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how can I make a dictionary with an exact key order in python?
2019 Community Moderator ElectionHow to merge two dictionaries in a single expression?How do I sort a list of dictionaries by a value of the dictionary?How can I safely create a nested directory in Python?How can I make a time delay in Python?How do I sort a dictionary by value?How to make a chain of function decorators?How to make a flat list out of list of lists?Add new keys to a dictionary?Check if a given key already exists in a dictionaryHow to remove a key from a Python dictionary?
I want to make a dictionary with a specific set of keys and a specific set of values. These are the keys I want to use:
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
And these are the values for each key:
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
If I use a set or try to make a dictionary using this:
d = dict(zip(k, v))
Or even this (what I really intend to do):
d = dict(zip(map(lambda x: "ga_%s" % x, k), v))
I get this:
'ga_itemRevenue': 0.0, 'ga_itemQuantity': 1, 'ga_deviceCategory': 'desktop', 'ga_date': datetime.date(2019, 3, 5), 'ga_channelGrouping': 'Tráfico de Búsqueda de Pago - Venta', 'ga_productSku': 60104621, 'ga_productName': '(not set)', 'ga_productCategoryHierarchy': 'sale/apartment/alicante/bajo-vinalopo/elx', 'ga_transactionId': 1551740677701
I know key order is not relevant in python dictionaries (at least, the ones made with dict()) but I need the keys and their matching values to form the dictionary in the exact same order, which is not alphabetical. Just... the same key order.
I've tried making an ordered dictionary with collections.OrderedDict() and the order is the one I want except for the fact it gives me a list of tuples. I've also tried to kind of 'convert' the ordered dictionary into a regular one with this:
d = json.loads(json.dumps(x))
But it gives me an error because the datetime object cannot be serialized (or so it says the error message) and I need it like that (as a datetime object) as this is going to be written to a database table with the cx_Oracle package.
I've also read about frozenset() but seems like I need a previously existing set to 'freeze' it and once I create a set is exactly like trying to make a dictionary. keys are sprayed over the set and I need them in the same order they're declared in the keys array.
How can I achieve this?
#EDIT 1. I forgot to say this is done in Python 2.7.x
#EDIT 2. Here is the code fragment I'm having problems with:
reports = response.get("reports", [])
if len(reports) > 0:
for report in reports:
rows = report.get("data", ).get("rows", [])
if len(rows) > 0:
k = ga_dimensions + ga_metrics
o = []
for row in rows:
o.append(map(lambda x, y: cast_field_type(x, y), row.get("dimensions", []) + row.get("metrics", [])[0]["values"], k))
if len(o) > 0:
# insert all data rows into the table
for v in o:
for i in range(0, len(v)):
if k[i] == "date" and is_date(v[i]):
v[i] = date(*map(int, v[i].split("-")))
elif isinstance(v[i], unicode):
v[i] = v[i].encode("utf-8")
v = dict(zip(map(lambda x: "ga_%s" % x, k), v))
cr.execute(q, v)
# commit all changes
db.commit()
This script fetches data from Google Analytics (using the v4 API), infer the appropiate data types (for database storage with Oracle) from the first row of data, traverse the data rows so specific fields (dates and Unicode strings, basically) get appropiately casted/converted/encoded before being sent to the database and, when done that, commit the changes so the data gets written for real.
I try to do this because the script gives me this error when trying to supply the dictionary per se:
cx_Oracle.DatabaseError: ORA-00932: inconsistent datatypes: expected DATE got NUMBER
And this is because the data is being supplied with a key order that is different from the SQL INSERT query being specified.
python python-2.7 dictionary key unordered
asked Mar 6 at 13:59
Julio María Meca HansenJulio María Meca Hansen
803929
add a comment |
I want to make a dictionary with a specific set of keys and a specific set of values. These are the keys I want to use:
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
And these are the values for each key:
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
If I use a set or try to make a dictionary using this:
d = dict(zip(k, v))
Or even this (what I really intend to do):
d = dict(zip(map(lambda x: "ga_%s" % x, k), v))
I get this:
'ga_itemRevenue': 0.0, 'ga_itemQuantity': 1, 'ga_deviceCategory': 'desktop', 'ga_date': datetime.date(2019, 3, 5), 'ga_channelGrouping': 'Tráfico de Búsqueda de Pago - Venta', 'ga_productSku': 60104621, 'ga_productName': '(not set)', 'ga_productCategoryHierarchy': 'sale/apartment/alicante/bajo-vinalopo/elx', 'ga_transactionId': 1551740677701
I know key order is not relevant in python dictionaries (at least, the ones made with dict()) but I need the keys and their matching values to form the dictionary in the exact same order, which is not alphabetical. Just... the same key order.
