CSV – blog.fossasia.org

Open Event Server – Export Speakers as CSV File

Post author:mayank8318
Post published:August 20, 2018
Post category:API Community Event Event Management FOSSASIA Open Event
Post comments:0 Comments

FOSSASIA‘s Open Event Server is the REST API backend for the event management platform, Open Event. Here, the event organizers can create their events, add tickets for it and manage all aspects from the schedule to the speakers. Also, once he/she makes his event public, others can view it and buy tickets if interested.

The organizer can see all the speakers in a very detailed view in the event management dashboard. He can see the statuses of all the speakers. The possible statuses are pending, accepted and rejected. He/she can take actions such as editing/viewing speakers.

If the organizer wants to download the list of all the speakers as a CSV file, he or she can do it very easily by simply clicking on the Export As CSV button in the top right-hand corner.

Let us see how this is done on the server.

Server side – generating the Speakers CSV file

Here we will be using the csv package provided by python for writing the csv file.

import csv

We define a method export_speakers_csv which takes the speakers to be exported as a CSV file as the argument.
Next, we define the headers of the CSV file. It is the first row of the CSV file.

def export_speakers_csv(speakers):
   headers = ['Speaker Name', 'Speaker Email', 'Speaker Session(s)',
              'Speaker Mobile', 'Speaker Bio', 'Speaker Organisation', 'Speaker Position']

A list is defined called rows. This contains the rows of the CSV file. As mentioned earlier, headers is the first row.

rows = [headers]

We iterate over each speaker in speakers and form a row for that speaker by separating the values of each of the columns by a comma. Here, every row is one speaker.
As a speaker can contain multiple sessions we iterate over each session for that particular speaker and append each session to a string. ‘;’ is used as a delimiter. This string is then added to the row. We also include the state of the session – accepted, rejected, confirmed.
The newly formed row is added to the rows list.

for speaker in speakers:
   column = [speaker.name if speaker.name else '', speaker.email if speaker.email else '']
   if speaker.sessions:
       session_details = ''
       for session in speaker.sessions:
           if not session.deleted_at:
               session_details += session.title + ' (' + session.state + '); '
       column.append(session_details[:-2])
   else:
       column.append('')
   column.append(speaker.mobile if speaker.mobile else '')
   column.append(speaker.short_biography if speaker.short_biography else '')
   column.append(speaker.organisation if speaker.organisation else '')
   column.append(speaker.position if speaker.position else '')
   rows.append(column)

rows contains the contents of the CSV file and hence it is returned.

return rows

We iterate over each item of rows and write it to the CSV file using the methods provided by the csv package.

with open(file_path, "w") as temp_file:
   writer = csv.writer(temp_file)
   from app.api.helpers.csv_jobs_util import export_speakers_csv
   content = export_speakers_csv(speakers)
   for row in content:
       writer.writerow(row)

Obtaining the Speakers CSV file:

Firstly, we have an API endpoint which starts the task on the server.

GET - /v1/events/{event_identifier}/export/speakers/csv

Here, event_identifier is the unique ID of the event. This endpoint starts a celery task on the server to export the speakers of the event as a CSV file. It returns the URL of the task to get the status of the export task. A sample response is as follows:

{
  "task_url": "/v1/tasks/b7ca7088-876e-4c29-a0ee-b8029a64849a"
}

The user can go to the above-returned URL and check the status of his/her Celery task. If the task completed successfully he/she will get the download URL. The endpoint to check the status of the task is:

and the corresponding response from the server –

{
  "result": {
    "download_url": "/v1/events/1/exports/http://localhost/static/media/exports/1/zip/OGpMM0w2RH/event1.zip"
  },
  "state": "SUCCESS"
}

The file can be downloaded from the above-mentioned URL.

Resources

Open Event Server – Export Sessions as CSV File

Post author:mayank8318
Post published:August 20, 2018
Post category:API Community Event Event Management FOSSASIA GSoC Open Event
Post comments:0 Comments

FOSSASIA‘s Open Event Server is the REST API backend for the event management platform, Open Event. Here, the event organizers can create their events, add tickets for it and manage all aspects from the schedule to the speakers. Also, once he/she makes his event public, others can view it and buy tickets if interested.

The organizer can see all the sessions in a very detailed view in the event management dashboard. He can see the statuses of all the sessions. The possible statuses are pending, accepted, confirmed and rejected. He/she can take actions such as accepting/rejecting the sessions.

