mcc -W 'java:Test,Class1' -T link:lib -d /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing class{Class1:/Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest.m} [Warning: Name is nonexistent or not a directory: /Users/chongming/Desktop/Experiment Trajectory/Dictionary_learning/cvx/builtins] [Warning: Name is nonexistent or not a directory: /Users/chongming/Desktop/Experiment Trajectory/Dictionary_learning/cvx/commands] [Warning: Name is nonexistent or not a directory: /Users/chongming/Desktop/Experiment Trajectory/Dictionary_learning/cvx/functions] [Warning: Name is nonexistent or not a directory: /Users/chongming/Desktop/Experiment Trajectory/Dictionary_learning/cvx/lib] [Warning: Name is nonexistent or not a directory: /Users/chongming/Desktop/Experiment Trajectory/Dictionary_learning/cvx/structures] [Warning: Name is nonexistent or not a directory: /Users/chongming/Desktop/Experiment Trajectory/Dictionary_learning/cvx/functions/vec_] [Warning: Name is nonexistent or not a directory: /Users/chongming/Desktop/Experiment Trajectory/Dictionary_learning/cvx] [Warning: Adding path "/Users/chongming/Desktop/TraCode/TrajectoryCompression" to Compiler path instance.] strVersion: 1.8.0_112 Loading source files for package Test... Constructing Javadoc information... Standard Doclet version 1.8.0_112 Building tree for all the packages and classes... Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/Test/Class1.html... /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/Test/Class1.java:109: warning: no @param for args public static void main (String[] args) ^ /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/Test/Class1.java:59: warning: no @throws for com.mathworks.toolbox.javabuilder.MWException public Class1() throws MWException ^ /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/Test/Class1.java:88: warning: no @throws for com.mathworks.toolbox.javabuilder.MWException public Class1(MWComponentOptions componentOptions) throws MWException ^ /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/Test/Class1.java:77: warning: no @throws for com.mathworks.toolbox.javabuilder.MWException public Class1(String pathToComponent) throws MWException ^ Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/Test/Class1Remote.html... /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/Test/Class1Remote.java:58: error: reference not found * @throws java.jmi.RemoteException An error has occurred during the function call or ^ /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/Test/Class1Remote.java:61: warning: no @throws for java.rmi.RemoteException public Object[] fortest(int nargout, Object... rhs) throws RemoteException; ^ /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/Test/Class1Remote.java:64: warning: no @throws for java.rmi.RemoteException void dispose() throws RemoteException; ^ Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/Test/TestMCRFactory.html... Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/Test/package-frame.html... Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/Test/package-summary.html... /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/Test/package-info.java:8: warning: emptytag
* ^ /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/Test/package-info.java:15: error: unexpected end tag: * ^ /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/Test/package-info.java:20: warning: emptytag
* ^ /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/Test/package-info.java:26: error: unexpected end tag: * ^ Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/Test/package-tree.html... Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/constant-values.html... Building index for all the packages and classes... Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/overview-tree.html... Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/index-all.html... Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/deprecated-list.html... Building index for all classes... Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/allclasses-frame.html... Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/allclasses-noframe.html... Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/index.html... Generating /Users/chongming/Desktop/TraCode/TrajectoryCompression/fortest/for_testing/doc/html/help-doc.html... 3 errors 8 warnings Error: An error occurred while shelling out to javadoc (error code = 1). Unable to build executable. For more information, pass the -v option to mcc.


PDX API |
Drag the map around to explore bike rack locations
|
|---|---|
|
UPDATE 5/13/10: PDXAPI is being migrated to a new version of GeoCouch and the API may be unavailable. This project is still very much a work in progress! Follow my tweeters if you want to stay up to date: @maxogden PDXAPI is a JSON API that provides access to data from CivicApps, the open data initiative by the City of Portland. Much of the data on CivicApps is in a very raw and hard to use form. PDX API exists to filter the data from CivicApps and provide it in the easiest way possible to application developers wanting to consume the data. |
Example JQuery JSONP request to the
$.ajax({
url: "http://www.pdxapi.com/bicycle_parking",
dataType: 'jsonp',
data: {
"bbox":"-122.6785969,45.5167974,-122.6763439,45.51772964"
},
success: function(data){
// manipulate data
}
});
|
|
#
API pdxapi.com/ You must specify the You’ll need to request the data using library that supports JSONP, such as jQuery. PDXAPI is powered by GeoCouch, a spatial index enabled flavor of CouchDB. This means that every piece of data in PDXAPI is accessible and editable through a REST-like interface. I am in the process of creating example client applications that take advantage of the full capabilities of the platform; the eye candy at the top of this page is just a teaser. Want to help out? Fork the project on Github or contact me if you are interested. |
DatasetsDatasets currently available through PDX API:
address_points_region bicycle_network bicycle_parking bridges business_association_boundaries capital_improvement_projects_line capital_improvement_projects_point capital_improvement_projects_poly city_boundaries city_halls_region corners county_boundaries county_boundaries_region curb_ramps curbs development_opportunity_areas elevation_map enterprise_and_e_commerce_zones fire_stations_region freight_districts freight_facilities garbage_hauler_boundaries guardrails heritage_trees home_buyer_opportunity_areas hospitals_region intermodal_facilities its_cameras_intelligent_transportation_system its_signs_intelligent_transportation_system leaf_pickup libraries_region light_rail light_rail_stops local_improvement_districts metro_council_districts neighborhood_associations neighborhood_associations_region parking_meters parks parks_easements parks_region parks_taxlots parks_trails parks_vegetation_survey pavement_maintained_not_maintained pavement_moratorium_streets pedestrian_districts schools_region sidewalks snow_ice_routes storefront_improvement_areas street_centerline_pdx street_centerlines street_sweeping_routes_day street_sweeping_routes_night streets_jobs_contract_jobs_line streets_jobs_contract_jobs_points streets_jobs_permit_jobs_line streets_jobs_permit_jobs_points streets_jobs_permit_jobs_polygon streets_local_improvement_district streets_region traffic_calming_devices traffic_signals transit_district_poly transit_stations trimet_bus_system_routes trimet_bus_system_stops trimet_park_and_ride_lots trimet_transit_centers tsp_classifications tsp_district_boundaries urban_renewal_areas vegetation watershed_sub_watershed_info wellhead_protection_area zip_codes zip_codes_region zoning_anno zoning_arrows zoning_lines zoning_region More to come soon! |


What is pair programming?
Pair programming is a way to collaborate on coding problems. It's beneficial as a learning tool as well as a teaching tool. In pair programming there is a driver and navigator. They can both contribute to solving a problem.
Why is pair programming important to DBC?
One of the barriers to working on a team is different personality types. Pair programming will help us relate to our different personalities better. It is also helpful to have two pairs of eyes checking the code to catch for mistakes.
Compare Driver and Navigator
The driver usually is the programmer who implements the code, and is the person sitting at the computer typing. The navigator usually serves as the guide and checks syntax and looks at the broader overview.
Reflection Comment
Reflect on your learning. How was it to pair this time? Did you feel more comfortable? How did you do with the learning competencies? Add your reflection as a comment in your gps1-2.html file.I felt much more comfortable pairing this time than GPS1-1. I felt I didn't have to struggle so much reading directions and then coding simultaneously. I realize that GPS is a method to give us feedback to advise us whether or not we are on track for success at DBC.
I felt more comfortable choosing and placing the appropriate HTML tags on the document. We did not have much time to compare the different HTML tags to one another, but I do feel comfortable about what these tags are and what they do. I feel comfortable choosing appropriate tags. I felt talking about pair-programming more solidified my opinion that pair-programming is a good learning tool. Teaching someone and guiding them, also working together and collaborating, and struggling through a problem together is beneficial to both programmers.


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Element index for package System.Data
[ c ]
[ e ]
[ g ]
[ i ]
[ o ]
[ s ]
[ t ]
[ _ ]
_
- __call
- in file TAdodb.php, method TAdodb::__call()
PHP magic function.
- __sleep
- in file TAdodb.php, method TAdodb::__sleep()
Cleanup work before serializing.
- __wakeup
- in file TAdodb.php, method TAdodb::__wakeup()
This method will be automatically called when unserialization happens.
top
c
- close
- in file TAdodb.php, method TAdodb::close()
Closes the DB connection.
top
top
top
top
o
- open
- in file TAdodb.php, method TAdodb::open()
Establishes a DB connection.
top
s
- setCacheDir
- in file TAdodb.php, method TAdodb::setCacheDir()
Sets the cache directory for ADODB (in adodb it is
- setDatabase
- in file TAdodb.php, method TAdodb::setDatabase()
Sets the database name
- setDataSourceName
- in file TAdodb.php, method TAdodb::setDataSourceName()
Sets the data source name (DSN).
- setDriver
- in file TAdodb.php, method TAdodb::setDriver()
Sets the DB driver (mysql, sqlite, etc.)
- setFetchMode
- in file TAdodb.php, method TAdodb::setFetchMode()
Sets the fetch mode of query data: Associative, Numeric, Both, Default (default)
- setHost
- in file TAdodb.php, method TAdodb::setHost()
Sets the DB host name/IP (and port number) in the format "host[:port]"
- setPassword
- in file TAdodb.php, method TAdodb::setPassword()
Sets the DB password
- setPersistentConnection
- in file TAdodb.php, method TAdodb::setPersistentConnection()
Sets whether the DB connection should be persistent
- setUsername
- in file TAdodb.php, method TAdodb::setUsername()
Sets the DB username
top
t
- TAdodb.php
- procedural page TAdodb.php
- TAdodb
- in file TAdodb.php, class TAdodb
TAdodb class
top
|
|


Symbol Index for "Access Group For Object"
Symbol Index for diagram
"Access Group For Object"
Access Group For Object (Class)
Access Type (Class)
Agent Access Group (Class)
group (Association)
maximum access (Association)
object (Association)
Object (Class)


--- layout: default title: JenNa's CV ---
My academic research interests are in experimental design with a focus on split-plot designs. My areas of research in split-plot designs have covered nonregular, semifoldover, and response surface methodology with categorical factors with a focus on computer algorithms for finding optimal designs. I am also actively studying and taking courses and workshops in teaching pedagogy. In particular I am interested in incorporating technology in the classroom, lesson planning, and active learning techniques.


