I have a problem when I try to merge two dictionaries to fit for doing a post later. For some reason the get seems to be nested and Im not sure how to clean it up. Would be great to get some tips on optimizing the code as well, right now it looks a bit messy.
for network in networks:
post_dict = {e1:e2 for e1,e2 in network['extattrs'].iteritems() if e1 not in keys }
pprint (post_dict['Stuff-Name']['value'])
post_dict['name'] = post_dict.pop('Stuff-Name')
post_dict['sid'] = post_dict.pop('Stuff-id')
dict_to_post = merge_two_dicts(post_dict, default_keys)
network:
{u'_ref': u'ref number',
u'comment': u'Name of object',
u'extattrs': {u'Network-Type': {u'value': u'Internal'},
u'Stuff-Id': {u'value': 110},
u'Stuff-Name': {u'value': u'Name of object'}},
u'network': u'Subnet-A',
u'network_view': u'default'}
default_keys:
default_keys = {'status':'Active',
'group':None,
'site':'City-A',
'role':'Production',
'description':None,
'custom_fields':None,
'tenant':None}
post_dict:
{'name': {u'value': u'Name of object'},
'sid': {u'value': 110}}
So what I want to achive is to get rid of the nested keys (within key "name" and "sid" so the key and value pair should be "name: Name of object" and "sid: 110"
The post function is not yet defined.
In my understanding, you case is really specific and I would probably go for a easy & dirty solution. First of all have you tried this:
post_dict['name'] = (post_dict.pop('Stuff-Name'))['value']
Secondly, how about making use of the "filter and renaming" and collapse the indexing there? This is not advisable, but if you are trying to do a lazy work-around it will suffice. I recommend you go with my first suggestion, as I'm pretty confident that it will solve your issue.
To get this first value of any nested dictionary you could use this
d = {'custom_fields': None, 'description': None, 'group': None, 'name':
{'value': 'Name of object'}, 'role': 'Production', 'site': 'City-A',
'status': 'Active', 'tenant': None, 'sid': {'value': 110}}
for key in d.keys():
if type(d[key]) == dict:
d[key] = d[key].popitem()[1]
It returns
{'custom_fields': None, 'description': None, 'group': None, 'name': 'Name of
object', 'role': 'Production', 'site': 'City-A', 'status': 'Active',
'tenant': None, 'sid': 110}
I think it's this step that's causing the dictionaries to be nested in the first place
post_dict['name'] = post_dict.pop('Stuff-Name')
post_dict['sid'] = post_dict.pop('Stuff-id')
You could try popitem()[1] here if you'll only ever need value of that dictionary and not the key.
Related
I call an API and this my JSON response:
{'data': [{
'id': 'd-1225959',
'startTime': '2022-12-30T00:00:00.000Z',
'endTime': '2022-12-30T23:59:00.000Z',
'checkedInAt': None,
'checkedOutAt': None,
'status': 'PENDING',
'space': {
'id': 'd-4063963',
'name': '082',
'type': 'DESK',
'createdAt': '2021-07-06T11:48:57.000Z',
'updatedAt': '2021-07-06T11:48:57.000Z',
'isAvailable': False,
'assignedTo': None,
'locationId': '133778',
'floorId': '41681',
'floorName': 'Car Park',
'neighborhoodId': '92267',
'neighborhoodName': 'NEI1'}}
I'm struggling to get the 'space' 'id' and 'name' extracted out if I do a nested python loop like so it only returns the headers like 'id' and 'name' not the values held within.
for order in response['data']:
print(order['id'])
print(order['startTime'])
print(order['endTime'])
print(order['checkedInAt'])
print(order['checkedOutAt'])
print(order['status'])
print(order['space'])
for doc in response['space']:
print(doc['id'], doc['name'])
Any help with this would be much appreciated!
for doc in response['space']: will iterate over the keys in response['space'] dict, i.e. doc will be str.
You want to do doc = response['space'] instead and then print(doc['id']). or directly print(response['space']['id']).
Note, you may want to use dict.get() method to avoid KeyError.
