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{% comment %} Confirmation modal for deleting an Article. Takes no data related to a specific article via Django context. Instead, the following details must be filled in by JavaScript before the modal is shown: "p.article-title" -- Insert the Article's `title` into this tag. "input[name=article_id]" -- Set this input's value to the Article's `id` . Controls for this modal are standardized. To create a link or button to launch this modal, add the following classes and attributes to that link or button: - class ".ctl-article-delete" - attribute "data-article-id", with the ID of the article to be removed. - attribute "data-article-title", with the title of the article to be removed. Django context: modal_id -- [optional] The ID to be used for the modal window. If not set, defaults to "delete-confirmation-modal" NOTE: If {{ modal_id }} is set, you must also add a "data-target" attribute to the triggering link or button, with the modal ID included. {% endcomment %} {% with delete_modal_id=modal_id|default:"delete-confirmation-modal" %}
{% endwith delete_modal_id %}


Professional educator, music industry entrepreneur, small business owner
Knowledgeable in theory and practice of teaching and learning, curriculum creation, instructional design and delivery, learning development, e-learning, distance learning, technology integration
Experienced with children and adult learners from all walks of life
Passionate about empowering learners and sharing the gift of knowledge and love of learning.
Excited to continue to collaborate towards positive goals
Professional Experience
Adult Options in Education, Hopkins, MN (2007-2016)
Distance Learning Coordinator
Increased school revenue by capturing student hours outside classroom
Supervised staff implementation of distance learning in classrooms
Managed student enrollment, activity, progress, and stakeholder feedback via database, spreadsheets, document sharing
Empowered students via differentiated instruction and anytime-anywhere learning
Curriculum Integration Specialist
Collaborated with teachers in the evaluation, acquisition, and effective integration of technology in their instruction according to their goals
Presented on various topics including best practices in educational technology
Staff Technology Trainer
Trained staff in the use of technology in their classrooms and professional activities
Jewish Family and Children’s Services (via partnership with Adult Options)
Created curriculum and instructed students in Reading, Writing, Math, and Basic IT in order to prepare them for various training programs such as Coding and IT bootcamps
Minnesota Hennepin South Workforce Center (via partnership with Adult Options)
Empowered students through technology training to aid in their job search and professional lives
Sabathani Community Center Adult Education, Minneapolis (via partnership with Adult Options)
GED Coordinator/Lead Teacher empowering students to earn their GEDs
Hennepin County Adult Correctional Facility (via partnership with Adult Options)
Inmate students achieved lasting life-changing improvements in their reading and writing abilities
Connected with students in a meaningful way to move them in the direction of better choices
Empowered students through technology to see one possible path to turning their lives around
SERV-Safe Food Handler Certification Training (via Adult Options)
Taught students basic food handling with goal of safety and potential employment opportunites
English as a Second Language (at Adult Options)
Created curriculum and instructed students from over 80 countries speaking over 50 languages
Taught all levels of English acquisition as well as other subjects such as Math
Freelance Educator, Minneapols, MN (2004-2007)
Pre-K to Adult Teacher, Tutor, Trainer Minneapolis, St Louis Park, Hopkins, Richfield
From PreK Special Ed to troubled teens, all subjects including Music, Drama, Art, Technology
Every teacher should “sub” or “freelance” for a while: it is humbling and enlightening
49th Street Elementary, Los Angeles, CA (2000-2004)
Inner-city LosAngeles 5th grade all subjects
Created engaging curriculum and delivered meaningful, empowering instruction
My students achieved highest test score improvement of any of the 15 upper-grade classes
Connected with students; empowering and challenging them to become the best they can be
Leadership: Upper-Grades Chair, Safety, Home-Visit Outreach Committee, Arts Committee
Volunteered for students and the community on weekends and during vacation periods
Voluntarily created a program in which students received tutoring and athletic training and paticipated in volunteer activities such as sorting clothes at a homeless shelter
Voluntarily lead many activities with students and families: college tours, plays, ballets, operas, sporting events, book fairs, hiking trips; hosted LA Opera and others for student productions
Music Industry Entrepreneur (1990-present)
Big Toe and the Jam (bigtoeandthejam.com) (2009-present)
Co-own/manage perform “front-man” singing/ dancing/ crowd interactions for 9-piece variety cover-band specializing in casinos, weddings, festivals, bars, and corporate events
Marketing, promotion, record-keeping, planning, visioning, research, managing musicians and their subs, coordinating with buyers, video editing and production, sound editing and production
Founding member of Grammy-Award winning vocal band, The Blenders (way back in the 90s)
Album sales in the millions; TV, awards, extensive nationwide tours


Preparation time
less than 30 mins
Cooking time
1 to 2 hours
Serves
Serves 4
Dietary
Bring the enchanting flavours of the Middle East to a simple pot of lentils. Top with fresh herbs and a squeeze of lemon for a moreish meal.
Heat the oil in a large frying pan and add the onions. Cook over a low heat and allow the onions to soften, sweeten and turn gold. This may take about 20 minutes. Do not rush this part, it is important that the onions are sweet.
Set aside half the onions, turn up the heat and add the garlic, cumin and chilli. Stir and when you can really smell the garlic add the lentils and enough water to cover them by 5cm/2in.
Bring to the boil and then reduce to a simmer. Cover the pan and cook until the lentils soften. You may have to top up the water if the lentils look dry but don't add too much, you don’t want to drain away any delicious juices later.
Meanwhile, heat the grill to high. Grill the pepper quarters skin-side up until the skin is blistered and blackened then transfer to a resealable plastic bag. Set aside for 5-10 minutes, or until the skin has loosened from the pepper flesh. Once the peppers are cool enough to handle peel off the skins. Thinly slice the peppers and set aside.
Once the lentils are really soft, and this can take up to an hour, season with salt, pepper and lemon juice. Stir in the coriander leaves and garnish with the remaining sweet fried onions, grilled peppers and mint.
Serve with warm flatbreads and a dollop of Greek yoghurt.


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Do you have the Right Stuff?
Exploration
You will need to find stuff on Mars...
Is there
life on
MARS?


Problem 1. Odd or Even
Result:
Problem 2. Divisible by 7 and 5
Result:
Problem 3. Rectangle area
Result:
Problem 4. Third digit (right-to-left)
Result:
Problem 5. Third bit
Result:
Problem 6. Point in Circle
Result:
Problem 7. Is prime
Result:
Problem 8. Trapezoid area
Result:
Problem 9. Point in Circle and outside Rectangle
Result:


Fill the textarea to make it grow This textarea is going to grow when you fill it with text. Just type a few more words in it and you will see.


"To ‘activate’ a common form, for example adverse event, the form first asks ‘are there any serious or adverse events of interest to report?’ with yes and no radio buttons. When Yes is selected and saved the data point table appears"
I interpret this as a eCRF gatekeeping the additional eCRFs that are of a "Common" type. This has only one field - Yes or No. Our Sections don't do this as there is no field to state no. I assume the term Common is from Oracle or elsewhere. Also in the slideplayer examples the Yes/No were not on the same 'page' as the log items. Are these Visit or Subject log lists?
"A log form is used when multiple instances of the same form are needed; for example, concomitant medications or adverse events. The log form adds additional records or entries, as needed, to a single form. Each entry is a log line."
Here he switches to calling it a log form - note how this needs a Save on the log parent form not the child - this also lacks modularity you get on the Oracle system. It contains a Submit that can act on the association
To add additional log lines, the user clicks on ‘Add a new Log Line’. Instead of deleting log lines, the user can only inactivate the log line. When clicking inactivate, a drop down list of log numbers appears, with the user clicking the appropriate log number. Users can also reactivate inactivated log lines.
Its not an eCRD SO;


