News@UnidataUnidata newshttps://www.unidata.ucar.edu/blogs/news/feed/entries/atom2024-03-06T11:18:50-07:00Apache Rollerhttps://www.unidata.ucar.edu/blogs/news/entry/announcing-introduction-to-metpy-virtualIntroduction to MetPy Virtual WorkshopNicole Corbin2021-09-02T10:27:38-06:002021-09-07T07:30:10-06:00<div class="img_l" style="width: 150px;"> <img width="150" src="/images/logos/metpy-400x400.png" alt="MetPy Virtual Workshop" />
</div>
<p>
<b>This event's registration is now closed.</b><br>
Announcing the next offering of the <b>Introduction to MetPy virtual workshop</b>! This 4-hour interactive workshop is designed to introduce participants to the MetPy Python package and accessing data products made available by Unidata. If you or someone you know has an interest in getting started with MetPy workflows, this is an optimal place to start.</p>
<div class="img_l" style="width: 150px;"> <img width="150" src="/images/logos/metpy-400x400.png" alt="MetPy Virtual Workshop" />
</div>
<p><b>This event's registration is now closed.</b></p>
<p>
Announcing the next offering of the <b>Introduction to MetPy virtual workshop</b>! This 4-hour interactive workshop is designed to introduce participants to the MetPy Python package and accessing data products made available by Unidata. If you or someone you know has an interest in getting started with MetPy workflows, this is an optimal place to start.</p><br><br>
<h3>Event Details</h3>
<ul>
<li><b>Event Date:</b> Tuesday, September 14</li>
<li><b>Event Time:</b> 12 PM - 4 PM MDT</li>
<li><b>Event Location:</b> Zoom</li>
</ul>
<br>
<h3>Course goals</h3>
<ul>
<li>Acquire current and recent meteorological data from a THREDDS data server</li>
<li>Prepare data for plotting on geographic axes</li>
<li>Create plots of meteorological data using MetPy tools</li>
</ul>
<br>
<h3>Intended audience</h3>
<ul>
<li>Individuals with a general knowledge of Python syntax</li>
<li>Individuals with a general knowledge of meteorological datasets</li>
<li>Individuals who are new to using MetPy, or those that would prefer a formal, synchronous experience for learning common MetPy workflows and best practices</li>
</ul>
<p class="highlight_box"><span style="color:#06778F; font-weight: bold;">NOTE: </span>This workshop assumes some knowledge of matplotlib, cartopy, and data access with xarray. Recommended supplemental materials will be provided upon enrollment for practicing those skills for those interested.
</p>
<p><br></p>
<h3>How to register</h3>
<p><b>This event's registration is now closed.</b><br>
<br></p>
https://www.unidata.ucar.edu/blogs/news/entry/ams-student-conference-python-workshopAMS Student Conference Python WorkshopUnidata News2020-12-30T10:03:01-07:002021-02-24T09:56:13-07:00<div class="img_l" style="width: 100px;"> <img width="100" src="/blog_content/images/logos/ams_2021.png" alt="AMS 2021 Annual Meeting" />
</div>
<p>
Students! Are you looking to make the transition to Python but unsure of where to start? Do
you already know Python but want to see atmospheric science specific applications?
Are you looking for data? If so, then please join us for a hands-on AMS Student
Conference Python Workshop where beginners and experts alike will learn skills that enhance
their ability to find, analyze, and explore data. All the workshop resources will
be in the cloud, so no specialized local software installations are necessary. All you need is a
laptop or tablet (a keyboard may be helpful) and a GitHub ID to participate.
</p>
<div class="img_l" style="width: 150px;"> <img width="150" src="/blog_content/images/logos/ams_2021.png" alt="AMS 2021 Annual Meeting" />
</div>
<p>
Students! Are you looking to make the transition to Python but unsure of where to start? Do
you already know Python but want to see atmospheric science specific applications?
Are you looking for data? If so, then please join us for a hands-on AMS Student
Conference Python Workshop where beginners and experts alike will learn skills that enhance
their ability to find, analyze, and explore data. All the workshop resources will
be in the cloud, so no specialized local software installations are necessary. All you need is a
laptop or tablet (a keyboard may be helpful) and a GitHub ID to participate.
