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Defining field values using an other fields values Esri Arcmap

I´m using arcMap, Esri. I have a polyline layer with information in text which I need to convert to number values. I want accomplish this using scripting with Python in the Field calculator.
My challenge:
Using field values in one field I want to define values in another field.
In my case I need to define the width of a road in numbers, depending on the field value in text from another field.
The road "widthNumber" will depend on the value of another fields value "widthText".

there are a number of ways you can do this. I'm making the assumption both fields are in the same feature class/shapefile and the widthNumber field is an int of some type.
The ideal case is to use a switch case (Java/C#), but those don't exist in python. So we can either use a dictionary to sort of recreate the switch or simply load up on ifs'. I'm a fan of cleaner code so I've included the logic for the dictionary. But you can always move that into a bunch of ifs' as you deem necessary.
All you have to do is use the pre-logic script code area to write a function which accepts the widthText and returns the widthNumber.
def calculateValue(text):
switcher ={
"Ones":1,
"Fivers":5,
"Threebs":3,
"Twotow":2,
"Four":4,
"Fivers":5
}
return switcher.get(text,"Invalid")`
Then in the bottom section you just call that function and pass in the attribute..
calculateValue(!widthText!)
In this example I did not write in any error handling to deal with invalid values, depending on how your values are stored it may be smart to ensure everything is in the same case (Upper/Lower) to ensure consistency.

How to implement this in python : Check if a vertex exist, if not, create a new vertex

I want to create a neptune db, and dump data to it. I download historical data from DynamoDB to S3, these files in csv format. The header in these csv like:
~id, someproperties:String, ~label
Then, I need to implement real-time streaming to this neptune db through lambda, in the lambda function, I will check if one vertex(or edges) exist or not, if exist, I will update the vertex(or edges), otherwise I creat a new one.
In python, my implementation like this:
g.V().hasLabel('Event').has(T.id, event['Id']).fold().coalesce(unfold(), addV('Event').property(T.id, event['Id'])).property(Cardinality.single, 'State', event['State']).property('sourceData', event['sourceData']).next()
Here I have some questions:
In real-time streaming, I need to query if vertex with a id already
there, so I need to query the nodes of historical data, so can
has(T.id, event['Id']) do this? or should I just use
has(id, event['Id']) or has("id", event['Id']) ?
I was using g.V().has('Event', T.id, event['Id']) instead of
g.V().hasLabel('Event').has(T.id, event['Id']), but got error
like cannot local NeptuneGraphTraversal.has(). Are these two
queries same thing?

Here's the three bits of Gremlin you had a question about:
g.V().has(T.id, "some-id")
g.V().has(id, "some-id")
g.V().has("id", "some-id")
The first two will return you the same result as id is a member of T (as a point of style, Gremlin users typically statically import id so that it can be referenced that way for brevity). The last traversal is different from the first two because, as a String value it refers to a standard property key named "id". Generally speaking, TinkerPop would recommend that you not use a property key name like "id" or "label" as it can lead to mistakes and confusion with values of T.
As for the second part of your question revolving around:
g.V().has('Event', T.id, event['Id'])
g.V().hasLabel('Event').has(T.id, event['Id'])
You can't pass T.id to the 3-ary form of has() as Kelvin points out as the step signature only allows a String in that second position. It also wouldn't make sense to allow T there because T.label is already accounted for by the first argument and T.id refers to the actual graph element identifier. If you know that value then you wouldn't bother specifying the T.label in the first place, as the T.id already uniquely identifies the element. You would just do g.V(event['Id']).

Peewee incrementing an integer field without the use of primary key during migration

I have a table I need to add columns to it, one of them is a column that dictates business logic. So think of it as a "priority" column, and it has to be unique and a integer field. It cannot be the primary key but it is unique for business logic purposes.
I've searched the docs but I can't find a way to add the column and add default (say starting from 1) values and auto increment them without setting this as a primarykey..
Thus creating the field like
example_column = IntegerField(null=False, db_column='PriorityQueue',default=1)
This will fail because of the unique constraint. I should also mention this is happening when I'm migrating the table (existing data will all receive a value of '1')
So, is it possible to do the above somehow and get the column to auto increment?