I've tried making an ordered dictionary with collections.OrderedDict() and the order is the one I want except for the fact it gives me a list of tuples. I've also tried to kind of 'convert' the ordered dictionary into a regular one with this:
d = json.loads(json.dumps(x))
But it gives me an error because the datetime object cannot be serialized (or so it says the error message) and I need it like that (as a datetime object) as this is going to be written to a database table with the cx_Oracle package.
I've also read about frozenset() but seems like I need a previously existing set to 'freeze' it and once I create a set is exactly like trying to make a dictionary. keys are sprayed over the set and I need them in the same order they're declared in the keys array.
How can I achieve this?
#EDIT 1. I forgot to say this is done in Python 2.7.x
#EDIT 2. Here is the code fragment I'm having problems with:
reports = response.get("reports", [])
if len(reports) > 0:
for report in reports:
rows = report.get("data", ).get("rows", [])
if len(rows) > 0:
k = ga_dimensions + ga_metrics
o = []
for row in rows:
o.append(map(lambda x, y: cast_field_type(x, y), row.get("dimensions", []) + row.get("metrics", [])[0]["values"], k))
if len(o) > 0:
# insert all data rows into the table
for v in o:
for i in range(0, len(v)):
if k[i] == "date" and is_date(v[i]):
v[i] = date(*map(int, v[i].split("-")))
elif isinstance(v[i], unicode):
v[i] = v[i].encode("utf-8")
v = dict(zip(map(lambda x: "ga_%s" % x, k), v))
cr.execute(q, v)
# commit all changes
db.commit()
This script fetches data from Google Analytics (using the v4 API), infer the appropiate data types (for database storage with Oracle) from the first row of data, traverse the data rows so specific fields (dates and Unicode strings, basically) get appropiately casted/converted/encoded before being sent to the database and, when done that, commit the changes so the data gets written for real.
I try to do this because the script gives me this error when trying to supply the dictionary per se:
cx_Oracle.DatabaseError: ORA-00932: inconsistent datatypes: expected DATE got NUMBER
And this is because the data is being supplied with a key order that is different from the SQL INSERT query being specified.
python python-2.7 dictionary key unordered
asked Mar 6 at 13:59
Julio María Meca HansenJulio María Meca Hansen
803929
1
Prior to Python 3.7, adictwould not preserve any information about the order in which key/value pairs were added. Usecollections.OrderedDictinstead. The issue of preserving adatetimeobject across JSON encoding/decoding is an entirely separate problem, though.
– chepner
Mar 6 at 14:04
3
It's only the representation of anOrderedDictthat looks like a list of tuples.
– chepner
Mar 6 at 14:04
OrderedDict behaves exactly like a dict , what are you trying to do with it that makes it not behave like one?
– AntiMatterDynamite
Mar 6 at 14:13
add a comment |
I want to make a dictionary with a specific set of keys and a specific set of values. These are the keys I want to use:
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
And these are the values for each key:
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
If I use a set or try to make a dictionary using this:
d = dict(zip(k, v))
Or even this (what I really intend to do):
d = dict(zip(map(lambda x: "ga_%s" % x, k), v))
I get this:
'ga_itemRevenue': 0.0, 'ga_itemQuantity': 1, 'ga_deviceCategory': 'desktop', 'ga_date': datetime.date(2019, 3, 5), 'ga_channelGrouping': 'Tráfico de Búsqueda de Pago - Venta', 'ga_productSku': 60104621, 'ga_productName': '(not set)', 'ga_productCategoryHierarchy': 'sale/apartment/alicante/bajo-vinalopo/elx', 'ga_transactionId': 1551740677701
I know key order is not relevant in python dictionaries (at least, the ones made with dict()) but I need the keys and their matching values to form the dictionary in the exact same order, which is not alphabetical. Just... the same key order.
I've tried making an ordered dictionary with collections.OrderedDict() and the order is the one I want except for the fact it gives me a list of tuples. I've also tried to kind of 'convert' the ordered dictionary into a regular one with this:
d = json.loads(json.dumps(x))
But it gives me an error because the datetime object cannot be serialized (or so it says the error message) and I need it like that (as a datetime object) as this is going to be written to a database table with the cx_Oracle package.
I've also read about frozenset() but seems like I need a previously existing set to 'freeze' it and once I create a set is exactly like trying to make a dictionary. keys are sprayed over the set and I need them in the same order they're declared in the keys array.
How can I achieve this?
