def main():
logger.enable(__name__)
processor = Jamboree()
example_handler = ExampleSearchHandler()
example_handler.processor = processor
example_handler["name"] = "Boi Gurl"
example_handler["category"] = "marketsx"
example_handler["sample_tags"] = ["four", "five", "six"]
# TODO: Figure out subcategory update
example_handler["subcategories"] = {
"hello": "world",
"country": "US",
}
example_handler["secondsub"] = {"my": "jac"}
example_handler.replacement["secondsub"] = {"my": "jack"}
example_handler["live"] = False
# example_handler.remove()
example_handler.insert(allow_duplicates=True)
records1 = example_handler.find()
records2 = example_handler.find()
records3 = example_handler.find()
logger.warning((records1, len(records1)))
logger.success((records2, len(records2)))
logger.error((records3, len(records3)))
def __init__(self):
# List of datasets we intend to download from yahoo finance
self.datalist = ["MSFT", "AAPL", "GOOG"]
self.datasets = []
self.dataset_info = {}
self.processor = Jamboree()
self.pricedata_management = PriceData()
self.pricedata_management.processor = self.processor
self.dow_metadata = []
self.reloaded_datasets = []
self.episodes = []
self._raw = []
self.set_name = "default_test"
def main():
import pandas_datareader.data as web
# data_msft = web.DataReader('MSFT','yahoo',start='2019/9/1',end='2020/1/30').round(2)
# data_apple = web.DataReader('AAPL','yahoo',start='2019/9/1',end='2020/1/30').round(2)
episode_id = uuid.uuid4().hex
jambo = Jamboree()
jam_processor = Jamboree()
data_hander = PriceData()
data_hander.processor = jam_processor
trx_tron = data_hander.build("Tron",
"TRX",
country="Japan",
sector="oil",
market="commodities",
exchange="binance")
# The episode and live parameters are probably not good for the scenario. Will probably need to switch to something else to identify data
trx_tron.episode = episode_id
trx_tron.live = False
trx_tron.reset()
res = trx_tron.multi_search(country="jap")
pprint.pprint(res)
def main():
import pandas_datareader.data as web
# data_msft = web.DataReader('MSFT','yahoo',start='2019/9/1',end='2020/1/30').round(2)
# data_apple = web.DataReader('AAPL','yahoo',start='2019/9/1',end='2020/1/30').round(2)
episode_id = uuid.uuid4().hex
jambo = Jamboree()
jam_processor = Jamboree()
data_hander = OrderbookData()
data_hander.processor = jam_processor
data_hander.event = jambo
# The episode and live parameters are probably not good for the scenario. Will probably need to switch to something else to identify data
data_hander.episode = episode_id
data_hander.live = False
data_hander['subcategories'] = {
"market": "stock",
"country": "Mexico",
"sector": "tech",
"exchange": "binance",
}
data_hander['name'] = "ETH Ethereum"
data_hander.reset()
# data_hander.store_time_df(data_msft, is_bar=True)
data_hander['name'] = "BTC Bitcoin"
# data_hander.reset()
# data_hander.store_time_df(data_apple, is_bar=True)
start = maya.now()._epoch
# res1 = data_hander.by_name("Bitcoin")
# logger.debug(res1)
end = maya.now()._epoch
logger.info(end - start)
res = data_hander.multi_part_search(market="stock",
exchange="binance",
country="Mexico")
logger.warning(res)
def main():
jambo = Jamboree()
sample_env_handler = SampleEnvHandler()
sample_env_handler.limit = 250
sample_env_handler.processor = jambo
# with timecontext():
current_time = maya.now()._epoch
mult = 60
# Create a new set of records and swap to another location to be acted on.
sample_env_handler['episode'] = uuid.uuid1().hex
with timecontext():
super_index = 0
for _ in range(100):
v1 = random.uniform(0, 12)
sample_env_handler.save({
"value":
v1,
"time": (current_time + (mult * super_index))
})
super_index += 1
many_list = []
catch_index_1 = random.randint(super_index - 10, super_index + 3)
catch_index_2 = random.randint(super_index - 10, super_index + 3)
last_by_time = (current_time + (mult * catch_index_1))
last_by_time_2 = (current_time + (mult * catch_index_2))
for _ in range(10):
item = {
"valuesssssss": random.uniform(0, 12),
"time": (current_time + (mult * super_index))
}
many_list.append(item)
super_index += 1
sample_env_handler.save_many(many_list)
latest = sample_env_handler.last()
last_by = sample_env_handler.last_by(last_by_time, ar="relative")
last_by_2 = sample_env_handler.last_by(last_by_time_2, ar="relative")
t1 = last_by.get('time', time.time())
t2 = last_by_2.get('time', time.time())
logger.info(latest)
logger.success(t1)
logger.error(t2)
"is_filter": True,
"values": {
"is_exact": True,
"term": submetatype
}
}
self._search['name'] = self.name
self._search['category'] = self.category
self._search['subcategories'] = self.subcategories
self._search['abbreviation'] = self.abbreviation
self._search.processor = self.processor
return self._search
def reset(self):
self.check()
qo = self.setup_query()
qo.pop("mtype", None)
if self.description is not None:
qo['description'] = self.description
return self.search.Create(allow_duplicates=False,
no_overwrite_must_have=True,
**qo)
if __name__ == "__main__":
jambo = Jamboree()
metahandler = MetaHandler()
metahandler.event = jambo
metahandler.reset()
_multi["submetatype"] = item["submetatype"]
_multi["category"] = item["category"]
_multi["metatype"] = item["metatype"]
_multi["subcategories"] = (item["subcategories"]).to_dict()
_multi.reset()
return _multi
if __name__ == "__main__":
with example_space("Multi-Data-Management") as example:
# set_name = uuid.uuid4().hex
with logger.catch():
set_name = "ac688d95336e41bdbe61c5c804d07f1a"
episode = uuid.uuid4().hex
# jam = Jamboree()
jam_proc = Jamboree()
multi_data = MultiDataManagement()
multi_data.processor = jam_proc
# The episode and live parameters are probably not good for the scenario.
# Will probably need to switch to something else to identify data.
multi_data["name"] = set_name
multi_data["category"] = "markets"
multi_data["subcategories"] = {
"market": "stock",
"country": "US",
"sector": "techologyyyyyyyy",
}
multi_data["submetatype"] = "DINGO"
multi_data["abbreviation"] = "MSFT"
multi_data.episode = episode
multi_data.live = False