--- layout: page title: Self introduction blog sitemap: priority: 0.9 ---
Name:JiSu Ham University:Kangwon National University Department:Media Engineering E-mail:h_h0164@naver.com


Step 3: Embedded Derby
Introduction
When an application accesses a Derby database using the Embedded Derby JDBC driver, the Derby engine does not run in a separate process, and there are no separate database processes to start up and shut down. Instead, the Derby database engine runs inside the same Java Virtual Machine (JVM) as the application. So, Derby becomes part of the application just like any other jar file that the application uses. Figure 1 depicts this embedded architecture.
Figure 1: Derby Embedded Architecture
This section shows how to compile and run a simple Java application using the Derby Embedded JDBC driver. The information presented is deliberately simple. For complete information, see the Derby Developer's Guide.
Set the environment
To set up the environment, follow the "Configure Embedded Derby" instructions.
Sample Application
Copy sample application
The Derby software includes a sample application called SimpleApp.java. In Derby 10.2 and above it is located in the DERBY_INSTALL/demo/programs/simple/ directory. (In Derby 10.1 it is located in the DERBY_INSTALL/demo/simple/ directory.) Copy that application into your current directory.
By default this application runs in embedded mode and does the following:
- Starts up the Derby engine
- Creates and connects to a database
- Creates a table
- Inserts data
- Updates data
- Selects data
- Drops a table
- Disconnects
- Shuts down Derby
A quick look at the code
The SimpleApp.java application spends most of its time creating a table, inserting data into that table, and selecting the data back, demonstrating many JDBC calls as it does so. This section highlights the JDBC calls that make this specifically an embedded Derby application. The "Derby Network Server" section shows how the same JDBC calls turn the same code into a client/server application.
Load the Embedded JDBC Driver
The SimpleApp application loads the Derby Embedded JDBC driver and starts Derby up with this code:
public String driver = "org.apache.derby.jdbc.EmbeddedDriver"; ... Class.forName(driver).newInstance();
Get an Embedded Connection
The SimpleApp application creates and connects to the derbyDB database with this code:
public String protocol = "jdbc:derby:"; ... conn = DriverManager.getConnection(protocol + "derbyDB;create=true", props);
That embedded connection URL, fully constructed, looks like this:
jdbc:derby:derbyDB;create=true
Shut Derby down
A clean shutdown performs a checkpoint and releases resources. If an embedded application doesn't shut down Derby, a checkpoint won't be performed. Nothing bad will happen; it just means that the next connection will be slower because Derby will run its recovery code.
 You might also notice that it tests for a SQL exception. A clean shutdown always throws SQL exception XJ015, which can be ignored.
Compile sample application
Compile the sample application as shown below:
javac SimpleApp.java
You can safely ignore any compile warnings that might pop up.
Run sample application
Run the sample application like this:
java SimpleApp
You should see the output shown below:
SimpleApp starting in embedded mode. Loaded the appropriate driver. Connected to and created database derbyDB Created table derbyDB Inserted 1956 Webster Inserted 1910 Union Updated 1956 Webster to 180 Grand Updated 180 Grand to 300 Lakeshore Verified the rows Dropped table derbyDB Closed result set and statement Committed transaction and closed connection Database shut down normally SimpleApp finished
If instead you see an error like the one below, it means the class path is not correctly set:
java SimpleApp SimpleApp starting in embedded mode. exception thrown: java.lang.ClassNotFoundException: org.apache.derby.jdbc.EmbeddedDriver at java.net.URLClassLoader$1.run(URLClassLoader.java:199) at java.security.AccessController.doPrivileged(Native Method) at java.net.URLClassLoader.findClass(URLClassLoader.java:187) at java.lang.ClassLoader.loadClass(ClassLoader.java:289) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:274) at java.lang.ClassLoader.loadClass(ClassLoader.java:235) at java.lang.ClassLoader.loadClassInternal(ClassLoader.java:302) at java.lang.Class.forName0(Native Method) at java.lang.Class.forName(Class.java:141) at SimpleApp.go(SimpleApp.java:77) at SimpleApp.main(SimpleApp.java:61) SimpleApp finished
For help resolving class path problems, see the "Configure Embedded Derby" and "Verify Derby" instructions.
Embedded Derby supports multiple users in one JVM
Derby supports multiple connections to a given database. An example of an embedded application that manages concurrent users is a Tomcat or Geronimo application server that embeds Derby. Any number of users can execute Web applications that access a database through that Web server.
However, only one JVM may boot ("open") that database, so multiple applications running in different JVMs cannot access the same database. To understand this better, do the following.
The SimpleApp application created a database called derbyDB. In one window connect to this database with ij as shown below:
java org.apache.derby.tools.ij ij version 10.4 ij> connect 'jdbc:derby:derbyDB'; ij>
Now, in another window try to run your SimpleApp application:
java SimpleApp SimpleApp starting in embedded mode Loaded the appropriate driver ----- SQLException ----- SQL State: XJ040 Error Code: 40000 Message: Failed to start database 'derbyDB', see the next exception for details. ----- SQLException ----- SQL State: XSDB6 Error Code: 45000 Message: Another instance of Derby may have already booted the database C:\Apache\db-derby-<IP_ADDRESS>-bin\tutorial\derbyDB. SimpleApp finished
The connection that SimpleApp tries to establish fails because another application, ij, is already connected to the derbyDB database.
The problem is ij and SimpleApp are running in different JVMs and a given database can only be accessed from one JVM. The first application to connect "wins", in this case ij, and prevents other applications from connecting.
In fact, you can establish multiple connections to a given database from different JVMs. That's the topic of the next section, "Step 4: Derby Network Server".


| pull {dplyr} | R Documentation |
pull()
is similar to $
. It's mostly useful because it looks a little
nicer in pipes, it also works with remote data frames, and it can optionally
name the output.
pull(.data, var = -1, name = NULL, ...)
.data |
A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr). See Methods, below, for more details. |
var |
A variable specified as:
The default returns the last column (on the assumption that's the column you've created most recently). This argument is taken by expression and supports quasiquotation (you can unquote column names and column locations). |
name |
An optional parameter that specifies the column to be used
as names for a named vector. Specified in a similar manner as |
... |
For use by methods. |
A vector the same size as .data
.
This function is a generic, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.
The following methods are currently available in loaded packages: no methods found.
mtcars %>% pull(-1) mtcars %>% pull(1) mtcars %>% pull(cyl) # Also works for remote sources if (requireNamespace("dbplyr", quietly = TRUE)) { df <- dbplyr::memdb_frame(x = 1:10, y = 10:1, .name = "pull-ex") df %>% mutate(z = x * y) %>% pull() } # Pull a named vector starwars %>% pull(height, name)


| Trees | Indices | Help |
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Contains all the core ShutIt methods and functionality.
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ShutIt ShutIt build class. |
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| string |
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shutit = init()
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__package__ = None
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cfg =
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cwd =
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pexpect_children =
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shutit_command_history =
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shutit_main_dir =
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shutit_map =
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shutit_modules =
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Generates a random string of given size from the given chars.
|
Initialize the shutit object. Called when imported. |
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cfg
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| Trees | Indices | Help |
|
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| Generated by Epydoc 3.0.1 on Sun Feb 22 17:06:22 2015 | http://epydoc.sourceforge.net |


