def stream_manager_010003(cls, d_xoi=None):
sql_maxver = "SELECT im.matched_id, xfi.fund_issue_org_amac, manage_type_amac, type_name_amac, fi.fund_name, fi.foundation_date, fi.end_date, fi.fund_status " \
"FROM x_fund_info_private xfi " \
"JOIN (SELECT fund_id, MAX(version) latest_ver FROM x_fund_info_private GROUP BY fund_id) tb_latest " \
"ON xfi.version = tb_latest.latest_ver AND xfi.fund_id = tb_latest.fund_id " \
"JOIN base.id_match im ON im.source_id = xfi.fund_id AND im.id_type = 1 AND im.source = '010003' AND im.is_used = 1 " \
"LEFT JOIN base.fund_info fi " \
"ON im.matched_id = fi.fund_id AND im.id_type = 1 AND im.source = '010003' " \
"WHERE fund_name_amac NOT LIKE '%%信托计划'"
inp = MysqlInput(ENGINE_C, sql_maxver)
inp2 = MysqlInput(ENGINE_B, "SELECT org_id, org_name FROM base.org_info")
def clean_org_type(mng_tp, tp):
# 私募证券投资基金 = 证券投资基金; 其他私募投资基金 = 其他投资基金
if mng_tp == "顾问管理":
if tp in {"私募证券投资基金", "证券投资基金"}:
return "基金管理人"
elif mng_tp == "受托管理":
if tp in {"私募证券投资基金", "证券投资基金", "创业投资基金", "其他私募投资基金", "其他投资基金", "股权投资基金"}:
return "基金管理人"
elif mng_tp == "自我管理":
if tp in {"私募证券投资基金", "证券投资基金", "股权投资基金", "创业投资基金", "其他私募投资基金", "其他投资基金"}:
return "基金管理人"
if d_xoi is None:
d_xoi = cls._d_oi_manager()
vm = transform.ValueMap(
OrderedDict([
("fund_issue_org_amac", lambda x: x.strip()),
("org_id", (lambda x: d_xoi.get(x), "fund_issue_org_amac")),
(FundOrgMapping.org_type.name,
(lambda mng_tp, tp: clean_org_type(mng_tp, tp), "manage_type_amac", "type_name_amac")),
(FundOrgMapping.is_current.name, (lambda x: cls._clean_iscurrent(x), "fund_status"))
])
)
jn = transform.Join(inp2, how="left", on="org_id")
dn = transform.Dropna(subset=["matched_id", "org_id", FundOrgMapping.org_type.name])
vm2 = transform.ValueMap({
FundOrgMapping.org_type_code.name: (lambda x: 2 if x == "基金管理人" else None, FundOrgMapping.org_type.name),
})
sk = transform.MapSelectKeys(cls.FIELDS)
s = Stream(inp, transform=(vm, jn, dn, vm2, sk))
return s
def stream_consultant_010004(cls, d_xoi=None):
"""
清洗010004源(证券公司)发行产品的投顾公司配对信息;
Args:
d_xoi:
Returns:
"""
sql_maxver = "SELECT im.matched_id, xfi.fund_issue_org_amac, manage_type_amac, fi.fund_name, fi.foundation_date, fi.end_date, fi.fund_status " \
"FROM x_fund_info_securities xfi " \
"JOIN (SELECT fund_id, MAX(version) latest_ver FROM x_fund_info_securities GROUP BY fund_id) tb_latest " \
"ON xfi.version = tb_latest.latest_ver AND xfi.fund_id = tb_latest.fund_id " \
"JOIN base.id_match im ON im.source_id = xfi.fund_id AND im.id_type = 1 AND im.source = '010004' AND im.is_used = 1 " \
"LEFT JOIN base.fund_info fi ON im.matched_id = fi.fund_id AND im.id_type = 1 AND im.source = '010004'" \
"WHERE fund_name_amac NOT LIKE '%%信托计划'"
inp = MysqlInput(ENGINE_C, sql_maxver)
inp2 = MysqlInput(ENGINE_B, "SELECT org_id, org_name FROM base.org_info")
if d_xoi is None:
d_xoi = cls._d_oi_consultant()
vm = transform.ValueMap(
OrderedDict([
("fund_issue_org_amac", lambda x: x.strip()),
("org_id", (lambda x: d_xoi.get(x), "fund_issue_org_amac")),
(FundOrgMapping.org_type.name, (lambda x: {"主动管理": "投资顾问"}.get(x), "manage_type_amac")),
(FundOrgMapping.is_current.name, (lambda x: cls._clean_iscurrent(x), "fund_status"))
])
)
jn = transform.Join(inp2, how="left", on="org_id")
dn = transform.Dropna(subset=["matched_id", "org_id", FundOrgMapping.org_type.name])
vm2 = transform.ValueMap({
FundOrgMapping.org_type_code.name: (lambda x: 1 if x == "投资顾问" else None, FundOrgMapping.org_type.name),
})
dd = transform.DropDuplicate(subset=["matched_id", "org_id", FundOrgMapping.org_type.name])
sk = transform.MapSelectKeys(cls.FIELDS)