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AutoML Benchmark in Production
Comparison and Analysis of Different AutoML Systems in the Production Domain.
AutoML Systems are tools that propose to automate the machine learning (ML) pipeline:
integration, preparation, modeling and model deployment.
Although all AutoML systems aim to facilitate the usage of ML in production,
they may differ on how to accomplish this objective, approaching the ML pipeline in different levels.
The purpose of this benchmark is to, using currently available AutoML systems in the market,
evaluate how each system approaches the ML pipeline and help a user to choose which system to pick.
25 AutoML systems are presented in this benchmark, listed in chapter AutoML Systems.
For a more objective evaluation approach,
this research includes evaluations concerning different criteria of each system:
Requirements and Boundaries, Performance,
Data Integration, Data Preparation,
Modeling, Deployment and Results.
Ending the benchmark, chapter Practical Examples presents what systems are recommended to four exemplified users.
1. Introduction to AutoML in Production
In the pursuit of leveraging the potential of data, companies usually rely on Machine Learning (ML) technologies. Applications of ML range from detecting anomalies in the operation and non-specialized machines designed to learn by themselves, to the optimization of routing and demand forecasting. Its most common use cases are for knowledge extraction operations and as the core technology underlying the control of processes and products. Projects that rely on the application of ML are usually referred to as ML projects.
However, the development of an ML project is not an automated task - much of it still relies on the expertise of data scientists and knowledge of the manufacturing process. Seeking a solution to this problem, AutoML systems are currently being developed, enabling a wide range of users to benefit from the valuable potential of data and facilitating the use of ML in real-world problems.
In short, AutoML systems propose to automate the ML pipeline. Although this naming is useful to get a straightforward view of the main idea, it conceals several tasks, as depicted in Fig. 1.
2. Methodology of the AutoML Benchmark
This benchmark is divided into 3 steps: AutoML Systems, Evaluation and Usage.
-
AutoML Systems
This step lists AutoML Systems currently available in the market and specifies how deeply each one of them is evaluated in step Evaluation.
Evaluation
This step aims to evaluate the models generated by the systems listed in step AutoML Systems and compare them. Each of the benchmarked systems was analysed in 7 different criteria:
- Requirements and Boundaries
- Performance
- Data Integration
- Data Preparation
- Modeling
- Deployment
- Results
These criteria are spread out from chapters Characteristics Requirements and Boundaries to Results.
Usage
This step guides the user on how to use the information provided in step Evaluation to choose systems that fulfill the user's requirements.
The criteria can be divided into two groups: user-oriented and system-oriented criteria.
To visualize how personal information may affect the choice of system, take a look at Requirements and Boundaries, the user-oriented criteria. Here, the required user's programming skills, hardware, software, price budget and other metrics are presented.
To compare models, created by the systems, between themselves, the system-oriented criteria can be used. Spread out from chapters Characteristics Requirements and Boundaries to Results, information ranging from input datatypes to deployment methods is found and can be compared to the use case of interest to find a system that fits the best the user's needs.To demonstrate how the procedure of choosing a system would occur, four exemplified users are presented in chapter Practical Examples, and AutoML systems are recommended for each of them.
3. AutoML Systems
AutoML systems are evaluated based on publicly available data from the production domain. These are the systems included in this benchmark:
Some were included in the analysis, but were not evaluated in every criteria:
- Uber Ludwig 16, not tested regarding its Performance.
- TransmogrifAI 17, systems that require no programming knowledge or Python skills were tested. Since TransmogrifAI requisites expertise in the programming language Scala, its Performance was not tested.
- The Automatic Statistician 18, since no version is available for the public, its Performance was not tested.
The following ones were not included in the analysis:
- Auto-WEKA19, last updated in 2017.
- Darwin20, a demo must be requested for use and the free trial only allows the user to use the dataset provided by the system.
- DataRobot21, a demo must be requested for use.
- Devol22, is not being actively developed, and most information required for this research is not provided by the system.
- ExploreKit23, most information required for this research is not provided by the system.
- AutoML Zero 24, most information required for this research is not provided by the system.
- Auto-PyTorch 25, it's currently in a very early pre-alpha version and most information required for this research is not provided by the system.
4. Characteristics, Requirements and Boundaries
The chapter Characteristics presents general information about each system and Requirements and Boundaries focuses on demonstrating how personal information of the user affects the choice of system.
4.1 Characteristics
Each benchmarked system was tested in a specific version, as can be seen in the "Tested at" column of Table 1.
Even though this research is focused on AutoML systems, not every evaluated system covers the whole AutoML Pipeline. This distinction is presented in the "AutoML" column of Table 1, where systems marked with a Yes cover a large portion of the Pipeline and the ones which do not are defined in plain text.
Feature Tools and tsfresh automate only the Data Preparation step of the AutoML Pipeline. Nevertheless, they were kept in the analysis since they propose to automate the most time-consuming step of it.
4.2 Requirements and Boundaries
The systems differ in user knowledge, hardware and software requirements and price, which may imply limitations for different users and use cases. Table 2 exhibits these limitations for each system.
Most of the systems are free to use through a
Python-based API and require little knowledge in the programming language.
When the user has no experience in programming,
cloud-based paid systems should be chosen, since these offer an interface easy to use.
A deep knowledge in Data Science is usually not required, but may impact on results depending on the use case.
5. Performance of the AutoML Systems
In order to compare performances between models created by the AutoML systems, they were tested on an ML use case from production, where the following data from a CNC mill was used: CNC Mill Tool Wear data set . This is a classification problem, where the objective here is to predict the success of a test. The dataset was pre-processed before being tested by each system, having in the end 7586 instances and 50 dimensions. The results are presented in Table 3.
A future version of this benchmark will further include the results generated with the SECOM data set.
An overview of other publicly available data sets for production can be found at Fraunhofer IPT Application Fields and Free-Access Data Records .
With state of the art results, high Accuracy, high F1 score and low Loss,
all systems presented a more than acceptable model as a solution for this particular problem
and a distinction between better and worse system is hard to establish here.
Performance also depends on the runtime, since running a system for more time can output better results.
6. Functionalities of the AutoML systems
The systems presented here propose to automate the AutoML Pipeline, or parts of it. Having that in mind, this chapter of the benchmark will evaluate to which degree every step of the Pipeline is covered by each system.
6.1 Data Integration
Data Integration aims to integrate data residing in different sources. In Table 4, data types accepted by each system are displayed, as well as if these automate the data integration process.
No systems proposes to automate the Data Integration step,
since adapting to the vast quantity of different kinds of data sources is not trivial.
Regarding the data type, some systems are more limited and others are more inclusive,
for example, Auto_ml and Google AutoML respectively.
Regarding a specific use case, when looking for what system to use,
some systems can already be filtered out based on Table 4.
For example, a user facing an audio classification problem and having audio files as input data,
can pick Uber Ludwig, but not ATM.
6.2 Data Preparation
After assembling the dataset in a way it can be utilized by AutoML Systems, it's time to prepare it for the Modeling phase. That means increasing the quality of the data (Data Preprocessing) and restructuring it in order to facilitate the extraction of knowledge by an ML algorithm (Feature Engineering). As can be seen in Table 5, each system was evaluated with respect to how deep this preparation step is explored.
The exact approach taken for each of these methods is not specified in this benchmark, e.g. System X uses PCA for Data Reduction, therefore a Yes means some approach is used for the method and a No means no approach is taken. Nevertheless, the concept might be helpful when deciding which system to use for a certain use case. H2O AutoML might grant better results when dealing with unbalanced data sets, whereas other systems may be more effective for data sets with many dimensions, for example.
6.3 Modeling
The Modeling phase requires a prepared dataset to output effective results. To that end, the systems might
iterate through Data Preparation and Modeling
multiple times before reaching the final result.
Some of the algorithms used for each system, as well as how they are selected,
are shown in Table 6.
Have in mind that some systems allow exporting specific algorithms, others just output the best model and the results. See Table 8 for more information. More visual results can be obtained by a system which provides graphs and other metrics. See column Diagnosis of table Table 6.
6.4 Deployment
Ending the AutoML Pipeline, deployment aims to make the model available to users. For that, Table 7 answers the following questions:
- How can the model be deployed?
- How can the model be accessed by the user?
- Is training during production possible?
There is not a standard way of exporting the generated model,
as can be seen in the Productionize Model column of Table 7.
Regarding the Web Service, usually a REST API is provided,
where the model can be accessed through an endpoint.
7: Results
Table 8
aims to show how the trained models results of each system are presented to the user.
Some systems also provide intermediary results - in case Modeling takes a long time,
it can be interesting to have access to a model that has already fully trained, even if that is not the best one.
As can be seen in the table, the results vary from outputting sometimes a list of models and their characteristics,
and sometimes just the best model and evaluations.
Consequently, the user is not always allowed to decide which model can be exported, and therefore run in production.
Looking at the non-AutoML System, since Feature Tools and tsfresh propose to automate only the
Data Preparation phase,
their outputs are structured as a new dataset, containing new features and transformed old ones.
8: Selection Tool
The following section contains a tool, which can be used to find the right AutoML system for the User.
The question "Highly Relevant?" excludes systems which don't match exactly the submitted characteristics. This can be decided for each question separately.
For the questions where you do not know what to answer, or which should not have any impact on the result, please select N/A for no answer. This ensures that the topic has no influence on the result.
9: Practical Examples
In order to simulate how the process of finding systems
that fulfill a person's restrictions and requirements occurs,
the Personas Cards were created.
Each card represents a persona - an exemplified user.
At the end of each card, the chosen systems are displayed,
followed by the reasons they were designated for the specific persona and use case.
Paid systems, such as Google AutoML and Azure,
can be used by the personas with no budget since these systems provide free trials,
but it would not be a long term solution.
Recommended systems are not ordered from most recommended to less recommended.
To test the systems, in case of security issues or non-availability of data, it is possible to use publicly available data sets from production. See Fraunhofer IPT Application Fields and Free-Access Data Records .
10. Wrap Up
The past developments in the area of AutoML indicate that progress towards improved automation of specific steps within the AutoML Pipeline can be expected. Overall, a full automation of the whole AutoML Pipeline from Data Integration to Deployment is a concept that requires more research. In the near future, it can be expected that tasks such as Modeling will be automated enough so that ML models will be created with little to no ML knowledge. Semi-AutoML systems that support data scientists in other activities can be expected in the future as well.
11. Bibliography
-
Komer B, Bergstra J, Eliasmith C (2019) Hyperopt-Sklearn. in Hutter F, Kotthoff L, Vanschoren J, (Eds.). Automated Machine Learning. Springer International Publishing. Cham, pp. 97–111. ↩
-
Feurer M, Klein A, Eggensperger K, Springenberg JT, Blum M, Hutter F (2019) Auto-sklearn: Efficient and Robust Automated Machine Learning. in Hutter F, Kotthoff L, Vanschoren J, (Eds.). Automated Machine Learning. Springer International Publishing. Cham, pp. 113–134. ↩
-
Olson RS, Moore JH (2019) TPOT: A Tree-Based Pipeline Optimization Tool for Automating Machine Learning. in Hutter F, Kotthoff L, Vanschoren J, (Eds.). Automated Machine Learning. Springer International Publishing. Cham, pp. 151–160. ↩
-
H2O.ai. AutoML: Automatic Machine Learning — H2O <IP_ADDRESS> documentation. http://docs.h2o.ai/h2o/latest-stable/h2o-docs/automl.html. Accessed on 20.11.2019. ↩
-
SAS Institute Inc. SAS Visual Data Mining and Machine Learning. https://www.sas.com/en_us/software/visual-data-mining-machine-learning.html. Accessed on 26.01.2020. ↩
-
ARONIO DE ROMBLAY A. MLBox Documentation. https://mlbox.readthedocs.io/en/latest/index.html. Accessed on 20.11.2019. ↩
-
Google Cloud. Best practices for creating training data | AutoML Tables Documentation | Google Cloud. https://cloud.google.com/automl-tables/docs/data-best-practices#tables-does. Accessed on 20.11.2019. ↩
-
Microsoft Azure. Azure Machine Learning documentation. https://docs.microsoft.com/en-us/azure/machine-learning/. Accessed on 20.11.2019. ↩
-
MLJAR. mljar-docs. https://docs.mljar.com/. Accessed on 06.02.2020. ↩
-
Swearingen T, Drevo W, Cyphers B, Cuesta-Infante A, Ross A, Veeramachaneni K (2017 - 2017) ATM: A distributed, collaborative, scalable system for automated machine learning. 2017 IEEE International Conference on Big Data (Big Data). IEEE, pp. 151–162. ↩
-
Parry P. auto_ml 0.1.0 documentation. https://auto-ml.readthedocs.io/en/latest/index.html. Accessed on 20.11.2019. ↩
-
AWS. Amazon SageMaker - Developer Guide. https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-dg.pdf . Accessed on 20.11.2019. ↩
-
Feurer M, Klein A, Eggensperger K, Springenberg JT, Blum M, Hutter F (2019) Auto-sklearn: Efficient and Robust Automated Machine Learning. in Hutter F, Kotthoff L, Vanschoren J, (Eds.). Automated Machine Learning. Springer International Publishing. Cham, pp. 113–134. ↩
-
Feature Labs. Featuretools 0.12.0 documentation. https://docs.featuretools.com/en/stable/index.html. Accessed on 20.11.2019. ↩
-
Christ M, Braun N, Neuffer J. tsfresh — tsfresh 0.12.0 documentation. https://tsfresh.readthedocs.io/en/latest/index.html. Accessed on 06.02.2020. ↩
-
Uber Ludwig documentation. https://uber.github.io/ludwig/. Accessed on 27.05.2020. ↩
-
Salesforce.com, Inc. AutoML library for building modular, reusable, strongly typed machine learning workflows on Spark from Salesforce Engineering. https://transmogrif.ai/. Accessed on 26.01.2020. ↩
-
The Automatic Statistician. https://link.springer.com/chapter/10.1007/978-3-030-05318-5_9. Accessed on 20.05.2020. ↩
-
Kotthoff L, Thornton C, Hoos HH, Hutter F, Leyton-Brown K (2019) Auto-WEKA: Automatic Model Selection and Hyperparameter Optimization in WEKA. in Hutter F, Kotthoff L, Vanschoren J, (Eds.). Automated Machine Learning. Springer International Publishing. Cham, pp. 81–95. ↩
-
SparkCognition (2019) From Data to Application: DARWINS UNIQUE APPROACH TO AUTOML. ↩
-
DataRobot. https://www.datarobot.com/. Accessed on 12.05.2020. ↩
-
Devol. https://github.com/joeddav/devol. Accessed on 20.05.2020. ↩
-
ExploreKit. http://people.eecs.berkeley.edu/~dawnsong/papers/icdm-2016.pdf. Accessed on 20.05.2020. ↩
-
AutoML Zero. https://arxiv.org/pdf/2003.03384.pdf. Accessed on 12.05.2020.↩
-
Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Matthias Urban, Michael Burkart, Max Dippel, Marius Lindauer, Frank Hutter (2018) Towards Automatically-Tuned Deep Neural Networks: 7. in Hutter F, Kotthoff L, Vanschoren J, (Eds.). AutoML: Methods, Sytems, Challenges. Springer, pp. 141–156. ↩