</p>
<p><strong>Note:</strong> No prior experience with GitHub or Python is necessary to take part
in this workshop!</p>
<p>
To join us, begin by <a href="https://docs.google.com/forms/d/e/1FAIpQLSdJAC7Zowt_2-Eci83_HYyluHEZCG80RV2o_M1eSPHROcRt2A/viewform?usp=sf_link">registering</a> for the workshop.
We'll need your GitHub user ID in order to provision the cloud resources you'll use
for the workshop. If you don't have a GitHub ID yet, don't worry — they're
easy to create and the accounts are free. Just point your browser to:
<a href="https://github.com/join">https://github.com/join</a>.
</p>
<p>
<strong>Note:</strong> Please <a href="https://docs.google.com/forms/d/e/1FAIpQLSdJAC7Zowt_2-Eci83_HYyluHEZCG80RV2o_M1eSPHROcRt2A/viewform?usp=sf_link">register</a>
by <span class="highlight_muted">January 7, 2021</span>, so we can get everything set up.
</p>
<p>
Things will kick off with two orientation sessions during the AMS Student Conference:
</p>
<ol>
<li><a href="https://ams.confex.com/ams/101ANNUAL/meetingapp.cgi/Session/58381">Session A: Sunday, January 10, 2021, 1:00 PM - 1:30 PM EST</a></li>
<li><a href="https://ams.confex.com/ams/101ANNUAL/meetingapp.cgi/Session/58412">Session B: Sunday, January 10, 2021, 1:30 PM - 2:00 PM EST</a></li>
</ol>
<p>
(Pick one session to attend; they'll both present the same information.)
</p>
<p>
After the orientation, you'll choose a project to work on over the course of the
week. Remote follow-up help will be available — visit <a href="https://www.unidata.ucar.edu/events/2021AMS/">Unidata's Virtual AMS
Booth</a> to learn how to join our video networking “office hours.”
Workshop sessions and office hours will be staffed by an elite team of student
volunteers who have signed up to help show you how using Python can benefit your science.
</p>
<p>To learn more about the workshop, visit the <a href="https://unidata.github.io/pyaos-ams-2021/agenda.html">Unidata AMS
2021 Python Workshop</a> site.</p>
<p>We hope you'll join us for the workshop!</p>
https://www.unidata.ucar.edu/blogs/news/entry/nsf-earthcube-funds-project-pythiaNSF EarthCube funds Project PythiaUnidata News2020-10-15T12:19:54-06:002020-10-15T12:19:54-06:00<div class="img_l" style="width: 100px;">
<img width="100" src="/blog_content/images/logos/EarthCubeLogo2013_vert.png" alt="EarthCube Logo" />
</div>
<p>
Unidata developer Ryan May is a co-PI on a recently-awarded grant by the National
Science Foundation's EarthCube program. The grant, which brings together
collaborators from Unidata, NCAR's Computational & Information Systems
Laboratory (CISL), NCAR's Climate and Global Dynamics Laboratory (CGD), and the
University at Albany, SUNY, funds <em>Project Pythia: A Community Learning
Resource for Geoscientists</em>.
</p>
<p>
Project Pythia aims to provide web-accessible training to help current and future
geoscientists understand and use the ever-expanding volume of numerical scientific
data. The project will
leverage Jupyter Notebooks as the primary delivery mechanism for training examples,
curricula, and as an interactive computing platform. The content for Project Pythia
will be hosted on GitHub and maintained using an Open Development model that will
facilitate and encourage contributions from a broad user community, as well as help
ensure the long-term sustainability of the project.
</p>
<div class="img_l" style="width: 100px;">
<img width="100" src="/blog_content/images/logos/EarthCubeLogo2013_vert.png" alt="EarthCube Logo" />
</div>
<p>
Unidata developer Ryan May is a co-PI on a recently-awarded grant by the National
Science Foundation's EarthCube program. The grant, which brings together
collaborators from Unidata, NCAR's Computational & Information Systems
Laboratory (CISL), NCAR's Climate and Global Dynamics Laboratory (CGD), and the
University at Albany, SUNY, funds <em>Project Pythia: A Community Learning
Resource for Geoscientists</em>.
</p>
<p>
Project Pythia aims to provide web-accessible training to help current and future
geoscientists understand and use the ever-expanding volume of numerical scientific
data. The project will
leverage Jupyter Notebooks as the primary delivery mechanism for training examples,
curricula, and as an interactive computing platform. The content for Project Pythia
will be hosted on GitHub and maintained using an Open Development model that will
facilitate and encourage contributions from a broad user community, as well as help
ensure the long-term sustainability of the project.