If the organizer wants to download the list of all the sessions as a CSV file, he or she can do it very easily by simply clicking on the Export As CSV button in the top right-hand corner.

Let us see how this is done on the server.

Server side – generating the Sessions CSV file

Here we will be using the csv package provided by python for writing the csv file.

import csv

We define a method export_sessions_csv which takes the sessions to be exported as a CSV file as the argument.
Next, we define the headers of the CSV file. It is the first row of the CSV file.

def export_sessions_csv(sessions):
   headers = ['Session Title', 'Session Speakers',
              'Session Track', 'Session Abstract', 'Created At', 'Email Sent']

A list is defined called rows. This contains the rows of the CSV file. As mentioned earlier, headers is the first row.

rows = [headers]

We iterate over each session in sessions and form a row for that session by separating the values of each of the columns by a comma. Here, every row is one session.
As a session can contain multiple speakers we iterate over each speaker for that particular session and append each speaker to a string. ‘;’ is used as a delimiter. This string is then added to the row.
The newly formed row is added to the rows list.

for session in sessions:
   if not session.deleted_at:
       column = [session.title + ' (' + session.state + ')' if session.title else '']
       if session.speakers:
           in_session = ''
           for speaker in session.speakers:
               if speaker.name:
                   in_session += (speaker.name + '; ')
           column.append(in_session[:-2])
       else:
           column.append('')
       column.append(session.track.name if session.track and session.track.name else '')
       column.append(strip_tags(session.short_abstract) if session.short_abstract else '')
       column.append(session.created_at if session.created_at else '')
       column.append('Yes' if session.is_mail_sent else 'No')
       rows.append(column)

rows contains the contents of the CSV file and hence it is returned.

return rows

We iterate over each item of rows and write it to the CSV file using the methods provided by the csv package.

writer = csv.writer(temp_file)
from app.api.helpers.csv_jobs_util import export_sessions_csv
content = export_sessions_csv(sessions)
for row in content:
   writer.writerow(row)

Obtaining the Sessions CSV file:

Firstly, we have an API endpoint which starts the task on the server.

GET - /v1/events/{event_identifier}/export/sessions/csv

Here, event_identifier is the unique ID of the event. This endpoint starts a celery task on the server to export the sessions of the event as a CSV file. It returns the URL of the task to get the status of the export task. A sample response is as follows:

{
  "task_url": "/v1/tasks/b7ca7088-876e-4c29-a0ee-b8029a64849a"
}

The user can go to the above-returned URL and check the status of his/her Celery task. If the task completed successfully he/she will get the download URL. The endpoint to check the status of the task is:

and the corresponding response from the server –

{
  "result": {
    "download_url": "/v1/events/1/exports/http://localhost/static/media/exports/1/zip/OGpMM0w2RH/event1.zip"
  },
  "state": "SUCCESS"
}

The file can be downloaded from the above-mentioned URL.

Resources

Open Event Server – Export Attendees as CSV File

Post author:mayank8318
Post published:July 31, 2018
Post category:API Community Event Event Management FOSSASIA GSoC Open Event
Post comments:0 Comments

FOSSASIA‘s Open Event Server is the REST API backend for the event management platform, Open Event. Here, the event organizers can create their events, add tickets for it and manage all aspects from the schedule to the speakers. Also, once he/she makes his event public, others can view it and buy tickets if interested.

The organizer can see all the attendees in a very detailed view in the event management dashboard. He can see the statuses of all the attendees. The possible statuses are completed, placed, pending, expired and canceled, checked in and not checked in. He/she can take actions such as checking in the attendee.

If the organizer wants to download the list of all the attendees as a CSV file, he or she can do it very easily by simply clicking on the Export As and then on CSV.

Let us see how this is done on the server.

