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or where the journey begins Have you ever thought of having your own open source project? I bet you have — you’re reading this article. Maybe you are thinking about it right now. Maybe you came here to better know what to expect, what challenges you’re going to face and how to deal with them. Well, you’ve come to the right place. In the following series of articles I’m going to share my personal experience in owning an open source project. Owning. Not contributing to an open source project but owning one. There is a big difference and in this series we’re going to learn why. Table of content: Intro Starting a project Documentation Publicity Issues and PRs (WIP) Automation (WIP) Versions management (WIP) Who I am My name is JeB and I’ve been maintaining a few open source projects for a couple of years. The most popular one and the one from which I’ve learnt the most is . At the moment of writing this article it has ~600 stars on Github and about 400k monthly downloads. @angular-builders Yes, it’s not even close to huge projects like Angular or React but I feel that I have enough experience to share with you in order to help you avoid the same mistakes I did and more important — to understand the cost of owning an open source project. So what is open source? Let’s first establish a common language and align on key terms and definitions. What is open source? Here is a very generic from a well known Encyclopedia (aka Wikipedia): definition Open Source is the concept of the information allowing the replication or modification of something being open to the public. Open source or, in terms of models: software development The open-source model is a decentralized model that encourages . A main principle of is , with products such as source code, , and documentation freely available to the public. software development open collaboration open-source software development peer production blueprints In the case of Wiki we have those who edit the articles ( ) and those who approve the edits (more experienced members, moderators). If we project it onto the software world the editors would form a core team of an open source project and the contributors would be, well, contributors. contributors Wikipedia is a huge open source project but it has all started from . Wikipedia was born from Nupedia and it was born for a reason: something small Despite its mailing list of interested editors, and the presence of a full-time editor-in-chief, , a graduate student hired by Wales, the writing of content for Nupedia was extremely slow, with only 12 articles written during the first year. Larry Sanger philosophy So here’s where the first question comes: Why bothering with open source As you can imagine from the previously read one of the main reasons for opening something to the wider audience is to gain collaborators. Together we’re strong (Zarya, 2016) At the moment of writing this article Wikipedia 37,899,499 registered accounts of which 134,022 are actively editing. has Just think of it… Oh, and it 6M content pages! 134,022 active collaborators. has Would the numbers have been the same if Nupedia didn’t move to open source model? I highly doubt it. Nothing is different when it comes to the software. In order to solve a certain problem you have to write code. In order to solve a big problem you have to write a lot of code. In order to solve it properly you have to write high quality code, make a high quality design etc. All this which, let’s be honest, you don’t have. You have a rent to pay after all. requires resources, While gaining collaborators is a reasonable incentive, almost no one starts a new open source project solely because of it. Obviously the reasons might be different but let’s talk about most popular ones. Careful what you wish for A few scenarios that come across my mind are: You face a problem, there is nothing out there that solves it for you (or there is something but it costs money) so you have to solve it yourself, you manage to solve it, you’re really excited about your work and you think others can benefit from it. You want to be recognized as founder of an open source project, you want this fancy line in your CV, you have an ego (we’re all human after all). If this is the for you then I promise you, after reading this series you’ll reconsider — it’s not worth it. main reason You face a problem, there is an open source project that actually solves it for you but it’s not good enough (in your opinion) or doesn’t have the exact feature you need. If you create a new open source solely because of this then you’re at #2 (ego). Make yourself a contributor, create a PR to the existing project instead. most probably If the existing project has a different vision and making a PR is not an option you should consider either extending it by reusing its functionality in your project or forking it. It may save you a lot of headache later. You face a problem, there is nothing out there that solves it for you and you think that starting the solution as open source from the very beginning is a very good idea. It’s not. Solve the problem, make sure it works for you and after that go to #1. These are the 4 incentives I find most popular for creating a new open source project but in this series we’re going to focus mainly on scenario #1. The reason is simple — I believe that if the for starting an open source project is other than eagerness to share and contribute then this won’t hold. For quite a long time the fact that you’re helping someone might be the only reward you get. And if this is not the kind of satisfaction you’re looking for then maybe you should stop here and not waste your time. main reason There is another quite popular scenario which is worth to mention. There are companies that open part of their code to the community. For example, Angular (maintained by Google), React (maintained by Facebook), VSCode (maintained by Microsoft) and more. The reasons for them to do that may vary but gaining collaborators and contributing to community are surely among them. While I can’t argue with the importance of this practice, this scenario is quite different from the others because employees that maintain such projects get paid for their job. If you work at a company that considers the possibility of creating an open source project, the majority of the content here will be still relevant for you, however the incentives might be different. Wrapping it up If I had to summarize this part in one sentence it would be: Make sure your intentions match your expectations Believing that you want to have an open source project is not the same as actually having one, as you will see in the following articles. Thanks for reading, make sure you follow me here or on if you don’t want to miss the next part in which we’re going to talk about actually . Twitter Starting an open source

Open Source Series: Intro

or how to open your project to the world Hello and welcome to the second part of the “Open Source” journey. For those of you who haven’t read the or wonder what is the planned content for the next parts: first part Table of content Intro Starting a project Documentation Publicity Issues and PRs (WIP) Automation (WIP) Versions management (WIP) Recap In the previous part we’ve discussed what is Open Source and why anyone would bother with that. In this part we’re going to get more practical and we’ll discuss how one actually starts an open source project. So you’re in scenario #1, you have a solution for a specific problem and you’re eager to share it with the world. Let’s emphasize it again: It’s not about your ego You’re not hoping to benefit from it You truly want to help others with the same problem If you answered yes to all of these then here is a quick checklist for you to make sure you’re doing the right thing: Make sure that open source is the right format. If it’s something small that you want to share with the world then a small blog post might be just enough. Double check that a similar project doesn’t exist already. Maybe your solution makes a perfect PR for an established open source project. Be prepared for what’s coming As I mentioned, owning an open source project carries a lot of difficulties. One difficulty that stands out is that it requires a lot of your time. Everything that you do for your open source requires time, whether it’s writing code, managing issues, updating dependencies, talking to people, answering questions and etc. Every minute that you invest into your open source is a minute that you could have but didn’t invest in your family, your hobby, your health and what not. The only thing that you can do about it is delegation. When (or should I say “if”) you have enough collaborators you can outsource part of your responsibilities to the people you trust. Code separation So here we go, you have a solution for your specific problem and you think others can benefit from that. It is still integrated within your code base and you probably don’t want to make the whole code base an open source (unless you do). First you have to separate this code from the rest of your code base. Start with refactoring …which will eventually cause all the code that is going to be opened to reside in a separate directory. Make it generic Make sure that the code in the new directory is generic and is not bound to your specific problem, make an abstraction layer if needed. As an example I started with a very specific need (coming from ) of adding custom loader for native modules to Angular build. angular-builders one of my other open source projects I could have created which would serve solely this very purpose. However, I realized that at a relatively low cost I can create a more generic solution that would solve similar (but not the same!) problems. This is how builder was born. native-module-builder custom-webpack Keep it simple Generic is great but be careful not to get too excited about that. Premature optimization and over-generalization are two very well known problems in software engineering. You should find this sweet spot where your solution solves problems other than yours but not all the problems in the world. If you build a scale where the solution for your specific problem is 1 and a solution for all the world problems is 100 then you should start with 2. Your generic code should be able to solve a a few more problems than your specific code. Eat your own dog food Keep using this generic code in your code base at every step — doing so makes sure you eliminate the unnecessary parts and leave only what’s needed. It also ensures that the code you’re going to open is working properly. Remember, you are the very first user of your open source project. Don’t get sued If you’re extracting the code from your company code base consult with your superiors and if needed with the legal department. Make sure that they support your initiative and that the code you’re going to open is not subject to the IP (intellectual property) of your company. This will also help you to decide which is more suitable for your project. open source license When everything is working, the code is separated and is generic enough, you have all the approvals (if needed) - it is time to open it to the world. Opening the project to the world Once your open source code is separated and generalized it’s time to disconnect it completely from your code base. Going public First, you have to open the source code of your project (at the end of the day that what makes it an Open Source Project!). There are for hosting source code online but we’ll go with the default — Github. different options on Github Create a new repo Clone the repository Move the sources from the directory you previously created (don’t remove the directory yet). Commit & push — voila it’s now an open source project. Or is it? Creating a package Your project is publicly available, but no one is using it (including you, since you’re using a copy of this code within your larger code base), and no one is aware of its existence. Furthermore the only format in which your project is publicly available on the web is the , and the only way to consume it is copy-pasting the code into ones code base. Not a very convenient way, don’t you think? source code In order to properly distribute your project you have to: Create a package out of the source code Make this package available on one of the public package registries (depends on your ecosystem, for example, for Java it might be , in the case of JavaScript it might be and etc.) Maven Central Repository Npm Package Registry This is when you add a build chain to your new shiny repository, define project name etc. I’m not going to break down the whole process because it is very dependent on your ecosystem, set of tools and language you are using. You might be an all around person to whom defining a new project as well as adding a build chain and publishing the package is a piece of cake. If this is the case — good for you! You also might be a person that is used to only write code but never faced all these definitions, configurations, artifacts and stuff like that. It might be a whole new world to you. Well, time to learn. Not going to be quick, I promise you that. In any case When you’re done with filling all the missing puzzle pieces in your head, you’ve learned everything about the relevant package registry and your package is actually published, can you truly consider your project open source. then and only then At this point you can actually tell people: “Hey, I already have a solution to your problem, just add this package to your project and use it!” Sanity check Before your project goes viral you better make sure it works. A sanity check for your package would be actually removing the generic directory from your larger code base and use the publicly available package instead. After all, . you’re the very first user of your open source project Further development When you start using the package in your code base the development flow is likely to change: previously the now-open-source-code has been a part of your code base; you could consume the changes right away but now it’s as much of an external package as any other 3rd party package used in your code. Thus, when you develop a new feature in your shiny new open source project you’ll have to publish it first in order to be able to consume it in your larger code base. However you cannot publish it if you aren’t positive it works, because once published it might affect other users. So here are a few things you can do in order to avoid publishing broken versions: Cover your code with tests, both unit tests and end-to-end tests. I don’t think I have to convince you how important the tests are. Package and install the new version of the package locally, into your larger code base. Once verified that everything works as expected you may publish it. Publish a beta version which is available only for those who explicitly want it rather than to the whole world. For example in npm package registry there are dist tags that can be used for this purpose. The default tag is latest and when you run npm install mypackage it effectively runs npm install mypackage@latest . When you publish a new version under another tag, for instance beta , one will have to explicitly install from this tag in order to get the latest version: npm install mypackage@beta . Wrapping it up Unlike the previous part, which was completely theoretical, this part actually requires some work from you. Depending on your experience and learning abilities it might take you a few days or even weeks to complete this mandatory step. And we didn’t even start yet. This is why it is my duty to ask you again: Are you really prepared to give a decent amount of your precious time to the community? Thanks for reading, make sure you follow me here or on if you don’t want to miss the next part in which we’re going to talk about . Twitter Documentation