apache_beam package¶
Subpackages¶
- apache_beam.coders package
- Submodules
- apache_beam.coders.coder_impl module
- apache_beam.coders.coders module
- apache_beam.coders.coders_test module
- apache_beam.coders.coders_test_common module
- apache_beam.coders.fast_coders_test module
- apache_beam.coders.observable module
- apache_beam.coders.observable_test module
- apache_beam.coders.proto2_coder_test_messages_pb2 module
- apache_beam.coders.slow_coders_test module
- apache_beam.coders.slow_stream module
- apache_beam.coders.standard_coders_test module
- apache_beam.coders.stream module
- apache_beam.coders.stream_test module
- apache_beam.coders.typecoders module
- apache_beam.coders.typecoders_test module
- Module contents
- apache_beam.examples package
- Subpackages
- apache_beam.examples.complete package
- Subpackages
- Submodules
- apache_beam.examples.complete.autocomplete module
- apache_beam.examples.complete.autocomplete_test module
- apache_beam.examples.complete.estimate_pi module
- apache_beam.examples.complete.estimate_pi_test module
- apache_beam.examples.complete.tfidf module
- apache_beam.examples.complete.tfidf_test module
- apache_beam.examples.complete.top_wikipedia_sessions module
- apache_beam.examples.complete.top_wikipedia_sessions_test module
- Module contents
- apache_beam.examples.cookbook package
- Submodules
- apache_beam.examples.cookbook.bigquery_schema module
- apache_beam.examples.cookbook.bigquery_side_input module
- apache_beam.examples.cookbook.bigquery_side_input_test module
- apache_beam.examples.cookbook.bigquery_tornadoes module
- apache_beam.examples.cookbook.bigquery_tornadoes_it_test module
- apache_beam.examples.cookbook.bigquery_tornadoes_test module
- apache_beam.examples.cookbook.bigshuffle module
- apache_beam.examples.cookbook.bigshuffle_test module
- apache_beam.examples.cookbook.coders module
- apache_beam.examples.cookbook.coders_test module
- apache_beam.examples.cookbook.combiners_test module
- apache_beam.examples.cookbook.custom_ptransform module
- apache_beam.examples.cookbook.custom_ptransform_test module
- apache_beam.examples.cookbook.datastore_wordcount module
- apache_beam.examples.cookbook.filters module
- apache_beam.examples.cookbook.filters_test module
- apache_beam.examples.cookbook.group_with_coder module
- apache_beam.examples.cookbook.group_with_coder_test module
- apache_beam.examples.cookbook.mergecontacts module
- apache_beam.examples.cookbook.mergecontacts_test module
- apache_beam.examples.cookbook.multiple_output_pardo module
- apache_beam.examples.cookbook.multiple_output_pardo_test module
- Module contents
- apache_beam.examples.snippets package
- apache_beam.examples.complete package
- Submodules
- apache_beam.examples.streaming_wordcap module
- apache_beam.examples.streaming_wordcount module
- apache_beam.examples.wordcount module
- apache_beam.examples.wordcount_debugging module
- apache_beam.examples.wordcount_debugging_test module
- apache_beam.examples.wordcount_it_test module
- apache_beam.examples.wordcount_minimal module
- apache_beam.examples.wordcount_minimal_test module
- apache_beam.examples.wordcount_test module
- Module contents
- Subpackages
- apache_beam.internal package
- apache_beam.io package
- Subpackages
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- Subpackages
- apache_beam.io.gcp.datastore package
- Subpackages
- apache_beam.io.gcp.datastore.v1 package
- Submodules
- apache_beam.io.gcp.datastore.v1.datastoreio module
- apache_beam.io.gcp.datastore.v1.datastoreio_test module
- apache_beam.io.gcp.datastore.v1.fake_datastore module
- apache_beam.io.gcp.datastore.v1.helper module
- apache_beam.io.gcp.datastore.v1.helper_test module
- apache_beam.io.gcp.datastore.v1.query_splitter module
- apache_beam.io.gcp.datastore.v1.query_splitter_test module
- Module contents
- apache_beam.io.gcp.datastore.v1 package
- Module contents
- Subpackages
- apache_beam.io.gcp.internal package
- apache_beam.io.gcp.tests package
- apache_beam.io.gcp.datastore package
- Submodules
- apache_beam.io.gcp.bigquery module
- apache_beam.io.gcp.bigquery_test module
- apache_beam.io.gcp.gcsio module
- apache_beam.io.gcp.gcsio_test module
- apache_beam.io.gcp.pubsub module
- apache_beam.io.gcp.pubsub_test module
- Module contents
- Subpackages
- apache_beam.io.gcp package
- Submodules
- apache_beam.io.avroio module
- apache_beam.io.avroio_test module
- apache_beam.io.concat_source module
- apache_beam.io.concat_source_test module
- apache_beam.io.filebasedsource module
- apache_beam.io.filebasedsource_test module
- apache_beam.io.fileio module
- apache_beam.io.fileio_test module
- apache_beam.io.iobase module
- apache_beam.io.range_trackers module
- apache_beam.io.range_trackers_test module
- apache_beam.io.source_test_utils module
- apache_beam.io.source_test_utils_test module
- apache_beam.io.sources_test module
- apache_beam.io.textio module
- apache_beam.io.textio_test module
- apache_beam.io.tfrecordio module
- apache_beam.io.tfrecordio_test module
- Module contents
- Subpackages
- apache_beam.metrics package
- apache_beam.runners package
- Subpackages
- apache_beam.runners.dataflow package
- Subpackages
- apache_beam.runners.dataflow.internal package
- Submodules
- apache_beam.runners.dataflow.internal.apiclient module
- apache_beam.runners.dataflow.internal.apiclient_test module
- apache_beam.runners.dataflow.internal.dependency module
- apache_beam.runners.dataflow.internal.dependency_test module
- apache_beam.runners.dataflow.internal.names module
- Module contents
- apache_beam.runners.dataflow.native_io package
- apache_beam.runners.dataflow.internal package
- Submodules
- apache_beam.runners.dataflow.dataflow_metrics module
- apache_beam.runners.dataflow.dataflow_metrics_test module
- apache_beam.runners.dataflow.dataflow_runner module
- apache_beam.runners.dataflow.dataflow_runner_test module
- apache_beam.runners.dataflow.template_runner_test module
- apache_beam.runners.dataflow.test_dataflow_runner module
- Module contents
- Subpackages
- apache_beam.runners.direct package
- Submodules
- apache_beam.runners.direct.bundle_factory module
- apache_beam.runners.direct.clock module
- apache_beam.runners.direct.consumer_tracking_pipeline_visitor module
- apache_beam.runners.direct.consumer_tracking_pipeline_visitor_test module
- apache_beam.runners.direct.direct_metrics module
- apache_beam.runners.direct.direct_metrics_test module
- apache_beam.runners.direct.direct_runner module
- apache_beam.runners.direct.evaluation_context module
- apache_beam.runners.direct.executor module
- apache_beam.runners.direct.helper_transforms module
- apache_beam.runners.direct.transform_evaluator module
- apache_beam.runners.direct.transform_result module
- apache_beam.runners.direct.watermark_manager module
- Module contents
- apache_beam.runners.test package
- apache_beam.runners.dataflow package
- Submodules
- apache_beam.runners.common module
- apache_beam.runners.runner module
- apache_beam.runners.runner_test module
- Module contents
- Subpackages
- apache_beam.tests package
- apache_beam.transforms package
- Submodules
- apache_beam.transforms.combiners module
- apache_beam.transforms.combiners_test module
- apache_beam.transforms.core module
- apache_beam.transforms.cy_combiners module
- apache_beam.transforms.display module
- apache_beam.transforms.display_test module
- apache_beam.transforms.ptransform module
- apache_beam.transforms.ptransform_test module
- apache_beam.transforms.sideinputs module
- apache_beam.transforms.sideinputs_test module
- apache_beam.transforms.timeutil module
- apache_beam.transforms.trigger module
- apache_beam.transforms.trigger_test module
- apache_beam.transforms.util module
- apache_beam.transforms.window module
- apache_beam.transforms.window_test module
- apache_beam.transforms.write_ptransform_test module
- Module contents
- apache_beam.typehints package
- Submodules
- apache_beam.typehints.decorators module
- apache_beam.typehints.opcodes module
- apache_beam.typehints.trivial_inference module
- apache_beam.typehints.trivial_inference_test module
- apache_beam.typehints.typecheck module
- apache_beam.typehints.typed_pipeline_test module
- apache_beam.typehints.typehints module
- apache_beam.typehints.typehints_test module
- Module contents
- apache_beam.utils package
- Submodules
- apache_beam.utils.annotations module
- apache_beam.utils.annotations_test module
- apache_beam.utils.counters module
- apache_beam.utils.path module
- apache_beam.utils.path_test module
- apache_beam.utils.pipeline_options module
- apache_beam.utils.pipeline_options_test module
- apache_beam.utils.pipeline_options_validator module
- apache_beam.utils.pipeline_options_validator_test module
- apache_beam.utils.processes module
- apache_beam.utils.processes_test module
- apache_beam.utils.profiler module
- apache_beam.utils.retry module
- apache_beam.utils.retry_test module
- apache_beam.utils.timestamp module
- apache_beam.utils.timestamp_test module
- apache_beam.utils.windowed_value module
- apache_beam.utils.windowed_value_test module
- Module contents
Submodules¶
apache_beam.error module¶
Python Dataflow error classes.
-
exception
apache_beam.error.
BeamError
[source]¶ Bases:
exceptions.Exception
Base class for all Beam errors.
-
exception
apache_beam.error.
PValueError
[source]¶ Bases:
apache_beam.error.BeamError
An error related to a PValue object (e.g. value is not computed).
-
exception
apache_beam.error.
PipelineError
[source]¶ Bases:
apache_beam.error.BeamError
An error in the pipeline object (e.g. a PValue not linked to it).
-
exception
apache_beam.error.
RunnerError
[source]¶ Bases:
apache_beam.error.BeamError
An error related to a Runner object (e.g. cannot find a runner to run).
-
exception
apache_beam.error.
SideInputError
[source]¶ Bases:
apache_beam.error.BeamError
An error related to a side input to a parallel Do operation.
-
exception
apache_beam.error.
TransformError
[source]¶ Bases:
apache_beam.error.BeamError
An error related to a PTransform object.
apache_beam.pipeline module¶
Pipeline, the top-level Dataflow object.
A pipeline holds a DAG of data transforms. Conceptually the nodes of the DAG are transforms (PTransform objects) and the edges are values (mostly PCollection objects). The transforms take as inputs one or more PValues and output one or more PValues.
The pipeline offers functionality to traverse the graph. The actual operation to be executed for each node visited is specified through a runner object.
Typical usage:
# Create a pipeline object using a local runner for execution. p = beam.Pipeline(‘DirectRunner’)
# Add to the pipeline a “Create” transform. When executed this # transform will produce a PCollection object with the specified values. pcoll = p | ‘create’ >> beam.Create([1, 2, 3])
# Another transform could be applied to pcoll, e.g., writing to a text file. # For other transforms, refer to transforms/ directory. pcoll | ‘write’ >> beam.io.WriteToText(‘./output’)
# run() will execute the DAG stored in the pipeline. The execution of the # nodes visited is done using the specified local runner. p.run()
-
class
apache_beam.pipeline.
AppliedPTransform
(parent, transform, full_label, inputs)[source]¶ Bases:
object
A transform node representing an instance of applying a PTransform.
This is an internal class used for bookkeeping by a Pipeline.
-
class
apache_beam.pipeline.
Pipeline
(runner=None, options=None, argv=None)[source]¶ Bases:
object
A pipeline object that manages a DAG of PValues and their PTransforms.
Conceptually the PValues are the DAG’s nodes and the PTransforms computing the PValues are the edges.
All the transforms applied to the pipeline must have distinct full labels. If same transform instance needs to be applied then a clone should be created with a new label (e.g., transform.clone(‘new label’)).
-
apply
(transform, pvalueish=None, label=None)[source]¶ Applies a custom transform using the pvalueish specified.
Parameters: - transform – the PTranform to apply.
- pvalueish – the input for the PTransform (typically a PCollection).
Raises: TypeError
– if the transform object extracted from the argument list is not a PTransform.RuntimeError
– if the transform object was already applied to this pipeline and needs to be cloned in order to apply again.
-
visit
(visitor)[source]¶ Visits depth-first every node of a pipeline’s DAG.
Parameters: visitor – PipelineVisitor object whose callbacks will be called for each node visited. See PipelineVisitor comments.
Raises: TypeError
– if node is specified and is not a PValue.pipeline.PipelineError
– if node is specified and does not belong to this pipeline instance.
-
-
class
apache_beam.pipeline.
PipelineVisitor
[source]¶ Bases:
object
Visitor pattern class used to traverse a DAG of transforms.
This is an internal class used for bookkeeping by a Pipeline.
-
enter_composite_transform
(transform_node)[source]¶ Callback for entering traversal of a composite transform node.
-
leave_composite_transform
(transform_node)[source]¶ Callback for leaving traversal of a composite transform node.
-
apache_beam.pipeline_test module¶
Unit tests for the Pipeline class.
-
class
apache_beam.pipeline_test.
Breakfast
(flags=None, **kwargs)[source]¶ Bases:
apache_beam.pipeline_test.Bacon
,apache_beam.pipeline_test.Eggs
-
class
apache_beam.pipeline_test.
DoFnTest
(methodName='runTest')[source]¶ Bases:
unittest.case.TestCase
-
class
apache_beam.pipeline_test.
FakeSource
(vals)[source]¶ Bases:
apache_beam.runners.dataflow.native_io.iobase.NativeSource
Fake source returning a fixed list of values.
-
class
apache_beam.pipeline_test.
PipelineOptionsTest
(methodName='runTest')[source]¶ Bases:
unittest.case.TestCase
apache_beam.pvalue module¶
PValue, PCollection: one node of a dataflow graph.
A node of a dataflow processing graph is a PValue. Currently, there is only one type: PCollection (a potentially very large set of arbitrary values). Once created, a PValue belongs to a pipeline and has an associated transform (of type PTransform), which describes how the value will be produced when the pipeline gets executed.
-
apache_beam.pvalue.
AsDict
(pcoll, label=None)[source]¶ Create a DictPCollectionView from the elements of input PCollection.
The contents of the given PCollection whose elements are 2-tuples of key and value will be available as a dict-like object in PTransforms that use the returned PCollectionView as a side input.
Parameters: - pcoll – Input pcollection containing 2-tuples of key and value.
- label – Label to be specified if several AsDict’s for the same PCollection.
Returns: A dict PCollectionView containing the dict as above.
-
apache_beam.pvalue.
AsIter
(pcoll, label=None)[source]¶ Create an IterablePCollectionView from the elements of input PCollection.
The contents of the given PCollection will be available as an iterable in PTransforms that use the returned PCollectionView as a side input.
Parameters: - pcoll – Input pcollection.
- label – Label to be specified if several AsIter’s for the same PCollection.
Returns: An iterable PCollectionView containing the elements as above.
-
apache_beam.pvalue.
AsList
(pcoll, label=None)[source]¶ Create a ListPCollectionView from the elements of input PCollection.
The contents of the given PCollection will be available as a list-like object in PTransforms that use the returned PCollectionView as a side input.
Parameters: - pcoll – Input pcollection.
- label – Label to be specified if several AsList’s for the same PCollection.
Returns: A list PCollectionView containing the elements as above.
-
apache_beam.pvalue.
AsSingleton
(pcoll, default_value=<object object>, label=None)[source]¶ Create a SingletonPCollectionView from the contents of input PCollection.
The input PCollection should contain at most one element (per window) and the resulting PCollectionView can then be used as a side input to PTransforms. If the PCollectionView is empty (for a given window), the side input value will be the default_value, if specified; otherwise, it will be an EmptySideInput object.
Parameters: - pcoll – Input pcollection.
- default_value – Default value for the singleton view.
- label – Label to be specified if several AsSingleton’s with different defaults for the same PCollection.
Returns: A singleton PCollectionView containing the element as above.
-
class
apache_beam.pvalue.
DictPCollectionView
(pipeline, window_mapping_fn)[source]¶ Bases:
apache_beam.pvalue.PCollectionView
A PCollectionView that can be treated as a dict.
-
class
apache_beam.pvalue.
DoOutputsTuple
(pipeline, transform, tags, main_tag)[source]¶ Bases:
object
An object grouping the multiple outputs of a ParDo or FlatMap transform.
-
class
apache_beam.pvalue.
EmptySideInput
[source]¶ Bases:
object
Value indicating when a singleton side input was empty.
If a PCollection was furnished as a singleton side input to a PTransform, and that PCollection was empty, then this value is supplied to the DoFn in the place where a value from a non-empty PCollection would have gone. This alerts the DoFn that the side input PCollection was empty. Users may want to check whether side input values are EmptySideInput, but they will very likely never want to create new instances of this class themselves.
-
class
apache_beam.pvalue.
IterablePCollectionView
(pipeline, window_mapping_fn)[source]¶ Bases:
apache_beam.pvalue.PCollectionView
A PCollectionView that can be treated as an iterable.
-
class
apache_beam.pvalue.
ListPCollectionView
(pipeline, window_mapping_fn)[source]¶ Bases:
apache_beam.pvalue.PCollectionView
A PCollectionView that can be treated as a list.
-
class
apache_beam.pvalue.
PBegin
(pipeline, tag=None, element_type=None)[source]¶ Bases:
apache_beam.pvalue.PValue
A pipeline begin marker used as input to create/read transforms.
The class is used internally to represent inputs to Create and Read transforms. This allows us to have transforms that uniformly take PValue(s) as inputs.
-
class
apache_beam.pvalue.
PCollection
(pipeline, **kwargs)[source]¶ Bases:
apache_beam.pvalue.PValue
A multiple values (potentially huge) container.
Dataflow users should not construct PCollection objects directly in their pipelines.
-
windowing
¶
-
-
class
apache_beam.pvalue.
PCollectionView
(pipeline, window_mapping_fn)[source]¶ Bases:
apache_beam.pvalue.PValue
An immutable view of a PCollection that can be used as a side input.
-
windowing
¶
-
-
class
apache_beam.pvalue.
PDone
(pipeline, tag=None, element_type=None)[source]¶ Bases:
apache_beam.pvalue.PValue
PDone is the output of a transform that has a trivial result such as Write.
-
class
apache_beam.pvalue.
PValue
(pipeline, tag=None, element_type=None)[source]¶ Bases:
object
Base class for PCollection.
Dataflow users should not construct PValue objects directly in their pipelines.
- A PValue has the following main characteristics:
- Belongs to a pipeline. Added during object initialization.
- Has a transform that can compute the value if executed.
- Has a value which is meaningful if the transform was executed.
-
apply
(*args, **kwargs)[source]¶ Applies a transform or callable to a PValue.
Parameters: - *args – positional arguments.
- **kwargs – keyword arguments.
The method will insert the pvalue as the next argument following an optional first label and a transform/callable object. It will call the pipeline.apply() method with this modified argument list.
-
class
apache_beam.pvalue.
SideOutputValue
(tag, value)[source]¶ Bases:
object
An object representing a tagged value.
ParDo, Map, and FlatMap transforms can emit values on multiple outputs which are distinguished by string tags. The DoFn will return plain values if it wants to emit on the main output and SideOutputValue objects if it wants to emit a value on a specific tagged output.
-
class
apache_beam.pvalue.
SingletonPCollectionView
(pipeline, has_default, default_value, window_mapping_fn)[source]¶ Bases:
apache_beam.pvalue.PCollectionView
A PCollectionView that contains a single object.
apache_beam.pvalue_test module¶
Unit tests for the PValue and PCollection classes.
-
class
apache_beam.pvalue_test.
FakePipeline
(runner=None, options=None, argv=None)[source]¶ Bases:
apache_beam.pipeline.Pipeline
Fake pipeline object used to check if apply() receives correct args.
apache_beam.test_pipeline module¶
Test Pipeline, a wrapper of Pipeline for test purpose
-
class
apache_beam.test_pipeline.
TestPipeline
(runner=None, options=None, argv=None, is_integration_test=False, blocking=True)[source]¶ Bases:
apache_beam.pipeline.Pipeline
TestPipeline class is used inside of Beam tests that can be configured to run against pipeline runner.
It has a functionality to parse arguments from command line and build pipeline options for tests who runs against a pipeline runner and utilizes resources of the pipeline runner. Those test functions are recommended to be tagged by @attr(“ValidatesRunner”) annotation.
In order to configure the test with customized pipeline options from command line, system argument ‘test-pipeline-options’ can be used to obtains a list of pipeline options. If no options specified, default value will be used.
For example, use following command line to execute all ValidatesRunner tests:
python setup.py nosetests -a ValidatesRunner --test-pipeline-options="--runner=DirectRunner --job_name=myJobName --num_workers=1"
For example, use assert_that for test validation:
pipeline = TestPipeline() pcoll = ... assert_that(pcoll, equal_to(...)) pipeline.run()
-
get_full_options_as_args
(**extra_opts)[source]¶ Get full pipeline options as an argument list.
Append extra pipeline options to existing option list if provided. Test verifier (if contains in extra options) should be pickled before appending, and will be unpickled later in the TestRunner.
-
apache_beam.test_pipeline_test module¶
Unit test for the TestPipeline class
-
class
apache_beam.test_pipeline_test.
SimpleMatcher
[source]¶ Bases:
hamcrest.core.base_matcher.BaseMatcher
-
class
apache_beam.test_pipeline_test.
TestPipelineTest
(methodName='runTest')[source]¶ Bases:
unittest.case.TestCase
-
EXTRA_OPT_CASES
= [{'expected': ['--name=Mark'], 'options': {'name': 'Mark'}}, {'expected': ['--student'], 'options': {'student': True}}, {'expected': [], 'options': {'student': False}}, {'expected': ['--name=Mark', '--student'], 'options': {'name': 'Mark', 'student': True}}]¶
-
TEST_CASE
= {'expected_list': ['--job=mockJob', '--male', '--age=1'], 'options': ['--test-pipeline-options', '--job=mockJob --male --age=1'], 'expected_dict': {'job': 'mockJob', 'male': True, 'age': 1}}¶
-
apache_beam.version module¶
Apache Beam SDK version information and utilities.
Module contents¶
Apache Beam SDK for Python.
Apache Beam <http://cloud.google.com/dataflow/> provides a simple, powerful programming model for building both batch and streaming parallel data processing pipelines.
The Apache Beam SDK for Python provides access to Apache Beam capabilities from the Python programming language.
Status¶
The SDK is still early in its development, and significant changes should be expected before the first stable version.
Overview¶
The key concepts in this programming model are
- PCollection: represents a collection of data, which could be bounded or unbounded in size.
- PTransform: represents a computation that transforms input PCollections into output PCollections.
- Pipeline: manages a directed acyclic graph of PTransforms and PCollections that is ready for execution.
- Runner: specifies where and how the Pipeline should execute.
- Reading and Writing Data: your pipeline can read from an external source and write to an external data sink.
Typical usage¶
At the top of your source file:
import apache_beam as beam
After this import statement
- transform classes are available as beam.FlatMap, beam.GroupByKey, etc.
- Pipeline class is available as beam.Pipeline
- text read/write transforms are available as beam.io.ReadfromText, beam.io.WriteToText
Examples
The examples subdirectory has some examples.