#EDIT 1. I forgot to say this is done in Python 2.7.x
#EDIT 2. Here is the code fragment I'm having problems with:
reports = response.get("reports", [])
if len(reports) > 0:
for report in reports:
rows = report.get("data", ).get("rows", [])
if len(rows) > 0:
k = ga_dimensions + ga_metrics
o = []
for row in rows:
o.append(map(lambda x, y: cast_field_type(x, y), row.get("dimensions", []) + row.get("metrics", [])[0]["values"], k))
if len(o) > 0:
# insert all data rows into the table
for v in o:
for i in range(0, len(v)):
if k[i] == "date" and is_date(v[i]):
v[i] = date(*map(int, v[i].split("-")))
elif isinstance(v[i], unicode):
v[i] = v[i].encode("utf-8")
v = dict(zip(map(lambda x: "ga_%s" % x, k), v))
cr.execute(q, v)
# commit all changes
db.commit()
This script fetches data from Google Analytics (using the v4 API), infer the appropiate data types (for database storage with Oracle) from the first row of data, traverse the data rows so specific fields (dates and Unicode strings, basically) get appropiately casted/converted/encoded before being sent to the database and, when done that, commit the changes so the data gets written for real.
I try to do this because the script gives me this error when trying to supply the dictionary per se:
cx_Oracle.DatabaseError: ORA-00932: inconsistent datatypes: expected DATE got NUMBER
And this is because the data is being supplied with a key order that is different from the SQL INSERT query being specified.
python python-2.7 dictionary key unordered
asked Mar 6 at 13:59
Julio María Meca HansenJulio María Meca Hansen
803929
I want to make a dictionary with a specific set of keys and a specific set of values. These are the keys I want to use:
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
And these are the values for each key:
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
If I use a set or try to make a dictionary using this:
d = dict(zip(k, v))
Or even this (what I really intend to do):
d = dict(zip(map(lambda x: "ga_%s" % x, k), v))
I get this:
'ga_itemRevenue': 0.0, 'ga_itemQuantity': 1, 'ga_deviceCategory': 'desktop', 'ga_date': datetime.date(2019, 3, 5), 'ga_channelGrouping': 'Tráfico de Búsqueda de Pago - Venta', 'ga_productSku': 60104621, 'ga_productName': '(not set)', 'ga_productCategoryHierarchy': 'sale/apartment/alicante/bajo-vinalopo/elx', 'ga_transactionId': 1551740677701
I know key order is not relevant in python dictionaries (at least, the ones made with dict()) but I need the keys and their matching values to form the dictionary in the exact same order, which is not alphabetical. Just... the same key order.
I've tried making an ordered dictionary with collections.OrderedDict() and the order is the one I want except for the fact it gives me a list of tuples. I've also tried to kind of 'convert' the ordered dictionary into a regular one with this:
d = json.loads(json.dumps(x))
But it gives me an error because the datetime object cannot be serialized (or so it says the error message) and I need it like that (as a datetime object) as this is going to be written to a database table with the cx_Oracle package.
I've also read about frozenset() but seems like I need a previously existing set to 'freeze' it and once I create a set is exactly like trying to make a dictionary. keys are sprayed over the set and I need them in the same order they're declared in the keys array.
How can I achieve this?
#EDIT 1. I forgot to say this is done in Python 2.7.x
#EDIT 2. Here is the code fragment I'm having problems with:
reports = response.get("reports", [])
if len(reports) > 0:
for report in reports:
rows = report.get("data", ).get("rows", [])
if len(rows) > 0:
k = ga_dimensions + ga_metrics
o = []
for row in rows:
o.append(map(lambda x, y: cast_field_type(x, y), row.get("dimensions", []) + row.get("metrics", [])[0]["values"], k))
if len(o) > 0:
# insert all data rows into the table
for v in o:
for i in range(0, len(v)):
if k[i] == "date" and is_date(v[i]):
v[i] = date(*map(int, v[i].split("-")))
elif isinstance(v[i], unicode):
v[i] = v[i].encode("utf-8")
v = dict(zip(map(lambda x: "ga_%s" % x, k), v))
cr.execute(q, v)
# commit all changes
db.commit()
This script fetches data from Google Analytics (using the v4 API), infer the appropiate data types (for database storage with Oracle) from the first row of data, traverse the data rows so specific fields (dates and Unicode strings, basically) get appropiately casted/converted/encoded before being sent to the database and, when done that, commit the changes so the data gets written for real.
