API Marketplace

Inferential-statistics maths as an API, computed locally and deterministically. The samplesize endpoint computes how many respondents a survey or experiment needs for a proportion, n = Z²·p(1−p)/E², from a confidence level and a margin of error (using p = 0.5 for the most conservative size), with a finite-population correction when the population is known. The confidence endpoint builds a confidence interval for a mean (estimate ± Z·σ/√n) or a proportion (p ± Z·√(p(1−p)/n)), returning the standard error, margin of error and the lower and upper bounds. The ztest endpoint runs a one-sample z-test, z = (x̄ − μ₀)/(σ/√n), and returns the z-score, the one- or two-tailed p-value and whether the result is significant at the chosen alpha. The z-scores come from an exact inverse-normal and the p-values from the normal CDF. Everything is computed locally and deterministically, so it is instant and private. Ideal for A/B-testing, survey, research and analytics app developers, experiment dashboards and data-science tools, and education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is inferential statistics; for descriptive statistics use a statistics API and for probability distributions use a probability API.

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100.0%

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78ms

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4,030

Descriptive-statistics maths as an API, computed locally and deterministically. The descriptive endpoint summarises a list of numbers — the count, sum, mean, median, mode, minimum, maximum and range, the population and sample variance and standard deviation, and the quartiles Q1/Q2/Q3 with the interquartile range by Tukey's method. The correlation endpoint computes the Pearson correlation coefficient r between two equal-length series — from −1 (perfect inverse) through 0 (none) to +1 (perfect direct) — along with R² and the covariance. The regression endpoint fits a least-squares line y = a + b·x, returning the slope, intercept and R², the equation, and an optional prediction for a given x. Data is accepted as a JSON array or a comma-separated list. Everything is computed locally and deterministically, so it is instant and private. Ideal for data-analysis, dashboard, research and education app developers, reporting and BI tools, and spreadsheet replacements. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is descriptive statistics; for probability distributions and combinatorics use a probability API.

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75ms

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4,403

API de matemáticas de métricas de marketing digital, calculadas local y determinísticamente. El endpoint ads calcula KPIs de campaña a partir de dos de los siguientes: gasto, impresiones, clics y conversiones: el CPM (costo por mil impresiones), el CPC (costo por clic), el CTR (tasa de clics), la tasa de conversión y el CPA (costo por adquisición). El endpoint roas calcula el retorno de la inversión publicitaria, ROAS = ingresos ÷ gasto, el porcentaje de ROI y la ganancia bruta, y — dado un margen bruto — el ROAS de equilibrio de 1 ÷ margen. El endpoint ltv calcula el valor de vida del cliente, valor promedio del pedido × frecuencia de compra × vida útil × margen bruto, y, con el gasto de marketing y el número de nuevos clientes, el costo de adquisición de clientes, la importantísima relación LTV:CAC y el período de recuperación del CAC en meses. Todo se calcula local y determinísticamente, por lo que es instantáneo y privado. Ideal para desarrolladores de aplicaciones de marketing, publicidad, comercio electrónico y crecimiento, paneles de campaña y herramientas de informes, y calculadoras de agencias. Cálculo local puro — sin clave, sin servicio de terceros, instantáneo. En vivo, nada almacenado. 3 endpoints. Esto son matemáticas de métricas de marketing; para matemáticas de porcentajes use una API de porcentajes y para conversión de divisas use una API de divisas.

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96ms

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3,880

Personal-savings planning maths as an API, computed locally and deterministically. The future endpoint computes the future value of regular saving — FV = initial·(1+r)^n + deposit·((1+r)^n − 1)/r with the rate compounded monthly — and breaks it into the total you put in and the interest earned. The goal endpoint works backwards: the monthly deposit needed to reach a target by a date, (target − initial·(1+r)^n)·r / ((1+r)^n − 1), and tells you when an initial sum already grows to the target by itself. The emergency endpoint sizes an emergency fund as a number of months of expenses (3–6 is the usual advice), reports the shortfall against current savings and, with a monthly saving amount, how many months it takes to get there. Everything is computed locally and deterministically, so it is instant and private. Ideal for personal-finance, budgeting and fintech app developers, savings-goal and money-coaching tools, and banking dashboards. Pure local computation — no key, no third-party service, instant. Live, nothing stored. Estimates, not financial advice. 3 endpoints. This is savings planning; for loans and mortgages use a loan API and for NPV/IRR use a finance-calc API.

