diff --git a/cli/cli.py b/cli/cli.py
index b2ffc8a801..00589d26d9 100644
--- a/cli/cli.py
+++ b/cli/cli.py
@@ -63,6 +63,7 @@ class Algorithm(StrEnum):
 VERBOSE = 'verbose'
 ERROR = 'error'
 ERROR_MEASURE = 'error_measure'
+TABLE = 'table'
 TABLES = 'tables'
 TABLES_LIST = 'tables_list'
 TABLES_DIRECTORY = 'tables_directory'
@@ -144,9 +145,6 @@ class Algorithm(StrEnum):
     Algorithms for some tasks (currently, only IND) accept multiple
     input files; see --task=TASK for more information
 
---is_null_equal_null=BOOLEAN
-    specify whether two NULLs should be considered equal
-
 --filename=FILENAME
     specify the file to write the results to. If none is selected, output is
     written to the console
@@ -469,7 +467,9 @@ class Algorithm(StrEnum):
                                     Algorithm.naive_ucc_verifier),
     Task.aucc_verification: TaskInfo([Algorithm.naive_aucc_verifier],
                                      Algorithm.naive_aucc_verifier),
-    Task.gfd_verification: TaskInfo([Algorithm.naive_gfd_verifier, Algorithm.gfd_verifier, Algorithm.egfd_verifier],
+    Task.gfd_verification: TaskInfo([Algorithm.naive_gfd_verifier,
+                                     Algorithm.gfd_verifier,
+                                     Algorithm.egfd_verifier],
                                     Algorithm.naive_gfd_verifier),
 }
 
@@ -697,8 +697,10 @@ def print_help_page(algo_name: str | None, task: str | None) -> None:
 def print_algo_help_page(algo_name: str) -> None:
     algo = ALGOS[Algorithm(algo_name)]()
     help_info = ''
-    for opt in algo.get_possible_options():
-        if opt not in ('table', TABLES, 'is_null_equal_null'):
+    algo_options = list(algo.get_possible_options())
+    algo_options.sort()
+    for opt in algo_options:
+        if opt not in (TABLE, TABLES):
             help_info += get_option_help_info(opt, algo)
     click.echo(f'{ALGO_HELP_PAGES[Algorithm(algo_name)]}{help_info}')
 
