From 20015bb141ed9648a725a4e1ab8f95f227e2e2f3 Mon Sep 17 00:00:00 2001 From: ryzanbui02 Date: Sat, 8 Nov 2025 03:45:54 +0000 Subject: [PATCH 1/7] refactor: move product params to models modules --- src/keepa/__init__.py | 2 +- src/keepa/interface.py | 2 +- .../product_params.py} | 0 uv.lock | 2359 +++++++++++++++++ 4 files changed, 2361 insertions(+), 2 deletions(-) rename src/keepa/{data_models.py => models/product_params.py} (100%) create mode 100644 uv.lock diff --git a/src/keepa/__init__.py b/src/keepa/__init__.py index 29b79cd..bf1c141 100644 --- a/src/keepa/__init__.py +++ b/src/keepa/__init__.py @@ -8,7 +8,6 @@ except PackageNotFoundError: __version__ = "unknown" -from keepa.data_models import ProductParams from keepa.interface import ( DCODES, KEEPA_ST_ORDINAL, @@ -24,6 +23,7 @@ process_used_buybox, run_and_get, ) +from keepa.models.product_params import ProductParams from keepa.plotting import plot_product __all__ = [ diff --git a/src/keepa/interface.py 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00:00:00 2001 From: ryzanbui02 Date: Sat, 8 Nov 2025 03:47:52 +0000 Subject: [PATCH 2/7] chore: remove typo in time_to_refill property --- src/keepa/interface.py | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/src/keepa/interface.py b/src/keepa/interface.py index 7cfdec1..486c20e 100644 --- a/src/keepa/interface.py +++ b/src/keepa/interface.py @@ -477,19 +477,19 @@ def time_to_refill(self) -> float: """ # Get current timestamp in milliseconds from UNIX epoch now = int(time.time() * 1000) - timeatrefile = self.status["timestamp"] + self.status["refillIn"] + time_at_refill = self.status["timestamp"] + self.status["refillIn"] # wait plus one second fudge factor - timetorefil = timeatrefile - now + 1000 - if timetorefil < 0: - timetorefil = 0 + time_to_refill = time_at_refill - now + 1000 + if time_to_refill < 0: + time_to_refill = 0 # Account for negative tokens left if self.tokens_left < 0: - timetorefil += (abs(self.tokens_left) / self.status["refillRate"]) * 60000 + time_to_refill += (abs(self.tokens_left) / self.status["refillRate"]) * 60000 # Return value in seconds - return timetorefil / 1000.0 + return time_to_refill / 1000.0 def update_status(self) -> dict[str, Any]: """Update available tokens.""" @@ -1900,19 +1900,19 @@ def time_to_refill(self) -> float: """Return the time to refill in seconds.""" # Get current timestamp in milliseconds from UNIX epoch now = int(time.time() * 1000) - timeatrefile = self.status["timestamp"] + self.status["refillIn"] + time_at_refill = self.status["timestamp"] + self.status["refillIn"] # wait plus one second fudge factor - timetorefil = timeatrefile - now + 1000 - if timetorefil < 0: - timetorefil = 0 + time_to_refill = time_at_refill - now + 1000 + if time_to_refill < 0: + time_to_refill = 0 # Account for negative tokens left if self.tokens_left < 0: - timetorefil += (abs(self.tokens_left) / self.status["refillRate"]) * 60000 + time_to_refill += (abs(self.tokens_left) / self.status["refillRate"]) * 60000 # Return value in seconds - return timetorefil / 1000.0 + return time_to_refill / 1000.0 async def update_status(self) -> None: """Update available tokens.""" From f9df8561618280c6a1710dc11800ea33ed46753e Mon Sep 17 00:00:00 2001 From: ryzanbui02 Date: Sat, 8 Nov 2025 04:09:44 +0000 Subject: [PATCH 3/7] feat: status model --- src/keepa/interface.py | 85 +++++++++++++++++++++++++++----------- src/keepa/models/status.py | 9 ++++ 2 files changed, 70 insertions(+), 24 deletions(-) create mode 100644 src/keepa/models/status.py diff --git a/src/keepa/interface.py b/src/keepa/interface.py index 486c20e..ff2a7c2 100644 --- a/src/keepa/interface.py +++ b/src/keepa/interface.py @@ -17,6 +17,7 @@ from tqdm import tqdm from keepa.models.product_params import ProductParams +from keepa.models.status import Status from keepa.query_keys import DEAL_REQUEST_KEYS @@ -49,7 +50,21 @@ def wrapper(target): # domain codes # Valid values: [ 1: com | 2: co.uk | 3: de | 4: fr | 5: # co.jp | 6: ca | 7: cn | 8: it | 9: es | 10: in | 11: com.mx | 12: com.br ] -DCODES = ["RESERVED", "US", "GB", "DE", "FR", "JP", "CA", "CN", "IT", "ES", "IN", "MX", "BR"] +DCODES = [ + "RESERVED", + "US", + "GB", + "DE", + "FR", + "JP", + "CA", + "CN", + "IT", + "ES", + "IN", + "MX", + "BR", +] # developer note: appears like CN (China) has changed to RESERVED2 # csv indices. used when parsing csv and stats fields. @@ -442,7 +457,12 @@ class Keepa: """ - def __init__(self, accesskey: str, timeout: float = 10.0, logging_level: str = "DEBUG"): + accesskey: str + tokens_left: int + status: Status + _timeout: float + + def __init__(self, accesskey: str, timeout: float = 10.0, logging_level: str = "DEBUG") -> None: """Initialize server connection.""" self.accesskey = accesskey self.tokens_left = 0 @@ -456,7 +476,7 @@ def __init__(self, accesskey: str, timeout: float = 10.0, logging_level: str = " # Don't check available tokens on init log.info("Using key ending in %s", accesskey[-6:]) - self.status = {"tokensLeft": None, "refillIn": None, "refillRate": None, "timestamp": None} + self.status = Status() @property def time_to_refill(self) -> float: @@ -477,7 +497,7 @@ def time_to_refill(self) -> float: """ # Get current timestamp in milliseconds from UNIX epoch now = int(time.time() * 1000) - time_at_refill = self.status["timestamp"] + self.status["refillIn"] + time_at_refill = self.status.timestamp + self.status.refillIn # wait plus one second fudge factor time_to_refill = time_at_refill - now + 1000 @@ -486,7 +506,7 @@ def time_to_refill(self) -> float: # Account for negative tokens left if self.tokens_left < 0: - time_to_refill += (abs(self.tokens_left) / self.status["refillRate"]) * 60000 + time_to_refill += (abs(self.tokens_left) / self.status.refillRate) * 60000 # Return value in seconds return time_to_refill / 1000.0 @@ -585,7 +605,11 @@ def download_graph_image( ) """ - payload = {"asin": asin, "key": self.accesskey, "domain": _domain_to_dcode(domain)} + payload = { + "asin": asin, + "key": self.accesskey, + "domain": _domain_to_dcode(domain), + } payload.update(graph_kwargs) resp = self._request("graphimage", payload, wait=wait, is_json=False) @@ -987,10 +1011,10 @@ def query( raise ValueError('Parameter "offers" must be between 20 and 100') # Report time to completion - if self.status["refillRate"] is not None: + if self.status.refillRate is not None: tcomplete = ( - float(nitems - self.tokens_left) / self.status["refillRate"] - - (60000 - self.status["refillIn"]) / 60000.0 + float(nitems - self.tokens_left) / self.status.refillRate + - (60000 - self.status.refillIn) / 60000.0 ) if tcomplete < 0.0: tcomplete = 0.5 @@ -999,7 +1023,7 @@ def query( nitems, tcomplete, ) - log.debug("\twith a refill rate of %d token(s) per minute", self.status["refillRate"]) + log.debug("\twith a refill rate of %d token(s) per minute", self.status.refillRate) # product list products = [] @@ -1801,11 +1825,11 @@ def _request( # user status is always returned if "tokensLeft" in response: self.tokens_left = response["tokensLeft"] - self.status["tokensLeft"] = self.tokens_left + self.status.tokensLeft = self.tokens_left log.info("%d tokens remain", self.tokens_left) for key in ["refillIn", "refillRate", "timestamp"]: if key in response: - self.status[key] = response[key] + setattr(self.status, key, response[key]) if status_code == "200": if raw_response: @@ -1883,8 +1907,13 @@ class AsyncKeepa: """ + accesskey: str + tokens_left: int + status: Status + _timeout: float + @classmethod - async def create(cls, accesskey: str, timeout: float = 10.0): + async def create(cls, accesskey: str, timeout: float = 10.0) -> "AsyncKeepa": """Create the async object.""" self = AsyncKeepa() self.accesskey = accesskey @@ -1892,7 +1921,7 @@ async def create(cls, accesskey: str, timeout: float = 10.0): self._timeout = timeout # don't update the user status on init - self.status = {"tokensLeft": None, "refillIn": None, "refillRate": None, "timestamp": None} + self.status = Status() return self @property @@ -1900,7 +1929,7 @@ def time_to_refill(self) -> float: """Return the time to refill in seconds.""" # Get current timestamp in milliseconds from UNIX epoch now = int(time.time() * 1000) - time_at_refill = self.status["timestamp"] + self.status["refillIn"] + time_at_refill = self.status.timestamp + self.status.refillIn # wait plus one second fudge factor time_to_refill = time_at_refill - now + 1000 @@ -1909,7 +1938,7 @@ def time_to_refill(self) -> float: # Account for negative tokens left if self.tokens_left < 0: - time_to_refill += (abs(self.tokens_left) / self.status["refillRate"]) * 60000 + time_to_refill += (abs(self.tokens_left) / self.status.refillRate) * 60000 # Return value in seconds return time_to_refill / 1000.0 @@ -1979,10 +2008,10 @@ async def query( raise ValueError('Parameter "offers" must be between 20 and 100') # Report time to completion - if self.status["refillRate"] is not None: + if self.status.refillRate is not None and self.status.refillIn is not None: tcomplete = ( - float(nitems - self.tokens_left) / self.status["refillRate"] - - (60000 - self.status["refillIn"]) / 60000.0 + float(nitems - self.tokens_left) / self.status.refillRate + - (60000 - self.status.refillIn) / 60000.0 ) if tcomplete < 0.0: tcomplete = 0.5 @@ -1991,7 +2020,7 @@ async def query( nitems, tcomplete, ) - log.debug("\twith a refill rate of %d token(s) per minute", self.status["refillRate"]) + log.debug("\twith a refill rate of %d token(s) per minute", self.status.refillRate) # product list products = [] @@ -2161,7 +2190,11 @@ async def search_for_categories( @is_documented_by(Keepa.category_lookup) async def category_lookup( - self, category_id, domain: str | Domain = "US", include_parents=0, wait: bool = True + self, + category_id, + domain: str | Domain = "US", + include_parents=0, + wait: bool = True, ): """Documented by Keepa.category_lookup.""" payload = { @@ -2267,7 +2300,11 @@ async def download_graph_image( **graph_kwargs: dict[str, Any], ) -> None: """Documented in Keepa.download_graph_image.""" - payload = {"asin": asin, "key": self.accesskey, "domain": _domain_to_dcode(domain)} + payload = { + "asin": asin, + "key": self.accesskey, + "domain": _domain_to_dcode(domain), + } payload.update(graph_kwargs) async with aiohttp.ClientSession() as session: @@ -2318,11 +2355,11 @@ async def _request( # user status is always returned if "tokensLeft" in response: self.tokens_left = response["tokensLeft"] - self.status["tokensLeft"] = self.tokens_left + self.status.tokensLeft = self.tokens_left log.info("%d tokens remain", self.tokens_left) for key in ["refillIn", "refillRate", "timestamp"]: if key in response: - self.status[key] = response[key] + setattr(self.status, key, response[key]) if status_code == "200": if raw_response: diff --git a/src/keepa/models/status.py b/src/keepa/models/status.py new file mode 100644 index 0000000..834714d --- /dev/null +++ b/src/keepa/models/status.py @@ -0,0 +1,9 @@ +from dataclasses import dataclass + + +@dataclass +class Status: + tokensLeft: int | None = None + refillIn: float | None = None + refillRate: float | None = None + timestamp: float | None = None From 54dc6b4ae79770a258930e688a5519c069d5697d Mon Sep 17 00:00:00 2001 From: ryzanbui02 Date: Sat, 8 Nov 2025 04:38:11 +0000 Subject: [PATCH 4/7] refactor: split interface module --- src/keepa/__init__.py | 17 +- src/keepa/constants.py | 78 ++ src/keepa/keepa_async.py | 563 +++++++++++ src/keepa/{interface.py => keepa_sync.py} | 1063 +-------------------- src/keepa/models/domain.py | 27 + src/keepa/models/status.py | 4 + src/keepa/plotting.py | 2 +- src/keepa/utils.py | 435 +++++++++ tests/test_async_interface.py | 2 +- tests/test_interface.py | 2 +- 10 files changed, 1120 insertions(+), 1073 deletions(-) create mode 100644 src/keepa/constants.py create mode 100644 src/keepa/keepa_async.py rename src/keepa/{interface.py => keepa_sync.py} (60%) create mode 100644 src/keepa/models/domain.py create mode 100644 src/keepa/utils.py diff --git a/src/keepa/__init__.py b/src/keepa/__init__.py index bf1c141..cadf18d 100644 --- a/src/keepa/__init__.py +++ b/src/keepa/__init__.py @@ -8,23 +8,20 @@ except PackageNotFoundError: __version__ = "unknown" -from keepa.interface import ( - DCODES, - KEEPA_ST_ORDINAL, - SCODES, - AsyncKeepa, - Domain, - Keepa, +from keepa.constants import DCODES, KEEPA_ST_ORDINAL, SCODES, csv_indices +from keepa.keepa_async import AsyncKeepa +from keepa.keepa_sync import Keepa +from keepa.models.domain import Domain +from keepa.models.product_params import ProductParams +from keepa.plotting import plot_product +from keepa.utils import ( convert_offer_history, - csv_indices, format_items, keepa_minutes_to_time, parse_csv, process_used_buybox, run_and_get, ) -from keepa.models.product_params import ProductParams -from keepa.plotting import plot_product __all__ = [ "AsyncKeepa", diff --git a/src/keepa/constants.py b/src/keepa/constants.py new file mode 100644 index 0000000..2bbf249 --- /dev/null +++ b/src/keepa/constants.py @@ -0,0 +1,78 @@ +"""Constants for Keepa API interactions.""" + +import numpy as np + +# hardcoded ordinal time from +KEEPA_ST_ORDINAL = np.datetime64("2011-01-01") + +# Request limit +REQUEST_LIMIT = 100 + +# Status code dictionary/key +SCODES = { + "400": "REQUEST_REJECTED", + "402": "PAYMENT_REQUIRED", + "405": "METHOD_NOT_ALLOWED", + "429": "NOT_ENOUGH_TOKEN", +} + +# domain codes +# Valid values: [ 1: com | 2: co.uk | 3: de | 4: fr | 5: +# co.jp | 6: ca | 7: cn | 8: it | 9: es | 10: in | 11: com.mx | 12: com.br ] +DCODES = [ + "RESERVED", + "US", + "GB", + "DE", + "FR", + "JP", + "CA", + "CN", + "IT", + "ES", + "IN", + "MX", + "BR", +] +# developer note: appears like CN (China) has changed to RESERVED2 + +# csv indices. used when parsing csv and stats fields. +# https://github.com/keepacom/api_backend +# see api_backend/src/main/java/com/keepa/api/backend/structs/Product.java +# [index in csv, key name, isfloat(is price or rating)] +csv_indices: list[tuple[int, str, bool]] = [ + (0, "AMAZON", True), + (1, "NEW", True), + (2, "USED", True), + (3, "SALES", False), + (4, "LISTPRICE", True), + (5, "COLLECTIBLE", True), + (6, "REFURBISHED", True), + (7, "NEW_FBM_SHIPPING", True), + (8, "LIGHTNING_DEAL", True), + (9, "WAREHOUSE", True), + (10, "NEW_FBA", True), + (11, "COUNT_NEW", False), + (12, "COUNT_USED", False), + (13, "COUNT_REFURBISHED", False), + (14, "CollectableOffers", False), + (15, "EXTRA_INFO_UPDATES", False), + (16, "RATING", True), + (17, "COUNT_REVIEWS", False), + (18, "BUY_BOX_SHIPPING", True), + (19, "USED_NEW_SHIPPING", True), + (20, "USED_VERY_GOOD_SHIPPING", True), + (21, "USED_GOOD_SHIPPING", True), + (22, "USED_ACCEPTABLE_SHIPPING", True), + (23, "COLLECTIBLE_NEW_SHIPPING", True), + (24, "COLLECTIBLE_VERY_GOOD_SHIPPING", True), + (25, "COLLECTIBLE_GOOD_SHIPPING", True), + (26, "COLLECTIBLE_ACCEPTABLE_SHIPPING", True), + (27, "REFURBISHED_SHIPPING", True), + (28, "EBAY_NEW_SHIPPING", True), + (29, "EBAY_USED_SHIPPING", True), + (30, "TRADE_IN", True), + (31, "RENT", False), +] + +_SELLER_TIME_DATA_KEYS = ["trackedSince", "lastUpdate"] diff --git a/src/keepa/keepa_async.py b/src/keepa/keepa_async.py new file mode 100644 index 0000000..5eb2aef --- /dev/null +++ b/src/keepa/keepa_async.py @@ -0,0 +1,563 @@ +"""Interface module to download Amazon product and history data from keepa.com asynchronously.""" + +import asyncio +import json +import logging +import time +from collections.abc import Sequence +from pathlib import Path +from typing import Any, Literal + +import aiohttp +from tqdm import tqdm + +from keepa.constants import SCODES +from keepa.keepa_sync import Keepa +from keepa.models.domain import Domain +from keepa.models.product_params import ProductParams +from keepa.models.status import Status +from keepa.query_keys import DEAL_REQUEST_KEYS +from keepa.utils import ( + _domain_to_dcode, + _parse_seller, + _parse_stats, + format_items, + is_documented_by, + parse_csv, +) + +log = logging.getLogger(__name__) + + +# Request limit +REQUEST_LIMIT = 100 + + +class AsyncKeepa: + r""" + Asynchronous Python interface to keepa backend. + + Initializes API with access key. Access key can be obtained by signing up + for a reoccurring or one time plan. To obtain a key, sign up for one at + `Keepa Data `_ + + Parameters + ---------- + accesskey : str + 64 character access key string. + timeout : float, default: 10.0 + Default timeout when issuing any request. This is not a time + limit on the entire response download; rather, an exception is + raised if the server has not issued a response for timeout + seconds. Setting this to 0.0 disables the timeout, but will + cause any request to hang indefiantly should keepa.com be down + + Examples + -------- + Query for all of Jim Butcher's books using the asynchronous + ``keepa.AsyncKeepa`` class. + + >>> import asyncio + >>> import keepa + >>> product_parms = {"author": "jim butcher"} + >>> async def main(): + ... key = "" + ... api = await keepa.AsyncKeepa().create(key) + ... return await api.product_finder(product_parms) + ... + >>> asins = asyncio.run(main()) + >>> asins + ['B000HRMAR2', + '0578799790', + 'B07PW1SVHM', + ... + 'B003MXM744', + '0133235750', + 'B01MXXLJPZ'] + + Query for product with ASIN ``'B0088PUEPK'`` using the asynchronous + keepa interface. + + >>> import asyncio + >>> import keepa + >>> async def main(): + ... key = "" + ... api = await keepa.AsyncKeepa().create(key) + ... return await api.query("B0088PUEPK") + ... + >>> response = asyncio.run(main()) + >>> response[0]["title"] + 'Western Digital 1TB WD Blue PC Internal Hard Drive HDD - 7200 RPM, + SATA 6 Gb/s, 64 MB Cache, 3.5" - WD10EZEX' + + """ + + accesskey: str + tokens_left: int + status: Status + _timeout: float + + @classmethod + async def create(cls, accesskey: str, timeout: float = 10.0) -> "AsyncKeepa": + """Create the async object.""" + self = AsyncKeepa() + self.accesskey = accesskey + self.tokens_left = 0 + self._timeout = timeout + + # don't update the user status on init + self.status = Status() + return self + + @property + def time_to_refill(self) -> float: + """Return the time to refill in seconds.""" + # Get current timestamp in milliseconds from UNIX epoch + now = int(time.time() * 1000) + time_at_refill = self.status.timestamp + self.status.refillIn + + # wait plus one second fudge factor + time_to_refill = time_at_refill - now + 1000 + if time_to_refill < 0: + time_to_refill = 0 + + # Account for negative tokens left + if self.tokens_left < 0: + time_to_refill += (abs(self.tokens_left) / self.status.refillRate) * 60000 + + # Return value in seconds + return time_to_refill / 1000.0 + + async def update_status(self) -> None: + """Update available tokens.""" + self.status = await self._request("token", {"key": self.accesskey}, wait=False) + + async def wait_for_tokens(self) -> None: + """Check if there are any remaining tokens and waits if none are available.""" + await self.update_status() + + # Wait if no tokens available + if self.tokens_left <= 0: + tdelay = self.time_to_refill + log.warning("Waiting %.0f seconds for additional tokens", tdelay) + await asyncio.sleep(tdelay) + await self.update_status() + + @is_documented_by(Keepa.query) + async def query( + self, + items: str | Sequence[str], + stats: int | None = None, + domain: str = "US", + history: bool = True, + offers: int | None = None, + update: int | None = None, + to_datetime: bool = True, + rating: bool = False, + out_of_stock_as_nan: bool = True, + stock: bool = False, + product_code_is_asin: bool = True, + progress_bar: bool = True, + buybox: bool = False, + wait: bool = True, + days: int | None = None, + only_live_offers: bool | None = None, + raw: bool = False, + videos: bool = False, + aplus: bool = False, + extra_params: dict[str, Any] = {}, + ): + """Documented in Keepa.query.""" + if raw: + raise ValueError("Raw response is only available in the non-async class") + + # Format items into numpy array + try: + items = format_items(items) + except BaseException: + raise Exception("Invalid product codes input") + assert len(items), "No valid product codes" + + nitems = len(items) + if nitems == 1: + log.debug("Executing single product query") + else: + log.debug("Executing %d item product query", nitems) + + # check offer input + if offers: + if not isinstance(offers, int): + raise TypeError('Parameter "offers" must be an interger') + + if offers > 100 or offers < 20: + raise ValueError('Parameter "offers" must be between 20 and 100') + + # Report time to completion + if self.status.refillRate is not None and self.status.refillIn is not None: + tcomplete = ( + float(nitems - self.tokens_left) / self.status.refillRate + - (60000 - self.status.refillIn) / 60000.0 + ) + if tcomplete < 0.0: + tcomplete = 0.5 + log.debug( + "Estimated time to complete %d request(s) is %.2f minutes", + nitems, + tcomplete, + ) + log.debug("\twith a refill rate of %d token(s) per minute", self.status.refillRate) + + # product list + products = [] + + pbar = None + if progress_bar: + pbar = tqdm(total=nitems) + + # Number of requests is dependent on the number of items and + # request limit. Use available tokens first + idx = 0 # or number complete + while idx < nitems: + nrequest = nitems - idx + + # cap request + if nrequest > REQUEST_LIMIT: + nrequest = REQUEST_LIMIT + + # request from keepa and increment current position + item_request = items[idx : idx + nrequest] # noqa: E203 + response = await self._product_query( + item_request, + product_code_is_asin, + stats=stats, + domain=domain, + stock=stock, + offers=offers, + update=update, + history=history, + rating=rating, + to_datetime=to_datetime, + out_of_stock_as_nan=out_of_stock_as_nan, + buybox=buybox, + wait=wait, + days=days, + only_live_offers=only_live_offers, + videos=videos, + aplus=aplus, + **extra_params, + ) + idx += nrequest + products.extend(response["products"]) + + if pbar is not None: + pbar.update(nrequest) + + return products + + @is_documented_by(Keepa._product_query) + async def _product_query(self, items, product_code_is_asin=True, **kwargs): + """Documented in Keepa._product_query.""" + # ASINs convert to comma joined string + assert len(items) <= 100 + + if product_code_is_asin: + kwargs["asin"] = ",".join(items) + else: + kwargs["code"] = ",".join(items) + + kwargs["key"] = self.accesskey + kwargs["domain"] = _domain_to_dcode(kwargs["domain"]) + + # Convert bool values to 0 and 1. + kwargs["stock"] = int(kwargs["stock"]) + kwargs["history"] = int(kwargs["history"]) + kwargs["rating"] = int(kwargs["rating"]) + kwargs["buybox"] = int(kwargs["buybox"]) + + if kwargs["update"] is None: + del kwargs["update"] + else: + kwargs["update"] = int(kwargs["update"]) + + if kwargs["offers"] is None: + del kwargs["offers"] + else: + kwargs["offers"] = int(kwargs["offers"]) + + if kwargs["only_live_offers"] is None: + del kwargs["only_live_offers"] + else: + kwargs["only-live-offers"] = int(kwargs.pop("only_live_offers")) + # Keepa's param actually doesn't use snake_case. + # Keeping with snake case for consistency + + if kwargs["days"] is None: + del kwargs["days"] + else: + assert kwargs["days"] > 0 + + if kwargs["stats"] is None: + del kwargs["stats"] + + # videos and aplus must be ints + kwargs["videos"] = int(kwargs["videos"]) + kwargs["aplus"] = int(kwargs["aplus"]) + + out_of_stock_as_nan = kwargs.pop("out_of_stock_as_nan", True) + to_datetime = kwargs.pop("to_datetime", True) + + # Query and replace csv with parsed data if history enabled + wait = kwargs.get("wait") + kwargs.pop("wait", None) + + raw_response = kwargs.pop("raw", False) + response = await self._request("product", kwargs, wait=wait, raw_response=raw_response) + if kwargs["history"]: + if "products" not in response: + raise RuntimeError("No products in response. Possibly invalid ASINs") + + for product in response["products"]: + if product["csv"]: # if data exists + product["data"] = parse_csv(product["csv"], to_datetime, out_of_stock_as_nan) + + if kwargs.get("stats", None): + for product in response["products"]: + stats = product.get("stats", None) + if stats: + product["stats_parsed"] = _parse_stats(stats, to_datetime) + + return response + + @is_documented_by(Keepa.best_sellers_query) + async def best_sellers_query( + self, + category: str, + rank_avg_range: Literal[0, 30, 90, 180] = 0, + variations: bool = False, + sublist: bool = False, + domain: str | Domain = "US", + wait: bool = True, + ): + """Documented by Keepa.best_sellers_query.""" + payload = { + "key": self.accesskey, + "domain": _domain_to_dcode(domain), + "variations": int(variations), + "sublist": int(sublist), + "category": category, + "range": rank_avg_range, + } + + response = await self._request("bestsellers", payload, wait=wait) + if "bestSellersList" not in response: + raise RuntimeError(f"Best sellers search results for {category} not yet available") + return response["bestSellersList"]["asinList"] + + @is_documented_by(Keepa.search_for_categories) + async def search_for_categories( + self, searchterm, domain: str | Domain = "US", wait: bool = True + ): + """Documented by Keepa.search_for_categories.""" + payload = { + "key": self.accesskey, + "domain": _domain_to_dcode(domain), + "type": "category", + "term": searchterm, + } + + response = await self._request("search", payload, wait=wait) + if response["categories"] == {}: # pragma no cover + raise Exception( + "Categories search results not yet available " + "or no search terms found." + ) + else: + return response["categories"] + + @is_documented_by(Keepa.category_lookup) + async def category_lookup( + self, + category_id, + domain: str | Domain = "US", + include_parents=0, + wait: bool = True, + ): + """Documented by Keepa.category_lookup.""" + payload = { + "key": self.accesskey, + "domain": _domain_to_dcode(domain), + "category": category_id, + "parents": include_parents, + } + + response = await self._request("category", payload, wait=wait) + if response["categories"] == {}: # pragma no cover + raise Exception("Category lookup results not yet available or no" + "match found.") + else: + return response["categories"] + + @is_documented_by(Keepa.seller_query) + async def seller_query( + self, + seller_id, + domain: str | Domain = "US", + to_datetime=True, + storefront=False, + update=None, + wait: bool = True, + ): + """Documented by Keepa.sellerer_query.""" + if isinstance(seller_id, list): + if len(seller_id) > 100: + err_str = "seller_id can contain at maximum 100 sellers" + raise RuntimeError(err_str) + seller = ",".join(seller_id) + else: + seller = seller_id + + payload = { + "key": self.accesskey, + "domain": _domain_to_dcode(domain), + "seller": seller, + } + + if storefront: + payload["storefront"] = int(storefront) + if update: + payload["update"] = update + + response = await self._request("seller", payload, wait=wait) + return _parse_seller(response["sellers"], to_datetime) + + @is_documented_by(Keepa.product_finder) + async def product_finder( + self, + product_parms: dict[str, Any] | ProductParams, + domain: str | Domain = "US", + wait: bool = True, + n_products: int = 50, + ) -> list[str]: + """Documented by Keepa.product_finder.""" + if isinstance(product_parms, dict): + product_parms_valid = ProductParams(**product_parms) + else: + product_parms_valid = product_parms + product_parms_dict = product_parms_valid.model_dump(exclude_none=True) + product_parms_dict.setdefault("perPage", n_products) + payload = { + "key": self.accesskey, + "domain": _domain_to_dcode(domain), + "selection": json.dumps(product_parms_dict), + } + + response = await self._request("query", payload, wait=wait) + return response["asinList"] + + @is_documented_by(Keepa.deals) + async def deals(self, deal_parms, domain: str | Domain = "US", wait: bool = True): + """Documented in Keepa.deals.""" + # verify valid keys + for key in deal_parms: + if key not in DEAL_REQUEST_KEYS: + raise ValueError(f'Invalid key "{key}"') + + # verify json type + key_type = DEAL_REQUEST_KEYS[key] + deal_parms[key] = key_type(deal_parms[key]) + + deal_parms.setdefault("priceTypes", 0) + + payload = { + "key": self.accesskey, + "domain": _domain_to_dcode(domain), + "selection": json.dumps(deal_parms), + } + + deals = await self._request("deal", payload, wait=wait) + return deals["deals"] + + @is_documented_by(Keepa.download_graph_image) + async def download_graph_image( + self, + asin: str, + filename: str | Path, + domain: str | Domain = "US", + wait: bool = True, + **graph_kwargs: dict[str, Any], + ) -> None: + """Documented in Keepa.download_graph_image.""" + payload = { + "asin": asin, + "key": self.accesskey, + "domain": _domain_to_dcode(domain), + } + payload.update(graph_kwargs) + + async with aiohttp.ClientSession() as session: + async with session.get( + "https://api.keepa.com/graphimage", + params=payload, + timeout=self._timeout, + ) as resp: + first_chunk = True + filename = Path(filename) + with open(filename, "wb") as f: + async for chunk in resp.content.iter_chunked(8192): + if first_chunk: + if not chunk.startswith(b"\x89PNG\r\n\x1a\n"): + raise ValueError( + "Response from