# if response dict has no 'space' key, return empty dict.
# if no 'id' key - return None
space_id = response.get('space', {}).get('id')
This is from an R guy.
I have this mess in a Pandas column: data['crew'].
array(["[{'credit_id': '54d5356ec3a3683ba0000039', 'department': 'Production', 'gender': 1, 'id': 494, 'job': 'Casting', 'name': 'Terri Taylor', 'profile_path': None}, {'credit_id': '56407fa89251417055000b58', 'department': 'Sound', 'gender': 0, 'id': 6745, 'job': 'Music Editor', 'name': 'Richard Henderson', 'profile_path': None}, {'credit_id': '5789212392514135d60025fd', 'department': 'Production', 'gender': 2, 'id': 9250, 'job': 'Executive In Charge Of Production', 'name': 'Jeffrey Stott', 'profile_path': None}, {'credit_id': '57892074c3a36835fa002886', 'department': 'Costume & Make-Up', 'gender': 0, 'id': 23783, 'job': 'Makeup Artist', 'name': 'Heather Plott', 'profile_path': None}
It goes on for quite some time. Each new dict starts with a credit_id field. One sell can hold several dicts in an array.
Assume I want the names of all Casting directors, as shown in the first entry. I need to check check the job entry in every dict and, if it's Casting, grab what's in the name field and store it in my data frame in data['crew'].
I tried several strategies, then backed off and went for something simple.
Running the following shut me down, so I can't even access a simple field. How can I get this done in Pandas.
for row in data.head().iterrows():
if row['crew'].job == 'Casting':
print(row['crew'])
EDIT: Error Message
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-138-aa6183fdf7ac> in <module>()
1 for row in data.head().iterrows():
----> 2 if row['crew'].job == 'Casting':
3 print(row['crew'])
TypeError: tuple indices must be integers or slices, not str
EDIT: Code used to get the array of dict (strings?) in the first place.
def convert_JSON(data_as_string):
try:
dict_representation = ast.literal_eval(data_as_string)
return dict_representation
except ValueError:
return []
data["crew"] = data["crew"].map(lambda x: sorted([d['name'] if d['job'] == 'Casting' else '' for d in convert_JSON(x)])).map(lambda x: ','.join(map(str, x))
To create a DataFrame from your sample data, write:
df = pd.DataFrame(data=[
{ 'credit_id': '54d5356ec3a3683ba0000039', 'department': 'Production',
'gender': 1, 'id': 494, 'job': 'Casting', 'name': 'Terri Taylor',
'profile_path': None},
{ 'credit_id': '56407fa89251417055000b58', 'department': 'Sound',
'gender': 0, 'id': 6745, 'job': 'Music Editor',
'name': 'Richard Henderson', 'profile_path': None},
{ 'credit_id': '5789212392514135d60025fd', 'department': 'Production',
'gender': 2, 'id': 9250, 'job': 'Executive In Charge Of Production',
'name': 'Jeffrey Stott', 'profile_path': None},
{ 'credit_id': '57892074c3a36835fa002886', 'department': 'Costume & Make-Up',
'gender': 0, 'id': 23783, 'job': 'Makeup Artist',
'name': 'Heather Plott', 'profile_path': None}])
Then you can get your data with a single instruction:
df[df.job == 'Casting'].name
The result is:
0 Terri Taylor
Name: name, dtype: object
The above result is Pandas Series object with names found.
In this case, 0 is the index value for the record found and
Terri Taylor is the name of (the only in your data) Casting Director.
Edit
If you want just a list (not Series), write:
df[df.job == 'Casting'].name.tolist()
The result is ['Terri Taylor'] - just a list.
I think, both my solutions should be quicker than "ordinary" loop
based on iterrows().
Checking the execution time, you may try also yet another solution:
df.query("job == 'Casting'").name.tolist()
==========
And as far as your code is concerned:
iterrows() returns each time a pair containing:
the key of the current row,
a named tuple - the content of this row.