s = Stream(inp, transform=[vm, jn, dn, vm2, dd, sk]) # 先去空, 避免空值产生, 导致整形列变成浮点型
return s
def stream_020001(cls, fund_id):
"""
清洗 d_fund_position（020001）;
"""
sql = " \
SELECT dp.fund_id, dp.fund_name, dp.data_source, dp.statistic_date, dp.subject_id, dp.subject_name, \
dp.quantity, dp.scale, dp.proportion, fa.total_asset FROM \
crawl_public.d_fund_position as dp \
JOIN base_public.fund_asset_scale AS fa \
ON dp.fund_id = fa.fund_id and dp.statistic_date=fa.statistic_date \
WHERE dp.type= '股票' AND dp.data_source= '020001'"
if fund_id is not None:
fids = SQL.values4sql(fund_id)
sql += "AND dp.fund_id IN {fids}".format(fids=fids)
inp = MysqlInput(ENGINE_RD, sql)
vm = transform.ValueMap({
"quantity":
lambda x: sub_wrong_to_none(x),
"scale":
lambda x: sub_wrong_to_none(x),
"proportion":
lambda x: sub_wrong_to_none(x),
"total_asset":
lambda x: float(x) if type(x) is str else x
})
vm1 = transform.ValueMap({
"quantity": lambda x: cls.clean_amount(x),
"scale": lambda x: cls.clean_amount(x)
})
vm2 = transform.ValueMap({
"quantity":
lambda x: float(x),
"scale":
lambda x: float(x),
"proportion":
lambda x: float(x) / 100 if type(x) is str else x
})
sk = transform.MapSelectKeys({
"fund_id": "fund_id",
"fund_name": "fund_name",
"data_source": "data_source",
"statistic_date": "statistic_date",
"subject_id": "subject_id",
"subject_name": "subject_name",
# "quantity": "quantity",
"scale": "scale",
"proportion": "proportion_net",
"total_asset": "asset_scale"
})
s = Stream(inp, transform=[vm, vm1, vm2, sk])
return s
def stream_010001(cls):
"""
清洗x_org_info(010001)
"""
sql = "SELECT org_id,legal_person_resume,special_tips FROM ( \
SELECT * FROM (SELECT matched_id,source_id FROM base.id_match WHERE \
source='010001' and id_type=2 and is_used=1) \
as b LEFT JOIN \
(SELECT org_id,legal_person_resume,special_tips FROM \
crawl_private.`x_org_info` \
ORDER BY version DESC) as p ON b.source_id=p.org_id \
WHERE p.org_id is not NULL) AS T \
GROUP BY T.org_id"
inp = MysqlInput(ENGINE_RD, sql)
vm = transform.ValueMap({
"legal_person_resume":
lambda x: sub_wrong_to_none(x),
"special_tips":
lambda x: sub_wrong_to_none(x)
})
sk = transform.MapSelectKeys({
'org_id':
'org_id',
"special_tips":
"special_tips",
"legal_person_resume":
"legal_person_resume"
})
s = Stream(inp, transform=[vm, sk])
return s
def stream_020001(cls, fund_ids):
sql = "SELECT im.matched_id, fi.fund_name, im.data_source, dfp.statistic_date, dfp.subject_id, dfp.subject_name, " \
"dfp.scale, dfp.proportion, fas.total_asset " \
"FROM base_public.id_match im " \
"JOIN crawl_public.d_fund_position dfp " \
"ON im.source_id = dfp.fund_id AND im.data_source = dfp.data_source " \
"JOIN base_public.fund_info fi ON im.matched_id = fi.fund_id " \
"left JOIN base_public.fund_asset_scale fas ON dfp.fund_id = fas.fund_id AND dfp.statistic_date = fas.statistic_date " \
"WHERE type = '债券' AND im.matched_id IN {fids} AND im.id_type = 1 AND im.is_used = 1 " \
"AND dfp.fund_id NOT IN (" \
"SELECT DISTINCT fund_id FROM crawl_public.d_fund_position WHERE data_source = '020002')" \
"AND im.data_source = '020001'".format(fids=sf.SQL.values4sql(fund_ids))
inp = MysqlInput(cls.engine, sql)
vm = transform.ValueMap({
"proportion":
lambda x: float(x.replace("%", "")) / 100,
"scale":
lambda x: cls._clean_amount(x),
})
sk = transform.MapSelectKeys({
"matched_id": "fund_id",
"fund_name": None,
"data_source": None,
"statistic_date": None,
"subject_id": None,
"subject_name": None,
"scale": None,
"proportion": "proportion_net",
"total_asset": "asset_scale",
})
return base.Stream(inp, transform=[vm, sk])
def conflu_is_member(cls):
