Run MS Flow on site in SharePoint 2016

The on-premesis data gateway does this, but it does require a few things:

  1. At least Flow P1 licensing
  2. The gateway must be part of the Active Directory forest.
  3. One or more gateways (you can have an active / active configuration) should be deployed on Windows servers. Let the gateway run under the account created by the gateway.
  4. When you create an action or trigger, add your credentials, but specify the gateway to use. Use the UPN or domain samAccountName format for all connections.

The gateway itself does not require open inbound ports, but does require outbound connectivity to connect to the cloud.

It should be noted that not all column types are supported with SharePoint Server 2016. For example, selection columns are not visible in flows. If you need data from a selection column, you need a standard SharePoint workflow to copy this data into a column text box for example.

Here are some official sources of information:

Install a local data gateway

Download the local data gateway

Spring Cloud Data Flow – Task – Pass a command line argument

I find it difficult to successfully complete a simple task in Spring Cloud Data Flow (SCDF). I just wanted to do that.

    @Override
    public void run(String... args) throws Exception {
        System.out.println(
                "Passed argument : " + args(0)
        );
    }

I am using the Docker Compose installation method for local testing. SCDF seems to overtake Mariadb as a driver. I'm not sure where to override these defaults.

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With SCDF, arguments can be passed on every run. I could pass the following argument to overwrite the Mariadb driver.

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However, the value is selected as a command line argument. I can't pass the command line argument !!

2020-04-02 03:08:32.557  INFO 115 --- (           main) c.v.cloudtask.CloudTaskApplication       : Started CloudTaskApplication in 2.719 seconds (JVM running for 3.267)
Passed argument : --spring.datasource.driverClassName=com.mysql.cj.jdbc.Driver
2020-04-02 03:08:32.595 DEBUG 115 --- (           main) o.s.c.t.r.support.SimpleTaskRepository  

Question:
1) How can I force the MySQL driver to be used and not use Mariadb?
2) How are command line arguments passed?

Data flow diagram for patient information system for a hospital

I have an example of a DFD for a patient information system implemented in a particular hospital. The following illustration shows the level 0 diagram (if we consider that the first level is the context diagram, then the second level is the level 0 diagram and so on).

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In this system, patients can search and make appointments. My problem is related to the flow of data that is labeled with the patient name that the process directs to make appointments for the database patients. I don't understand why we have such data in our system. In other words, in which scenario does the process appointment send the patient name to the patient database? The process already sends the patient name. Maintain patient information!

Machine learning – ML text generation code with Python and tensor flow

I wanted a simple code review for improvement to increase the efficiency of my text generation model. This model comes from the official TensorFlow website, but is trained on various data sets. I use the GPU version of TensorFlow 2.0 (Beta1) and Keras.

I trained this on a Harry Potter book, but I found that the issue wasn't the best, even though I had been training it for a few hours (when the loss stabilized at around 0.0565). Here is the code: –

import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import Dropout
from keras.callbacks import ModelCheckpoint
from keras.layers import LSTM
from keras.utils import np_utils
import os

text = open ("/home/awesome_ruler/Documents/Atom projects/HarryPotter/hp.txt").read()
vocab = sorted(set(text))

# Creating a mapping from unique characters to indices
char2idx = {u:i for i, u in enumerate(vocab)}
idx2char = np.array(vocab)

text_as_int = np.array((char2idx(c) for c in text))

# The maximum length sentence we want for a single input in characters
seq_length = 200
examples_per_epoch = len(text)//(seq_length+1)

# Create training examples / targets
char_dataset = tf.data.Dataset.from_tensor_slices(text_as_int)

sequences = char_dataset.batch(seq_length+1, drop_remainder=True)

def split_input_target(chunk):
    input_text = chunk(:-1)
    target_text = chunk(1:)
    return input_text, target_text

dataset = sequences.map(split_input_target)

# Batch size
BATCH_SIZE = 64 # DEfault is 64

# Buffer size to shuffle the dataset
# (TF data is designed to work with possibly infinite sequences,
# so it doesn't attempt to shuffle the entire sequence in memory. Instead,
# it maintains a buffer in which it shuffles elements).
BUFFER_SIZE = 10000

dataset = dataset.shuffle(BUFFER_SIZE).batch(BATCH_SIZE, drop_remainder=True)

# Length of the vocabulary in chars
vocab_size = len(vocab)

# The embedding dimension
embedding_dim = 256

# Number of RNN units
rnn_units = 960 # 32 multiple

def build_model(vocab_size, embedding_dim, rnn_units, batch_size):
  model = tf.keras.Sequential((
    tf.keras.layers.Embedding(vocab_size, embedding_dim,
                              batch_input_shape=(batch_size, None)),
    tf.keras.layers.LSTM(rnn_units,
                        return_sequences=True,
                        stateful=True,
                        recurrent_initializer='glorot_uniform'),
    tf.keras.layers.Dropout(0.5),
    tf.keras.layers.Dense(vocab_size)
  ))
  return model

model = build_model(
  vocab_size = len(vocab),
  embedding_dim=embedding_dim,
  rnn_units=rnn_units,
  batch_size=BATCH_SIZE)

def loss(labels, logits):
  return tf.keras.losses.sparse_categorical_crossentropy(labels, logits, from_logits=True)

model.compile(optimizer='Adam', loss=loss)

