def __init__(self, name, dataset_url):
"""
Parameters
----------
name: string
Name of the column. No check is actually done to see if the column
exists.
dataset_id:
The base url where the dataset is located.
e.g. localhost:8888/v1/datasets/<dataset_name>
"""
logging.debug("Instanciating Column with {}".format(name))
self.name = "\"{}\"".format(name)
self.execution_name = "\"{}\"".format(name)
self.dataset_url = dataset_url
self.query = Query(dataset_url)
self.query.addSELECT(self.name)
class Time(object):
"""docstring for Time"""
def __init__(self, dataset_url):
super(Time, self).__init__()
self.dataset_url = dataset_url
self.query = Query(dataset_url)
def __getitem__(self, value):
print(value)
def copy(self):
copy_time = Time(self.dataset_url)
copy_time = self.query.copy()
return copy_time
def __init__(self, dataset_url):
super(Time, self).__init__()
self.dataset_url = dataset_url
self.query = Query(dataset_url)
def __init__(self, dataset_url):
self.dataset_url = dataset_url
self.query = Query(dataset_url)
self._time = Time(dataset_url)
self._index = Index(self)
class BatFrame(object):
def __init__(self, dataset_url):
self.dataset_url = dataset_url
self.query = Query(dataset_url)
self._time = Time(dataset_url)
self._index = Index(self)
def __getitem__(self, val):
if isinstance(val, str):
col = Column(val, self.dataset_url)
col.query.mergeQuery(self.query)
return col
elif isinstance(val, Query):
bf = self.copy()
# bf.query.addSELECT('*')
bf.query.mergeQuery(val)
return bf
elif isinstance(val, slice):
start = val.start
stop = val.stop
# step = val.step
bf = self.copy()
# bf.query.addSELECT('*')
if start is not None:
bf.query.setOFFSET(start)
if stop is not None:
bf.query.setLIMIT(stop)
return bf
elif isinstance(val, list):
bf = self.copy()
for value in val:
bf.query.addSELECT("\"{}\"".format(value))
return bf
elif isinstance(val, Column):
bf = self.copy()
bf.query.addWHERE("({})".format(val.execution_name))
return bf
@property
def columns(self):
"""Returns a numpy array of the columns name"""
return requests.get(self.dataset_url + '/columns').json()
@property
def rows(self):
"""Returns a numpy array of the rows name"""
bf = self.copy()
result = bf.query.executeQuery(format="soa")
return result["_rowName"]
@property
def time(self):
copy_time = self._time.copy()
return copy_time.query.mergeQuery(self.Query)
@property
def ix(self):
copy_index = self._index.copy()
return copy_index
def copy(self):
bf = BatFrame(self.dataset_url)
bf.query = self.query.copy()
return bf
def toPandas(self):
result = self.query.executeQuery(format="aos")
if len(result) == 0:
return pd.DataFrame()
return pd.DataFrame.from_records(result, index="_rowName")
def head(self, num_rows=5):
bf = self.copy()
bf.query.setLIMIT(num_rows)
return bf
def query(self, query):
raise NotImplementedError()
def sort(self, value, ascending=True):
bf = self.copy()
if not isinstance(value, list):
value = [value]
if not isinstance(ascending, list):
ascending = [ascending]*len(value)
if len(value) != len(ascending):
raise RuntimeError("len(value) != len(ascending)")
for by, asc in zip(value, ascending):
if asc:
sort = "ASC"
else:
sort = "DESC"
bf.query.addORDERBY("\"{}\" {}".format(by, sort))
return bf
@property
def shape(self):
"""
Returns (rowCount, valueCount)
"""
bf = self.copy()
content = requests.get(bf.dataset_url).json()
rowCount = content['status']['rowCount']
valueCount = content['status']['valueCount']
return (rowCount, valueCount)
def __repr__(self):
bf = self.copy()
bf.query.setLIMIT(40)
print(bf.toPandas())
response = requests.get(bf.dataset_url).json()
try:
rowCount = response['status']['rowCount']
except:
rowCount = None
if rowCount is not None and rowCount > 40:
print("{} rows".format(rowCount))
return ""
class Column(object):
def __init__(self, name, dataset_url):
"""
Parameters
----------
name: string
Name of the column. No check is actually done to see if the column
exists.
dataset_id:
The base url where the dataset is located.