# is_member, member_type
sql = "SELECT org_id, is_reg_now, is_member, member_type FROM {tb_test} ".format(tb_test=TEST_TABLE)
inp = MysqlInput(ENGINE_RD, sql)
def clean_membertype(is_reg, is_member, member_type, org_id):
if is_reg == "否":
if org_id[0] == "P":
return "注销备案资格"
else:
return "未备案"
if is_reg == "是":
if is_member == "否":
return "尚未取得会员资格"
return member_type
vm = transform.ValueMap({
OrgInfo.is_member.name: (lambda is_reg, is_member: "否" if is_reg == "否" else is_member, "is_reg_now", "is_member"),
OrgInfo.member_type.name: (lambda is_reg, is_member, member_type, org_id: clean_membertype(is_reg, is_member, member_type, org_id), "is_reg_now", "is_member", "member_type", "org_id")
})
sk = transform.MapSelectKeys({
"org_id": OrgInfo.org_id.name,
OrgInfo.is_member.name: None,
OrgInfo.member_type.name: None,
})
s = Stream(inp, [vm, sk])
return Confluence(s)
def conflu_place(cls):
# region, prov, city, area
sql = "SELECT org_id, address FROM {tb_test} WHERE address IS NOT NULL".format(tb_test=TEST_TABLE)
inp = MysqlInput(ENGINE_RD, sql)
vm0 = transform.ValueMap({
"__tmp": (lambda x: cls._clean_place(x), "address")
})
vm = transform.ValueMap({
OrgInfo.region.name: (lambda x: x[0], "__tmp"),
OrgInfo.prov.name: (lambda x: x[1], "__tmp"),
OrgInfo.city.name: (lambda x: x[2], "__tmp"),
OrgInfo.area.name: (lambda x: x[3], "__tmp"),
})
sk = transform.MapSelectKeys({
OrgInfo.org_id.name: None,
OrgInfo.region.name: None,
OrgInfo.prov.name: None,
OrgInfo.city.name: None,
OrgInfo.area.name: None,
})
s = Stream(inp, transform=[vm0, vm, sk])
return Confluence(s)
def stream_602_4(cls, c_cleaned):
sql = "SELECT fi.fund_id, fi.fund_name " \
"FROM base.fund_info fi " \
"WHERE fi.fund_id NOT IN (SELECT DISTINCT fund_id FROM base.fund_type_mapping_import WHERE typestandard_code = 602) "
inp = MysqlInput(ENGINE, sql)
# 非惰性求值
fids = set(c_cleaned.dataframe["fund_id"])
vm0 = transform.ValueMap({
"__tmp": (lambda x: (60201, "非结构化", None, None) if x not in fids else (None, None, None, None), "fund_id")
})
vm1 = transform.ValueMap({
FundTypeMappingImport.typestandard_code.name: 602,
FundTypeMappingImport.typestandard_name.name: "按结构类型分类",
FundTypeMappingImport.type_code.name: (lambda x: x[0], "__tmp"),
FundTypeMappingImport.type_name.name: (lambda x: x[1], "__tmp"),
FundTypeMappingImport.stype_code.name: (lambda x: x[2], "__tmp"),
FundTypeMappingImport.stype_name.name: (lambda x: x[3], "__tmp"),
FundTypeMappingImport.classified_by.name: CLASSIFIED_BY
})
sk = transform.MapSelectKeys(cls.FIXED_FIELDS)
dn = transform.Dropna(subset=[FundTypeMappingImport.type_code.name, FundTypeMappingImport.stype_code.name], how="all")
s = base.Stream(inp, [vm0, vm1, sk, dn])
return s
def stream_000001():
session = dbsession(bind=engine_r)
stmt = session.query(YBondInfo).join(
BondInfo, YBondInfo.bond_id == BondInfo.bond_id).filter(
and_(YBondInfo.is_used == 1,
YBondInfo.is_used == 1)).with_entities(
YBondInfo.bond_id, YBondInfo.interest_type)
inp = MysqlInput(session.bind, stmt)
dn = transform.Dropna(subset=[YBondInfo.interest_type.name])
km = transform.MapSelectKeys({
YBondInfo.bond_id.name:
BondInfo.bond_id.name,
YBondInfo.source_id.name:
None,
YBondInfo.interest_type.name:
BondInfo.interest_type.name,
})
s = Stream(inp, (
dn,
km,
))
return s
def stream_consultant_000001(cls):
sql = "SELECT fund_id, fund_name, oi.org_id, oi.org_name, org_type_code, start_date, end_date, is_current " \
"FROM crawl_private.y_fund_org_mapping yfom " \
"JOIN base.org_info oi ON yfom.org_id = oi.org_id " \
"WHERE org_type_code = 1 AND is_used = 1"
inp = MysqlInput(ENGINE_C, sql)
vm = transform.ValueMap({
"org_type": "投资顾问"
