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Ciprian Dorin Craciun cipriancraciun Volutico @volutico Timisoara, Romania https://volution.ro/ciprian [looking for a challenge!] IT enthusiast: from programming to operating systems, from networking to cryptography, from cloud to hardware, from Erlang to Java.

cipriancraciun/covid19-datasets 20

COVID-19 derived and augmented datasets (based on JHU, NY Times, ECDC) exported as JSON, TSV, SQL, SQLite DB (plus visualizations)

cipriancraciun/z-run 2

z-run -- lightweight Go-based scripts library tool

cipriancraciun/askama 1

[patched fork] Askama -- compiled Rust template based on Jinja syntax

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issue commentcipriancraciun/covid19-datasets

Please restore combined datasets (perhaps as releases)

OK, bad news... I had to remove the combined values-sqlite.db.gz variant, but the plain SQL inserts based on which it was created is still available as values-sqlite.sql.gz.

(The reason is that even compressed it surpassed the 100 MiB limit.)

jgoerzen

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[combined] Remove SQLite DB variant (including `gz` variant); only SQL is available.

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[nytimes][datasets] Update NY Times datasets due to upstream data changes.

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[ecdc][datasets] Update ECDC datasets due to upstream data changes.

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issue commentcipriancraciun/covid19-datasets

Please restore combined datasets (perhaps as releases)

I did adapt covid19db to download the various constituent datasets and combine them, and extract locations-diff.tsv from a previous commit, so I'm unblocked for now but it's a bit sub-optimal.

I've just made a commit and pushed the old files again (re-generated up-to-date).

However please note that in the following days I'll start removing some large non-archived files and replacing them with their .gz alternative.

Also I'll think about using an alternative distribution method. I'll create a new issue for that and ping you there.


As far as I can tell, GitHub actions have no particular limits for public repos on the free tier. But I may be missing something?

Apparently they did state that in some old documents, but removed them in the interim:

  • https://web.archive.org/web/20200521202931/https://help.github.com/en/github/managing-large-files/what-is-my-disk-quota

FWIW, the Rust code I'm using in covid19db runs in about 10 minutes in GitHub Actions. The majority of that time actually goes into compiling dependencies. The most time-consuming part of the actual data ingestion is in processing your datasets. Running the Rust code in debug mode (without optimizations) causes it to compile faster but run slower. It's probably not worth the effort, but I would surmise that redoing your processing pipeline in a compiled language like Rust or Go, targeting Sqlite directly with commits in long-running transactions, and then exporting the other formats from there would dramatically reduce the preparation time.

:) I bet that using Rust, C/C++, or any more "performant" language, would make the processing blazing fast... However at the moment when I wrote the scripts I used jq that allowed me to easily express various map / reduce pipelines, and some Python here and there.

At that time (1-2 months into the European situation) it ran on my laptop in a few minutes, which was acceptable... However now, as months have started piling-up, it is quite a slug... :) (Time is not so much an issue, however the fan noise drives me mad...) :)

Unfortunately rewriting all the scripts would take quite some time, and at the moment I don't think it is worth it. (As you know, the "open-source" model doesn't pay the bills...) :)


Anyhow, I have made sure to credit your project in covid19db, and also in covid19ks, which is my project that consumes all this stuff and generates the graphs of local interest to me at https://jgoerzen.github.io/covid19ks/

Thanks! I've also added your projects in my readme.

jgoerzen

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issue commentcipriancraciun/covid19-datasets

Please restore combined datasets (perhaps as releases)

Thanks for the report!

I'll investigate today a way to bring it back, although perhaps outside the GitHub environment, by example uploading it on a "plain" HTTP server.


The issue is not only with the size of the individual file, which even compressed approaches the 100MiB limit, but also with the overall size of the entire repository. At the moment GitHub reports it has over 75 GiB, therefore I estimate in at most 2 months it will reach the 100 GiB limit, at which point I'll be in trouble...

