Click here to go to the corresponding page for the latest version of DIALS
Processing in Detail with DUI¶
Introduction¶
This tutorial follows the same steps as the command line tutorial Processing in Detail, but here processing will be driven graphically through the DIALS User Interface, DUI.
DUI is part of CCP4 and can be launched from ccp4i2 by selecting the relevant icon from within the “Integrate X-ray images” task folder.
Tutorial data¶
The following example uses a Beta-Lactamase dataset collected using beamline I04 at Diamond Light Source, and reprocessed especially for these tutorials.
Hint
If you are physically at Diamond on the CCP4 Workshop, then
this data is already available in your training data area. After
typing module load ccp4-workshop
you’ll be moved to a working
folder, with the data already located in the tutorial-data/summed
subdirectory.
The data is otherwise available for download from .
We’ll only be using the first run of data in this tutorial,
C2sum_1.tar
, extracted to a tutorial-data/summed
subdirectory.
Import¶
When DUI starts up you will initially be presented by a window like the following.
At this stage you can resize various parts of the interface until you are comfortable with the layout, but you can’t do much else until the dataset is imported by DIALS. To do this, click on the “Select File(s)” button, navigate to the location of the images and select any one of them. DUI will automatically determine the filename template and will show that with a wildcard in the text box. If there are problems with this template it is possible to edit this before importing the images. Otherwise, just click the “Run” button to proceed.
What happens then is that that the metadata are read for all the images in the dataset. If these are consistent, then the dataset is imported and initial models for the “Beam”, “Scan” and “Detector” are created. The images are now also displayed within the “Image” tab. You can adjust the contrast and colour scheme by controls under the “Display” pull-down.
Find Spots¶
The first “real” task in any processing using DIALS is the spot finding. To run this job, click on the “find” button at the upper-left of the window. When you do this you will see a new node will be created in the “History Tree”. This node is currently green, which indicates that it has not been run yet. By contrast, the import step is blue, which means this has been run. In general, it is always possible to navigate between each step of processing by clicking on the relevant position in the history. Advanced users will find this gives a great deal of control, allowing them to keep track of complex history, including parallel branches.
Spot-finding, like most of the other processing steps in DUI, presents user parameters at two levels of detail. The “Simple” tab contains the basic parameters that are the most commonly changed. The “Advanced” tab contains all of those again, plus other parameters that may be required for expert use with challenging data sets. In many cases, however, the default settings are fine.
Note that spot-finding is done on every image in the dataset. This means the job can take some time, but by default it will be run in parallel using multiple processors. To proceed, press the “Run” button below the input parameters.
Once the job is finished, the image viewer will display small blue boxes around the pixels that have been marked as strong. It is also useful to click on the “Report View” tab and scroll down to the “Analysis of strong reflections”. This shows a graph of the number of strong spots found per image. In this case there is a pretty steady rate of around 150 spots found on each image. If instead we had seen the number of strong spots drop off over the dataset, or otherwise show large variability we would start to worry about issues such as radiation damage or a poorly-centred crystal.
The cyan button at the bottom left of the graph opens a help window with a description of how the appearance of this plot may be affected by various data collection issues. In the “Log Text” window you can see the text output from the dials.find_spots program, which also includes an ASCII-art version of this plot.
The default parameters for spot finding usually do a good job for Pilatus images, such as these. However they may not be optimal for data from other detector types, such as CCDs or image plates. If you have a case where spot-finding has gone badly, it may be helpful to debug using the dials.image_viewer and dials.reciprocal_lattice_viewer, which can be launched via buttons shown on the “Tools” tab.
In particular, the effect of changing the spot-finding parameters can be explored interactively with the dials.image_viewer. The image mode buttons at the bottom of the “Settings” window allow a preview of how the parameters affect the spot finding algorithm. The final image, (“threshold”) is the one on which spots were found, so ensuring this produces peaks at real diffraction spot positions will give the best chance of success.
The second external viewer, the dials.reciprocal_lattice_viewer, displays the strong spots in 3D, after mapping them from their detector positions to reciprocal space. In a favourable case you should be able to see the crystal’s reciprocal lattice by eye in the strong spot positions. Some practice may be needed in rotating the lattice to an orientation that shows off the periodicity in reciprocal lattice positions.
Although the reciprocal spacing is visible, in this data, there are clearly some systematic distortions. These will be solved during indexing.
Indexing¶
The next step will be indexing of the strong spots. Click on the “Index” button
to move on to this step, and form a new node in the history tree. Here we see
that the simple parameters allow only to select between different “Indexing
Methods”, the default of which is the 3D FFT algorithm. The other options are
the 1D FFT (DPS) algorithm and a special version of the 3D FFT called
real_space_grid_search
, which is particularly useful for narrow wedges
containing multiple lattices, but requires a known cell and space group to be
set under the “Advanced” parameters. If we do know the cell and space group,
these can also be set as hints for either of the other two indexing algorithms.
This can help in difficult cases and will be used to constrain the lattice
during refinement. Otherwise
indexing and refinement will be carried out in the primitive lattice
using space group P1.
In this case, keep the method set to the default fft3d
and click “Run” to
start the indexing job. Once the job has finished running, you can see in the
“Experiment” tab that the experimental models have now been completed with a
“Crystal” model.
Now let’s click through the all the tabs of output. First, on the “Image” tab you will now see that indexed strong spots are assigned Miller indices. If you also click on the “Predictions” checkbox, under “Reflection Type” you will in addition see centroid positions and Miller indices for all predicted reflections, not just the strong spots.
Moving to the “Log Text” tab, it is worth reading through the output to understand what the indexing program has done. Inspecting the beginning of the log shows that the indexing step is done at a resolution lower than the full dataset; 1.84 Å:
Found max_cell: 94.4 Angstrom
Setting d_min: 1.84
FFT gridding: (256,256,256)
The resolution limit of data that can be used in indexing is determined by the size of the 3D FFT grid, and the likely maximum cell dimension. Here we used the default 256³ grid points. These are used to make an initial estimate for the unit cell parameters.
What then follows are ‘macro-cycles’ of refinement where the experimental model is first tuned to get the best possible fit from the data, and then the resolution limit is reduced to cover more data than the previous cycle. 16 parameters of the diffraction geometry are tuned: 6 for the detector, one for beam angle, 3 crystal orientation angles and the 6 triclinic cell parameters. At each stage only 36000 reflections are used in the refinement job. In order to save time, a subset of the input reflections are used - by default using 100 reflections for every degree of the 360° scan.
We see that the first macrocycle of refinement makes a big improvement in the positional RMSDs:
+--------+--------+----------+----------+------------+
| Step | Nref | RMSD_X | RMSD_Y | RMSD_Phi |
| | | (mm) | (mm) | (deg) |
|--------+--------+----------+----------+------------|
| 0 | 36000 | 0.56197 | 0.55131 | 0.13413 |
| 1 | 36000 | 0.24338 | 0.26503 | 0.15575 |
| 2 | 36000 | 0.10648 | 0.13198 | 0.13476 |
| 3 | 36000 | 0.055785 | 0.059567 | 0.10888 |
| 4 | 36000 | 0.051066 | 0.052336 | 0.10514 |
| 5 | 36000 | 0.050906 | 0.052372 | 0.10505 |
| 6 | 36000 | 0.050901 | 0.052378 | 0.10505 |
+--------+--------+----------+----------+------------+
Second and subsequent macrocycles are refined using the same number of reflections, but after extending to higher resolution. The RMSDs at the start of each cycle start off worse than at the end of the previous cycle, because the best fit model for lower resolution data is being applied to higher resolution reflections. As long as each macrocyle shows a reduction in RMSDs then refinement is doing its job of extending the applicability of the model out to a new resolution limit, until eventually the highest resolution strong spots have been included. The final macrocycle includes data out to 1.30 Å and produces a final model with RMSDs of 0.050 mm in X, 0.049 mm in Y and 0.104° in φ, corresponding to 0.29 pixels in X, 0.28 pixels in Y and 0.21 image widths in φ.
Despite the high quality of this data, we notice from the log that at each macrocycle there were some outliers identified and removed from refinement as resolution increases. Large outliers can dominate refinement using a least squares target, so it is important to be able to remove these. More about this is discussed below in Refinement. It’s also worth checking the total number of reflections that were unable to be assigned an index:
+------------+-------------+---------------+-------------+
| Imageset | # indexed | # unindexed | % indexed |
|------------+-------------+---------------+-------------|
| 0 | 107264 | 733 | 99.3% |
+------------+-------------+---------------+-------------+
because this can be an indication of poor data quality or a sign that more care needs to be taken in selecting the indexing parameters.
Now the “Report View” contains more information than just after spot-finding. The “Spot count per image” plot also contains information about the number of indexed spots. In addition there are heat maps giving information about the positions of indexed and unindexed spots. Here we see that most of the unindexed spots are found in the region around the rotation axis. The “Analysis of reflection centroids” plots provide lots of detail regarding how well the predicted spot positions match the observed positions, both in image space and as a function of the position within the rotation scan.
After indexing it can be useful to inspect the reciprocal lattice again under the “External Tools”. Now indexed/unindexed spots are differentiated by colour, and it is possible to see which spots were marked by dials.refine as outliers. If you have a dataset with multiple lattices present, it may be possible to spot them in the unindexed reflections.
In this case, we can see that the refinement has clearly resolved whatever systematic error was causing distortions in the reciprocal space view, and the determined reciprocal unit cell fits the data well:
Bravais Lattice Refinement¶
Since we didn’t know the Bravais lattice before indexing, we can now determine likely candidates - by taking the results of the P1 autoindexing, and running refinement with all of the possible Bravais settings applied. You can then choose your preferred solution. This step is accessed by the “Lattice” button on the left of the DUI window. As before, run this without altering any of the defaults, as they are suitable for the majority of data sets.
Once the job has run, a window will pop up containing scoring data and the unit cell for each Bravais setting.
The scores for each setting include max δ (a metric fit measured in degrees), RMSDs (in mm), and the best and worse correlation coefficients for data related by symmetry elements (the symmetry elements implied by the lowest symmetry space group from the Bravais setting). This uses the raw spot intensity measurement from the spot-finding procedure (uncorrected and unscaled) but provides a very useful check to see if the data does appear to adhere to the proposed symmetry operators.
DIALS uses an heuristic to determine which solutions are acceptable or not, indicated on this window by either a green highlighted “Y” or a red highlighted “N”. In addition, the single “best” solution (the highest symmetry of the acceptable results) is pre-selected (highlighted in blue). To pick this solution, simply click “OK” while the chosen solution is highlighted. This will automatically apply the symmetry constraints and will reindex the reflections ready for further refinement.
Refinement¶
The model is already refined during indexing, but we can also add explicit refinement steps here. This is beneficial because it will use all reflections in refinement rather than a subset, uses a more sophisticated outlier rejection algorithm and will later allow us to fit a scan-varying model of the crystal.
We start by refining a static model including the monoclinic constraints from our chosen reindexed solution. For this we leave “Scan Varying Refinement” as “False”. There are various choices of outlier rejection algorithm allowed by refinement. The default selection of “auto” will choose the “mcd” algorithm for a rotation scan like this, which performs outlier rejection on the X, Y and φ residuals simultaneously, taking into account the multivariate nature of the data. This is appropriate for the ‘polishing up’ stage of refinement, whereas before during indexing the rougher, but less computationally expensive “tukey” option was used instead.