# Directory where the checkpoints will be saved
checkpoint_dir = '/home/awesome_ruler/Documents/Atom projects/HarryPotter/CheckPoints'

checkpoint_prefix = os.path.join(checkpoint_dir, "ckpt_{epoch}")

checkpoint_callback=tf.keras.callbacks.ModelCheckpoint(
    filepath=checkpoint_prefix,
    save_weights_only=True)


EPOCHS=350
history = model.fit(dataset, epochs=EPOCHS, callbacks=(checkpoint_callback)) # Comment to evaluate the model

checkpoint_dir = 'CheckPoints/ckpt_380'

model = build_model(vocab_size, embedding_dim, rnn_units, batch_size=1)

model.load_weights(checkpoint_dir)

model.summary()

def generate_text(model, start_string):
  # Evaluation step (generating text using the learned model)

  # Number of characters to generate
  num_generate = 1000

  # Converting our start string to numbers (vectorizing)
  input_eval = (char2idx(s) for s in start_string)
  input_eval = tf.expand_dims(input_eval, 0)

  # Empty string to store our results
  text_generated = ()

  # Low temperatures results in more predictable text.
  # Higher temperatures results in more surprising text.
  # Experiment to find the best setting.
  temperature = 0.2

  # Here batch size == 1
  model.reset_states()
  for i in range(num_generate):
      predictions = model(input_eval)
      # remove the batch dimension
      predictions = tf.squeeze(predictions, 0)

      # using a categorical distribution to predict the character returned by the model
      predictions = predictions / temperature
      predicted_id = tf.random.categorical(predictions, num_samples=1)(-1,0).numpy()

      # We pass the predicted character as the next input to the model
      # along with the previous hidden state
      input_eval = tf.expand_dims((predicted_id), 0)

      text_generated.append(idx2char(predicted_id))

  return (start_string + ''.join(text_generated))

print(generate_text(model, start_string=u"homework"))

Since the original data set contained many more characters, I reduced the Rnn units and kept a multiple of 32. I also converted the GRU layer to LSTM because (theoretically) it has better storage capacity. Can anyone suggest other improvements? I would be very happy to know you

Windows – Samsung SideSync / Flow not compatible (S10 / Win7)

I recently upgraded from a Galaxy S7 to an S10e. Unfortunately, SideSync doesn't seem to be an option for the S10e.
No big deal as Samsung Flow offers the same ease of use (or as I thought …)
At that point, I realized that the Windows part of the program is only Windows 10+

I find it doubtful that I'll be able to get a working version of SideSync on my S10e (I've already tried a hosted APK but haven't noticed the version, to no avail)
or that I will somehow manage to sandbox a Windows 10 app for Windows 7

In view of this, does anyone know of any alternative app / program combinations?
The main goal is screen sharing (phone to PC)

(Sorry if this question is in the wrong place)

Microsoft Flow – How do I only see values ​​in a copy of a custom SharePoint list where the values ​​are the result of choosing options from a drop-down list?

Surroundings

Of the Site Contents Directory in SharePointI created one Custom List about New > App > Custom List.

I created my columns and added entries using the form associated with the list.

Some of the columns are of type Choice and configured to allow multiple selections.

For example:

Service Type:  
 - Groceries - Apples
 - Groceries - Oranges   
 - Groceries - General

(note: multiple options can be selected)    

Desired behavior

Copy a SharePoint list through a recurring Microsoft Flow based on this template from Microsoft into a CSV file.

Current behavior

The flow I created works.

However, when I open the CSV in Excel, where values ​​result from the selection of options from a drop-down list, the corresponding field contains 4 columns (and not just 1):

ServiceType
ServiceType@odata.type
ServiceType#Id  
ServiceType#Id@odata.type

with the corresponding values ​​of:


({"@odata.type":"#Microsoft.Azure.Connectors.SharePoint.SPListExpandedReference","Id":2,"Value":"Groceries - General"})



#Collection(Microsoft.Azure.Connectors.SharePoint.SPListExpandedReference)



(2) 



#Collection(Int64)

question

How can I make sure that:

  • Only one column is shown for each dropdown box
  • Only the values ​​are displayed and not all of the Microsoft markup text

Flow:

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Web Part – How do I use Flow to create a brand new Sharepoint news story?

I am very new to Sharepoint, Forms and Flow. I am trying to automate a workflow when sending a form response to create a Newspost page on Sharepoint with data from the form.

I want to designate the author of the page as the person who submitted the form.

The page title should also be taken from one of the answers. The rest of the answers can be in a text web part.

The key is automating all of this in Flow (or Power Automate). So far no success after many hours of research and testing. I only managed to collect data when a form was submitted.

Rotation transformation – Why the degree of rotation of the flow field differs from the angle specified by the "RotationMatrix" function

If I specify the angle of rotation as Pi / 2 in the rotation matrix function, the parameter equation Pi / 2 rotates:

ParametricPlot[{x, x^2}, {x, -3, 3}]
ParametricPlot[Evaluate[RotationMatrix[-Pi/2].{x, x^2}], {x, -3, 3}]

Why do I give the rotation angle of Pi / 2 in the rotation matrix function, but the flow field only rotates Pi / 4?

u[x_, y_, z_] := x
v[x_, y_, z_] := -y
StreamPlot[
 Evaluate[RotationTransform[-Pi/2][{u[x, y, z], v[x, y, z]}]], {x, -3,
   3}, {y, -3, 3}]