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Variable Frequency Oscillator Using Direct Digital Synthesis
Project Photos
Solar Power Electronics Designs and Projects
Power Conversion - Quasi-DC Power Converter
Power Electronics Designs and Projects
High-side Current Sense
Hacking the TL494 LTSpice Model


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BREAKING Baby 'seriously hurt' and rushed to hospital after 'incident'
We'll be bringing you the very latest updates, pictures and video on this breaking news story
by Tom Davidson, https://www.mirror.co.uk/authors/tom-davidson/A baby is said to have been seriously hurt in an 'incident' in Balymoney this evening.
A PSNI spokesperson said: "Police are currently investigating an incident in the Mosside area of Ballymoney.
"There are no further details at this stage."
DUP Causeway Councillor John McAuley said forensics are at the family's home and that a criminal investigation appears to have been launched.
He added: "A baby has been seriously injured so obviously our thoughts are first and foremost with them and connected family members.
"We hope the injured baby makes a speedy recovery.
"I am not sure who is involved but if anybody has any information I would certainly ask them to pass it on to the police.
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See morePaku is an interactive menu for the restaurant built with JS
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See moreA web publicity banner for a coffee, built with HTML and GASP.
See moreA React Funtional Component Testimony, an App developed with React
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I performed as a Web Developer and content in AEM, creating some of the pages from scratch and also applying changes in multiple existing vehicles pages and campaigns for VolksWagen account website.
During this time as a Web Developer I was in charge of creating web pages from scratch, updating web paes with the highest standards.
I was directly involved to get in touch with our customers, via phone, mail, conference, e.g. Providing tech support on HP UCMDB and HP OO.
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After getting involved with technology, I realize that it would be a great opportunity to grow and learn by studying IT. Which indeed it has been; I got familiar with programming languages and methodologies, project management techniques, operative systems and of course create and provide solutions.