Open Source Series: Starting a Project

Since the reverse withstand voltage of the is limited, when used in a high- voltage environment, it is often necessary to use plurality of step-recovery rectifier diodes in series to meet the need of reverse withstand voltage. Due to the inconsistency in the volt-ampere characteristics, turn-on time, and recovery charges of the diode during the production process, the voltage sharing problem occurs when used in series, which causes the reverse voltage of a certain diode to be too high and damaged, disturbing the normal operation of other diodes, which ultimately affects the reliability and stability of the entire device. step-recovery diode 1. Characteristics and Factors of Uneven Voltage of the Diode 1.1 Characteristics Diodes are very commonly-used power electronic devices. Generally, we are easier to miss the key parameters of familiar devices, and only care about macroscopic parameters on the macro level, such as reverse withstand voltage, on-state current, and reverse leakage current. While the junction capacitance, turn-off and turn-on characteristics of the diode are easily overlooked. 1.2 Uneven Voltage Problem The main reason for the voltage sharing problem may be caused by either internal reasons or external ones. The internal reasons is related to the processing technology, and the external cause is about the external circuit. The volt-ampere characteristics of the diodes produced in the same batch are inconsistent, resulting in static uneven voltage of the diode; the inconsistency between the reverse recovery time and the on state state causes the dynamic uneven voltage of the diode. External circuit design can cause stray inductance and capacitance, which can cause uneven voltage problems in high-voltage high-frequency environments. 2. Analysis of the Uneven Voltage Problem 2.1 Analysis in Macroscopic Scale At the macro level, the diodes in series does not need to have voltage sharing, the main consideration is the influence of the diode itself. As shown in Figure 1, the two diodes are connected in series with an external reverse DC voltage. The diode with a small reverse saturation current can withstand a large voltage as the two diodes are connected in series, and the reverse saturation current is constant under an externally applied voltage rating. As shown in Figure 2, assumed that there is difference in the reverse saturation current between the two diodes, and the reverse saturation current of D2 is smaller, the above conclusion can be clearly drawn. FIG 1. Circuit of Two Diodes Connected in Series In actual operation, macroscopically, diodes have different voltage drops due to their own differences as shown in Figure 2. When the the voltage drop on D2 from the external voltage U increases reaches the critical point, the voltage drop of D1 is relatively small and still in the safe and stable region due to its large reverse saturation currents. FIG 2. Volt-ampere characteristics Diagram of Diode According to the above analysis, when U increases continuously. , the voltage drop on D2 will break through the critical transition voltage, causing the current to increase sharply. As D1 and D2 are connected in series in the main circuit, the current of D1 certainly increase with D2. However, the volt-ampere curve of D1 shows that the reverse voltage drop of D1 should reach the breakover voltage when a large current pass through it, so the sum of u1 and u2 is greater than U, which proves the speculation above is not true. Therefore, when U increases, the voltage of D2 will not continue to increase, and the voltage of D1 will keep increasing until its value is more than the sum of the reverse withstand voltages of the two tubes, at which point diode breakdown occurs. 2.2 Analysis in Microscopic Scale The pins and the layout of the diode on the board naturally evolve into and inductance in a high-voltage and high-frequency environment. The introduction of stray capacitance and inductance directly affects the turn-on and turn-off waveforms of the diode. stray capacitance The introduction of capacitance prevents a sudden change in voltage and the introduction of an  inductance prevents a sudden change in current. Figure 3 is the equivalent circuit diagram of the diodes in series at high frequency. In the figure, C1 is the junction capacitance, R is the reverse resistance, C2 is the stray capacitance at the high voltage, C3 is the stray capacitance formed by the diode to the ground. FIG 3. equivalent Circuit Diagram of series diodes at high frequency 3. Applications of Diodes in Series The high-frequency power supply of the electrostatic precipitator outputs high-frequency PWM waves, and the waves pass through the boosting transformer and the rectifier module to finally become an approximate linear voltage waveform. The rectifier module is integrated in the boosting transformer, and the diodes are in series. Because the voltage level is relatively high, it is generally considered to reach 10KV or more. Since the requirement for the accuracy of the output voltage waveform is not high, the diode can be directly connected in series, and the high-frequency rectifier diode is selected. The rectified output simulation waveform is shown in FIG. 4, and the measured waveform is shown in FIG. 5. FIG 4. Simulation Waveform FIG 5.  Measured Waveform As shown in the figures, the rectified output voltage has high and low peaks due to the influence of stray parameters. With the continuous development of science and technology, the manufacturing process of diodes is constantly improving, and the influence of its own factors is negligible. 4. Conclusion By simply analyzing the voltage sharing problem of the from both macroscopic and microscopic perspectives, it is concluded that when the diode is used in series in a high-voltage high-frequency environment, the diode itself will generate uneven voltage but not cause breakdown. series diode The uneven voltage generated by external factors is the result of breakdown of the diode, and it will cause even more serious problems.

Misunderstanding of Voltage Sharing Problem of Series Diode 

This is my C++ Telltales Series where I share some tips and tricks for C++ developers. Some of the parts are pretty basic stuff but might come in handy for some developers out there. In this story I collect links to the individual stories so they can be found from a single place. Feel free to check them out and use as you like — open source all the way! Part 1: Human-readable Thread ID Part 2: Shared Enum Operators Part 3: Shared Static Variable For All Template Class Instances Part 4: Forward Declarations and <iosfwd> Part 5: Protected and Private Inheritance Part 6: The Mapleton Pattern Part 7: The Object Pool Pattern Part 8: Same Name for a Function And a Class I will update this story when new part is published and I try to publish a new one at least weekly so stay tuned! If you liked any of the stories, please press the ❤ button below (did you know that you can give more than one clap). Also please feel free to share this story! About me I am Heikki Hellgren, Software Expert and technology enthusiast working at . My interests are in software construction, tools, automatic testing and all the new and cool stuff like AI and autonomous driving. You can follow me on and and check out my for more information. Elektrobit Automotive Medium Twitter website

C++ Telltales Series

Comments, notes, and suggestions from the Mediumsphere. Are we clapping or are we not? Personally I’m clapping! I’m a big fan of Medium, almost an addict! And I’ve already on ’s post and spread my love for , the new product that the company debuted a few days ago. commented katie zhu Series Photo credits: katie zhu Of course, as every newly-released product, it’s going to receive lots of scrutiny — in particular from the Medium community who loves the product as it is and often times seems to adjust slowly to changes. Like me, many Mediumers are addicted to Medium — in a good way! — and enjoy the simple, elegant, networked storytelling it allows. How not to agree with when they write: “To Medium, we LOVE your platform! We all think it is great for everyone to express themselves.” Formed News _Just yesterday we told you our plan for Formed News and how we would be using social media to interact with you all in…_medium.com How WE are going to use the “Series” feature here on Medium… In a way, Medium is also polarizing and some users seem either projected away from the platform or critical of it because of the changes and the recent re-focus efforts by and the management. Ev Williams For example writes: “This seems mot much different from starting a publication and adding new contributions to it. So I doubt it will be a game-changer at all. Also ANDROID-Users are excluded from this feature :-(.” Stephan Jaeckel “I’ve been using Medium for about three years now and, as I stated recently, I’m not going anywhere,” says in a post on the launch of . Justin Cox 🍩 Series Series’ are Medium’s venture into serialized storytelling. This is HUGE for the fiction community. _I’ve been using Medium for about three years now and, as I stated recently, I’m not going anywhere. In that time Medium…_writingcooperative.com The Future of Storytelling on Medium He adds: “While this is one of the coolest evolutions Medium has made in awhile, the killer feature is that users can to ’. This means a is meant to be . When a writer hits publish, the story doesn’t have be over. Followers are notified each time a is updated.” subscribe Series Series updated Series And in fact, earlier in February, wrote about Ev’s announcement at _Upfront Summit: “_In the next couple months, Medium will be releasing one of it’s biggest features yet: a subscription model.” Dakota Shane _At Upfront Summit, Ev Williams made an enormous announcement. In the next couple months, Medium will be releasing one…_medium.com Wow, It’s Official — The Subscription Model is Coming to Medium… How that subscription model will roll out remains to be seen, but it seems that is part of the new model that Medium is trying to embrace to bring revenues. Series “With this new form of storytelling, more influencers will (hopefully) be attracted to Medium in addition to big brands and publishers,” says Dakota. “And wherever these folks go, the money follows shortly after.” _I’m sure we’ve all been wondering, WTF is the new Series feature we’re seeing on our Medium mobile app? I know I was._medium.com WTF is Medium’s New “Series” Feature, and What Does It Mean For Us? One thing that many are agreeing on is the Snapchat-inspired capabilities of . Series But this is “a good thing” as puts it. Steve Cole _Snapchat for actual stories and why that’s a good thing_medium.com Medium “Series”👏🏽👏👏🏿👏🏾 “At first glance, it looks like yet another version of the feature known originally from Snapchat,” says . “But after checking a couple of series on Medium, especially ones with more serious content like the series by , it feels different.” Adam Juras Melinda Gates _A couple of days ago I wrote about the new Stories feature from Snapchat, Instagram and WhatsApp, concluding with a…_medium.com Stories, Status, Series and other words that start with S Interesting what writes: Abhishek Chakraborty Millennials and teens are famous for their short attention span. They seem to love things which don’t demand a lot of cognition or thinking. For example, you can express your creativity easily through Snapchat by clicking a picture and then drawing some stuff over it. Or just go to plain old Instagram and put some photo filters. There you are…awesome result with minimal effort. Instant gratification. Hedonism at its best! Medium used to be different. Medium needed a lot of attention. It takes some effort to write your own story, or even read someone else’s story. It takes some time in processing and understanding the text, and then retaining the knowledge to gain fulfilment or gratification. When I have another platform where I can get this pleasure so easily, then why waste so much of energy here, right? Why don’t I go and read some Snapchat stories before they disappear? Medium was burning money and firing employees, so they needed some feature to tap into the attention deficient citizens of the internet who are the major sources of company valuation. Hence ! Series _We Already Had Stories. So Now We’ve Built Series. Beat That!_blog.prototypr.io How Medium is Trying to be The Snapchat For Text Many Medium users are now experimenting wth . Series Here is my first attempt at : Series _View the series Digital Diplomacy on Medium. Series are a new type of immersive, episodic story format._medium.com Digital Diplomacy on Medium - Medium “What interests me is using the series format as a way to tell an on-going piece of fiction, or maybe one that plays out in bite-sized segments,” says . Elliot Nichols _The development of Series here on Medium is interesting to me. You don’t need me to explain what the new mobile-only…_medium.com I’m trying out my first series comments: “The great thing about this is it gets people to start publishing now and not wait until everything is perfect.” Herrin medium.com This is awesome! After using , has published a few notes, ranging from how to share the new stories to linking them to a Medium profile. Series Sebastián GdeLyL _Dear Medium and Your Friends @ Medium,_medium.com Quick notes about Series Some other users like are waiting to use it and are reflecting on the tool. He writes: Zac Chapepa - It’s a cool feature. - I’m probably going to use it often, perhaps create one myself. - It is fun but how many would I have to read? - What happens if I love the series more than the stories in my feed? - Are publications dead? ____ __medium.com On board the new Series… Similarly, posts a few thoughts and recommendations about Series. Michael Cohen _@Medium looks committed to this. You don’t put something in the top-left corner of your app if you want to hide a…_medium.com Five thoughts on the new platform: “Is good for Medium?,” asks . “Is it an improvement or a downgrade?.” Series Tanner Brodess _What do all great songs, movies, books and stories have in common?_medium.com Is “Series” Good For Medium? Food for thought!