</p>
<div class="img_r" style="width: 200px;">
<a class="lightbox" title="A diagram of Project Pythia, which will include a web portal for finding and viewing
content, downloading executable Python scripts or Jupyter Notebooks, or launching a
Notebook on a cloud resource. (NCAR CISL)" href="/blog_content/images/2020/20201015_Pythia_Diagram.png">
<img width="200" src="/blog_content/images/2020/20201015_Pythia_Diagram.png" alt="Description" />
</a>
<div class="caption">
Project Pythia<br>(click to enlarge)
</div>
<p></div></p>
<p>
May explains that Unidata's role in the project will be to contribute
meteorology-focused content (leveraging Unidata's <a href="https://www.unidata.ucar.edu/software/metpy/">MetPy</a> software package) and to
help with teaching workshops. “I see the project as building a
community-curated portal of resources (Jupyter notebooks) on using Python not just
for meteorology, but for the wider Climate and Atmospheric Science community,”
he says.
</p>
<p>
Additional details on Project Pythia are available from NCAR CISL:
<a href="https://www2.cisl.ucar.edu/news/cisl-cgd-unidata-and-suny-albany-win-earthcube-grants">CISL, CGD, Unidata and SUNY Albany win EarthCube grants</a>
</p>
https://www.unidata.ucar.edu/blogs/news/entry/unidata-science-gateway-jupyterhubs-areUnidata Science Gateway JupyterHubs are Helping U.S. Naval Academy Faculty Learn PythonUnidata News2020-02-13T10:15:52-07:002020-02-21T14:48:44-07:00<div class="img_l" style="width: 100px;"> <img width="100" src="/blog_content/images/logos/usna_logo.png"
alt="US Naval Academy" />
</div>
<p>
Faculty members in the U.S. Naval Academy (USNA) Oceanography Department are embarking
upon a new voyage: to learn Python. The <a href="https://www.usna.edu/Oceanography/">USNA Oceanography Department</a> has traditionally used
Matlab as the primary tool to analyze and visualize geosciences data. To build on that
coding success and align with the efforts of the geosciences community, at the
start of the spring 2020 semester, Associate Professor Bradford Barrett and Instructor
Alexander Davies organized a “Python Book Club” in which faculty members meet
once or twice
a month to collaboratively learn Python. Because USNA is a small undergraduate-only
institution with resource limitations and complex federal networking restrictions, Barrett
(USNA’s UCAR Representative) and Davies (currently serving on the Unidata Users Committee)
reached out to Unidata for help.
</p>
<p class="byline">
By Alexander Davies<br />
Oceanography Department<br />
United States Naval Academy
</p>
<div class="img_l" style="width: 100px;"> <img width="100" src="/blog_content/images/logos/usna_logo.png"
alt="US Naval Academy" />
</div>
<p>
Faculty members in the U.S. Naval Academy (USNA) Oceanography Department are embarking
upon a new voyage: to learn Python. The <a href="https://www.usna.edu/Oceanography/">USNA Oceanography Department</a> has traditionally used
Matlab as the primary tool to analyze and visualize geosciences data. To build on that
coding success and align with the efforts of the geosciences community, at the
start of the spring 2020 semester, Associate Professor Bradford Barrett and Instructor
Alexander Davies organized a “Python Book Club” in which faculty members meet
once or twice
a month to collaboratively learn Python. Because USNA is a small undergraduate-only
institution with resource limitations and complex federal networking restrictions, Barrett
(USNA’s UCAR Representative) and Davies (currently serving on the Unidata Users Committee)
reached out to Unidata for help.
</p>
<div class="img_r" style="width: 200px;"> <a class="lightbox" title="USNA Oceanography Department “Python Book Club” participants during the first meeting. Unidata developer Julien Chastang provided an initial JupyterHub orientation and coding demonstration via Google Hangouts."