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100.0%

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79ms

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3,249

Asset-depreciation maths as an API, computed locally and deterministically, returning the full year-by-year schedule. The straight-line endpoint spreads the depreciable amount evenly, annual = (cost − salvage) / life, with the book value falling to the salvage value over the asset life. The declining-balance endpoint is accelerated — each year depreciates the current book value times factor/life (a factor of 2 is the double-declining method) — and it is capped so the book value never drops below salvage. The sum-of-years-digits endpoint is also accelerated, front-loading the expense: year t depreciates (remaining life / SYD) × (cost − salvage), where SYD = n(n+1)/2. Each method returns the depreciation, accumulated depreciation and book value for every year. Everything is computed locally and deterministically, so it is instant and private. Ideal for accounting, ERP, asset-management and bookkeeping app developers, fixed-asset registers, and finance dashboards. Pure local computation — no key, no third-party service, instant. Live, nothing stored. General accounting maths — tax rules such as MACRS differ by jurisdiction. 3 endpoints. This is asset depreciation; for NPV and IRR use a finance-calc API and for loans use a loan API.

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77ms

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Lumber and framing material-estimation maths as an API, computed locally and deterministically. The boardfeet endpoint computes board feet — the standard volume unit for sawn timber, (thickness_in × width_in × length_ft) ÷ 12 — for a quantity of boards, with the total board feet and linear feet. The studs endpoint frames a wall: the number of vertical studs, ceil(wall length ÷ spacing) + 1 (16-inch ≈ 0.4064 m or 24-inch ≈ 0.6096 m centres), with two extra studs per opening, plus the plate boards for the top and bottom plates. The cost endpoint totals the lumber either by board foot (board feet × price per board foot) or by piece (pieces × price per piece). Everything is computed locally and deterministically, so it is instant and private. Ideal for construction, carpentry and DIY app developers, framing and material take-off tools, and lumberyard and builder calculators. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is lumber and framing estimation; for drywall sheets use a drywall API and for concrete use a concrete API.

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84ms

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4,756

Drywall (plasterboard) material-estimation maths as an API, computed locally and deterministically. The sheets endpoint computes how many boards a wall or ceiling needs — the area (given directly, or as perimeter × height, or length × width) divided by the sheet area, with a waste allowance — and the number of screws (about 32 per standard sheet). The compound endpoint estimates the joint compound in kilograms and the joint tape in metres for taping and finishing the boarded area, with adjustable per-square-metre factors for your product and number of coats. The cost endpoint totals the project from the sheets and their price plus the compound and tape. The standard 2.4 × 1.2 m board is assumed unless you override it. Everything is computed locally and deterministically, so it is instant and private. Ideal for construction, renovation and trade app developers, drywall and plastering estimators, and builder and retailer tools. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is drywall material estimation; for insulation R-values use a U-value API and for wall paint use a paint API.

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81ms

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3,893

Wallpaper-estimating maths as an API, computed locally and deterministically. The rolls endpoint uses the proper drop method: it works out how many full-height drops come from each roll, floor(roll length ÷ (wall height + pattern repeat)), how many drops the room perimeter needs, ceil(perimeter ÷ roll width), and from those the rolls required — so a larger pattern repeat correctly increases the count. The simple endpoint gives a quick area-based estimate, rolls = ceil(wall area·(1+waste) ÷ roll coverage), handy for plain papers. The cost endpoint totals the project from the rolls and price per roll plus the adhesive, with one tub of paste hanging about five rolls. The standard roll of 10.05 m × 0.53 m is assumed unless you override it. Everything is computed locally and deterministically, so it is instant and private. Ideal for home-decor, renovation and trade app developers, DIY and room-planning tools, and decorator and retailer calculators. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is wallpaper estimation; for wall paint use a paint API and for floor tiles use a flooring API.

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80ms

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4,222

Flooring and tiling material-estimation maths as an API, computed locally and deterministically. The tile endpoint computes how many tiles a floor needs — the floor area (given directly or as length × width) divided by the tile area, with a waste allowance for cuts and breakage (10 % by default) — and, given the tiles per box, how many boxes to buy. The packs endpoint sizes laminate, vinyl or carpet from the coverage printed on each pack: packs = ceil(area·(1+waste) / coverage per pack), with the total coverage supplied. The grout endpoint estimates the grout in kilograms for a tiled area from the tile size, the joint width and the tile thickness, ((A+B)/(A·B))·joint·thickness·density per square metre. Everything is computed locally and deterministically, so it is instant and private. Ideal for home-improvement, renovation and trade app developers, DIY and material-ordering tools, and builder and retailer calculators. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is floor-covering estimation; for wall paint use a paint API, for roofing use a roofing API and for concrete use a concrete API.