How do you like Medium’s Series?

Time-Series Modeling and Forecasting with AutoGluon In the previous article, we explored key concepts and techniques for understanding and preprocessing time-series data. This included visualization, decomposition, stationarity assessment, autocorrelation analysis, and outlier detection. With a solid grasp of the data's characteristics, we are now prepared to model the time-series and generate forecasts. For this task, we will leverage AutoGluon, an AutoML toolkit that streamlines the process of training and evaluating multiple models in parallel. AutoGluon's time-series capabilities allow us to quickly experiment with a diverse set of modeling techniques, identify the best-performing approaches, and explore their strengths and limitations. Experimental Setup We continue working with the hourly U.S. energy consumption dataset from 2015 to 2018. After importing the necessary libraries and preprocessing steps, we convert the data into the TimeSeriesDataFrame format required by AutoGluon: import pandas as pd
from autogluon.timeseries import TimeSeriesDataFrame, TimeSeriesPredictor

df = pd.read_csv('AEP_hourly.csv', sep=',')
# ... preprocessing steps ...

single_series_ts = TimeSeriesDataFrame.from_data_frame(
    df_single_series,
    id_column='item_id',
    timestamp_column='datetime'
) To assess model performance, we split the data into training and test sets, reserving the most recent 30 days (720 hours) for testing: train_df_single, test_df_single = single_series_ts.train_test_split(24*30) Single Time-Series Modeling We begin by modeling the electricity consumption as a single univariate time-series, excluding any additional covariate information: predictor = TimeSeriesPredictor(
    prediction_length=30*24,
    target='elec_cons',
    eval_metric='RMSE',
    freq='H'
)

predictor.fit(
    train_df_single,
    presets='fast_training',
    num_val_windows=6,
    refit_full=True
) AutoGluon's TimeSeriesPredictor fits a variety of models in parallel, evaluating their performance on validation windows from the training data. This allows the toolkit to automatically select the best-performing models and stack/ensemble them for robust predictions. Please note that the configuration we have chosen for this example uses ‘fast_training’ configuration, and there are three more configurations that train the models as follows: We can inspect the leaderboard of models evaluated during training and on the test set: predictor.leaderboard(train_df_single)
predictor.leaderboard(test_df_single) If you observe that the test score is lower than the training data, it indicates that the model is not fully optimized, suggesting the potential for further improvement through comprehensive hyperparameter tuning. To quantify the accuracy, we compute error metrics like root mean squared error (RMSE), mean absolute percentage error (MAPE), and mean absolute scaled error (MASE) on the test set: error_dict = predictor.evaluate(test_df_single, metrics=['MAPE', 'RMSE', 'MASE']) Multivariate Time-Series Modeling With Covariates While univariate models rely solely on the target series' historical values, we can potentially improve forecasting accuracy by incorporating additional covariate information. In our case, we can provide relevant datetime-derived features like the day of the week, week of the year, the hour of the day, etc. as known covariates: known_covariates = ['weekday', 'week', 'day', 'hour', 'date', 'month', 'year']

full_df = TimeSeriesDataFrame.from_data_frame(
    df,
    id_column='item_id', 
    timestamp_column='datetime'
)

predictor_full = TimeSeriesPredictor(
    prediction_length=30*24,
    target='elec_cons',
    eval_metric='RMSE',
    known_covariates_names=known_covariates,
    freq='H'
) We then fit this multivariate model, again, utilizing AutoGluon's automated machine-learning capabilities: predictor_full.fit(
    train_df_full,
    presets='fast_training', 
    num_val_windows=6,
    refit_full=True
) Inspecting the leaderboards and evaluating the test set allows us to assess the incremental impact of including covariate information compared to the univariate approach. predictor.leaderboard(test_df_full) Results and Discussion The error metrics computed on the test sets quantify the predictive performance of the single and multivariate time-series models. We can analyze these results to understand the relative strengths of each approach and identify areas for further investigation or improvement. Some potential findings and insights: Univariate models may suffice if the time-series exhibit strong temporal dependencies and periodic patterns that can be captured from historical values alone. Including relevant covariates often boosts predictive accuracy by injecting supplementary information to better model complexities like daily/weekly/yearly seasonalities. The relative performance of different model classes (e.g., ARIMA, Prophet, transformers) can guide our selection of techniques to prioritize for this specific domain and data characteristics. Error distributions across different prediction horizons may reveal performance degradation over longer forecast ranges, highlighting opportunities for advanced techniques tailored to long-range forecasting. While this automated modeling process is efficient for rapid experimentation, careful data preparation, feature engineering, and human oversight remain critical for achieving optimal results. The leaderboard model performances provide a starting point for iterative improvements and deeper technique-specific tuning. Conclusion In this article, we demonstrated how to leverage AutoGluon's AutoML capabilities to streamline the process of training and evaluating diverse time-series forecasting models. We explored both univariate and multivariate modeling approaches, incorporating relevant covariate information to potentially boost predictive performance. The empirical results and error analyses facilitated by AutoGluon enable practitioners to quickly identify high-performing model classes and gain insights into their respective strengths and limitations for the given data characteristics. This serves as a strong foundation for further tuning, ensembling, and developing bespoke solutions tailored to the specific time-series forecasting problem at hand. References https://auto.gluon.ai/stable/tutorials/timeseries/forecasting-quick-start.html Time-Series Modeling and Forecasting with AutoGluon Time-Series Modeling and Forecasting with AutoGluon In the previous article, we explored key concepts and techniques for understanding and preprocessing time-series data. This included visualization, decomposition, stationarity assessment, autocorrelation analysis, and outlier detection. With a solid grasp of the data's characteristics, we are now prepared to model the time-series and generate forecasts. For this task, we will leverage AutoGluon, an AutoML toolkit that streamlines the process of training and evaluating multiple models in parallel. AutoGluon's time-series capabilities allow us to quickly experiment with a diverse set of modeling techniques, identify the best-performing approaches, and explore their strengths and limitations. Experimental Setup Experimental Setup We continue working with the hourly U.S. energy consumption dataset from 2015 to 2018. After importing the necessary libraries and preprocessing steps, we convert the data into the TimeSeriesDataFrame format required by AutoGluon: import pandas as pd
from autogluon.timeseries import TimeSeriesDataFrame, TimeSeriesPredictor

df = pd.read_csv('AEP_hourly.csv', sep=',')
# ... preprocessing steps ...

single_series_ts = TimeSeriesDataFrame.from_data_frame(
    df_single_series,
    id_column='item_id',
    timestamp_column='datetime'
) import pandas as pd
from autogluon.timeseries import TimeSeriesDataFrame, TimeSeriesPredictor

df = pd.read_csv('AEP_hourly.csv', sep=',')
# ... preprocessing steps ...

single_series_ts = TimeSeriesDataFrame.from_data_frame(
    df_single_series,
    id_column='item_id',
    timestamp_column='datetime'
) To assess model performance, we split the data into training and test sets, reserving the most recent 30 days (720 hours) for testing: train_df_single, test_df_single = single_series_ts.train_test_split(24*30) train_df_single, test_df_single = single_series_ts.train_test_split(24*30) Single Time-Series Modeling Single Time-Series Modeling We begin by modeling the electricity consumption as a single univariate time-series, excluding any additional covariate information: predictor = TimeSeriesPredictor(
    prediction_length=30*24,
    target='elec_cons',
    eval_metric='RMSE',
    freq='H'
)

predictor.fit(
    train_df_single,
    presets='fast_training',
    num_val_windows=6,
    refit_full=True
) predictor = TimeSeriesPredictor(
    prediction_length=30*24,
    target='elec_cons',
    eval_metric='RMSE',
    freq='H'
)

predictor.fit(
    train_df_single,
    presets='fast_training',
    num_val_windows=6,
    refit_full=True
) AutoGluon's TimeSeriesPredictor fits a variety of models in parallel, evaluating their performance on validation windows from the training data. This allows the toolkit to automatically select the best-performing models and stack/ensemble them for robust predictions. Please note that the configuration we have chosen for this example uses ‘fast_training’ configuration, and there are three more configurations that train the models as follows: TimeSeriesPredictor We can inspect the leaderboard of models evaluated during training and on the test set: predictor.leaderboard(train_df_single)
predictor.leaderboard(test_df_single) predictor.leaderboard(train_df_single)
predictor.leaderboard(test_df_single) If you observe that the test score is lower than the training data, it indicates that the model is not fully optimized, suggesting the potential for further improvement through comprehensive hyperparameter tuning. To quantify the accuracy, we compute error metrics like root mean squared error (RMSE), mean absolute percentage error (MAPE), and mean absolute scaled error (MASE) on the test set: error_dict = predictor.evaluate(test_df_single, metrics=['MAPE', 'RMSE', 'MASE']) error_dict = predictor.evaluate(test_df_single, metrics=['MAPE', 'RMSE', 'MASE']) Multivariate Time-Series Modeling With Covariates Multivariate Time-Series Modeling With Covariates While univariate models rely solely on the target series' historical values, we can potentially improve forecasting accuracy by incorporating additional covariate information. In our case, we can provide relevant datetime-derived features like the day of the week, week of the year, the hour of the day, etc. as known covariates: known_covariates = ['weekday', 'week', 'day', 'hour', 'date', 'month', 'year']

full_df = TimeSeriesDataFrame.from_data_frame(
    df,
    id_column='item_id', 
    timestamp_column='datetime'
)

predictor_full = TimeSeriesPredictor(
    prediction_length=30*24,
    target='elec_cons',
    eval_metric='RMSE',
    known_covariates_names=known_covariates,
    freq='H'
) known_covariates = ['weekday', 'week', 'day', 'hour', 'date', 'month', 'year']

