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django-reportato-1.0


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توضیحات

Very simple CSV reports with Django
ویژگی مقدار
سیستم عامل -
نام فایل django-reportato-1.0
نام django-reportato
نسخه کتابخانه 1.0
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Pablo Recio
ایمیل نویسنده pablo@potatolondon.com
آدرس صفحه اصلی https://github.com/potatolondon/reportato
آدرس اینترنتی https://pypi.org/project/django-reportato/
مجوز BSD
# Reportato [![build-status-image]][travis] The goal of Reportato is to provide a Django-ish approach to easily get CSV or Google Spreadsheet generated reports. This is still a very alpha version, and this documentation may lie. **Note:** Generating a report can take a long time if the table you're generating your report from is large. You might want to avoid forcing your users to experience this latency, e.g. by generating the report regularly on a cron and allowing them to download the most recent copy, or by fetching the report via AJAX so you can show your user pictures of kittens while they wait. ## Installation Reportato is [hosted on PyPI](https://pypi.python.org/pypi/django-reportato) so you can just install it using either: $ pip install django-reportato Or: $ easy_install django-reportato If you prefer to use the development version of it, you can clone the repository and build it manually: $ git clone https://github.com/potatolondon/reportato.git $ cd reportato $ python setup.py install ## Basic configuration With Reportato, the way you declare how your report should look is similar to Django's ModelForms: ```python #### reporters.py from reportato.reporters import ModelReporter from .models import Journalist class JournalistReporter(ModelReporter): class Meta: model = Journalist fields = ('first_name', 'last_name', 'email') custom_headers = { 'first_name': 'Different header' } def get_email_column(self, instance): return instance.email.replace('@', '< AT >') #### usage example >>> from journalists.models import Journalist >>> from journalists.reporters import JournalistReporter >>> reporter = JournalistReporter() # by default uses model.objects.all(), can use any queryset >>> reporter.get_header_row() [u'Different header', u'Last name', u'Email'] >>> [row for row in reporter.get_rows()] [ [u'Angelica', u'Edlund', u'angelicaedlund <AT> engadget.com'], [u'Arnold', u'Ofarrell', u'arnoldofarrell <AT> reddit.com'], # ... ] ``` ## Documentation ### Model Reporters To create a report for a given model, you just need to write a class that will inherit from `reportato.reporters.ModelReporter`, and indicate which model you want to report on. A very simple example: ```python from reportato.reporters import ModelReporter class MyReport(ModelReporter): class Meta: model = MyModel ``` By default this will generate reports with every field on `MyModel`. You can especify which fields to include by using the `fields` variable: ```python # ... class Meta: model = MyModel fields = ('field1', 'field2', 'field3') ``` The header row will be generated based on the model field's `verbose_name` value, or a simple capitalization of the field name if it doesn't have a `verbose_name`. If you want to override that, you can do it using `custom_headers`: ```python # ... class Meta: model = MyModel custom_headers { 'field1': 'Very cool header' } ``` The way reportato resolves each given field is very simple: * Checks if the reporter class has some method named `get_FIELDNAME_column(instance)`. If it does, uses it. Otherwise: * Checks if the given `FIELDNAME` is accessible directly through the instance. * Will raise a `reportato.reporters.UndefinedField` exception if neither of those are defined. What this means is that you can define whatever you want in your report as a field while you have the proper `get_FIELDNAME_column` method. And also will be able to use model's fields, decorators or even aggregated fields. As an example: ```python # ... def get_field1_column(self, instance): return instance.field1.replace('_', '-') ``` To create the report, you need to instantiate the object using a list of objects or a queryset. If you do not pass one, it will take all the objects for the given model: ```python >>> MyReport() # report with MyModel.objects.all() >>> MyReport(MyModel.objects.filter(something=something_else)) ``` Additionally, you can define what fields you want to see on your report during creation time using the `visible_fields` parameter: >>> MyReport(visible_fields=['first_name', 'last_name']) This