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Connection¶
-
class
O365.connection.
Connection
(credentials, *, scopes=None, proxy_server=None, proxy_port=8080, proxy_username=None, proxy_password=None, requests_delay=200, raise_http_errors=True, request_retries=3, token_file_name=None)[source]¶ Bases:
object
Handles all communication (requests) between the app and the server
-
__init__
(credentials, *, scopes=None, proxy_server=None, proxy_port=8080, proxy_username=None, proxy_password=None, requests_delay=200, raise_http_errors=True, request_retries=3, token_file_name=None)[source]¶ Creates an API connection object
Parameters: - credentials (tuple) –
a tuple of (client_id, client_secret)
Generate client_id and client_secret in https://apps.dev.microsoft.com
- scopes (list[str]) – list of scopes to request access to
- proxy_server (str) – the proxy server
- proxy_port (int) – the proxy port, defaults to 8080
- proxy_username (str) – the proxy username
- proxy_password (str) – the proxy password
- requests_delay (int) –
number of milliseconds to wait between api calls.
The Api will respond with 429 Too many requests if more than 17 requests are made per second. Defaults to 200 milliseconds just in case more than 1 connection is making requests across multiple processes.
- raise_http_errors (bool) – If True Http 4xx and 5xx status codes will raise as exceptions
- request_retries (int) – number of retries done when the server responds with 5xx error codes.
- token_file_name (str) – custom token file name to be used when storing the OAuth token credentials.
Raises: ValueError – if credentials is not tuple of (client_id, client_secret)
- credentials (tuple) –
-
check_token_file
()[source]¶ Checks if the token file exists at the given position
Returns: if file exists or not Return type: bool
-
delete
(url, **kwargs)[source]¶ Shorthand for self.request(url, ‘delete’)
Parameters: - url (str) – url to send delete oauth request to
- kwargs – extra params to send to request api
Returns: Response of the request
Return type: requests.Response
-
get
(url, params=None, **kwargs)[source]¶ Shorthand for self.oauth_request(url, ‘get’)
Parameters: - url (str) – url to send get oauth request to
- params (dict) – request parameter to get the service data
- kwargs – extra params to send to request api
Returns: Response of the request
Return type: requests.Response
Initializes the oauth authorization flow, getting the authorization url that the user must approve.
Parameters: - requested_scopes (list[str]) – list of scopes to request access for
- redirect_uri (str) – redirect url configured in registered app
Returns: authorization url
Return type: str
-
get_session
(token_path=None)[source]¶ Create a requests Session object
Parameters: token_path (Path) – (Only oauth) full path to where the token should be load from Returns: A ready to use requests session Return type: OAuth2Session
-
naive_request
(url, method, **kwargs)[source]¶ Makes a request to url using an without oauth authorization session, but through a normal session
Parameters: - url (str) – url to send request to
- method (str) – type of request (get/put/post/patch/delete)
- kwargs – extra params to send to the request api
Returns: Response of the request
Return type: requests.Response
-
oauth_request
(url, method, **kwargs)[source]¶ Makes a request to url using an oauth session
Parameters: - url (str) – url to send request to
- method (str) – type of request (get/put/post/patch/delete)
- kwargs – extra params to send to the request api
Returns: Response of the request
Return type: requests.Response
-
patch
(url, data=None, **kwargs)[source]¶ Shorthand for self.oauth_request(url, ‘patch’)
Parameters: - url (str) – url to send patch oauth request to
- data (dict) – patch data to update the service
- kwargs – extra params to send to request api
Returns: Response of the request
Return type: requests.Response
-
post
(url, data=None, **kwargs)[source]¶ Shorthand for self.oauth_request(url, ‘post’)
Parameters: - url (str) – url to send post oauth request to
- data (dict) – post data to update the service
- kwargs – extra params to send to request api
Returns: Response of the request
Return type: requests.Response
-
put
(url, data=None, **kwargs)[source]¶ Shorthand for self.oauth_request(url, ‘put’)
Parameters: - url (str) – url to send put oauth request to
- data (dict) – put data to update the service
- kwargs – extra params to send to request api
Returns: Response of the request
Return type: requests.Response
-
request_token
(authorization_url, store_token=True, token_path=None)[source]¶ Authenticates for the specified url and gets the token, save the token for future based if requested
Parameters: - authorization_url (str) – url given by the authorization flow
- store_token (bool) – whether or not to store the token in file system, so u don’t have to keep opening the auth link and authenticating every time
- token_path (Path) – full path to where the token should be saved to
Returns: Success/Failure
Return type: bool
-
-
class
O365.connection.
MSGraphProtocol
(api_version='v1.0', default_resource='me', **kwargs)[source]¶ Bases:
O365.connection.Protocol
A Microsoft Graph Protocol Implementation https://docs.microsoft.com/en-us/outlook/rest/compare-graph-outlook
-
__init__
(api_version='v1.0', default_resource='me', **kwargs)[source]¶ Create a new Microsoft Graph protocol object
_protocol_url = ‘https://graph.microsoft.com/’
_oauth_scope_prefix = ‘https://graph.microsoft.com/’
Parameters: - api_version (str) – api version to use
- default_resource (str) – the default resource to use when there is nothing explicitly specified during the requests
-
-
class
O365.connection.
MSOffice365Protocol
(api_version='v2.0', default_resource='me', **kwargs)[source]¶ Bases:
O365.connection.Protocol
A Microsoft Office 365 Protocol Implementation https://docs.microsoft.com/en-us/outlook/rest/compare-graph-outlook
-
__init__
(api_version='v2.0', default_resource='me', **kwargs)[source]¶ Create a new Office 365 protocol object
_protocol_url = ‘https://outlook.office.com/api/’
_oauth_scope_prefix = ‘https://outlook.office.com/’
Parameters: - api_version (str) – api version to use
- default_resource (str) – the default resource to use when there is nothing explicitly specified during the requests
-
-
class
O365.connection.
Protocol
(*, protocol_url=None, api_version=None, default_resource='me', casing_function=None, protocol_scope_prefix=None, timezone=None, **kwargs)[source]¶ Bases:
object
Base class for all protocols
-
__init__
(*, protocol_url=None, api_version=None, default_resource='me', casing_function=None, protocol_scope_prefix=None, timezone=None, **kwargs)[source]¶ Create a new protocol object
Parameters: - protocol_url (str) – the base url used to communicate with the server
- api_version (str) – the api version
- default_resource (str) – the default resource to use when there is nothing explicitly specified during the requests
- casing_function (function) – the casing transform function to be used on api keywords (camelcase / pascalcase)
- protocol_scope_prefix (str) – prefix url for scopes
- timezone (pytz.UTC) – preferred timezone, defaults to the system timezone
Raises: ValueError – if protocol_url or api_version are not supplied
-
convert_case
(key)[source]¶ Returns a key converted with this protocol casing method
Converts case to send/read from the cloud
When using Microsoft Graph API, the keywords of the API use lowerCamelCase Casing
When using Office 365 API, the keywords of the API use PascalCase Casing
Default case in this API is lowerCamelCase
Parameters: key (str) – a dictionary key to convert Returns: key after case conversion Return type: str
-
get_scopes_for
(user_provided_scopes)[source]¶ Returns a list of scopes needed for each of the scope_helpers provided, by adding the prefix to them if required
Parameters: user_provided_scopes (list or tuple or str) – a list of scopes or scope helpers Returns: scopes with url prefix added Return type: list Raises: ValueError – if unexpected datatype of scopes are passed
-
-
O365.connection.
oauth_authentication_flow
(client_id, client_secret, scopes=None, protocol=None, **kwargs)[source]¶ A helper method to perform the OAuth2 authentication flow. Authenticate and get the oauth token
Parameters: - client_id (str) – the client_id
- client_secret (str) – the client_secret
- scopes (list[str]) – a list of protocol user scopes to be converted by the protocol
- protocol (Protocol) – the protocol to be used. Defaults to MSGraphProtocol
- kwargs – other configuration to be passed to the Connection instance
Returns: Success or Failure
Return type: bool