As before, click “Run” to start the job. The “Log Text” is familiar from the indexing stage. We see that all strong reflections were used in refinement, providing a small reduction in RMSDs. However, the refined model is still static over the whole dataset. We would like to do an additional refinement job at this point, to fit a more sophisticated model for the crystal, allowing small misset rotations to occur over the course of the scan. There are usually even small changes to the cell dimensions (typically resulting in a net increase in cell volume) caused by exposure to radiation during data collection. To account for both of these effects we can extend our parameterisation to obtain a smoothed scan-varying model for both the crystal orientation and unit cell.
This means running a further refinement job starting from the output of the previous job. To do that, note that the current “refine” node is a completed job and the parameters we entered are now greyed-out and cannot be edited. To do a second refinement starting from this point we simply click on the “refine” button again, opening a new green node in the history tree. Here we can select “Scan Varying Refinement” as “True” and click “Run” again to start the job.
The log output shows a decrease in each dimension, but especially in Y.
+--------+--------+----------+----------+------------+
| Step | Nref | RMSD_X | RMSD_Y | RMSD_Phi |
| | | (mm) | (mm) | (deg) |
|--------+--------+----------+----------+------------|
| 0 | 95415 | 0.045994 | 0.047882 | 0.1047 |
| 1 | 95415 | 0.043137 | 0.040683 | 0.10342 |
| 2 | 95415 | 0.041146 | 0.039717 | 0.1028 |
| 3 | 95415 | 0.040602 | 0.039511 | 0.10247 |
| 4 | 95415 | 0.040487 | 0.039501 | 0.10226 |
| 5 | 95415 | 0.040464 | 0.039497 | 0.10216 |
| 6 | 95415 | 0.040459 | 0.039496 | 0.10214 |
| 7 | 95415 | 0.040458 | 0.039497 | 0.10214 |
+--------+--------+----------+----------+------------+
The final RMSDs are less than a quarter of a pixel in both X and Y, and just under a fifth of a pixel in φ. This is about as good as we can expect from a high quality Pilatus data set such as this.
In the “Report View” we can now see plots of how the cell and orientation changes during the scan. The smoothness of these plots is guaranteed by the smoother model used by dials.refine. However, we are satisfied that this model is sufficient to match real changes present in the dataset because of the very low overall RMSDs.
Other useful plots in the report are:
- Difference between observed and calculated centroids vs phi, which shows how the average residuals in each of X, Y, and φ vary as a fuction of φ. If scan-varying refinement has been successful in capturing the real changes during the scan then we would expect these plots to be straight lines.
- Centroid residuals in X and Y, in which the X, Y residuals are shown directly. The key point here is to look for a globular shape centred at the origin.
- Difference between observed and calculated centroids in X and Y, which show the difference between predicted and observed reflection positions in either X or Y as functions of detector position. From these plots it is very easy to see whole tiles that are worse than their neighbours, and whether those tiles might be simply shifted or slightly rotated compared to the model detector.
In this tutorial, we see no overall increase in all three cell parameters. If significant cell volume increases had been observed that might be indicative of radiation damage. However we can’t yet conclude that there is no radiation damage from the lack of considerable change observed.
Integration¶
After the refinement is done the next step is integration. Click on the “integrate” button to move to this job. Mostly, the default parameters are fine for Pilatus data, which will perform XDS-like 3D profile fitting while using a generalized linear model in order to fit a Poisson-distributed background model. As with spot-finding, the number of processes can be set >1 to speed the job up (but DUI will have selected a suitable default). Click “Run” to start integration. This is the most computationally-demanding stage of processing, so it will take a while to complete.
Checking the “Log Text” output, we see that after loading in the reference
reflections, new predictions are made up to the highest resolution at the
corner of the detector. This is fine, but if we wanted to we could have
adjusted the resolution limits using parameters d_min
and d_max
under prediction
in the “Advanced” parameters tab. The predictions are
made using the scan-varying crystal model from the previous step. As this
scan-varying model was determined in advance of integration, each of the
integration jobs is independent and we can take advantage of true parallelism
during processing.
The profile model is then calculated from the reflections file resulting from refinement. First reflections with a too small ‘zeta’ factor are filtered out. This essentially removes reflections that are too close to the spindle axis. In general these reflections require significant Lorentz corrections and as a result have less trustworthy intensities anyway. From the remaining reflection shoeboxes, the average beam divergence and reflecting range is calculated, providing the two Gaussian width parameters \(\sigma_D\) and \(\sigma_M\) used in the 3D profile model.
Following this, independent integration jobs are set up. These jobs overlap, so reflections are assigned to one or more jobs. What follows are blocks of information specific to each integration job.
After these jobs are finished, the reflections are ‘post-processed’, which includes the application of the LP correction to the intensities. Then summary tables are printed giving quality statistics first by frame, and then by resolution bin.
On the “Image View” tab we can now see integration “shoeboxes” around the spots, not just tight boxes around the strong pixels. If all stages up to this point have gone well, then the boxes should be centred on the strong pixels and should extend beyond the strong pixels to include pixels used for local background level determination.
The “Report View” now contains additional plots under the “Analysis of reflection intensities” and “Analysis of reference profiles” sections. It is worth checking through these, particularly paying attention to the following:
- Reflection and reference correlations binned in X/Y. These are useful companions to the plots of centroid residual as a function of detector position above. Whereas the above plots show systematic errors in the positions and orientations of tiles of a multi-panel detector, these plots indicate what effect that (and any other position-specific systematic error) has on the integrated data quality. The first of these plots shows the correlation between reflections and their reference profiles for all reflections in the dataset. The second shows only the correlations between the strong reference reflections and their profiles (thus these are expected to be higher and do not extend to such high resolution).
- Distribution of I/Sigma vs Z. This reproduces the \(\frac{I}{\sigma_I}\) information versus frame number given in the log file in a graphical form. Here we see that \(\frac{I}{\sigma_I}\) is fairly flat over the whole dataset, which we might use as an indication that there were no bad frames, not much radiation damage occurred and that scale factors are likely to be fairly uniform.
At this point we could export the integrated data set in MTZ format, however we will continue with this tutorial to demonstrate scaling within DIALS.
Checking the symmetry¶
After integration we can return to our hypothesis of the space group of the crystal. Although we made an assessment of that when we chose a Bravais lattice after indexing, we now have better, background-subtracted, values for the intensities, and for all reflections, not just the strong spots. So, it is prudent to repeat the assessment to see if there is any indication that our initial assessment should be revised.
This job is run using the “symmetry” button. We will again run with default settings only. Once the job is finished, check the “Log Text” output. The most important part here is the table printed at the end:
Scoring all possible sub-groups
---------------------------------------------------------------------------------------------
Patterson group Likelihood NetZcc Zcc+ Zcc- CC CC- delta Reindex operator
---------------------------------------------------------------------------------------------
C 1 2/m 1 *** 0.909 9.72 9.72 0.00 0.97 0.00 0.0 -a,b,-c
P -1 0.091 0.11 9.77 9.66 0.98 0.97 0.0 -x-y,-x+y,-z
---------------------------------------------------------------------------------------------
Best solution: C 1 2/m 1
Here we see clearly that the best solution is given by C 1 2/m 1
, with
a high likelihood, in agreement with the result from
dials.refine_bravais_settings
. As we remain confident with this choice,
we now continue to scaling.
Scaling¶
Before the data can be reduced for structure solution, the intensity values must be corrected for experimental effects which occur prior to the reflection being measured on the detector. These primarily include sample illumination/absorption effects and radiation damage, which result in symmetry-equivalent reflections having unequal measured intensities (i.e. a systematic effect in addition to any variance due to counting statistics). Thus the purpose of scaling is to determine a scale factor to apply to each reflection, such that the scaled intensities are representative of the ‘true’ scattering intensity from the contents of the unit cell.
During scaling, a scaling model is created, from which we derive scale factors for
each reflection. By default, three components are used to create a physical model
for scaling (model=physical
), in a similar manner to that used in the
program aimless. This model consists of a smoothly varying scale factor as a
function of rotation angle, a smoothly varying B-factor to
account for radiation damage as a function of rotation angle
and an absorption surface correction, dependent on the direction of the incoming
and scattered beam vector relative to the crystal.
Let’s scale the Beta-lactamase dataset, after setting a resolution cutoff (d_min) of 1.4. This job is created by clicking the “scale” button. Enter 1.4 in the d_min field in the “simple” tab and click “Run” to start the job.
As can be seen from the “Log Text”, 70 parameters are used to parameterise the scaling model for this dataset. A subset of reflections are selected to be used in scaling model minimisation, which helps to speed up the algorithm (the model is used to calculate scales for all reflections at the end). Outlier rejection is performed at several stages, as outliers have a disproportionately large effect during scaling and can lead to poor scaling results. During scaling, the distribution of the intensity uncertainties are also analysed and an error model is optimised to transform the intensity errors to an expected normal distribution. An error estimate for each scale factor is also determined based on the covariances of the model parameters. At the end of the output, a table and summary of the merging statistics are presented, which give indications of the quality of the scaled dataset.
----------Overall merging statistics (non-anomalous)----------
Resolution: 69.19 - 1.40
Observations: 274799
Unique reflections: 41140
Redundancy: 6.7
Completeness: 94.11%
Mean intensity: 80.7
Mean I/sigma(I): 15.4
R-merge: 0.065
R-meas: 0.071
R-pim: 0.027
Inspecting the results¶
To see what the scaling is telling us about the dataset, plots of the scaling model should be viewed. These are visible within the “Report View” tab, at the bottom under “Analysis of scaling model”.
What is immediately apparent is the periodic nature of the scale term, with peaks
and troughs 90° apart. This indicates that the illuminated volume was changing
significantly during the experiment: a reflection would be measured as twice as
intense if it was measured at rotation angle of ~120° compared to at ~210°.
The absorption surface also shows a similar periodicity, as may be expected.
What is less clear is the form of the relative B-factor, which also has a
periodic nature. As a B-factor can be understood to represent radiation damage,
this would not be expected to be periodic, and it is likely that this model
component is accounting for variation that could be described only by a scale
and absorption term. To test this, we can repeat the scaling process but turn
off the decay_term
.
To do this in DUI, click “Retry” to set up a new scaling job continuing from the successful symmetry-determination step. This time, enter the “Advanced” tab and under parameterisation change the value of decay_term to False. Now click “Run” to start the job.
----------Overall merging statistics (non-anomalous)----------
Resolution: 69.19 - 1.40
Observations: 274578
Unique reflections: 41140
Redundancy: 6.7
Completeness: 94.11%
Mean intensity: 76.6
Mean I/sigma(I): 16.0
R-merge: 0.064
R-meas: 0.070
R-pim: 0.027
By inspecting the statistics in the output, we can see that removing the decay
term has had the effect of causing around 200 more reflections to be marked as
outliers (taking the outlier count from 0.72% to 0.80% of the data), while
improving some of the R-factors and mean I/sigma(I). Therefore it is probably
best to exclude the decay correction for this dataset. Other options which
could be explored under the “Advanced” tab are the numbers of parameters used
for the various components, for example by changing the scale_interval
,
or by adjusting the outlier rejection criterion with a different
outlier_zmax
.
Exporting as MTZ¶
Once we are happy with the results from scaling, the data can be exported as an unmerged mtz file, for further symmetry analysis with pointless or to start structural solution.
To do this, click on the “export” button. This gives the option of an mtz output name and the option to output scaled intensities. Make sure that box is ticked otherwise the exported MTZ will only contain intensities from integration.