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85ms

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4,281

Matemáticas de gestión de inventarios como API, calculadas local y determinísticamente. El endpoint eoq calcula la cantidad económica de pedido, EOQ = √(2·D·S/H) a partir de la demanda anual, el costo por pedido y el costo de mantenimiento por unidad por año — el tamaño de pedido que minimiza el costo total — y devuelve el número de pedidos por año, los días entre pedidos y los costos anuales de pedido, mantenimiento y totales (que son iguales en el EOQ). El endpoint reorder calcula el punto de reorden, demanda diaria × tiempo de entrega + stock de seguridad, el nivel de stock en el que se debe realizar el próximo pedido. El endpoint safety calcula el stock de seguridad para un nivel de servicio objetivo, Z × σ × √tiempo_de_entrega, donde Z es el valor de la distribución normal para el nivel de servicio (95 % da 1.645) encontrado mediante un cálculo exacto de la inversa de la normal, por lo que cualquier nivel de servicio funciona. Todo se calcula local y determinísticamente, por lo que es instantáneo y privado. Ideal para desarrolladores de aplicaciones de comercio electrónico, venta minorista, almacenes y cadena de suministro, herramientas de planificación de existencias y adquisiciones, y paneles de operaciones. Cálculo local puro — sin clave, sin servicio de terceros, instantáneo. En vivo, nada almacenado. 3 endpoints. Esto es optimización de inventarios; para punto de equilibrio y costo-volumen-beneficio, use una API de punto de equilibrio.

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84ms

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3,606

Break-even and cost-volume-profit maths as an API, computed locally and deterministically. The breakeven endpoint computes the break-even point of a product — the units you must sell to cover all costs, fixed costs ÷ (price − variable cost) — together with the break-even revenue, the contribution margin per unit and the contribution-margin ratio. The target endpoint computes the units and revenue needed to reach a target profit, (fixed costs + target profit) ÷ contribution margin. The margin-of-safety endpoint takes an actual sales level (in units or revenue) and returns the margin of safety — how far sales can fall before a loss — both in units and as a percentage, plus the profit at that level. Everything is computed locally and deterministically, so it is instant and private. Ideal for business, startup and finance app developers, pricing and product-planning tools, and small-business and accounting dashboards. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is cost-volume-profit analysis; for per-unit margin and markup pricing use a margin API.

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78ms

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3,686

Matemáticas de altura adulta predicha como una API, calculada local y determinísticamente. El endpoint midparental aplica el método de Tanner de altura parental media — para un niño (padre + madre + 13)/2 y para una niña (padre + madre − 13)/2 en centímetros — y devuelve la altura objetivo junto con el rango de ±8.5 cm dentro del cual cae la mayoría de los niños. El endpoint double utiliza la conocida regla general de que la altura adulta de un niño es aproximadamente el doble de su altura a los dos años. El endpoint restante toma la altura actual de un niño y una altura adulta predicha (dada directamente o calculada a partir de los padres) y devuelve el crecimiento restante y el porcentaje de altura adulta ya alcanzado. Todo se calcula local y determinísticamente, por lo que es instantáneo y privado. Ideal para desarrolladores de aplicaciones de crianza, pediatría y salud familiar, herramientas de seguimiento de crecimiento e hitos, y paneles de bienestar. Cálculo local puro — sin clave, sin servicio de terceros, instantáneo. En vivo, nada almacenado. Estimaciones poblacionales con amplia variación individual — no es consejo médico. 3 endpoints. Esto es predicción de altura adulta; para IMC y composición corporal use una API de IMC.

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81ms

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3,563

Trailer-towing weight maths as an API, computed locally and deterministically. The tongue endpoint computes the tongue (hitch) weight as a percentage of the loaded trailer weight and reports the recommended 10–15 % range — too little tongue weight is the main cause of trailer sway. The capacity endpoint computes the maximum trailer weight a tow vehicle can pull, GCWR − curb weight − payload (the passengers and cargo in the vehicle), and checks a proposed trailer against it with the margin remaining. The payload endpoint computes the vehicle payload still available once the trailer is hitched, GVWR − curb weight − tongue weight, since the tongue weight presses down on the tow vehicle and counts against its payload rating. Everything is computed locally and deterministically, so it is instant and private. Ideal for RV, caravan, trailer and fleet apps, tow-vehicle matching and load-planning tools, and automotive calculators. Pure local computation — no key, no third-party service, instant. Live, nothing stored. Guidance only — follow the manufacturer's ratings. 3 endpoints. This is trailer-towing weights; for tyre size and rolling circumference use a tyre API.