href="/blog_content/images/2020/20200213_usna_01.png">
<img width="200" src="/blog_content/images/2020/20200213_usna_01.png" alt="Description" />
</a>
<div class="caption"> A meeting of the “Python Book Club”<br />(Click to
enlarge) </div>
</div>
<p>
Unidata software developer Julien Chastang set up common Python JupyterHub environments for
all “Python Book Club” participants on the <a
href="https://science-gateway.unidata.ucar.edu/">Unidata Science Gateway</a>. (The Science
Gateway is supported by the National Science Foundation’s <a
href="https://jetstream-cloud.org/">Jetstream</a> project and in collaboration with <a
href="https://www.xsede.org/">XSEDE</a> Extended Collaborative Support Services (<a
href="https://doi.org/10.1007/978-3-319-32243-8_1">ECSS</a>).) To kick off the first meeting
of the “Python Book Club,” Chastang provided a JupyterHub orientation and coding
demonstration via Google Hangouts. Few of the participating faculty members had prior
working experience with Python or cloud-based coding, and Unidata’s Science Gateway allows
them to interactively learn Python while also becoming more comfortable working in a cloud
environment.
</p>
<p>
The “book club” model of collaborative learning has proven to be successful.
Before arriving at a meeting, participants are asked to read assigned sections or chapters
of “<a href="https://sundogpublishingstore.myshopify.com/products/python-programming-and-visualization-for-scientists-alex-j-decaria">Python
Programming and Visualization for Scientists</a>,” by Alex DeCaria. During the
meetings, participants interactively work through the Python examples using JupyterHub on
the Unidata Science Gateway, ask questions, and experiment with different coding
approaches.
</p>
<p>
“This approach works because we have an informal group of peers, with similar coding
experience, and we are all working toward the same goal,” said Commander Allon Turek,
a rotational military instructor within the USNA Oceanography Department. “As an
established Matlab user, this model represents an accessible way to learn Python, and
JupyterHubs are an approachable platform.”
</p>
<p>
The USNA Oceanography Department has embraced data collection, analysis, and visualization
throughout the curriculum. While there are no formal programming courses offered, almost
every core course within the major has a lab component with programming outcomes, and the
programming skills being taught build upward throughout the major course sequence. Python
and JupyterHubs represent an exciting potential alternative to Matlab.
</p>
<p>
“At the Naval Academy we are always looking for ways to innovate within our
curriculum,” said Barrett. “In order to do that effectively and fulfill USNA’s
unique mission, we need to be on the cutting edge. We have noticed that the geosciences
community is increasingly moving toward Python-based coding. We need to equip our students
with those tools and Unidata has been invaluable in helping us achieve our goals.”
</p>
<p style="font-style: italic;">
Editor's note —<br />
The Unidata Program Center is committed to continuing to develop, test, and deploy
cloud-based resources for the university community. If you have a project you think
could benefit from Unidata Science Gateway resources, please contact us by e-mail at
<a href="mailto:support-gateway@unidata.ucar.edu">support-gateway@unidata.ucar.edu</a>.
You can also learn more about the Science Gateway's JupyterHub features in
<a href="https://www.unidata.ucar.edu/blogs/news/entry/a-jupyterhub-for-the-unidata">this
blog post</a>.
</p>
https://www.unidata.ucar.edu/blogs/news/entry/siphon-0-8-0-releasedSiphon 0.8.0 ReleasedRyan May2018-08-23T10:33:24-06:002018-08-23T10:34:48-06:00<p>siphon 0.8.0 has been released with a variety of new features, including a client for downloading National Data Buoy Center text data and support for basic HTTP authentication. For full release notes see the <a href="https://github.com/Unidata/siphon/releases/tag/v0.8.0">GitHub Release Page</a>.</p>
<p>siphon 0.8.0 has been released:</p>
<ul>
<li>Added client for National Data Buoy Center text data</li>
<li>Added <code>session_manager.set_session_options</code> to set options for Siphon-created HTTP sessions. This allows setting basic HTTP authentication.</li>
<li>Support downloading data for stations without an ICAO for Wyoming archive</li>
<li>Support downloading data for all stations from IEM upper air archive</li>
<li>Support opening using XArray in <code>TDSCatalog.remote_access()</code></li>
<li>Bug fixes for IGRA2</li>
</ul>
<h2>Contributors</h2>
<p>@DanielWatkins, @haileyajohnson, @jthielen, @swnesbitt, @lesserwhirls, @jrleeman, and @dopplershift contributed code to this release.</p>
<p>For full release notes see the <a href="https://github.com/Unidata/siphon/releases/tag/v0.8.0">GitHub Release Page</a>.</p>
<p>siphon packages are available for Conda on the <a href="https://anaconda.org/conda-forge/siphon">conda-forge channel</a>
and for pip from the <a href="https://pypi.python.org/pypi/siphon">Python Package Index</a>.</p>
<p>Let us know if you run into any problems, either at <a href="https://github.com/Unidata/siphon/issues">siphon issue tracker</a>,
using support-python@unidata.ucar.edu, or on
the <a href="https://www.unidata.ucar.edu/support/#mailinglists">python-users list</a>.
