Table structure like -
db.define_table('parent',
Field('name'),format='%(name)s')
db.define_table('children',
Field('name'),
Field('mother','reference parent'),
Field('father','reference parent'))
db.children.mother.requires = IS_IN_DB(db, db.parent.id,'%(name)s')
db.children.father.requires = IS_IN_DB(db, db.parent.id,'%(name)s')
Controller :
grid = SQLFORM.grid(db.children, orderby=[db.children.id],
csv=True,
fields=[db.children.id, db.children.name, db.children.mother, db.children.father])
return dict(grid=grid)
Here grid shows proper values i.e names of the mother and father from the parent table.
But when I try to export it via csv link - resulted excelsheet shows ids and not the names of mother and father.
Please help!
The CSV download just gives you the raw database values without first applying each field's represent attribute. If you want the "represented" values of each field, you have two options. First, you can choose the TSV (tab-separated-values) download instead of CSV. Second, you can define a custom export class:
import cStringIO
class CSVExporter(object):
file_ext = "csv"
content_type = "text/csv"
def __init__(self, rows):
self.rows = rows
def export(self):
if self.rows:
s = cStringIO.StringIO()
self.rows.export_to_csv_file(s, represent=True)
return s.getvalue()
else:
return ''
grid = SQLFORM.grid(db.mytable, exportclasses=dict(csv=(CSVExporter, 'CSV')))
The exportclasses argument is a dictionary of custom download types that can be used to override existing types or add new ones. Each item is a tuple including the exporter class and the label to be used for the download link in the UI.
We should probably add this as an option.
Related
I have a function that sees what card is in a player's hand and will add to their score depending on the card in their hand. I have all the card values stored in a JSON file. I have code this so far:
with open("values.json") as values:
value = json.load(values)
for i in range(0, len(hand)):
card = hand[i]
values.json
{
"3Hearts": 3
}
if the card is 3Hearts how could I get the 3 to be returned?
Or is there a better way to store the data?
I will admit I am not very familiar with json files. However if the json file is not a necessity you could just store the data in another .py file (Cards.py for example).
Also, because you are using python, you would be better off making a Card class and make Card objects.
This is what it would look like:
# Make Card Class
class Card:
def __init__(self, name, number):
self.name = name
self.number = number
# Make Card Objects
threehearts = Card("3Hearts", "3")
Here I used threehearts instead of 3Hearts because making an object name starting with a number is not good practice. To compensate I made an attribute Card.name where you can "name" the card "3Hearts" as you did in the question.
So assuming you are going to use that .py file to store your data, this is what I would propose:
# Import data here
from Cards import*
# Make the player's hand
hand = [threehearts]
# Display the number corresponding to the player's hand
for i in range(0, len(hand)):
card = hand[i]
print(card.number)
The output of this code will be:
3
You can also store hand = [threehearts] in the Cards.py file as well if you need to.
I am using odoo 10 and I have two models Order_Line and Products.
OrderLine
class OrderLine(models.Model):
_name = 'order_line'
_description = 'Order Lines'
name = fields.Char()
products = fields.Many2one('amgl.products', String='Products')
Products
class Products(models.Model):
_name = 'products'
_description = 'Products'
_sql_constraints = [
('uniq_poduct_code', 'unique(product_code)', 'Product Code already exists!')
]
name = fields.Char()
product_code = Char()
Now i am trying to create order_line from a csv file and in csv file the customer is providing me 'Product Code' instead of Id. How to handle this that, we use product code and system automatically fills the products associated with that product code.
Note :
Product Code in products table is also unique, so there is no chance of duplicating.
CSV template:
customer/account_number,customer/first_name,customer/last_name,customer/account_type,order/transaction_id,order/products/product_code,order/quantity,order/customer_id/id
Case 1: there are no products stored in the database with any of the product codes the customer is giving to you
If the product codes haven't been created yet in the database, you should have two CSV files (Products.csv and OrderLine.csv). The first one must have three columns (id, name and product_code). The second one must have three columns too (id, name and products/id). So you would only have to make up a XML ID under the id column in Products.csv and call this XML ID from the respective row of the column products/id of the file OrderLine.csv.