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||||||
|---|---|---|---|---|---|---|
| Avg Playtime | ELO | Total games played | Wins | Losses | Average winrate | |
| {{king.avg_playtime_s}} | {{king.elo}} | {{stats[king.id].games_played}} | {{stats[king.id].wins}} | {{stats[king.id].games_played - stats[king.id].wins}} | {{stats[king.id].winrate}}% |
| {{player.name}} (loser) |
Total Games | Playtime | Wins | elo | |
|---|---|---|---|---|---|
| {{player.name}} (winner) | {{match.wins}} | {{stats[player.id].games_played || 0}} | {{stats[player.id].avg_playtime_s || 0}} | {{stats[player.id].wins || 0}} | {{stats[player.id].elo || 0}} |


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current:
1995


HEARTBREAKERS (director: David Mirkin; screenwriters: Robert Dunn/Paul Guay/ Stephen Mazur; cinematographer: Dean Semler; editor: William Steinkamp; cast: Sigourney Weaver (Angela Nardino/ Max Conners/Ulga Yevanova), Jennifer Love Hewitt (Wendy/Page Conners/Jane Helstrom), Ray Liotta (Dean Cumanno/Vinny Staggliano), Jason Lee (Jack Withrowe), Anne Bancroft (Gloria Vogal/Barbara), Nora Dunn (Housekeeper), Gene Hackman (William B. Tensy), Michael Hitchcock (Dr. Davis); Runtime: 120; MGM; 2001)
Reviewed by Dennis Schwartz
Sigourney Weaver and Jennifer Love Hewitt are mother-and-daughter con artists.  Then the deadly duo finds a new target, using different names and disguises. It results in laughs that are engineered from the lowest common denominator of comedy. But the good news is, that there are laughs to be had, if you are willing to bite into the over-the-top performances, the unseamly sight gags, and absurd plot. The bad news is, the film is sympathetic to these revolting hustlers and the film's amoral theme is hard to justify, except to say that this is just a cartoon for adults. It also begins to drag, as the premise grows weary from overkill.
Their latest victim is Ray Liotta, a chop-shop operator from New Jersey and a womanizer who lusts for Weaver, that is until on their wedding night she passes out from too much drink. Hewitt, his new office worker, tempts him when he returns to the office during his wife's wedding night sleeping attack.
The divorce settlement is $300,000 and a Mercedes-Benz, but it's not enough to pay off the IRS according to an agent (Anne Bancroft), who closes mom's bank account. The petulant daughter wanted out of the partnership, anxious to go on her own con jobs, which is the reason why mom arranged for the phony con artist IRS agent, her old friend who taught her the ropes. She does this to keep Hewitt with her, even if it is a dysfunctional relationship she is trying to save, one filled with all the signs of a Freudian-like mother-daughter rivalry.  But, while mom pretends to be an exotic Russian to catch the chain-smoking and constantly coughing and wheezing Hackman's interest, daughter falls for the only nice guy in the film, Jason Lee, who owns the restaurant he is a bartender in and owns the piece of waterfront property the restaurant sits on, that is worth $3,000,000. She wavers back and forth on whether his love for her is sincere or if he's just goofy, as she decides whether to con him or not.
"Heartbreakers" is a forgettable fluff film, that tries unsuccessfully to work its way to romance and also be a caper flick. It works best when showing off the boobs of Weaver and Hewitt, who are outfitted in dresses sluts would wear to walk the streets, as the film proudly relies on the old adage, that sex sells. There were a number of funny bits, and they came from Hackman's W. C. Fields-like performance, calling out for the love of smoking and preaching its virtues, even encouraging children to take up smoking. In one scene he blows smoke into a parrot's cage and it soon keels over. The rest of the comedy was delivered by Liotta's enthusiastic over-the-top way of doing things, whether fishing by firing a gun into the ocean, ditching a corpse New Jersey-style, or by preparing for sex while almost completely naked and tied to the bedposts. What the comedy had going for it, was a lot of spunk, enough to overlook the film's many drawbacks.
REVIEWED ON 4/1/2001 GRADE: C+
Dennis Schwartz: "Ozus' World Movie Reviews"
http://www.sover.net/~ozus
<EMAIL_ADDRESS>© ALL RIGHTS RESERVED DENNIS SCHWARTZ
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


COURANT INSTITUTE OF MATHEMATICAL SCIENCES
The Courant Institute of Mathematical Sciences is affiliated (but somewhat independent) of New York University. It teaches many things like pure math, applied math, statistics, and computer science. Acceptance is based on skill and personal character.
Courant is ranked #1 for applied math in the world.
Courant is home to Facebook's AI Research Director, Yann LeCun.
This project was made for a Practical Computer Security course, intended to be genuinely useful, although it could use some internal polishing around the edges. If it educates a new audience at all and provides a working extension, it has done well.
The project addresses reflected cross site scripting and uses Google SafeBrowing API and the Web of Trust API to reliably alert of probable threats, yet keeping it simple for the user.
The makers of the project are here:
- P. Chen
- M. Lukiman<EMAIL_ADDRESS>- C. Wong


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Level of confidence that token is an accurately-transcribed word
extremely low
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very high