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76ms

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3,655

Exercise calorie-burn maths as an API, computed locally and deterministically with the MET (metabolic-equivalent) method. The activity endpoint computes the calories burned by an activity, calories = MET × weight × hours, taking the MET value directly or from a named-activity table (walking, running, cycling, swimming, HIIT, rowing, yoga, weightlifting and more), and returns the calories per minute. The steps endpoint turns a step count into distance and calories: the stride is estimated from height (about 0.415 × height for walking, 0.65 for running), the distance is steps × stride, and the energy is the distance times bodyweight times a net cost of roughly 0.5 kcal/kg/km walking or 1.0 running. The duration endpoint works backwards, giving the minutes of an activity needed to burn a target number of calories. Everything is computed locally and deterministically, so it is instant and private. Ideal for fitness, activity-tracking and weight-management app developers, workout and step-counter tools, and wellness dashboards. Pure local computation — no key, no third-party service, instant. Live, nothing stored. Estimates only. 3 endpoints. This is activity energy expenditure; for resting metabolism and TDEE use a BMR API.

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79ms

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Hydration and fluid-balance maths as an API, computed locally and deterministically. The daily endpoint estimates the daily fluid need from bodyweight (about 35 ml per kilogram), the minutes of exercise (about 12 ml per minute) and the climate (hot adds 500 ml, very hot 1000 ml, cold subtracts 200 ml), reported in millilitres, litres and 250 ml glasses. The sweat endpoint computes the sweat rate and the degree of dehydration from a before-and-after body weight, the fluid drunk and the duration — sweat loss = (pre − post) + intake − urine, with 1 kg of lost mass treated as 1 litre, and it flags when losses pass the 2 % of body mass where performance falls off. The rehydrate endpoint computes the post-exercise rehydration target, about 1.5 times the fluid deficit to cover ongoing urine losses, with a sodium note for larger losses. Everything is computed locally and deterministically, so it is instant and private. Ideal for fitness, sports and wellness app developers, endurance-training and hydration-reminder tools, and health dashboards. Pure local computation — no key, no third-party service, instant. Live, nothing stored. General guidance, not medical advice. 3 endpoints. This is fluid balance; for basal calories use a BMR API and for heart-rate zones use a heart-rate API.

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81ms

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4,678

Estimación de la capacidad aeróbica (VO2 max) como API, calculada local y determinísticamente. El endpoint cooper estima el VO2 max a partir de la prueba de carrera de 12 minutos de Cooper, VO2max = (distancia − 504.9)/44.73, desde la distancia recorrida en doce minutos. El endpoint resting utiliza el método de frecuencia cardíaca en reposo (Uth-Sørensen), VO2max = 15.3 × (FCmax/FCreposo), con la frecuencia cardíaca máxima tomada directamente o como 220 − edad — un pulso en reposo más bajo indica mejor condición física. El endpoint rockport aplica la prueba de caminata de una milla de Rockport, una fórmula de regresión múltiple sobre edad, peso, sexo, tiempo de caminata y frecuencia cardíaca al finalizar, la prueba de campo submáxima más accesible. Cada resultado viene con una clasificación general de condición física desde pobre hasta superior y el valor en mL/kg/min. Todo se calcula local y determinísticamente, por lo que es instantáneo y privado. Ideal para desarrolladores de aplicaciones de fitness, running y entrenamiento de resistencia, herramientas de coaching y evaluación, paneles de ciencias del deporte y bienestar. Cálculo local puro — sin clave, sin servicio de terceros, instantáneo. En vivo, nada almacenado. Solo estimaciones, no consejo médico. 3 endpoints. Esto es estimación de capacidad aeróbica; para zonas de frecuencia cardíaca use una API de frecuencia cardíaca y para metabolismo basal use una API de BMR.