It should definitely be possible, especially outside of peewee. You can definitely make a counter that starts at 1 and increments to the stop and at the interval of your choice with range(). You can then write each incremented variable to the desired field in each row as you iterate through.

Depends on your database, but postgres uses sequences to handle this kind of thing. Peewee fields accept a sequence name as an initialization parameter, so you could pass it in that manner.

Doing "group by" in django but still retaining complete object

I want to do a GROUP BY in Django. I saw answers on Stack Overflow that recommend:
Member.objects.values('designation').annotate(dcount=Count('designation'))
This works, but the problem is you're getting a ValuesQuerySet instead of a QuerySet, so the queryset isn't giving me full objects but only specific fields. I want to get complete objects.
Of course, since we're grouping we need to choose which object to take out of each group; I want a way to specify the object (e.g. take the one with the biggest value in a certain field, etc.)
Does anyone know how I can do that?

If you're willing to make two queries, you could do the following:
dcounts = Member.objects.values('id', 'designation').annotate(dcount=Count('designation')).order_by('-dcount')
member = Member.objects.get(id=dcounts.first()['id'])
If you wanted the top five objects by dcount, you could do the following:
ids = [dcount['id'] for dcount in dcounts[:5]]
members = Member.objects.filter(id__in=ids)

It sounds like you don't necessarily need to GROUP BY, but just want to limit your selection to one item per field (eg, the MAX value of a certain field).
Can you try getting distinct objects by field, such as
In Postgres
Member.objects.order_by('designation').distinct('designation')
In any other database
Member.objects.distinct('designation')
https://docs.djangoproject.com/en/dev/ref/models/querysets/#django.db.models.query.QuerySet.distinct

Annotate with a filtered related object set

So I have a SensorType model, which has a collection of SensorReading objects as part of a sensorreading_set (i.e., the sensor type has many sensor readings). I want to annotate the sensor types to give me the sensor reading with the max id. To wit:
sensor_types = SensorType.objects.annotate(
newest_reading_id=Max('sensorreading__id'))
This works fantastically, but there's a catch. Sensor Readings have another foreign key, Device. What I really want is the highest sensor reading id for a given sensor type for a given device. Is it possible to have the annotation refer to a subset of sensor readings that basically amounts to SensorReading.objects.filter(device=device)?

Filtering works perfectly fine with related objects, and annotations work perfectly fine with those filters. What you need to do is:
from django.db.models import Max
SensorType.objects.filter(sensorreading__device=device) \
.annotate(newest_reading_id=Max('sensorreading__id'))
Note that the order of function calls matters. Using filter before annotate will only annotate on the filtered set, using annotate before filter will annotate on the complete set, and then filter. Also, when filtering on related objects, keep in mind that filter(sensorreading__x=x, sensorreading__y=y) will filter for sensorreadings where all conditions are true, while .filter(sensorreading__x=x).filter(sensorreading__y=y) will filter for sensorreadings where either one of these conditions is true.

You can use .extra for these type of Queries in Django:
Like this:
SensorType.objects.extra(
select={
"newest_reading_id": "SELECT MAX(id) FROM sensorreading WHERE sensorreading.sensortype_id = sensortype.id AND sensorreading.device_id=%s",
},
select_params = [device.id]
)
You can read more about .extra here : https://docs.djangoproject.com/en/1.6/ref/models/querysets/#django.db.models.query.QuerySet.extra

As I understood, you want to GROUP_BY on two fields, device_id and sensortype_id. This can be done using:
SensorReading.objects.all().values('device_id', 'sensortype_id').annotate(max=Max('id'))
I didn't tried it; it was taken from 2 different answers in SO, this one and this one.