referenced
by Eliot Jordan at 2023-07-12 19:17:30.merged
by Eliot Jordan at 2023-07-12 19:17:30.closed
by Eliot Jordan at 2023-07-12 19:17:30.head_ref_deleted
by Eliot Jordan at 2023-07-12 19:17:33.labeled
by Kevin Reiss at 2023-07-12 15:50:23.assigned
by Kevin Reiss at 2023-07-12 17:05:11.ready_for_review
by Jane Sandberg at 2023-07-12 17:28:14.referenced
by Max Kadel at 2023-07-12 19:37:28.merged
by Max Kadel at 2023-07-12 19:37:28.closed
by Max Kadel at 2023-07-12 19:37:28.head_ref_deleted
by Max Kadel at 2023-07-12 19:37:29.Re-opening this one, since we aren't yet logging the error messages that traject throws.
reopened
by Jane Sandberg at 2023-07-12 14:22:18.unassigned
by Max Kadel at 2023-07-12 14:36:45.labeled
by Kevin Reiss at 2023-07-12 15:35:10.unlabeled
by Kevin Reiss at 2023-07-12 15:35:25.assigned
by Jane Sandberg at 2023-07-12 16:00:14.assigned
by Max Kadel at 2023-07-12 16:00:14.assigned
by Liz Garcia at 2023-07-12 16:00:14.assigned
by None at 2023-07-12 16:00:15.closed
by Max Kadel at 2023-07-12 19:37:30.I've asked Rachael and Ming to review and when I have their feedback, we can move forward with this in production.
assigned
by esmé cowles at 2023-07-12 13:14:52.assigned
by Cliff Wulfman at 2023-07-12 13:14:53.assigned
by Cliff Wulfman at 2023-07-12 13:53:23.The site is being recomposed.
closed
by Cliff Wulfman at 2023-07-12 19:08:16.The site is being recomposed.
closed
by Cliff Wulfman at 2023-07-12 19:08:37.Reminder to recepient of the report: Opening the .csv directly in Excel risks corrupting the MMSID, which may be converted to scientific notations. Import it instead to avoid the corruption.
The last bit of housekeeping is the new webfile share needs to be writable by www-data. Right now on the staging site you get errors like:
assigned
by Francis Kayiwa at 2023-07-12 15:15:07.@mzelesky just another ping on this one so we can flesh out the details here.
I was thinking it would be useful to include the successful items as well, as Circ may want to be able to point to easy evidence that a particular item was renewed. But maybe it's overkill that isn't actually needed.
mentioned
by None at 2023-07-12 15:09:18.subscribed
by None at 2023-07-12 15:09:18.See https://gist.github.com/mzelesky/2c70e8ad9e41ad66a7c517973eec4cc3
The job does not have to be run in sequence, meaning you don't have to wait for another job to complete before submitting it, though I think running this job the day after the other 2 jobs run would make sense.
See https://gist.github.com/mzelesky/3e4a0167c00899839fd1d5f79e8bb047
This should be run weekly.
See https://gist.github.com/mzelesky/4382296a6fa4bfac7c68a4139ccbb60e
This job should be run weekly.
review_requested
by None at 2023-07-12 22:03:44.referenced
by Jane Sandberg at 2023-07-12 22:07:41.merged
by Jane Sandberg at 2023-07-12 22:07:41.closed
by Jane Sandberg at 2023-07-12 22:07:41.head_ref_deleted
by Jane Sandberg at 2023-07-12 22:07:42.head_ref_force_pushed
by Jane Sandberg at 2023-07-12 20:22:16.head_ref_force_pushed
by Jane Sandberg at 2023-07-12 20:58:14.head_ref_force_pushed
by Jane Sandberg at 2023-07-12 22:50:32.head_ref_force_pushed
by Jane Sandberg at 2023-07-12 22:56:05.head_ref_force_pushed
by Jane Sandberg at 2023-07-12 23:06:10.unassigned
by None at 2023-07-12 13:17:17.I was able to follow these procedures to get advanced search working with the blacklight .internaltestapp: https://code4lib.slack.com/archives/C54TB5WDQ/p1687452502967029
These don't work for orangelight -- I wonder if it's because we also have a complex default query that we also send.
unassigned
by Jane Sandberg at 2023-07-12 15:51:19.referenced
by Hector Correa at 2023-07-11 23:41:36.merged
by Hector Correa at 2023-07-11 23:41:36.closed
by Hector Correa at 2023-07-11 23:41:36.head_ref_deleted
by Hector Correa at 2023-07-11 23:41:37.review_dismissed
by Hector Correa at 2023-07-11 23:42:40.closed
by None at 2023-07-12 12:34:38.closed
by Bess Sadler at 2023-07-12 13:06:33.closed
by Kate Lynch at 2023-07-12 15:13:46.I was under the impression that my team would review and approve them and then check Discovery to ensure it's indexed before closing out this ticket. Forgive me if I misunderstood.
closed
by Kate Lynch at 2023-07-12 15:13:21.head_ref_force_pushed
by None at 2023-07-12 12:27:07.renamed
by None at 2023-07-12 12:33:35.head_ref_force_pushed
by None at 2023-07-12 12:34:04.ready_for_review
by None at 2023-07-12 15:12:20.referenced
by Kate Lynch at 2023-07-12 15:15:29.merged
by Kate Lynch at 2023-07-12 15:15:29.closed
by Kate Lynch at 2023-07-12 15:15:29.head_ref_deleted
by Kate Lynch at 2023-07-12 15:15:31.closed
by Kate Lynch at 2023-07-12 15:15:31.Deprecate in favor of a shared upon common practice to remove ActiveStorage as the team proceeds with other issues.
closed
by Kate Lynch at 2023-07-12 15:18:08.Ongoing known issue with Princeton VPN for shifting IP ranges; closing.
closed
by Kate Lynch at 2023-07-12 15:19:10.Completed.
closed
by Kate Lynch at 2023-07-12 15:19:29.labeled
by Kate Lynch at 2023-07-12 15:32:22.Only the depositor can see the "complete" button currently. This is the issue.
This will only be an issue for our fixture objects in testing data migration, when others are checking and advancing them.
labeled
by Bess Sadler at 2023-07-12 15:34:30.renamed
by Kate Lynch at 2023-07-12 15:46:37.unlabeled
by Kate Lynch at 2023-07-12 15:46:46.labeled
by Kate Lynch at 2023-07-12 15:46:46.head_ref_force_pushed
by James R. Griffin III at 2023-07-12 13:21:20.head_ref_force_pushed
by James R. Griffin III at 2023-07-12 13:26:10.closed
by James R. Griffin III at 2023-07-12 15:54:48.labeled
by Kate Lynch at 2023-07-12 15:29:25.unassigned
by Hannah H at 2023-07-12 15:29:28.assigned
by None at 2023-07-12 15:57:04.assigned
by None at 2023-07-12 15:57:21.assigned
by None at 2023-07-12 15:57:22.Functionality for MVP:
Use first two net IDs from list (order created in database for now)
"@hhh409, @mcj12, and 11 others" and when "11 others" is hovered over, the other display names appear in a tooltip
mentioned
by None at 2023-07-12 15:38:13.subscribed
by None at 2023-07-12 15:38:13.assigned
by None at 2023-07-12 17:31:00.referenced
by Kate Lynch at 2023-07-12 19:43:11.merged
by Kate Lynch at 2023-07-12 19:43:11.closed
by Kate Lynch at 2023-07-12 19:43:11.head_ref_deleted
by Kate Lynch at 2023-07-12 19:43:12.labeled
by Kate Lynch at 2023-07-12 15:35:56.assigned
by None at 2023-07-12 17:27:42.closed
by Kate Lynch at 2023-07-12 19:43:12.assigned
by Kate Lynch at 2023-07-12 19:47:54.assigned
by Kate Lynch at 2023-07-12 20:01:24.@hackartisan - where do you think an appropriate place to document would be? It does seem to give more / better nginx insight, which is helpful, especially for the types of issues we've been seeing on Orangelight. See the NGINX dashboard - now with Orangelight data!
mentioned
by None at 2023-07-12 13:27:51.subscribed
by None at 2023-07-12 13:27:52.mentioned
by None at 2023-07-11 22:51:43.subscribed
by None at 2023-07-11 22:51:43.I will schedule a meeting with Mark and the mendel staff to finalize the details.
The issue comes from the import configuration we have for library databases from libguides. Descriptions should be imported as html rather than plain text. The linked PR updates the configuration for the importer. In this instance the "Best Bet" content type referenced the Worldcat Database content type which is where the description rendered is pulled from.
labeled
by Liz Garcia at 2023-07-12 20:15:52.transferred
by Jane Sandberg at 2023-07-12 20:25:56.transferred
by Kevin Reiss at 2023-07-12 21:31:48.assigned
by Kevin Reiss at 2023-07-12 22:43:31.For #2021
Deployed to staging.
deployed
by None at 2023-07-12 22:47:10.ready_for_review
by Kevin Reiss at 2023-07-12 23:12:41.referenced
by Trey Pendragon at 2023-07-12 00:21:44.merged
by Trey Pendragon at 2023-07-12 00:21:44.closed
by Trey Pendragon at 2023-07-12 00:21:44.head_ref_deleted
by Trey Pendragon at 2023-07-12 00:21:45.referenced
by None at 2023-07-12 00:04:48.closed
by Trey Pendragon at 2023-07-12 00:21:45.head_ref_force_pushed
by Eliot Jordan at 2023-07-12 17:51:01.referenced
by Eliot Jordan at 2023-07-12 17:59:08.merged
by Eliot Jordan at 2023-07-12 17:59:09.closed
by Eliot Jordan at 2023-07-12 17:59:09.head_ref_deleted
by Eliot Jordan at 2023-07-12 17:59:10.closed
by Eliot Jordan at 2023-07-12 17:59:10.assigned
by Eliot Jordan at 2023-07-12 18:47:29.@tpendragon Just needs a rebase.
@eliotjordan Rebased.
@tpendragon Something's amiss after that rebase. Maybe just need to re-add TC040?
Yup, lost a commit in there.
mentioned
by Trey Pendragon at 2023-07-12 18:05:50.subscribed
by Trey Pendragon at 2023-07-12 18:05:50.head_ref_force_pushed
by Trey Pendragon at 2023-07-12 18:10:27.mentioned
by Eliot Jordan at 2023-07-12 18:10:47.subscribed
by Eliot Jordan at 2023-07-12 18:10:47.mentioned
by Trey Pendragon at 2023-07-12 18:47:07.subscribed
by Trey Pendragon at 2023-07-12 18:47:07.head_ref_force_pushed
by Trey Pendragon at 2023-07-12 19:19:06.referenced
by Trey Pendragon at 2023-07-12 19:26:17.merged
by Trey Pendragon at 2023-07-12 19:26:17.closed
by Trey Pendragon at 2023-07-12 19:26:17.head_ref_deleted
by Trey Pendragon at 2023-07-12 19:26:18.referenced
by Trey Pendragon at 2023-07-12 18:10:27.referenced
by Trey Pendragon at 2023-07-12 19:19:05.closed
by Trey Pendragon at 2023-07-12 19:26:18.head_ref_force_pushed
by Trey Pendragon at 2023-07-12 18:09:43.convert_to_draft
by Trey Pendragon at 2023-07-12 19:19:37.head_ref_force_pushed
by Trey Pendragon at 2023-07-12 19:26:49.deployed
by None at 2023-07-12 19:29:04.deployed
by None at 2023-07-12 19:43:27.deployed
by None at 2023-07-12 21:13:53.referenced
by Eliot Jordan at 2023-07-12 21:47:26.merged
by Eliot Jordan at 2023-07-12 21:47:26.closed
by Eliot Jordan at 2023-07-12 21:47:27.head_ref_deleted
by Eliot Jordan at 2023-07-12 21:47:27.closed
by Eliot Jordan at 2023-07-12 21:47:28.referenced
by Trey Pendragon at 2023-07-12 23:26:18.Closed in preference to https://github.com/pulibrary/pulfalight/issues/1281
I'm seeing the same effect on staging, but it looks slightly different.
labeled
by Trey Pendragon at 2023-07-12 21:33:14.referenced
by Trey Pendragon at 2023-07-12 23:24:54.referenced
by Trey Pendragon at 2023-07-12 23:26:18.head_ref_deleted
by Eliot Jordan at 2023-07-12 17:10:20.referenced
by Eliot Jordan at 2023-07-12 20:40:25.merged
by Eliot Jordan at 2023-07-12 20:40:25.closed
by Eliot Jordan at 2023-07-12 20:40:25.head_ref_deleted
by Eliot Jordan at 2023-07-12 20:40:28.


Nepal, the landlocked multiethnic, multilingual, multi-religious country, is situated north of India in the Himalayas, in the region where, about 40 to 50 million years ago, the Indian subcontinent has crashed into Asia. Because of that accident, Nepal has some of the world's highest mountains including Sagarmatha (Mt. Everest, 8848m, which it shares with Tibet (by now a province of China). The highest mountain on Earth is towering above populated valleys and forested plains.
Somewhere here in the Kapilavastu district, there is a place called Lumbini where in about 500 B.C.E. Queen Mayadevi is said to have given birth to Siddhartha Gautama, better known as Buddha.
Nepal can be divided broadly into three ecological zones: the lowland, the midland and the highland. The altitude of the Himalayan Region (the highland) ranges between 4877 m - 8848 m, It includes 8 of the highest 14 summits in the world, which exceed altitude of 8000 meters including Mount Everest
The mountain region accounts for about 64 percent of total land area, which is formed by the Mahabharat range that soars up to 4877 m and the lower Churia range.


|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object org.apache.poi.hssf.record.Record org.apache.poi.hssf.record.ColumnInfoRecord
public class ColumnInfoRecord
Title: ColumnInfo Record
Description: Defines with width and formatting for a range of columns
REFERENCE: PG 293 Microsoft Excel 97 Developer's Kit (ISBN: 1-57231-498-2)
| Field Summary | |
|---|---|
static short |
sid
|
| Constructor Summary | |
|---|---|
ColumnInfoRecord()
|
|
ColumnInfoRecord(RecordInputStream in)
Constructs a ColumnInfo record and sets its fields appropriately |
| Method Summary | |
|---|---|
java.lang.Object |
clone()
|
protected void |
fillFields(RecordInputStream in)
called by the constructor, should set class level fields. |
boolean |
getCollapsed()
get whether the cells are collapsed |
short |
getColumnWidth()
get the columns' width in 1/256 of a character width |
short |
getFirstColumn()
get the first column this record defines formatting info for |
boolean |
getHidden()
get whether or not these cells are hidden |
short |
getLastColumn()
get the last column this record defines formatting info for |
short |
getOptions()
get the options bitfield - use the bitsetters instead |
short |
getOutlineLevel()
get the outline level for the cells |
int |
getRecordSize()
gives the current serialized size of the record. |
short |
getSid()
return the non static version of the id for this record. |
short |
getXFIndex()
get the columns' default format info |
int |
serialize(int offset,
byte[] data)
called by the class that is responsible for writing this sucker. |
void |
setCollapsed(boolean iscollapsed)
set whether the cells are collapsed |
void |
setColumnWidth(short cw)
set the columns' width in 1/256 of a character width |
void |
setFirstColumn(short fc)
set the first column this record defines formatting info for |
void |
setHidden(boolean ishidden)
set whether or not these cells are hidden |
void |
setLastColumn(short lc)
set the last column this record defines formatting info for |
void |
setOptions(short options)
set the options bitfield - use the bitsetters instead |
void |
setOutlineLevel(short olevel)
set the outline level for the cells |
void |
setXFIndex(short xfi)
set the columns' default format info |
java.lang.String |
toString()
get a string representation of the record (for biffview/debugging) |
protected void |
validateSid(short id)
called by constructor, should throw runtime exception in the event of a record passed with a differing ID. |
| Methods inherited from class org.apache.poi.hssf.record.Record |
|---|
isInValueSection, isValue, serialize |
| Methods inherited from class java.lang.Object |
|---|
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Field Detail |
|---|
public static final short sid
| Constructor Detail |
|---|
public ColumnInfoRecord()
public ColumnInfoRecord(RecordInputStream in)
id
- id must be 0x7d or an exception will be throw upon validationsize
- the size of the data area of the recorddata
- data of the record (should not contain sid/len)| Method Detail |
|---|
protected void fillFields(RecordInputStream in)
Record
fillFields
in class Record
protected void validateSid(short id)
Record
validateSid
in class Record
id
- alleged id for this recordpublic void setFirstColumn(short fc)
fc
- - the first column index (0-based)public void setLastColumn(short lc)
lc
- - the last column index (0-based)public void setColumnWidth(short cw)
cw
- - column widthpublic void setXFIndex(short xfi)
xfi
- - the extended format indexExtendedFormatRecord
public void setOptions(short options)
options
- - the bitfield raw valuepublic void setHidden(boolean ishidden)
ishidden
- - whether the cells are hidden.setOptions(short)
public void setOutlineLevel(short olevel)
olevel
- -outline level for the cellssetOptions(short)
public void setCollapsed(boolean iscollapsed)
iscollapsed
- - wether the cells are collapsedsetOptions(short)
public short getFirstColumn()
public short getLastColumn()
public short getColumnWidth()
public short getXFIndex()
ExtendedFormatRecord
public short getOptions()
public boolean getHidden()
setOptions(short)
public short getOutlineLevel()
setOptions(short)
public boolean getCollapsed()
setOptions(short)
public short getSid()
Record
getSid
in class Record
public int serialize(int offset, byte[] data)
Record
serialize
in class Record
offset
- to begin writing atdata
- byte array containing instance data
public int getRecordSize()
Record
getRecordSize
in class Record
public java.lang.String toString()
Record
toString
in class Record
public java.lang.Object clone()
clone
in class Record
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