full_df = TimeSeriesDataFrame.from_data_frame(
    df,
    id_column='item_id', 
    timestamp_column='datetime'
)

predictor_full = TimeSeriesPredictor(
    prediction_length=30*24,
    target='elec_cons',
    eval_metric='RMSE',
    known_covariates_names=known_covariates,
    freq='H'
) We then fit this multivariate model, again, utilizing AutoGluon's automated machine-learning capabilities: predictor_full.fit(
    train_df_full,
    presets='fast_training', 
    num_val_windows=6,
    refit_full=True
) predictor_full.fit(
    train_df_full,
    presets='fast_training', 
    num_val_windows=6,
    refit_full=True
) Inspecting the leaderboards and evaluating the test set allows us to assess the incremental impact of including covariate information compared to the univariate approach. predictor.leaderboard(test_df_full) predictor.leaderboard(test_df_full) Results and Discussion Results and Discussion The error metrics computed on the test sets quantify the predictive performance of the single and multivariate time-series models. We can analyze these results to understand the relative strengths of each approach and identify areas for further investigation or improvement. Some potential findings and insights: Univariate models may suffice if the time-series exhibit strong temporal dependencies and periodic patterns that can be captured from historical values alone. Univariate models may suffice if the time-series exhibit strong temporal dependencies and periodic patterns that can be captured from historical values alone. Including relevant covariates often boosts predictive accuracy by injecting supplementary information to better model complexities like daily/weekly/yearly seasonalities. Including relevant covariates often boosts predictive accuracy by injecting supplementary information to better model complexities like daily/weekly/yearly seasonalities. The relative performance of different model classes (e.g., ARIMA, Prophet, transformers) can guide our selection of techniques to prioritize for this specific domain and data characteristics. The relative performance of different model classes (e.g., ARIMA, Prophet, transformers) can guide our selection of techniques to prioritize for this specific domain and data characteristics. Error distributions across different prediction horizons may reveal performance degradation over longer forecast ranges, highlighting opportunities for advanced techniques tailored to long-range forecasting. Error distributions across different prediction horizons may reveal performance degradation over longer forecast ranges, highlighting opportunities for advanced techniques tailored to long-range forecasting. While this automated modeling process is efficient for rapid experimentation, careful data preparation, feature engineering, and human oversight remain critical for achieving optimal results. The leaderboard model performances provide a starting point for iterative improvements and deeper technique-specific tuning. Conclusion Conclusion In this article, we demonstrated how to leverage AutoGluon's AutoML capabilities to streamline the process of training and evaluating diverse time-series forecasting models. We explored both univariate and multivariate modeling approaches, incorporating relevant covariate information to potentially boost predictive performance. The empirical results and error analyses facilitated by AutoGluon enable practitioners to quickly identify high-performing model classes and gain insights into their respective strengths and limitations for the given data characteristics. This serves as a strong foundation for further tuning, ensembling, and developing bespoke solutions tailored to the specific time-series forecasting problem at hand. References https://auto.gluon.ai/stable/tutorials/timeseries/forecasting-quick-start.html https://auto.gluon.ai/stable/tutorials/timeseries/forecasting-quick-start.html https://auto.gluon.ai/stable/tutorials/timeseries/forecasting-quick-start.html

Modeling Time-Series With Quick Experimentation - The AutoML Approach

Plunging Into Data: Unraveling Time Series Patterns

From Pre-Seed to Series A: Navigating the Key Stages of Product Development

The TechBeat: Dealing with Missing Data in Financial Time Series - Recipes and Pitfalls  (4/22/2024)

The TechBeat: Dealing with Missing Data in Financial Time Series - Recipes and Pitfalls  (4/20/2024)

The TechBeat: Dealing with Missing Data in Financial Time Series - Recipes and Pitfalls  (4/18/2024)

Bybit's Web3 operations have been a driving force in the NFT industry, notably with the amazing success of the 2023 Velocity Series. This achievement has been particularly noteworthy. We are ecstatic to have the opportunity to discuss the effect of the series, the exciting new partnerships that are scheduled for 2024, and your vision for the future of NFTs. Ishan Pandey: The 2023 Velocity Series, a collaboration with Oracle Red Bull Racing, truly merged speed, technology, and art. Can you elaborate on the genesis of this project? Emily: Yes. Here at Bybit Web3, we are firm believers that cooperation is the most important factor in driving forward the NFT business. By exhibiting the convergence of the thrilling world of Formula One with the inventiveness of prominent digital artists, the Velocity Series exemplified this principle at its core. The Velocity Series showcased the limitless possibilities that can be achieved when different industries come together to collaborate. A one-of-a-kind Web3 experience that was based on the RB19 racing vehicle was made possible by our collaboration with Oracle Red Bull Racing. Ishan Pandey: The series featured renowned artists like Erick Snowfro and Jack Butcher. How did Bybit Web3 foster their artistic expression and connect them with a wider audience? Emily: We partnered with AOI, a renowned art and technology foundation, to assemble four visionary artists – Rik Oostenbroek, Per Kristian, Erick Snowfro, and Jack Butcher. Each artist created a unique NFT collection inspired by Formula One, coinciding with specific races throughout the season. Rik Oostenbroek: Captured the essence of speed and fluidity, amassing 70 ETH.

Explore Rik's Collection and dive deeper into the Speed, Art, and NFTs convergence.


Per Kristian Stoveland: Brought nature into the digital realm, garnering 115 ETH.

Delve into Per Kristian's World.


Erick Snowfro: Pushed the boundaries of abstract digital art, attracting 288 ETH.

__Embark on Snowfro's Artistic Odyssey __and view the collection here.


Jack Butcher: Revolutionized the digital collectible market with his "Trademark" collection, achieving an incredible 952 ETH.


__Experience Jack Butcher's Vision __and explore the __Dutch Auction __and Open Edition pieces. Bybit Web3 provided these artists with a global platform to showcase their work. We offered extensive marketing and promotional support, ensuring the series garnered significant attention within the NFT community. Ishan Pandey: Emily, with the Velocity Series 1.0 hailed as a monumental success, can you share what's new and exciting with the upcoming Velocity Series 2.0? Emily: Absolutely, Ishan. Building on the incredible momentum of the 2023 Velocity Series, we're elevating the experience with Velocity Series 2.0. This year, we're introducing "Data Driven Art," a novel concept that blends the thrill of racing with the creativity of digital art, all inspired by the achievements of the iconic RB20 F1 car. Another groundbreaking innovation we're excited about is the launch of fractional NFTs on the DN-404 protocol, a first in the industry. These fractional NFTs make ownership more accessible, allowing a wider audience to participate in our unique digital art collections. Ishan Pandey: That sounds like a significant leap forward. Can you delve a little deeper into the specifics of the Series 2.0 Pass sale and what it offers to fans and collectors? Emily: The Series 2.0 Pass sale, kicking off on April 12th, 2023, at 2PM UTC, promises an array of exclusive benefits. We're releasing an additional 1,000 passes, bringing the total to 2,000, to meet the overwhelming demand. Pass holders will gain access to three exclusive NFT artwork drops by world-renowned artists throughout 2024, along with token-gated activations and experiences related to the series. There’s also the exciting chance to win real-life prizes through our raffles. It's an opportunity for fans to deepen their connection with the world of Formula One and digital art like never before. Ishan Pandey: Beyond artistic exposure, the Velocity Series demonstrably broadened the collector base. Can you share some success stories? Emily: Erick Snowfro: Exposing New Audiences to Artistic Brilliance – A staggering 92% of collectors for his /// collection were newcomers to his work. Snowfro, a renowned digital sculptor, used 3D modeling and animation to create a captivating series that captured the essence of movement and speed. (Insert image of Erick Snowfro's /// collection here) This achievement highlights the series' ability to introduce talented artists to a fresh audience of enthusiasts. Snowfro's work resonated deeply with collectors unfamiliar with his previous work, demonstrating the power of the NFT space to expose new audiences to established artists. Jack Butcher: Democratizing Digital Art Ownership – Approximately 84% of collectors for his "Trademark" collection were first-time Butcher owners. Butcher, a pioneer in generative art, utilized his signature algorithmically generated style to create a dynamic collection that explored themes of branding and identity. (Insert image of Jack Butcher's "Trademark" collection here) The "Trademark" collection's innovative approach and accessible pricing structure attracted a new wave of collectors to the NFT space. By offering a variety of ownership tiers, Bybit Web3 made it possible for more people to participate in the NFT market, fostering a more inclusive and vibrant community. Ishan Pandey: Looking back, what were some key takeaways from the 2023 Velocity Series that Bybit Web3 will leverage for 2024? Emily: The series offered valuable insights on designing for multi-fan participation. We learned that seasoned collectors appreciate references and expansions on existing IP/universes, while beginners benefit from publicly available collections. Additionally, content creator remix competitions with merch integration, like Snowfro's with Joyn.XYZ, proved highly successful. Ishan Pandey: The theme for Velocity Series 2024 is "Data-Driven Ark." Can you give us a sneak peek into what to expect? Emily: We're incredibly excited about Velocity Series 2.0! This year, we're embracing the future of NFTs with a focus on innovation and decentralization. Here are some key highlights: Collaboration: We have a thrilling collaboration lined up, but it's still under wraps! Stay tuned for an exciting announcement soon.
New NFT Standards: We'll be exploring the potential of ERC-404 tokens, a revolutionary standard that combines fungible and non-fungible token characteristics. This paves the way for exciting possibilities like fractionalized NFT ownership.
Full DEX Experience: Bybit Web3 is committed to a decentralized NFT future. We'll leverage our own decentralized NFT and inscription marketplaces to provide a complete DEX experience. Bybit Web3 is at the forefront of shaping the NFT landscape. We are certain that Velocity Series 2.0 will be even more revolutionary than its predecessor since it will place a greater emphasis on community development, creativity, and collaboration. There is no denying that decentralization will be the future of non-fungible tokens (NFTs), and Bybit Web3 is in an excellent position to do so. Ishan Pandey: Emily, I am grateful to you for sharing these eye-opening ideas. Our anticipation for the upcoming installment in the Velocity Series is palpable. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our brand-as-author program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Bybit's Web3 operations have been a driving force in the NFT industry, notably with the amazing success of the 2023 Velocity Series. This achievement has been particularly noteworthy. We are ecstatic to have the opportunity to discuss the effect of the series, the exciting new partnerships that are scheduled for 2024, and your vision for the future of NFTs. NFTs. Ishan Pandey: The 2023 Velocity Series, a collaboration with Oracle Red Bull Racing, truly merged speed, technology, and art. Can you elaborate on the genesis of this project? Ishan Pandey: The 2023 Velocity Series, a collaboration with Oracle Red Bull Racing, truly merged speed, technology, and art. Can you elaborate on the genesis of this project? Emily: Yes. Here at Bybit Web3, we are firm believers that cooperation is the most important factor in driving forward the NFT business. By exhibiting the convergence of the thrilling world of Formula One with the inventiveness of prominent digital artists, the Velocity Series exemplified this principle at its core. The Velocity Series showcased the limitless possibilities that can be achieved when different industries come together to collaborate. Emily: A one-of-a-kind Web3 experience that was based on the RB19 racing vehicle was made possible by our collaboration with Oracle Red Bull Racing. Ishan Pandey: The series featured renowned artists like Erick Snowfro and Jack Butcher. How did Bybit Web3 foster their artistic expression and connect them with a wider audience? Ishan Pandey: The series featured renowned artists like Erick Snowfro and Jack Butcher. How did Bybit Web3 foster their artistic expression and connect them with a wider audience? Emily: We partnered with AOI, a renowned art and technology foundation, to assemble four visionary artists – Rik Oostenbroek, Per Kristian, Erick Snowfro, and Jack Butcher. Each artist created a unique NFT collection inspired by Formula One, coinciding with specific races throughout the season. Emily: Rik Oostenbroek: Captured the essence of speed and fluidity, amassing 70 ETH.