You can also ask questions using the "python-siphon" tag on <a href="https://stackoverflow.com/questions/tagged/python-siphon">Stack Overflow</a>.</p>
https://www.unidata.ucar.edu/blogs/news/entry/siphon-0-6-1-releasedSiphon 0.6.1 ReleasedRyan May2017-11-06T13:05:26-07:002018-06-13T09:41:14-06:00<p>Siphon 0.6.1 has been released. This includes bug fixes for 0.6.0, including fixing issues accessing development THREDDS servers as well as RAMADDA servers. For full release notes see the <a href="https://github.com/Unidata/siphon/releases/tag/v0.6.1">GitHub Release Page</a>.</p>
<p>Siphon 0.6.1 has been released, fixing a few bugs in the 0.6.0 release:</p>
<ul>
<li>Add upper air support to API documentation</li>
<li>Improve various string representations</li>
<li>Fix up catalog reading to work with RAMADDA servers</li>
<li>Fix issues accessing NCSS and catalog references on TDS v5 servers</li>
</ul>
<p>For full release notes see the <a href="https://github.com/Unidata/MetPy/releases/tag/v0.6.1">GitHub Release Page</a>.</p>
<p>siphon packages are available for Conda on the <a href="https://anaconda.org/conda-forge/siphon">conda-forge channel</a>
and for pip from the <a href="https://pypi.python.org/pypi/siphon">Python Package Index</a>.</p>
<p>Let us know if you run into any problems, either at <a href="https://github.com/Unidata/siphon/issues">siphon issue tracker</a>, or on
the <a href="https://www.unidata.ucar.edu/support/#mailinglists">python-users list</a>.</p>
https://www.unidata.ucar.edu/blogs/news/entry/siphon-0-6-0-releasedSiphon 0.6.0 ReleasedRyan May2017-09-18T14:59:39-06:002017-09-18T14:59:39-06:00<p>Siphon 0.6.0 has been released. This includes some bug fixes and improvements, including support for access to the University of Wyoming upper air data archive (ported from MetPy). For full release notes see the <a href="https://github.com/Unidata/siphon/releases/tag/v0.6.0">GitHub Release Page</a>.</p>
<p>Siphon 0.6.0 has been released. This includes a few scattered bug fixes and improvements:</p>
<ul>
<li>Incorporate support for accessing the University of Wyoming upper air archive, moved in from <a href="https://github.com/Unidata/MetPy">MetPy</a>. This reflects a broadening of Siphon's mission to facilitate remote access to many data services</li>
<li>Fix an issue with <code>access_urls</code> for TDS catalogs specifying a service contained within a compound service</li>
<li>Improvements to string representations and printing to help when working interactively (i.e. in the notebook) with CDM Remote <code>Dataset</code> (and other related objects) as well as <code>catalog.datasets</code></li>
</ul>
<p>For full release notes see the <a href="https://github.com/Unidata/MetPy/releases/tag/v0.6.0">GitHub Release Page</a>.</p>
<p>siphon packages are available for Conda on the <a href="https://anaconda.org/conda-forge/siphon">conda-forge channel</a>
and for pip from the <a href="https://pypi.python.org/pypi/siphon">Python Package Index</a>.</p>
<p>Let us know if you run into any problems, either at <a href="https://github.com/Unidata/siphon/issues">siphon issue tracker</a>, or on
the <a href="https://www.unidata.ucar.edu/support/#mailinglists">python-users list</a>.</p>
https://www.unidata.ucar.edu/blogs/news/entry/siphon-0-5Siphon 0.5.0Ryan May2017-08-03T15:48:05-06:002017-08-03T15:48:05-06:00<p>Siphon 0.5.0 has been released with API improvements as well as time-based filtering of datasets. Full releases notes are available on the <a href="https://github.com/Unidata/siphon/releases/tag/v0.5.0">GitHub Release page</a></p>
<p>Siphon packages are available for Conda on the <a href="https://anaconda.org/conda-forge/siphon">conda-forge</a> channel, and for pip from the <a href="https://pypi.python.org/pypi/siphon">Python Package Index</a>.</p>
