{"bank_hash":"8ad4dea4fe0b53a67184c305f645a228a1a0d48425a7787bae5990c7e7fd023e","tasks":[{"category":"coding","group":"Data correctness","id":"coding-reconcile","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input has invoices and payments lists of {id, cents}. Sum amounts by id; payments subtract from invoices. Return a dict of nonzero outstanding amounts sorted by id, including negative overpayments. IDs are strings. Empty lists are valid.","review_status":"machine_checked_pending_owner_approval","title":"Reconcile invoices and payments"},{"category":"coding","group":"Data correctness","id":"coding-dedup","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input is a list of {id, version, value}. Keep the highest version for each id; on equal version keep the last occurrence. Return the retained objects sorted lexicographically by id. Do not mutate the input.","review_status":"machine_checked_pending_owner_approval","title":"Resolve duplicate event deliveries"},{"category":"coding","group":"Algorithms","id":"coding-intervals","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input is a list of [start,end] integer half-open intervals, with start<=end. Drop empty intervals; merge overlapping or touching intervals. Return sorted merged intervals without mutating input.","review_status":"machine_checked_pending_owner_approval","title":"Merge maintenance windows"},{"category":"coding","group":"Safety and edge cases","id":"coding-redact","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input is arbitrary JSON. Recursively remove dictionary keys whose lowercase spelling equals password, token or secret. Preserve other values and list order; never mutate the original.","review_status":"machine_checked_pending_owner_approval","title":"Redact nested customer records"},{"category":"coding","group":"Algorithms","id":"coding-rolling","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input is {events:[[day,count],...], query_days:[integer,...]}. Return totals for each query day covering inclusive days q-6 through q. Events can be unsorted, repeated or negative-day; count is nonnegative. Query order must be preserved.","review_status":"machine_checked_pending_owner_approval","title":"Calculate seven-day activity totals"},{"category":"coding","group":"Data correctness","id":"coding-allocate","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input is {total:nonnegative integer,weights:[nonnegative integer,...]}. Allocate proportionally using largest remainders: floor each share, then give leftover cents to largest fractional remainders, ties to lower index. If weights empty return []; if all zero return zeros.","review_status":"machine_checked_pending_owner_approval","title":"Allocate cents without rounding loss"},{"category":"coding","group":"Data correctness","id":"coding-csv","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input is CSV text with header customer,cents, including quoted fields. Ignore rows with a blank customer or cents that is not a signed base-10 integer. Sum by customer and return a dictionary, including zero totals. Preserve customer spelling.","review_status":"machine_checked_pending_owner_approval","title":"Parse and aggregate CSV purchases"},{"category":"coding","group":"Algorithms","id":"coding-dependencies","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input is a dict mapping each named job to prerequisite names. Include names referenced only as prerequisites. Return the lexicographically smallest valid topological order, choosing the smallest ready name at every step. Return null for any cycle.","review_status":"machine_checked_pending_owner_approval","title":"Order deployment dependencies"},{"category":"coding","group":"Data correctness","id":"coding-fifo","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input is {lots:[[quantity,unit_cents],...], sold:nonnegative integer}. Sell in lot order. Return {remaining_units,remaining_value_cents,unfilled_units}. All quantities/prices nonnegative; unfilled is sales beyond available inventory.","review_status":"machine_checked_pending_owner_approval","title":"Value remaining FIFO inventory"},{"category":"coding","group":"Algorithms","id":"coding-percentile","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input is {values:[finite numbers,...],p:number in [0,100]}. Return nearest-rank percentile: sorted values at 1-based rank max(1,ceil(p/100*n)). Return null for no values. Do not interpolate or mutate input.","review_status":"machine_checked_pending_owner_approval","title":"Calculate service latency percentiles"},{"category":"coding","group":"Safety and edge cases","id":"coding-slug","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input is a string. Apply Unicode NFKD normalization, drop combining marks, lowercase, retain only ASCII a-z and digits, replace each run of other characters with one hyphen, strip edge hyphens. Return the slug.","review_status":"machine_checked_pending_owner_approval","title":"Normalize Unicode article slugs"},{"category":"coding","group":"Safety and edge cases","id":"coding-rate","prompt":"Implement solve(data) in Python 3.9. Allowed imports: math, json, csv, io, re, collections, heapq, unicodedata. Use functions and built-in types; no custom classes, private/dunder attributes, globals/nonlocals, or async. Return only Python code, with no Markdown. Do not read files, use the network, run processes or access system state. Input is {limit:positive integer,window:positive integer,events:[{user,time},...]