Results for f-record

Procedural macros supporting the `stdf` crate

Data model and parser for Sender Policy Framework (SPF) records

This gem is still under active development. Please contact me directly with any questions or suggestions. To start: r = RedcapAPI.new(token, url) # your institution has it's own url, and each project has it's own token r.get(optional record_id) # returns all records in JSON format or a specific record if specified r.get_fields # returns all fields for that instrument r.post(data) # this will either update an old record or create a new one. the data should be in form of array of hashes or as a hash (for one item). dates are accepted in Date class or in strftime('%F') format. for example data = {name: 'this is a test', field_2: Date.today} r.post(data) # creates a new object using the fields above. field names must match those in the existing project "{\"count\": 1}" --> indicates the object posted. to update an existing record: data = {record_id: 3, name: 'this is a test to update', field_2: Date.today} r.post(data) # this will update the record with record_id 3. if record_id 3 does not exist it will create an entry with that record id

== E9Tags An extension to ActsAsTaggableOn[http://github.com/mbleigh/acts-as-taggable-on] which "improves" on custom tagging, or at least makes it more dynamic. Additionally it provides some autocomplete rack apps and the corresponding javascript. == Installation 1. E9Tags requires jquery and jquery-ui for the autocompletion and tag-adding form, be sure they're loaded in your pages where the tags form will be rendered. 2. E9Tags extends ActsAsTaggableOn and requires it. Run it's generator if you have not. 3. Run the E9Tags install script to copy over the required JS rails g e9_tags:install 4. Then make sure it is loaded, how you do that doesn't matter, e.g. <%= javascript_include_tag 'e9_tags' %> 5. Create an initializer for that sets up the taggable models and their controllers. This gives the models the tag associations and methods and prepares their controller to handle the otherwise unexpected tag params. require 'e9_tags' require 'contacts_controller' require 'contact' E9Tags.controllers << ContactsController E9Tags.models << Contact OR You can just include the modules in your classes yourself. The first way really exists for the case where the classes you wish to extend are part of another plugin/gem. # in contact.rb include E9Tags:Model # in contacts_controller.rb include E9Tags::Controller 6. Render the tags form partial in whatever model forms require it. = render 'e9_tags/form', :f => f If you pass a context, it will be locked and no longer possible to change/add the contexts on the form (and as a side effect, the tags autocompletion will be restricted to that context). = render 'e9_tags/form', :f => f, :context => :users Finally if you pass a 2nd arg to :context you can set a tag context to be "private" (default is false). In this case the tag context will be locked as private (typically suffixed with *), meaning that the tags will not be publicly searchable/visible. This is useful for organizational tags tags, say if you wanted to arbitrarily group records, or create a custom search based on a tag context. = render 'e9_tags/form', :f => f, :context => [:users, true] NOTE: The form and javascript are intended to work out of the box, but the certainly aren't going to look pretty. If you do intend to use the forms, you'll no doubt need to style them.

Log2json lets you read, filter and send logs as JSON objects via Unix pipes. It is inspired by Logstash, and is meant to be compatible with it at the JSON event/record level so that it can easily work with Kibana. Reading logs is done via a shell script(eg, `tail`) running in its own process. You then configure(see the `syslog2json` or the `nginxlog2json` script for examples) and run your filters in Ruby using the `Log2Json` module and its contained helper classes. `Log2Json` reads from stdin the logs(one log record per line), parses the log lines into JSON records, and then serializes and writes the records to stdout, which then can be piped to another process for processing or sending it to somewhere else. Currently, Log2json ships with a `tail-log` script that can be run as the input process. It's the same as using the Linux `tail` utility with the `-v -F` options except that it also tracks the positions(as the numbers of lines read from the beginning of the files) in a few files in the file system so that if the input process is interrupted, it can continue reading from where it left off next time if the files had been followed. This feature is similar to the sincedb feature in Logstash's file input. Note: If you don't need the tracking feature(ie, you are fine with always tailling from the end of file with `-v -F -n0`), then you can just use the `tail` utility that comes with your Linux distribution.(Or more specifically, the `tail` from the GNU coreutils). Other versions of the `tail` utility may also work, but are not tested. The input protocol expected by Log2json is very simple and documented in the source code. ** The `tail-log` script uses a patched version of `tail` from the GNU coreutils package. A binary of the `tail` utility compiled for Ubuntu 12.04 LTS is included with the Log2json gem. If the binary doesn't work for your distribution, then you'll need to get GNU coreutils-8.13, apply the patch(it can be found in the src/ directory of the installed gem), and then replace the bin/tail binary in the directory of the installed gem with your version of the binary. ** P.S. If you know of a way to configure and compile ONLY the tail program in coreutils, please let me know! The reason I'm not building tail post gem installation is that it takes too long to configure &amp;&amp; make because that actually builds every utilties in coreutils. For shipping logs to Redis, there's the `lines2redis` script that can be used as the output process in the pipe. For shipping logs from Redis to ElasticSearch, Log2json provides a `redis2es` script. Finally here's an example of Log2json in action: From a client machine: tail-log /var/log/{sys,mail}log /var/log/{kern,auth}.log | syslog2json | queue=jsonlogs \ flush_size=20 \ flush_interval=30 \ lines2redis host.to.redis.server 6379 0 # use redis DB 0 On the Redis server: redis_queue=jsonlogs redis2es host.to.es.server Resources that help writing log2json filters: - look at log2json.rb source and example filters - http://grokdebug.herokuapp.com/ - http://www.ruby-doc.org/stdlib-1.9.3/libdoc/date/rdoc/DateTime.html#method-i-strftime