At the moment there are two solutions for large files:

  • as you've said releases, which it seems imposes no limit;
  • Git LFS (Large File Storage), https://docs.github.com/en/github/managing-large-files/versioning-large-files, which unfortunately for a free account is limited to 1 GiB both in storage and bandwidth; (thus out of the question for my use-case;)

Getting back to the releases feature it has a few drawbacks:

  • first, given that I re-generate the datasets daily, it will quickly amount hundreds of "releases", thus becoming a mess;
  • secondly, I'll have to implement it as a separate step in the processing pipeline; (I can't use GitHub actions, because the time required to "process" the current data will quickly consume all the free allocations; for example at the moment the processing takes about 2 hours on a 8 core system with 32 GiB of RAM;)

Thus based on the above observations, I must rethink my distribution model for output files, which it seems doesn't match anymore the "self-contained" GitHub repository. :(

jgoerzen

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Ciprian Dorin Craciun

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Junegunn Choi

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[vim] Add 'tmux' layout option to use fzf-tmux e.g. if exists('$TMUX') let g:fzf_layout = { 'tmux': '-p90%,60%' } else let g:fzf_layout = { 'window': { 'width': 0.9, 'height': 0.6 } } endif

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Fix typo

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Junegunn Choi

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[fzf-tmux] Allow positional flags Since we don't know in advance which flags tmux will support, simply allow a single uppercase character ([A-Z]) for now. fzf-tmux -xR -yS fzf-tmux -x R -y S Fix #1956

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Jack Bates

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Run rubocop --auto-correct --disable-uncorrectable (#1967) Co-authored-by: Junegunn Choi <junegunn.c@gmail.com>

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Junegunn Choi

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[zsh-completion] Fix error with backslash-prefixed commands Fix #1973 Fix #1974 Fix #1975

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Junegunn Choi

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[install] Clarify that .bashrc should be loaded from .bash_profile on macOS Close #1986

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Jack Bates

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Make flaky tests reliable (#1978)

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Junegunn Choi

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[completion] Make kill completion more consistent with the others Support both ordinary completion trigger and empty trigger kill <tab> kill foo**<tab> Close #1988 Close #385

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Junegunn Choi

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Remove dead code

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Janek

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Add more details on apt installation in README.md (#1977)

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Junegunn Choi

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Add conda installation instruction Close #1949

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Quote LDFLAGS (#1995) Make sure that `extldflags` is quoted so that LDFLAGS containing spaces won't break the build command. Close #1994

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Jack Bates

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Improve error messages (#1962) * Add RuboCop Minitest extension * Improve error messages * Use chomp option

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Slaven Rezić

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[zsh] Make CTRL-R work with older Perls (#2003) s///r is only available since perl 5.14. The Perl oneliner was changed to work with older Perls, possibly even with 5.000. Fix #2001

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ichizok

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[vim] Don't start extra process when opening popup (#2000) Fix #2038

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[vim] Don't set wfw, wfh, bh options when opening popup (#2042) * No need to restore &wfw and &wfh when using popup window Co-authored-by: lacygoill <lacygoill@lacygoill.me> Co-authored-by: Junegunn Choi <junegunn.c@gmail.com>

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Do not disable mouse after execute(-silent) when --height option is used The action takes place in the alternate screen so the offsets should still be correct.

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karasu

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Revert file mode of key-bindings.zsh

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Janek

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README: Use --line-range instead of head in bat example (#2064) * Use --line-range instead of head in bat example * README: extend preview section

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Ciprian Dorin Craciun

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[go] Upgrade dependencies.

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startedcipriancraciun/netlifyctl

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issue commentnetlify/netlifyctl

Print errors to stderr only

I've solved this issue as a by-product of another issue. My patch is available at:

https://github.com/cipriancraciun/netlifyctl/commit/0167fe06b5179d542060f163694f7b3f23169e0e

(Given that this tool is unmaintained by the upstream team, I don't think I'll submit a pull request. However you could use my fork at the link above.)

chrstphrknwtn

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issue commentnetlify/netlifyctl

out of memory with 'netlifyctl deploy'

I found the issue, namely the memory leak is due to the logging done in the DebugMiddleware function. What happens:

  • in order to output the netlifyctl-debug.log file (which is enabled by the --debug flag, but also written in case of failure),
  • the logger is instructed to write the log to a buffer (see https://github.com/netlify/netlifyctl/blob/master/commands/middleware/middleware.go#L57-L66);
  • unfortunately one of the dependencies (I think github.com/netlify/open-api) also uses the logger to trace all HTTP calls, which unfortunately includes in the request body the original file;
  • thus when large uploads are involved, all the files are stored in the logging buffer;

I've made the following patch, which unless it receives the --debug flag it won't save that file, and it increases the log level to warnings: https://github.com/cipriancraciun/netlifyctl/commit/0167fe06b5179d542060f163694f7b3f23169e0e

(I could have completely removed that buffer, but I don't want to touch the code too much...)

rockonedege

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issue commentnetlify/netlifyctl

Failed deploy does not exit neither gives an error message

@danielo515 Please check if perhaps the tool fails due to an out-of-memory condition.