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Reference Language | Libraries | Comparison | Changes
|
The Arduino Yún has two processors on board. One is an ATmega32U4 like on the Arduino Leonardo. The other is an Atheros 9331, running Linux and the OpenWRT wireless stack, which enables the board to connect to WiFi and Ethernet networks. It is possible to call programs or custom scripts on the Linux system through the Arduino to connect with various internet services. The Bridge library simplifies communication between the ATmega32U4 and the AR9331. It inherits from Stream, and many of the methods should be familiar from Serial and other derivatives of Stream. Bridge commands from the 32U4 are interpreted by Python on the AR9331. Its role is to execute programs on the GNU/Linux side when asked by Arduino, provide a shared storage space for sharing data like sensor readings between the Arduino and the Internet, and receiving commands from the Internet and passing them directly to the Arduino. Bridge allows communication in both directions, acting as an interface to the the Linux command line. For a brief explanations of the terminal and executing commands on Linux see here. To become familiar with the Yún, please see the getting started page and hardware page. ProcessProcess is used to launch processes on the Linux processor, and other things like shell scripts. ConsoleConsole can be used to communicate with the network monitor in the Arduino IDE, through a shell. Functionally, it is very similar to Serial. FileIOAn interface to the Linux file system. Can be used to read/write files on the SD card HttpClientCreates a HTTP client on Linux. Acts as a wrapper for common CURL commands, by extending Process. MailboxAn asynchronous, sessionless interface for communicating between Linux and Arduino. YunClientAn Arduino based HTTP client, modeled after the EthernetClient class. YunServerAn Arduino based HTTP server, modeled after the EthernetServer class. TembooAn interface to Temboo making it easy to connect to a large variety of online tools. See the Tembo documentation for more. SpacebrewSpacebrew is "a simple way to connect interactive things to one another" that uses WebSockets to communicate. you can find more about Spacebrew through their online documentations. Examples
|
Bridge Class
FunctionsProcess Class
Functions
Console Class
FunctionsFileIO ClassFunctions
Mailbox ClassFunctionsHttpClient ClassFunctionsYunClient ClassFunctionsYunServer ClassFunctions |
Corrections, suggestions, and new documentation should be posted to the Forum.
The text of the Arduino reference is licensed under a Creative Commons Attribution-ShareAlike 3.0 License. Code samples in the reference are released into the public domain.


Minimalist interior design is one of the centerpieces of the 20th century. Spare and streamlined while still being inviting, minimalism is charming in almost any space. With less clutter to wade through and mentally process, the innate beauty of each piece of furniture or art in the home really starts to stand out.
With roots in both tropical and British Colonial decor, our Sakura Armchair reflects the well-traveled style of the past. Hand-woven rattan has the timeless good looks of a natural material in a neutral color, introducing a lighter, less formal aesthetic when mixed with heavier furniture. One in a room is impressive—add a pair, and you've made a major design statement. Requires a Large Modular Cushion.
Variety may be the spice of life, but Calliope is the spice of outdoor life. As attractive as any indoor pillow, our self-welted design is UV-resistant and mildew-resistant, yet oh-so-soft. Sprinkle generously on patio furniture.
Our contemporary Anywhere Collection is the perfect hybrid of classic cabinetry and sleek, modern design. Distinctive features include sturdy hardwood construction, a painted antique white finish, raised panels, an overhanging top with ogee edge, turned legs and durable, wood-on-wood drawer glides with stops. In short, all the traditional details you love without all the bulk. And guess where this collection can go? Come on, you know this one.
| Item | Item Name | Color | Price | |
|---|---|---|---|---|
| Pale Pillow | Navi | $30.50 | delete | |
| Pale Pillow | White | $20.50 | delete | |
| Pale Pillow | Grey | $40.50 | delete | |
| Chair | Wood | $120.00 | delete |
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Given a C++ model, we need to go through the four steps of transformation (as shown in Figure 12) in order to generate a final application that will run under both the C++ and Objective-C environments. Figure 13 shows the details of the steps involved for final user application generation. Since this can be managed automatically via the make process, this complexity is not visible to the programmer.