Log2json lets you read, filter and send logs as JSON objects via Unix pipes. It is inspired by Logstash, and is meant to be compatible with it at the JSON event/record level so that it can easily work with Kibana. Reading logs is done via a shell script(eg, `tail`) running in its own process. You then configure(see the `syslog2json` or the `nginxlog2json` script for examples) and run your filters in Ruby using the `Log2Json` module and its contained helper classes. `Log2Json` reads from stdin the logs(one log record per line), parses the log lines into JSON records, and then serializes and writes the records to stdout, which then can be piped to another process for processing or sending it to somewhere else. Currently, Log2json ships with a `tail-log` script that can be run as the input process. It's the same as using the Linux `tail` utility with the `-v -F` options except that it also tracks the positions(as the numbers of lines read from the beginning of the files) in a few files in the file system so that if the input process is interrupted, it can continue reading from where it left off next time if the files had been followed. This feature is similar to the sincedb feature in Logstash's file input. Note: If you don't need the tracking feature(ie, you are fine with always tailling from the end of file with `-v -F -n0`), then you can just use the `tail` utility that comes with your Linux distribution.(Or more specifically, the `tail` from the GNU coreutils). Other versions of the `tail` utility may also work, but are not tested. The input protocol expected by Log2json is very simple and documented in the source code. ** The `tail-log` script uses a patched version of `tail` from the GNU coreutils package. A binary of the `tail` utility compiled for Ubuntu 12.04 LTS is included with the Log2json gem. If the binary doesn't work for your distribution, then you'll need to get GNU coreutils-8.13, apply the patch(it can be found in the src/ directory of the installed gem), and then replace the bin/tail binary in the directory of the installed gem with your version of the binary. ** P.S. If you know of a way to configure and compile ONLY the tail program in coreutils, please let me know! The reason I'm not building tail post gem installation is that it takes too long to configure && make because that actually builds every utilties in coreutils. For shipping logs to Redis, there's the `lines2redis` script that can be used as the output process in the pipe. For shipping logs from Redis to ElasticSearch, Log2json provides a `redis2es` script. Finally here's an example of Log2json in action: From a client machine: tail-log /var/log/{sys,mail}log /var/log/{kern,auth}.log | syslog2json | queue=jsonlogs \ flush_size=20 \ flush_interval=30 \ lines2redis host.to.redis.server 6379 0 # use redis DB 0 On the Redis server: redis_queue=jsonlogs redis2es host.to.es.server Resources that help writing log2json filters: - look at log2json.rb source and example filters - http://grokdebug.herokuapp.com/ - http://www.ruby-doc.org/stdlib-1.9.3/libdoc/date/rdoc/DateTime.html#method-i-strftime

== FEATURES: * Input your data as an array of hashes * Input a report layout, built using a Ruby DSL * Outputs ASCII pivot tables suitable for fast reports * Pretty fast: takes less than a second to process 1,000 records of data by a report with 100 rows and 10 columns. == SYNOPSIS: require 'rubygems' require 'crosstab' data = [{:gender =&gt; &quot;M&quot;, :age =&gt; 1}, {:gender =&gt; &quot;F&quot;, :age =&gt; 2}, {:gender =&gt; &quot;M&quot;, :age =&gt; 3}] my_crosstab = crosstab data do table do title &quot;Q.A Age:&quot; group &quot;18 - 54&quot; do row &quot;18 - 34&quot;, :age =&gt; 1 row &quot;35 - 54&quot;, :age =&gt; 2 end row &quot;55 or older&quot;, :age =&gt; 3 end banner do column &quot;Total&quot; group &quot;Gender&quot; do column &quot;Male&quot;, :gender =&gt; &quot;M&quot; column &quot;Female&quot;, :gender =&gt; &quot;F&quot; end end end puts my_crosstab.to_s # =&gt; ... Table 1 Q.A Age: Gender ---------------- Total Male Female (A) (B) (C) ------- ------- ------- (BASE) 3 2 1 18 - 54 2 1 1 ----------------------------- 67% 50% 100% 18 - 34 1 1 -- 33% 50% 35 - 54 1 -- 1 33% 100% 55 or older 1 1 -- 33% 50% == JUST THE BEGINNING: * I hope to add in later releases: * New export formats: html, pdf, csv, excel. * More stats than just frequency and percentage: mean, median, std. deviation, std. error, and significance testing * Optional row and table suppression for low frequencies * Optional table rows populating from the data * Optional table ranking -- automatically reorder rows based in descending order based on frequencies observed == REQUIREMENTS: * None

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