<p>Let us know if you run into any problems, either at Siphon's <a href="https://github.com/Unidata/siphon">issue tracker</a>, or on the Unidata <a href="https://www.unidata.ucar.edu/support/#mailinglists">python-users</a> list.</p>
<p>Siphon 0.5.0 has been released with a few improvements and features:</p>
<ul>
<li>The datasets and catalog references can now be grabbed from their collections by position (index) (as well as by name).</li>
<li>Collections of datasets and catalog references now have helper functions that allow extracting a time range or item closest to a time, assuming the entries have appropriately formatted times in the names.</li>
<li>Datasets gained functions that simplify setting up access over various TDS services</li>
<li>A catalog with a latest dataset now has a <code>latest</code> attribute that points directly to this dataset</li>
</ul>
<p>Full releases notes are available on the <a href="https://github.com/Unidata/siphon/releases/tag/v0.5.0">GitHub Release page</a></p>
<p>Siphon packages are available for Conda on the <a href="https://anaconda.org/conda-forge/siphon">conda-forge</a> channel, and for pip from the <a href="https://pypi.python.org/pypi/siphon">Python Package Index</a>.</p>
<p>Let us know if you run into any problems, either at Siphon's <a href="https://github.com/Unidata/siphon">issue tracker</a>, or on the Unidata <a href="https://www.unidata.ucar.edu/support/#mailinglists">python-users</a> list.</p>
<h2>Specific examples of new APIs</h2>
<p>Two of the main improvements to the Siphon API are access to the collection of
datasets directly by numeric index and simplified methods for using different
data access methods. So before in Siphon one might do:</p>
<pre><code class="language-python">cat = TDSCatalog('http://thredds.ucar.edu/thredds/catalog/grib/'
'NCEP/GFS/Global_0p25deg/catalog.xml')
ds = list(cat.datasets.values())[0]
ncss = NCSS(ds.access_urls['NetcdfSubset'])</code>
</pre>
<p>This becomes:</p>
<pre><code class="language-python">cat = TDSCatalog('http://thredds.ucar.edu/thredds/catalog/grib/'
'NCEP/GFS/Global_0p25deg/catalog.xml')
ds = cat.datasets[0]
ncss = ds.subset()</code>
</pre>
<p>Similarly, for OPeNDAP or CDMRemote access, you now can do:</p>
<pre><code class="language-python">nc = ds.remote_access()</code>
</pre>
<p>where <code>nc</code> is a netCDF4-python <code>Dataset</code> object (or similar for CDMRemote).
By default this uses CDMRemote where available (since it's built into Siphon),
but will fall-back to OPeNDAP (or can be manually selected).</p>
<p>There is also support for getting a file-like object for accessing the raw
data using HTTP, or just downloading the file locally:</p>
<pre><code class="language-python">fobj = ds.remote_open()
# Download locally
ds.download('local/file/path')</code>
</pre>
<p>Siphon has also simplified access to the automatically resolved latest dataset
identified on THREDDS servers. Previously, this involved manually finding the
latest within the collection of datasets, or using the helper function as:</p>
<pre><code class="language-python">latest_opendap = get_latest_access_url('http://thredds.ucar.edu/thredds/catalog/grib/'
'NCEP/GFS/Global_0p25deg/catalog.xml', 'OPENDAP')
nc = Dataset(latest_opendap)</code>
</pre>
<p>This now becomes:</p>
<pre><code class="language-python">cat = TDSCatalog('http://thredds.ucar.edu/thredds/catalog/grib/'
'NCEP/GFS/Global_0p25deg/catalog.xml')
nc = cat.latest.remote_access()</code>
</pre>
<p>Siphon has also gained the ability to filter particular datasets from those
in the catalog using dates and times. This relies on extracting times from the
names using an assumed time format (defaults to YYYYMMDD_HHMM).