Explore Rik's Collection and dive deeper into the Speed, Art, and NFTs convergence. Per Kristian Stoveland: Brought nature into the digital realm, garnering 115 ETH.

Delve into Per Kristian's World. Erick Snowfro: Pushed the boundaries of abstract digital art, attracting 288 ETH.

__Embark on Snowfro's Artistic Odyssey __and view the collection here. Jack Butcher: Revolutionized the digital collectible market with his "Trademark" collection, achieving an incredible 952 ETH.


__Experience Jack Butcher's Vision __and explore the __Dutch Auction __and Open Edition pieces. Rik Oostenbroek: Captured the essence of speed and fluidity, amassing 70 ETH. Explore Rik's Collection and dive deeper into the Speed, Art, and NFTs convergence. Explore Rik's Collection and dive deeper into the Speed, Art, and NFTs convergence. Explore Rik's Collection and dive deeper into the Speed, Art, and NFTs convergence. Explore Rik's Collection Rik's Collection Speed, Art, and NFTs convergence . Speed, Art, and NFTs convergence Per Kristian Stoveland: Brought nature into the digital realm, garnering 115 ETH. Delve into Per Kristian's World. Delve into Per Kristian's World. Delve into Per Kristian's World. Delve into Per Kristian's World . Delve into Per Kristian's World Erick Snowfro: Pushed the boundaries of abstract digital art, attracting 288 ETH. __Embark on Snowfro's Artistic Odyssey __and view the collection here. __Embark on Snowfro's Artistic Odyssey __and view the collection here. __ Embark on Snowfro's Artistic Odyssey __and view the collection here. Embark on Snowfro's Artistic Odyssey view the collection here . view the collection here Jack Butcher: Revolutionized the digital collectible market with his "Trademark" collection, achieving an incredible 952 ETH. __Experience Jack Butcher's Vision __and explore the __Dutch Auction __and Open Edition pieces. __Experience Jack Butcher's Vision __and explore the __Dutch Auction __and Open Edition pieces. __Experience Jack Butcher's Vision __and explore the __Dutch Auction __and Open Edition pieces. __ Experience Jack Butcher's Vision __and explore the __ Dutch Auction __and Open Edition pieces. Experience Jack Butcher's Vision Dutch Auction Open Edition pieces . Open Edition pieces Bybit Web3 provided these artists with a global platform to showcase their work. We offered extensive marketing and promotional support, ensuring the series garnered significant attention within the NFT community. Ishan Pandey: Emily, with the Velocity Series 1.0 hailed as a monumental success, can you share what's new and exciting with the upcoming Velocity Series 2.0? Ishan Pandey: Emily, with the Velocity Series 1.0 hailed as a monumental success, can you share what's new and exciting with the upcoming Velocity Series 2.0? Ishan Pandey: Emily, with the Velocity Series 1.0 hailed as a monumental success, can you share what's new and exciting with the upcoming Velocity Series 2.0? Emily: Absolutely, Ishan. Building on the incredible momentum of the 2023 Velocity Series, we're elevating the experience with Velocity Series 2.0. This year, we're introducing "Data Driven Art," a novel concept that blends the thrill of racing with the creativity of digital art, all inspired by the achievements of the iconic RB20 F1 car. Another groundbreaking innovation we're excited about is the launch of fractional NFTs on the DN-404 protocol, a first in the industry. These fractional NFTs make ownership more accessible, allowing a wider audience to participate in our unique digital art collections. Emily: Ishan Pandey: That sounds like a significant leap forward. Can you delve a little deeper into the specifics of the Series 2.0 Pass sale and what it offers to fans and collectors? Ishan Pandey: That sounds like a significant leap forward. Can you delve a little deeper into the specifics of the Series 2.0 Pass sale and what it offers to fans and collectors? Ishan Pandey: That sounds like a significant leap forward. Can you delve a little deeper into the specifics of the Series 2.0 Pass sale and what it offers to fans and collectors? Emily: The Series 2.0 Pass sale, kicking off on April 12th, 2023, at 2PM UTC, promises an array of exclusive benefits. We're releasing an additional 1,000 passes, bringing the total to 2,000, to meet the overwhelming demand. Pass holders will gain access to three exclusive NFT artwork drops by world-renowned artists throughout 2024, along with token-gated activations and experiences related to the series. There’s also the exciting chance to win real-life prizes through our raffles. It's an opportunity for fans to deepen their connection with the world of Formula One and digital art like never before. Emily: Ishan Pandey: Beyond artistic exposure, the Velocity Series demonstrably broadened the collector base. Can you share some success stories? Ishan Pandey: Beyond artistic exposure, the Velocity Series demonstrably broadened the collector base. Can you share some success stories? Emily: Erick Snowfro: Exposing New Audiences to Artistic Brilliance – A staggering 92% of collectors for his /// collection were newcomers to his work. Snowfro, a renowned digital sculptor, used 3D modeling and animation to create a captivating series that captured the essence of movement and speed. (Insert image of Erick Snowfro's /// collection here) This achievement highlights the series' ability to introduce talented artists to a fresh audience of enthusiasts. Snowfro's work resonated deeply with collectors unfamiliar with his previous work, demonstrating the power of the NFT space to expose new audiences to established artists. Emily: Jack Butcher: Democratizing Digital Art Ownership – Approximately 84% of collectors for his "Trademark" collection were first-time Butcher owners. Butcher, a pioneer in generative art, utilized his signature algorithmically generated style to create a dynamic collection that explored themes of branding and identity. (Insert image of Jack Butcher's "Trademark" collection here) The "Trademark" collection's innovative approach and accessible pricing structure attracted a new wave of collectors to the NFT space. By offering a variety of ownership tiers, Bybit Web3 made it possible for more people to participate in the NFT market, fostering a more inclusive and vibrant community. Ishan Pandey: Looking back, what were some key takeaways from the 2023 Velocity Series that Bybit Web3 will leverage for 2024? Ishan Pandey: Looking back, what were some key takeaways from the 2023 Velocity Series that Bybit Web3 will leverage for 2024? Emily: The series offered valuable insights on designing for multi-fan participation. We learned that seasoned collectors appreciate references and expansions on existing IP/universes, while beginners benefit from publicly available collections. Additionally, content creator remix competitions with merch integration, like Snowfro's with Joyn.XYZ, proved highly successful. Emily: Ishan Pandey: The theme for Velocity Series 2024 is "Data-Driven Ark." Can you give us a sneak peek into what to expect? Ishan Pandey: The theme for Velocity Series 2024 is "Data-Driven Ark." Can you give us a sneak peek into what to expect? Emily: We're incredibly excited about Velocity Series 2.0! This year, we're embracing the future of NFTs with a focus on innovation and decentralization. Here are some key highlights: Emily: Collaboration: We have a thrilling collaboration lined up, but it's still under wraps! Stay tuned for an exciting announcement soon. New NFT Standards: We'll be exploring the potential of ERC-404 tokens, a revolutionary standard that combines fungible and non-fungible token characteristics. This paves the way for exciting possibilities like fractionalized NFT ownership. Full DEX Experience: Bybit Web3 is committed to a decentralized NFT future. We'll leverage our own decentralized NFT and inscription marketplaces to provide a complete DEX experience. Collaboration: We have a thrilling collaboration lined up, but it's still under wraps! Stay tuned for an exciting announcement soon. New NFT Standards: We'll be exploring the potential of ERC-404 tokens, a revolutionary standard that combines fungible and non-fungible token characteristics. This paves the way for exciting possibilities like fractionalized NFT ownership. Full DEX Experience: Bybit Web3 is committed to a decentralized NFT future. We'll leverage our own decentralized NFT and inscription marketplaces to provide a complete DEX experience. Bybit Web3 is at the forefront of shaping the NFT landscape. We are certain that Velocity Series 2.0 will be even more revolutionary than its predecessor since it will place a greater emphasis on community development, creativity, and collaboration. There is no denying that decentralization will be the future of non-fungible tokens (NFTs), and Bybit Web3 is in an excellent position to do so. Ishan Pandey: Emily, I am grateful to you for sharing these eye-opening ideas. Our anticipation for the upcoming installment in the Velocity Series is palpable. Ishan Pandey: Emily, I am grateful to you for sharing these eye-opening ideas. Our anticipation for the upcoming installment in the Velocity Series is palpable. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our brand-as-author program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: This author is an independent contributor publishing via our brand-as-author program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: Vested Interest Disclosure: This author is an independent contributor publishing via our brand-as-author program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR

Bybit Revs Up the NFT Market with Data-Driven Velocity Series 2.0

বাইবিট ডেটা-চালিত বেগ সিরিজ 2.0 সহ NFT বাজারকে উত্থাপন করে৷

Bybit bringt den NFT-Markt mit der datengesteuerten Velocity Series 2.0 in Schwung

Bybit acelera el mercado NFT con Data-Driven Velocity Series 2.0

Bybit relance le marché NFT avec Data-Driven Velocity Series 2.0

बायबिट ने डेटा-ड्रिवेन वेलोसिटी सीरीज 2.0 के साथ एनएफटी बाजार को बढ़ावा दिया

Bybit、データ駆動型Velocityシリーズ2.0でNFT市場を活性化

Bybit, 데이터 기반 Velocity 시리즈 2.0으로 NFT 시장 활성화

Bybit acelera o mercado NFT com Data-Driven Velocity Series 2.0

Bybit расширяет рынок NFT с помощью Data-Driven Velocity Series 2.0

Bybit, Veriye Dayalı Hız Serisi 2.0 ile NFT Pazarını Hızlandırıyor

Bybit thúc đẩy thị trường NFT với dòng vận tốc theo hướng dữ liệu 2.0

Bybit 通过数据驱动的 Velocity Series 2.0 加速 NFT 市场

Dealing with Missing Data in Financial Time Series - Recipes and Pitfalls 

ফাইন্যান্সিয়াল টাইম সিরিজে অনুপস্থিত ডেটা নিয়ে কাজ করা - রেসিপি এবং ক্ষতি

Umgang mit fehlenden Daten in Finanzzeitreihen – Rezepte und Fallstricke

Manejo de datos faltantes en series de tiempo financieras: recetas y trampas

Gérer les données manquantes dans les séries temporelles financières – Recettes et pièges