way your reporter will only show those fields, even if you had more on your Reporter definition. This allows you to build custom logic if the final user wants to customise what columns he/she wants to see each time. Other methods: #### `get_header_row()` Returns an ordered list with the CSV headers #### `get_row(instance)` Returns a sorted dict with the value of each field for the given `instance` #### `get_rows()` Returns an iterable with an ordered list of the values for the given fields. ### reportato.views.BaseCSVGeneratorView Are you a CBV fan? It's your lucky day, because `reportato` provides a base view from which you can inherit for building your own stuff. `BaseCSVGeneratorView` inherits from Django's `django.views.generic.ListView` meaning that it needs a model or a queryset to work with. Internally, `BaseCSVGeneratorView` will use `get_queryset()` method to resolve the list of objects to report with. #### `reporter_class` Class attribute to define the class of the reporter you are going to use on this view. Should inherit from `ModelReporter`. If you need to decide what reporter to use in execution time, override `get_reporter_class()` method instead. #### `writer_class` Class attribute to define the CSV writer class. By default uses `UnicodeWriter`, as implemented on Python documentation. #### `WRITE_HEADER` Flag to determine whether to include the headers in the report or not. ### `file_name` Class attribute to define the file name for the generated report. If you want something more dynamic, you should override `get_file_name()` method. ### `write_csv()` Method that receiving an input flow (`HttpResponse`, `io.BytesIO`...) uses reporter's method to write into such flow. ## Further examples ### Report as a Google Sheet The initial plan was to add some features to automatically create spreadsheets from given reports. However, I changed my mind during implementation because it made certain assumptions about how the tool needed to implement OAuth and felt that it was overkill. Instead, I'm providing some examples of how to do it using this library. The basic undersanding is that we need to dump the CSV file into a `BytesIO` and upload it to Google Drive using `google-api-python-client`. ```python import io # google apiclient dependencies import httplib2 from apiclient.discovery import build from apiclient.http import MediaIoBaseUpload from reporters.views import BaseCSVGeneratorView from .models import MyModel from .reports import MyReport class MyReportToSpreadsheet(BaseCSVGeneratorView): model = MyModel reporter_class = MyReport def get(self, request, *args, **kwargs): outfile = io.BytesIO() self.write_csv(outfile) # now outfile is filled with the CSV we want. # we need to fetch the user credentials using OAuth, not covering it here credentials = request.user.oauth_credentials http = credentials.authorize(httplib2.Http()) service = build( serviceName='drive', version='v2', developerKey=settings.GOOGLE_API_KEY, http=http ) media_body = MediaIoBaseUpload( outfile, mimetype='text/csv', resumable=False ) body = { "title": title, "description": description, "mimeType": 'text/csv' } uploaded_file = service.files().insert( body=body, media_body=media_body, convert=True # to convert CSV's to Spreadsheet ).execute() return HttpResponseRedirect(uploaded_file['alternateLink']) ``` ## Running tests Running reportato tests is dead simple. First, you need a `virtualenv`. I highly recommend to use [`virtualenvrapper`](http://virtualenvwrapper.readthedocs.org/en/latest/) for it. Having it installed, you'll just need to: $ mkvirtualenv reportato # will create the virtualenv $ workon reportato # will activate the virtualenv # deactivate # will deactivate it In order to run the tests we need `Django` and `Mock`: $ pip install Django Mock Once those dependencies are installed, you can run the tests simply with: $ python runtests.py ## Future plans * Add custom columns that aren't part of a model for adding aggregates * Make some sort of Mixin for making the upload to Google Sheets easier * Use `values_list` instead of composing the models for trying to be more efficient * Provide helpers for deferring the report generation to GAE task queues [build-status-image]: https://secure.travis-ci.org/potatolondon/reportato.png?branch=master [travis]: http://travis-ci.org/potatolondon/reportato?branch=master


نحوه نصب


نصب پکیج whl django-reportato-1.0:

    pip install django-reportato-1.0.whl


نصب پکیج tar.gz django-reportato-1.0:

    pip install django-reportato-1.0.tar.gz