})
sk = transform.MapSelectKeys({
"fund_id": None,
"fund_name": None,
"org_id": None,
"org_name": None,
"org_type": None,
"org_type_code": None,
"start_date": None,
"end_date": None,
"is_current": None,
})
dn = transform.Dropna(
subset=[FundOrgMapping.fund_id.name, FundOrgMapping.org_id.name, FundOrgMapping.org_type_code.name]
)
s = Stream(inp, transform=[vm, sk, dn])
return s
def stream_020001_ts304(cls):
source_id = "020001"
tb = "crawl_private.d_fund_info"
tmpsql = cls.SQL_X04.format(tb=tb, sid=source_id)
inp = MysqlInput(ENGINE, tmpsql)
vm = transform.ValueMap(
OrderedDict([
[FundTypeSource.source_id.name, source_id],
[FundTypeSource.typestandard_code.name, "104"],
[FundTypeSource.typestandard_name.name, "按发行主体分类"],
[
"__cached",
(lambda x: cls.TS_MAPPER_304.get(x, [None, None]),
"fund_type_issuance")
],
[FundTypeSource.type_code.name, (lambda x: x[0], "__cached")],
[FundTypeSource.type_name.name, (lambda x: x[1], "__cached")],
]))
sk = transform.MapSelectKeys({
"matched_id": FundTypeSource.fund_id.name,
"fund_name": FundTypeSource.fund_name.name,
FundTypeSource.source_id.name: None,
FundTypeSource.typestandard_code.name: None,
FundTypeSource.typestandard_name.name: None,
FundTypeSource.type_code.name: None,
FundTypeSource.type_name.name: None,
})
dn = transform.Dropna(subset=[FundTypeSource.type_code.name])
s = base.Stream(inp, [vm, sk, dn])
return s
def gfundnv2src(fund_id=None, source_id=None, update_time=None):
session = dbsession(bind=engine_r)
stmt = session.query(GFundNv).filter(
GFundNv.is_used == 1, GFundNv.statistic_date > MIN_DATE, GFundNv.nav < 2000
).with_entities(
GFundNv.fund_id, GFundNv.source_id, GFundNv.statistic_date, GFundNv.source_id, GFundNv.nav, GFundNv.added_nav, GFundNv.adjusted_nav
)
if update_time is not None:
stmt = stmt.filter(GFundNv.update_time >= update_time)
if fund_id is not None:
stmt = stmt.filter(GFundNv.fund_id == fund_id)
if source_id is not None:
stmt = stmt.filter(GFundNv.source_id == source_id)
inp = MysqlInput(session.bind, stmt)
vm = transform.ValueMap({
GFundNv.added_nav.name: lambda x: None if x == 0 else x
})
km = transform.MapSelectKeys({
GFundNv.fund_id.name: FundNvDataSource.fund_id.name,
GFundNv.statistic_date.name: FundNvDataSource.statistic_date.name,
GFundNv.source_id.name: FundNvDataSource.source_id.name,
GFundNv.nav.name: FundNvDataSource.nav.name,
GFundNv.added_nav.name: FundNvDataSource.added_nav.name,
GFundNv.adjusted_nav.name: FundNvDataSource.adjusted_nav.name,
})
s = Stream(inp, [vm, km])
return s
def tfundnv2src(fund_id=None, source_id=None, update_time=None):
session = dbsession(bind=engine_r)
stmt = session.query(TFundNv).join(
IdMatch, and_(IdMatch.source_id == TFundNv.fund_id, IdMatch.source == TFundNv.source_id, IdMatch.id_type == 1, IdMatch.is_used == 1)
).filter(
TFundNv.is_used == 1, TFundNv.source_id == source_id, TFundNv.statistic_date > MIN_DATE, TFundNv.nav < 2000
).with_entities(
IdMatch.matched_id, TFundNv.fund_id, TFundNv.statistic_date, TFundNv.source_id, TFundNv.nav, TFundNv.added_nav
)
if update_time is not None:
stmt = stmt.filter(TFundNv.update_time >= update_time)
if fund_id is not None:
stmt = stmt.filter(TFundNv.fund_id == fund_id)
inp = MysqlInput(session.bind, stmt)
vm = transform.ValueMap({
TFundNv.added_nav.name: lambda x: None if x == 0 else x
})
km = transform.MapSelectKeys({
IdMatch.matched_id.name: FundNvDataSource.fund_id.name,
TFundNv.statistic_date.name: FundNvDataSource.statistic_date.name,
TFundNv.source_id.name: FundNvDataSource.source_id.name,
TFundNv.nav.name: FundNvDataSource.nav.name,
TFundNv.added_nav.name: FundNvDataSource.added_nav.name,