वित्तीय समय श्रृंखला में गुम डेटा से निपटना - विधियां और नुकसान

金融時系列における欠損データの扱い - 秘訣と落とし穴

금융 시계열에서 누락된 데이터 처리 - 방법 및 함정

Lidando com dados ausentes em séries temporais financeiras – receitas e armadilhas

Работа с недостающими данными в финансовых временных рядах: рецепты и подводные камни

Finansal Zaman Serilerinde Eksik Verilerle Başa Çıkmak - Tarifler ve Tuzaklar

Xử lý dữ liệu bị thiếu trong chuỗi thời gian tài chính - Bí quyết và cạm bẫy

处理金融时间序列中的缺失数据 - 秘诀和陷阱

Welcome to Daylight Savings Recovery Week – a period of days when most of the world expresses shock, dismay, despair, and the other 5 stages of grief about waking up an hour early and generally being cranky. Like so many things in 2024, the act of saving daylight (whatever that might actually mean) has become increasingly polarizing (and somewhat partisan) with both citizens and politicians clamoring for an end to the madness of changing our clocks twice a year. on a bill signed in 2022 that would keep daylight savings time permanently in place. Colorado is awaiting federal approval would permanently end daylight savings time. A new bill in California got a bill passed in the Senate that would put an end to DST, but it wasn’t taken up in the house. In the US Congress, a senator from Oklahoma , another Republican – from Utah this time – reintroduced a bill to make DST permanent, or at least allow states to do so if they chose. Meanwhile, over in the House In all, there are that relate to the abolishment of, or standardization of, daylight saving time. 500 bills (between state and federal legislatures) currently in play I’m sharing this by way of making two points: Lots of people have: an opinion on daylight saving time the authority to try to change it the desire to change it now There is no consistency, no unified plan on how to do this. The result of this can be described by words ranging from “absurd” to “disastrous.” “Absurd” because it’s entirely possible that, in the current situation, one state would abolish DST, while another would permanently stay on it. Meaning you could travel from Ohio at 6:00 am (with a bill currently under consideration to remain on DST), drive 1 hour to Pennsylvania where it would be 8:00 am (because they’ve continued to change their clocks seasonally); and arrive 4 hours later in New York, where the time is… no, not 12:00 pm, but instead, it would be 11:00 am. I’m probably exaggerating a little because, as I understand it, states can pass all the DST bills they want but it will require a federal ruling to allow that law to take effect. Or something like that. I’m neither a lawyer nor a politician so I’m not 100% sure. Let’s face it, it’s 2024. The push to remote work that started with the pandemic has caused many of us to feel that time is mostly meaningless. Things get done, people are awake (or asleep) whenever it suits them, and the number on the clock has less bearing on our lives than it once did. Nevertheless, the current rash of polarized opinions related to changing daylight savings time could make life (or at least certain times of day) very hard for folks who observe solar-centric, rather than clock-centric, times. , which helps developers easily incorporate and display so-called “Jewish” times (zmanim) into their websites. But here’s a quick primer for those who haven’t followed along: I’ve been writing about my work using PHP Zmanim It’s difficult to understate the importance of accurate time calculations on the Jewish religious day, week, and life. It figures into everything from when a fast starts and ends; to when it’s too late (or too early) to say certain prayers; to the moment when simply owning (let alone eating) bread is forbidden. “What time are afternoon prayers?” To understand that, we have to first understand what defines “day” (versus “night”); how to understand what demarcation separates “morning” from “afternoon”; how to effectively divide the day into parts; and so much more. Here’s a sampling of sun-specific times: Before sunrise, (the moment when the top edge of the disk of the sun touches the horizon) comes “dawn”, the moment when light can first be seen shining over the horizon. No prayers can happen before dawn. At a specific time between dawn and sunrise, it’s permissible to put on tallit and tefillin. a “seasonal hour” is determined by taking the amount of daylight (from sunrise to sunset) and dividing it into 12 equal parts. Afternoon prayers cannot be said until 6.5 seasonal hours after sunrise. My point is not to bog you down with complex (and, to the non-religious reader, seemingly whimsical) calculations. My point is that there is a significant population of folks (a rough estimate is 3.1 million people) for whom this DOES matter. And that doesn’t even begin to consider that the 5 salah (Muslim prayers) times are equally dependent on the sun. How does the current kerfluffle about DST factor in? let’s consider (all times are given for my location in Cleveland Ohio. Your Sunlight May Vary!): On Nov 5, the, time “falls” back – so that what WOULD have been an 8 am sunrise becomes 7 am. But sunrise, and sunlight, continue moving forward. In fact, the day gets progressively later all the way to Dec 31, when it hits 7:53 am Sunrise sits at that point for another 8 days, until it starts rolling back (getting earlier) starting January 8. But consider that without that shift in time, sunrise on November 6 would proceed forward – eventually stopping just shy of 9 am. For the observant Jewish person, that means dawn comes at almost 7:30 am. The earliest time for tallit and tefillin would be 7:56 am. A typical morning service runs between 30-45 minutes, meaning that most folks won’t get out of services until 8:45 am. For a person who has an early start to their day, or has to travel to the office; or get kids to school, this makes attending prayers almost impossible. On the other hand, what happens if we don’t ever go back to daylight saving? On March 9 the clocks “spring forward” so that the 6:47 am sunrise becomes 7:45 am on March 10. But sunrise continues to get earlier, all the way until June 8, when it hits 5:52 am. And sunrise sits at that time for 12 days, all the way until it finally starts to move forward again on June 20. But without the DST adjustment, sunrise would come at 4:52 am. You might expect, at this point, that I’d do a big reveal and show that sunSET is impacted. That’s not the case. Back in November, sunset goes from 6:18 pm on November 4 to 5:17 pm the following day. It keeps getting earlier until December 5 when it hits 4:56 pm. Now, I’ll freely admit that I think sunset at 5 pm kind of sucks. But I’m willing to accept it far more than having to manage prayers at almost 9 am. Meanwhile, on the other side of the equation, the latest sunset hits on June 20, at 9:04 pm. If you are completely turned around at that point, join the club. I had to do a few exports from and some manual sorting to get it all straight: timeanddate.com If we never sprang forward into daylight saving time: The earliest sunrise would be 4:49 am (on Jun 13) The latest sunrise would be 7:51 am (Jan 9) The earliest sunset would be 4:56 pm (Dec 4) The latest sunset would be 8:04 pm (Jul 4) Meanwhile, if we never fell back – meaning permanent daylight saving time: The earliest sunrise would be 5:49 am (Jun 13) The latest sunrise would be 8:51 am (Jan 9) The earliest sunset would be 5:56 pm (Dec 4) The latest sunset would be 9:04 pm (Jul 4) It’s worth clarifying what DST is giving us now: The earliest sunrise is 5:49 am (Jun 13) The latest sunrise is 7:59 am (Nov 5) The earliest sunset is 4:56 pm (Dec 4) The latest sunset is 9:04 pm (Jul 4) With all of that said, my opinion is that the DST system doesn’t offer very much benefit for the trouble. Moreover, as an orthodox Jew – for whom prayers (and therefore the cycles of sunrise and sunset) matter more than the time on a clock – remaining on standard (non-DST) time would be my choice. On the one hand, I’m in luck. While, under Federal law, states can opt out of DST, they cannot choose to remain permanently on DST without approval. On the other, it seems this is the less popular choice. In recent years, to make DST permanent have been considered in various states across the country. 19 states have passed those bills, which would immediately take effect the moment the federal government approves it. over 650 bills But for the moment, things appear to be staying put. I guess I’ll try not to lose any sleep over it. Share this: Also published here

What Daylight Are We Saving? Time Data Series

Acknowledgments This post continues my exploration of concepts and techniques related to both the way so-called “Jewish times” (zmanim) are calculated; as well as the techniques needed to use the – a library of functions that let you easily calculate Jewish times. PHP Zmanim library Once again, I owe a huge debt of gratitude to several folks – including Eliyahu Hershfeld, creator of the , Zachary Weixelbaum (owner of the PHP Zmanim library, a port of Kosher Java), Elyahu Jacobi (who built with those tools and patiently explained so many concepts to me), and Maor Neim, who offered explanations that turned theory into practice. Kosher Java library RoyZmanim.com Introduction , I explored both the foundational concepts of Jewish time calculations (zmanim) and also the initial steps needed to install and use PHP Zmanim. We got as far as calculating sunrise with that library. In my last post By itself, this isn’t particularly impressive. The fact is that with the same information (latitude, longitude, time zone, and a specific date) you can get the same information using PHP’s built-in functions. In this post, we’re going to get into the types of calculations you CAN’T get with built-in PHP tools, not only because they require some “interesting” time manipulations, but because there are so many ways to calculate the same religiously significant moment, based on various Rabbinic opinions and traditions. The Answer to Every Jewish Question Starts With “Well, It Depends…” Let me take a minute to unpack that idea in a little more detail. In the last post, I started to get into this idea: Dawn is the moment when light (but not the sun) is visible over the horizon. Unfortunately, whether or not there is or isn’t “light” is highly subjective, and therefore the way it’s come to be calculated ranges all over the map. Some traditions use a fixed number of clock minutes before sunrise or after sunset. Others will use astronomy to identify the time when the sun is below the horizon by a specific number of degrees. Others will use a formula, such as taking the amount of daylight (from sunrise to sunset), dividing that into 10 equal parts, and then subtracting that amount from sunrise or adding it to sunset. Still others will take the time the sun is below the horizon on an “equal” day (meaning the spring or fall equinox, when the amount of sunshine and darkness are exactly the same), calculate the difference (in clock minutes) between that time and sunrise, normalize those minutes against “seasonal minutes” (“sha’ot zmaniyot”) for the specific day in question, and finally subtract that amount from sunrise (or add THAT to sunset) for the day in question. One moment of the day, but a wide variety of ways to determine it. It may be hard for those outside of mainstream orthodox Judaism to understand and is definitely the subject of a completely different type of blog post, but the answer is to embrace the understanding that all of the calculations above (and many others) are capital-T “True.” Not just in a “well, it’s how I feel about it so it’s true to me” kind of way, but as being absolutely, factually, empirically true even when one method stands in opposition to another (or several others). Like I said, THAT is the topic of a completely different blog post. For now, I mention this to explain why, in creating the , Eliyahu Hershfeld took the route of enabling the ability to easily calculate times using ANY of those methods, rather than trying to espouse a single method and coding exclusively for that. Kosher Java library And ports – such as Zachary Weixelbaum’s – simply continue with that ideal. PHP Zmanim library Which brings us back to the nitty-gritty of using the PHP Zmanim library. Making Time Pretty , we left off with this snippet of code: In the last post <?php
require 'vendor/autoload.php';
use PhpZmanim\Zmanim;
use PhpZmanim\Calendar\ComplexZmanimCalendar;
use PhpZmanim\Geo\GeoLocation;