(See #106 for details.)

danielo515

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Ciprian Dorin Craciun

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[logging] Set default log level to warning.

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[ui] Use only ASCII characters for spinner.

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[logging] Do not save `netlifyctl-debug.log` unless the `--debug` flag was given. (Also this solves a memory leak issue.)

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[nytimes][datasets] Update NY Times datasets due to upstream data changes.

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issue commentCSSEGISandData/COVID-19

Date format

@phanidevarakonda I'm sorry but I'm afraid that the repository you've mentioned has no relation with this repository where this issue is being discussed.

I would suggest opening an issue is that repository.

BenAveling

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issue commentnetlify/netlifyctl

out of memory with 'netlifyctl deploy'

I have encountered a similar issue, and I think I've linked it to large files (around 100 MiB) in size.

Although I haven't sought the problem in the code, I've applied the following workarounds (by writing a wrapper bash script, which works only on Linux):

  • use ulimit -m 4194304 -d 4194304 to make sure that it will never eat more than 4 GiB of RAM;
  • use printf -- 1000 >| "/proc/${$}/oom_score_adj" to make sure that when the out-of-memory-killer runs it will hit netlifyctl and not other processes (most often a browser);
  • export -- GOMAXPROCS=1 -- I doubt it actually helps, but at least I hope to reduce the stress on the system under memory pressure;
  • export -- GOGC=5 -- make the Go's garbage collector more aggressive (it helps somewhat);
  • export -- GODEBUG=gcstoptheworld=1,madvdontneed=1 -- it makes Go pause when garbage collecting (which again helps with the OOM killer), and hopefully unused memory is marked as unused so the OS can skip swapping;

However, none of these measures actually solve the problem, they just delay the crash sometimes.

Luckily if you run the netlifyctl deploy command in a loop, it will eventually push everything.

rockonedege

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issue commentStackExchange/dnscontrol

CF_REDIRECT always in "preview" output, nothing actually changed

The lines you've mentioned, https://github.com/StackExchange/dnscontrol/blob/a9f2ab84c8e0db722dec40894059c181dc7ee221/providers/cloudflare/cloudflareProvider.go#L343-L348, will affect all records.

Thus, I think perhaps after the line https://github.com/StackExchange/dnscontrol/blob/a9f2ab84c8e0db722dec40894059c181dc7ee221/providers/cloudflare/cloudflareProvider.go#L369 of the same file could be added:

if rec.Type == "CF_REDIRECT" || rec.Type == "CF_TEMP_REDIRECT" {
    rec.TTL = 1
svenluijten

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issue commentCSSEGISandData/COVID-19

Date format

@phanidevarakonda I don't know exactly at what files you are looking at, but all the series and daily series contain the total cumulative cases for that date. You can easily extract the delta for a day by substracting the current value with the previous value.

If you want something already processed, take a look at my derived dataset available at:

https://github.com/cipriancraciun/covid19-datasets

BenAveling

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issue commentStackExchange/dnscontrol

CF_REDIRECT always in "preview" output, nothing actually changed

@svenluijten The CF_REDIRECT (and CF_TEMP_REDIRECT) are not actual DNS records, but are modeled as such for dnscontrol; therefore there is no TTL for them.

I would assume that dnscontrol should always reset the TTL to 1 (or any other constant value), regardless of what the user sets in DefaultTTL(...), TTL(...), or other ways to set defaults at higher levels.

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issue commentCSSEGISandData/COVID-19

Date format

@phanidevarakonda could you be more specific in what you mean by:

Is there any way to get time series data?

BenAveling

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issue commentcipriancraciun/covid19-datasets

Sqlite3 schema suggestions

Herein are multiple issues, and I'll take them one-by-one:

When the values in the absolute_* and delta_* columns are zero, put a zero there rather than a NULL. Both columns should be defined NOT NULL in the schema. [...] On another topic, there doesn't appear to be a row for every day in the table, although this is present in the source material. It appears rows are omitted when all of the delta_* values would be zero. Although that reduces storage space, it makes it substantially more difficult to perform analyses using WHERE date = type of clauses. For instance, creating a sum of cases over a set of counties or something would normally be possible using a SELECT but couldn't be done here, since the rows are omitted.