main.s
LICENSE
res.txt
Makefile
main.cpp
test.asm
test.bin
README.md
bench.asm
bench.txt
opcodes.s
rules.hpp
assembler.s
opcodes.cpp
opcodes.hpp
assembler.cbp
assembler.cpp
assembler.hpp
rules.hpp.gch
CMakeCache.txt
CMakeLists.txt
disassembler.s
opcodes.hpp.gch
disassembler.cpp
disassembler.hpp
assembler.hpp.gch
cmake_install.cmake
disassembler.hpp.gch


Flood sensor suspected stolen from Pune bridge
The incident came to light when Amol Bhalerao, 26, a technician involved in installing the machine that costs Rs 87,900, lodged a complaint with Khadki police on Wednesday
Pune: A miscreant seems to have stolen a flood sensor installed on the Mula river. Flood sensors were installed at 100 locations in the city to observe and monitor water levels as part of the Smart City initiative of the Pune Municipal Corporation (PMC).
The incident came to light when Amol Bhalerao, 26, a technician involved in installing the machine that costs Rs 87,900, lodged a complaint with Khadki police on Wednesday. The incident is believed to have taken place between November 5 and November 7.
Senior Inspector Bhagwat Misal of the Khadki police station said, "The complainant is a technician who works with the reputed company that had installed the flood sensors in 2017, in around 100 sensitive areas and on bridges. These machines provide information about water levels due to the rain and release from dams. The system provides information every 15 minutes."
Assistant Police Inspector Harish Thakur of Khadki police station, who is investigating the case said, "The machine was installed on Vishrantwadi bridge. The complainant claims that the incident took place between November 5 and 7, as he found they were not receiving data from the machine then. Technicians went to the spot and found it missing. We suspect that a drug peddler or thief robbed it. We are probing the case."
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Module: ActiveSupport::ActionableError
| Relationships & Source Files | |
| Namespace Children | |
|
Modules:
| |
|
Exceptions:
| |
| Extension / Inclusion / Inheritance Descendants | |
|
Included In:
| |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Class Chain:
self,
Concern
|
|
| Defined in: | activesupport/lib/active_support/actionable_error.rb |
Overview
Actionable Errors
Actionable errors lets you define actions to resolve an error.
To make an error actionable, include the ActionableError
module and invoke the action
class macro to define the action. An action needs a name and a block to execute.
Class Method Summary
- .actions(error) Internal use only
- .dispatch(error, name) Internal use only
Concern
- Extended
| class_methods | Define class methods from given block. |
| included | Evaluate given block in context of base class, so that you can write class macros here. |
| prepended | Evaluate given block in context of base class, so that you can write class macros here. |
| append_features, prepend_features |
DSL Calls
included
[ GitHub ]16 17 18
# File 'activesupport/lib/active_support/actionable_error.rb', line 16
included do class_attribute :_actions, default: {} end
Class Method Details
.actions(error)
This method is for internal use only.
[ GitHub ]
# File 'activesupport/lib/active_support/actionable_error.rb', line 20
def self.actions(error) # :nodoc: case error when ActionableError, -> it { Class === it && it < ActionableError } error._actions else {} end end
.dispatch(error, name)
This method is for internal use only.
[ GitHub ]
# File 'activesupport/lib/active_support/actionable_error.rb', line 29
def self.dispatch(error, name) # :nodoc: actions(error).fetch(name).call rescue KeyError raise NonActionable, "Cannot find action \"#{name}\"" end


Developer overview¶
If you are a first-time contributor:
Go to https://github.com/networkx/networkx and click the “fork” button to create your own copy of the project.
Clone the project to your local computer:
git clone git@github.com:your-username/networkx.git
Add the upstream repository:
git remote add upstream git@github.com:networkx/networkx.git
Now, you have remote repositories named:
upstream
, which refers to thenetworkx
repositoryorigin
, which refers to your personal fork
Develop your contribution:
Pull the latest changes from upstream:
git checkout master git pull upstream master
Create a branch for the feature you want to work on. Since the branch name will appear in the merge message, use a sensible name such as ‘bugfix-for-issue-1480’:
git checkout -b bugfix-for-issue-1480
Commit locally as you progress (
git add
andgit commit
)
To submit your contribution:
Push your changes back to your fork on GitHub:
git push origin bugfix-for-issue-1480
Go to GitHub. The new branch will show up with a green Pull Request button—click it.
If you want, post on the mailing list to explain your changes or to ask for review.
For a more detailed discussion, read these detailed documents on how to use Git with networkx
(https://networkx.github.io/documentation/latest/developer/gitwash/index.html).
Review process:
- Reviewers (the other developers and interested community members) will write inline and/or general comments on your Pull Request (PR) to help you improve its implementation, documentation, and style. Every single developer working on the project has their code reviewed, and we’ve come to see it as friendly conversation from which we all learn and the overall code quality benefits. Therefore, please don’t let the review discourage you from contributing: its only aim is to improve the quality of project, not to criticize (we are, after all, very grateful for the time you’re donating!).
- To update your pull request, make your changes on your local repository and commit. As soon as those changes are pushed up (to the same branch as before) the pull request will update automatically.
- Travis-CI, a continuous integration service, is triggered after each Pull Request update to build the code and run unit tests of your branch. The Travis tests must pass before your PR can be merged. If Travis fails, you can find out why by clicking on the “failed” icon (red cross) and inspecting the build and test log.
- AppVeyor, is another continuous integration service, which we use. You will also need to make sure that the AppVeyor tests pass.
Note
If closing a bug, also add “Fixes #1480” where 1480 is the issue number.
Divergence between upstream master
and your feature branch¶
Never merge the main branch into yours. If GitHub indicates that the branch of your Pull Request can no longer be merged automatically, rebase onto master:
git checkout master
git pull upstream master
git checkout bugfix-for-issue-1480
git rebase master
If any conflicts occur, fix the according files and continue:
git add conflict-file1 conflict-file2
git rebase --continue
However, you should only rebase your own branches and must generally not rebase any branch which you collaborate on with someone else.
Finally, you must push your rebased branch:
git push --force origin bugfix-for-issue-1480
(If you are curious, here’s a further discussion on the dangers of rebasing. Also see this LWN article.)
Guidelines¶
- All code should have tests.
- All code should be documented, to the same standard as NumPy and SciPy.
- All changes are reviewed. Ask on the mailing list if you get no response to your pull request.
Stylistic Guidelines¶
Set up your editor to remove trailing whitespace. Follow PEP08. Check code with
pyflakes
/flake8
.Use the following import conventions:
import numpy as np import scipy as sp import matplotlib as mpl import matplotlib.pyplot as plt import networkx as nx cimport numpy as cnp # in Cython code
Pull request codes¶
When you submit a pull request to GitHub, GitHub will ask you for a summary. If
your code is not ready to merge, but you want to get feedback, please consider
using WIP: experimental optimization
or similar for the title of your pull
request. That way we will all know that it’s not yet ready to merge and that
you may be interested in more fundamental comments about design.
When you think the pull request is ready to merge, change the title (using the
Edit button) to remove the WIP:
.
Developer Notes¶
For additional information about contributing to NetworkX, please see the Developer Notes.
Bugs¶
Please report bugs on GitHub.