MRS. PARKER AND THE VICIOUS CIRCLE A film review by Alex Fung Copyright 1994 Alex Fung
Fineline Starring Jennifer Jason Leigh, Matthew Broderick, Campbell Scott, Jennifer Beals, Peter Gallagher, Andrew McCarthy, Wallace Shawn, Martha Plimpton, Sam Robards, Lili Taylor, James LeGros, Gwyneth Paltrow, Heather Graham, Stephen Baldwin Written by Alan Rudolph and Randy Sue Coburn Produced by Robert Altman Directed by Alan Rudolph Rated AA [Adult Accompaniment] in Canada for brief nudity and coarse language
After opening exclusively in New York in late November 1994, the new Alan Rudolph film, MRS. PARKER AND THE VICIOUS CIRCLE is beginning to get a wider, if somewhat restricted, distribution, and has opened here in Toronto during the Xmas weekend.
Filmed in Montreal, MRS. PARKER is a loosely biographical film dealing with the writer Dorothy Parker, who entertained America in the 1920s with her sharp tongue and witticisms, and her follies with what became known as the Algonquin Round Table, a group of friends and colleagues who would dine daily at the Algonquin in New York and trade verbal barbs and amused chatterings. This group would encompass some of the most influential figures on American culture of their time.
If you're looking for an upbeat feel-good comedy, this is likely a film you would want to stay away from. As Dorothy Parker's life is revealed through a series of flashbacks, swapping between her youth and her old age, it is revealed that behind her banter and sly wit lay sorrow, despair, self-consciousness and perpetual depression. We cringe in the audience as we watch Parker desperately enter futile relationship after relationship, thus perpetuating the cycle of her misery, and we morosely watch the elderly Parker, a shadow of her former self, react with regret and grief on actions unfulfilled and love unconsummated.
The young ensemble cast is very solid in MRS. PARKER in their limited roles, but the three major characters featured in the film are Dorothy Parker (Leigh), Robert Benchley (Scott), and Charles MacArthur (Broderick). Broderick is fine as one of Parker's loves, and Campbell Scott is outstanding in a potential break-out performance as Parker's confidant and soulmate--physically, in this film he mildly resembles a dapper Patrick Bergen--but by and large, this film is a vehicle for Jennifer Jason Leigh, who is in virtually every scene.
Much has been said in the press and the newsgroups about how Leigh's rendition of Parker's slurred, grating voice has rendered much of her dialogue incomprehensible, but honestly, I did not encounter this problem at all. It may be a function of the theatre speakers and background noise (i.e., viewers talking) that may compound the difficulty for some, but in general her words are understandable, if mildly challenging. In any case, her version sounds so true to the original that one must give her points for trying.
Dorothy Parker, as depicted in this film, is a well-suited entry in Leigh's catalog of downbeat, dark, and quirky characters, and while she is capable in the role, it is a mild disappointment that, save for the inflection, she did not stretch much further for it. Many of Leigh's own characteristic performance ticks can be seen in the film, but it may due to the character's lack of range in the screenplay that this becomes obvious. Nonetheless, Leigh will probably get serious Oscar consideration, since this is one of very few high-profile dominant female roles of the year, and her other work has been critically accepted.
MRS. PARKER suffers from some significant pacing problems and at times seems too choppy and uneven. The film lurches between the two timelines, and while what's depicted on-screen is done well, it only gives the audience a voyeuristic glance into scenes from Parker's life, and doesn't flesh out the characters sufficiently. The conclusion of the film seems to come rather abruptly, and some scenes in the movie tend to be a bit overlong in bringing their significance to point. The humour is a hit-and-miss affair; some points are roaringly funny, while other jabs provide nary a chuckle. The costumes (by John Hay) and production design (by Francois Seguin) are first rate, and the period score, though appropriate, is slightly overprominent and becomes grating at times.
Though the screenplay could have probably undergone a bit more revision, it is nonetheless very effective in its ultimate portrayal of Parker as a tragic figure. While those with no familiarity or interest in Dorothy Parker may be disenchanted, the combination of this unfortunate soul in American history with an excellent ensemble cast makes MRS. PARKER AND THE VICIOUS CIRCLE a haunting little film. On my four-star scale, I give this a two-and-a-half.
Note: There is one scene that is shown after the credits have begun to roll, so one may want to remain for that scene to complete before leaving. Incidentally, Leigh's half-sister, Mina Badie, has a minor speaking part in this film.
-- Alex Fung<EMAIL_ADDRESS>.
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Hi my name is Stephen Keating. I am a senior in the Florida State University Information
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and development while integrating as much website development experience as possible.
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skills. I have combined these life experiences with my continued education so that I can integrate
myself into any development team I become a part of.
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Use this area of the page to describe your project. The icon above is part of a free icon set by Flat Icons. On their website, you can download their free set with 16 icons, or you can purchase the entire set with 146 icons for only $12!


Dimple Kapadia’s mother hospitalised
Dimple Kapadia's mother Betty Kapadia has been admitted to Hinduja hospital in suburban Khar, sources said on Saturday.
by PTIVeteran Bollywood actor Dimple Kapadia’s mother Betty Kapadia has been admitted to Hinduja hospital in suburban Khar, sources said on Saturday.
“She was admitted to the hospital on November 14. She is in the ICU,” the hospital sources said, without divulging more details.
Earlier in the day, there were rumours about Dimple being hospitalised after her daughter Twinkle and son-in-law Akshay Kumar were seen at the hospital.
Workwise, Dimple will be seen next in renowned filmmaker Christopher Nolan’s film Tenet.


--- layout: main title: Housing Insights Tool --- Nov. 15, 2016 | Latest status on the Housing Insights Tool development process
There are many relevant data sources we could incorporate into the Housing Insights tool. We need the affordable housing community to help us decide which to focus on. Please take our one page survey to share what you would find most useful in a tool designed to help prioritize efforts in affordable housing preservation.
Read below for more context on the data sources we're considering, and then come back here to:
Take the surveyBefore taking the survey, read this list for background information on the data sources we are considering.
| Type of Data | Use | Potential Sources |
| Value of the property | Can provide an indicator of the magnitude of investment required, for comparison to actual spending allocations. | - City tax records - Comparison of tax record to market prices |
| Distance to DC funded economic development | - Specific criteria of an 'economic development project' TBD, from city records | |
| Distance to transit | Indicates both value to residents, as well as an early indicator of potential risk (being close to metro will often indicate being more likely to increase neighborhood market rents) | - Metro locations and high-traffic bus stops |
| Inspection scores | - Already available in the Preservation Catalog (REAC scores) - DCRA inspections |
|
| Market rents and home prices | By comparing this to the rent received by the building owner we can have an indicator of the risk of loss in a neighborhood. | - Zillow price data by
neighborhood - American Community Survey data |
| Neighborhood Demographics | - Census data, e.g. population, education, employment and income levels. | |
| Owner details (property records) | Useful when specific owners are known to the preservation community to behave in certain ways. | - Register of deeds - If possible, tracing LLC registrations to find actual owner lists |
| Quantity nearby affordable units | Indicate whether preserving a building is needed to maintain economic diversity in a neighborhood. | - Preservation Catalog properties - Additional buildings not yet covered in the Catalog |
| Resident Type | The typical income level of residents as well as information like elderly and disabled residents. | - Subsidy type - Other data TBD |
| TOPA notices | We can incorporate items like email notifications when TOPA notifications are issued, so that everyone in the preservation community can be aware of current developments. | |
| Upcoming private neighborhood investment | Rent and home price data are neighborhood level; this provides a more specific indicator of potential pressure to sell a property due to changes within a few block radius.. | - Planned Unit Development
Process records - Nearby building permits |
As one example of the type of analysis we envision this tool will be able to provide, we've already connected the Preservation Catalog to DC's tax assessment database. Although just an example, we hope that this type of analysis can make it easier to better prioritize the time and money spent on affordable housing preservation.
Not all affordable housing units will cost the same to preserve if their building owners decide to sell. To get a sense of this difference, we connected the Preservation Catalog to DC's Real Property Tax Database to find out the assessed tax value of all the affordable buildings in DC.
This graph sums the tax value of all affordable developments in the Preservation Catalog by neighborhood cluster. The values on both the map and bar chart represent the average assessed value per affordable unit.
Note this is draft data - while close to accurate, we haven't completed full quality assurance to make sure all buildings are accurately represented. This should, however, give you a sense of the type of information the Housing Insights tool will provide.
$3.8 Billion total tax value of affordable housing in DC
38,455 affordable units
$98,500 avg DC tax value per affordable unit
This is draft analysis, and should not be quoted or used outside of this page until a final analysis is published. The purpose of this page is to show Preservation Network Members the type of information that we intend to include in the final Housing Insights tool.
Data on this page comes from matching all 'Active' projects in the Preservation Catalog to their corresponding tax assessment records from the DC Government. A few known issues with the data include:


| Package | Description |
|---|---|
| com.google.gson |
This package provides the
Gson class to convert Json to Java and
vice-versa. |
| Class and Description |
|---|
| ExclusionStrategy
A strategy (or policy) definition that is used to decide whether or not a field or top-level
class should be serialized or deserialized as part of the JSON output/input.
|
| FieldAttributes
A data object that stores attributes of a field.
|
| FieldNamingPolicy
An enumeration that defines a few standard naming conventions for JSON field names.
|
| FieldNamingStrategy
A mechanism for providing custom field naming in Gson.
|
| Gson
This is the main class for using Gson.
|
| GsonBuilder
Use this builder to construct a
Gson instance when you need to set configuration
options other than the default. |
| JsonArray
A class representing an array type in Json.
|
| JsonDeserializationContext
Context for deserialization that is passed to a custom deserializer during invocation of its
JsonDeserializer.deserialize(JsonElement, Type, JsonDeserializationContext)
method. |
| JsonElement
A class representing an element of Json.
|
| JsonIOException
This exception is raised when Gson was unable to read an input stream
or write to one.
|
| JsonNull
A class representing a Json
null value. |
| JsonObject
A class representing an object type in Json.
|
| JsonParseException
This exception is raised if there is a serious issue that occurs during parsing of a Json
string.
|
| JsonPrimitive
A class representing a Json primitive value.
|
| JsonSerializationContext
Context for serialization that is passed to a custom serializer during invocation of its
JsonSerializer.serialize(Object, Type, JsonSerializationContext) method. |
| JsonSyntaxException
This exception is raised when Gson attempts to read (or write) a malformed
JSON element.
|
| LongSerializationPolicy
Defines the expected format for a
long or Long type when its serialized. |
| TypeAdapter
Converts Java objects to and from JSON.
|
| TypeAdapterFactory
Creates type adapters for set of related types.
|
Copyright © 2008–2014 Google, Inc.. All rights reserved.


Download
Source code
Fire UI is completely open source and available on GitHub
Examples
Examples of Fire UI will available soon
Package managers
npm
Install Bootstrap in your Node.js powered apps with the npm package manager
npm install @fire-ui/fire-ui


"Architecture -- Italy"
"Italy -- Description and travel"
"Landscape architecture -- Italy"
"Architecture, Domestic -- Italy"
"Landscape gardening"


This Domain used Cloudflare during the affected time period.
Make sure to invalidate session tokens by logging out & back in. It's recommended to also change your password in the process.
This is, however, no clear indicator whether requests were actually leaked or not because this list is incomplete and features domains not affected. Narrowing down the list is WIP.
Nobody can be sure if requests of your entered domain were actually leaked, because search engine caches have been mostly scrubbed by now.
Please be aware of the fact that there may be more leaked domains which are not yet included in this list.


Custom Projects Without Branding
This section contains all the projects that work as an infrastructure and are added in all of my next programs on programming and tools that I invented in order to facilitate my life when designing programs
Android Infrastructure That Includes The Common Cases In Any Application With Ready Configuration, Mvvm Base Code With Redux State Handling, Implementation Check The Docs To See The Features
Mvp Implementation With Ready Base Code To Handle Presenters, Common Application Configuration With Gradle Plugin To Implement Gradle App Module Dpendencies With UseCases, Api Handling
Backend Project Restful Api With Mongo DB , Kotlin Api, Ktor Framework Example and This Project is An Starter Kit To Start Any Ktor Application With Common Server Side Configuration
Graduation Project Designed With Vortex-Firebase and Firebase as a Backend Side, Firestore Database, Firebase Auth To Login, Register, Kotlin Programming Language
Restful Api For Books Application and Mysql Database Implementation For Manage The Books With Restful Apis (Trainig Project) Written In Java Language
Dark Theme With Orange, Yellow Color For kotlin :P Nice Plugin For Kotlin that provides you to write kotlin code with nice orange color
Spring Boot With Kotlin Restful Api To Manage Restaurant Application With Recipes, Config, Security, JWT, Json Response, Error Handling, Full Project With MySql Database
Spring Boot With Gson To Generate Postman Collection From Spring Controllers And Create Json File To Import The Api's into Postman Client Writter In Kotlin Language
Kotlin Multi Platform Domain Layer Leader Lead The Domain Layer Into Shared Code, Custom Implementation For Android , IOS Layer That Handle The Local Mobile Operations
My Personal Website Writter In Angular Framework , Typescript, This Project Deployed On Github IO Pages To Manage The All Projects


Bolstered with a new identity, Equestrian Canada, the Canadian federation for equestrian sport mandated Locomotive with the redesign of its portal. The tram is a thing of a past, a thing from our childhood.


 Before I discovered git hooks, my deployment process consisted of pushing changes to my remote repository, SSH’ing into the server, navigating to the site directory, pulling the changes, and restarting the webserver. It wasn’t efficient at all and a waste of time doing that several times a day. I’ll explain how to set up a simple git hook making the deployment process a bit more effortless, but first I want to give credit to this how-to article which got me started.
In this example we’ll be deploying the production branch but it can be whatever branch name you want, and our site name will be called foo.
On the server
Initialize an empty git repo. This will act as the mediator.
mkdir -p /opt/git/foo.git
cd /opt/git/tracfone.git
git init --bare # no source files, only version control
Create a post-receive
hook which gets called after a push is complete.
vim /opt/git/foo.git/hooks/post-receive
#!/bin/bash
SITE_NAME="Foo"
SITE_PATH="/var/www/foo.com"
BRANCH="production"
echo "**** $SITE_NAME [post-receive] hook received."
while read oldrev newrev ref
do
branch_received=`echo $ref | cut -d/ -f3`
echo "**** Received [$branch_received] branch."
# Making sure we received the branch we want.
if [ $branch_received = $BRANCH ]; then
cd $SITE_PATH
# Unset to use current working directory.
unset GIT_DIR
echo "**** Pulling changes."
git pull origin $BRANCH
# Instead of pulling we can also do a checkout.
: '
echo "**** Checking out branch."
GIT_WORK_TREE=$SITE_PATH git checkout -f $BRANCH
'
# Or we can also do a fetch and reset.
: '
echo "**** Fetching and reseting."
git fetch --all
git reset --hard origin/$BRANCH
'
else
echo "**** Invalid branch, aborting."
exit 0
fi
done
# [Restart/reload webserver stuff here]
echo "**** Done."
exec git-update-server-info
Make sure to make the hook executable.
chmod u+rwx /opt/git/foo.git/hooks/post-receive
On the client
Add the remote url.
git remote add production ssh://<username@<server ip>/opt/git/foo.git
Push the production branch.
git push production +production:refs/heads/production
# Afterwards you can simply do
git push production
It’s also possible to deploy to multiple servers, just add the remote urls in .git/config
.
[remote "production"]
url = ssh://<username>@<server 1 ip>/opt/git/foo.git
url = ssh://<username>@<server 2 ip>/opt/git/foo.git
By default git will push all branches to the remotes but we can have it push the current branch only.
git config --global push.default current
Conclusion
Git hooks can help automate your deployment process. Checkout the list of client and server-side Git hooks available.


Human Rights Court Shields Workers From Speech Retaliation
by MOLLY QUELLSTRASBOURG, France (CN) – Protections for freedom of speech extend into the workplace, the European Court of Human Rights clarified Tuesday in the case of a bank employee fired for writing online articles about human resources issues.
“The court reiterates that the enjoyment of the right to freedom of expression should be secured even in the relations between employer and employee,” the seven-judge panel’s ruling states.
Csaba Herbai, a Hungarian national, was working as a human resources manager at a bank in the country’s capital city of Budapest. While he was employed there, he helped start a knowledge-sharing website directed at HR professionals.
Herbai had signed a confidentiality agreement with the unnamed bank in which he agreed “not to publish formally or informally any information relating to the functioning and activities of his employer,” according to court records.
On his HR website, Herbai identified himself as a contributor to the site, including a photo and a biography that mentioned he “worked in the human resources department of a large domestic bank,” though he did not name his employer.
In 2011, the bank fired him on the basis that his website articles violated the confidentiality agreement. Herbai sued in Hungarian court over his dismissal, but the court held that his writings could have jeopardized the bank’s interests.
After taking his case all the way to the Hungarian Supreme Court, which affirmed the lower courts, Herbai filed a complaint with the European Court of Human Rights in 2015.
The Strasbourg-based court was created by the 1953 European Convention on Human Rights and hears cases on political freedom and human rights.
Article 10 of the Convention protects the freedom of expression of European citizens, and the court ruled Tuesday that Herbai’s conduct falls under that protection.
“[Hungarian] courts found that the website conveyed information of a commercial nature, inviting discussion on the business practices of the audience; and, moreover, that the contested articles were addressed to a limited circle of professionals and did not directly concern the public as a whole,” the ruling states. “However, as the Court has previously found, such information cannot be excluded from the scope of Article 10 § 1, which does not apply solely to certain types of information or ideas or forms of expression. In other words, workplace-related free speech does not only protect comments that demonstrably contribute to a debate on a public matter.”
The rights court acknowledged that employers are allowed under Hungarian law to restrict employees’ speech to some degree, but it found that the national courts had not carried out a proper assessment of proportionality.
“The court finds that in the present case the domestic authorities have failed to demonstrate convincingly that the rejection of the applicant’s challenge against his dismissal was based on a fair balance between the applicant’s right to freedom of expression, on the one hand, and his employer’s right to protect its legitimate business interests, on the other hand,” the judges said. “They therefore did not discharge their positive obligations under Article 10 of the Convention.”
Hungary was ordered to pay Herbai damages of 10,000 euros, or about $11,000, and about $5,000 in expenses.
Copyright © 2019 courthousenews.com