e.g. localhost:8888/v1/datasets/<dataset_name>
"""
logging.debug("Instanciating Column with {}".format(name))
self.name = "\"{}\"".format(name)
self.execution_name = "\"{}\"".format(name)
self.dataset_url = dataset_url
self.query = Query(dataset_url)
self.query.addSELECT(self.name)
@property
def values(self):
result = self.query.executeQuery(format="soa")
if len(result) > 2:
raise RuntimeError("Only one column should be returned")
colName = [x for x in result.keys() if x != "_rowName"][0]
return np.array(result[colName])
def __getitem__(self, val):
if isinstance(val, slice):
start = val.start
stop = val.stop
# step = val.step
col = self.copy()
if start is not None:
col.query.setOFFSET(start)
if stop is not None:
col.query.setLIMIT(stop)
return col
elif isinstance(val, Query):
col = self.copy()
col.query.mergeQuery(val)
return col
elif isinstance(val, str):
col = self.copy()
col.query.addWHERE("(rowName()='{}')".format(val))
return col
####################
# Rich comparison #
####################
def _comparison(self, value, operator):
"""
Parameters
----------
value: Column object or base type
The value against which to compare the column. It can either be
another column or a base type value (e.g. int)
Returns
-------
self.query
Notes
-----
Returning self.query will allow the next object to use this column
ops and concatenate something else
"""
if isinstance(value, Column):
self.query.addWHERE("(({}){}({}))".format(
self.execution_name,
operator,
value.execution_name))
elif isinstance(value, str):
self.query.addWHERE("(({}){}\'{}\')".format(
self.execution_name,
operator,
value))
else:
self.query.addWHERE("(({}){}({}))".format(
self.execution_name,
operator,
value))
copy = self.copy()
copy.query.removeSELECT("{}".format(copy.execution_name))
return copy.query
def __eq__(self, value):
return self._comparison(value, '=')
def __ne__(self, value):
return self._comparison(value, '!=')
def __gt__(self, value):
return self._comparison(value, '>')
def __ge__(self, value):
return self._comparison(value, '>=')
def __lt__(self, value):
return self._comparison(value, '<')
def __le__(self, value):
return self._comparison(value, '<=')
##################################
# Binary arithmetic operations #
##################################
def _binary_arithemtic(self, left, binary, right):
"""
Parameters
----------
operand: Column object, integer or float
Value on which to apply operator to this column
binary: char
binary arithmetic operator (-, +, *, /, ^, %)
Returns
-------
self
Notes
-----
Returning self will allow the next object to use this column ops and
concatenate something else
"""
if isinstance(right, (int, float)):
right = right
elif isinstance(right, Column):
right = right.execution_name
else:
raise AttributeError(
"{} can only be used ".format(binary)
+ "with integer, float or column")
if isinstance(left, (int, float)):
left = left
elif isinstance(left, Column):
left = left.execution_name
else:
raise AttributeError(
"{} can only be used ".format(binary)
+ "with integer, float or column")
copy = self.copy()
copy.query.removeSELECT("{}".format(copy.execution_name))
if binary == '^': # POWER needs a different treatment
copy.execution_name = "pow({},{})".format(left, right)
else:
copy.execution_name = "{}{}{}".format(left, binary, right)
copy.query.addSELECT(copy.execution_name)
return copy
def __mul__(self, value):
return self._binary_arithemtic(self, '*', value)
def __rmul__(self, value):
return self._binary_arithemtic(value, '*', self)
def __div__(self, value):
if isinstance(value, (int, float)) and value == 0:
raise ValueError(
"Cannot divide by zero. "
"Do you really want to explode the planet?")
return self._binary_arithemtic(self, '/', value)
def __rdiv__(self, value):
return self._binary_arithemtic(value, '/', self)
def __truediv__(self, value):
if isinstance(value, (int, float)) and value == 0:
raise ValueError(
"Cannot divide by zero. "
"Do you really want to explode the planet?")
