500 | Mode: ADAPTIVE..................................................

========================================================================================
PERFORMANCE SUMMARY
========================================================================================
SIZE   | MODE     | MAX (GRADE)        | MIN (GRADE)        | AVG (GRADE)        | FAILS
----------------------------------------------------------------------------------------
100    | SIMPLE   | 450 (EXCELLENT)    | 320 (EXCELLENT)    | 380 (EXCELLENT)    | 0
100    | MEDIUM   | 1200 (GOOD)        | 900 (EXCELLENT)    | 1050 (GOOD)        | 0
...

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License

This project is licensed under the MIT License.