})
s = Stream(inp, (vm, km))
return s
def gfundnv2src_whole(fund_id=None, source_id=None, update_time=None):
session = dbsession(bind=engine_r)
stmt = session.query(GFundNv).filter(
GFundNv.source_id == source_id,
GFundNv.is_used == 1).with_entities(GFundNv.fund_id, GFundNv.source_id,
GFundNv.statistic_date,
GFundNv.source_id, GFundNv.nav,
GFundNv.added_nav,
GFundNv.adjusted_nav)
if update_time is not None:
stmt = stmt.filter(GFundNv.update_time >= update_time)
if fund_id is not None:
stmt = stmt.filter(GFundNv.fund_id == fund_id)
inp = MysqlInput(session.bind, stmt)
km = transform.MapSelectKeys({
GFundNv.fund_id.name:
FundNvDataSource.fund_id.name,
GFundNv.statistic_date.name:
FundNvDataSource.statistic_date.name,
GFundNv.source_id.name:
FundNvDataSource.source_id.name,
GFundNv.nav.name:
FundNvDataSource.nav.name,
GFundNv.added_nav.name:
FundNvDataSource.added_nav.name,
GFundNv.adjusted_nav.name:
FundNvDataSource.adjusted_nav.name,
})
s = Stream(inp, (km, ))
return s
def stream_020002(cls):
"""
清洗 d_org_asset_scale;
"""
sql = " \
select idm.matched_id, doa.org_name, doa.data_source, doa.statistic_date, doa.total_asset, doa.funds_num \
FROM crawl_public.d_org_asset_scale as doa \
JOIN base_public.id_match as idm \
ON doa.org_id = idm.source_id \
WHERE idm.id_type = 2 AND idm.is_used = 1 AND doa.data_source = '020002' \
AND idm.data_source = '020002'"
inp = MysqlInput(ENGINE_RD, sql)
vm = transform.ValueMap({
"total_asset":
lambda x: cls.sub_wrong_to_none(x) if type(x) is str else x
})
sk = transform.MapSelectKeys({
"matched_id": "org_id",
# 'org_name': 'org_name',
'data_source': 'data_source',
'statistic_date': 'statistic_date',
'total_asset': 'total_asset',
'funds_num': 'funds_num'
})
s = Stream(inp, transform=[vm, sk])
return s
def stream_020003(cls):
"""
清洗 d_person_info;
"""
sql = "SELECT im.matched_id, person_name, background FROM crawl_private.d_person_info tb_main " \
"JOIN (SELECT person_id, MAX(version) latest_ver FROM crawl_private.d_person_info GROUP BY person_id) tb_latest " \
"ON tb_main.version = tb_latest.latest_ver AND tb_main.person_id = tb_latest.person_id " \
"JOIN base.id_match im ON im.source_id = tb_main.person_id " \
"AND im.id_type = 3 AND im.source = '020003' AND im.is_used = 1 "
inp = MysqlInput(ENGINE_RD, sql)
vm = transform.ValueMap({
"background":
lambda x: cls.BACKGROUND.get(x) if type(x) is str else x,
"person_name_py": (lambda x: "".join(
[x[0] for x in py(x, style=py_style.FIRST_LETTER)]).upper(),
"person_name"),
})
sk = transform.MapSelectKeys({
"matched_id": "person_id",
'background': 'background',
'person_name': 'person_name',
"person_name_py": "person_name_py"
})
s = Stream(inp, transform=[vm, sk])
return s
def stream_020001_op():
sql = "SELECT im.matched_id, person_name FROM crawl_private.d_org_person tb_main " \
"JOIN (SELECT person_id, MAX(version) latest_ver FROM crawl_private.d_org_person GROUP BY person_id) tb_latest " \
"ON tb_main.version = tb_latest.latest_ver AND tb_main.person_id = tb_latest.person_id " \
"JOIN base.id_match im ON im.source_id = tb_main.person_id " \
"AND im.id_type = 3 AND im.source = '020001' AND im.is_used = 1 "
inp = MysqlInput(ENGINE, sql)
vm = transform.ValueMap(
OrderedDict([
[
PersonInfo.person_name_py.name,
(lambda x: "".join(
[x[0]
for x in py(x, style=py_style.FIRST_LETTER)]).upper(),
"person_name")
],
]))
sk = transform.MapSelectKeys({
"matched_id": PersonInfo.person_id.name,
"person_name": PersonInfo.person_name.name,
PersonInfo.person_name_py.name: None,
})
s = base.Stream(inp, transform=(vm, sk))
return s
def stream_y_person_info(cls):