The fact that we have NULL values, and the fact that some dates don't exist when all deltas are zero, are not an oversight, but a "feature". :)

Think about the following situation:

  • say in day+1 a country reports a total of 10101 cases so far; then on day+2 it still reports 10101 total cases; thus the delta is 0;
  • say the say country reports in day+1 a total of 10101 cases; but on day+2 it reports nothing (i.e. no official statement is made, no datapoint is created for that day), but then on day+3 it reports 10102 cases; what is the delta for day 2 and 3? my assumption is that for day 2 we have no delta (thus NULL), and for day 3 we have 1;
  • however going back to the first situation, given that many countries have tens of thousands of cases, is it likely that there is really a zero number of new cases (or deaths or recoveries) in a given day?

Therefore, given that deltas are important in deciding the direction the current situation takes, and the fact that a true zero delta is highly unlikely, I've taken the two decisions you've observed:

  • all delta values that are 0 are replaced with a NULL, based on the fact that we don't truly know, and its highly unlikely, that we have a "true" zero report, and thus we transform it into a "we don't know" marker;
  • also given that no new cases and no deaths and no recoveries is also highly unlikely (unless the situation was overcome for that country), I have decided to remove all lines that don't change the situation (i.e. all zero deltas implies no row); also by not repeating the same data over-and-over, we can easily identify when the situation ended for a certain country.

To conclude: my decision was based on this principle: I shouldn't "make-up-data" where there is high uncertainty that there is any. I prefer to let the user (the researcher) to decide how to fill in the gaps.

Regarding the WHERE date clauses, you can do a LEFT JOIN between a generated dates table (or SELECT x in VALUES ('date-1', 'date-2', etc.)) and thus you have your table that contains all dates.

Regarding the aggregate functions (SUM, AVG, etc.) they shouldn't be impacted by the NULL values.

Therefore with regard the NULL values and the missing rows, I don't think a change should be made, without introducing "made-up-data".


Removing the FIPS codes from the county-related rows makes it more difficult to cross-reference with other sources. It would be great to have those still present, or a separate locations table that could be cross-referenced using the location_key to look it up.

I'll add the FIPS code as administrative_code somewhere in the weekend.


A more relational model could be useful; for instance, there wouldn't necessarily be a reason to duplicate all the factbook entries on every row when they could be correlated with a separate factbook table at select time.

Although I agree that normalization is useful in general, when it comes to analytics databases (which this dataset tries to provide), denormalization is actually helpful:

  • first it simplifies queries by having all columns "pre-JOINed", thus anyone with simple SQL knowledge (that for example isn't well versed in JOINs) could use this database;
  • then it also provides "feature" (population or continent for example) attributes that can easily be filtered upon in simple queries;

As such if it would really help you, I could create a second normalized SQL script that provides more tables.

jgoerzen

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issue commentcipriancraciun/covid19-datasets

Populate per100k in US County-level data

First of all thank you for your interest!

Now regarding the per US-county level statistics, initially my main focus for the COVID19 dataset was the situation in Europe (where I live), plus at that time the only data that was available was at country level. Then JHU and NYTimes started adding the data at US state level and US county level. Although the data for US at state level had almost the same quality as the country one, the per US-county data was quite sparse and unreliable, thus I didn't focus on that.

My initial attempt to normalize the US-county level data was to create a mapping file to normalize the county names, as seen in this file: https://github.com/cipriancraciun/covid19-datasets/blob/master/sources/facts-files/us-locations.odshttps://github.com/cipriancraciun/covid19-datasets/blob/master/sources/facts-files/us-locations.ods

However for some reason the US FIPS data (from the official .gov site) was blocked from outside US (or perhaps from inside EU), and thus I tried my best to use the Wikipedia pages to get at least the names right. (But gave up on any further tries.)

Regarding the lookup-table pointed out, given that I merge both JHU and NYTimes data, I would have preferred a third party data source for the population (and area and location if possible).

Thus if you can help me identify a suitable dataset for this additional data I could try to integrate it.


That being said, given that my focus is on the "global" scale, thus not US, I've take the decision to map non-continental dependencies as individual countries. For example Virgin Islands, Puerto Rico, French & Dutch & Holand & China's dependencies.

Thus for those US dependencies, I've also merged all country-level data, and at this moment I don't think I'll revert this.

jgoerzen

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