So now users can do:</p>
<pre><code class="language-python">cat = TDSCatalog('http://thredds.ucar.edu/thredds/catalog/grib/'
'NCEP/GFS/Global_0p25deg/catalog.xml')
# Find the run closest to 6 hours ago
time = datetime.utcnow() - timedelta(hours=6)
ds = cat.filter_time_nearest(time)
# Find all runs from the last day
end = datetime.utcnow()
start = end - timedelta(days=1)
datasets = cat.filter_time_range(start, end)</code>
</pre>
<p>It is possible to pass a custom regular expression to support other time formats.</p>
https://www.unidata.ucar.edu/blogs/news/entry/get-involved-in-python-developmentGet Involved in Python Development for the Geosciences!Unidata News2017-06-07T11:43:17-06:002017-06-07T11:43:17-06:00<p>
You may have noticed that Unidata Program Center developer Ryan May spends
a bit of his time evangelizing the use of the Python language in the
atmospheric sciences. This week he appears over on Johnny Lin's <a href="http://pyaos.johnny-lin.com/">PyAOS</a>
(Python for the Atmospheric and Oceanic Sciences) blog, weighing in on
the future of AOS Python.
</p>
<p>
Ryan's post, titled “<a href="http://pyaos.johnny-lin.com/?p=1560">What's
needed for the Future of AOS Python? Get Involved!</a>,” lays out the
case for widespread community involvement in AOS Python projects.
</p>
<p>
You may have noticed that Unidata Program Center developer Ryan May spends
a bit of his time evangelizing the use of the Python language in the
atmospheric sciences. This week he appears over on Johnny Lin's <a href="http://pyaos.johnny-lin.com/">PyAOS</a>
(Python for the Atmospheric and Oceanic Sciences) blog, weighing in on
the future of AOS Python.
</p>
<p>
Ryan's post, titled “<a href="http://pyaos.johnny-lin.com/?p=1560">What's
needed for the Future of AOS Python? Get Involved!</a>,” lays out the
case for widespread community involvement in AOS Python projects:
</p>
<div class="pullquote">
By contributing to the projects you use, you can help
sustain their success. Selfishly, that means that you have a
say in their direction, ensuring that the project helps
solve your particular problems. In the big picture, though,
a vibrant, active community is the lifeblood of a project,
helping sustain it.
</div>
<p>
Ryan also points out that participation takes many forms, and that one
need not consider oneself an expert coder (or a coder at all!) to make
valuable contributions to a software project.
</p>
<p>
Head on over and <a href="http://pyaos.johnny-lin.com/?p=1560">read Ryan's full post</a> — with luck it will inspire
you to find ways that you can pitch in and help build a strong open source
software community.
</p>
https://www.unidata.ucar.edu/blogs/news/entry/siphon-0-4-1-releasedSiphon 0.4.1 releasedRyan May2017-04-03T15:25:46-06:002017-04-04T09:16:13-06:00<p>Siphon 0.4.1 has been released with fixes for some minor issues in 0.4.0, including various fixes for catalog parsing, as well as updated documentation. Full releases notes are available on the <a href="https://github.com/Unidata/siphon/releases/tag/v0.4.1">GitHub Release page</a></p>
<p>Siphon packages are available for Conda on the <a href="https://anaconda.org/conda-forge/siphon">conda-forge</a> channel, and for pip from the <a href="https://pypi.python.org/pypi/siphon">Python Package Index</a>.</p>
<p>Let us know if you run into any problems, either at Siphon's <a href="https://github.com/Unidata/siphon">issue tracker</a>, or on the Unidata <a href="https://www.unidata.ucar.edu/support/#mailinglists">python-users</a> list.</p>
<p>Siphon 0.4.1 has been released with fixes for some minor issues in 0.4.0:</p>
<ul>
<li>Make catalog parsing more permissive</li>
<li>Handle catalogs from non-standard server context</li>
<li>Handle catalogs from Hyrax servers</li>
<li>Documentation now hosted at https://unidata.github.io/siphon</li>
<li>Examples stored in repository as scripts, but can be downloaded from built examples as notebooks (thanks to sphinx-gallery)
Full releases notes are available on the <a href="https://github.com/Unidata/siphon/releases/tag/v0.4.1">GitHub Release page</a></li>
</ul>
<p>Siphon packages are available for Conda on the <a href="https://anaconda.org/conda-forge/siphon">conda-forge</a> channel, and for pip from the <a href="https://pypi.python.org/pypi/siphon">Python Package Index</a>.</p>
<p>Let us know if you run into any problems, either at Siphon's <a href="https://github.com/Unidata/siphon">issue tracker</a>, or on the Unidata <a href="https://www.unidata.ucar.edu/support/#mailinglists">python-users</a> list.</p>