Case 2: the product codes the customer has given to you belong to existing products in the database
Now, the customer has given you product codes of products which already exist in the database. In this case you don't have to create a Products.csv file. You need to know which are the XML IDs of the products which have the product codes the customer gave to you. For that, you can go through the interface of Odoo to the tree view of the model products (if this view doesn't exist, you must create it). Then, you'll have to select all records (click on the number 80 of the top right corner to show more records per page if you need it). Once all of them are selected, click on More button and afterwars on Export. Select the column product_code and name and afterwards proceed. Save the generated CSV file as Products.csv, for example. Open it, you'll see all the XML ID of the exported products (if they hadn't XML ID, after the exportation they'll do -an exportation generates XML ID for each exported record if it doesn't have anyone-). Now, I guess the customer has given you something like a file with columns Name of the order line, Product code, so replace the Product code column values with the respective XML IDs of the products you have just exported. So in the end youu should have one file to import, OrderLine.csv, with id, name and products/id columns.
Case 3: there are some product codes belonging to existing products stored in the database and there are some ones which still don't exist
In this case you will have to combine both cases 1 and 2, first, export the products as described in case 2, and then, create a new one with the products whose code doesn't exist yet, as described in case 1. Then replace the product codes the customer gave to you with the respective ones as described in case 2.
Note: this process will give you a lot of time if you have thousands of records to import and you replace them manually. In this case it is mandatory to create a macro in your CSV editor which does the replacements (with search and replace). For example, with LibreOffice you can do macros with Python.
Example (Case 3)
The customer has given you a file of order lines, with two lines:
Name: OL A, Product Code: AAA
Name: OL B, Product Code: BBB
You export products from Odoo interface and you get a file with one
line:
id,name,product_code
__export__.products_a,"Product A","AAA"
You look for the coincidences of the product codes in both files, and
do the replacements in a copy of the customer file, so now you have
this:
Name: OL A, Product Code: __export__.products_a
Name: OL B, Product Code: BBB
Then you create a new CSV Products.csv and put in there the products
whose product code don't exist yet:
id,name,product_code
__import__.products_b,"Product B","BBB"
Now apply the replacements again comparing this new file with the one
we had, and you will get this:
Name: OL A, Product Code: __export__.products_a
Name: OL B, Product Code: __import__.products_b
Convert this file to a right CSV format for Odoo, and save it as
OrderLine.csv:
id,name,products/id
__import__.order_line_1,"OL A",__export__.products_a
__import__.order_line_2,"OL B",__import__.products_b
And finally, import the files, and take into account: import
Products.csv before OrderLine.csv.
EDIT
I think it should be better to waste a bit of time in programming a macro for your CSV editor (Excel, LibreOffice, Open Office or whatever), but if you're desperated and you need to do this only through Odoo, I came up with an awful workaround, but at least, it should work too.
1.Create a new Char field named product_code in order_line model (it would be there temporaly).
2.Modify the ORM create method of this model:
#api.model
def create(self, vals):
product_id = False
product_code = vals.get('product_code', False)
if product_code:
product = self.env['products'].search([
('product_code', '=', product_code)
])
if product:
product_id = product[0].id
vals.update({
'products': product_id,
})
return super(OrderLine, self).create(vals)
3.Copy the file which the customer's sent you, rename the headers properly, and rename the column order/products/product_code as product_code. Import the CSV file. Each importation of records will call the ORM create method of order_line model.
After the importation you'll have in the database the order lines rightly related to the products.
When you've finished you'll have to remember to remove the code you've added (and also remove the column product_code from order_line model in the database, in order to remove junk).