return self._binary_arithemtic(self, '/', value)
def __rtruediv__(self, value):
return self._binary_arithemtic(value, '/', self)
def __sub__(self, value):
return self._binary_arithemtic(self, '-', value)
def __rsub__(self, value):
return self._binary_arithemtic(value, '-', self)
def __add__(self, value):
return self._binary_arithemtic(self, '+', value)
def __radd__(self, value):
return self._binary_arithemtic(value, '+', self)
def __pow__(self, value):
return self._binary_arithemtic(self, '^', value)
def __rpow__(self, value):
return self._binary_arithemtic(value, '^', self)
def __mod__(self, value):
return self._binary_arithemtic(self, '%', value)
def __rmod__(self, value):
return self._binary_arithemtic(value, '%', self)
def __or__(self, value):
col = self.copy()
left = self.execution_name
right = value
col.query.removeSELECT(left)
if isinstance(right, Column):
right = value.execution_name
col.query.removeSELECT(right)
elif isinstance(right, Query):
right = right.WHERE
col.query.addWHERE('(({}) OR ({}))'.format(left, right))
return col.query
def __and__(self, value):
col = self.copy()
left = self.execution_name
right = value
col.query.removeSELECT(left)
if isinstance(right, Column):
right = value.execution_name
col.query.removeSELECT(right)
elif isinstance(right, Query):
right = right.WHERE
col.query.addWHERE('(({}) AND ({}))'.format(left, right))
return col.query
def __rand__(self, value):
col = self.copy()
left = self.execution_name
right = value
col.query.removeSELECT(left)
if isinstance(right, Column):
right = value.execution_name
col.query.removeSELECT(right)
elif isinstance(right, Query):
right = right.WHERE
col.query.addWHERE('(({}) AND ({}))'.format(right, left))
def __ror__(self, value):
col = self.copy()
left = self.execution_name
right = value
col.query.removeSELECT(left)
if isinstance(right, Column):
right = value.execution_name
col.query.removeSELECT(right)
elif isinstance(right, Query):
right = right.WHERE
col.query.addWHERE('(({}) OR ({}))'.format(right, left))
return col.query
#################################
# Unary arithmetic operations #
#################################
def _unary_arithmetic(self, unary):
"""
Parameters
----------
unary: char
Unary arithmetic operator (-, +) to be applied to this column
Returns
-------
self
Notes
-----
Returning self will allow the next object to use this column ops and
concatenate something else
"""
copy = self.copy()
copy.query.removeSELECT("{}".format(copy.execution_name))
copy.execution_name = "{}({})".format(unary, self.execution_name)
copy.query.addSELECT(copy.execution_name)
return copy
def __neg__(self):
return self._unary_arithmetic('-')
def __pos__(self):
raise NotImplementedError()
def __invert__(self):
copy = self.copy()
copy.execution_name = "NOT {}".format(copy.execution_name)
return copy
def __abs__(self):
raise NotImplementedError()
#############
# Casting #
#############
def __float__(self):
raise NotImplementedError()
def __int__(self):
raise NotImplementedError()
def __long__(self):
raise NotImplementedError()
###########
# Other #
###########
def __iter__(self):
result = self.query.executeQuery(format="soa")
if len(result) > 2:
raise RuntimeError("Only one column should be returned")
colName = [x for x in result.keys() if x != "_rowName"][0]
values = result[colName]
i = 0
while i < len(values):
yield values[i]
i += 1
def max(self):
copy = self.copy()
copy.query.removeSELECT("{}".format(copy.execution_name))
copy.execution_name = "max({})".format(self.execution_name)
copy.query.addSELECT(copy.execution_name)
copy.query.addGROUPBY(1)
result = copy.query.executeQuery(format="table")
return result[1][1]
def min(self):
copy = self.copy()
copy.query.removeSELECT("{}".format(copy.execution_name))
copy.execution_name = "min({})".format(self.execution_name)
copy.query.addSELECT(copy.execution_name)
copy.query.addGROUPBY(1)
result = copy.query.executeQuery(format="table")
return result[1][1]
def copy(self):
name = self.name[1:-1] # Removing the surrounding ''
col = Column(name, self.dataset_url)
col.execution_name = self.execution_name
col.query = self.query.copy()
return col
def count(self):
"""Return number of non-NA/null observations in the Series"""
raise NotImplementedError()
def head(self, n=5):
"""Returns first n rows"""
col = self.copy()
col.query.setLIMIT(n)
return col.toPandas()
def isnull(self):
raise NotImplementedError()
def isin(self, values):
raise NotImplementedError()
def value_counts(self):
raise NotImplementedError()
def unique(self):
if self.name == self.execution_name:
url = self.dataset_url + '/columns/{}/values'.format(
self.name[1:-1])
logging.debug("Getting values at {}".format(url))
return requests.get(url).json()
else:
result = self.query.executeQuery(format="soa")
if len(result) > 2:
raise RuntimeError("Only one column should be returned")
colName = [x for x in result.keys() if x != "_rowName"][0]
return set(result[colName])
def sort(self, ascending=True):
col = self.copy()
if ascending:
sort = "ASC"
else:
sort = "DESC"
col.query.addORDERBY("{} {}".format(col.execution_name, sort))
return col
def toPandas(self):
result = self.query.executeQuery(format="soa")
if len(result) > 2:
raise RuntimeError("Only one column should be returned")
colName = [x for x in result.keys() if x != "_rowName"][0]
values = result[colName]
rowName = result["_rowName"]
if len(values) > 0:
s = pd.Series(values, index=rowName)
else:
s = pd.Series()
return s
def __repr__(self):
col = self.copy()
col.query.setLIMIT(40)
print(col.toPandas())
response = requests.get(col.dataset_url).json()
try:
rowCount = response['status']['rowCount']
except:
rowCount = None
if rowCount is not None and rowCount > 40:
print("{} rows".format(rowCount))
return ""