How much of your life has been in "The Internet Age"?
I was born in:
{{#each chart_details}} {{> chart}} {{/each}}
{{title}} : {{year}}


Pricing Table
Best Price Guarantee!
No Booking Fees
Hourly
You pay for every minute you drive
Full Insurance: No
Duration: 1 Hour
Mileage: 10 km
£189
Best Value
Full Day
The best package money can buy
Full Insurance: Yes
Duration: 24 Hours
Mileage: 10 Km
£449
Weekend
Enjoy an extraordinary weekend


Bring an idea that you have and the skills you are looking for. You'll be able to pitch your idea to everyone at the event kickoff around 12:30 on Saturday.
Teams tend to form organically around the pitched ideas. You can also go solo if you'd like. There is no limit to members on a team!
Hack away! All types of projects are encouraged.
After 24 hours of hard work, you'll present your projects to everyone. Judges will then select some winners to take home some awesome prizes.
Doors Open 11:00am
Intro and Kickoff 12:00 - 12:45pm
Idea Pitching 12:45 - 1:15pm
Form Teams, Begin Hacking 1:15pm
Lunch - Roso's (Sandwiches, Chips) 2:00pm
Provided by Troy Web Consulting and Rowe Digital
Dinner - Johnny's (Pizza, Wings, Salad) 7:00pm
Provided by Troy Web Consulting and Rowe Digital
Lots of Coffee Brewed 9:00pm
Breakfast Pizzas & Breakfast Sandwiches 9:00am
Provided by Troy Web Consulting and Rowe Digital
Stop hacking, Submit Projects 11:45am
Intro, Welcome judges 12:00 - 12:15pm
Demos 12:15 - 1:45 pm
Judge Deliberation 1:45 - 2:00 pm
Award Ceremony 2:00pm
Prizes Provided by CoveyCS
Is the project new and something that hasn't been attempted before? How does this approach a unique solution to a problem?
Subjective and buzz-wordy, huh?
Did your team successfully execute your project concept? Is it usable? Does it work? Is it well designed? Is the user experience smooth?
You'll have 2-3 minutes for a demo to tell the judges about your project, followed by a Q/A. We're interested in the problems you solved, API's you leveraged, technologies used, and lessons learned. We recommend a quick powerpoint.
We encourage and applaud interdisciplinary projects fueled by eclectic teams with diverse backgrounds.


| Interface | Description |
|---|---|
| CrossJoinArg |
"Light version" of a
TupleConstraint ,
represents one of
member.children, level.members, member.descendants, {enumeration}. |
| MemberChildrenConstraint |
Restricts the SQL result of a MembersChildren query in SqlMemberSource.
|
| SqlConstraint |
Restricts the members that are fetched by SqlMemberSource.
|
| SqlQueryChecker |
Runs a SQL query.
|
| TupleConstraint |
Restricts the SQL result of
TupleReader . |
| Class | Description |
|---|---|
| CrossJoinArgFactory |
Creates CrossJoinArgs for use in constraining SQL queries.
|
| DescendantsCrossJoinArg |
Represents one of:
Level.Members: member == null and level != null
Member.Children: member != null and level =
member.getLevel().getChildLevel()
Member.Descendants: member != null and level == some level below
member.getLevel()
|
| MemberKeyConstraint |
Restricts the SQL result set to members where particular columns have
particular values.
|
| MemberListCrossJoinArg |
Represents an enumeration {member1, member2, ...}.
|
| SqlQuery |
SqlQuery allows us to build a select
statement and generate it in database-specific SQL syntax. |
| SqlQuery.ClauseList | |
| SqlQuery.CodeSet |
Collection of alternative code for alternative dialects.
|
| SqlQuery.FromClauseList |


Messaging & Word Processing Integration
A proof of concept for applying logic to communication over text.
- Collaboratively draft and edit at close to messaging speed
- Develop paragraphs rationalistically by discussion and debate
- Co-edit without conflict: share the document's outline and settle with an unlimited number of co-authors
over entire paragraphs of ideas. Keep those you want, discard those you don't
- Draft a document without the need to view the document


 MonadFree f m => m a) -> Free f a |
|
| Produced by Haddock version 2.1.0 |


The WebDriver implementation.
Controls a browser by sending commands to a remote server. This server is expected to be running the WebDriver wire protocol as defined here: http://code.google.com/p/selenium/wiki/JsonWireProtocol
| Attributes : |
|
|---|
Create a new driver that will issue commands using the wire protocol.
| Args : |
|
|---|
Adds a cookie to your current session.
| Args : |
|
|---|
Returns the handle of the current window.
| Usage : | driver.current_window_handle |
|---|
Delete all cookies in the scope of the session.
| Usage : | driver.delete_all_cookies() |
|---|
Deletes a single cookie with the given name.
| Usage : | driver.delete_cookie(‘my_cookie’) |
|---|
Sends a command to be executed by a command.CommandExecutor.
| Args : |
|
|---|---|
| Returns : | The command’s JSON response loaded into a dictionary object. |
Asynchronously Executes JavaScript in the current window/frame.
| Args : |
|
|---|---|
| Usage : | driver.execute_async_script(‘document.title’) |
Synchronously Executes JavaScript in the current window/frame.
| Args : |
|
|---|---|
| Usage : | driver.execute_script(‘document.title’) |
‘Private’ method used by the find_element_by_* methods.
| Usage : | Use the corresponding find_element_by_* instead of this. |
|---|
Finds an element by class name.
| Args : |
|
|---|---|
| Usage : | driver.find_element_by_class_name(‘foo’) |
Finds an element by css selector.
| Args : |
|
|---|---|
| Usage : | driver.find_element_by_css_selector(‘#foo’) |
Finds an element by id.
| Args : |
|
|---|---|
| Usage : | driver.find_element_by_id(‘foo’) |
Finds an element by link text.
| Args : |
|
|---|---|
| Usage : | driver.find_element_by_link_text(‘Sign In’) |
Finds an element by name.
| Args : |
|
|---|---|
| Usage : | driver.find_element_by_name(‘foo’) |
Finds an element by a partial match of its link text.
| Args : |
|
|---|---|
| Usage : | driver.find_element_by_partial_link_text(‘Sign’) |
Finds an element by tag name.
| Args : |
|
|---|---|
| Usage : | driver.find_element_by_tag_name(‘foo’) |
Finds an element by xpath.
| Args : |
|
|---|---|
| Usage : | driver.find_element_by_xpath(‘//div/td[1]’) |
‘Private’ method used by the find_elements_by_* methods.
| Usage : | Use the corresponding find_elements_by_* instead of this. |
|---|
Finds elements by class name.
| Args : |
|
|---|---|
| Usage : | driver.find_elements_by_class_name(‘foo’) |
Finds elements by css selector.
| Args : |
|
|---|---|
| Usage : | driver.find_element_by_css_selector(‘#foo’) |
Finds multiple elements by id.
| Args : |
|
|---|---|
| Usage : | driver.find_element_by_id(‘foo’) |
Finds elements by link text.
| Args : |
|
|---|---|
| Usage : | driver.find_elements_by_link_text(‘Sign In’) |
Finds elements by name.
| Args : |
|
|---|---|
| Usage : | driver.find_elements_by_name(‘foo’) |
Finds elements by a partial match of their link text.
| Args : |
|
|---|---|
| Usage : | driver.find_element_by_partial_link_text(‘Sign’) |
Finds elements by tag name.
| Args : |
|
|---|---|
| Usage : | driver.find_elements_by_tag_name(‘foo’) |
Finds multiple elements by xpath.
| Args : |
|
|---|---|
| Usage : | driver.find_elements_by_xpath(“//div[contains(@class, ‘foo’)]”) |
Get a single cookie by name. Returns the cookie if found, None if not.
| Usage : | driver.get_cookie(‘my_cookie’) |
|---|
Returns a set of dictionaries, corresponding to cookies visible in the current session.
| Usage : | driver.get_cookies() |
|---|
Gets the log for a given log type
| Args : |
|
|---|---|
| Usage : | driver.get_log(‘browser’) driver.get_log(‘driver’) driver.get_log(‘client’) driver.get_log(‘server’) |
| Usage : | driver.get_screenshot_as_base64() |
|---|
| Args : |
|
|---|---|
| Usage : | driver.get_screenshot_as_file(‘/Screenshots/foo.png’) |
Gets the screenshot of the current window as a binary data.
| Usage : | driver.get_screenshot_as_png() |
|---|
Gets the x,y position of the current window.
| Usage : | driver.get_window_position() |
|---|
Gets the width and height of the current window.
| Usage : | driver.get_window_size() |
|---|
| Args : |
|
|---|---|
| Usage : | driver.implicitly_wait(30) |
Gets the current orientation of the device
| Usage : | orientation = driver.orientation |
|---|
| Args : |
|
|---|---|
| Usage : | driver.get_screenshot_as_file(‘/Screenshots/foo.png’) |
| Args : |
|
|---|---|
| Usage : | driver.set_page_load_timeout(30) |
| Args : |
|
|---|---|
| Usage : | driver.set_script_timeout(30) |
Sets the x,y position of the current window. (window.moveTo)
| Args : |
|
|---|---|
| Usage : | driver.set_window_position(0,0) |
Sets the width and height of the current window. (window.resizeTo)
| Args : |
|
|---|---|
| Usage : | driver.set_window_size(800,600) |
Called before starting a new session. This method may be overridden to define custom startup behavior.
Creates a new session with the desired capabilities.
| Args : |
|
|---|
Called after executing a quit command. This method may be overridden to define custom shutdown behavior.
Returns the element with focus, or BODY if nothing has focus.
| Usage : | driver.switch_to_active_element() |
|---|
Switch focus to the default frame.
| Usage : | driver.switch_to_default_content() |
|---|
Switches focus to the specified frame, by index, name, or webelement.
| Args : |
|
|---|---|
| Usage : | driver.switch_to_frame(‘frame_name’) driver.switch_to_frame(1) driver.switch_to_frame(driver.find_elements_by_tag_name(“iframe”)[0]) |