"""
清洗 y_person_info;
"""
sql = "SELECT person_id, person_name, gender, background, education," \
"graduate_school, investment_years FROM crawl_private.y_person_info"
inp = MysqlInput(ENGINE_RD, sql)
vm = transform.ValueMap({
"person_name_py": (lambda x: "".join(
[x[0] for x in py(x, style=py_style.FIRST_LETTER)]).upper(),
"person_name"),
})
sk = transform.MapSelectKeys({
"person_id": "person_id",
'person_name': 'person_name',
"person_name_py": "person_name_py",
"gender": "gender",
"background": "background",
"graduate_school": "graduate_school",
"investment_years": "investment_years"
})
s = Stream(inp, transform=[vm, sk])
return s
def stream(cls):
sql = "SELECT idm.person_id FROM( \
SELECT person_id FROM base.person_info) as idm \
JOIN \
base.org_person_mapping as op \
on op.person_id = idm.person_id \
WHERE op.duty_detail IN ( \
'基金经理', \
'投资总监', \
'投资经理', \
'投研总监', \
'风控总监', \
'投资部经理', \
'投资决策委员会主席', \
'总经理', \
'投资部主管' \
)GROUP BY idm.person_id"
inp = MysqlInput(ENGINE_RD, sql)
vm = transform.ValueMap({
"is_core_member": "是"
})
sk = transform.MapSelectKeys({
"person_id": "person_id",
'is_core_member': 'is_core_member'
})
s = Stream(inp, transform=[vm, sk])
return s
def stream_x_org_info():
sql = "SELECT xoi.org_id, xoi.final_report_time, real_capital, reg_capital, employee_scale FROM crawl_private.x_org_info xoi " \
"JOIN (SELECT org_id, MAX(version) latest_ver FROM crawl_private.x_org_info WHERE is_used = 1 GROUP BY org_id) tb " \
"ON xoi.org_id = tb.org_id AND xoi.version = tb.latest_ver"
inp = MysqlInput(ENGINE, sql)
vm = transform.ValueMap(
{
"employee_scale": lambda x: int(x.replace(",", "")),
OrgTimeseries.data_time.name: dt.date.today()
}
)
sk = transform.MapSelectKeys(
{
"org_id": OrgTimeseries.org_id.name,
"final_report_time": OrgTimeseries.statistic_date.name,
"real_capital": OrgTimeseries.real_capital.name,
"reg_capital": OrgTimeseries.reg_capital.name,
"employee_scale": OrgTimeseries.employee_scale.name,
OrgTimeseries.data_time.name: None
}
)
s = base.Stream(inp, transform=(vm, sk))
return s
def stream18_60409(cls):
tmp_sql = "SELECT fi.fund_id, fi.fund_name " \
"FROM fund_type_source fts " \
"JOIN fund_info fi ON fts.fund_id = fi.fund_id WHERE fi.fund_id NOT IN (" \
"SELECT DISTINCT fund_id FROM base.fund_type_mapping_import WHERE typestandard_code = 604) " \
"AND fi.fund_id IN (" \
"SELECT DISTINCT fund_id FROM fund_type_source WHERE " \
"type_code IN (30410, 30411)) " \
"AND fi.fund_id IN (" \
"SELECT DISTINCT fund_id FROM fund_type_source WHERE " \
"type_code = 40407)"
inp = MysqlInput(ENGINE, tmp_sql)
vm = transform.ValueMap({
FundTypeMappingImport.typestandard_code.name: 604,
FundTypeMappingImport.typestandard_name.name: "按发行主体分类",
FundTypeMappingImport.type_code.name: 60409,
FundTypeMappingImport.type_name.name: "单账户",
FundTypeMappingImport.classified_by.name: CLASSIFIED_BY
})
sk = transform.MapSelectKeys(cls.FIXED_FIELDS)
s = base.Stream(inp, [vm, sk])
return s
def stream_020005(cls):
"""
清洗 d_org_info;
"""
sql = " \
SELECT idm.matched_id, dfi.open_date, dfi.locked_time_limit, dfi.min_purchase_amount, \
dfi.min_append_amount,dfi.fee_subscription,dfi.fee_redeem, dfi.fee_manage,dfi.duration, \
dfi.fee_pay, dfi.source_id \
FROM \
(SELECT matched_id, source_id FROM base.id_match where id_type=1 and is_used=1 AND source='020001' GROUP BY matched_id) as idm \
JOIN \
(SELECT MAX(version) maxversion, fund_id FROM crawl_private.d_fund_info WHERE source_id = '020001' GROUP BY fund_id) as ma \
ON idm.source_id = ma.fund_id \
JOIN crawl_private.d_fund_info as dfi \
on dfi.version = ma.maxversion and dfi.fund_id = ma.fund_id"