# Set variables:
#41.4939407, -81.516709;
$locname = "Beit Knesset Chochmat Shlomo, Beachwood, OH";
$lat = 41.4939407;
$long = -81.516709;
$elev = 0;
$tz = 'America/New_York';

$getyear = 2024;
$getday = 20;
$getmonth = 12;
$testzmanim = Zmanim::create($getyear, $getmonth, $getday, $locname, $lat, $long, $elev, $tz);
$sunrise = $testzmanim->sunrise;
echo "$sunrise\n";
?> Which produced a result that looked something like this: 2024-12-20 07:48:52 It works, but it’s not what I’d want to see on a page when I’m just expecting a simple “7:48 am”. Which brings me to the next interesting insight for the PHP Zmanim library: You can format the output using another function, rather than hammering through PHP’s built-in options. You’ll still use the but getting what you want is easier. PHP time/date formatting codes Let’s say I want to only display the hour, minute, and am/pm for the sunrise output. I’d add a line like this: $sunrise = $zmanim->sunrise;
$sunrise = $sunrise->format('g:i a'); Which would look like this when printed on the screen: 7:48 am Getting Your First Actual real-time – Mincha Gedola The problem with using sunrise/sunset as an example is that PHP has built-in options to do the exact same thing. So, let’s look at getting a time that is more relevant to Jewish religious times: the earliest time for afternoon prayers (Mincha Gedola). Once again, it’s somewhat anti-climactic in that it’s a single command: $gedolah = $zmanim->minchaGedola; Which outputs a time like this: 2024-12-20 12:46:55 HOWEVER, as I mentioned earlier in this post, there are several ways to calculate this time. Here are all the methods supported by the PHP Zmanim library: minchaGedola: Returns a time of 6.5 halachic hours (shaos zmaniyos) after sunrise. minchaGedola30Minutes: Returns the time 30 standard (clock) minutes after the half-day calculation (chatzot). minchaGedola72Minutes: Calculates according to the Magen Avraham (Abraham Abele Gombiner, 1635-1682) with the day starting 72 minutes before sunrise and ending 72 minutes after sunset. minchaGedola16Point1Degrees: Calculated according to the Magen Avraham with the day starting and ending when the sun is 16.1 degrees below the horizon. minchaGedolaAhavatShalom: Calculated based on the opinion of as half a seasonal hour (shaah) after mid-day (chatzos) with seasonal minutes (shaos zmaniyos) calculated based on a day starting 72 minutes before sunrise and ending 13.5 minutes after sunset. Rabbi Yaakov Moshe Hillel minchaGedolaGreaterThan30: This is a convenience method that returns the later of the standard “minchaGedola” function or ‘minchaGedola30Minutes. In the winter when 1/2 of a seasonal hour (sha’ah) is less than 30 minutes, then minchaGedola30Minutes will be returned, otherwise, the regular minchaGedola will be returned. minchaGedolaAteretTorah: This method returns the time of according to the Magen Avraham with the day starting and ending when the sun is 16.1 degrees below the horizon. mincha ketana minchaGedolaBaalHatanya: This calculation is based on the opinion of the . Baal Hatanya minchaGedolaBaalHatanyaGreaterThan30: This is a convenience method that returns the later of either minchaGedolaBaalHatanya or minchaGedola30Minutes. In the winter when 1/2 of a seasonal hour (sha’ah) is less than 30 minutes, then minchaGedola30Minutes will be returned, otherwise minchaGedolaBaalHatanya will be returned. minchaGedolaGRAFixedLocalChatzos30Minutes: This method returns a time based on opinion. Rav Moshe Feinstein’s As you can see, there are a number of opinions. Determining which one you want/need to use is outside the scope of this blog post and will likely require some conversations with the users of the app or website, as well as a Rabbi. Or two. Or several. But the good news is that to use any of them, it’s as simple as: $gedolah = $zmanim->minchaGedola16Point1Degrees;
$gedolah = $gedolah->format('g:i a'); Getting Something Complicated – Nightfall (Tzais Hakochavim) Now that you’ve seen how we get one time, you should understand that even times that my previous post labeled as “complicated” aren’t that complicated. Furthermore, it should reinforce your understanding of just how powerful a tool like PHP Zmanim is because of what it enables you to do in such a short time. Calculating nightfall (tzais hakochavim) is as simple as the command $tzais = $zmanim->tzais; If there is any challenge at all, it’s the sheer number of variations to consider. I’m listing them here without explanation, just so you have a sense of how many there are. That’s right, there are 32 different options for calculating this one time. I list them here without detailed explanation simply to underscore my point: tzais tzais72 tzaisGeonim3Point7Degrees tzaisGeonim3Point8Degrees tzaisGeonim5Point95Degrees tzaisGeonim3Point65Degrees tzaisGeonim3Point676Degrees tzaisGeonim4Point61Degrees tzaisGeonim4Point37Degrees tzaisGeonim5Point88Degrees tzaisGeonim4Point8Degrees tzaisGeonim6Point45Degrees tzaisGeonim7Point083Degrees tzaisGeonim7Point67Degrees tzaisGeonim8Point5Degrees tzaisGeonim9Point3Degrees tzaisGeonim9Point75Degrees tzais60 tzaisAteretTorah tzais72Zmanis tzais90Zmanis tzais96Zmanis tzais90 tzais120 tzais120Zmanis tzais16Point1Degrees tzais26Degrees tzais18Degrees tzais19Point8Degrees tzais96 tzaisBaalHatanya tzais50 Time (and This Blog Series) Marches On Armed with the information in this post, you could probably make decent headway simply by looking through the main README on Zachary’s page itself, and selecting the best (for your purposes) calculations for: PHP Zmanim Sunrise and Sunset (no, do not sing ) That Song A “seasonal” hour (Sha’ah Zmanim) Dawn (alos hashachar) The earliest time to put on tallit and tefillin (misheyakir) The latest time to say Shema (sof zman kria shema) The latest time for morning prayers (sof zman tefillah) When Passover begins Halfway through the day (chatzos) The earliest time for afternoon prayers (mincha gedola) The “best” time for afternoon prayers (mincha ketana) The latest time for afternoon prayers (plag hamincha) The time to light Shabbat candles Dusk – the time between sunset and night (bain hashmashot) Night (tzais hakochavim) Halfway through the night (chatozs halayla) But there is still more to cover. In upcoming articles, I’ll talk about: Taking these standard times and adjusting them for synagogue specific needs (“Mincha starts 25 minutes before Shkia each day”). Using the PHP Zmanim library to display non-time calculations such as the weekly Torah Portion, Rosh Chodesh, and the Molad. Leveraging the build-in astronomy functions for time calculations that aren’t built into the library itself. I hope you’ll continue on this journey with me. As always if you have questions, comments, or kudos, please leave them in the comments.

