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    Alan D. Snow
    @snowman2

    @snowman2 one more: Ever experienced a bug in rasterio/GDAL where it drops some of the projection parameters? I have a WKT rasterio CRS object that has the Latitude of natural origin and Longitude of natural origin for a laea projection, but after saving to a geotiff with rasterio it has those parameters set to 0

    Huh, I haven't seen that. But, definitely something to be concerned about.

    Alan D. Snow
    @snowman2

    PROJ/pyproj have no way of guessing the datum from a PROJ string unless it is explicitly set.

    I believe PROJ has assumed defaults. GRS80 is a common one IIRC. In the docs I see it quite a bit example aea.

    Looks like that was ellps not datum. Not sure about the internals on how PROJ matches the datum.

    Juho Häme
    @JuhoHame_twitter
    Hi, I'm looking to change the datum transformation for a CRS. Can I do this by poking around in proj.db?
    Juho Häme
    @JuhoHame_twitter
    Looks like the answer is here! https://gis.stackexchange.com/questions/179790/lookup-projection-name-from-epsg-with-pyproj/179807#179807
    Alan D. Snow
    @snowman2
    That answer is out of date. The EPSG file does not exist in newer versions.
    I would recommend looking into either PROJ pyproj4/pyproj#389
    Or, looking into modifying the SQL used to create the PROJ.db in the PROJ code. Or, looking into a custom proj pipeline.
    Juho Häme
    @JuhoHame_twitter
    umm, pyproj 2.4 seems to be using that /usr/share/proj/epsg file?
    Juho Häme
    @JuhoHame_twitter
    (at least it fixed my issue, added alternative datum transformation for 3844)
    Alan D. Snow
    @snowman2
    It still works, you are correct, but it is mostly because the old functionality hasn't been removed. I have seen inconsistencies with it and wouldn't recommend using it.
    Walter Lorenzetti
    @wlorenzetti
    Hi all, I'm newone, nice to meet you!
    I've a timing calculation problen with pyproj
    I use pyproj to project official Italy cadastrian data...
    by on a customer VM istallation I notice a 40 times lower then on my laptop
    this is my test code: 
    from pyproj import Proj, transform
import time

start = time.time()
outProj = Proj(init='epsg:3003')
inProj = Proj("+proj=cass +lat_0=43.318293 +lon_0=11.332212 +x_0=0.000000000000000 +y_0=0.000000000000000 +datum=WGS84 +units=m +no_defs")
x = 61759.831
y = -41125.585
ret = transform(inProj, outProj, y, x)
stop = time.time()
print "TIME: {}".format(stop - start)
print ret
    on my laptop I obtain this: 
    TIME: 0.00243186950684
(1646302.7175562638, 4859396.617420217)
    on my customer VM server this:
    Walter Lorenzetti
    @wlorenzetti
    TIME: 0.0984871387482
(1646302.7175560538, 4859396.61741957)
    any idea about this lower behaviour?
    thanks in advance and good weekend
    Alan D. Snow
    @snowman2
    How did you install each one? What version of pyproj/PROJ are you using?
    Walter Lorenzetti
    @wlorenzetti
    Hi Alan, I've different version on my laptop and on remote VM: laptop Ubuntu 16.04 PROJ: 4.9.2 pyproj: 1.9.5.1 installe into virtualenv by pip ; Vm remote ubuntu 18.04 PROJ:4.9.3 pyproj: 2.2.2 installed into virtualenv by pip.
    Walter Lorenzetti
    @wlorenzetti
    Hi Alan, another step for understanding the possibile problem. I installed on VM remote machine pyproj 1.9.1.5 e remove 2.2.2 version and now the reprojection are more kindly :) : 
    TIME: 0.000527143478394
(1646302.7175562638, 4859396.617420217)
    I hope this can help..
    Walter Lorenzetti
    @wlorenzetti
    i continue analisys:
    on my laptop

    v 1.9.6:

    TIME: 0.000527143478394
(1646302.7175562638, 4859396.617420217)

    v 2.0.0

    TIME: 0.0132768154144
(1646279.7128513593, 4859469.284666889)

    v 2.0.1

    TIME: 0.0472819805145
(1646279.7128513593, 4859469.284666889)

    v 2.1.0

    TIME: 0.0480349063873
(1646279.7128513593, 4859469.284666889)

    v 2.1.1

    TIME: 0.0479390621185
(1646279.7128513593, 4859469.284666889)

    v 2.1.2

    TIME: 0.142739057541
(1646302.7175560538, 4859396.61741957)

    v 2.1.3

    TIME: 0.149616956711
(1646302.7175560538, 4859396.61741957)

    v 2.2.0

    TIME: 0.0712070465088
(1646302.7175560538, 4859396.61741957)

    v 2.2.1

    TIME: 0.0708930492401
(1646302.7175560538, 4859396.61741957)

    v 2.2.2

    TIME: 0.0708050727844
(1646302.7175560538, 4859396.61741957)
    Schermata del 2019-12-02 11-53-50.png
    Alan D. Snow
    @snowman2
    That makes sense. There is a little more overhead in the pyproj 2+ to create the Proj object due to the changes in PROJ 6+.
    Walter Lorenzetti
    @wlorenzetti
    So with PROJ4 is better stay lower then pyproj 2
    David Hoese
    @djhoese
    @snowman2 Am I correct that in pyproj 2.4.2 the transform always returns float64s?
    Nevermind, this has likely been this way for a while
    Alan D. Snow
    @snowman2
    So with PROJ4 is better stay lower then pyproj 2
    It depends on your use case. Personally I would recommend pyproj 2+.
    Walter Lorenzetti
    @wlorenzetti
    Thnks @snowman2 !
    Joris Van den Bossche
    @jorisvandenbossche
    @wlorenzetti the difference in speed between pyproj 1.9 and pyproj 2 is only for single transformations
    if you do repeated transformations using the same inProj and outProj, you can use the Transformer object in pyproj 2+, which will be much faster
    Walter Lorenzetti
    @wlorenzetti
    Thanks @jorisvandenbossche I'll try!
    Joris Van den Bossche
    @jorisvandenbossche
    With the transform function, each time you call transform(inProj, outProj, y, x), pyproj (PROJ) needs to find the best transformation between inProj and outProj, which makes it slower. But the Transform object can remember that
    See https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1
    Walter Lorenzetti
    @wlorenzetti
    Good it's clear
    Walter Lorenzetti
    @wlorenzetti
    I just try with pyproj 2.2.2 with Transformer object: 
    # https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1

from pyproj import Transformer
import time

start = time.time()
x = 61759.831
y = -41125.585
transformer = Transformer.from_crs("+proj=cass +lat_0=43.318293 +lon_0=11.332212 +x_0=0.000000000000000 +y_0=0.000000000000000 +datum=WGS84 +units=m +no_defs", "epsg:3003")
ret = transformer.transform(y, x)
stop = time.time()
print "TIME: {}".format(stop - start)
print ret
    but timing in not good again.. 
    TIME: 0.0580408573151
(1646302.7175560538, 4859396.61741957)
    I' tryee inside a 20 time cycle to test memory effect: 
    TIME: 0.0537190437317
(1646302.7175560538, 4859396.61741957)
TIME: 0.0591440200806
(1646302.7175560538, 4859396.61741957)
TIME: 0.0580699443817
(1646302.7175560538, 4859396.61741957)
TIME: 0.0595941543579
(1646302.7175560538, 4859396.61741957)
TIME: 0.0600090026855
(1646302.7175560538, 4859396.61741957)
TIME: 0.059278011322
(1646302.7175560538, 4859396.61741957)
TIME: 0.0588028430939
(1646302.7175560538, 4859396.61741957)
TIME: 0.0584590435028
(1646302.7175560538, 4859396.61741957)
TIME: 0.0585939884186
(1646302.7175560538, 4859396.61741957)
TIME: 0.0572869777679
(1646302.7175560538, 4859396.61741957)
TIME: 0.0574839115143
(1646302.7175560538, 4859396.61741957)
TIME: 0.0569059848785
(1646302.7175560538, 4859396.61741957)
TIME: 0.0589108467102
(1646302.7175560538, 4859396.61741957)
TIME: 0.0600910186768
(1646302.7175560538, 4859396.61741957)
TIME: 0.0592269897461
(1646302.7175560538, 4859396.61741957)
TIME: 0.058445930481
(1646302.7175560538, 4859396.61741957)
TIME: 0.0585761070251
(1646302.7175560538, 4859396.61741957)
TIME: 0.0573010444641
(1646302.7175560538, 4859396.61741957)
TIME: 0.067663192749
(1646302.7175560538, 4859396.61741957)
TIME: 0.0576071739197
(1646302.7175560538, 4859396.61741957)
    But I can see a better timing...