Server side – generating the Attendees CSV file

Here we will be using the csv package provided by python for writing the csv file.

import csv

We define a method export_attendees_csv which takes the attendees to be exported as a CSV file as the argument.
Next, we define the headers of the CSV file. It is the first row of the CSV file.

def export_attendees_csv(attendees):
   headers = ['Order#', 'Order Date', 'Status', 'First Name', 'Last Name', 'Email',
              'Country', 'Payment Type', 'Ticket Name', 'Ticket Price', 'Ticket Type']

A list is defined called rows. This contains the rows of the CSV file. As mentioned earlier, headers is the first row.

rows = [headers]

We iterate over each attendee in attendees and form a row for that attendee by separating the values of each of the columns by a comma. Here, every row is one attendee.
The newly formed row is added to the rows list.

for attendee in attendees:
   column = [str(attendee.order.get_invoice_number()) if attendee.order else '-',
             str(attendee.order.created_at) if attendee.order and attendee.order.created_at else '-',
             str(attendee.order.status) if attendee.order and attendee.order.status else '-',
             str(attendee.firstname) if attendee.firstname else '',
             str(attendee.lastname) if attendee.lastname else '',
             str(attendee.email) if attendee.email else '',
             str(attendee.country) if attendee.country else '',
             str(attendee.order.payment_mode) if attendee.order and attendee.order.payment_mode else '',
             str(attendee.ticket.name) if attendee.ticket and attendee.ticket.name else '',
             str(attendee.ticket.price) if attendee.ticket and attendee.ticket.price else '0',
             str(attendee.ticket.type) if attendee.ticket and attendee.ticket.type else '']

   rows.append(column)

rows contains the contents of the CSV file and hence it is returned.

return rows

We iterate over each item of rows and write it to the CSV file using the methods provided by the csv package.

writer = csv.writer(temp_file)
from app.api.helpers.csv_jobs_util import export_attendees_csv
content = export_attendees_csv(attendees)
for row in content:
   writer.writerow(row)

Obtaining the Attendees CSV file:

Firstly, we have an API endpoint which starts the task on the server.

GET - /v1/events/{event_identifier}/export/attendees/csv

Here, event_identifier is the unique ID of the event. This endpoint starts a celery task on the server to export the attendees of the event as a CSV file. It returns the URL of the task to get the status of the export task. A sample response is as follows:

{
  "task_url": "/v1/tasks/b7ca7088-876e-4c29-a0ee-b8029a64849a"
}

The user can go to the above-returned URL and check the status of his/her Celery task. If the task completed successfully he/she will get the download URL. The endpoint to check the status of the task is:

and the corresponding response from the server –

{
  "result": {
    "download_url": "/v1/events/1/exports/http://localhost/static/media/exports/1/zip/OGpMM0w2RH/event1.zip"
  },
  "state": "SUCCESS"
}

The file can be downloaded from the above-mentioned URL.

References

Open Event Server – Export Orders as CSV File

Post author:mayank8318
Post published:July 31, 2018
Post category:API Community Event Event Management FOSSASIA GSoC Open Event
Post comments:0 Comments

FOSSASIA‘s Open Event Server is the REST API backend for the event management platform, Open Event. Here, the event organizers can create their events, add tickets for it and manage all aspects from the schedule to the speakers. Also, once he/she makes his event public, others can view it and buy tickets if interested.

The organizer can see all the orders in a very detailed view in the event management dashboard. He can see the statuses of all the orders. The possible statuses are completed, placed, pending, expired and canceled.

If the organizer wants to download the list of all the orders as a CSV file, he or she can do it very easily by simply clicking on the Export As and then on CSV.

Let us see how this is done on the server.

Server side – generating the Orders CSV file

Here we will be using the csv package provided by python for writing the csv file.

import csv

We define a method export_orders_csv which takes the orders to be exported as a CSV file as the argument.
Next, we define the headers of the CSV file. It is the first row of the CSV file.

def export_orders_csv(orders):
   headers = ['Order#', 'Order Date', 'Status', 'Payment Type', 'Total Amount', 'Quantity',
              'Discount Code', 'First Name', 'Last Name', 'Email']

A list is defined called rows. This contains the rows of the CSV file. As mentioned earlier, headers is the first row.

rows = [headers]

We iterate over each order in orders and form a row for that order by separating the values of each of the columns by a comma. Here, every row is one order.
The newly formed row is added to the rows list.

for order in orders:
   if order.status != "deleted":
       column = [str(order.get_invoice_number()), str(order.created_at) if order.created_at else '',
                 str(order.status) if order.status else '', str(order.paid_via) if order.paid_via else '',
                 str(order.amount) if order.amount else '', str(order.get_tickets_count()),
                 str(order.discount_code.code) if order.discount_code else '',
                 str(order.user.first_name)
                 if order.user and order.user.first_name else '',
                 str(order.user.last_name)
                 if order.user and order.user.last_name else '',
                 str(order.user.email) if order.user and order.user.email else '']
       rows.append(column)

rows contains the contents of the CSV file and hence it is returned.

return rows

We iterate over each item of rows and write it to the CSV file using the methods provided by the csv package.

writer = csv.writer(temp_file)
from app.api.helpers.csv_jobs_util import export_orders_csv
content = export_orders_csv(orders)
for row in content:
   writer.writerow(row)

Obtaining the Orders CSV file:

Firstly, we have an API endpoint which starts the task on the server.