inp = MysqlInput(ENGINE_RD, sql)
vm = transform.ValueMap({
"open_date":
lambda x: cls.sub_wrong_to_none(x) if type(x) is str else x,
"locked_time_limit":
lambda x: cls.sub_wrong_to_none(x) if type(x) is str else x
})
sk = transform.MapSelectKeys({
"matched_id": "fund_id",
'locked_time_limit': 'locked_time_limit',
'open_date': 'open_date',
'source_id': 'source_id'
})
s = Stream(inp, transform=[vm, sk])
return s
def conflu_is_reg_now(cls):
# is_reg_now
sql = "SELECT xoi.org_id as org_id_, oi.org_id " \
"FROM crawl_private.x_org_info xoi " \
"JOIN (SELECT DISTINCT org_id, version FROM crawl_private.x_org_info WHERE version >= {ver} ) tmp " \
"ON xoi.org_id = tmp.org_id AND xoi.version = tmp.version " \
"JOIN (SELECT matched_id, source_id FROM base.id_match WHERE id_type = 2 AND source = '010001' AND is_used = 1) im " \
"ON xoi.org_id = im.source_id " \
"RIGHT JOIN (SELECT org_id FROM {tb_test} WHERE org_category = '私募基金管理公司') oi " \
"ON im.matched_id = oi.org_id ".format(tb_test=TEST_TABLE, ver=(dt.datetime.now() - dt.timedelta(8)).strftime("%Y%m%d%H"))
inp = MysqlInput(ENGINE_RD, sql)
vm = transform.ValueMap({
OrgInfo.is_reg_now.name: (lambda x: "否" if x is None else "是", "org_id_")
})
sk = transform.MapSelectKeys({
"org_id": OrgInfo.org_id.name,
OrgInfo.is_reg_now.name: None
})
s = Stream(inp, [vm, sk])
return Confluence(s)
def stream_020003(cls, fund_ids):
sql = "SELECT im.matched_id, dfp.statistic_date, dfp.subject_id, fpb.data_source, dfp.quantity " \
"FROM base_public.id_match im " \
"JOIN crawl_public.d_fund_position dfp " \
"ON im.source_id = dfp.fund_id AND im.data_source = dfp.data_source " \
"JOIN base_test.fund_position_bond_test_20180515 fpb " \
"ON im.matched_id = fpb.fund_id AND fpb.statistic_date = dfp.statistic_date AND fpb.subject_id = dfp.subject_id " \
"WHERE type = '债券' AND im.matched_id IN {fids} AND im.id_type = 1 AND im.is_used = 1 " \
"AND im.data_source = '020003'".format(fids=sf.SQL.values4sql(fund_ids))
inp = MysqlInput(cls.engine, sql)
vm = transform.ValueMap({
"quantity": lambda x: cls._clean_amount(x),
})
sk = transform.MapSelectKeys({
"matched_id": "fund_id",
"statistic_date": None,
"subject_id": None,
"quantity": None
})
dn = transform.Dropna(subset=["quantity"])
return base.Stream(inp, transform=[vm, sk, dn])
def conflu_master_strategy(cls):
# master_strategy
# 外层以org_info表左连接查询, 以确保所有主键都会被更新到, 以处理源表数据变动的情况;
sql = "SELECT t1.org_id, t2.stype_name FROM {tb_test} t1 " \
"LEFT JOIN (SELECT oi.org_id, ftm.stype_name " \
"FROM {tb_test} oi " \
"JOIN base.fund_org_mapping fom ON oi.org_id = fom.org_id " \
"JOIN (SELECT fund_id, stype_code, stype_name FROM fund_type_mapping " \
"WHERE typestandard_code = 601 AND stype_code <> 6010901 AND flag = 1) ftm ON fom.fund_id = ftm.fund_id " \
"WHERE fom.org_type_code = 1 " \
"GROUP BY oi.org_id, ftm.stype_code " \
"ORDER BY org_id ASC, COUNT(fom.fund_id) DESC) t2 ON t1.org_id = t2.org_id ".format(tb_test=TEST_TABLE)
inp = MysqlInput(ENGINE_RD, sql)
dd = transform.DropDuplicate(subset=["org_id"])
sk = transform.MapSelectKeys({
"org_id": OrgInfo.org_id.name,
"stype_name": OrgInfo.master_strategy.name
})
s = Stream(inp, [dd, sk])
return Confluence(s)
def stream_x_org_info():
sql = "SELECT xoi.org_id, xoi.final_report_time, fund_num, fund_scale FROM crawl_private.x_org_info xoi " \
"JOIN (SELECT org_id, MAX(version) latest_ver FROM crawl_private.x_org_info WHERE is_used = 1 GROUP BY org_id) tb " \
"ON xoi.org_id = tb.org_id AND xoi.version = tb.latest_ver"
inp = MysqlInput(ENGINE, sql)
vm = transform.ValueMap({OrgAssetScale.data_time.name: dt.date.today()})
sk = transform.MapSelectKeys({
"org_id":
OrgAssetScale.org_id.name,
"final_report_time":
OrgAssetScale.statistic_date.name,
"fund_num":
OrgAssetScale.funds_num.name,
"fund_scale":
OrgAssetScale.asset_scale.name,
OrgAssetScale.data_time.name:
None
})
dn = transform.Dropna(subset=[
OrgAssetScale.asset_scale.name, OrgAssetScale.funds_num.name,
OrgAssetScale.statistic_date.name
],
how="all")
s = base.Stream(inp, transform=(vm, sk, dn))
return s
def stream_020003(cls):
"""
清洗 d_fund_position（020003）;
"""
sql = " \
SELECT fps.fund_id,fps.statistic_date,fps.subject_id,dfp.quantity, fps.data_source \
FROM base_public.fund_position_stock AS fps \
JOIN crawl_public.d_fund_position AS dfp \
ON fps.fund_id = dfp.fund_id AND fps.statistic_date = dfp.statistic_date \
AND fps.subject_id = dfp.subject_id \
WHERE dfp.data_source = '020001' AND dfp.quantity is not NULL"
inp = MysqlInput(ENGINE_RD, sql)
vm = transform.ValueMap({
"quantity": lambda x: cls.sub_wrong_to_none(x)
})
vm2 = transform.ValueMap({
"quantity": lambda x: float(x)
})
sk = transform.MapSelectKeys({
"fund_id": "fund_id",
"data_source": "data_source",
"statistic_date": "statistic_date",
"subject_id": "subject_id",
"quantity": "quantity"
})
s = Stream(inp, transform=[vm, vm2, sk])
return s
def stream_02000x(cls):
sql = " \
SELECT idm.matched_id, df.data_source, df.statistic_date, \
df.nav, df.added_nav, fi.fund_name \
FROM (SELECT matched_id,source_id,data_source \
FROM base_public.id_match WHERE id_type = 1 and is_used = 1) AS idm \
JOIN \
crawl_public.d_fund_nv AS df \
on idm.source_id = df.fund_id \
AND idm.data_source = df.data_source \
JOIN base_public.fund_info as fi \
ON fi.fund_id = df.fund_id \
WHERE df.update_time BETWEEN '{start}' \
AND '{end}' and is_used = 1".format(start=cls.start, end=cls.end)
inp = MysqlInput(ENGINE_RD, sql)
sk = transform.MapSelectKeys({
"matched_id": "fund_id",
'data_source': 'data_source',
'statistic_date': 'statistic_date',
'nav': 'nav',
'added_nav': 'added_nav',
"fund_name": "fund_name"
})
s = Stream(inp, transform=[sk])
return s
def stream_04xxxx_type2(cls):
"""
清洗id_match, 04xxx源基金管理人
"""
sql = "SELECT idm.matched_id,oi.org_id,oi.org_full_name " \
"FROM (SELECT DISTINCT matched_id,source FROM base.id_match " \
"WHERE id_type = 1 AND is_used = 1 AND source LIKE '040%%' " \
"AND matched_id NOT IN (SELECT fund_id FROM base.fund_org_mapping WHERE org_type_code=2)) idm " \
"JOIN data_test.source_info_org sig ON idm.source = sig.source_id " \
"JOIN base.org_info oi ON sig.org_id = oi.org_id"
inp = MysqlInput(ENGINE_RD, sql)
vm = transform.ValueMap({
"org_type": "基金管理人",
"org_type_code": 2
})
sk = transform.MapSelectKeys({
"matched_id": "fund_id",
'org_full_name': 'org_name',
"org_type": "org_type",
"org_type_code": "org_type_code",
"org_id": "org_id"
})
s = Stream(inp, transform=[vm, sk])
return s
def stream_000001(cls):
"""
清洗stock_info_010001 CSRC分类;
"""
sql = "SELECT stock_id,type_csrc FROM crawl_finance.stock_info_010001"
inp = MysqlInput(ENGINE_RD, sql)
vm = transform.ValueMap({
"type_csrc":
lambda x: re.sub("\s", "",
x.split(",")[1]),
"category_code": (lambda x: cls.TYPE_CODE.get(x), "type_csrc"),
"category_name": (lambda x: cls.TYPE_NAME.get(x), "type_csrc"),
"type_code": (lambda x: cls.STYPE_CODE.get(x), "type_csrc"),
"stock_id":
lambda x: str(cls.add_stock_suffix(x)) + ".SH"
})
sk = transform.MapSelectKeys({
"stock_id": "stock_id",
"category_name": "category_name",
"category_code": "category_code",
"type_code": "type_code",
"type_csrc": "type_name"
})
dn = transform.Dropna(subset=None, axis=0, how='any')
s = Stream(inp, transform=[vm, sk, dn])
return s