What is Coozilla?
CooZilla helps freelance web professionals promote their skills and find new work opportunities. If you hire freelancers, post a job on CooZilla , and the most relevant freelancers will be instantly informed, enabling you to find the best talent.


What?Alexey MigutskyThe Reactive Manifesto is a "bullshit bingo words dictionary", which incorporates distributed system design best practices.
Why?
- We need to communicate to business executives.
- We need to talk on their language.
- We need a bridge built of "bullshit bingo words".
What?Alexey MigutskyThe Reactive Manifesto is a "bullshit bingo words dictionary", which incorporates distributed system design best practices.
Why?
- We need to communicate to business executives.
- We need to talk on their language.
- We need a bridge built of "bullshit bingo words".
| 10 years ago | Now | |
|---|---|---|
| Downtime | hours | none |
| Response time | seconds | milliseconds |
Builds end user confidence and encourages further interactions with system
Parts of the system can fail and recover without compromising the system as a whole
Reactive Systems can react to changes in the input rate by increasing or decreasing the resources allocated to service.
This implies designs that have no central bottlenecks
val socket = Socket() val packet = socket.readFromMemory() val result = socket.sendPacketToUs(packet)
trait Future[T] { def filter(p: T=>Boolean): Future[T] def flatMap[S](f: T=>Future[S]): Future[S] def map[S](f: T=>S): Future[S] def zip[U](that: Future[U]): Future[(T, U)] def recoverWith(f: PartialFunction[Throwable, Future[T]]): Future[T] def recover(pf: PartialFunction[Throwable, U]): Future[T] } object Future { def apply[T](body :=>T): Future[T] def successful[T](result: T): Future[T] def failed[T](exception: Throwable): Future[T] }


{% extends "base.html" %} {% block title %}Precon Survey{% endblock %} {% block page_title %}Precon Survey{% endblock %} {% block content %}
The purpose of this survey is threefold:
The deadline for responding is Friday, February 7, 2014.
To be clear: not all of these events will run. We have more events than we have space. (Yay!) So we need some way to decide what will run. Hence this survey.
We will have a schedule up and distributed shortly after that.
Please e-mail Kevin Riggle at<EMAIL_ADDRESS>if you have any questions or encounter any technical issues.


Animation Controller Asset
The animation controller asset is used to configure complex animations. See the animation controller chapter for a conceptiual description.
Animation Controller Graph
Animation controllers are set up as graph structures. Nodes represent actions. Data flows from left to right. Nodes have input pins and output pins which represent different kinds of data, such as trigger states (on/off), number values, animation poses and bone weights.
The goal of an animation controller is to sample a number of animation clips, combine them together, and generate a final pose which can then be applied to an animated mesh.
Creating Nodes
Right click into the main area to open a context menu. Here you select which nodes to add to the graph. Every graph requires at least an output node, a model space conversion node and a node to sample a clip, for example a play single clip node. Once the graph samples two different clips you also need a combine poses node.
Connecting Nodes
You connect nodes through their pins. Just left click and drag from one output pin to another input pin. The UI will display which pins can be connected once you start dragging. Since every pin represents a certain data type, only compatible pin types may get connected.
Some pins allow to connect to multiple other pins, or have multiple incoming connections. If a pin does not allow this, creating a new connection removes previous connections automatically.
Nodes that are not ultimately connected to the output node, will not have any effect.
Node Properties
Nodes may additionally have properties. These are displayed in the property pane when a node is selected. See the documentation for the different node types for more detailed descriptions.
Using Animation Controller Assets
Once an animation controller asset is set up, it can be applied to an animated mesh by adding an animation controller component to the same game object. The component will evaluate the graph in every update, and send the final animation pose to the animated mesh.
To control what the animation controller does, you may also need a blackboard for storing state, and potentially a script component to decide when which animation should be active.


--- layout: page title: About header-img: "img/about-bg.png" ---
Hi there! My name is Takia. My background is in Biology, but through my job have found an interest for coding. Some of my other interests include animals, traveling, and scary movies.


You've made too many requests. Please wait a moment before trying again.
If this error persists, please let us know.


We work directly with farmers from across Vanuatu including the islands of Epi, Santo, Pentecost, and Malekula, to bring you noble varieties such as Melo Melo, Borogu, Borongoru, and more! We’ve been working with the same generational kava farmers for over 25 years and have established relationships with sustainable and ethical kava farmers. We distribute over 40,000kgs of Vanuatu kava world wide annually and have recently partnered with distributors world wide to bring you farm fresh, noble variety Kava that meets current USDA, FDA, and Codex standards.
Our kava is hand chosen by our exert quality control team, thoroughly cleaned with pressurized filtered water, dried in our indoor drying facility and then sterilized before shipment. The kava is tested by our internal quality control team in house, as well as at bio-security before export, ensuring that you get the highest quality Noble Kava root Available.. Our distributors also re-test the kava upon entry to create a certificate of analysis detailing out the quality of our kava batch by batch.
Email us your order requirements and receive a quote within 24 hours!


{% extends 'admin/my_base.html' %}
{% block body %}
{% if form %}
Predict GO terms from Neighborhoods
Help
Predict GO terms based on the co-expression network. GO-terms enriched in the direct (first-level)
neighborhood of each gene in the networks are tested for enrichment and enriched terms are added to the
source gene.


Actual system of direct bug uploading to the collecting server is now out
of order.
You can help the NetBeans.org project by reporting this problem to
our existing bug tracking system using the Report to Issuezilla
button bellow.
Thank you for helping us make NetBeans better!


{{ app_title }}
Challenge your friends to see who has the best music knowledge!
Click login to link your spotify account.
Login to SpotifyChallenge your friends to see who has the best music knowledge!
Click login to link your spotify account.
Login to Spotify


|
Indexes are defined under the OAObject window, in the "Indexes"
tab. The properties, sort order, etc. are defined there.
This information is then used to create the indexes for the database.
Primary key indexes are created based on creating a property that is flagged as a "Key". |


This demo is interesting because as well as employing the traditional adjustable
feature it also uses a custom event listener in order to add mouse wheel support. This means
that you can also use your mouse wheel to control the value of the Fuel gauge.
<script src="RGraph.common.core.js"></script> <script src="RGraph.fuel.js"></script>Put this where you want the chart to show up:
<canvas id="cvs" width="200" height="200">[No canvas support]</canvas>This is the code that generates the chart - it should be placed AFTER the canvas tag(s):


---
layout: page
description: "creating new local low-carbon collaborations across Scotland"
---
{% for post in paginator.posts %}
{% comment %}
{{ post.title }}
{% if post.subtitle %}
{{ post.subtitle }}
{% endif %}
{% if post.author %}
{% assign author = site.data.authors[post.author] %}
{% if author %}
{% assign author_name = author.name %}
{% else %}
{% assign author_name = post.author %}
{% endif %}
{% else %}
{% assign author_name = site.title %}
{% endif %}
Posted by {{ author_name }} on {{ post.date | date: "%B %-d, %Y" }}
{{ landing.excerpt | strip_html }}
{% endcomment %}
There are hundreds of groups in Scotland making progress and creating change on environmental issues.
But these groups often work in isolation.
Our research team would like to invite you to learn with us about the diversity of approaches in Scotlands grassroots.
Let us seek to find common ground!
Here's how you can get involved:
Learn about:


{% extends 'portfolio/base.html' %} {% load staticfiles %} {% load humanize %}{% load mathfilters %} {% block content %}
| Portfolio Initial Investments | Portfolio Current Investments | Grand Total Results |
|---|---|---|
| {{ sav |add:sum_of_initial_stock_value | intcomma}} | {{ srv |add:sum_current_stocks_value |intcomma }} | {{ stockdiff |add:acquirediff | intcomma }} |
| Cust ID | Symbol | Name | Share | Initial Stock Price | Initial Stock Price |
|---|---|---|---|---|---|
| {{ stock.customer }} | {{ stock.symbol }} | {{ stock.name }} | {{ stock.shares | intcomma }} | {{ stock.purchase_price | intcomma }} | {{ stock.initial_stock_value | intcomma }} |
| Total of initial Stocks | Total of Currents Stocks | Result |
|---|---|---|
| {{ sum_of_initial_stock_value | intcomma }} | {{ sum_current_stocks_value | intcomma }} | {{ sum_current_stocks_value |sub:sum_of_initial_stock_value |intcomma }} |
| Customer ID | Category | Description | Acquired Value | Acquired Date | Recent Value | Recent Date | Results |
|---|---|---|---|---|---|---|---|
| {{ investment.customer }} | {{ investment.category }} | {{ investment.description }} | {{ investment.acquired_value | intcomma }} | {{ investment.acquired_date }} | {{ investment.recent_value | intcomma}} | {{ investment.recent_date }} | {{ investment.results_by_investment | intcomma}} |
| Total of initial Investments | Total of Currents Investments | Results |
|---|---|---|
| {{ sav | intcomma }} | {{ srv | intcomma}} | {{ srv |sub:sav | intcomma}} |