}. Times are nondecreasing integer seconds. Process in input order. Accept only when fewer than limit previously accepted events for that user have times strictly greater than time-window. Rejections do not consume allowance. Return a list of booleans.","review_status":"machine_checked_pending_owner_approval","title":"Apply a per-user rolling rate limit"},{"category":"math","group":"Finance","id":"math-margin","prompt":"A shop buys 240 items at $18 each. It sells 210 at $30 and 30 at $24. Platform fees are 3% of revenue plus $0.20 per sold item. Shipping costs $2.50 per sold item. Calculate revenue, profit after these costs, and profit margin as a percentage of revenue. Return only a JSON object with these keys: revenue, profit, margin_percent. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Separate markup from margin"},{"category":"math","group":"Optimization","id":"math-mix","prompt":"Make exactly 80 litres of a 35% concentrate from 20% and 60% stocks, with additive volumes. How many litres of each stock are needed? Return only a JSON object with these keys: litres_20, litres_60. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Solve a production mix"},{"category":"math","group":"Statistics","id":"math-weighted","prompt":"Campaign A has 900 visits and 45 purchases. Campaign B has 100 visits and 20 purchases. Next week A has 100 visits and 8 purchases; B has 900 visits and 162 purchases. Return each week’s total conversion percentage and next-minus-first percentage-point change. Return only a JSON object with these keys: week1_percent, week2_percent, change_points. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Aggregate conversion rates correctly"},{"category":"math","group":"Probability","id":"math-bayes","prompt":"A defect affects 2% of units. A detector flags 95% of defective units and 4% of nondefective units. Given a flag, calculate the probability the unit is defective, as a decimal from 0 to 1. Return only a JSON object with these keys: probability. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Interpret a screening result"},{"category":"math","group":"Finance","id":"math-loan","prompt":"A $12000 loan charges a nominal annual rate of 12%, compounded monthly, repaid with 24 equal end-of-month payments. Calculate the monthly payment and total interest, without intermediate rounding. Return only a JSON object with these keys: payment, interest. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Calculate an amortizing payment"},{"category":"math","group":"Finance","id":"math-break-even","prompt":"A product sells for $40. Variable costs are $17 production, $3 shipping, and a payment fee of 2.5% of sale price plus $0.30. Fixed monthly costs are $1870. Return the minimum whole units needed to break even and profit at that unit count. Return only a JSON object with these keys: units, profit. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Calculate break-even with fees"},{"category":"math","group":"Probability","id":"math-queue","prompt":"Each of three independent services succeeds with probability 0.98. A workflow requires all three. It retries the complete workflow once if the first attempt fails; attempts are independent. Calculate eventual success probability and expected number of complete attempts. Return only a JSON object with these keys: success_probability, expected_attempts. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Calculate independent service reliability"},{"category":"math","group":"Finance","id":"math-discount","prompt":"An item is $250 before discounts and tax. Apply 20% off, then a further 15% off the discounted price, then 8% tax. Return the final price and effective pretax discount percentage. Return only a JSON object with these keys: final_price, discount_percent. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Compare sequential and additive discounts"},{"category":"math","group":"Optimization","id":"math-capacity","prompt":"Product A uses 3 labour hours and 2 machine hours and earns $40 contribution. B uses 2 labour and 4 machine hours and earns $50. Weekly limits are 120 labour and 160 machine hours. Products must be whole units. Maximize contribution; if tied choose more A. Return A, B and contribution. Return only a JSON object with these keys: a, b, contribution. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Optimize a constrained production plan"},{"category":"math","group":"Finance","id":"math-npv","prompt":"Pay $1000 now, then receive $400 at each year end for three years. Use a 10% annual discount rate. Return net present value without rounding intermediate values. Return only a JSON object with these keys: npv. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Discount a project cash flow"},{"category":"math","group":"Finance","id":"math-allocation","prompt":"Allocate exactly $10.00 to three departments with weights 1, 1, 1. Work in cents: floor shares, then allocate remaining cents by descending fractional remainder, ties to lower index. Return integer cents for departments A, B and C. Return only a JSON object with these keys: a_cents, b_cents, c_cents. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Allocate a shared expense"},{"category":"math","group":"Statistics","id":"math-variance","prompt":"For observations 4, 7, 7, 10, 12 calculate the arithmetic mean, unbiased sample variance (denominator n-1), and standard error of the mean. Return only a JSON object with these keys: mean, sample_variance, standard_error. Numeric fields must be numbers. No Markdown or explanation.","review_status":"machine_checked_pending_owner_approval","title":"Calculate sample uncertainty"}],"version":"tested-best-bank-v1"}