I try to do this because the script gives me this error when trying to supply the dictionary per se:
cx_Oracle.DatabaseError: ORA-00932: inconsistent datatypes: expected DATE got NUMBER
And this is because the data is being supplied with a key order that is different from the SQL INSERT query being specified.
python python-2.7 dictionary key unordered
python python-2.7 dictionary key unordered
asked Mar 6 at 13:59
Julio María Meca HansenJulio María Meca Hansen
803929
asked Mar 6 at 13:59
Julio María Meca HansenJulio María Meca Hansen
803929
edited Mar 6 at 14:41
Julio María Meca Hansen
asked Mar 6 at 13:59
Julio María Meca HansenJulio María Meca Hansen
803929
asked Mar 6 at 13:59
Julio María Meca HansenJulio María Meca Hansen
803929
asked Mar 6 at 13:59
Julio María Meca HansenJulio María Meca Hansen
803929
803929
1
Prior to Python 3.7, adictwould not preserve any information about the order in which key/value pairs were added. Usecollections.OrderedDictinstead. The issue of preserving adatetimeobject across JSON encoding/decoding is an entirely separate problem, though.
– chepner
Mar 6 at 14:04
3
It's only the representation of anOrderedDictthat looks like a list of tuples.
– chepner
Mar 6 at 14:04
OrderedDict behaves exactly like a dict , what are you trying to do with it that makes it not behave like one?
– AntiMatterDynamite
Mar 6 at 14:13
add a comment |
1
Prior to Python 3.7, adictwould not preserve any information about the order in which key/value pairs were added. Usecollections.OrderedDictinstead. The issue of preserving adatetimeobject across JSON encoding/decoding is an entirely separate problem, though.
– chepner
Mar 6 at 14:04
3
It's only the representation of anOrderedDictthat looks like a list of tuples.
– chepner
Mar 6 at 14:04
OrderedDict behaves exactly like a dict , what are you trying to do with it that makes it not behave like one?
– AntiMatterDynamite
Mar 6 at 14:13
1
1
Prior to Python 3.7, a
dict would not preserve any information about the order in which key/value pairs were added. Use collections.OrderedDict instead. The issue of preserving a datetime object across JSON encoding/decoding is an entirely separate problem, though.– chepner
Mar 6 at 14:04
Prior to Python 3.7, a
dict would not preserve any information about the order in which key/value pairs were added. Use collections.OrderedDict instead. The issue of preserving a datetime object across JSON encoding/decoding is an entirely separate problem, though.– chepner
Mar 6 at 14:04
3
3
It's only the representation of an
OrderedDict that looks like a list of tuples.– chepner
Mar 6 at 14:04
It's only the representation of an
OrderedDict that looks like a list of tuples.– chepner
Mar 6 at 14:04
OrderedDict behaves exactly like a dict , what are you trying to do with it that makes it not behave like one?
– AntiMatterDynamite
Mar 6 at 14:13
OrderedDict behaves exactly like a dict , what are you trying to do with it that makes it not behave like one?
– AntiMatterDynamite
Mar 6 at 14:13
add a comment |
3 Answers
3
active
oldest
votes
collections.OrderedDict seems to do what you want. To illustrate what @chepner mentioned about the representation of OrderedDict being tuples, I'll show you what I ran:
#encoding: utf-8
from collections import OrderedDict
import datetime
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
d = OrderedDict(zip(k,v))
for i in d:
print(': '.format(i,d[i]))
print('nn')
print(d)
and this was the output:
date: 2019-03-05
deviceCategory: desktop
transactionId: 1551740677701
productSku: 60104621
productName: (not set)
productCategoryHierarchy: sale/apartment/alicante/bajo-vinalopo/elx
channelGrouping: Tráfico de Búsqueda de Pago - Venta
itemRevenue: 0.0
itemQuantity: 1
OrderedDict([('date', datetime.date(2019, 3, 5)), ('deviceCategory', 'desktop'), ('transactionId', 1551740677701), ('productSku', 60104621), ('productName', '(not set)'), ('productCategoryHierarchy', 'sale/apartment/alicante/bajo-vinalopo/elx'), ('channelGrouping', 'Trxc3xa1fico de Bxc3xbasqueda de Pago - Venta'), ('itemRevenue', 0.0), ('itemQuantity', 1)])
So it looks like it's behaving as you were trying to get it to.