Select Your Color
Input Your Name or Initials (16 Chars Max)
Click on Button to Enter Circle Field
Submit


I like to be nerdy!
Check out what I like to write code in below.
You can contact me through GitHub by my Username Zeno333


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r
- Variable in class org.robobrain.sdk.graphics.
Color
The Color's Red channel.
Rectangle
- Class in
org.robobrain.sdk.graphics
Encapsulates a 2D Rectangle.
Rectangle()
- Constructor for class org.robobrain.sdk.graphics.
Rectangle
Initializes the Rectangle at the origin with no width or height.
Rectangle(int, int, int, int)
- Constructor for class org.robobrain.sdk.graphics.
Rectangle
Initializes the Rectangle at specific point in space.
RED
- Static variable in class org.robobrain.sdk.graphics.
Color
A convenience constant for the color Red.
registerGame(Engine)
- Method in class org.robobrain.sdk.
GameActivity
Registers a game Engine class to be used by this Activity to run a game.
registerGame(Engine)
- Method in class org.robobrain.sdk.
GLRenderer
Registers your game's Engine with this renderer.
registerGame(Engine)
- Method in class org.robobrain.sdk.
GLView
Registers your game's Engine with this renderer.
registerSound(String, int)
- Static method in class org.robobrain.sdk.audio.
SoundManager
Register an integer handle for a sound file.
registerTexture(String, int)
- Static method in class org.robobrain.sdk.graphics.
TextureManager
Registers a numeric constant with a particular texture.
registerWorld(World)
- Method in class org.robobrain.sdk.game.
Engine
Registers the World with the game Engine.
release()
- Static method in class org.robobrain.sdk.audio.
MusicManager
Clears and releases any resources used by the player.
release()
- Static method in class org.robobrain.sdk.audio.
SoundManager
Releases all resources the SoundManager is using.
release()
- Static method in class org.robobrain.sdk.graphics.
TextureManager
Releases any memory associated with the TextureManager.
remove
- Variable in class org.robobrain.sdk.game.
Entity
Used by the World to determine when to remove this Entity.
removeEntity(Entity)
- Method in class org.robobrain.sdk.game.
World
Removes an Entity from the World.
render(GL10)
- Method in class org.robobrain.sdk.game.
Engine
Draws all sprites.
render(GL10)
- Method in class org.robobrain.sdk.game.
World
Renderable
- Class in
org.robobrain.sdk.graphics
The base Renderable object.
Renderable()
- Constructor for class org.robobrain.sdk.graphics.
Renderable
resume()
- Method in class org.robobrain.sdk.
GLRenderer
Unpauses the Renderer.
rotate(float)
- Method in class org.robobrain.sdk.graphics.
Vector
rotation
- Variable in class org.robobrain.sdk.game.
Entity
rotation
- Variable in class org.robobrain.sdk.graphics.
Renderable
The angle of rotation applied to the Renderable.
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This course will walk you through the basic concepts of Programming using the Python programming language.
Programming is simply the act of entering instructions for the computer to perform. These instructions might crunch some numbers, modify text, look up information in files, or communicate with other computers over the Internet.
A program is like a:
But for the computer!
All programs, written in any language uses the same basic building blocks
Her are a few of the most common:
For most people, their computer is just an appliance instead of a tool. But by learning how to program, you'll gain access to one of the most powerful tools of the modern world, and you'll have fun along the way. Programming isn't brain surgery—it's fine for amateurs to experiment and make mistakes.
Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
Developed by Guido van Rossum
Test that Python is properly installed by running
python --version
in a CMD/Powershell shell.
In case of errors reference the - Using Python on Windows page: link
Ubuntu
sudo apt-get update
sudo apt-get install python3.7
python3 --version
On macOS, the best way to install Python 3 is to use Homebrew. Not familiar with homebrew? link
brew install python3
There are several tools installed with the Python interpeter. Here are some of them:
python interpreter | The python interpreter. The executable that can be called directly from the commandline/terminal to start a new interactive python session (REPL) or to run python modules/files/packages |
pip | The Python package manager. The official Python package manager. Lets the user download and manage third-party packages hosted on the Python package index (PyPI) |
IDLE | IDLE is Python's Integrated Development and Learning Environment. Its a Python IDE for and by Python |
pydoc | The pydoc module automatically generates documentation from Python modules. |
Python can be used and developed with using only a basic text editor and the python interpreter. But for larger and more complex projects there is a benefit to use porpouse built tools for Python development.
Objects are Python's abstraction for data. All data in a Python program is represented by objects or by relations between objects.
Python has two main versions. Python 2 and Python 3. Python 3 is the newest, but it has struggeled with adoption for some time. Python 3 has as of 2018 taken the mantle as the main version from Python 2.
Practicly this means that new Python packages and application will in most cases be written in Python 3.


This tool transpiles the given Python code into form that Jsvee understands and can execute.
Not all Python language features are supported. Arithmetical operations, assignments, while loops,
for loops to iterate a list, functions, lists, dictionaries and simple classes are available.
The only built-in functions available are: abs
, float
, input
, int
,
len
, max
, min
, range
(in for
loop), list.append
,
str.split
, and print
. You will get an error if the code contains language features which are not available.


Entrepreneur since 2007, experience as employer for another ten years.
I have suffered the lack of information to manage my own business, to minimize mistakes, to take better and fast decisions and to work in the core business that is selling, instead of the effort to gather the data need in order to make in the business more profits.
As employee I was the responsible of the quality system, I learned that all the efforts a business should make, must be in order to find and accomplish the client needs. I have learned that if we have enough information, we can solve almost all the problems appears. We could find the solutions in order to get the best business performance.
Always first hearing the client before proposing.
I would like to find the specific information needs of any business and full fill them with interactions through apps to get friendly reports as the big company does it.
Back and Front Solutions
Always earing your problemes to improve our soluctions
Support is our decision
Always checking performace


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- The @ACR884 Tech Slot #005
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- @ACR884 Tech Slot #002 – Tablets
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iPhone
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Sony
iOS
- The @ACR884 Tech Slot #004
- Why Are Android Smartphones Bigger Than the iPhone?
- @ACR884 Tech Slot #002 – Tablets
- @ACR884 Tech Slot #001 - Phones


Watch: Insane Hail Storm Wreaks Havoc In Harare CBD, Zimbabweans React
by AndrewInsane Hail Storm Wreaks Havoc In Harare CBD, Zimbabweans React
A vicious hailstorm accompanied by strong winds swept across Harare’s CBD on Monday afternoon, forcing many to seek shelter in nearby buildings. Motorists and pedestrians were pelted by the ice pellets during the storm which only lasted for just about an hour.
Most Zimbabweans seemingly were ecstatic for the rain which has brought relief from the heatwave scorching most parts of the country. However, there were mixed feelings over the violent storm which has already left a trail of destruction in some parts of the country, evocative of the Cyclone disaster.
Check out some of the twitter reactions below………
MORE FROM IHARARE
“This Food is for ZANU PF Supporters Only,” WATCH as ZANU PF Official politicises food
To View and Apply for the latest Jobs and Vacancies in Zimbabwe, Please Visit our Sister website iHarare Jobs


Inherits Programmer.
|
| | Senior (string name, string birth, string email, double baseSalary, int NIF) |
| | Base constructor for the manager class. More...
|
| |
|
double | getSalary () |
| | Function to return the senior programmer's salary.
|
| |
◆ Senior()
| Senior::Senior |
( |
string |
name, |
|
|
string |
birth, |
|
|
string |
email, |
|
|
double |
baseSalary, |
|
|
int |
NIF |
|
) |
| |
Base constructor for the manager class.
- Parameters
-
| name | - string of the senior programmer's name |
| birth | - string of the senior programmer's date of birth |
| email | - string of the senior programmer's email |
| email | - double of the senior programmer's base salary |
| email | - int of the senior programmer's NIF |
The documentation for this class was generated from the following files:
- C:/Users/Afonso Sá/source/repos/AEDAPROJ1/AEDAPROJ1/User.h
- C:/Users/Afonso Sá/source/repos/AEDAPROJ1/AEDAPROJ1/User.cpp