Solution 1
You can create a transient model with the fields that you are using in the CSV. And applying the idea of #forvas:
class ImportOrderLines(models.TransientModel):
_name = 'import.order.lines'
product_code = Char()
#api.model
def create(self, vals):
product_id = False
product_code = vals.get('product_code', False)
if product_code:
product = self.env['products'].search([
('product_code', '=', product_code)
])
if product:
product_id = product[0].id
self.env['order_line'].create({
'products': product_id,
})
return False # you don't need to create the record in the transient model
You can go to the list view of this transient model and import like in any other model, with the base_import view.
Solution 2
You could create a wizard in order to import the CSV to create the Order Lines.
Check the following source code. You must assing the method import_order_lines to a button in the wizard.
import base64
import magic
import csv
from cStringIO import StringIO
import codecs
from openerp import models, fields, api, _
from openerp.exceptions import Warning
class ImportDefaultCodeWizard(models.TransientModel):
_name = 'import.default_code.wizard'
name = fields.Char(
string='File name',
)
file = fields.Binary(
string='ZIP file to import to Odoo',
required=True,
)
#api.multi
def import_order_lines(self):
self.ensure_one()
content = base64.decodestring(self.file)
if codecs.BOM_UTF8 == content[:3]: # remove "byte order mark" (windows)
content = content[3:]
file_type = magic.from_buffer(content, mime=True)
if file_type == 'text/plain':
self._generate_order_line_from_csv(content)
return self._show_result_wizard()
raise Warning(
_('WRONG FILETYPE'),
_('You should send a CSV file')
)
def _show_result_wizard(self):
return {
'type': 'ir.actions.act_window',
'res_model': self._name,
'view_type': 'form',
'view_mode': 'form',
'target': 'new',
'context': self.env.context,
}
def _generate_order_line_from_csv(self, data):
try:
reader = csv.DictReader(StringIO(data))
except Exception:
raise Warning(
_('ERROR getting data from csv file'
'\nThere was some error trying to get the data from the csv file.'
'\nMake sure you are using the right format.'))
n = 1
for row in reader:
n += 1
self._validate_data(n, row)
default_code = row.get('default_code', False)
order_line = {
'default_code': self._get_product_id(default_code),
# here you should add all the order line fields
}
try:
self.env['order_line'].create(order_line)
except Exception:
raise Warning(
_('The order line could not be created.'
'\nROW: %s') % n
)
def _validate_data(self, n, row):
csv_fields = [
'default_code',
]
""" here is where you should add the CSV fields in order to validate them
customer/account_number, customer/first_name, customer/last_name,
customer/account_type, order/transaction_id, order/products/product_code ,order/quantity, order/customer_id/id
"""
for key in row:
if key not in csv_fields:
raise Warning(_('ERROR\nThe file format is not right.'
'\nCheck the column names and the CSV format'
'\nKEY: %s' % key))
if row.get('default_code', False) == '':
raise Warning(
_('ERROR Validating data'),
_('The product code should be filled.'
'\nROW: %s') % n
)
def _get_product_id(self, default_code):
if partner_id:
product_obj = self.env['product.product'].search([
('default_code', '=', default_code),
])
if len(product_code_obj) == 1:
return product_obj.default_code
else:
raise Warning(
_('ERROR Validating data'),
_('The product code should be filled.'
'\nROW: %s') % n
)
return False
You can search by product_code like so:
#api.model
def search_by_code(self, code):
result = self.env['products'].search([('product_code', '=', code)])
I have a CSV file of data in the form
21.06.2016 23:00:00.349, 153.461, 153.427
21.06.2016 23:00:00.400, 153.460, 153.423
etc
The initial step of creating a frame involves the optional inclusion of a 'schema' to specify or rename column heads and specify types:
let df = Frame.ReadCsv(__SOURCE_DIRECTORY__ + "/data/GBPJPY.csv", hasHeaders=true, inferTypes=false, schema="TS (DateTimeOffset), Bid (float(3)), Ask (float(3))")
I would like to specify the first column of string values to be ParseExact'ed to DateTimeOffset of the format
"dd.mm.yyyy HH:mm:ss.fff"
(I'm assuming the use of the setting System.Globalization.CultureInfo.InvariantCulture).