Abstract
This vignette provides an introduction into the functions and workflow inragp
R package. ragp
is designed for mining and analysis of plant Hydroxyproline rich glycoproteins but it can also be used for protein annotation and for obtaining predictions for several protein features based on sequence (secretory signals, transmembrane regions, domains and glycosylphosphatidylinositol attachment sites). Additionally ragp
provides tools for visualization of the mentioned attributes.
Hydroxyproline rich glycoproteins (HRGPs) are one of the most complex families of macromolecules found in plants, due to the diversity of glycans decorating the protein backbone, as well as the heterogeneity of the protein backbones. While this diversity is responsible for the wide array of physiological functions associated with HRGPs, it hinders attempts for homology based identification. Current approaches, based on identifying sequences with characteristic motifs and biased amino acid composition, are limited to prototypical sequences.
ragp
is an R package for mining and analyses of HRGPs, with emphasis on arabinogalactan protein sequences (AGPs). The ragp
filtering pipeline exploits one of the HRGPs key features, the presence of hydroxyprolines which represent glycosylation sites. Main package features include prediction of proline hydroxylation sites, amino acid motif and bias analyses, efficient communication with web servers for prediction of N-terminal signal peptides and glycosylphosphatidylinositol modification sites, as well as the ability to annotate sequences through CDD or hmmscan and subsequent GO enrichment, based on predicted Pfam domains.
The workflow in ragp
is illustrated with the following diagram (ragp
functions to be used for each of the tasks are boxed grey):
The filtering layer:
get_signalp5()
which queries SignalP5 (Almagro Armenteros et al. 2019).predict_hyp()
) and filter sequences containing several (for example three or more) potential hydroxyprolines.The analysis layer:
scan_ag()
) among the hydroxyproline containing sequences.maab()
) to classify hydroxyproline containing sequences.get_hmm()
) and enrich with gene ontology (GO) terms (pfam2go()
). Alternatively annotate domains using CDD.get_big_pi()
, get_pred_gpi()
and get_netGPI()
).get_espritz()
).get_phobius()
and get_tmhmm()
)Additionally ragp
provides tools for visualization of the mentioned attributes via plot_prot()
.
There are several ways to install R packages hosted on git-hub, however the simplest is to use devtools::install_github()
which will perform all the required steps automatically.
To install ragp
run:
#install.packages("devtools") #if it is not installed on your system
devtools::install_github("missuse/ragp")
alternatively run:
# install.packages("devtools")
devtools::install_github("missuse/ragp",
build_vignettes = TRUE)
to build vignettes which can be viewed by:
browseVignettes("ragp")
Most ragp
functions require single letter protein sequences and the corresponding identifiers as input. These can be provided in the form of basic R
data types such as vectors or data frames. Additionally ragp
imports the seqinr
package for the manipulation of .FASTA
files, so the input objects can be a list of SeqFastaAA
objects returned by the seqinr::read.fasta()
. The location of a .FASTA
file is also possible as a type of input. As of ragp version 0.3.5 objects of class AAStringSet
are also supported.
Input options will be illustrated using scan_ag()
function:
character
vector of protein sequences to the sequence
argument and a character
vector of protein identifiers to the id
argument:library(ragp)
data(at_nsp) #a data frame of 2700 Arabidopsis sequences
input1 <- scan_ag(sequence = at_nsp$sequence,
id = at_nsp$Transcript.id)
data.frame
to data
argument, and names of columns containing the protein sequences and corresponding identifiers to sequence
and id
arguments:input2 <- scan_ag(data = at_nsp,
sequence = "sequence",
id = "Transcript.id")
quoting column names is not necessary:
input3 <- scan_ag(data = at_nsp,
sequence = sequence,
id = Transcript.id)
SeqFastaAA
objects to data
argument:library(seqinr) #to create a fasta file with protein sequences
#write a FASTA file
seqinr::write.fasta(sequence = strsplit(at_nsp$sequence, ""),
name = at_nsp$Transcript.id, file = "at_nsp.fasta")
#read a FASTA file to a list of SeqFastaAA objects
At_seq_fas <- read.fasta("at_nsp.fasta",
seqtype = "AA",
as.string = TRUE)
input4 <- scan_ag(data = At_seq_fas)
.FASTA
file to be analyzed as string:input5 <- scan_ag(data = "at_nsp.fasta") #file at_nsp.fasta is in the working directory
AAStringSet
object:dat <- Biostrings::readAAStringSet("at_nsp.fasta") #file at_nsp.fasta is in the working directory
input6 <- scan_ag(data = dat)
All of the outputs are equal:
all.equal(input1,
input2)
#> [1] TRUE
all.equal(input1,
input3)
#> [1] TRUE
all.equal(input1,
input4)
#> [1] TRUE
all.equal(input1,
input5)
#> [1] TRUE
all.equal(input1,
input6)
#> [1] TRUE
The only exceptions to this design are the plotting function plot_prot()
which requires protein sequences to be supplied in the form of string vectors (input1 in the above example) and pfam2go()
which does not take sequences as input.
All ragp
functions return basic R data structures such as data frames, lists of vectors and lists of data frames, making them convenient for manipulation to anyone familiar with R. An especially effective way to manipulate these objects is by utilizing the tidyverse
collection of packages, especially dplyr
and ggplot2
. Several dplyr
functions that will be especially handy for data wrangling are:
dplyr::left_join()
dplyr::mutate()
dplyr::group_by()
dplyr::summarise()
dplyr::filter()
dplyr::distinct()
Examples on usage of these functions on objects returned by ragp
functions are provided in HRGP filtering and HRGP analysis tutorials. Additionally there are extensive examples on the internet on usage of the mentioned functions.
Obtaining pretty visualizations is usually the goal of the above mentioned data manipulations. The golden standard of R graphics at present is the ggplot2 package and we recommend it to graphically summarize the data. Additionally ragp
contains plot_prot()
function which is a wrapper for ggplot2
, and while plot_prot()
can be used without knowing ggplot2
syntax, to tweak the plot style at least a basic knowledge of ggplot2
is required. Examples are provided in protein sequence visualization tutorial.
This software was developed with funding from the Ministry of Education, Science and Technological Development of the Republic of Serbia (Projects TR31019 and OI173024).


--- layout: default nav: attributes > ic-select-from-response ---
ic-select-from-response
- The Response Selector AttributeThe response selector attribute can be used to select the element to take the inner HTML from in a a server response.
The value of the attribute should be a valid selector of the element to take the content from.
This attribute may be placed on parent elements, allowing you to specify behavior across multiple elements.
Here is a simple example of a response selector filtering a full HTML document for a list:


HTML 5 Boilerplate
A ready-made frontend template based on HTML5, CSS3 and Javascript used to build scalable and robust static website
Dependencies
Material Design Lite (MDL) is a Css and Javascript library which lets you add a Material Design look and feel to your static content websites.
Modernizr is a JavaScript library that detects the features available in a user's browser. This lets web pages avoid unsupported features by handling it in the code.
jQuery is a JavaScript library designed to simplify HTML DOM tree traversal and manipulation, as well as event handling, CSS animation, and Ajax.