|
Short guide to DBI (The Perl Database Interface Module)
by Mark-Jason Dominus
Oct. 22, 1999
Relational databases started to get to be a big deal in the 1970's, and
they're still a big deal today, which is a little peculiar, because they're
a 1960's technology.
 Each row of a table
is a record about one person or thing; the record contains several pieces
of information called fields. Here is an example table:
LASTNAME FIRSTNAME ID POSTAL_CODE AGE SEX
Gauss Karl 119 19107 30 M
Smith Mark 3 T2V 3V4 53 M
Noether Emmy 118 19107 31 F
Smith Jeff 28 K2G 5J9 19 M
Hamilton William 247 10139 2 M
The names of the fields are LASTNAME , FIRSTNAME , ID ,
POSTAL_CODE , AGE , and SEX . Each line in the table is a
record, or sometimes a row or tuple. For example, the first row of the table represents a 30-year-old male
whose name is Karl Gauss, who lives at postal code 19107, and whose ID
number is 119.
Sometimes this is a very silly way to store information. When the
information naturally has a tabular structure it's fine. When it doesn't,
you have to squeeze it into a table, and some of the techniques for doing
that are more successful than others. Nevertheless, tables are simple and
are easy to understand, and most of the high-performance database systems
you can buy today operate under this 1960's model.
SQL stands for Structured Query Language. It was invented by Oracle in the 1970's. It's a language for describing
searches and modifications to a relational database.
SQL was a huge success, probably because it's incredibly simple and anyone
can pick it up in ten minutes. As a result, all the important database
systems support it in some fashion or another. This includes the big
players, like Oracle and Sybase, high-quality free or inexpensive database
systems like MySQL, and funny hacks like Perl's
DBD::CSV module, which we'll see later.
There are four important things one can do with a table:
- SELECT
-
Find all the records that have a certain property
- INSERT
-
Add new records
- DELETE
-
Remove old records
- UPDATE
-
Modify records that are already there
Those are the four most important SQL commands, also called
queries. Suppose that the example table above is named people . Here are examples of each of the four important kinds of queries:
SELECT firstname FROM people WHERE lastname = 'Smith'
(Locate the first names of all the Smiths.)
DELETE FROM people WHERE id = 3
(Delete Mark Smith from the table)
UPDATE people SET age = age+1 WHERE id = 247
(William Hamilton just had a birthday.)
INSERT INTO people VALUES ('Euler', 'Leonhard', 248, NULL, 58, 'M')
(Add Leonhard Euler to the table.)
 But these four are the important ones.
Congratulations; you are now a SQL programmer. For the details, go to any
reasonable bookstore and pick up a SQL quick reference.
Every database system is a little different. You talk to some databases over
the network and make requests of the database engine; other databases you
talk to through files or something else.
Typically when you buy a commercial database, you get a library
with it. The vendor has written some functions for talking to the database
in some language like C, compiled the functions, and the compiled code is
the library. You can write a C program that calls the functions in the
library when it wants to talk to the database.
Every vendor's library is different. The names of the functions vary, and
the order in which you call them varies, and the details of passing queries
to the functions and getting the data back out will vary. Some libraries,
like Oracle's, are very thinthey just send the query over to the network
to the real database and let the giant expensive real database engine deal
with it directly. Other libraries will do more predigestion of the query,
and more work afterwards to turn the data into a data structure.
There's a saying that any software problem can be solved by adding a layer
of indirection. That's what Perl's DBI (`Database Interface') module is all about. It was written by Tim Bunce.
DBI is designed to protect you from the details of the vendor libraries. It has
a very simple interface for saying what SQL queries you want to make, and
for getting the results back. DBI doesn't know how to talk to any particular database, but it does know how
to locate and load in DBD (`Database Driver') modules. The DBD modules have the vendor libraries in them and know how to talk to the real
databases; there is one DBD module for every different database.
When you ask DBI to make a query for you, it sends the query to the appropriate DBD module, which spins around three times or drinks out of its sneaker or
whatever is necessary to communicate with the real database. When it gets the
results back, it passes them to DBI . Then DBI gives you the results. Since your program only has to deal with DBI , and not with the real database, you don't have to worry about barking
like a chicken.
Here's your program talking to the DBI library. You are using two databases at once. One is an Oracle database
server on some other machine, and another is a DBD::CSV database that stores the data in a bunch of plain text files on the local
disk.
Your program sends a query to DBI , which forwards it to the appropriate DBD module; let's say it's DBD::Oracle . DBD::Oracle knows how to translate what it gets from DBI into the format demanded by the Oracle library, which is built into it. The
library forwards the request across the network, gets the results back, and
returns them to
DBD::Oracle . DBD::Oracle returns the results to DBI as a Perl data structure. Finally, your program can get the results from
DBI .
On the other hand, suppose that your program was querying the text files.
It would prepare the same sort of query in exactly the same way, and send
it to DBI in exactly the same way. DBI would see that you were trying to talk to the DBD::CSV database and forward the request to the DBD::CSV module. The DBD::CSV module has Perl functions in it that tell it how to parse SQL and how to
hunt around in the text files to find the information you asked for. It
then returns the results to DBI as a Perl data structure. Finally, your program gets the results from DBI in exactly the same way that it would have if you were talking to Oracle
instead.
There are two big wins that result from this organization. First, you don't
have to worry about the details of hunting around in text files or talking
on the network to the Oracle server or dealing with Oracle's library. You
just have to know how to talk to DBI .
Second, if you build your program to use Oracle, and then the following
week upper management signs a new Strategic Partnership with Sybase, it's
easy to convert your code to use Sybase instead of Oracle. You change
exactly one line in your program, the line that tells DBI to talk to DBD::Oracle , and have it use DBD::Sybase
instead. Or you might build your program to talk to a cheap, crappy
database like MS Access, and then next year when the application is doing
well and getting more use than you expected, you can upgrade to a better
database next year without changing any of your code.
There are DBD modules for talking to every important kind of SQL database. DBD::Oracle will talk to Oracle, and DBD::Sybase will talk to Sybase. DBD::ODBC will talk to any ODBC database including Microsoft Acesss. (ODBC is a
Microsoft invention that is analogous to
DBI itself. There is no DBD module for talking to Access directly.) DBD::CSV allows SQL queries on plain text files.
DBD::mysql talks to the excellent MySQL database from TCX DataKonsultAB in Sweden.
(MySQL is a tremendous bargain: It's $200 for commercial use,
and free for noncommerical use.)
Here's a typical program. When you run it, it waits for you to type a last
name. Then it searches the database for people with that last name and
prints out the full name and ID number for each person it finds. For
example:
Enter name> Noether
118: Emmy Noether
Enter name> Smith
3: Mark Smith
28: Jeff Smith
Enter name> Snonkopus
No names matched `Snonkopus'.
Enter name> ^D
Here is the code:
use DBI;
my $dbh = DBI->connect('DBI:Oracle:payroll')
or die "Couldn't connect to database: " .  Notice that we don't have to load in any DBD module. DBI will do that for us when it needs to.
my $dbh = DBI->connect('DBI:Oracle:payroll');
or die "Couldn't connect to database: " . DBI->errstr;
The connect call tries to connect to a database. The first argument, DBI:Oracle:payroll , tells DBI what kind of database it is connecting to. The Oracle part tells it to load DBD::Oracle and to use that to communicate with the database. If we had to switch to
Sybase next week, this is the one line of the program that we would change.
We would have to change Oracle to Sybase .
payroll is the name of the database we will be searching. If we were going to
supply a username and password to the database, we would do it in the connect call:
my $dbh = DBI->connect('DBI:Oracle:payroll', 'username', 'password');
or die "Couldn't connect to database: " . DBI->errstr;
If DBI connects to the database, it returns a database handle
object, which we store into $dbh . This object represents the database connection. We can be connected to
many databases at once and have many such database connection obejcts.
If DBI can't connect, it returns an undefined value. In this case, we use die to abort the program with an error message.
DBI->errstr returns the reason why we couldn't connect``Bad password'' for example.
my $sth = $dbh->prepare('SELECT * FROM people WHERE lastname = ?')
or die "Couldn't prepare statement: " . $dbh->errstr;
The prepare call prepares a query to be executed by the database. The argument is any
SQL at all. On high-end databases, prepare will send the SQL to the database server, which will compile it. If
prepare is successful, it returns a statement handle object which represents the statement; otherwise it returns an undefined
value and we abort the program. $dbh->errstr will return the reason for failure, which might be ``Syntax error in SQL''.
It gets this reason from the actual database, if possible.
The ? in the SQL will be filled in later. Most databases can handle this. For
some databases that don't understand the ? , the DBD module will emulate it for you and will pretend that the database
understands how to fill values in later, even though it doesn't.
print "Enter name> ";
Here we just print a prompt for the user.
while ($lastname = <>) { # Read input from the user
...
}
This loop will repeat over and over again as long as the user enters a last
name. If they type a blank line, it will exit. The Perl
<> symbol means to read from the terminal or from files named on the command
line if there were any.
my @data;
This declares a variable to hold the data that we will get back from the
database.
chomp $lastname;
This trims the newline character off the end of the user's input.
$sth->execute($lastname) # Execute the query
or die "Couldn't execute statement: " . $sth->errstr;
execute executes the statement that we prepared before. The argument $lastname is substituted into the SQL in place of the
? that we saw earlier. execute returns a true value if it succeeds and a false value otherwise, so we
abort if for some reason the execution fails.
while (@data = $sth->fetchrow_array()) {
...
}
fetchrow_array returns one of the selected rows from the database. You get back an array
whose elements contain the data from the selected row. In this case, the
array you get back has six elements. The first element is the person's
last name; the second element is the first name; the third element is the
ID, and then the other elements are the postal code, age, and sex.
Each time we call fetchrow_array , we get back a different record from the database. When there are no more
matching records,
fetchrow_array returns the empty list and the while loop exits.
my $firstname = $data[1];
my $id = $data[2];
These lines extract the first name and the ID number from the record data.
print "\t$id: $firstname $lastname\n";
This prints out the result.
if ($sth->rows == 0) {
print "No names matched `$lastname'.\n\n";
}
The rows method returns the number of rows of the
database that were selected. If no rows were selected, then there is
nobody in the database with the last name that the user is looking
for. In that case, we print out a message. We have to do this
after the while loop that fetches whatever rows
were available, because with some databases you don't know how many
rows there were until after you've gotten them all.
print "\n";
print "Enter name> ";
Once we're done reporting about the result of the query, we print another
prompt so that the user can enter another name.
$sth->finish;
$dbh->disconnect;
When the user has finished querying the database, they type a blank line
and the main while loop exits. finish tells the database that we won't need this statement handle any more and it
can forget the SQL in it. disconnect closes the connection to the database.
Here's a function which looks up someone in the example table, given their
ID number, and returns their age:
sub age_by_id {
# Arguments: database handle, person ID number
my ($dbh, $id) = @_;
my $sth = $dbh->prepare('SELECT age FROM people WHERE id = ?')
or die "Couldn't prepare statement: " . $dbh->errstr;
$sth->execute($id)
or die "Couldn't execute statement: " . $sth->errstr;
my ($age) = $sth->fetchrow_array();
return $age;
}
It prepares the query, executes it, and retrieves the result.
There's a problem here though. Even though the function works correctly,
it's inefficient. Every time it's called, it prepares a new query.
Typically, preparing a query is a relatively expensive operation. For
example, the database engine may parse and understand the SQL and translate
it into an internal format. Since the query is the same every time, it's
wasteful to throw away this work when the function returns.
Here's one solution:
{ my $sth;
sub age_by_id {
# Arguments: database handle, person ID number
my ($dbh, $id) = @_;
if (! defined $sth) {
$sth = $dbh->prepare('SELECT age FROM people WHERE id = ?')
or die "Couldn't prepare statement: " . $dbh->errstr;
}
$sth->execute($id)
or die "Couldn't execute statement: " . $sth->errstr;
my ($age) = $sth->fetchrow_array();
return $age;
}
}
There are two big changes to this function from the previous version.
First, the $sth variable has moved outside of the function; this tells Perl that its value
should persist even after the function returns. Next time the function is
called, $sth will have the same value as before.
Second, the prepare code is in a conditional block. It's only executed if $sth does not yet have a value. The first time the function is called, the prepare code is executed and the statement handle is stored into $sth . This value persists after the function returns, and the next time the
function is called, $sth
still contains the statement handle and the prepare code is skipped.
Here's another solution:
sub age_by_id {
# Arguments: database handle, person ID number
my ($dbh, $id) = @_;
my $sth = $dbh->prepare_cached('SELECT age FROM people WHERE id = ?')
or die "Couldn't prepare statement: " . $dbh->errstr;
$sth->execute($id)
or die "Couldn't execute statement: " . $sth->errstr;
my ($age) = $sth->fetchrow_array();
return $age;
}
Here the only change to to replace prepare with prepare_cached . The prepare_cached call is just like prepare , except that it looks to see if the query is the same as last time. If so,
it gives you the statement handle that it gave you before.
Many databases support transactions. This means that you can make a whole bunch of queries which would modify
the databases, but none of the changes are actually made. Then at the end
you issue the special SQL query COMMIT , and all the changes are made simultaneously. Alternatively, you can issue
the query ROLLBACK , in which case all the queries are thrown away.
As an example of this, consider a function to add a new employee to a
database. The database has a table called employees that looks like this:
FIRSTNAME LASTNAME DEPARTMENT_ID
Gauss Karl 17
Smith Mark 19
Noether Emmy 17
Smith Jeff 666
Hamilton William 17
and a table called departments that looks like this:
ID NAME NUM_MEMBERS
17 Mathematics 3
666 Legal 1
19 Grounds Crew 1
The mathematics department is department #17 and has three members: Karl
Gauss, Emmy Noether, and William Hamilton.
Here's our first cut at a function to insert a new employee. It will return
true or false depending on whether or not it was successful:
sub new_employee {
# Arguments: database handle; first and last names of new employee;
# department ID number for new employee's work assignment
my ($dbh, $first, $last, $department) = @_;
my ($insert_handle, $update_handle);
my $insert_handle =
$dbh->prepare_cached('INSERT INTO employees VALUES (?,?,?)');
my $update_handle =
$dbh->prepare_cached('UPDATE departments
SET num_members = num_members + 1
WHERE id = ?');
die "Couldn't prepare queries; aborting"
unless defined $insert_handle && defined $update_handle;
$insert_handle->execute($first, $last, $department) or return 0;
$update_handle->execute($department) or return 0;
return 1; # Success
}
We create two handles, one for an insert query that will insert the new employee's name and department number into
the employees table, and an update query that will increment the number of members in the new employee's
department in the department table. Then we execute the two queries with the appropriate arguments.
There's a big problem here: Suppose, for some reason, the second query
fails. Our function returns a failure code, but it's too late, it has
already added the employee to the employees table, and that means that the count in the departments table is wrong. The database now has corrupted data in it.
The solution is to make both updates part of the same transaction. Most
databases will do this automatically, but without an explicit instruction
about whether or not to commit the changes, some databases will commit the
changes when we disconnect from the database, and others will roll them
back. We should specify the behavior explicitly.
Typically, no changes will actually be made to the database until we issue
a commit . The version of our program with commit looks like this:
sub new_employee {
# Arguments: database handle; first and last names of new employee;
# department ID number for new employee's work assignment
my ($dbh, $first, $last, $department) = @_;
my ($insert_handle, $update_handle);
my $insert_handle =
$dbh->prepare_cached('INSERT INTO employees VALUES (?,?,?)');
my $update_handle =
$dbh->prepare_cached('UPDATE departments
SET num_members = num_members + 1
WHERE id = ?');
die "Couldn't prepare queries; aborting"
unless defined $insert_handle && defined $update_handle;
my $success = 1;
$success &&= $insert_handle->execute($first, $last, $department);
$success &&= $update_handle->execute($department);
my $result = ($success ? $dbh->commit : $dbh->rollback);
unless ($result) {
die "Couldn't finish transaction: " . $dbh->errstr
}
return $success;
}
We perform both queries, and record in $success whether they both succeeded. $success will be true if both queries succeeded, false otherwise. If the queries
succeded, we commit the transaction; otherwise, we roll it back, cancelling
all our changes.
The problem of concurrent
database access is also solved by transactions. Suppose that queries were executed immediately, and that
some other program came along and examined the database after our insert
but before our update. It would see inconsistent data in the database, even
if our update would eventually have succeeded. But with transactions, all
the changes happen simultaneously when we do the commit , and the changes are committed automatically, which means that any other
program looking at the database either sees all of them or none.
If you're doing an UPDATE , INSERT , or DELETE there is no data that comes back from the database, so there is a short
cut. You can say
$dbh->do('DELETE FROM people WHERE age > 65');
for example, and DBI will prepare the statement, execute it, and finish it. do returns a true value if it succeeded, and a false value if it failed.
Actually, if it succeeds it returns the number of affected rows. In the
example it would return the number of rows that were actually deleted. (DBI plays a magic trick so that the value it turns is true even when it is 0.
This is bizarre, because 0 is usually false in Perl. But it's convenient
because you can use it either as a number or as a true-or-false success
code, and it works both ways.)
If your transactions are simple, you can save yourself the trouble of
having to issue a lot of commit s. When you make the connect call, you can specify an AutoCommit option which will perform an automatic commit operation after every successful query. Here's what it looks like:
my $dbh = DBI->connect('DBI:Oracle:payroll',
{AutoCommit => 1},
)
or die "Couldn't connect to database: " . DBI->errstr;
When you make the connect call, you can specify a RaiseErrors
option that handles errors for you automatically. When an error occurs, DBI will abort your program instead of returning a failure code. If all you
want is to abort the program on an error, this can be convenient:
my $dbh = DBI->connect('DBI:Oracle:payroll',
{RaiseError => 1},
)
or die "Couldn't connect to database: " . DBI->errstr;
People are always writing code like this:
while ($lastname = <>) {
my $sth = $dbh->prepare("SELECT * FROM people
WHERE lastname = '$lastname'");
$sth->execute();
# and so on ...
}
Here we interpolated the value of $lastname directly into the SQL in the prepare call.
This is a bad thing to do for three reasons.
First, prepare calls can take a long time. The database server has to compile the SQL and
figure out how it is going to run the query. If you have many similar
queries, that is a waste of time.
Second, it will not work if $lastname contains a name like O'Malley or D'Amico or some other name with an ' . The ' has a special meaning in SQL, and the database will not understand when you
ask it to prepare a statement that looks like
SELECT * FROM people WHERE lastname = 'O'Malley'
It will see that you have three ' s and complain that you
don't have a fourth matching '
somewhere else.
Finally, if you're going to be constructing your query based on a user
input, as we did in the example program, it's unsafe to simply
interpolate the input directly into the query, because the user can
construct a strange input in an attempt to trick your program into
doing something it didn't expect. For example, suppose the user
enters the following bizarre value for $input :
x' or lastname = lastname or lastname = 'y
Now our query has become something very surprising:
SELECT * FROM people WHERE lastname = 'x'
or lastname = lastname or lastname = 'y'
The part of this query that our sneaky user is interested in is the
second or clause. This clause selects all the records
for which lastname is equal to lastname ;
that is, all of them. We thought that the user was only going to be
able to see a few records at a time, and now they've found a way to
get them all at once. This probably wasn't what we wanted.
|
References |
|
A complete list of DBD modules are available here
You can download these modules here
DBI modules are available here
You can get MySQL from www.tcx.se
|
People go to all sorts of trouble to get around these problems with
interpolation. They write a function that puts the last name in quotes
and then backslashes any apostrophes that appear in it. Then it breaks
because they forgot to backslash backslashes. Then they make their
escape function better. Then their code is a big message because they
are calling the backslashing function every other line. They put a lot
of work into it the backslashing function, and it was all for nothing,
because the whole problem is solved by just putting a ?
into the query, like this
SELECT * FROM people WHERE lastname = ?
All my examples look like this. It is safer and more convenient and
more efficient to do it this way.
|