api.keepa.com/graphimage is not a valid " + "PNG image" + ) + first_chunk = False + f.write(chunk) + + async def _request( + self, + request_type: str, + payload: dict[str, Any], + wait: bool = True, + raw_response: bool = False, + is_json: bool = True, + ): + """Documented in Keepa._request.""" + while True: + async with aiohttp.ClientSession() as session: + async with session.get( + f"https://api.keepa.com/{request_type}/?", + params=payload, + timeout=self._timeout, + ) as raw: + status_code = str(raw.status) + + if not is_json: + return raw + + try: + response = await raw.json() + except Exception: + raise RuntimeError(f"Invalid JSON from Keepa API (status {status_code})") + + # user status is always returned + if "tokensLeft" in response: + self.tokens_left = response["tokensLeft"] + self.status.tokensLeft = self.tokens_left + log.info("%d tokens remain", self.tokens_left) + for key in ["refillIn", "refillRate", "timestamp"]: + if key in response: + setattr(self.status, key, response[key]) + + if status_code == "200": + if raw_response: + return raw + return response + + if status_code == "429" and wait: + tdelay = self.time_to_refill + log.warning("Waiting %.0f seconds for additional tokens", tdelay) + time.sleep(tdelay) + continue + + # otherwise, it's an error code + if status_code in SCODES: + raise RuntimeError(SCODES[status_code]) + raise RuntimeError(f"REQUEST_FAILED. Status code: {status_code}") diff --git a/src/keepa/interface.py b/src/keepa/keepa_sync.py similarity index 60% rename from src/keepa/interface.py rename to src/keepa/keepa_sync.py index ff2a7c2..9569231 100644 --- a/src/keepa/interface.py +++ b/src/keepa/keepa_sync.py @@ -1,407 +1,26 @@ """Interface module to download Amazon product and history data from keepa.com.""" -import asyncio -import datetime import json import logging import time from collections.abc import Sequence -from enum import Enum from pathlib import Path from typing import Any, Literal -import aiohttp -import numpy as np -import pandas as pd import requests from tqdm import tqdm +from keepa.constants import SCODES +from keepa.models.domain import Domain from keepa.models.product_params import ProductParams from keepa.models.status import Status from keepa.query_keys import DEAL_REQUEST_KEYS - - -def is_documented_by(original): - """Avoid copying the documentation.""" - - def wrapper(target): - target.__doc__ = original.__doc__ - return target - - return wrapper - +from keepa.utils import _domain_to_dcode, _parse_seller, _parse_stats, format_items, parse_csv log = logging.getLogger(__name__) -# hardcoded ordinal time from -KEEPA_ST_ORDINAL = np.datetime64("2011-01-01") - -# Request limit REQUEST_LIMIT = 100 -# Status code dictionary/key -SCODES = { - "400": "REQUEST_REJECTED", - "402": "PAYMENT_REQUIRED", - "405": "METHOD_NOT_ALLOWED", - "429": "NOT_ENOUGH_TOKEN", -} - -# domain codes -# Valid values: [ 1: com | 2: co.uk | 3: de | 4: fr | 5: -# co.jp | 6: ca | 7: cn | 8: it | 9: es | 10: in | 11: com.mx | 12: com.br ] -DCODES = [ - "RESERVED", - "US", - "GB", - "DE", - "FR", - "JP", - "CA", - "CN", - "IT", - "ES", - "IN", - "MX", - "BR", -] -# developer note: appears like CN (China) has changed to RESERVED2 - -# csv indices. used when parsing csv and stats fields. -# https://github.com/keepacom/api_backend -# see api_backend/src/main/java/com/keepa/api/backend/structs/Product.java -# [index in csv, key name, isfloat(is price or rating)] -csv_indices: list[tuple[int, str, bool]] = [ - (0, "AMAZON", True), - (1, "NEW", True), - (2, "USED", True), - (3, "SALES", False), - (4, "LISTPRICE", True), - (5, "COLLECTIBLE", True), - (6, "REFURBISHED", True), - (7, "NEW_FBM_SHIPPING", True), - (8, "LIGHTNING_DEAL", True), - (9, "WAREHOUSE", True), - (10, "NEW_FBA", True), - (11, "COUNT_NEW", False), - (12, "COUNT_USED", False), - (13, "COUNT_REFURBISHED", False), - (14, "CollectableOffers", False), - (15, "EXTRA_INFO_UPDATES", False), - (16, "RATING", True), - (17, "COUNT_REVIEWS", False), - (18, "BUY_BOX_SHIPPING", True), - (19, "USED_NEW_SHIPPING", True), - (20, "USED_VERY_GOOD_SHIPPING", True), - (21, "USED_GOOD_SHIPPING", True), - (22, "USED_ACCEPTABLE_SHIPPING", True), - (23, "COLLECTIBLE_NEW_SHIPPING", True), - (24, "COLLECTIBLE_VERY_GOOD_SHIPPING", True), - (25, "COLLECTIBLE_GOOD_SHIPPING", True), - (26, "COLLECTIBLE_ACCEPTABLE_SHIPPING", True), - (27, "REFURBISHED_SHIPPING", True), - (28, "EBAY_NEW_SHIPPING", True), - (29, "EBAY_USED_SHIPPING", True), - (30, "TRADE_IN", True), - (31, "RENT", False), -] - -_SELLER_TIME_DATA_KEYS = ["trackedSince", "lastUpdate"] - - -def _normalize_value(v: int, isfloat: bool, key: str) -> float | None: - """Normalize a single value based on its type and key context.""" - if v < 0: - return None - if isfloat: - v = float(v) / 100 - if key == "RATING": - v *= 10 - return v - - -def _is_stat_value_skippable(key: str, value: Any) -> bool: - """Determine if the stat value is skippable.""" - if key in { - "buyBoxSellerId", - "sellerIdsLowestFBA", - "sellerIdsLowestFBM", - "buyBoxShippingCountry", - "buyBoxAvailabilityMessage", - }: - return True - - # -1 or -2 --> not exist - if isinstance(value, int) and value < 0: - return True - - return False - - -def _parse_stat_value_list( - value_list: list, to_datetime: bool -) -> dict[str, float | tuple[Any, float]]: - """Parse a list of stat values into a structured dict.""" - convert_time = any(isinstance(v, list) for v in value_list if v is not None) - result = {} - - for ind, key, isfloat in csv_indices: - item = value_list[ind] if ind < len(value_list) else None - if item is None: - continue - - if convert_time: - ts, val = item - val = _normalize_value(val, isfloat, key) - if val is not None: - ts = keepa_minutes_to_time([ts], to_datetime)[0] - result[key] = (ts, val) - else: - val = _normalize_value(item, isfloat, key) - if val is not None: - result[key] = val - - return result - - -def _parse_stats(stats: dict[str, None, int, list[int]], to_datetime: bool): - """Parse numeric stats object. - - There is no need to parse strings or list of strings. Keepa stats object - response documentation: - https://keepa.com/#!discuss/t/statistics-object/1308 - """ - stats_parsed = {} - - for stat_key, stat_value in stats.items(): - if _is_stat_value_skippable(stat_key, stat_value): - continue - - if stat_value is not None: - if stat_key == "lastOffersUpdate": - stats_parsed[stat_key] = keepa_minutes_to_time([stat_value], to_datetime)[0] - elif isinstance(stat_value, list) and len(stat_value) > 0: - stat_value_dict = _parse_stat_value_list(stat_value, to_datetime) - if stat_value_dict: - stats_parsed[stat_key] = stat_value_dict - else: - stats_parsed[stat_key] = stat_value - - return stats_parsed - - -def _parse_seller(seller_raw_response, to_datetime): - sellers = list(seller_raw_response.values()) - for seller in sellers: - - def convert_time_data(key): - date_val = seller.get(key, None) - if date_val is not None: - return (key, keepa_minutes_to_time([date_val], to_datetime)[0]) - else: - return None - - seller.update( - filter(lambda p: p is not None, map(convert_time_data, _SELLER_TIME_DATA_KEYS)) - ) - - return dict(map(lambda seller: (seller["sellerId"], seller), sellers)) - - -def parse_csv(csv, to_datetime: bool = True, out_of_stock_as_nan: bool = True) -> dict[str, Any]: - """ - Parse csv list from keepa into a python dictionary. - - Parameters - ---------- - csv : list - csv list from keepa - to_datetime : bool, default: True - Modifies numpy minutes to datetime.datetime values. - Default True. - out_of_stock_as_nan : bool, optional - When True, prices are NAN when price category is out of stock. - When False, prices are -0.01 - Default True - - Returns - ------- - product_data : dict - Dictionary containing the following fields with timestamps: - - AMAZON: Amazon price history - - NEW: Marketplace/3rd party New price history - Amazon is - considered to be part of the marketplace as well, so if - Amazon has the overall lowest new (!) price, the - marketplace new price in the corresponding time interval - will be identical to the Amazon price (except if there is - only one marketplace offer). Shipping and Handling costs - not included! - - USED: Marketplace/3rd party Used price history - - SALES: Sales Rank history. Not every product has a Sales Rank. - - LISTPRICE: List Price history - - 5 COLLECTIBLE: Collectible Price history - - 6 REFURBISHED: Refurbished Price history - - 7 NEW_FBM_SHIPPING: 3rd party (not including Amazon) New price - history including shipping costs, only fulfilled by - merchant (FBM). - - 8 LIGHTNING_DEAL: 3rd party (not including Amazon) New price - history including shipping costs, only fulfilled by - merchant (FBM). - - 9 WAREHOUSE: Amazon Warehouse Deals price history. Mostly of - used condition, rarely new. - - 10 NEW_FBA: Price history of the lowest 3rd party (not - including Amazon/Warehouse) New offer that is fulfilled - by Amazon - - 11 COUNT_NEW: New offer count history - - 12 COUNT_USED: Used offer count history - - 13 COUNT_REFURBISHED: Refurbished offer count history - - 14 COUNT_COLLECTIBLE: Collectible offer count history - - 16 RATING: The product's rating history. A rating is an - integer from 0 to 50 (e.g. 45 = 4.5 stars) - - 17 COUNT_REVIEWS: The product's review count history. - - 18 BUY_BOX_SHIPPING: The price history of the buy box. If no - offer qualified for the buy box the price has the value - -1. Including shipping costs. The ``buybox`` parameter - must be True for this field to be in the data. - - 19 USED_NEW_SHIPPING: "Used - Like New" price history - including shipping costs. - - 20 USED_VERY_GOOD_SHIPPING: "Used - Very Good" price history - including shipping costs. - - 21 