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Fix explicit using Package: Package, foo
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+74
-51
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3 files changed

+74
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‎test/runtests.jl‎

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,5 @@
1-
using TulipaIO, Test
1+
using TulipaIO: TulipaIO
2+
using Test: Test, @test, @testset, @test_throws
23

34
const DATA = joinpath(@__DIR__, "data")
45

‎test/test-convenience.jl‎

Lines changed: 9 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,7 @@
1-
using CSV, DataFrames, DuckDB, TulipaIO
1+
using CSV: CSV
2+
using DataFrames: DataFrames, DataFrame
3+
using DuckDB: DuckDB, DBInterface
4+
using TulipaIO: TulipaIO
25

36
@testset "Test convenience functions" begin
47
@testset "Read CSV folder" begin
@@ -12,7 +15,7 @@ using CSV, DataFrames, DuckDB, TulipaIO
1215
end
1316

1417
connection = DBInterface.connect(DuckDB.DB)
15-
read_csv_folder(connection, tmpdir)
18+
TulipaIO.read_csv_folder(connection, tmpdir)
1619
@test (DBInterface.execute(connection, "SHOW TABLES") |> DataFrame |> df -> df.name) ==
1720
["some_file"]
1821
end
@@ -23,16 +26,16 @@ using CSV, DataFrames, DuckDB, TulipaIO
2326
"rep_periods_mapping" =>
2427
Dict(:period => "INT", :rep_period => "VARCHAR", :weight => "DOUBLE"),
2528
)
26-
read_csv_folder(con, "data/Norse"; schemas)
29+
TulipaIO.read_csv_folder(con, "data/Norse"; schemas)
2730
df_types = DuckDB.query(con, "DESCRIBE rep_periods_mapping") |> DataFrame
2831
@test df_types.column_name == ["period", "rep_period", "weight"]
2932
@test df_types.column_type == ["INTEGER", "VARCHAR", "DOUBLE"]
3033
end
3134

3235
@testset "Test show_tables and get_table" begin
3336
connection = DBInterface.connect(DuckDB.DB)
34-
create_tbl(connection, "data/Norse/assets-data.csv"; name = "my_table")
35-
@test show_tables(connection).name == ["my_table"]
36-
@test "Asgard_Battery" in get_table(connection, "my_table").name
37+
TulipaIO.create_tbl(connection, "data/Norse/assets-data.csv"; name = "my_table")
38+
@test TulipaIO.show_tables(connection).name == ["my_table"]
39+
@test "Asgard_Battery" in TulipaIO.get_table(connection, "my_table").name
3740
end
3841
end

‎test/test-pipeline.jl‎

Lines changed: 63 additions & 44 deletions
Original file line numberDiff line numberDiff line change
@@ -1,9 +1,9 @@
1-
using CSV, DataFrames, DuckDB
2-
3-
TIO = TulipaIO
1+
using CSV: CSV
2+
using DataFrames: DataFrames, DataFrame
3+
using DuckDB: DuckDB, DBInterface
44

55
function shape(df::DataFrame)
6-
return (nrow(df), ncol(df))
6+
return (DataFrames.nrow(df), DataFrames.ncol(df))
77
end
88

99
function tmp_tbls(con::DuckDB.DB)
@@ -17,47 +17,47 @@ end
1717
When row order is different, do a join to determine equality; use the
1818
columns `cols`, join on `on` (often :name). The resulting DataFrame
1919
is returned. It uniquifies columns with clashing names (see
20-
`?leftjoin`), and stores a "source" under the `:source` column.
20+
`?DataFrames.leftjoin`), and stores a "source" under the `:source` column.
2121
2222
"""
2323
function join_cmp(df1, df2, cols; on::Union{Symbol, Vector{Symbol}})
24-
leftjoin(df1[!, cols], df2[!, cols]; on = on, makeunique = true, source = :source)
24+
DataFrames.leftjoin(df1[!, cols], df2[!, cols]; on = on, makeunique = true, source = :source)
2525
end
2626

2727
@testset "Utilities" begin
2828
csv_path = joinpath(DATA, "Norse/assets-data.csv")
2929

3030
@testset "get_tbl_name(source, tmp)" begin
3131
for (name, tmp) in [["my_file", false], ["t_my_file", true]]
32-
@test name == TIO.get_tbl_name("path/my-file.csv", tmp)
32+
@test name == TulipaIO.get_tbl_name("path/my-file.csv", tmp)
3333
end
3434
end
3535

3636
# redundant for the current implementation, needed when we support globs
3737
@testset "check_file(source)" begin
38-
@test TIO.check_file(csv_path)
39-
@test !TIO.check_file("not-there")
38+
@test TulipaIO.check_file(csv_path)
39+
@test !TulipaIO.check_file("not-there")
4040
end
4141

4242
con = DBInterface.connect(DuckDB.DB)
4343
tbl_name = "mytbl"
4444

4545
@testset "check_tbl(con, source)" begin
4646
DBInterface.execute(con, "CREATE TABLE $tbl_name AS SELECT * FROM range(5)")
47-
@test TIO.check_tbl(con, tbl_name)
48-
@test !TIO.check_tbl(con, "not_there")
47+
@test TulipaIO.check_tbl(con, tbl_name)
48+
@test !TulipaIO.check_tbl(con, "not_there")
4949
end
5050

5151
@testset "Conditionally format source as SQL" begin
52-
read_ = TIO.fmt_source(con, csv_path)
52+
read_ = TulipaIO.fmt_source(con, csv_path)
5353
@test occursin("read_csv", read_)
5454
@test occursin(csv_path, read_)
55-
@test TIO.fmt_source(con, tbl_name) == tbl_name
56-
@test_throws TIO.NeitherTableNorFileError TIO.fmt_source(con, "not-there")
55+
@test TulipaIO.fmt_source(con, tbl_name) == tbl_name
56+
@test_throws TulipaIO.NeitherTableNorFileError TulipaIO.fmt_source(con, "not-there")
5757
if (VERSION.major >= 1) && (VERSION.minor >= 8)
5858
msg_re = r"not-there.+"
5959
msg_re *= "$con"
60-
@test_throws msg_re TIO.fmt_source(con, "not-there")
60+
@test_throws msg_re TulipaIO.fmt_source(con, "not-there")
6161
end
6262
end
6363
end
@@ -71,19 +71,19 @@ end
7171

7272
@testset "CSV -> DataFrame" begin
7373
con = DBInterface.connect(DuckDB.DB)
74-
df_res = TIO.create_tbl(con, csv_path; show = true)
74+
df_res = TulipaIO.create_tbl(con, csv_path; show = true)
7575
@test shape(df_org) == shape(df_res)
76-
@test_throws TIO.FileNotFoundError TIO.create_tbl(con, "not-there")
76+
@test_throws TulipaIO.FileNotFoundError TulipaIO.create_tbl(con, "not-there")
7777
if (VERSION.major >= 1) && (VERSION.minor >= 8)
78-
@test_throws r"not-there" TIO.create_tbl(con, "not-there")
78+
@test_throws r"not-there" TulipaIO.create_tbl(con, "not-there")
7979
end
8080
end
8181

8282
@testset "CSV -> DataFrame w/ a schema" begin
8383
con = DBInterface.connect(DuckDB.DB)
8484
mapping_csv_path = joinpath(DATA, "Norse/rep-periods-mapping.csv")
8585
col_schema = Dict(:period => "INT", :rep_period => "VARCHAR", :weight => "DOUBLE")
86-
TIO.create_tbl(con, mapping_csv_path; types = col_schema)
86+
TulipaIO.create_tbl(con, mapping_csv_path; types = col_schema)
8787
df_types = DuckDB.query(con, "DESCRIBE rep_periods_mapping") |> DataFrame
8888
@test df_types.column_name == ["period", "rep_period", "weight"]
8989
@test df_types.column_type == ["INTEGER", "VARCHAR", "DOUBLE"]
@@ -92,25 +92,30 @@ end
9292
opts = Dict(:on => [:name], :cols => [:investable], :show => true)
9393
@testset "CSV w/ alternatives -> DataFrame" begin
9494
con = DBInterface.connect(DuckDB.DB)
95-
df_res = TIO.create_tbl(con, csv_path, csv_copy; opts..., fill = false)
95+
df_res = TulipaIO.create_tbl(con, csv_path, csv_copy; opts..., fill = false)
9696
df_exp = DataFrame(CSV.File(csv_copy; header = 2))
9797
@test df_exp.investable == df_res.investable
9898
@test df_org.investable != df_res.investable
9999
end
100100

101101
@testset "no filling for missing rows" begin
102102
con = DBInterface.connect(DuckDB.DB)
103-
df_res = TIO.create_tbl(con, csv_path, csv_fill; opts..., fill = false)
103+
df_res = TulipaIO.create_tbl(con, csv_path, csv_fill; opts..., fill = false)
104104
df_ref = DataFrame(CSV.File(csv_fill; header = 2))
105105
# NOTE: row order is different, join to determine equality
106106
cmp = join_cmp(df_res, df_ref, ["name", "investable"]; on = :name)
107-
@test (subset(cmp, :investable_1 => ByRow(ismissing)).source .== "left_only") |> all
108-
@test (subset(cmp, :investable_1 => ByRow(!ismissing)).source .== "both") |> all
107+
@test (
108+
DataFrames.subset(cmp, :investable_1 => DataFrames.ByRow(ismissing)).source .==
109+
"left_only"
110+
) |> all
111+
@test (
112+
DataFrames.subset(cmp, :investable_1 => DataFrames.ByRow(!ismissing)).source .== "both"
113+
) |> all
109114
end
110115

111116
@testset "back-filling missing rows" begin
112117
con = DBInterface.connect(DuckDB.DB)
113-
df_res = TIO.create_tbl(con, csv_path, csv_fill; opts..., fill = true)
118+
df_res = TulipaIO.create_tbl(con, csv_path, csv_fill; opts..., fill = true)
114119
df_exp = DataFrame(CSV.File(csv_copy; header = 2))
115120
cmp = join_cmp(df_exp, df_res, ["name", "investable"]; on = :name)
116121
@test all(cmp.investable .== cmp.investable_1)
@@ -119,7 +124,7 @@ end
119124

120125
@testset "back-filling missing rows w/ alternate values" begin
121126
con = DBInterface.connect(DuckDB.DB)
122-
df_res = TIO.create_tbl(
127+
df_res = TulipaIO.create_tbl(
123128
con,
124129
csv_path,
125130
csv_fill;
@@ -129,22 +134,23 @@ end
129134
)
130135
df_ref = DataFrame(CSV.File(csv_fill; header = 2))
131136
cmp = join_cmp(df_res, df_ref, ["name", "investable"]; on = :name)
132-
@test (subset(cmp, :investable_1 => ByRow(ismissing)).investable) |> all
137+
@test (DataFrames.subset(cmp, :investable_1 => DataFrames.ByRow(ismissing)).investable) |>
138+
all
133139
end
134140

135141
@testset "temporary tables" begin
136142
con = DBInterface.connect(DuckDB.DB)
137-
tbl_name = TIO.create_tbl(con, csv_path; name = "tmp_assets", tmp = true)
143+
tbl_name = TulipaIO.create_tbl(con, csv_path; name = "tmp_assets", tmp = true)
138144
@test tbl_name in tmp_tbls(con)[!, :name]
139145

140-
tbl_name = TIO.create_tbl(con, csv_path; tmp = true)
146+
tbl_name = TulipaIO.create_tbl(con, csv_path; tmp = true)
141147
@test tbl_name == "t_assets_data" # t_<cleaned up filename>
142148
@test tbl_name in tmp_tbls(con)[!, :name]
143149
end
144150

145151
@testset "CSV -> table" begin
146152
con = DBInterface.connect(DuckDB.DB)
147-
tbl_name = TIO.create_tbl(con, csv_path; name = "no_assets")
153+
tbl_name = TulipaIO.create_tbl(con, csv_path; name = "no_assets")
148154
df_res = DataFrame(DBInterface.execute(con, "SELECT * FROM $tbl_name"))
149155
@test shape(df_org) == shape(df_res)
150156
# @show df_org[1:3, 1:5] df_res[1:3, 1:5]
@@ -168,18 +174,24 @@ end
168174
@testset "table + CSV w/ alternatives -> table" begin
169175
# test setup
170176
con = DBInterface.connect(DuckDB.DB)
171-
TIO.create_tbl(con, csv_path; name = "no_assets")
177+
TulipaIO.create_tbl(con, csv_path; name = "no_assets")
172178

173179
opts = Dict(:on => [:name], :cols => [:investable])
174-
tbl_name =
175-
TIO.create_tbl(con, "no_assets", csv_copy; name = "alt_assets", opts..., fill = false)
180+
tbl_name = TulipaIO.create_tbl(
181+
con,
182+
"no_assets",
183+
csv_copy;
184+
name = "alt_assets",
185+
opts...,
186+
fill = false,
187+
)
176188
df_res = DataFrame(DBInterface.execute(con, "SELECT * FROM $tbl_name"))
177189
df_exp = DataFrame(CSV.File(csv_copy; header = 2))
178190
@test df_exp.investable == df_res.investable
179191
@test df_org.investable != df_res.investable
180192

181193
@testset "back-filling missing rows" begin
182-
tbl_name = TIO.create_tbl(
194+
tbl_name = TulipaIO.create_tbl(
183195
con,
184196
"no_assets",
185197
csv_fill;
@@ -196,7 +208,7 @@ end
196208
end
197209

198210
@testset "back-filling missing rows w/ alternate values" begin
199-
tbl_name = TIO.create_tbl(
211+
tbl_name = TulipaIO.create_tbl(
200212
con,
201213
"no_assets",
202214
csv_fill;
@@ -208,7 +220,9 @@ end
208220
df_res = DataFrame(DBInterface.execute(con, "SELECT * FROM $tbl_name"))
209221
df_ref = DataFrame(CSV.File(csv_fill; header = 2))
210222
cmp = join_cmp(df_res, df_ref, ["name", "investable"]; on = :name)
211-
@test (subset(cmp, :investable_1 => ByRow(ismissing)).investable) |> all
223+
@test (
224+
DataFrames.subset(cmp, :investable_1 => DataFrames.ByRow(ismissing)).investable
225+
) |> all
212226
end
213227
end
214228
end
@@ -224,35 +238,40 @@ end
224238
@testset "w/ vector" begin
225239
con = DBInterface.connect(DuckDB.DB)
226240
df_exp = DataFrame(CSV.File(csv_copy; header = 2))
227-
df_res = TIO.create_tbl(con, csv_path, Dict(:investable => df_exp.investable); opts...)
241+
df_res = TulipaIO.create_tbl(con, csv_path, Dict(:investable => df_exp.investable); opts...)
228242
# NOTE: row order is different, join to determine equality
229243
cmp = join_cmp(df_exp, df_res, ["name", "investable"]; on = :name)
230244
investable = cmp[!, [c for c in propertynames(cmp) if occursin("investable", String(c))]]
231245
@test isequal.(investable[!, 1], investable[!, 2]) |> all
232246

233247
# stupid Julia! grow up!
234248
args = [con, csv_path, Dict(:investable => df_exp.investable[2:end])]
235-
@test_throws DimensionMismatch TIO.create_tbl(args...; opts...)
249+
@test_throws DimensionMismatch TulipaIO.create_tbl(args...; opts...)
236250
if (VERSION.major >= 1) && (VERSION.minor >= 8)
237-
@test_throws r"Length.+different" TIO.create_tbl(args...; opts...)
238-
@test_throws r"index.+value" TIO.create_tbl(args...; opts...)
251+
@test_throws r"Length.+different" TulipaIO.create_tbl(args...; opts...)
252+
@test_throws r"index.+value" TulipaIO.create_tbl(args...; opts...)
239253
end
240254
end
241255

242256
@testset "w/ constant" begin
243257
con = DBInterface.connect(DuckDB.DB)
244-
df_res = TIO.create_tbl(con, csv_path, Dict(:investable => true); opts...)
258+
df_res = TulipaIO.create_tbl(con, csv_path, Dict(:investable => true); opts...)
245259
@test df_res.investable |> all
246260

247-
table_name = TIO.create_tbl(con, csv_path, Dict(:investable => true); on = :name)
261+
table_name = TulipaIO.create_tbl(con, csv_path, Dict(:investable => true); on = :name)
248262
@test "assets_data" == table_name
249263
end
250264

251265
@testset "w/ constant after filtering" begin
252266
con = DBInterface.connect(DuckDB.DB)
253-
where_clause = TIO.FmtSQL.@where_(lifetime in 25:50, name % "Valhalla_%")
254-
df_res =
255-
TIO.create_tbl(con, csv_path, Dict(:investable => true); opts..., where_ = where_clause)
267+
where_clause = TulipaIO.FmtSQL.@where_(lifetime in 25:50, name % "Valhalla_%")
268+
df_res = TulipaIO.create_tbl(
269+
con,
270+
csv_path,
271+
Dict(:investable => true);
272+
opts...,
273+
where_ = where_clause,
274+
)
256275
@test shape(df_res) == shape(df_org)
257276
df_res =
258277
filter(row -> 25 <= row.lifetime <= 50 && startswith(row.name, "Valhalla_"), df_res)

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