Time Data Series: How to Work With PHP Zmanim

Time Data Series: Getting Started with PHP Zmanim - AdatoSystems Acknowledgments In this blog, I’m explaining concepts and techniques related to both the way so-called “Jewish times” (zmanim) are calculated, as well as the techniques needed to use the – a library of functions that let you easily calculate Jewish times. PHP Zmanim library The PHPZmanim library is maintained by Zachary Weixelbaum. As with so many things in tech today, PHP Zmanim is itself based on the foundational Kosher Java library by Eliyahu Hershfeld. I owe a huge debt of gratitude to both Zachary and Eliyahu – not only for the work they put into developing those libraries but also for the support they have given me as I came up to speed on both the technical and Jewish religious guidelines (halacha) needed to use them. Introduction “What time will afternoon prayers (Mincha) be this week?” is a deceptively complex question. It’s deceptive because “afternoon prayers” seems to be self-explanatory, but (as with so many things related to Jewish religious rules (halacha) there’s a vast amount of background, commentary, and specificity required. NOTE: If you are already comfortable with Jewish time concepts (zmanim), feel free to skip to the section labeled “Installing PHP Zmanim.” I won’t be insulted nor hold it against you. It’s difficult to understand the importance of accurate time calculations on the Jewish religious day, week, and life. It figures into everything from when a fast starts and ends to when it’s too late (or too early) to say certain prayers to the moment when simply owning (let alone eating) bread is forbidden. To put it another way, I’ll share a quote from Rabbi Abraham Joshua Heschel in his book “The Sabbath”, The meaning of the Sabbath is to celebrate time rather than space. Six days a week we live under the tyranny of things of space; on the Sabbath we try to become attuned to holiness in time. Rabbi Abraham Joshua Heschel, “The Sabbath” Even with that explanation, some readers may still wonder, “Why make such a big deal about it? Are you telling me God is going to hold it against you if you’re 5 minutes off?” It’s a valid question and worth a moment of discussion because otherwise, the need for, let alone the impact of, this blog (and the techniques and technologies it describes) is diminished. No, of course, God doesn’t care. Just like my track coach doesn’t “care” if I warm up before running, do my off-season workouts, or drink enough water. Let’s face it: no matter how hard I train, my coach won’t be any healthier. However, my coach – who cares for me beyond my performance in the next race, wants ME to care. They want me to be fully committed, if only because they know my experience will be more fulfilling because of it. In the same way, God doesn’t “care.” But we know (through the texts of the Torah and Talmud) that God wants the US to care. And so Jewish scholars through the millennia have attempted – using the evidence presented in the text – to eschew simple and simplistic answers and dig deeper to uncover the details. Back to the question at hand: “What time are afternoon prayers?” To understand that, we have to first understand what defines “day” (versus “night”), how to understand what demarcation separates “morning” from “afternoon,” how to effectively divide the day into parts, and so much more. While this blog will introduce some of these concepts and terms as needed, it should not be considered exhaustive by any stretch of the imagination. It comes as no surprise that computers have made quick work of calculating these times, and now there’s a wide array of websites and applications ready to do the job for us. Even for those who want to create their own programs to do these calculations, there are time-saving solutions in the form of code libraries like and its many ports, including , , , , , and many more. KosherJava PHP Swift .Net JavaScript Python Nevertheless, it’s important to understand the theory behind the tools. Anyone who wants to create a website or app has to be certain their program isn’t inadvertently giving the wrong times. While, as mentioned earlier, nobody will “go to hell” (so to speak) for praying at the wrong time, there is a strict commandment: וְלִפְנֵ֣י עִוֵּ֔ר לֹ֥א תִתֵּ֖ן מִכְשֹׁ֑ל וְיָרֵ֥אתָ מֵּאֱלֹהֶ֖יךָ“lifnei iver lo titein michshol v’yareita mei-elohecha”“Don’t put a stumbling block before the blind” (Leviticus 19:14) It’s one thing if an individual gets something wrong by accident. It’s quite another to provide bad information that causes someone (or worse, LOTS of folks) to make a mistake, believing the information they got (from your app) was accurate and trustworthy. The Basic Times With that in mind, we’ll start with understanding the times that are fairly straightforward and the least affected by variations in Jewish tradition: Sunrise (Netz Hachma) is a good old nautical sunrise – the moment when the top edge of the disk of the sun touches the horizon. Sunset (Shkia) is the other side of the daily coin – the moment when the top edge of the sun drops just below the horizon. A “seasonal hour” (sha’ah) refers to the even division of daylight, the time between sunrise and sunset. There are always 12 seasonal hours, but they may be longer or shorter than a regular (on your clock) hour because the amount of daylight fluctuates with the season. Note that some traditions calculate a sha’ah as 12 divisions of the time from dawn (alot hashachar, or just “alot” when light is visible over the horizon, but before sunrise itself) to night (tzeis hakochavim, or just “tzeis”, when NO light is visible over the horizon, after sunset). We’ll get more into both dawn (a lot) and night (tzeit) later in the blog. Seasonal minutes (sha’ot zmaniyot) is 1/60 of a seasonal hour and, just like a seasonal hour, may be larger or smaller than a minute on your clock. As you can see, sunrise and sunset form the fundamental core of all other time calculations, and a great number of important Jewish times during the day are derived directly from those. For example, in some traditions, you’ll find: Shabbat begins on Friday night, 18 minutes before sunset (shkia) Shabbat ends on Saturday night 45 (or 50, or 72) minutes after sunset (shkia) …and so on. Calculations where “It’s Complicated” Once you have sunrise and sunset nailed down, the next step is to identify the two critical times of dawn and night. Dawn (Alot haShachar, or just “Alot”) and night (Tzeis hakochavim, or just “Tzeis”) mirror each other the way sunrise and sunset do. Dawn is the moment when light (but not the sun) is visible over the horizon. Night is the moment when light is no longer visible. Unfortunately, whether or not there is or isn’t “light” is highly subjective, and therefore, the way it’s calculated ranges all over the map. Some traditions use a fixed number of clock minutes before sunrise or after sunset. Others will use astronomy to identify the time when the sun is below the horizon by a specific number of degrees. Others will use a formula, such as taking the amount of daylight (from sunrise to sunset), dividing that into 10 equal parts, and then subtracting that amount from sunrise or adding it to sunset. Still, others will take the time the sun is below the horizon on an “equal” day (meaning the spring or fall equinox, when the amount of sunshine and darkness are exactly the same), calculate the difference (in clock minutes) between that time and sunrise, normalize those minutes against “seasonal minutes” (“sha’ot zmaniyot”) for the specific day in question, and finally subtract that amount from sunrise (or add THAT to sunset) for the day in question. Sound confusing? As the title of this section says, “It’s complicated.” My point in describing these isn’t to settle on a single “correct” calculation but rather to help you understand the ultimate goal of each type of calculation – as well as for you to understand that there are multiple ways different Jewish traditions arrive at each calculation. The Complex times Once you have dawn (alot), sunrise (netz), sunset (shkia), and night (tzeis), it becomes possible to calculate other important daily times. These include: The earliest time for afternoon prayers (Mincha Gedola), which is often calculated as a certain number of seasonal hours (sha’ah) after either dawn or sunrise. The point of this time is that it is the earliest moment when “afternoon” (literally, after mid-day) happens. The preferable time for afternoon prayers (Mincha ketana), which is calculated as a larger number of seasonal hours (sha’ah) after either sunrise (netz) or dawn (alot). The point here is that it’s more than 3/4 of the way through the day, when it’s CLEARLY afternoon – but without the risk of it accidentally being night (tzeis). The latest time for afternoon prayers (Plag haMincha, or “plag”) , which is often calculated as the time between the best time for afternoon prayers (mincha ketana) and night (tzeis). While there are several other key times that we’ll get to in a different blog, these are enough to get us started. Installing the PHP Zmanim Library With those technical details taken care of, we can now move on to… some technical details! Except this time, they are TECHNICAL technical details. ( ) and for those people who skipped all the way from the introduction to this section, WELCOME! It’s great to have you back! PHP Zmanim is a complex library that comprises not just the import of Kosher Java into the PHP language but also some supporting modules like (a tool that helps make date and time conversions faster, easier, and more accurate); (a web design framework); and a few other smaller utilities. Carbon Symfony The point is that all those modules work in concert with PHP Zmanim, and you need all of them installed for anything to work. The easiest way to get them all installed is using the PHP utility that manages dependencies. “composer” If you need to run PHP Zmanim on a web server and don’t have access to run installers at the command line, you’re still in luck. Simply copy the ./vendor directory from a local installation, and – with some caveats – it will work. What are those caveats? The main one is to make sure the version of PHP supported by your hosting provider matches the one you use when installing via Composer. This brings me to the actual composer install command. I know we haven’t gotten to actually coding anything yet, but let’s set up a directory where the scripts are going to go. For this blog, I’m going to call it /phpzmanim_test. In a terminal window, move to that directory: cd /php zmanim_test Now type the command: composer -V (note that’s a capital V) This will confirm whether composer is installed or not. If not, do a quick search to find out the best way to get it installed on your operating system. Next, type the command: composer require zachweix/php-zmanim This will do two things: First, it will create the file in the current directory, with instructions that PHP Zmanim should be installed. composer.json It actually installs PHP Zmanim for you, into a ./vendor directory inside the current directory. No extra steps are needed. The only other “composer” related item to note is that if you ever need to update, you can do so easily by going into the /phpzmanim_test directory (or whatever you called yours) and typing the command . This will read the information in the composer.json file and update everything it finds there. composer update (SPOILER: this means you should NOT delete the composer.json file. You don’t, however, have to copy it to your remote site with the rest of your application if you don’t want to.) Once this is done, you need to include the following line in every PHP script that will use the PHP Zmanim library: require 'vendor/autoload.php'; Getting Started with PHP Zmanim Now that PHP Zmanim is installed, you’re ready to start writing some code with it. To do this, you’ll first create a php object – a collection (array, really) of data that are passed into various functions. This object contains both the specific date for the times you’ll want to pull and also the precise location information. Creating an object with “Zmanim::create()” Before you start, you’ll need to know a few things about the location where you are asking for times: The latitude and longitude. The time zone is formatted using the tz database format. (example: “America/New_York”). The elevation of that location, if you choose to use it. (SPOILER: very rarely does elevation factor into these calculations.) The year, month, and day of the times you’ll be calculating. The format for creating your object is: $VARNAME = Zmanim::create(YEAR, MONTH, DAY, "NAME OF LOCATION", LATITUDE, LONGITUDE, ELEVATION, "TIME ZONE"); Here’s a specific example: $zmanim = Zmanim::create(2019, 2, 21, "New York City", 40.850519, -73.929214, 200, "America/New_York"); What that looks like as a script with some variables in place of the literal input: <?php
require 'vendor/autoload.php';
use PhpZmanim\Zmanim;
use PhpZmanim\Calendar\ComplexZmanimCalendar;
use PhpZmanim\Geo\GeoLocation;

$getdate = date('Y-m-d');
$getyear = date('Y', strtotime($getdate));
$getmonth = date('m', strtotime($getdate));
$getday = date('d', strtotime($getdate));

$locname = "Beit Knesset Chochmat Shlomo, Beachwood, OH";
$lat = 41.4939407;
$long = -81.516709;
$elev = 0;
$tz = 'America/New_York';

$zmanim = Zmanim::create($getyear, $getmonth, $getday, $locname, $lat, $long, $elev, $tz); With that code in place, you have an object for today’s date, for the specified location. You can even print it out using PHP’s function: print_r() print_r($zmanim); Which should give you output that looks something like this: PhpZmanim\Zmanim Object
(
    [calendar:PhpZmanim\Calendar\AstronomicalCalendar:private] => Carbon\Carbon Object
        (
            [endOfTime:protected] => 
            [startOfTime:protected] => 
            [constructedObjectId:protected] => 00000000000000080000000000000000
            [localMonthsOverflow:protected] => 
            [localYearsOverflow:protected] => 
            [localStrictModeEnabled:protected] => 
            [localHumanDiffOptions:protected] => 
            [localToStringFormat:protected] => 
            [localSerializer:protected] => 
            [localMacros:protected] => 
            [localGenericMacros:protected] => 
            [localFormatFunction:protected] => 
            [localTranslator:protected] => 
            [dumpProperties:protected] => Array
                (
                    [0] => date
                    [1] => timezone_type
                    [2] => timezone
                ) (there’s more, but you get the idea). Getting your first real-time – Sunrise (Netz HaHachma) Once you have an object created, using it to get specific times through PHP Zmanim is almost anti-climactic. Getting sunrise is as simple as: $sunrise = $zmanim->sunrise; If you aren’t familiar with it or haven’t used it before, the indicates you’re querying an object (again, a collection of data elements) or using a built-in method. -> This will return something that looks like this: 2024-12-20 07:48:52 For those following along, the complete code so far looks like this: <?php
require 'vendor/autoload.php';
use PhpZmanim\Zmanim;
use PhpZmanim\Calendar\ComplexZmanimCalendar;
use PhpZmanim\Geo\GeoLocation;


# Set variables:
#41.4939407, -81.516709;
$locname = "Beit Knesset Chochmat Shlomo, Beachwood, OH";
$lat = 41.4939407;
$long = -81.516709;
$elev = 0;
$tz = 'America/New_York';

$getyear = 2024;
$getday = 20;
$getmonth = 12;
$testzmanim = Zmanim::create($getyear, $getmonth, $getday, $locname, $lat, $long, $elev, $tz);
$sunrise = $testzmanim->sunrise;
echo "$sunrise\n";
?> Summary There is a lot more to cover in PHP Zmanim, which I plan to do in the coming weeks. But this should at least get you started with building a PHP-based script or website and displaying accurate times for Jewish moments. As always, I welcome questions, corrections, and kudos in the comments below. Also published . here

Time Data Series: A Beginner's Guide to PHP Zmanim

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