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77ms

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4,112

Body-composition maths as an API, computed locally and deterministically. The bmi endpoint computes the body mass index, BMI = weight/height², classifies it on the WHO scale (underweight, normal, overweight, obese) and returns the healthy weight range for the person's height. The idealweight endpoint computes the ideal body weight by the four classic formulas — Devine, Robinson, Miller and Hamwi — each a base weight plus an increment for every inch of height above five feet, and their average. The bodyfat endpoint estimates body-fat percentage by the US Navy circumference method from the neck and waist (and hip for women) and the height, classifies it from essential to high, and — given a weight — splits it into fat mass and lean mass. Everything is computed locally and deterministically, so it is instant and private. Ideal for fitness, health and wellness app developers, body-tracking and coaching tools, gym and clinic dashboards, and self-assessment apps. Pure local computation — no key, no third-party service, instant. Live, nothing stored. Estimates only, not medical advice. 3 endpoints. This is body composition; for basal metabolic rate and calories use a BMR API.

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75ms

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3,780

Energy-expenditure and nutrition maths as an API, computed locally and deterministically. The bmr endpoint computes the basal metabolic rate — the calories the body burns at rest — from weight, height, age and sex, using the modern Mifflin-St Jeor equation (BMR = 10·kg + 6.25·cm − 5·age + 5 for men, −161 for women) and reporting the classic revised Harris-Benedict value alongside for comparison. The tdee endpoint computes the total daily energy expenditure, TDEE = BMR × an activity factor from sedentary (1.2) to very active (1.9), and the goal calories for maintenance, mild and standard weight loss and weight gain — a 500 kcal/day deficit or surplus is about 0.45 kg per week. The macros endpoint splits a calorie target into protein, fat and carbohydrate grams, with protein set per kilogram of bodyweight (4 kcal/g protein and carbs, 9 kcal/g fat). Everything is computed locally and deterministically, so it is instant and private. Ideal for fitness, nutrition and health-app developers, diet and meal-planning tools, gym and coaching apps, and wellness dashboards. Pure local computation — no key, no third-party service, instant. Live, nothing stored. Estimates only, not medical advice. 3 endpoints. This is metabolic-rate and calorie maths; for body-mass-index use a BMI calculator.

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80ms

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4,047

Gear-train ratio, speed and torque maths as an API, computed locally and deterministically. The ratio endpoint computes the gear ratio of a single pair from the driver and driven tooth counts (or pitch diameters), ratio = N_driven/N_driver, classifies it as a reduction (more torque, less speed) or an overdrive, and — given an input speed and torque — returns the output speed (input/ratio) and the output torque (input·ratio·efficiency). The train endpoint computes a compound gear train: the overall ratio is the product of the individual stage ratios, and it returns each stage ratio, the output speed and torque, noting that idler gears change only the direction of rotation, not the ratio. The solve endpoint finds the missing one of the input speed, the output speed and the ratio from the other two — for example, the ratio needed to drop a 1500 rpm motor to a 500 rpm output. Everything is computed locally and deterministically, so it is instant and private. Ideal for drivetrain, robotics and machine-design tools, gearbox and transmission selection, bicycle and vehicle gearing, and mechanical-engineering education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is gear-train ratio and torque; for spur-gear tooth geometry use a spur-gear API.

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74ms

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3,511

Matemática de propriedades coligativas para soluções como uma API, computada local e deterministicamente. O endpoint osmótico calcula a pressão osmótica pela equação de van 't Hoff, π = i·M·R·T, a partir da molaridade, temperatura e fator de van 't Hoff (número de partículas dissolvidas por unidade de fórmula — 1 para açúcar, 2 para NaCl, 3 para CaCl₂), reportada em atmosferas, bar e quilopascals, e também resolve a molaridade a partir de uma pressão medida. O endpoint de congelamento calcula o abaixamento do ponto de congelamento, ΔTf = i·Kf·m, a partir da molalidade e da constante crioscópica (1,86 °C·kg/mol para água), e o novo ponto de congelamento. O endpoint de ebulição calcula a elevação do ponto de ebulição, ΔTb = i·Kb·m, a partir da constante ebulioscópica (0,512 °C·kg/mol para água), e o novo ponto de ebulição. Tudo é computado local e deterministicamente, portanto é instantâneo e privado. Ideal para ferramentas de química, biologia e ciência de alimentos, estimativas de osmose reversa e dessalinização, formulação de anticongelantes e degelo, aplicações de laboratório e educação. Computação puramente local — sem chave, sem serviço de terceiros, instantâneo. Ao vivo, nada armazenado. 3 endpoints. Isto é química de propriedades coligativas; para diluição de soluções use uma API de diluição e para pH e tampões use uma API de pH.