--- layout: page permalink: /providers/email/ title: "Private Email Providers" description: "Find a secure email provider that will keep your privacy in mind. Don't settle for ad-supported platforms. Never trust any company with your privacy, always encrypt." --- {% include legacy/sections/email-warning.html %} {% include legacy/sections/email-providers.html %}
Please note we are not affiliated with any of the providers we recommend. This allows us to provide completely objective recommendations. We have developed a clear set of requirements for any Email provider wishing to be recommended, including implementing industry best practices, modern technology and more. We suggest you familiarize yourself with this list before choosing an Email provider, and conduct your own research to ensure the Email provider you choose is the right choice for you.
Operating outside the five/nine/fourteen-eyes countries is not necessarily a guarantee of privacy, and there are other factors to consider. However, we believe that avoiding these countries is important if you wish to avoid mass government dragnet surveillance, especially from the United States. Read our page on global mass surveillance and avoiding the US and UK to learn more about why we feel this is important.
Minimum to Qualify:
Best Case:
We regard these features as important in order to provide a safe and optimal service to users. Users should consider the provider which has the features they require.
Minimum to Qualify:
Best Case:
gpg --locate-key<EMAIL_ADDRESS>We prefer our recommended providers to collect as little data as possible.
Minimum to Qualify:
Received
header field.Best Case:
Email servers deal with a lot of very sensitive data. We expect that providers will adopt best industry practices in order to protect their users.
Minimum to Qualify:
p
value set to either none
, quarantine
or reject
.Best Case:
You wouldn't trust your finances to someone with a fake identity, so why trust them with your email? We require our recommended providers to be public about their ownership or leadership. We also would like to see frequent transparency reports, especially in regard to how government requests are handled.
Minimum to Qualify:
Best Case:
With the email providers we recommend we like to see responsible marketing.
Minimum to Qualify:
Must not have any marketing which is irresponsible:
Best Case:
While not strictly requirements, there are some factors we looked into when determining which providers to recommend.
End-to-end encryption (E2EE) is a way of encrypting email contents so that nobody but the recipient(s) can read the email message.
The standard way to do email E2EE and have it work between different email providers is with OpenPGP. There are different implementations of the OpenPGP standard, the most common being GnuPG and OpenPGP.js.
There is another standard that was popular with business called S/MIME, however it requires a certificate issued from a Certificate Authority (not all of them issue S/MIME certificates). It has support in Google Workplace and Outlook for Web or Exchange Server 2016, 2019.
Email providers which allow you to use standard access protocols like IMAP and SMTP can be used with any of the email clients we recommend. This can be less secure as you are now relying on email providers to ensure that their encryption implementation works and has not been compromised in anyway.
A smartcard (such as a Yubikey or Nitrokey) works by receiving an encrypted email message from a device (phone, tablet, computer etc) running an email/webmail client. The message is then decrypted by the smartcard and the decrypted content is sent back to the device.
It is advantageous for the decryption to occur on the smartcard so as to avoid possibly exposing your private key to a compromised device.
Email metadata is able to be seen by your email client software (or webmail) and any servers relaying the message from you to any recipients. Sometimes email servers will also use external parties to protect against spam.
Email software will often show some visible headers that you may have seen such as: To
, From
, Cc
, Date
, Subject
.
Client software may use it to show who a message is from and what time it was received. Servers may use it to determine where an email message must be sent, among other purposes not transparent to the user.
Email metadata is stored in the message header of the email message.
Email metadata is crucial to the most basic functionality of email (where it came from, and where it has to go). E2EE was not built into the email protocols originally and is also optional, therefore, only the message content is protected.
When emails travel between email providers an encrypted connection is negotiated using Opportunistic TLS. This protects the metadata from outside observers, but as it is not E2EE, server administrators can snoop on the metadata of an email.
AnonAddy lets users create aliases that forward to their email address. Can be self-hosted. Source code on GitHub.
SimpleLogin allows you to easily create aliases for your email. Can be self-hosted. Source code on GitHub.
Advanced users may consider setting up their own email server. Mailservers require attention and continuous maintenance in order to keep things secure and mail delivery reliable.
Mail-in-a-Box is an automated setup script for deploying a mail server on Ubuntu. Its goal is to make it easier for users to set up their own mail server.
Mailcow is a more advanced mail server perfect for those with a bit more Linux experience. It has everything you need in a Docker container: A mailserver with DKIM support, antivirus and spam monitoring, webmail and ActiveSync with SOGo, and web-based administration with 2FA support. Mailcow Dockerized docs
For a more manual approach we've picked out these two articles.


Profile
Education
Experience
Projects
Interview
Blog
Bucket List
My Map
Quotes
My Recipes
Tyler Citrin
I code, play soccer, like cats, and think a lot.
I finally decided to put my thoughts to paper
//


| Use && and || Operators Like a Boss | |
|---|---|
function getMeBeers(count){ if(count){ return count; } else{ return 1; } } |
function getMeBeers(count){ return count || 1; } |
| Use === and !== Instead of == and != | |
|---|---|
10 == '10' //true 10 === '10' //false 10 === 10 //true |
The operators == and != do automatic type conversion, if needed. But === and !== will consider both value and type while comparing and won't do any automatic type conversion. So, to reliably compare two values for equality/non-equality always use === and !==. |
| Use Strict mode while writing JS | |
|---|---|
<script type="text/javascript"> 'use strict' //Strict mode code goes here </script> |
Strict mode was introduced in ECMA 5. It allows you to put a function or an entire script into strict operating context. The benefits are: - It eliminates some of the silent JavaScript errors by throwing the errors explicitly. - It throws exceptions when relatively unsafe actions take place. - Sometimes strict mode code can run faster than non strict mode code. |
| Use splice() to remove an array element | |
|---|---|
var array=[1,2,3]; delete array[1]; // now array= [1,undefined,3] array.splice(1,1); //now array=[1,3] |
If you want to remove an element from an array use splice() instead of delete. delete sets the particular array item to undefined while splice() actually removes the item. |
| Use [] to create new array | |
|---|---|
var a = { name:'John Doe', email<EMAIL_ADDRESS>} |
Use [] to create a new array. Writing var a=[1,2,3] will create a 3-element array whereas new Array(N) will create a physically empty array of N logical length. Similarly, use var a={} to create an object rather than new Object(). The former one is compact, readable and takes less space. You can also instantly populate the object like: |
| Use String.link() to create Hyperlinks | |
|---|---|
var text="Cool JS Tips"; var url="http://www.htmlxprs.com"; var block=''+ text +''; |
Many times in JavaScript you will need to generate HTML anchors on the fly. For that you will need some concatenation which may look ugly and messy.
Instead, how about this:
var block=text.link(url); // Cool JS Tips |
| Cache the length while looping | |
|---|---|
for (var i=0,length=array.length;i<length;i++){ //awesome code goes here } |
While looping through a JavaScript array you can cache the length so that the overall performance is better. Be careful while creating an inner loop. You need to name the length variable differently in the inner one. |
| Put 'var' before your variable name | |
|---|---|
var localVar=12; //this is a local variable globalVar=12; //variable goes to 'window' global |
While creating variables don't forget to use the var keyword. If you forget then the variable gets added to the global scope which is definitely a bad thing. |
| Use Closures and Self Executing Functions | |
|---|---|
var car=(function(){ var _name='Benz Velo'; return { getName: function(){ return _name; } } })(); //function created and invoked console.log(car.getName()); //Logs Benz Velo |
Closures, if used carefully and precisely, can take your JS code to a whole new level. There are plenty of tutorials available which can teach you about closures. I will just give an example of closures and self executing functions for creating modular code. As you see we just created a function and immediately invoked it. These are called self executing functions or Immediately Invoked Function Expression (IIFE). The function returns an object which is stored in variable car. We also used closure because the object being returned can access the variable _name defined by the parent function. This is helpful for creating modules and emulating private variables. |


The IEU GWAS database comprises over 10,000 curated, QC’d and harmonised complete GWAS summary datasets and can be queried using an API. See here for documentation on the API itself. This R package is a wrapper to make generic calls to the API, plus convenience functions for specific queries.
Methods currently implemented:
There are a few convenience functions also:
See [https://github.com/MRCIEU/gwasglue] for information about how to connect the genotype and LD data to other packages involving colocalisation, finemapping, visualisation and MR.
You can install the developer version of ieugwasr with:
devtools::install_github("mrcieu/ieugwasr")
Browse the vignettes etc for information on how to use this package: https://mrcieu.github.io/ieugwasr/


Money Play. How should Red play 64?
pips Red=165 White=138
(CorrectAnswer= 0/0, ErrorScore= 0)
Over the board I hit with 13/3* but that is the wrong game plan as Red doesn’t have the ammunition for an attack.
It is better to play to prime White’s rear checkers by making the key bar-point and 5-pt. To that end the best play is 17/13, 17/11 which dismantles an awkward point and puts the builders in good positions. 13/3* is a blunder.
It is better to play to prime White’s rear checkers by making the key bar-point and 5-pt. To that end the best play is 17/13, 17/11 which dismantles an awkward point and puts the builders in good positions. 13/3* is a blunder.
1. Cubeful 2-ply 17/13 17/11 Eq.: +0.159 0.545 0.145 0.006 - 0.455 0.119 0.002 2. Cubeful 2-ply 13/3* Eq.: +0.093 (-0.066) 0.528 0.159 0.009 - 0.472 0.156 0.003 3. Cubeful 2-ply 8/2 6/2 Eq.: +0.055 (-0.104) 0.514 0.157 0.007 - 0.486 0.145 0.003 4. Cubeful 0-ply 13/7 8/4 Eq.: -0.048 (-0.207) 0.493 0.133 0.007 - 0.507 0.167 0.004 5. Cubeful 0-ply 17/11 8/4 Eq.: -0.075 (-0.234) 0.487 0.135 0.008 - 0.513 0.179 0.005


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