So your loop should look something like:
for row in df.iterrows():
if row[1].job == 'Casting':
print(row[1]['name'])
You can not write row[1].name because it refers to the index value
(here we have a collision with default attributes of the named tuple).
I know that somewhat related questions have been asked here: Accessing key, value in a nested dictionary and here: python accessing elements in a dictionary inside dictionary among other places but I can't quite seem to apply the answers' methodology to my issue.
I'm getting a KeyError trying to access the keys within response_dict, which I know is due to it being nested/paginated and me going about this the wrong way. Can anybody help and/or point me in the right direction?
import requests
import json
URL = "https://api.constantcontact.com/v2/contacts?status=ALL&limit=1&api_key=<redacted>&access_token=<redacted>"
#make my request, store it in the requests object 'r'
r = requests.get(url = URL)
#status code to prove things are working
print (r.status_code)
#print what was retrieved from the API
print (r.text)
#visual aid
print ('---------------------------')
#decode json data to a dict
response_dict = json.loads(r.text)
#show how the API response looks now
print(response_dict)
#just for confirmation
print (type(response_dict))
print('-------------------------')
# HERE LIES THE ISSUE
print(response_dict['first_name'])
And my output:
200
{"meta":{"pagination":{}},"results":[{"id":"1329683950","status":"ACTIVE","fax":"","addresses":[{"id":"4e19e250-b5d9-11e8-9849-d4ae5275509e","line1":"222 Fake St.","line2":"","line3":"","city":"Kansas City","address_type":"BUSINESS","state_code":"","state":"OK","country_code":"ve","postal_code":"19512","sub_postal_code":""}],"notes":[],"confirmed":false,"lists":[{"id":"1733488365","status":"ACTIVE"}],"source":"Site Owner","email_addresses":[{"id":"1fe198a0-b5d5-11e8-92c1-d4ae526edd6c","status":"ACTIVE","confirm_status":"NO_CONFIRMATION_REQUIRED","opt_in_source":"ACTION_BY_OWNER","opt_in_date":"2018-09-11T18:18:20.000Z","email_address":"rsmith#fake.com"}],"prefix_name":"","first_name":"Robert","middle_name":"","last_name":"Smith","job_title":"I.T.","company_name":"FBI","home_phone":"","work_phone":"5555555555","cell_phone":"","custom_fields":[],"created_date":"2018-09-11T15:12:40.000Z","modified_date":"2018-09-11T18:18:20.000Z","source_details":""}]}
---------------------------
{'meta': {'pagination': {}}, 'results': [{'id': '1329683950', 'status': 'ACTIVE', 'fax': '', 'addresses': [{'id': '4e19e250-b5d9-11e8-9849-d4ae5275509e', 'line1': '222 Fake St.', 'line2': '', 'line3': '', 'city': 'Kansas City', 'address_type': 'BUSINESS', 'state_code': '', 'state': 'OK', 'country_code': 've', 'postal_code': '19512', 'sub_postal_code': ''}], 'notes': [], 'confirmed': False, 'lists': [{'id': '1733488365', 'status': 'ACTIVE'}], 'source': 'Site Owner', 'email_addresses': [{'id': '1fe198a0-b5d5-11e8-92c1-d4ae526edd6c', 'status': 'ACTIVE', 'confirm_status': 'NO_CONFIRMATION_REQUIRED', 'opt_in_source': 'ACTION_BY_OWNER', 'opt_in_date': '2018-09-11T18:18:20.000Z', 'email_address': 'rsmith#fake.com'}], 'prefix_name': '', 'first_name': 'Robert', 'middle_name': '', 'last_name': 'Smith', 'job_title': 'I.T.', 'company_name': 'FBI', 'home_phone': '', 'work_phone': '5555555555', 'cell_phone': '', 'custom_fields': [], 'created_date': '2018-09-11T15:12:40.000Z', 'modified_date': '2018-09-11T18:18:20.000Z', 'source_details': ''}]}
<class 'dict'>
-------------------------
Traceback (most recent call last):
File "C:\Users\rkiek\Desktop\Python WIP\Chris2.py", line 20, in <module>
print(response_dict['first_name'])
KeyError: 'first_name'
first_name = response_dict["results"][0]["first_name"]
Even though I think this question would be better answered by yourself by reading some documentation, I will explain what is going on here. You see the dict-object of the man named "Robert" is within a list which is a value under the key "results". So, at first you need to access the value within results which is a python-list.