How do I express the schema such that it will parse the datetime string in that first Frame.ReadCsv("file.csv", schema = ........ )? Or is this not possible to accomplish within the schema statement?
I am using Dell Boomi to map data from one system to another. I can use groovy in the maps but have no experience with it. I tried to do this with the other Boomi tools, but have been told that I'll need to use groovy in a script. My inbound data is:
132265,Brown
132265,Gold
132265,Gray
132265,Green
I would like to output:
132265,"Brown,Gold,Gray,Green"
Hopefully this makes sense! Any ideas on the groovy code to make this work?
It can be elegantly solved with groupBy and the spread operator:
#Grapes(
#Grab(group='org.apache.commons', module='commons-csv', version='1.2')
)
import org.apache.commons.csv.*
def csv = '''
132265,Brown
132265,Gold
132265,Gray
132265,Green
'''
def parsed = CSVParser.parse(csv, CSVFormat.DEFAULT.withHeader('code', 'color')
parsed.records.groupBy({ it.code }).each { k,v -> println "$k,\"${v*.color.join(',')}\"" }
The above prints:
132265,"Brown,Gold,Gray,Green"
Well, I don't know how are you getting your data, but here is a general way to achieve your goal. You can use a library, such as the one bellow to parse the csv.
https://github.com/xlson/groovycsv
The example for your data would be:
#Grab('com.xlson.groovycsv:groovycsv:1.1')
import static com.xlson.groovycsv.CsvParser.parseCsv
def csv = '''
132265,Brown
132265,Gold
132265,Gray
132265,Green
'''
def data = parseCsv(csv)
I believe you want to associate the number with various values of colors. So for each line you can create a map of the number and the colors associated with that number, splitting the line by ",":
map = [:]
for(line in data) {
number = line.split(',')[0]
colour = line.split(',')[1]
if(!map[number])
map[number] = []
map[number].add(colour)
}
println map
So map should contain:
[132265:["Brown","Gold","Gray","Green"]]
Well, if it is not what you want, you can extract the general idea.
Assuming your data is coming in as a comma separated string of data like this:
"132265,Brown 132265,Gold 132265,Gray 132265,Green 122222,Red 122222,White"
The following Groovy script code should do the trick.
def csvString = "132265,Brown 132265,Gold 132265,Gray 132265,Green 122222,Red 122222,White"
LinkedHashMap.metaClass.multiPut << { key, value ->
delegate[key] = delegate[key] ?: []; delegate[key] += value
}
def map = [:]
def csv = csvString.split().collect{ entry -> entry.split(",") }
csv.each{ entry -> map.multiPut(entry[0], entry[1]) }
def result = map.collect{ k, v -> k + ',"' + v.join(",") + '"'}.join("\n")
println result
Would print:
132265,"Brown,Gold,Gray,Green"
122222,"Red,White"
Do you HAVE to use scripting for some reason? This can be easily accomplished with out-of-the-box Boomi functionality.
Create a map function that prepends the ID field to a string of your choice (i.e. 222_concat_fields). Then use that value to set a dynamic process prop with that value.
The value of the process prop will contain the result of concatenating the name fields. Simply adding this function to your map should take care of it. Then use the final value to populate your result.
Well it depends upon the data how is it coming.
If the data which you have posted in the question is coming in a single document, then you can easily handle this in a map with groovy scripting.
If the data which you have posted in the question is coming into multiple documents i.e.
doc1: 132265,Brown
doc2: 132265,Gold
doc3: 132265,Gray
doc4: 132265,Green
In that case it cannot be handled into map. You will need to use Data Process Step with Custom Scripting.
For the code which you are asking to create in groovy depends upon the input profile in which you are getting the data. Please provide more information i.e. input profile, fields etc.