|
“Cellmodeller4”
|
Variables | |
| int | max_overlap = 5 |
| int | width = 5 |
| Value above which the cell stops growing till the pressure decreases. More... | |
| int | length = 15 |
| Half cell width. More... | |
| int | growth_speed = 30 |
| Initial cell length. More... | |
| Gt = length*growth_speed | |
| Iterations between elongation processes (time to resolve forces, define bigger for big simulations) More... | |
| int | real_Gt = 100 |
| tuple | minute = float(Gt) |
| Real generation time in Minutes. More... | |
| float | p_d = 0.001 |
| Iterations per minute. More... | |
| float | p_t1 = 0.02 |
| Probability of conjugation event in donors. More... | |
| float | p_t2 = 0.05 |
| Probability of conjugation event in transconjugant (converted from donor) More... | |
| int | c_time = 10 |
| Probability of conjugation event in transconjugant (converted from trans) More... | |
| int | network_steps = 18 |
| Conjugation time in iterations. More... | |
| tuple | i_time = float(network_steps) |
| Number of steps of the ODEs per Gt. More... | |
| int | number_recipients = 20 |
| Number of integration steps in each call to the program. More... | |
| int | number_donors = 20 |
| Initial number of recipients. More... | |
| int | spring_bias_coeficient = 10 |
| Initial number of donors. More... | |
| int | spring_rest_length = 10 |
| Spring bias coeficient. More... | |
| int | spring_stiffness = 10 |
| Spring rest length. More... | |
| int | spring_damping = 100 |
| Spring stiffness. More... | |
| float | cell_infancy = 0.20 |
| Spring damping. More... | |
| int | pymunk_steps = 1 |
| (Percentage) Time in which the cell is too young to conjugate More... | |
| float | pymunk_clock_ticks = 1500.0 |
| Pymunk steps. More... | |
| int | bac_mass = 10 |
| Pymunk clock ticks. More... | |
| int | bac_friction = 10 |
| Cell's mass. More... | |
| int Imports.parameters.bac_friction = 10 |
Cell's mass.
Definition at line 49 of file parameters.py.
| int Imports.parameters.bac_mass = 10 |
Pymunk clock ticks.
Definition at line 48 of file parameters.py.
| int Imports.parameters.c_time = 10 |
Probability of conjugation event in transconjugant (converted from trans)
Definition at line 36 of file parameters.py.
| float Imports.parameters.cell_infancy = 0.20 |
Spring damping.
Definition at line 45 of file parameters.py.
| int Imports.parameters.growth_speed = 30 |
Initial cell length.
Definition at line 29 of file parameters.py.
| Imports.parameters.Gt = length*growth_speed |
Iterations between elongation processes (time to resolve forces, define bigger for big simulations)
Definition at line 30 of file parameters.py.
| tuple Imports.parameters.i_time = float(network_steps) |
Number of steps of the ODEs per Gt.
Definition at line 38 of file parameters.py.
| int Imports.parameters.length = 15 |
Half cell width.
Definition at line 28 of file parameters.py.
| int Imports.parameters.max_overlap = 5 |
Definition at line 26 of file parameters.py.
| tuple Imports.parameters.minute = float(Gt) |
Real generation time in Minutes.
Definition at line 32 of file parameters.py.
| int Imports.parameters.network_steps = 18 |
Conjugation time in iterations.
Definition at line 37 of file parameters.py.
| int Imports.parameters.number_donors = 20 |
Initial number of recipients.
Definition at line 40 of file parameters.py.
| int Imports.parameters.number_recipients = 20 |
Number of integration steps in each call to the program.
Definition at line 39 of file parameters.py.
| float Imports.parameters.p_d = 0.001 |
Iterations per minute.
Definition at line 33 of file parameters.py.
| float Imports.parameters.p_t1 = 0.02 |
Probability of conjugation event in donors.
Definition at line 34 of file parameters.py.
| float Imports.parameters.p_t2 = 0.05 |
Probability of conjugation event in transconjugant (converted from donor)
Definition at line 35 of file parameters.py.
| float Imports.parameters.pymunk_clock_ticks = 1500.0 |
Pymunk steps.
Definition at line 47 of file parameters.py.
| int Imports.parameters.pymunk_steps = 1 |
(Percentage) Time in which the cell is too young to conjugate
Definition at line 46 of file parameters.py.
| int Imports.parameters.real_Gt = 100 |
Definition at line 31 of file parameters.py.
| int Imports.parameters.spring_bias_coeficient = 10 |
Initial number of donors.
Definition at line 41 of file parameters.py.
| int Imports.parameters.spring_damping = 100 |
Spring stiffness.
Definition at line 44 of file parameters.py.
| int Imports.parameters.spring_rest_length = 10 |
Spring bias coeficient.
Definition at line 42 of file parameters.py.
| int Imports.parameters.spring_stiffness = 10 |
Spring rest length.
Definition at line 43 of file parameters.py.
| int Imports.parameters.width = 5 |
Value above which the cell stops growing till the pressure decreases.
Definition at line 27 of file parameters.py.


model_structure.Rmd
To structure and dimensions of SPAMc are defined by the combination of predefined number of crops and farming systems, and several parameters that are set by the user. Changing these parameters
The number of crops and farming systems are similar to those used by SPAM
SPAMc models 40 different crop (and crop groups) that together cover the full agricultural sector and are each identified by a four letter code (Table 1).1 The main reason for this classification is the limited availability of crop-specific biophysical suitability maps, which form a key element in the crop allocation process (see spatial data for more information). It would be relatively easy to add new crops by splitting them off from broader crop groups (e.g. tropical and temperate fruits, and vegetables) if appropriate agricultural statistics and suitability maps would be available. We plan to add an example on how to do this in future updates. The actual number of crops in the model is determined by the number of crops that are actually grown in the target country and identified by the availability of national statistics.
# Add 40 crop table
Year. Relevant to select matching spatial information that is available for multiple years, in particular cropland exent, population and travel time (see spatial data.
Solve = 0 and solve = 1
Wood-Sichra, Ulrike, Alison B. Joglekar, and Liangzhi You. 2016. “Spatial Producion Allocation Model (SPAM) 2005: Technical Documentation.” Harvest Choice Working Paper. Washington, D.C.: International Food Policy Research (IFPRI).
Global SPAM uses 42 different crops because it includes two types of millet and two types of coffee (Wood-Sichra, Joglekar, and You 2016). As this level of detail is not supported by most national statistics and FAOSTAT, the have been merged into millet and coffee, respectively.↩


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Munich 'no longer most expensive city for renting' in Germany
by The LocalMunich is no longer the most expensive city for renting in Germany, a new study has revealed.
According to Research and Consulting Company for Housing, Real Estate and the Environment (F+B), the Bavarian capital has been overtaken by Stuttgart.
Tenants have to pay significantly more to rent an apartment in the Baden-Württemberg city, where the average net cold rent (before extra costs such as for heating and insurance) is now €10.41 per square metre.
This makes Stuttgart the most expensive city for tenants in Germany for the first time since F+B started compiling their research in 1996, pushing Munich into second place.
SEE ALSO: The ultimate guide to living in Munich on a budget
Overall, the study found rents in Germany are continuing to rise, although not as strongly as in previous years.
In 2019, rents climbed by 1.8 percent, 0.4 percentage points less than in 2018.
Tenants in Germany have to pay on average €7.04 per square metre. According to the study, local comparative rents are most reasonable in the likes of Erfurt, eastern Berlin, Potsdam, Dresden and Schwerin.
"Stuttgart residents pay an average of €10.41 per square metre of net rent for their apartments, 48 percent above the €7.04 per square metre paid on average in cities," said F+B managing director Dr. Bernd Leutner.
Munich is ranked sixth and tenants pay an average of €9.74 per square metre for net cold rent, according to the study.
Berlin becomes more expensive – but not for everyone
Prices in Hamburg, Düsseldorf, Frankfurt am Main and Cologne are also far above the overall average – in Berlin, on the other hand, they are only slightly above the average at €7.32 per square metre.
According to F+B, tenants with old leases in Berlin have a much better deal compared to newcomers.
Although existing rents in old and new flats have recently risen at an above-average rate, long-term tenants can still live relatively cheaply in the capital.
SEE ALSO: The complete guide to how you can (still) live cheaply in Berlin
Suburbs becoming more expensive than cities
The most expensive municipality for tenants is Karlsfeld in the district of Dachau in the neighbourhood of Munich, F+B reported. The average net cold rent here reaches €10.86 per square metre. The cities of Germering and Dachau, where there are also very high rent costs, are also in Bavaria.
Flats in Munich. Photo: DPA
"This shows that the old rule that anyone who wants to live more cheaply must move to the surrounding area no longer applies in the same way," F+B explained.
The high cost of renting an apartment in German cities has led to more demand for homes in the surrounding area and suburbs, which in turn pushes up prices there.
Overall, the top 10 most expensive cities for tenants are located in southern Germany, the most prosperous part of the country.
READ ALSO: High costs, long queues and discrimination: What it's like to rent in Germany
The top 20 most expensive cities and municipalities
Karlsfeld (Bavaria, most expensive municipality)
Stuttgart (Baden-Württemberg), most expensive city)
Leinfelden-Echterdingen (Baden-Württemberg)
Germering (Bavaria)
Dachau (Bavaria)
Munich (Bavaria)
Tübingen (Baden-Württemberg)
Ludwigsburg (Baden-Württemberg)
Erding (Bavaria)
Ditzingen (Baden-Württemberg)
Darmstadt (Hesse)
Kornwestheim (Baden-Württemberg)
Hamburg
Esslingen am Neckar (Baden-Württemberg)
Wiesbaden (Hesse)
Leonberg (Baden-Württemberg)
Fellbach (Baden-Württemberg)
Konstanz (Baden-Württemberg)
Düsseldorf (North-Rhine Westphalia)
Frankfurt am Main (Hesse)
The first eastern German city in the ranking is Jena, which comes in at 90th place, where rents are roughly at the national average level.
F+B annually compares rent overviews and the development of the housing costs to find out what Germany's tenants have to pay on average.
The company examines the net cold rents of typical 65 square metre flats in municipalities and cities with at least 20,000 people to produce a rent index. In 2019 there were 351 cities in the index.


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