Academic posters are usually designed using presentation software and distributed as images or PDFs.
While PDFs are fine for printing posters, they are not particularly user-friendly: they are hard to read on small screens, don't support resizing text or increasing contrast, and often don't work nicely with screen readers.
The recent shift to online conferences is a great opportunity to reconsider our poster-making tools, and it turns out that plain HTML5 + CSS works pretty well for making (more) accessible posters.
This template is released under a permissive license: all we ask if you use it for your own posters is that you leave a one-line comment in the HTML sources.
Using this template
There are two ways to use this template: directly editing the HTML, and using Jinja2 templates.
Editing the HTML directly
This is the simplest way to get started, since it just requires a text editor:
Create your own jinja2 template, starting from this tutorial.
Render to HTML using the render.py script: ./render.py your_jinja2_poster.jinja output.html
The template for this tutorial includes documentation for each variable and block.
Poster layout
Posters made using this template are composed of a sequence of blocks. You can use CSS to customize the way the blocks are designed; by default they scroll left to right on wide screens and top to bottom on narrow screens.
Try resizing your browser to see how the poster's layout changes.
Block template
Each block has the following structure (fill in the italicized parts):
Prefer scalable images (SVG) for technical drawings and figures.
Most technical drawing software supports saving as SVG; if yours does not, you can typically save to PDF, which can then easily be converted to SVG (this is useful for TikZ diagrams in particular).
Make sure to include an alt attribute: it will be read by assistive technology and displayed while the image is loading
Mathematics
This poster template loads MathJax by default, so you can include inline math in backslash-parentheses \( … \) and display math in backslash-brackets \[ … \]:
\((\lambda x. e) v \downarrow e[x/v]\) (β-reduction)