answered Mar 6 at 14:35
Andrew DeCotiis-MauroAndrew DeCotiis-Mauro
297
add a comment |
The above solution might be what you need, but if you used pandas you'd get an intermediate dataframe which makes manipulating, analyzing, and visualizing data easier (if that's an avenue you wanted). The solution looks something like this:
import datetime
import pandas as pd
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
df = pd.concat([pd.DataFrame(v, k)], axis=1)
# the dataframe
date 2019-03-05
deviceCategory desktop
transactionId 1551740677701
productSku 60104621
productName (not set)
productCategoryHierarchy sale/apartment/alicante/bajo-vinalopo/elx
channelGrouping Tráfico de Búsqueda de Pago - Venta
itemRevenue 0
itemQuantity 1
dict = df.to_dict()
results = dict[0]
results
# the dictionary
'date': datetime.date(2019, 3, 5),
'deviceCategory': 'desktop',
'transactionId': 1551740677701,
'productSku': 60104621,
'productName': '(not set)',
'productCategoryHierarchy': 'sale/apartment/alicante/bajo-vinalopo/elx',
'channelGrouping': 'Tráfico de Búsqueda de Pago - Venta',
'itemRevenue': 0.0,
'itemQuantity': 1
answered Mar 6 at 14:48
SamSam
917
New contributor
Sam is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
using Pandas is an option for me so... I'm going to try it. Thank you very much for your suggestion :)
– Julio María Meca Hansen
Mar 6 at 14:50
No problem! Hope it solves your issue. :)
– Sam
Mar 6 at 14:55
Demons! I must be doing something really nasty with the data or it's the pre-processing of each column what's tampering with the dictionary because... I get exactly the same result as withdict(zip(map(lambda x: "ga_%s" % x, k), v)):S
– Julio María Meca Hansen
Mar 6 at 15:22
add a comment |
Two important things to note:
- make sure you use bind variables (for performance and security).
This will also let you name the variables so the data order shouldn't
matter - when inserting lots of rows it is MUCH more efficient to
useexecuteMany()as discussed in
https://blogs.oracle.com/opal/efficient-and-scalable-batch-statement-execution-in-python-cx_oracle
answered Mar 6 at 21:35
Christopher JonesChristopher Jones
2,1141715
add a comment |
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collections.OrderedDict seems to do what you want. To illustrate what @chepner mentioned about the representation of OrderedDict being tuples, I'll show you what I ran:
#encoding: utf-8
from collections import OrderedDict
import datetime
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
d = OrderedDict(zip(k,v))
for i in d:
print(': '.format(i,d[i]))
print('nn')
print(d)
and this was the output:
date: 2019-03-05
deviceCategory: desktop
transactionId: 1551740677701
productSku: 60104621
productName: (not set)
productCategoryHierarchy: sale/apartment/alicante/bajo-vinalopo/elx
channelGrouping: Tráfico de Búsqueda de Pago - Venta
itemRevenue: 0.0
itemQuantity: 1
OrderedDict([('date', datetime.date(2019, 3, 5)), ('deviceCategory', 'desktop'), ('transactionId', 1551740677701), ('productSku', 60104621), ('productName', '(not set)'), ('productCategoryHierarchy', 'sale/apartment/alicante/bajo-vinalopo/elx'), ('channelGrouping', 'Trxc3xa1fico de Bxc3xbasqueda de Pago - Venta'), ('itemRevenue', 0.0), ('itemQuantity', 1)])
So it looks like it's behaving as you were trying to get it to.
answered Mar 6 at 14:35
Andrew DeCotiis-MauroAndrew DeCotiis-Mauro
297
add a comment |
collections.OrderedDict seems to do what you want. To illustrate what @chepner mentioned about the representation of OrderedDict being tuples, I'll show you what I ran:
#encoding: utf-8
from collections import OrderedDict
import datetime
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
d = OrderedDict(zip(k,v))
for i in d:
print(': '.format(i,d[i]))
print('nn')
print(d)
and this was the output:
date: 2019-03-05
deviceCategory: desktop
transactionId: 1551740677701
productSku: 60104621
productName: (not set)
productCategoryHierarchy: sale/apartment/alicante/bajo-vinalopo/elx
channelGrouping: Tráfico de Búsqueda de Pago - Venta
itemRevenue: 0.0
itemQuantity: 1
OrderedDict([('date', datetime.date(2019, 3, 5)), ('deviceCategory', 'desktop'), ('transactionId', 1551740677701), ('productSku', 60104621), ('productName', '(not set)'), ('productCategoryHierarchy', 'sale/apartment/alicante/bajo-vinalopo/elx'), ('channelGrouping', 'Trxc3xa1fico de Bxc3xbasqueda de Pago - Venta'), ('itemRevenue', 0.0), ('itemQuantity', 1)])
So it looks like it's behaving as you were trying to get it to.
answered Mar 6 at 14:35
Andrew DeCotiis-MauroAndrew DeCotiis-Mauro
297
add a comment |
collections.OrderedDict seems to do what you want. To illustrate what @chepner mentioned about the representation of OrderedDict being tuples, I'll show you what I ran:
#encoding: utf-8
from collections import OrderedDict
import datetime
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
d = OrderedDict(zip(k,v))
for i in d:
print(': '.format(i,d[i]))
print('nn')
print(d)
and this was the output:
date: 2019-03-05
deviceCategory: desktop
transactionId: 1551740677701
productSku: 60104621
productName: (not set)
productCategoryHierarchy: sale/apartment/alicante/bajo-vinalopo/elx
channelGrouping: Tráfico de Búsqueda de Pago - Venta
itemRevenue: 0.0
itemQuantity: 1
OrderedDict([('date', datetime.date(2019, 3, 5)), ('deviceCategory', 'desktop'), ('transactionId', 1551740677701), ('productSku', 60104621), ('productName', '(not set)'), ('productCategoryHierarchy', 'sale/apartment/alicante/bajo-vinalopo/elx'), ('channelGrouping', 'Trxc3xa1fico de Bxc3xbasqueda de Pago - Venta'), ('itemRevenue', 0.0), ('itemQuantity', 1)])
So it looks like it's behaving as you were trying to get it to.
answered Mar 6 at 14:35
Andrew DeCotiis-MauroAndrew DeCotiis-Mauro
297
collections.OrderedDict seems to do what you want. To illustrate what @chepner mentioned about the representation of OrderedDict being tuples, I'll show you what I ran:
#encoding: utf-8
from collections import OrderedDict
import datetime
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
d = OrderedDict(zip(k,v))
for i in d:
print(': '.format(i,d[i]))
print('nn')
print(d)
and this was the output:
date: 2019-03-05
deviceCategory: desktop
transactionId: 1551740677701
productSku: 60104621
productName: (not set)
productCategoryHierarchy: sale/apartment/alicante/bajo-vinalopo/elx
channelGrouping: Tráfico de Búsqueda de Pago - Venta
itemRevenue: 0.0
itemQuantity: 1
OrderedDict([('date', datetime.date(2019, 3, 5)), ('deviceCategory', 'desktop'), ('transactionId', 1551740677701), ('productSku', 60104621), ('productName', '(not set)'), ('productCategoryHierarchy', 'sale/apartment/alicante/bajo-vinalopo/elx'), ('channelGrouping', 'Trxc3xa1fico de Bxc3xbasqueda de Pago - Venta'), ('itemRevenue', 0.0), ('itemQuantity', 1)])
So it looks like it's behaving as you were trying to get it to.
answered Mar 6 at 14:35
Andrew DeCotiis-MauroAndrew DeCotiis-Mauro
297
answered Mar 6 at 14:35
Andrew DeCotiis-MauroAndrew DeCotiis-Mauro
297
answered Mar 6 at 14:35
Andrew DeCotiis-MauroAndrew DeCotiis-Mauro
297
answered Mar 6 at 14:35
Andrew DeCotiis-MauroAndrew DeCotiis-Mauro
297
297
add a comment |
add a comment |
The above solution might be what you need, but if you used pandas you'd get an intermediate dataframe which makes manipulating, analyzing, and visualizing data easier (if that's an avenue you wanted). The solution looks something like this:
import datetime
import pandas as pd
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
df = pd.concat([pd.DataFrame(v, k)], axis=1)
# the dataframe
date 2019-03-05
deviceCategory desktop
transactionId 1551740677701
productSku 60104621
productName (not set)
productCategoryHierarchy sale/apartment/alicante/bajo-vinalopo/elx
channelGrouping Tráfico de Búsqueda de Pago - Venta
itemRevenue 0
itemQuantity 1
dict = df.to_dict()
results = dict[0]
results
# the dictionary
'date': datetime.date(2019, 3, 5),
'deviceCategory': 'desktop',
'transactionId': 1551740677701,
'productSku': 60104621,
'productName': '(not set)',
'productCategoryHierarchy': 'sale/apartment/alicante/bajo-vinalopo/elx',
'channelGrouping': 'Tráfico de Búsqueda de Pago - Venta',
'itemRevenue': 0.0,
'itemQuantity': 1
answered Mar 6 at 14:48
SamSam
917
New contributor
Sam is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
using Pandas is an option for me so... I'm going to try it. Thank you very much for your suggestion :)
– Julio María Meca Hansen
Mar 6 at 14:50
No problem! Hope it solves your issue. :)
– Sam
Mar 6 at 14:55
Demons! I must be doing something really nasty with the data or it's the pre-processing of each column what's tampering with the dictionary because... I get exactly the same result as withdict(zip(map(lambda x: "ga_%s" % x, k), v)):S
– Julio María Meca Hansen
Mar 6 at 15:22
add a comment |
The above solution might be what you need, but if you used pandas you'd get an intermediate dataframe which makes manipulating, analyzing, and visualizing data easier (if that's an avenue you wanted). The solution looks something like this:
import datetime
import pandas as pd
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
df = pd.concat([pd.DataFrame(v, k)], axis=1)
# the dataframe
date 2019-03-05
deviceCategory desktop
transactionId 1551740677701
productSku 60104621
productName (not set)
productCategoryHierarchy sale/apartment/alicante/bajo-vinalopo/elx
channelGrouping Tráfico de Búsqueda de Pago - Venta
itemRevenue 0
itemQuantity 1
dict = df.to_dict()
results = dict[0]
results
# the dictionary
'date': datetime.date(2019, 3, 5),
'deviceCategory': 'desktop',
'transactionId': 1551740677701,
'productSku': 60104621,
'productName': '(not set)',
'productCategoryHierarchy': 'sale/apartment/alicante/bajo-vinalopo/elx',
'channelGrouping': 'Tráfico de Búsqueda de Pago - Venta',
'itemRevenue': 0.0,
'itemQuantity': 1
answered Mar 6 at 14:48
SamSam
917
New contributor
Sam is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
using Pandas is an option for me so... I'm going to try it. Thank you very much for your suggestion :)
– Julio María Meca Hansen
Mar 6 at 14:50
No problem! Hope it solves your issue. :)
– Sam
Mar 6 at 14:55
Demons! I must be doing something really nasty with the data or it's the pre-processing of each column what's tampering with the dictionary because... I get exactly the same result as withdict(zip(map(lambda x: "ga_%s" % x, k), v)):S
– Julio María Meca Hansen
Mar 6 at 15:22
add a comment |
The above solution might be what you need, but if you used pandas you'd get an intermediate dataframe which makes manipulating, analyzing, and visualizing data easier (if that's an avenue you wanted). The solution looks something like this:
import datetime
import pandas as pd
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
df = pd.concat([pd.DataFrame(v, k)], axis=1)
# the dataframe
date 2019-03-05
deviceCategory desktop
transactionId 1551740677701
productSku 60104621
productName (not set)
productCategoryHierarchy sale/apartment/alicante/bajo-vinalopo/elx
channelGrouping Tráfico de Búsqueda de Pago - Venta
itemRevenue 0
itemQuantity 1
dict = df.to_dict()
results = dict[0]
results
# the dictionary
'date': datetime.date(2019, 3, 5),
'deviceCategory': 'desktop',
'transactionId': 1551740677701,
'productSku': 60104621,
'productName': '(not set)',
'productCategoryHierarchy': 'sale/apartment/alicante/bajo-vinalopo/elx',
'channelGrouping': 'Tráfico de Búsqueda de Pago - Venta',
'itemRevenue': 0.0,
'itemQuantity': 1
answered Mar 6 at 14:48
SamSam
917
New contributor
Sam is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
The above solution might be what you need, but if you used pandas you'd get an intermediate dataframe which makes manipulating, analyzing, and visualizing data easier (if that's an avenue you wanted). The solution looks something like this:
import datetime
import pandas as pd
k = ['date', 'deviceCategory', 'transactionId', 'productSku', 'productName', 'productCategoryHierarchy', 'channelGrouping', 'itemRevenue', 'itemQuantity']
v = [datetime.date(2019, 3, 5), 'desktop', 1551740677701, 60104621, '(not set)', 'sale/apartment/alicante/bajo-vinalopo/elx', 'Tráfico de Búsqueda de Pago - Venta', 0.0, 1]
df = pd.concat([pd.DataFrame(v, k)], axis=1)
# the dataframe
date 2019-03-05
deviceCategory desktop
transactionId 1551740677701
productSku 60104621
productName (not set)
productCategoryHierarchy sale/apartment/alicante/bajo-vinalopo/elx
channelGrouping Tráfico de Búsqueda de Pago - Venta
itemRevenue 0
itemQuantity 1
dict = df.to_dict()
results = dict[0]
results
# the dictionary
'date': datetime.date(2019, 3, 5),
'deviceCategory': 'desktop',
'transactionId': 1551740677701,
'productSku': 60104621,
'productName': '(not set)',
'productCategoryHierarchy': 'sale/apartment/alicante/bajo-vinalopo/elx',
'channelGrouping': 'Tráfico de Búsqueda de Pago - Venta',
'itemRevenue': 0.0,
'itemQuantity': 1
answered Mar 6 at 14:48
SamSam
917
New contributor
Sam is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered Mar 6 at 14:48
SamSam
917
New contributor
Sam is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered Mar 6 at 14:48
SamSam
917
answered Mar 6 at 14:48
SamSam
917
917
New contributor
Sam is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Sam is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Sam is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
using Pandas is an option for me so... I'm going to try it. Thank you very much for your suggestion :)