GET - /v1/events/{event_identifier}/export/orders/csv

Here, event_identifier is the unique ID of the event. This endpoint starts a celery task on the server to export the orders of the event as a CSV file. It returns the URL of the task to get the status of the export task. A sample response is as follows:

{
  "task_url": "/v1/tasks/b7ca7088-876e-4c29-a0ee-b8029a64849a"
}</span

The user can go to the above-returned URL and check the status of his/her Celery task. If the task completed successfully he/she will get the download URL. The endpoint to check the status of the task is:

and the corresponding response from the server –

{
  "result": {
    "download_url": "/v1/events/1/exports/http://localhost/static/media/exports/1/zip/OGpMM0w2RH/event1.zip"
  },
  "state": "SUCCESS"
}

The file can be downloaded from the aabove-mentionedURL.

References

Saving Sensor Data in CSV format

Post author:CloudyPadmal
Post published:July 20, 2018
Post category:GSoC Pocket Science Lab
Post comments:0 Comments

PSLab Android app by FOSSASIA provides a variety of features to its users. One of them is accessing various types of sensors both built into mobile phone and external sensors connected with PSLab device. In earlier versions users were only able to view the captured data. Moving forward, adding improvements to the app, now there is a feature to save those data displayed in graphs in csv format.

This feature is important in many ways. One is educational. In a classroom, teachers can ask students to perform an experiment and prepare a report using the data collected. By just visualizing they cannot do this. Actual data points must be made available. Another use is sharing data sets related to say environmental data over different demographics.

CSV, or comma-separated values file is a text file where stored data are separated by commas. The file stores these tabular data (numbers and text) in plain text format. Each line of the file represents a data record. Each data record consists of one or more fields, separated by commas. CSV files are commonly used to store sensor data because of its easy use. This post is about how PSLab device uses CSV file to write sensor data in it.

In PSLab android source code, there is a dedicated class to handle read sensor data from different instruments called “CSVLogger”. Developers can easily instantiate this class wherever they want a data logging as follows;

CSVLogger logger = new CSVLogger(<SUBFOLDER>); 
logger .writeCSVFile("Heading1,Heading2,Heading3\n");

This will create a blank folder in “PSLab” folder in device storage. The CSV file is generated with the following convention according to the date and time where data is saved in the file.

yyyymmdd-hhmmss.csv

A sample file would have a name like 20180710-07:30:28.csv inside the SUBFOLDER which is specific to each instrument. Folder name will be the one used when initiating the CSVLogger.

With this method, logging data is pretty easy. Simply create a string which is a comma seperated and ended with a new line character. Then simply call the writeCSVFile(data) method with the string as a parameter added to it. It will keep appending string data until a new file is created. File creation can be handled by developers at their own interests and preferences.

String data = String.valueOf(System.currentTimeMillis()) + "," + item.getX() + "," + item.getY() + "\n";
logger.writeCSVFile(data);

To bring out an example let’s view how it’s implemented in Lux Meter instrument. This is a good source one can refer to when adding this feature in fragments

inside a main activity. In Lux Meter, there is the parent activity named Lux Meter and inside that there are two fragments, one is fragmentdata and the other one is fragmentsettings. Data capturing and saving occurs inside fragmentdata.

Menu icon controlling happens in the parent activity and we have bound a variable across the main activity and child fragment as follows;

LuxMeterActivity parent = (LuxMeterActivity) getActivity();
if (parent.saveData) {/* Save Data */}

This makes it easier listening menu icon clicks and start/stop recording accordingly. How to handle menu icons is beyond the scope of this blog and you can find tutorials on how to do that in the Resources section at the bottom of this blog post.

Once these CSV files are available, users can easily integrate them with advanced software like Matlab or Octave to do further analysis and processing to captured data sets.

Resources: