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.gitignore
View file @ 7615da40
*~
*.pyc
__pycache__
*.py[cod]
__pycache__/
dist/
# Ignore data files
*.csv
README.md
View file @ 7615da40
......@@ -13,6 +13,84 @@ Packaging informations :
- https://packaging.python.org/en/latest/tutorials/packaging-projects/
- https://choosealicense.com/
## Build and install the package
```shell
$ flit build
$ pip install dist/import_resources_example-0.0.1-py3-none-any.whl
```
WARNING : The package is installed in the virtual environment, so the data
files must be placed there which is not a very pleasant location.
```shell
$ tree .venv/lib/python3.10/site-packages/import_resources_example
├── data
│ └── __init__.py
├── get_oms_data.py
├── get_population_info.py
└── __init__.py
```
When installing the package in development mode with `pip install -e .`, the
data folder is in the clone repository.
## Usage
Install the package and try to execute the functions.
```ipython
In [1]: from import_resources_example import get_population_info
In [2]: get_population_info.extract_population_general_info()
{'AUKUS': {'Time': '1950', 'PopTotal': '206513.782', 'PopDensity': '12.096'},
'African Group': {'Time': '1950',
'PopTotal': '227261.208',
'PopDensity': '7.761'},
'African Union': {'Time': '1950',
'PopTotal': '227274.19',
'PopDensity': '7.692'},
In [3]: from import_resources_example import get_oms_data
In [4]: get_oms_data.get_oms_data()
Out[4]:
[{'TrialID': 'NCT00173563',
'Public-title': 'Induction of Cytokines in Human Monocytes by SARS-CoV in Adults and Children',
'Date-registration': '12/09/2005',
'Source-Register': 'ClinicalTrials.gov',
'Recruitment-Status': 'Recruiting',
'Study type': 'Observational'},
{'TrialID': 'NCT00523276',
'Public-title': 'SARS Survivor Evaluations',
'Date-registration': '30/08/2007',
'Source-Register': 'ClinicalTrials.gov',
'Recruitment-Status': 'Not recruiting',
'Study type': 'Observational'},
```
## Remark
The data files do not need to be packaged, just place them where the data
folder is installed.
WARNING : you have to manually remove the data files copied in the data folder
installed in `site-packages` with pip if you want to remove the package.
```shell
$ pip uninstall import_resources_example
Found existing installation: import_resources_example 0.0.1
Uninstalling import_resources_example-0.0.1:
Would remove:
/home/fconil/Progs/python/imports/resources/.venv/lib/python3.10/site-packages/import_resources_example-0.0.1.dist-info/*
/home/fconil/Progs/python/imports/resources/.venv/lib/python3.10/site-packages/import_resources_example/*
Would not remove (might be manually added):
/home/fconil/Progs/python/imports/resources/.venv/lib/python3.10/site-packages/import_resources_example/data/COVID19-web.27-07-2022.csv
/home/fconil/Progs/python/imports/resources/.venv/lib/python3.10/site-packages/import_resources_example/data/WPP2022_TotalPopulationBySex.csv
Proceed (Y/n)? y
Successfully uninstalled import_resources_example-0.0.1
```
## Troubleshooting
If we have untracked data files in the package tree, flist refuses to build the
......@@ -24,12 +102,13 @@ Fetching list of valid trove classifiers
Untracked or deleted files in the source directory. Commit, undo or ignore these files in your VCS.
```
If we add a line to ignore, e.g. all csv files, in `.gitignore` we get a warning when we want to add one.
If we add a line to ignore, e.g. all csv files, in `.gitignore` we get a
warning when we want to add one.
```shell
$ git add src/import-resources-example/data/WPP2022_TotalPopulationBySex.csv
$ git add WPP2022_TotalPopulationBySex.csv
Les chemins suivants sont ignorés par un de vos fichiers .gitignore :
src/import-resources-example/data/WPP2022_TotalPopulationBySex.csv
src/import_resources_example/data/WPP2022_TotalPopulationBySex.csv
astuce: Utilisez -f si vous voulez vraiment les ajouter.
astuce: Éliminez ce message en lançant
astuce: "git config advice.addIgnoredFile false"
......@@ -37,3 +116,7 @@ astuce: "git config advice.addIgnoredFile false"
As we can append the data files with `-f`, I will ignore the data file in `.gitignore`.
```shell
$ git add -f WPP2022_TotalPopulationBySex.csv
$
```
src/import_resources_example/data/WPP2022_TotalPopulationBySex.csv 0 → 100644
View file @ 7615da40
SortOrder,LocID,Notes,ISO3_code,ISO2_code,SDMX_code,LocTypeID,LocTypeName,ParentID,Location,VarID,Variant,Time,MidPeriod,PopMale,PopFemale,PopTotal,PopDensity
,98502,,,,,,,,ESCWA: Gulf Cooperation Council (GCC),2,Medium,2076,2076.5,44194.054,37123.151,81317.205,31.76
,98300,,,,,,,,ECLAC: United Nations Economic Commission for Latin America and the Caribbean - All countries,6,Instant replacement,2064,2064.5,410753.295,421804.662,832557.957,41.107
161.0,208,16,DNK,DK,208.0,4.0,Country/Area,924.0,Denmark,2,Medium,2057,2057.5,3273.006,3263.523,6536.529,154.185
31.0,262,,DJI,DJ,262.0,4.0,Country/Area,910.0,Djibouti,2,Medium,1998,1998.5,345.318,349.602,694.92,29.979
4.0,1833,,,,747.0,12.0,SDG region,1828.0,Northern Africa and Western Asia,4,Low,2052,2052.5,363538.057,353912.941,717450.998,57.495
141.0,634,,QAT,QA,634.0,4.0,Country/Area,922.0,Qatar,2,Medium,1955,1955.5,14.313,14.354,28.668,2.474
91.0,935,,,,142.0,2.0,Geographic region,1840.0,Asia,3,High,2074,2074.5,3173574.797,3125127.443,6298702.24,200.829
243.0,32,,ARG,AR,32.0,4.0,Country/Area,931.0,Argentina,10,Momentum,2062,2062.5,26136.267,26897.895,53034.162,18.996
122.0,458,9,MYS,MY,458.0,4.0,Country/Area,920.0,Malaysia,7,Zero migration,2098,2098.5,17411.11,17090.822,34501.933,105.013
159.0,804,15,UKR,UA,804.0,4.0,Country/Area,923.0,Ukraine,7,Zero migration,2065,2065.5,14677.116,16269.552,30946.668,53.419
,98423,,,,,,,,ESCAP: Europe (Europe),3,High,2098,2098.5,332181.425,332545.406,664726.831,116.291
42.0,690,,SYC,SC,690.0,4.0,Country/Area,910.0,Seychelles,207,Lower 95 PI,2090,2090.5,37.245,42.183,79.226,173.361
224.0,652,2,BLM,BL,652.0,4.0,Country/Area,915.0,Saint Barthélemy,3,High,2045,2045.5,5.729,5.43,11.159,507.25
137.0,400,,JOR,JO,400.0,4.0,Country/Area,922.0,Jordan,4,Low,2049,2049.5,6963.959,6707.307,13671.266,153.966
,1552,,,,,,,,New EU member states (joined since 2004),6,Instant replacement,2051,2051.5,50247.115,51653.331,101900.447,91.363
147.0,887,,YEM,YE,887.0,4.0,Country/Area,922.0,Yemen,10,Momentum,2058,2058.5,23743.993,24411.127,48155.12,91.208
263.0,909,,,,9.0,2.0,Geographic region,1840.0,Oceania,5,Constant fertility,2070,2070.5,34681.412,34563.132,69244.545,8.157
,1825,,,,,,,,Eastern European Group,2,Medium,2027,2027.5,156328.218,174547.67,330875.888,17.711
,98419,,,,,,,,ESCAP: South-East Asia (SEA),7,Zero migration,2085,2085.5,392638.164,396910.216,789548.38,177.418
190.0,688,24,SRB,RS,688.0,4.0,Country/Area,925.0,Serbia,4,Low,2046,2046.5,2725.575,2901.06,5626.636,73.325
210.0,535,28,BES,BQ,535.0,4.0,Country/Area,915.0,"Bonaire, Sint Eustatius and Saba",5,Constant fertility,2088,2088.5,14.258,14.367,28.624,87.268
,1586,,,,,,,,UNICEF Programme Regions: East Asia and Pacific (EAPRO),7,Zero migration,2041,2041.5,1104290.247,1089770.351,2194060.598,135.103
,1551,,,,,,,,European Union (EU: 27),10,Momentum,2083,2083.5,189587.652,191680.928,381268.579,95.176
222.0,500,19,MSR,MS,500.0,4.0,Country/Area,915.0,Montserrat,6,Instant replacement,2083,2083.5,2.03,1.999,4.029,39.121
,98402,,,,,,,,ESCAP: ADB Group A (ADB_DMC_A),3,High,2031,2031.5,97091.689,98591.252,195682.941,85.776
108.0,4,,AFG,AF,4.0,4.0,Country/Area,5501.0,Afghanistan,207,Lower 95 PI,2031,2031.5,24007.292,23700.67,47719.929,73.495
86.0,566,,NGA,NG,566.0,4.0,Country/Area,914.0,Nigeria,207,Lower 95 PI,2073,2073.5,152268.43,153486.602,307057.44,337.14
231.0,796,19,TCA,TC,796.0,4.0,Country/Area,915.0,Turks and Caicos Islands,6,Instant replacement,2027,2027.5,24.236,24.084,48.321,50.864
,2074,,,,,,,,Commonwealth of Nations,9,No change,2078,2078.5,2388782.484,2385340.109,4774122.593,159.201
34.0,404,,KEN,KE,404.0,4.0,Country/Area,910.0,Kenya,202,Median PI,2075,2075.5,51023.02,53683.41,104706.431,180.302
62.0,434,,LBY,LY,434.0,4.0,Country/Area,912.0,Libya,204,Lower 80 PI,2078,2078.5,3702.868,3789.578,7488.931,4.468
,98437,,,,,,,,ESCAP: WB Upper Middle Income Economies,2,Medium,1977,1977.5,606193.042,599786.999,1205980.04,38.96
173.0,752,,SWE,SE,752.0,4.0,Country/Area,924.0,Sweden,206,Upper 95 PI,2026,2026.5,5482.407,5384.788,10865.053,26.673
251.0,328,,GUY,GY,328.0,4.0,Country/Area,931.0,Guyana,203,Upper 80 PI,2078,2078.5,496.214,464.812,961.478,4.884
154.0,616,,POL,PL,616.0,4.0,Country/Area,923.0,Poland,203,Upper 80 PI,2033,2033.5,18856.896,20060.879,38909.814,127.076
43.0,706,,SOM,SO,706.0,4.0,Country/Area,910.0,Somalia,3,High,2092,2092.5,40760.715,41531.734,82292.45,131.177
24.0,1500,j,,,911.0,13.0,Income group,1802.0,Low-income countries,202,Median PI,2086,2086.5,1031237.413,1062323.155,2093560.568,142.536
,1525,,,,,,,,BRIC,7,Zero migration,2061,2061.5,1654534.73,1623515.116,3278049.846,87.867
199.0,442,,LUX,LU,442.0,4.0,Country/Area,926.0,Luxembourg,207,Lower 95 PI,2071,2071.5,359.048,364.37,724.277,279.644
167.0,372,,IRL,IE,372.0,4.0,Country/Area,924.0,Ireland,202,Median PI,2075,2075.5,2888.068,2876.276,5764.344,84.315
141.0,634,,QAT,QA,634.0,4.0,Country/Area,922.0,Qatar,3,High,2089,2089.5,3004.338,2105.838,5110.176,441.065
,2093,,,,,,,,"SIDS Atlantic, Indian Ocean and South China Sea (AIS)",16,Instant replacement zero migration,2067,2067.5,10262.487,10080.279,20342.765,47.33
,2037,,,,,,,,UNICEF Regions: Middle East and North Africa,16,Instant replacement zero migration,2071,2071.5,353619.855,349167.62,702787.475,63.219
82.0,430,,LBR,LR,430.0,4.0,Country/Area,914.0,Liberia,3,High,2099,2099.5,9276.71,9480.467,18757.178,194.738
8.0,1835,,,,543.0,12.0,SDG region,1828.0,Oceania (excluding Australia and New Zealand),204,Lower 80 PI,2093,2093.5,9088.428,9396.241,18483.177,34.132
54.0,178,,COG,CG,178.0,4.0,Country/Area,911.0,Congo,206,Upper 95 PI,2067,2067.5,8927.899,8966.828,17912.978,52.454
7.0,1830,,,,419.0,12.0,SDG region,1828.0,Latin America and the Caribbean,3,High,2092,2092.5,470663.81,473942.742,944606.552,46.611
203.0,904,,,,419.0,2.0,Geographic region,1840.0,Latin America and the Caribbean,204,Lower 80 PI,2068,2068.5,345269.488,358746.387,704904.202,34.783
218.0,312,2,GLP,GP,312.0,4.0,Country/Area,915.0,Guadeloupe,9,No change,2090,2090.5,157.939,179.046,336.985,206.993
187.0,807,,MKD,MK,807.0,4.0,Country/Area,925.0,North Macedonia,203,Upper 80 PI,2026,2026.5,1044.211,1050.623,2094.699,84.081
157.0,643,,RUS,RU,643.0,4.0,Country/Area,923.0,Russian Federation,202,Median PI,2095,2095.5,55612.811,57817.179,113429.989,6.927
41.0,646,,RWA,RW,646.0,4.0,Country/Area,910.0,Rwanda,2,Medium,2014,2014.5,5524.552,5843.9,11368.451,469.577
228.0,670,,VCT,VC,670.0,4.0,Country/Area,915.0,Saint Vincent and the Grenadines,8,Constant mortality,2036,2036.5,49.465,49.824,99.288,254.586
,1613,,,,,,,,UNFPA: Latin America and the Caribbean (LAC),10,Momentum,2067,2067.5,379130.899,396725.835,775856.735,38.486
59.0,912,,,,15.0,3.0,Subregion,903.0,Northern Africa,6,Instant replacement,2076,2076.5,189327.344,190492.628,379819.971,49.416
,1615,,,,,,,,Non-Self-Governing Territories,9,No change,2100,2100.5,1219.422,1164.799,2384.221,7.863
158.0,703,,SVK,SK,703.0,4.0,Country/Area,923.0,Slovakia,207,Lower 95 PI,2089,2089.5,1571.463,1620.62,3194.051,65.141
276.0,584,,MHL,MH,584.0,4.0,Country/Area,954.0,Marshall Islands,202,Median PI,2089,2089.5,26.09,26.577,52.667,292.594
267.0,928,,,,54.0,3.0,Subregion,909.0,Melanesia,9,No change,2038,2038.5,8257.058,8006.076,16263.135,30.662
222.0,500,19,MSR,MS,500.0,4.0,Country/Area,915.0,Montserrat,9,No change,2079,2079.5,1.341,1.36,2.701,26.223
68.0,72,,BWA,BW,72.0,4.0,Country/Area,913.0,Botswana,4,Low,2100,2100.5,1335.111,1428.685,2763.796,4.877
,2081,,,,,,,,African Union: Eastern Africa,5,Constant fertility,2040,2040.5,332750.437,334815.745,667566.182,104.674
102.0,158,8,TWN,TW,158.0,4.0,Country/Area,906.0,"China, Taiwan Province of China",203,Upper 80 PI,2038,2038.5,11934.576,12387.311,24310.548,686.545
13.0,902,e,,,515.0,5.0,Development group,1803.0,Less developed regions,203,Upper 80 PI,2088,2088.5,5070703.979,5101211.005,10175587.215,125.092
279.0,580,29,MNP,MP,580.0,4.0,Country/Area,954.0,Northern Mariana Islands,204,Lower 80 PI,2076,2076.5,20.932,18.858,39.735,86.947
59.0,912,,,,15.0,3.0,Subregion,903.0,Northern Africa,4,Low,2086,2086.5,175594.656,178390.625,353985.281,46.055
125.0,702,,SGP,SG,702.0,4.0,Country/Area,920.0,Singapore,8,Constant mortality,2083,2083.5,2523.307,2577.544,5100.851,7468.303
,1540,,,,,,,,Economic Community of West African States (ECOWAS),8,Constant mortality,2060,2060.5,418755.731,412672.068,831427.799,165.211
174.0,826,21,GBR,GB,826.0,4.0,Country/Area,924.0,United Kingdom,6,Instant replacement,2062,2062.5,40694.484,40342.699,81037.183,333.842
,1559,,,,,,,,"League of Arab States (LAS, informal name: Arab League)",16,Instant replacement zero migration,2047,2047.5,308857.233,297599.183,606456.416,46.959
,98102,,,,,,,,ECA: Eastern Africa,7,Zero migration,2050,2050.5,341132.008,345032.436,686164.443,147.994
13.0,902,e,,,515.0,5.0,Development group,1803.0,Less developed regions,5,Constant fertility,2078,2078.5,6246811.62,6237480.957,12484292.577,153.473
33.0,231,,ETH,ET,231.0,4.0,Country/Area,910.0,Ethiopia,2,Medium,2008,2008.5,42458.192,41898.913,84357.105,84.357
276.0,584,,MHL,MH,584.0,4.0,Country/Area,954.0,Marshall Islands,6,Instant replacement,2064,2064.5,26.346,26.198,52.544,291.911
,1858,,,,,,,,CANZUK,10,Momentum,2058,2058.5,70351.371,70718.313,141069.683,8.162
64.0,729,,SDN,SD,729.0,4.0,Country/Area,912.0,Sudan,8,Constant mortality,2055,2055.5,44588.156,44932.196,89520.352,50.718
28.0,910,,,,14.0,3.0,Subregion,903.0,Eastern Africa,206,Upper 95 PI,2041,2041.5,378062.748,383109.479,761305.052,114.439
,98433,,,,,,,,ESCAP: ENEA including Russian Fed (ENEA_RUS),6,Instant replacement,2043,2043.5,934969.218,926485.98,1861455.198,66.172
258.0,60,19,BMU,BM,60.0,4.0,Country/Area,918.0,Bermuda,9,No change,2038,2038.5,28.464,31.05,59.514,1102.111
214.0,531,28,CUW,CW,531.0,4.0,Country/Area,915.0,Curaçao,6,Instant replacement,2043,2043.5,106.388,109.309,215.697,508.719
290.0,876,2,WLF,WF,876.0,4.0,Country/Area,957.0,Wallis and Futuna Islands,9,No change,2038,2038.5,5.246,6.002,11.248,80.339
82.0,430,,LBR,LR,430.0,4.0,Country/Area,914.0,Liberia,2,Medium,1987,1987.5,1180.694,1191.755,2372.449,24.631
239.0,484,,MEX,MX,484.0,4.0,Country/Area,916.0,Mexico,2,Medium,1955,1955.5,15739.859,15712.282,31452.141,16.053
,2084,,,,,,,,African Union: Western Africa,9,No change,2077,2077.5,865848.203,850140.233,1715988.435,340.979
163.0,234,17,FRO,FO,234.0,4.0,Country/Area,924.0,Faroe Islands,203,Upper 80 PI,2068,2068.5,36.787,34.821,71.615,51.708
266.0,554,33,NZL,NZ,554.0,4.0,Country/Area,927.0,New Zealand,4,Low,2080,2080.5,2480.588,2487.044,4967.632,18.753
276.0,584,,MHL,MH,584.0,4.0,Country/Area,954.0,Marshall Islands,9,No change,2080,2080.5,34.179,33.263,67.442,374.678
159.0,804,15,UKR,UA,804.0,4.0,Country/Area,923.0,Ukraine,8,Constant mortality,2080,2080.5,8585.976,10020.799,18606.775,32.118
268.0,242,,FJI,FJ,242.0,4.0,Country/Area,928.0,Fiji,202,Median PI,2050,2050.5,546.444,547.73,1094.173,59.889
,98503,,,,,,,,ESCWA: Mashreq subregion,2,Medium,2062,2062.5,168399.535,167916.661,336316.195,195.722
,1704,,,,,,,,UNFPA: West and Central Africa (WCA),4,Low,2091,2091.5,518212.075,530525.37,1048737.445,116.015
69.0,748,,SWZ,SZ,748.0,4.0,Country/Area,913.0,Eswatini,3,High,2041,2041.5,786.356,812.807,1599.163,92.102
,1111,,,,,,,,United States of America (and dependencies),4,Low,2099,2099.5,140188.973,143065.75,283254.723,30.93
,2098,,,,,,,,Countries with Access to the Sea: Northern America,16,Instant replacement zero migration,2051,2051.5,200727.993,202814.842,403542.834,21.636
,1207,,,,,,,,Asia-Pacific Economic Cooperation (APEC),7,Zero migration,2079,2079.5,1271430.314,1268801.754,2540232.067,41.993
60.0,12,,DZA,DZ,12.0,4.0,Country/Area,912.0,Algeria,2,Medium,1957,1957.5,5423.979,5279.272,10703.251,4.494
,2074,,,,,,,,Commonwealth of Nations,6,Instant replacement,2053,2053.5,1737136.695,1718713.613,3455850.308,115.241
1.0,900,,,,1.0,1.0,World,0.0,World,4,Low,2060,2060.5,4415821.287,4455871.747,8871693.034,68.033
168.0,833,19,IMN,IM,833.0,4.0,Country/Area,924.0,Isle of Man,204,Lower 80 PI,2029,2029.5,41.919,42.867,84.793,148.24
268.0,242,,FJI,FJ,242.0,4.0,Country/Area,928.0,Fiji,203,Upper 80 PI,2078,2078.5,679.998,680.781,1361.347,74.513