--- layout: post title: 3G Princess defends pricey content palace date: 2005-11-09 00:00:00 categories: business digital-media mobile ---
3G Princess defends pricey content palace: ""If you built a palace would you rent it to people for $1000 a month?” WiMAX has no roaming abilities and Hutchison W is a media company now rather than just an operator.""


Use this area of the page to describe your project. The icon above is part of a free icon set by Flat Icons. On their website, you can download their free set with 16 icons, or you can purchase the entire set with 146 icons for only $12!
Use this area of the page to describe your project. The icon above is part of a free icon set by Flat Icons. On their website, you can download their free set with 16 icons, or you can purchase the entire set with 146 icons for only $12!
Use this area of the page to describe your project. The icon above is part of a free icon set by Flat Icons. On their website, you can download their free set with 16 icons, or you can purchase the entire set with 146 icons for only $12!
Use this area of the page to describe your project. The icon above is part of a free icon set by Flat Icons. On their website, you can download their free set with 16 icons, or you can purchase the entire set with 146 icons for only $12!
Use this area of the page to describe your project. The icon above is part of a free icon set by Flat Icons. On their website, you can download their free set with 16 icons, or you can purchase the entire set with 146 icons for only $12!
Use this area of the page to describe your project. The icon above is part of a free icon set by Flat Icons. On their website, you can download their free set with 16 icons, or you can purchase the entire set with 146 icons for only $12!


Freelancer
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intelligence is nothing without ambition
.
We’re small but impressive creative agency.
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My name is Caroline Nyambura, a student currently undertaking a prep course at Moringa school. I am a tech enthusiast and I love coding, a journey I have recently started in my current school. In the future, I would really love to venture into stuff like Cyber security and network forensics. Checkout Moringa school here.


Instructor: Professor Hong
(type-name) expression
>
>=
<
<=
==
!=
&&
||
!0
!1
!100
!(5 < 2)
!((5 < 2) || !(3 < 1))
&
|
^
<<
>>
~
i = i + 2
i += 2
i = i - 2
i -= 2
expr1 = (expr1) op (expr2)
expr1 op= expr2
* / % << >> & ^ |


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LCD Configuration for Time Division Multiplexing. More...
#include <csl_dssVideoPort.h>
Data Fields | |
| uint32_t | tdmEnable |
| uint32_t | tdmUnusedBitsLevel |
| uint32_t | tdmCycleFormat |
| uint32_t | tdmParallelMode |
| uint32_t | numBitsPixel1Cycle0 |
| uint32_t | numBitsPixel1Cycle1 |
| uint32_t | numBitsPixel1Cycle2 |
| uint32_t | bitAlignPixel1Cycle0 |
| uint32_t | bitAlignPixel1Cycle1 |
| uint32_t | bitAlignPixel1Cycle2 |
| uint32_t | numBitsPixel2Cycle0 |
| uint32_t | numBitsPixel2Cycle1 |
| uint32_t | numBitsPixel2Cycle2 |
| uint32_t | bitAlignPixel2Cycle0 |
| uint32_t | bitAlignPixel2Cycle1 |
| uint32_t | bitAlignPixel2Cycle2 |
LCD Configuration for Time Division Multiplexing.
| uint32_t CSL_DssVpLcdTdmCfg::bitAlignPixel1Cycle0 |
Alignment of the bits from pixel 1 for cycle0 on the output interface
| uint32_t CSL_DssVpLcdTdmCfg::bitAlignPixel1Cycle1 |
Alignment of the bits from pixel 1 for cycle1 on the output interface
| uint32_t CSL_DssVpLcdTdmCfg::bitAlignPixel1Cycle2 |
Alignment of the bits from pixel 1 for cycle2 on the output interface
| uint32_t CSL_DssVpLcdTdmCfg::bitAlignPixel2Cycle0 |
Alignment of the bits from pixel 2 for cycle 0 on the output interface
| uint32_t CSL_DssVpLcdTdmCfg::bitAlignPixel2Cycle1 |
Alignment of the bits from pixel 2 for cycle 1 on the output interface
| uint32_t CSL_DssVpLcdTdmCfg::bitAlignPixel2Cycle2 |
Alignment of the bits from pixel 2 for cycle 2 on the output interface
| uint32_t CSL_DssVpLcdTdmCfg::numBitsPixel1Cycle0 |
Number of bits from the pixel 1 for cycle 0(value from 0 to 16 bits). The values from 17 to 31 are invalid
| uint32_t CSL_DssVpLcdTdmCfg::numBitsPixel1Cycle1 |
Number of bits from the pixel 1 for cycle 1(value from 0 to 16 bits). The values from 17 to 31 are invalid
| uint32_t CSL_DssVpLcdTdmCfg::numBitsPixel1Cycle2 |
Number of bits from the pixel 1 for cycle 2(value from 0 to 16 bits). The values from 17 to 31 are invalid
| uint32_t CSL_DssVpLcdTdmCfg::numBitsPixel2Cycle0 |
Number of bits from the pixel 2 for cycle 0(value from 0 to 16 bits). The values from 17 to 31 are invalid
| uint32_t CSL_DssVpLcdTdmCfg::numBitsPixel2Cycle1 |
Number of bits from the pixel 2 for cycle 1(value from 0 to 16 bits). The values from 17 to 31 are invalid
| uint32_t CSL_DssVpLcdTdmCfg::numBitsPixel2Cycle2 |
Number of bits from the pixel 2 for cycle 2(value from 0 to 16 bits). The values from 17 to 31 are invalid
| uint32_t CSL_DssVpLcdTdmCfg::tdmCycleFormat |
Cycle format (TDM mode only) for the VP output. For valid values see CSL_DssVpTdmCycleFormat
| uint32_t CSL_DssVpLcdTdmCfg::tdmEnable |
Enable the multiple cycle format for the VP output FALSE: Disable TDM TRUE: Enable TDM
| uint32_t CSL_DssVpLcdTdmCfg::tdmParallelMode |
Output interface width (TDM mode only) for the VP output. For valid values see CSL_DssVpTdmParallelMode
| uint32_t CSL_DssVpLcdTdmCfg::tdmUnusedBitsLevel |
State of unused bits (TDM mode only) for the VP output. For valid values see CSL_DssVpTdmUnusedBitsLevel


While most people enjoy casino gambling,
Sports betting, lottery and bingo playing for the fun
The Myspace page defines the individual.
Personal choices and the overall personality of the person.
Vampires The Romantic Ideology Behind Them
CEO, PrettyDopeDesigns
“When To Use High Heat On Your Barbeque, What S Under Your Grill”
Vampires The Romantic Ideology Behind Them
There is something about parenthood that gives us a sense of history and a deeply rooted desire to send on into the next generation the great things we have discovered about life.
And part of that is the desire to instill in our children the love of science, of learning and particularly the love of nature.
There are advances being made in science and technology everyday, and a good example of this is the LCD monitor. LCD monitors have several benefits over the old chunky computer monitors that most users are familiar with. Old computer monitors, take up quite a bit of desktop space, put out a ton of heat, drain a ton of energy, and most often have low picture quality and resolution.
Vampires The Romantic Ideology Behind Them
By Abul Hasan Milon | 02 Feb 2019
By Milon Mahamud | 06 Feb 2019
By Speed Smith | 08 Feb 2019
Maui helicopter tours are a great way to
see the island from a different
perspective and have a fun adventure.
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Messenger connector common model
MessengerConnectorMessage |
abstract class MessengerConnectorMessage : ConnectorMessage |
Recipient |
One of id or userRef must not be null. data class Recipient |
Sender |
data class Sender |
UserProfile |
data class UserProfile |


Efficient way to manage your input data using sanitization decorators.
you need to install @rxweb/sanitizers