Then you can use a loop to iterate through each of the elements within the list, and treat each individual element as a regular dictionary object.
results = response_dict["results"]
results = response_dict.get("results", None)
# use any one of the two above, the first one will throw a KeyError if there is no key=="results" the other will return NULL
# this results is now a list according to the data you mentioned.
for item in results:
print(item.get("first_name", None)
# here you can loop through the list of dictionaries and treat each item as a normal dictionary
I seem to be stuck on very simple task. I'm still dipping my toes into Python.
I'm trying to download Sentinel 2 Images with SentinelHub API:SentinelHub
The result of data that my code returns is like this:
{'geometry': {'coordinates': [[[[35.895906644, 31.602691754],
[36.264307655, 31.593801516],
[36.230618703, 30.604681346],
[35.642363693, 30.617971909],
[35.678587829, 30.757888786],
[35.715700562, 30.905919341],
[35.754290061, 31.053632806],
[35.793289298, 31.206946419],
[35.895906644, 31.602691754]]]],
'type': 'MultiPolygon'},
'id': 'ee923fac-0097-58a8-b861-b07d89b99310',
'properties': {'**productType**': '**S2MSI1C**',
'centroid': {'coordinates': [18.1321538275, 31.10368655], 'type': 'Point'},
'cloudCover': 10.68,
'collection': 'Sentinel2',
'completionDate': '2017-06-07T08:15:54Z',
'description': None,
'instrument': 'MSI',
'keywords': [],
'license': {'description': {'shortName': 'No license'},
'grantedCountries': None,
'grantedFlags': None,
'grantedOrganizationCountries': None,
'hasToBeSigned': 'never',
'licenseId': 'unlicensed',
'signatureQuota': -1,
'viewService': 'public'},
'links': [{'href': 'http://opensearch.sentinel-hub.com/resto/collections/Sentinel2/ee923fac-0097-58a8-b861-b07d89b99310.json?&lang=en',
'rel': 'self',
'title': 'GeoJSON link for ee923fac-0097-58a8-b861-b07d89b99310',
'type': 'application/json'}],
'orbitNumber': 10228,
'organisationName': None,
'parentIdentifier': None,
'platform': 'Sentinel-2',
'processingLevel': '1C',
'productIdentifier': 'S2A_OPER_MSI_L1C_TL_SGS__20170607T120016_A010228_T36RYV_N02.05',
'published': '2017-07-26T13:09:17.405352Z',
'quicklook': None,
'resolution': 10,
's3Path': 'tiles/36/R/YV/2017/6/7/0',
's3URI': 's3://sentinel-s2-l1c/tiles/36/R/YV/2017/6/7/0/',
'sensorMode': None,
'services': {'download': {'mimeType': 'text/html',
'url': 'http://sentinel-s2-l1c.s3-website.eu-central-1.amazonaws.com#tiles/36/R/YV/2017/6/7/0/'}},
'sgsId': 2168915,
'snowCover': 0,
'spacecraft': 'S2A',
'startDate': '2017-06-07T08:15:54Z',
'thumbnail': None,
'title': 'S2A_OPER_MSI_L1C_TL_SGS__20170607T120016_A010228_T36RYV_N02.05',
'updated': '2017-07-26T13:09:17.405352Z'},
'type': 'Feature'}
Can you explain how can I iterate through this set of data and extract only 'productType'? For example, if there are several similar data sets it would return only different product types.