– Julio María Meca Hansen
Mar 6 at 14:50
No problem! Hope it solves your issue. :)
– Sam
Mar 6 at 14:55
Demons! I must be doing something really nasty with the data or it's the pre-processing of each column what's tampering with the dictionary because... I get exactly the same result as withdict(zip(map(lambda x: "ga_%s" % x, k), v)):S
– Julio María Meca Hansen
Mar 6 at 15:22
add a comment |
using Pandas is an option for me so... I'm going to try it. Thank you very much for your suggestion :)
– Julio María Meca Hansen
Mar 6 at 14:50
No problem! Hope it solves your issue. :)
– Sam
Mar 6 at 14:55
Demons! I must be doing something really nasty with the data or it's the pre-processing of each column what's tampering with the dictionary because... I get exactly the same result as withdict(zip(map(lambda x: "ga_%s" % x, k), v)):S
– Julio María Meca Hansen
Mar 6 at 15:22
using Pandas is an option for me so... I'm going to try it. Thank you very much for your suggestion :)
– Julio María Meca Hansen
Mar 6 at 14:50
using Pandas is an option for me so... I'm going to try it. Thank you very much for your suggestion :)
– Julio María Meca Hansen
Mar 6 at 14:50
No problem! Hope it solves your issue. :)
– Sam
Mar 6 at 14:55
No problem! Hope it solves your issue. :)
– Sam
Mar 6 at 14:55
Demons! I must be doing something really nasty with the data or it's the pre-processing of each column what's tampering with the dictionary because... I get exactly the same result as with
dict(zip(map(lambda x: "ga_%s" % x, k), v)) :S– Julio María Meca Hansen
Mar 6 at 15:22
Demons! I must be doing something really nasty with the data or it's the pre-processing of each column what's tampering with the dictionary because... I get exactly the same result as with
dict(zip(map(lambda x: "ga_%s" % x, k), v)) :S– Julio María Meca Hansen
Mar 6 at 15:22
add a comment |
Two important things to note:
- make sure you use bind variables (for performance and security).
This will also let you name the variables so the data order shouldn't
matter - when inserting lots of rows it is MUCH more efficient to
useexecuteMany()as discussed in
https://blogs.oracle.com/opal/efficient-and-scalable-batch-statement-execution-in-python-cx_oracle
answered Mar 6 at 21:35
Christopher JonesChristopher Jones
2,1141715
add a comment |
Two important things to note:
- make sure you use bind variables (for performance and security).
This will also let you name the variables so the data order shouldn't
matter - when inserting lots of rows it is MUCH more efficient to
useexecuteMany()as discussed in
https://blogs.oracle.com/opal/efficient-and-scalable-batch-statement-execution-in-python-cx_oracle
answered Mar 6 at 21:35
Christopher JonesChristopher Jones
2,1141715
add a comment |
Two important things to note:
- make sure you use bind variables (for performance and security).
This will also let you name the variables so the data order shouldn't
matter - when inserting lots of rows it is MUCH more efficient to
useexecuteMany()as discussed in
https://blogs.oracle.com/opal/efficient-and-scalable-batch-statement-execution-in-python-cx_oracle
answered Mar 6 at 21:35
Christopher JonesChristopher Jones
2,1141715
Two important things to note:
- make sure you use bind variables (for performance and security).
This will also let you name the variables so the data order shouldn't
matter - when inserting lots of rows it is MUCH more efficient to
useexecuteMany()as discussed in
https://blogs.oracle.com/opal/efficient-and-scalable-batch-statement-execution-in-python-cx_oracle
answered Mar 6 at 21:35
Christopher JonesChristopher Jones
2,1141715
answered Mar 6 at 21:35
Christopher JonesChristopher Jones
2,1141715
answered Mar 6 at 21:35
Christopher JonesChristopher Jones
2,1141715
answered Mar 6 at 21:35
Christopher JonesChristopher Jones
2,1141715
2,1141715
add a comment |
add a comment |
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1
Prior to Python 3.7, a
dictwould not preserve any information about the order in which key/value pairs were added. Usecollections.OrderedDictinstead. The issue of preserving adatetimeobject across JSON encoding/decoding is an entirely separate problem, though.– chepner
Mar 6 at 14:04
3
It's only the representation of an
OrderedDictthat looks like a list of tuples.– chepner
Mar 6 at 14:04
OrderedDict behaves exactly like a dict , what are you trying to do with it that makes it not behave like one?
– AntiMatterDynamite
Mar 6 at 14:13