USED_GOOD_SHIPPING: "Used - Good" price history including - shipping costs. - - 22 USED_ACCEPTABLE_SHIPPING: "Used - Acceptable" price history - including shipping costs. - - 23 COLLECTIBLE_NEW_SHIPPING: "Collectible - Like New" price - history including shipping costs. - - 24 COLLECTIBLE_VERY_GOOD_SHIPPING: "Collectible - Very Good" - price history including shipping costs. - - 25 COLLECTIBLE_GOOD_SHIPPING: "Collectible - Good" price - history including shipping costs. - - 26 COLLECTIBLE_ACCEPTABLE_SHIPPING: "Collectible - Acceptable" - price history including shipping costs. - - 27 REFURBISHED_SHIPPING: Refurbished price history including - shipping costs. - - 30 TRADE_IN: The trade in price history. Amazon trade-in is - not available for every locale. - - 31 RENT: Rental price history. Requires use of the rental - and offers parameter. Amazon Rental is only available - for Amazon US. - - Notes - ----- - Negative prices - - """ - product_data = {} - - for ind, key, isfloat in csv_indices: - if csv[ind]: # Check if entry it exists - if "SHIPPING" in key: # shipping price is included - # Data goes [time0, value0, shipping0, time1, value1, - # shipping1, ...] - times = csv[ind][::3] - values = np.array(csv[ind][1::3]) - values += np.array(csv[ind][2::3]) - else: - # Data goes [time0, value0, time1, value1, ...] - times = csv[ind][::2] - values = np.array(csv[ind][1::2]) - - # Convert to float price if applicable - if isfloat: - nan_mask = values < 0 - values = values.astype(float) / 100 - if out_of_stock_as_nan: - values[nan_mask] = np.nan - - if key == "RATING": - values *= 10 - - timeval = keepa_minutes_to_time(times, to_datetime) - - product_data["%s_time" % key] = timeval - product_data[key] = values - - # combine time and value into a data frame using time as index - product_data[f"df_{key}"] = pd.DataFrame({"value": values}, index=timeval) - - return product_data - - -def format_items(items): - """Check if the input items are valid and formats them.""" - if isinstance(items, list) or isinstance(items, np.ndarray): - return np.unique(items) - elif isinstance(items, str): - return np.asarray([items]) - - -class Domain(Enum): - """Enumeration for Amazon domain regions. - - Examples - -------- - >>> import keepa - >>> keepa.Domain.US - - - """ - - RESERVED = "RESERVED" - US = "US" - GB = "GB" - DE = "DE" - FR = "FR" - JP = "JP" - CA = "CA" - RESERVED2 = "RESERVED2" - IT = "IT" - ES = "ES" - IN = "IN" - MX = "MX" - BR = "BR" - - -def _domain_to_dcode(domain: str | Domain) -> int: - """Convert a domain to a domain code.""" - if isinstance(domain, Domain): - domain_str = domain.value - else: - domain_str = domain - - if domain_str not in DCODES: - raise ValueError(f"Invalid domain code {domain}. Should be one of the following:\n{DCODES}") - return DCODES.index(domain_str) - class Keepa: r""" @@ -1846,679 +1465,3 @@ def _request( if status_code in SCODES: raise RuntimeError(SCODES[status_code]) raise RuntimeError(f"REQUEST_FAILED. Status code: {status_code}") - - -class AsyncKeepa: - r""" - Asynchronous Python interface to keepa backend. - - Initializes API with access key. Access key can be obtained by signing up - for a reoccurring or one time plan. To obtain a key, sign up for one at - `Keepa Data `_ - - Parameters - ---------- - accesskey : str - 64 character access key string. - timeout : float, default: 10.0 - Default timeout when issuing any request. This is not a time - limit on the entire response download; rather, an exception is - raised if the server has not issued a response for timeout - seconds. Setting this to 0.0 disables the timeout, but will - cause any request to hang indefiantly should keepa.com be down - - Examples - -------- - Query for all of Jim Butcher's books using the asynchronous - ``keepa.AsyncKeepa`` class. - - >>> import asyncio - >>> import keepa - >>> product_parms = {"author": "jim butcher"} - >>> async def main(): - ... key = "" - ... api = await keepa.AsyncKeepa().create(key) - ... return await api.product_finder(product_parms) - ... - >>> asins = asyncio.run(main()) - >>> asins - ['B000HRMAR2', - '0578799790', - 'B07PW1SVHM', - ... - 'B003MXM744', - '0133235750', - 'B01MXXLJPZ'] - - Query for product with ASIN ``'B0088PUEPK'`` using the asynchronous - keepa interface. - - >>> import asyncio - >>> import keepa - >>> async def main(): - ... key = "" - ... api = await keepa.AsyncKeepa().create(key) - ... return await api.query("B0088PUEPK") - ... - >>> response = asyncio.run(main()) - >>> response[0]["title"] - 'Western Digital 1TB WD Blue PC Internal Hard Drive HDD - 7200 RPM, - SATA 6 Gb/s, 64 MB Cache, 3.5" - WD10EZEX' - - """ - - accesskey: str - tokens_left: int - status: Status - _timeout: float - - @classmethod - async def create(cls, accesskey: str, timeout: float = 10.0) -> "AsyncKeepa": - """Create the async object.""" - self = AsyncKeepa() - self.accesskey = accesskey - self.tokens_left = 0 - self._timeout = timeout - - # don't update the user status on init - self.status = Status() - return self - - @property - def time_to_refill(self) -> float: - """Return the time to refill in seconds.""" - # Get current timestamp in milliseconds from UNIX epoch - now = int(time.time() * 1000) - time_at_refill = self.status.timestamp + self.status.refillIn - - # wait plus one second fudge factor - time_to_refill = time_at_refill - now + 1000 - if time_to_refill < 0: - time_to_refill = 0 - - # Account for negative tokens left - if self.tokens_left < 0: - time_to_refill += (abs(self.tokens_left) / self.status.refillRate) * 60000 - - # Return value in seconds - return time_to_refill / 1000.0 - - async def update_status(self) -> None: - """Update available tokens.""" - self.status = await self._request("token", {"key": self.accesskey}, wait=False) - - async def wait_for_tokens(self) -> None: - """Check if there are any remaining tokens and waits if none are available.""" - await self.update_status() - - # Wait if no tokens available - if self.tokens_left <= 0: - tdelay = self.time_to_refill - log.warning("Waiting %.0f seconds for additional tokens", tdelay) - await asyncio.sleep(tdelay) - await self.update_status() - - @is_documented_by(Keepa.query) - async def query( - self, - items: str | Sequence[str], - stats: int | None = None, - domain: str = "US", - history: bool = True, - offers: int | None = None, - update: int | None = None, - to_datetime: bool = True, - rating: bool = False, - out_of_stock_as_nan: bool = True, - stock: bool = False, - product_code_is_asin: bool = True, - progress_bar: bool = True, - buybox: bool = False, - wait: bool = True, - days: int | None = None, - only_live_offers: bool | None = None, - raw: bool = False, - videos: bool = False, - aplus: bool = False, - extra_params: dict[str, Any] = {}, - ): - """Documented in Keepa.query.""" - if raw: - raise ValueError("Raw response is only available in the non-async class") - - # Format items into numpy array - try: - items = format_items(items) - except BaseException: - raise Exception("Invalid product codes input") - assert len(items), "No valid product codes" - - nitems = len(items) - if nitems == 1: - log.debug("Executing single product query") - else: - log.debug("Executing %d item product query", nitems) - - # check offer input - if offers: - if not isinstance(offers, int): - raise TypeError('Parameter "offers" must be an interger') - - if offers > 100 or offers < 20: - raise ValueError('Parameter "offers" must be between 20 and 100') - - # Report time to completion - if self.status.refillRate is not None and self.status.refillIn is not None: - tcomplete = ( - float(nitems - self.tokens_left) / self.status.refillRate - - (60000 - self.status.refillIn) / 60000.0 - ) - if tcomplete < 0.0: - tcomplete = 0.5 - log.debug( - "Estimated time to complete %d request(s) is %.2f minutes", - nitems, - tcomplete, - ) - log.debug("\twith a refill rate of %d token(s) per minute", self.status.refillRate) - - # product list - products = [] - - pbar = None - if progress_bar: - pbar = tqdm(total=nitems) - - # Number of requests is dependent on the number of items and - # request limit. Use available tokens first - idx = 0 # or number complete - while idx < nitems: - nrequest = nitems - idx - - # cap request - if nrequest > REQUEST_LIMIT: - nrequest = REQUEST_LIMIT - - # request from keepa and increment current position - item_request = items[idx : idx + nrequest] # noqa: E203 - response = await self._product_query( - item_request, - product_code_is_asin, - stats=stats, - domain=domain, - stock=stock, - offers=offers, - update=update, - history=history, - rating=rating, - to_datetime=to_datetime, - out_of_stock_as_nan=out_of_stock_as_nan, - buybox=buybox, - wait=wait, - days=days, - only_live_offers=only_live_offers, - videos=videos, - aplus=aplus, - **extra_params, - ) - idx += nrequest - products.extend(response["products"]) - - if pbar is not None: - pbar.update(nrequest) - - return products - - @is_documented_by(Keepa._product_query) - async def _product_query(self, items, product_code_is_asin=True, **kwargs): - """Documented in Keepa._product_query.""" - # ASINs convert to comma joined string - assert len(items) <= 100 - - if product_code_is_asin: - kwargs["asin"] = ",".join(items) - else: - kwargs["code"] = ",".join(items) - - kwargs["key"] = self.accesskey - kwargs["domain"] = _domain_to_dcode(kwargs["domain"]) - - # Convert bool values to 0 and 1. - kwargs["stock"] = int(kwargs["stock"]) - kwargs["history"] = int(kwargs["history"]) - kwargs["rating"] = int(kwargs["rating"]) - kwargs["buybox"] = int(kwargs["buybox"]) - - if kwargs["update"] is None: - del kwargs["update"] - else: - kwargs["update"] = int(kwargs["update"]) - - if kwargs["offers"] is None: - del kwargs["offers"] - else: - kwargs["offers"] = int(kwargs["offers"]) - - if kwargs["only_live_offers"] is None: - del kwargs["only_live_offers"] - else: - kwargs["only-live-offers"] = int(kwargs.pop("only_live_offers")) - # Keepa's param actually doesn't use snake_case. - # Keeping with snake case for consistency - - if kwargs["days"] is None: - del kwargs["days"] - else: - assert kwargs["days"] > 0 - - if kwargs["stats"] is None: - del kwargs["stats"] - - # videos and aplus must be ints - kwargs["videos"] = int(kwargs["videos"]) - kwargs["aplus"] = int(kwargs["aplus"]) - - out_of_stock_as_nan = kwargs.pop("out_of_stock_as_nan", True) - to_datetime = kwargs.pop("to_datetime", True) - - # Query and replace csv with parsed data if history enabled - wait = kwargs.get("wait") - kwargs.pop("wait", None) - - raw_response = kwargs.pop("raw", False) - response = await self._request("product", kwargs, wait=wait, raw_response=raw_response) - if kwargs["history"]: - if "products" not in response: - raise RuntimeError("No products in response. Possibly invalid ASINs") - - for product in response["products"]: - if product["csv"]: # if data exists - product["data"] = parse_csv(product["csv"], to_datetime, out_of_stock_as_nan) - - if kwargs.get("stats", None): - for product in response["products"]: - stats = product.get("stats", None) - if stats: - product["stats_parsed"] = _parse_stats(stats, to_datetime) - - return response - - @is_documented_by(Keepa.best_sellers_query) - async def best_sellers_query( - self, - category: str, - rank_avg_range: Literal[0, 30, 90, 180] = 0, - variations: bool = False, - sublist: bool = False, - domain: str | Domain = "US", - wait: bool = True, - ): - """Documented by Keepa.best_sellers_query.""" - payload = { - "key": self.accesskey, - "domain": _domain_to_dcode(domain), - "variations": int(variations), - "sublist": int(sublist), - "category": category, - "range": rank_avg_range, - } - - response = await self._request("bestsellers", payload, wait=wait) - if "bestSellersList" not in response: - raise RuntimeError(f"Best sellers search results for {category} not yet available") - return response["bestSellersList"]["asinList"] - - @is_documented_by(Keepa.search_for_categories) - async def search_for_categories( - self, searchterm, domain: str | Domain = "US", wait: bool = True - ): - """Documented by Keepa.search_for_categories.""" - payload = { - "key": self.accesskey, - "domain": _domain_to_dcode(domain), - "type": "category", - "term": searchterm, - } - - response = await self._request("search", payload, wait=wait) - if response["categories"] == {}: # pragma no cover - raise Exception( - "Categories search results not yet available " + "or no search terms found." - ) - else: - return response["categories"] - - @is_documented_by(Keepa.category_lookup) - async def category_lookup( - self, - category_id, - domain: str | Domain = "US", - include_parents=0, - wait: bool = True, - ): - """Documented by Keepa.category_lookup.""" - payload = { - "key": self.accesskey, - "domain": _domain_to_dcode(domain), - "category": category_id, - "parents": include_parents, - } - - response = await self._request("category", payload, wait=wait) - if response["categories"] == {}: # pragma no cover - raise Exception("Category lookup results not yet available or no" + "match found.") - else: - return response["categories"] - - @is_documented_by(Keepa.seller_query) - async def seller_query( - self, - seller_id, - domain: str | Domain = "US", - to_datetime=True, - storefront=False, - update=None, - wait: bool = True, - ): - """Documented by Keepa.sellerer_query.""" - if isinstance(seller_id, list): - if len(seller_id) > 100: - err_str = "seller_id can contain at maximum 100 sellers" - raise RuntimeError(err_str) - seller = ",".join(seller_id) - else: - seller = seller_id - - payload = { - "key": self.accesskey, - "domain": _domain_to_dcode(domain), - "seller": seller, - } - - if storefront: - payload["storefront"] = int(storefront) - if update: - payload["update"] = update - - response = await self._request("seller", payload, wait=wait) - return _parse_seller(response["sellers"], to_datetime) - - @is_documented_by(Keepa.product_finder) - async def product_finder( - self, - product_parms: dict[str, Any] | ProductParams, - domain: str | Domain = "US", - wait: bool = True, - n_products: int = 50, - ) -> list[str]: - """Documented by Keepa.product_finder.""" - if isinstance(product_parms, dict): - product_parms_valid = ProductParams(**product_parms) - else: - product_parms_valid = product_parms - product_parms_dict = product_parms_valid.model_dump(exclude_none=True) - product_parms_dict.setdefault("perPage", n_products) - payload = { - "key": self.accesskey, - "domain": _domain_to_dcode(domain), - "selection": json.dumps(product_parms_dict), - } - - response = await self._request("query", payload, wait=wait) - return response["asinList"] - - @is_documented_by(Keepa.deals) - async def deals(self, deal_parms, domain: str | Domain = "US", wait: bool = True): - """Documented in Keepa.deals.""" - # verify valid keys - for key in deal_parms: - if key not in DEAL_REQUEST_KEYS: - raise ValueError(f'Invalid key "{key}"') - - # verify json type - key_type = DEAL_REQUEST_KEYS[key] - deal_parms[key] = key_type(deal_parms[key]) - - deal_parms.setdefault("priceTypes", 0) - - payload = { - "key": self.accesskey, - "domain": _domain_to_dcode(domain), - "selection": json.dumps(deal_parms), - } - - deals = await self._request("deal", payload, wait=wait) - return deals["deals"] - - @is_documented_by(Keepa.download_graph_image) - async def download_graph_image( - self, - asin: str, - filename: str | Path, - domain: str | Domain = "US", - wait: bool = True, - **graph_kwargs: dict[str, Any], - ) -> None: - """Documented in Keepa.download_graph_image.""" - payload = { - "asin": asin, - "key": self.accesskey, - "domain": _domain_to_dcode(domain), - } - payload.update(graph_kwargs) - - async with aiohttp.ClientSession() as session: - async with session.get( - "https://api.keepa.com/graphimage", - params=payload, - timeout=self._timeout, - ) as resp: - first_chunk = True - filename = Path(filename) - with open(filename, "wb") as f: - async for chunk in resp.content.iter_chunked(8192): - if first_chunk: - if not chunk.startswith(b"\x89PNG\r\n\x1a\n"): - raise ValueError( - "Response from api.keepa.com/graphimage is not a valid " - "PNG image" - ) - first_chunk = False - f.write(chunk) - - async def _request( - self, - request_type: str, - payload: dict[str, Any], - wait: bool = True, - raw_response: bool = False, - is_json: bool = True, - ): - """Documented in Keepa._request.""" - while True: - async with aiohttp.ClientSession() as session: - async with session.get( - f"https://api.keepa.com/{request_type}/?", - params=payload, - timeout=self._timeout, - ) as raw: - status_code = str(raw.status) - - if not is_json: - return raw - - try: - response = await raw.json() - except Exception: - raise RuntimeError(f"Invalid JSON from Keepa API (status {status_code})") - - # user status is always returned - if "tokensLeft" in response: - self.tokens_left = response["tokensLeft"] - self.status.tokensLeft = self.tokens_left - log.info("%d tokens remain", self.tokens_left) - for key in ["refillIn", "refillRate", "timestamp"]: - if key in response: - setattr(self.status, key, response[key]) - - if status_code == "200": - if raw_response: - return raw - return response - - if status_code == "429" and wait: - tdelay = self.time_to_refill - log.warning("Waiting %.0f seconds for additional tokens", tdelay) - time.sleep(tdelay) - continue - - # otherwise, it's an error code - if status_code in SCODES: - raise RuntimeError(SCODES[status_code]) - raise RuntimeError(f"REQUEST_FAILED. Status code: {status_code}") - - -def convert_offer_history(csv, to_datetime=True): - """Convert an offer history to human readable values. - - Parameters - ---------- - csv : list - Offer list csv obtained from ``['offerCSV']`` - - to_datetime : bool, optional - Modifies ``numpy`` minutes to ``datetime.datetime`` values. - Default ``True``. - - Returns - ------- - times : numpy.ndarray - List of time values for an offer history. - - prices : numpy.ndarray - Price (including shipping) of an offer for each time at an - index of times. - - """ - # convert these values to numpy arrays - times = csv[::3] - values = np.array(csv[1::3]) - values += np.array(csv[2::3]) # add in shipping - - # convert to dollars and datetimes - times = keepa_minutes_to_time(times, to_datetime) - prices = values / 100.0 - return times, prices - - -def _str_to_bool(string: str) -> bool: - if string: - return bool(int(string)) - return False - - -def process_used_buybox(buybox_info: list[str]) -> pd.DataFrame: - """ - Process used buybox information to create a Pandas DataFrame. - - Parameters - ---------- - buybox_info : list of str - A list containing information about used buybox in a specific order: - [Keepa time minutes, seller id, condition, isFBA, ...] - - Returns - ------- - pd.DataFrame - A DataFrame containing four columns: - - 'datetime': Datetime objects converted from Keepa time minutes. - - 'user_id': String representing the seller ID. - - 'condition': String representing the condition of the product. - - 'isFBA': Boolean indicating whether the offer is Fulfilled by Amazon. - - Notes - ----- - The `condition` is mapped from its code to a descriptive string. - The `isFBA` field is converted to a boolean. - - Examples - -------- - Load in product offers and convert the buy box data into a - ``pandas.DataFrame``. - - >>> import keepa - >>> key = "" - >>> api = keepa.Keepa(key) - >>> response = api.query("B0088PUEPK", offers=20) - >>> product = response[0] - >>> buybox_info = product["buyBoxUsedHistory"] - >>> df = keepa.process_used_buybox(buybox_info) - datetime user_id condition isFBA - 0 2022-11-02 16:46:00 A1QUAC68EAM09F Used - Like New True - 1 2022-11-13 10:36:00 A18WXU4I7YR6UA Used - Very Good False - 2 2022-11-15 23:50:00 AYUGEV9WZ4X5O Used - Like New False - 3 2022-11-17 06:16:00 A18WXU4I7YR6UA Used - Very Good False - 4 2022-11-17 10:56:00 AYUGEV9WZ4X5O Used - Like New False - .. ... ... ... ... - 115 2023-10-23 10:00:00 AYUGEV9WZ4X5O Used - Like New False - 116 2023-10-25 21:14:00 A1U9HDFCZO1A84 Used - Like New False - 117 2023-10-26 04:08:00 AYUGEV9WZ4X5O Used - Like New False - 118 2023-10-27 08:14:00 A1U9HDFCZO1A84 Used - Like New False - 119 2023-10-27 12:34:00 AYUGEV9WZ4X5O Used - Like New False - - """ - datetime_arr = [] - user_id_arr = [] - condition_map = { - "": "Unknown", - "2": "Used - Like New", - "3": "Used - Very Good", - "4": "Used - Good", - "5": "Used - Acceptable", - } - condition_arr = [] - isFBA_arr = [] - - for i in range(0, len(buybox_info), 4): - keepa_time = int(buybox_info[i]) - datetime_arr.append(keepa_minutes_to_time([keepa_time])[0]) - user_id_arr.append(buybox_info[i + 1]) - condition_arr.append(condition_map[buybox_info[i + 2]]) - isFBA_arr.append(_str_to_bool(buybox_info[i + 3])) - - df = pd.DataFrame( - { - "datetime": datetime_arr, - "user_id": user_id_arr, - "condition": condition_arr, - "isFBA": isFBA_arr, - } - ) - - return df - - -def keepa_minutes_to_time(minutes, to_datetime=True): - """Accept an array or list of minutes and converts it to a numpy datetime array. - - Assumes that keepa time is from keepa minutes from ordinal. - """ - # Convert to timedelta64 and shift - dt = np.array(minutes, dtype="timedelta64[m]") - dt = dt + KEEPA_ST_ORDINAL # shift from ordinal - - # Convert to datetime if requested - if to_datetime: - return dt.astype(datetime.datetime) - return dt - - -def run_and_get(coro): - """Attempt to run an async request.""" - try: - loop = asyncio.get_event_loop() - except RuntimeError: - loop = asyncio.new_event_loop() - task = loop.create_task(coro) - loop.run_until_complete(task) - return task.result() diff --git a/src/keepa/models/domain.py b/src/keepa/models/domain.py new file mode 100644 index 0000000..459484e --- /dev/null +++ b/src/keepa/models/domain.py @@ -0,0 +1,27 @@ +from enum import Enum + + +class Domain(Enum): + """Enumeration for Amazon domain regions. + + Examples + -------- + >>> import keepa + >>> keepa.Domain.US + + + """ + + RESERVED = "RESERVED" + US = "US" + GB = "GB" + DE = "DE" + FR = "FR" + JP = "JP" + CA = "CA" + RESERVED2 = "RESERVED2" + IT = "IT" + ES = "ES" + IN = "IN" + MX = "MX" + BR = "BR" diff --git a/src/keepa/models/status.py b/src/keepa/models/status.py index 834714d..516144c 100644 --- a/src/keepa/models/status.py +++ b/src/keepa/models/status.py @@ -1,8 +1,12 @@ +"""Status model.""" + from dataclasses import dataclass @dataclass class Status: + """Status model class.""" + tokensLeft: int | None = None refillIn: float | None = None refillRate: float | None = None diff --git a/src/keepa/plotting.py b/src/keepa/plotting.py index a0e8c92..af74c94 100644 --- a/src/keepa/plotting.py +++ b/src/keepa/plotting.py @@ -2,7 +2,7 @@ import numpy as np -from keepa.interface import keepa_minutes_to_time, parse_csv +from keepa.utils import keepa_minutes_to_time, parse_csv def plot_product( diff --git a/src/keepa/utils.py b/src/keepa/utils.py new file mode 100644 index 0000000..5d3ddcc --- /dev/null +++ b/src/keepa/utils.py @@ -0,0 +1,435 @@ +"""Interface module to download Amazon product and history data from keepa.com.""" + +import asyncio +import datetime +from typing import Any + +import numpy as np +import pandas as pd + +from keepa.constants import _SELLER_TIME_DATA_KEYS, DCODES, KEEPA_ST_ORDINAL, csv_indices +from keepa.models.domain import Domain + + +def is_documented_by(original): + """Avoid copying the documentation.""" + + def wrapper(target): + target.__doc__ = original.__doc__ + return target + + return wrapper + + +def _normalize_value(v: int, isfloat: bool, key: str) -> float | None: + """Normalize a single value based on its type and key context.""" + if v < 0: + return None + if isfloat: + v = float(v) / 100 + if key == "RATING": + v *= 10 + return v + + +def _is_stat_value_skippable(key: str, value: Any) -> bool: + """Determine if the stat value is skippable.""" + if key in { + "buyBoxSellerId", + "sellerIdsLowestFBA", + "sellerIdsLowestFBM", + "buyBoxShippingCountry", + "buyBoxAvailabilityMessage", + }: + return True + + # -1 or -2 --> not exist + if isinstance(value, int) and value < 0: + return True + + return False + + +def _parse_stat_value_list( + value_list: list, to_datetime: bool +) -> dict[str, float | tuple[Any, float]]: + """Parse a list of stat values into a structured dict.""" + convert_time = any(isinstance(v, list) for v in value_list if v is not None) + result = {} + + for ind, key, isfloat in csv_indices: + item = value_list[ind] if ind < len(value_list) else None + if item is None: + continue + + if convert_time: + ts, val = item + val = _normalize_value(val, isfloat, key) + if val is not None: + ts = keepa_minutes_to_time([ts], to_datetime)[0] + result[key] = (ts, val) + else: + val = _normalize_value(item, isfloat, key) + if val is not None: + result[key] = val + + return result + + +def _parse_stats(stats: dict[str, None, int, list[int]], to_datetime: bool): + """Parse numeric stats object. + + There is no need to parse strings or list of strings. Keepa stats object + response documentation: + https://keepa.com/#!discuss/t/statistics-object/1308 + """ + stats_parsed = {} + + for stat_key, stat_value in stats.items(): + if _is_stat_value_skippable(stat_key, stat_value): + continue + + if stat_value is not None: + if stat_key == "lastOffersUpdate": + stats_parsed[stat_key] = keepa_minutes_to_time([stat_value], to_datetime)[0] + elif isinstance(stat_value, list) and len(stat_value) > 0: + stat_value_dict = _parse_stat_value_list(stat_value, to_datetime) + if stat_value_dict: + stats_parsed[stat_key] = stat_value_dict + else: + stats_parsed[stat_key] = stat_value + + return stats_parsed + + +def _parse_seller(seller_raw_response, to_datetime): + sellers = list(seller_raw_response.values()) + for seller in sellers: + + def convert_time_data(key): + date_val = seller.get(key, None) + if date_val is not None: + return (key, keepa_minutes_to_time([date_val], to_datetime)[0]) + else: + return None + + seller.update( + filter(lambda p: p is not None, map(convert_time_data, _SELLER_TIME_DATA_KEYS)) + ) + + return dict(map(lambda seller: (seller["sellerId"], seller), sellers)) + + +def parse_csv(csv, to_datetime: bool = True, out_of_stock_as_nan: bool = True) -> dict[str, Any]: + """ + Parse csv list from keepa into a python dictionary. + + Parameters + ---------- + csv : list + csv list from keepa + to_datetime : bool, default: True + Modifies numpy minutes to datetime.datetime values. + Default True. + out_of_stock_as_nan : bool, optional + When True, prices are NAN when price category is out of stock. + When False, prices are -0.01 + Default True + + Returns + ------- + product_data : dict + Dictionary containing the following fields with timestamps: + + AMAZON: Amazon price history + + NEW: Marketplace/3rd party New price history - Amazon is + considered to be part of the marketplace as well, so if + Amazon has the overall lowest new (!) price, the + marketplace new price in the corresponding time interval + will be identical to the Amazon price (except if there is + only one marketplace offer). Shipping and Handling costs + not included! + + USED: Marketplace/3rd party Used price history + + SALES: Sales Rank history. Not every product has a Sales Rank. + + LISTPRICE: List Price history + + 5 COLLECTIBLE: Collectible Price history + + 6 REFURBISHED: Refurbished Price history + + 7 NEW_FBM_SHIPPING: 3rd party (not including Amazon) New price + history including shipping costs, only fulfilled by + merchant (FBM). + + 8 LIGHTNING_DEAL: 3rd party (not including Amazon) New price + history including shipping costs, only fulfilled by + merchant (FBM). + + 9 WAREHOUSE: Amazon Warehouse Deals price history. Mostly of + used condition, rarely new. + + 10 NEW_FBA: Price history of the lowest 3rd party (not + including Amazon/Warehouse) New offer that is fulfilled + by Amazon + + 11 COUNT_NEW: New offer count history + + 12 COUNT_USED: Used offer count history + + 13 COUNT_REFURBISHED: Refurbished offer count history + + 14 COUNT_COLLECTIBLE: Collectible offer count history + + 16 RATING: The product's rating history. A rating is an + integer from 0 to 50 (e.g. 45 = 4.5 stars) + + 17 COUNT_REVIEWS: The product's review count history. + + 18 BUY_BOX_SHIPPING: The price history of the buy box. If no + offer qualified for the buy box the price has the value + -1. Including shipping costs. The ``buybox`` parameter + must be True for this field to be in the data. + + 19 USED_NEW_SHIPPING: "Used - Like New" price history + including shipping costs. + + 20 USED_VERY_GOOD_SHIPPING: "Used - Very Good" price history + including shipping costs. + + 21 USED_GOOD_SHIPPING: "Used - Good" price history including + shipping costs. + + 22 USED_ACCEPTABLE_SHIPPING: "Used - Acceptable" price history + including shipping costs. + + 23 COLLECTIBLE_NEW_SHIPPING: "Collectible - Like New" price + history including shipping costs. + + 24 COLLECTIBLE_VERY_GOOD_SHIPPING: "Collectible - Very Good" + price history including shipping costs. + + 25 COLLECTIBLE_GOOD_SHIPPING: "Collectible - Good" price + history including shipping costs. + + 26 COLLECTIBLE_ACCEPTABLE_SHIPPING: "Collectible - Acceptable" + price history including shipping costs. + + 27 REFURBISHED_SHIPPING: Refurbished price history including + shipping costs. + + 30 TRADE_IN: The trade in price history. Amazon trade-in is + not available for every locale. + + 31 RENT: Rental price history. Requires use of the rental + and offers parameter. Amazon Rental is only available + for Amazon US. + + Notes + ----- + Negative prices + + """ + product_data = {} + + for ind, key, isfloat in csv_indices: + if csv[ind]: # Check if entry it exists + if "SHIPPING" in key: # shipping price is included + # Data goes [time0, value0, shipping0, time1, value1, + # shipping1, ...] + times = csv[ind][::3] + values = np.array(csv[ind][1::3]) + values += np.array(csv[ind][2::3]) + else: + # Data goes [time0, value0, time1, value1, ...] + times = csv[ind][::2] + values = np.array(csv[ind][1::2]) + + # Convert to float price if applicable + if isfloat: + nan_mask = values < 0 + values = values.astype(float) / 100 + if out_of_stock_as_nan: + values[nan_mask] = np.nan + + if key == "RATING": + values *= 10 + + timeval = keepa_minutes_to_time(times, to_datetime) + + product_data["%s_time" % key] = timeval + product_data[key] = values + + # combine time and value into a data frame using time as index + product_data[f"df_{key}"] = pd.DataFrame({"value": values}, index=timeval) + + return product_data + + +def format_items(items): + """Check if the input items are valid and formats them.""" + if isinstance(items, list) or isinstance(items, np.ndarray): + return np.unique(items) + elif isinstance(items, str): + return np.asarray([items]) + + +def _domain_to_dcode(domain: str | Domain) -> int: + """Convert a domain to a domain code.""" + if isinstance(domain, Domain): + domain_str = domain.value + else: + domain_str = domain + + if domain_str not in DCODES: + raise ValueError(f"Invalid domain code {domain}. Should be one of the following:\n{DCODES}") + return DCODES.index(domain_str) + + +def convert_offer_history(csv, to_datetime=True): + """Convert an offer history to human readable values. + + Parameters + ---------- + csv : list + Offer list csv obtained from ``['offerCSV']`` + + to_datetime : bool, optional + Modifies ``numpy`` minutes to ``datetime.datetime`` values. + Default ``True``. + + Returns + ------- + times : numpy.ndarray + List of time values for an offer history. + + prices : numpy.ndarray + Price (including shipping) of an offer for each time at an + index of times. + + """ + # convert these values to numpy arrays + times = csv[::3] + values = np.array(csv[1::3]) + values += np.array(csv[2::3]) # add in shipping + + # convert to dollars and datetimes + times = keepa_minutes_to_time(times, to_datetime) + prices = values / 100.0 + return times, prices + + +def _str_to_bool(string: str) -> bool: + if string: + return bool(int(string)) + return False + + +def process_used_buybox(buybox_info: list[str]) -> pd.DataFrame: + """ + Process used buybox information to create a Pandas DataFrame. + + Parameters + ---------- + buybox_info : list of str + A list containing information about used buybox in a specific order: + [Keepa time minutes, seller id, condition, isFBA, ...] + + Returns + ------- + pd.DataFrame + A DataFrame containing four columns: + - 'datetime': Datetime objects converted from Keepa time minutes. + - 'user_id': String representing the seller ID. + - 'condition': String representing the condition of the product. + - 'isFBA': Boolean indicating whether the offer is Fulfilled by Amazon. + + Notes + ----- + The `condition` is mapped from its code to a descriptive string. + The `isFBA` field is converted to a boolean. + + Examples + -------- + Load in product offers and convert the buy box data into a + ``pandas.DataFrame``. + + >>> import keepa + >>> key = "" + >>> api = keepa.Keepa(key) + >>> response = api.query("B0088PUEPK", offers=20) + >>> product = response[0] + >>> buybox_info = product["buyBoxUsedHistory"] + >>> df = keepa.process_used_buybox(buybox_info) + datetime user_id condition isFBA + 0 2022-11-02 16:46:00 A1QUAC68EAM09F Used - Like New True + 1 2022-11-13 10:36:00 A18WXU4I7YR6UA Used - Very Good False + 2 2022-11-15 23:50:00 AYUGEV9WZ4X5O Used - Like New False + 3 2022-11-17 06:16:00 A18WXU4I7YR6UA Used - Very Good False + 4 2022-11-17 10:56:00 AYUGEV9WZ4X5O Used - Like New False + .. ... ... ... ... + 115 2023-10-23 10:00:00 AYUGEV9WZ4X5O Used - Like New False + 116 2023-10-25 21:14:00 A1U9HDFCZO1A84 Used - Like New False + 117 2023-10-26 04:08:00 AYUGEV9WZ4X5O Used - Like New False + 118 2023-10-27 08:14:00 A1U9HDFCZO1A84 Used - Like New False + 119 2023-10-27 12:34:00 AYUGEV9WZ4X5O Used - Like New False + + """ + datetime_arr = [] + user_id_arr = [] + condition_map = { + "": "Unknown", + "2": "Used - Like New", + "3": "Used - Very Good", + "4": "Used - Good", + "5": "Used - Acceptable", + } + condition_arr = [] + isFBA_arr = [] + + for i in range(0, len(buybox_info), 4): + keepa_time = int(buybox_info[i]) + datetime_arr.append(keepa_minutes_to_time([keepa_time])[0]) + user_id_arr.append(buybox_info[i + 1]) + condition_arr.append(condition_map[buybox_info[i + 2]]) + isFBA_arr.append(_str_to_bool(buybox_info[i + 3])) + + df = pd.DataFrame( + { + "datetime": datetime_arr, + "user_id": user_id_arr, + "condition": condition_arr, + "isFBA": isFBA_arr, + } + ) + + return df + + +def keepa_minutes_to_time(minutes, to_datetime=True): + """Accept an array or list of minutes and converts it to a numpy datetime array. + + Assumes that keepa time is from keepa minutes from ordinal. + """ + # Convert to timedelta64 and shift + dt = np.array(minutes, dtype="timedelta64[m]") + dt = dt + KEEPA_ST_ORDINAL # shift from ordinal + + # Convert to datetime if requested + if to_datetime: + return dt.astype(datetime.datetime) + return dt + + +def run_and_get(coro): + """Attempt to run an async request.""" + try: + loop = asyncio.get_event_loop() + except RuntimeError: + loop = asyncio.new_event_loop() + task = loop.create_task(coro) + loop.run_until_complete(task) + return task.result() diff --git a/tests/test_async_interface.py b/tests/test_async_interface.py index 8bfea3c..2bb915c 100644 --- a/tests/test_async_interface.py +++ b/tests/test_async_interface.py @@ -15,7 +15,7 @@ import keepa # reduce the request limit for testing -keepa.interface.REQLIM = 2 +keepa.keepa_async.REQLIM = 2 path = os.path.dirname(os.path.realpath(__file__)) keyfile = os.path.join(path, "key") diff --git a/tests/test_interface.py b/tests/test_interface.py index df67867..797e5aa 100644 --- a/tests/test_interface.py +++ b/tests/test_interface.py @@ -18,7 +18,7 @@ from keepa import Keepa # reduce the request limit for testing -keepa.interface.REQLIM = 2 +keepa.keepa_sync.REQLIM = 2 path = os.path.dirname(os.path.realpath(__file__)) keyfile = os.path.join(path, "key") From ee1121de3437f82ba4d5ae99e834866a9028158b Mon Sep 17 00:00:00 2001 From: ryzanbui02 Date: Sat, 8 Nov 2025 04:50:41 +0000 Subject: [PATCH 5/7] docs: docstring for domain module --- src/keepa/models/domain.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/keepa/models/domain.py b/src/keepa/models/domain.py index 459484e..868edde 100644 --- a/src/keepa/models/domain.py +++ b/src/keepa/models/domain.py @@ -1,3 +1,5 @@ +"""Module defining the Domain enumeration for Amazon regions.""" + from enum import Enum From 82bb922a2378654aa5dc25a9ca34db6140bf8f59 Mon Sep 17 00:00:00 2001 From: Alex Kaszynski Date: Sat, 8 Nov 2025 08:16:23 -0700 Subject: [PATCH 6/7] make default extra_params None --- src/keepa/keepa_async.py | 5 ++++- src/keepa/keepa_sync.py | 7 +++++-- 2 files changed, 9 insertions(+), 3 deletions(-) diff --git a/src/keepa/keepa_async.py b/src/keepa/keepa_async.py index 5eb2aef..7a5a4d7 100644 --- a/src/keepa/keepa_async.py +++ b/src/keepa/keepa_async.py @@ -165,12 +165,15 @@ async def query( raw: bool = False, videos: bool = False, aplus: bool = False, - extra_params: dict[str, Any] = {}, + extra_params: dict[str, Any] | None = None, ): """Documented in Keepa.query.""" if raw: raise ValueError("Raw response is only available in the non-async class") + if extra_params is None: + extra_params = {} + # Format items into numpy array try: items = format_items(items) diff --git a/src/keepa/keepa_sync.py b/src/keepa/keepa_sync.py index 9569231..aa52fac 100644 --- a/src/keepa/keepa_sync.py +++ b/src/keepa/keepa_sync.py @@ -266,7 +266,7 @@ def query( raw: bool = False, videos: bool = False, aplus: bool = False, - extra_params: dict[str, Any] = {}, + extra_params: dict[str, Any] | None = {}, ) -> list[dict[str, Any]]: """ Perform a product query of a list, array, or single ASIN. @@ -407,7 +407,7 @@ def query( available. If you need up-to-date data, you have to use the offers parameter. - extra_params : dict, default: {} + extra_params : dict[str, Any], optional Dictionary of parameters that are not specifically called out in the api. For example, a new parameters might be added to `Request.java @@ -621,6 +621,9 @@ def query( else: log.debug("Executing %d item product query", nitems) + if extra_params is None: + extra_params = {} + # check offer input if offers: if not isinstance(offers, int): From df4818dd67308719f47f3505ab3693c078fcbae1 Mon Sep 17 00:00:00 2001 From: Alex Kaszynski Date: Sat, 8 Nov 2025 08:26:22 -0700 Subject: [PATCH 7/7] Update src/keepa/utils.py --- src/keepa/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/keepa/utils.py b/src/keepa/utils.py index 5d3ddcc..e467017 100644 --- a/src/keepa/utils.py +++ b/src/keepa/utils.py @@ -1,4 +1,4 @@ -"""Interface module to download Amazon product and history data from keepa.com.""" +"""Shared utilities module for ``keepa``.""" import asyncio import datetime