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75ms

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4,006

Particle settling-velocity maths as an API, computed locally and deterministically. The stokes endpoint computes the terminal settling velocity of a small spherical particle by Stokes' law, vt = (ρp − ρf)·g·d²/(18·μ), from the particle diameter and density, the fluid density and the dynamic viscosity, and checks the particle Reynolds number to tell you whether the creeping-flow assumption (Re < 1) still holds — a negative velocity means a buoyant particle that rises. The terminal endpoint computes the drag-based terminal velocity for larger, faster particles, vt = √(4·g·d·(ρp − ρf)/(3·Cd·ρf)), from a drag coefficient (≈0.44 in the turbulent Newton regime). The time endpoint computes the time for a particle to settle through a given depth, t = height/vt, taking the velocity directly or deriving it from the particle properties via Stokes. Everything is computed locally and deterministically, so it is instant and private. Ideal for water- and wastewater-treatment, mineral-processing and environmental-engineering tools, clarifier and settling-tank design, sediment and aerosol analysis, and engineering education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is particle sedimentation; for pipe-flow Reynolds/Froude/Mach numbers use a Reynolds API.

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79ms

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4,135

Heating and cooling degree-day maths as an API, computed locally and deterministically. The daily endpoint computes the heating degree days, HDD = max(0, base − mean), and the cooling degree days, CDD = max(0, mean − base), for a single day from a base temperature and the daily mean — or the minimum and maximum, since the mean is taken as their average. The period endpoint sums the degree days over a list of daily temperatures (means or min/max pairs), returning the total HDD and CDD, the count of heating and cooling days and the average temperature — the standard way to characterise a heating or cooling season. The energy endpoint turns degree days into an energy estimate: the heat delivered is UA·DD·24/1000 kWh from the building heat-loss coefficient, the fuel or electricity input is that divided by the boiler efficiency (or a heat-pump COP), and — with an energy price — the cost. Everything is computed locally and deterministically, so it is instant and private. Ideal for building-energy, HVAC and facilities tools, heating-bill and fuel-budget estimation, weather-normalisation and energy-benchmarking apps, and engineering education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is degree-day demand estimation; for U-value and heat-loss fabric calculations use a U-value API.

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83ms

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3,467

Belt-conveyor design maths as an API, computed locally and deterministically. The capacity endpoint computes the throughput of a belt conveyor — the volumetric capacity Q = A·v·3600 (m³/h) from the belt cross-section and speed, and the mass capacity Q·ρ/1000 (t/h) from the bulk density — and, when only the belt width is given, estimates the cross-section as A ≈ load_factor·width². The power endpoint computes the drive power as the sum of the horizontal friction power, μ·g·(material + 2·belt + idler mass per metre)·length·speed, and the vertical lift power, ṁ·g·height, then divides by the drive efficiency to give the motor power. The tension endpoint computes the belt tensions from the effective tension Te = P/v: the tight-side tension T1 = Te·e^(μθ)/(e^(μθ)−1) and the slack-side tension T2 = T1 − Te, using the Euler-Eytelwein grip of the belt on the drive pulley. Everything is computed locally and deterministically, so it is instant and private. Ideal for bulk-materials-handling, mining and plant-design tools, conveyor selection and motor sizing, and mechanical-engineering education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is a simplified belt-conveyor model; for rope/belt capstan friction use a capstan API and for belt-drive geometry use a belt-drive API.

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80ms

Abbonati

4,207

Dimensionless flow-number maths for fluid-mechanics similitude as an API, computed locally and deterministically. The reynolds endpoint computes the Reynolds number, Re = v·L/ν = ρvL/μ — the ratio of inertial to viscous forces — from the velocity, a characteristic length (pipe diameter) and either the kinematic viscosity or the density and dynamic viscosity, and classifies the flow as laminar (< 2300), transitional (2300–4000) or turbulent (> 4000). The froude endpoint computes the Froude number, Fr = v/√(g·L) — the ratio of inertia to gravity used for open-channel and ship flows — together with the critical velocity, and tells you whether the flow is subcritical (tranquil), critical or supercritical (shooting). The mach endpoint computes the Mach number, M = v/c, with the sound speed taken directly or worked out from the air temperature, c = √(γRT), and classifies the speed as subsonic, transonic, supersonic or hypersonic. Everything is computed locally and deterministically, so it is instant and private. Ideal for fluid-mechanics, aerodynamics and hydraulics tools, model-scaling and wind-tunnel similitude, pipe-flow and open-channel analysis, and engineering education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is dimensionless-number similitude; for pipe friction pressure drop use a Darcy-Weisbach API and for open-channel uniform flow use a Manning API.

Tempo di attività

100.0%

Latenza

80ms

Abbonati

4,385