Dati
921 API attive
Media Bias API
Political-bias and factual-reporting ratings for 1,350+ news sources, sourced from AllSides and Media Bias/Fact Check. Look up any outlet by domain or name to get its left/center/right political lean (5-point scale) and high/mixed/low factual reliability — ideal for news aggregators, media-literacy tools and content moderation.
Baking Pan Scaler API
Baking-pan maths as an API, computed locally and deterministically — the area and scale-factor numbers a baker resizes a recipe between pans with. The trick everyone gets wrong is that a recipe scales by the pan’s AREA, not its diameter, so a 10-inch round holds far more batter than a 9-inch. The area endpoint gives the surface area of any pan — round and springform as π/4·d², square as s², rectangle as length × width, and bundt or tube pans as the ring (the outer circle minus the centre hole) — so a 9-inch round is 63.6 in², an 8-inch square 64 and a 9×13 is 117; add a depth and it returns the volume in cubic inches and cups. The convert endpoint gives the scale factor to move a recipe from one pan to another, factor = target area ÷ source area: a 9-inch round to a 9×13 is ×1.84, and two 8-inch rounds really do equal one 9×13. Pass an ingredient amount and it scales it for you, with a note to keep the batter depth similar and adjust the bake time. Everything is computed locally and deterministically, so it is instant and private. Ideal for baking, recipe, meal-prep and kitchen app developers, recipe-scaling and substitution tools, and culinary software. Pure local computation — no key, no third-party service, instant. Inches. Live, nothing stored. 2 compute endpoints. For ingredient unit conversion use a cooking API.
BJT Transistor API
Bipolar-junction-transistor (BJT) circuit maths as an API, computed locally and deterministically. The currents endpoint relates the three terminal currents through the DC current gain β (hFE): the collector current Ic = β·Ib, the emitter current Ie = (β+1)·Ib and the common-base gain α = β/(β+1) ≈ 1, from β and any one current. The bias endpoint analyses the operating point of the classic voltage-divider bias network — from the supply voltage, the two divider resistors, the collector and emitter resistors, β and the base-emitter drop it computes the Thévenin equivalent (Vth = Vcc·R2/(R1+R2), Rth = R1‖R2), the base current Ib = (Vth − Vbe)/(Rth + (β+1)·Re), the collector and emitter currents, the collector-emitter voltage Vce and the node voltages, and classifies the operating region as cutoff, active or saturation. The power endpoint computes the transistor's power dissipation, Pd ≈ Vce·Ic (plus Vbe·Ib), to check it against the rated maximum. Currents are in amperes, resistances in ohms and voltages in volts, with Vbe defaulting to 0.7 V for silicon. Everything is computed locally and deterministically, so it is instant and private. Ideal for electronics, amplifier-design, embedded and hobbyist app developers, biasing and operating-point tools, and electronics education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is BJT biasing; for op-amp circuits use an op-amp API and for an LED series resistor an LED-resistor API.