BACKGROUND:
I am having issues trying to search through some CSV files.
I've gone through the python documentation: http://docs.python.org/2/library/csv.html
about the csv.DictReader(csvfile, fieldnames=None, restkey=None, restval=None, dialect='excel', *args, **kwds) object of the csv module.
My understanding is that the csv.DictReader assumes the first line/row of the file are the fieldnames, however, my csv dictionary file simply starts with "key","value" and goes on for atleast 500,000 lines.
My program will ask the user for the title (thus the key) they are looking for, and present the value (which is the 2nd column) to the screen using the print function. My problem is how to use the csv.dictreader to search for a specific key, and print its value.
Sample Data:
Below is an example of the csv file and its contents...
"Mamer","285713:13"
"Champhol","461034:2"
"Station Palais","972811:0"
So if i want to find "Station Palais" (input), my output will be 972811:0. I am able to manipulate the string and create the overall program, I just need help with the csv.dictreader.I appreciate any assistance.
EDITED PART:
import csv
def main():
with open('anchor_summary2.csv', 'rb') as file_data:
list_of_stuff = []
reader = csv.DictReader(file_data, ("title", "value"))
for i in reader:
list_of_stuff.append(i)
print list_of_stuff
main()
The documentation you linked to provides half the answer:
class csv.DictReader(csvfile, fieldnames=None, restkey=None, restval=None, dialect='excel', *args, **kwds)
[...] maps the information read into a dict whose keys are given by the optional fieldnames parameter. If the fieldnames parameter is omitted, the values in the first row of the csvfile will be used as the fieldnames.
It would seem that if the fieldnames parameter is passed, the given file will not have its first record interpreted as headers (the parameter will be used instead).
# file_data is the text of the file, not the filename
reader = csv.DictReader(file_data, ("title", "value"))
for i in reader:
list_of_stuff.append(i)
which will (apparently; I've been having trouble with it) produce the following data structure:
[{"title": "Mamer", "value": "285713:13"},
{"title": "Champhol", "value": "461034:2"},
{"title": "Station Palais", "value": "972811:0"}]
which may need to be further massaged into a title-to-value mapping by something like this:
data = {}
for i in list_of_stuff:
data[i["title"]] = i["value"]
Now just use the keys and values of data to complete your task.
And here it is as a dictionary comprehension:
data = {row["title"]: row["value"] for row in csv.DictReader(file_data, ("title", "value"))}
The currently accepted answer is fine, but there's a slightly more direct way of getting at the data. The dict() constructor in Python can take any iterable.
In addition, your code might have issues on Python 3, because Python 3's csv module expects the file to be opened in text mode, not binary mode. You can make your code compatible with 2 and 3 by using io.open instead of open.
import csv
import io
with io.open('anchor_summary2.csv', 'r', newline='', encoding='utf-8') as f:
data = dict(csv.reader(f))
print(data['Champhol'])
As a warning, if your csv file has two rows with the same value in the first column, the later value will overwrite the earlier value. (This is also true of the other posted solution.)
If your program really is only supposed to print the result, there's really no reason to build a keyed dictionary.
import csv
import io
# Python 2/3 compat
try:
input = raw_input
except NameError:
pass
def main():
# Case-insensitive & leading/trailing whitespace insensitive
user_city = input('Enter a city: ').strip().lower()
with io.open('anchor_summary2.csv', 'r', newline='', encoding='utf-8') as f:
for city, value in csv.reader(f):
if user_city == city.lower():
print(value)
break
else:
print("City not found.")
if __name __ == '__main__':
main()
The advantage of this technique is that the csv isn't loaded into memory and the data is only iterated over once. I also added a little code the calls lower on both the keys to make the match case-insensitive. Another advantage is if the city the user requests is near the top of the file, it returns almost immediately and stops looking through the file.
With all that said, if searching performance is your primary consideration, you should consider storing the data in a database.