My code is :
import matplotlib.pyplot as plt
import numpy as np
from sentinelhub import AwsProductRequest, AwsTileRequest, AwsTile, BBox, CRS
betsiboka_coords_wgs84 = [31.245117,33.897777,34.936523,36.129002]
bbox = BBox(bbox=betsiboka_coords_wgs84, crs=CRS.WGS84)
date= '2017-06-05',('2017-06-08')
data=sentinelhub.opensearch.get_area_info(bbox, date_interval=date, maxcc=None)
for i in data:
print(i)
Based on what you have provided, replace your bottom for loop:
for i in data:
print(i)
with the following:
for i in data:
print(i['properties']['**productType**'])
If you want to access only the propertyType you can use i['properties']['productType'] in your for loop. If you want to access it any time you want without writing each time those keys, you can define a generator like this:
def property_types(data_array):
for data in data_array
yield data['properties']['propertyType']
So you can use it like this in a loop (your data_array is data, as returned by sentinelhub api):
for property_type in property_types(data):
# do stuff with property_type
keys = []
for key in d.keys():
if key == 'properties':
for k in d[key].keys():
if k == '**productType**' and k not in keys:
keys.append(d[key][k])
print(keys)
Getting only specific (nested) values: Since your request key is nested, and resides inside the parent "properties" object, you need to access it first, preferably using the get method. This can be done as follows (note the '{}' parameter in the first get, this returns an empty dictionary if the first key is not present)
data_dictionary = json.loads(data_string)
product_type = data_dictionary.get('properties', {}).get('**productType**')
You can then aggregate the different product_type objects in a set, which will automatically guarantee that no 2 objects are the same
product_type_set = set()
product_type.add(product_type)
I have a YAML file that parses into an object, e.g.:
{'name': [{'proj_directory': '/directory/'},
{'categories': [{'quick': [{'directory': 'quick'},
{'description': None},
{'table_name': 'quick'}]},
{'intermediate': [{'directory': 'intermediate'},
{'description': None},
{'table_name': 'intermediate'}]},
{'research': [{'directory': 'research'},
{'description': None},
{'table_name': 'research'}]}]},
{'nomenclature': [{'extension': 'nc'}
{'handler': 'script'},
{'filename': [{'id': [{'type': 'VARCHAR'}]},
{'date': [{'type': 'DATE'}]},
{'v': [{'type': 'INT'}]}]},
{'data': [{'time': [{'variable_name': 'time'},
{'units': 'minutes since 1-1-1980 00:00 UTC'},
{'latitude': [{'variable_n...
I'm having trouble accessing the data in python and regularly see the error TypeError: list indices must be integers, not str
I want to be able to access all elements corresponding to 'name' so to retrieve each data field I imagine it would look something like:
import yaml
settings_stream = open('file.yaml', 'r')
settingsMap = yaml.safe_load(settings_stream)
yaml_stream = True
print 'loaded settings for: ',
for project in settingsMap:
print project + ', ' + settingsMap[project]['project_directory']
and I would expect each element would be accessible via something like ['name']['categories']['quick']['directory']
and something a little deeper would just be:
['name']['nomenclature']['data']['latitude']['variable_name']
or am I completely wrong here?
The brackets, [], indicate that you have lists of dicts, not just a dict.
For example, settingsMap['name'] is a list of dicts.
Therefore, you need to select the correct dict in the list using an integer index, before you can select the key in the dict.
So, giving your current data structure, you'd need to use:
settingsMap['name'][1]['categories'][0]['quick'][0]['directory']
Or, revise the underlying YAML data structure.
For example, if the data structure looked like this:
settingsMap = {
'name':
{'proj_directory': '/directory/',
'categories': {'quick': {'directory': 'quick',
'description': None,
'table_name': 'quick'}},
'intermediate': {'directory': 'intermediate',
'description': None,
'table_name': 'intermediate'},
'research': {'directory': 'research',
'description': None,
'table_name': 'research'},
'nomenclature': {'extension': 'nc',
'handler': 'script',
'filename': {'id': {'type': 'VARCHAR'},
'date': {'type': 'DATE'},
'v': {'type': 'INT'}},
'data': {'time': {'variable_name': 'time',
'units': 'minutes since 1-1-1980 00:00 UTC'}}}}}
then you could access the same value as above with
settingsMap['name']['categories']['quick']['directory']
# quick