diff --git a/cli/cli_tests/dev-requirements.txt b/cli/cli_tests/dev-requirements.txt
new file mode 100644
index 0000000000..df6b3a13c0
--- /dev/null
+++ b/cli/cli_tests/dev-requirements.txt
@@ -0,0 +1,3 @@
+click==8.1.6
+desbordante==2.0.0
+snapshottest==0.6.0
diff --git a/cli/cli_tests/snapshots/snap_test_cli_help_pages.py b/cli/cli_tests/snapshots/snap_test_cli_help_pages.py
new file mode 100644
index 0000000000..92af5a27a3
--- /dev/null
+++ b/cli/cli_tests/snapshots/snap_test_cli_help_pages.py
@@ -0,0 +1,669 @@
+# -*- coding: utf-8 -*-
+# snapshottest: v1 - https://goo.gl/zC4yUc
+from __future__ import unicode_literals
+
+from snapshottest import Snapshot
+
+
+snapshots = Snapshot()
+
+snapshots['TestCLIHelpPages::test_algos_help_pages aid_help'] = '''A modern algorithm for discovery of exact functional
+dependencies. Unlike all other algorithms, it is approximate, i.e. it can
+miss some dependencies or produce non-valid ones. In exchange,
+it is significantly faster (10x-100x). For more information, refer to the
+“Approximate Discovery of Functional Dependencies for Large Datasets” paper
+by T.Bleifus et al.
+
+--max_lhs=INTEGER
+\tmax considered LHS size
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages apriori_help'] = '''An algorithm for frequent item set mining and association 
+rule discovery. For more information, refer to the "Fast Algorithms for 
+Mining Association Rules" paper by Agrawal and Srikant from 1994.
+
+--has_tid=BOOLEAN
+\tindicates that the first column contains the transaction IDs
+
+--input_format=STRING
+\tformat of the input dataset for AR mining
+[singular|tabular]
+
+--item_column_index=INTEGER
+\tindex of the column where an item name is stored
+
+--minconf=FLOAT
+\tminimum confidence value (between 0 and 1)
+
+--minsup=FLOAT
+\tminimum support value (between 0 and 1)
+
+--tid_column_index=INTEGER
+\tindex of the column where a TID is stored
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages dep_miner_help'] = '''A classic algorithm for discovery of exact functional
+dependencies. For more information refer to “Efficient Discovery of
+Functional Dependencies and Armstrong Relations” paper by S. Lopes et al.
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--max_lhs=INTEGER
+\tmax considered LHS size
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages dfd_help'] = '''A modern algorithm for discovery of exact functional
+dependencies. For more information, refer to the “DFD: Efficient Functional
+Dependency Discovery” paper by Z. Abedjan et al.
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--max_lhs=INTEGER
+\tmax considered LHS size
+
+--threads=INTEGER
+\tnumber of threads to use. If 0, then as many threads are used as the hardware can handle concurrently.
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages egfd_verifier_help'] = '''Algorithm for verifying whether a given
+graph functional dependency holds. For more information about the primitive
+refer to “Functional Dependencies for Graphs” by Wenfei Fan et al.
+
+--gfd=STRING
+\tPath to file with GFD
+\tFor multiple values, specify multiple times 
+\t(e.g., --gfd=1 --gfd=2)
+
+--graph=STRING
+\tPath to dot-file with graph
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages faida_help'] = '''Both unary and n-ary inclusion dependency mining algorithm.
+Unlike all other algorithms, it is approximate, i.e. it can
+miss some dependencies or produce non-valid ones. In exchange,
+it is significantly faster. For more information, refer to "Fast approximate
+discovery of inclusion dependencies" by S. Kruse et al.
+
+--find_nary=BOOLEAN
+\tDetect n-ary inclusion dependencies [true|false]
+
+--hll_accuracy=FLOAT
+\tHyperLogLog approximation accuracy. Must be positive
+Closer to 0 - higher accuracy, more memory needed and slower the algorithm.
+
+
+--ignore_constant_cols=BOOLEAN
+\tIgnore INDs which contain columns filled with only one value. May increase performance but impacts the result. [true|false]
+
+--ignore_null_cols=BOOLEAN
+\tIgnore INDs which contain columns filled only with NULLs. May increase performance but impacts the result. [true|false]
+
+--sample_size=INTEGER
+\tSize of a table sample. Greater value - more correct answers, but higher memory consumption.
+ Applies to all tables
+
+--threads=INTEGER
+\tnumber of threads to use. If 0, then as many threads are used as the hardware can handle concurrently.
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages fastfds_help'] = '''A classic algorithm for discovery of exact functional
+dependencies. For more information, refer to “FastFDs: A Heuristic-Driven,
+Depth-First Algorithm for Mining Functional Dependencies from Relation
+Instances Extended Abstract” paper by C. Wyss et al.
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--max_lhs=INTEGER
+\tmax considered LHS size
+
+--threads=INTEGER
+\tnumber of threads to use. If 0, then as many threads are used as the hardware can handle concurrently.
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages fastod_help'] = '''A modern algorithm for discovery of canonical order 
+dependencies. For more information, refer to the “Effective and complete 
+discovery of order dependencies via set-based axiomatization” paper by 
+J. Szlichta et al.
+
+--time_limit=INTEGER
+\tmax running time of the algorithm. Pass 0 to remove limit
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages fd_first_help'] = '''FD-First algorithm belongs to the family of algorithms
+for discovering approximate conditional functional dependencies. For more
+information, refer to the “Revisiting Conditional Functional Dependency
+Discovery: Splitting the “C” from the “FD”” paper by J. Rammelaere 
+and F. Geerts.
+
+--cfd_max_lhs=INTEGER
+\tcfd max considered LHS size
+
+--cfd_minconf=FLOAT
+\tcfd minimum confidence value (between 0 and 1)
+
+--cfd_minsup=INTEGER
+\tminimum support value (integer number between 1 and number of tuples in dataset)
+
+--cfd_substrategy=STRING
+\tCFD lattice traversal strategy to use
+[dfs|bfs]
+
+--columns_number=INTEGER
+\tNumber of columns in the part of the dataset if you want to use algo not on the full dataset, but on its part
+
+--tuples_number=INTEGER
+\tNumber of tuples in the part of the dataset if you want to use algo not on the full dataset, but on its part
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages fd_mine_help'] = '''A classic algorithm for discovery of exact functional
+dependencies. Has issues with the minimality of answer. For more
+information, refer to the “FD_Mine: discovering functional dependencies in a
+database using equivalences paper” by H. Yao et al.
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--max_lhs=INTEGER
+\tmax considered LHS size
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages fdep_help'] = '''A classic algorithm for discovery of exact functional
+dependencies. For more information, refer to the “Database Dependency
+Discovery: A Machine Learning Approach” paper by Peter A. Flach and
+Iztok Savnik.
+
+--max_lhs=INTEGER
+\tmax considered LHS size
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages fun_help'] = '''A classic algorithm for discovery of exact functional
+dependencies. For more information,  refer to the “FUN: An efficient
+algorithm for mining functional and embedded dependencies” paper by
+N. Novelli and R. Cicchetti.
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--max_lhs=INTEGER
+\tmax considered LHS size
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages gfd_verifier_help'] = '''Algorithm for verifying whether a given
+graph functional dependency holds. For more information about the primitive
+refer to “Functional Dependencies for Graphs” by Wenfei Fan et al.
+
+--gfd=STRING
+\tPath to file with GFD
+\tFor multiple values, specify multiple times 
+\t(e.g., --gfd=1 --gfd=2)
+
+--graph=STRING
+\tPath to dot-file with graph
+
+--threads=INTEGER
+\tnumber of threads to use. If 0, then as many threads are used as the hardware can handle concurrently.
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages hyfd_help'] = '''A modern algorithm for discovery of exact functional
+dependencies. One of the most high-performance algorithms for this task. For
+more information, refer to “A Hybrid Approach to Functional Dependency
+Discovery” by T. Papenbrock and F. Naumann.
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--max_lhs=INTEGER
+\tmax considered LHS size
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages icde09_mfd_verifier_help'] = '''A family of metric functional dependency
+verification algorithms. For more information about the primitive and the
+algorithms, refer to “Metric Functional Dependencies” by N. Koudas et al.
+
+--dist_from_null_is_infinity=BOOLEAN
+\tspecify whether distance from NULL value is infinity (if not, it is 0)
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--lhs_indices=INTEGER
+\tLHS column indices
+\tFor multiple values, specify multiple times 
+\t(e.g., --lhs_indices=1 --lhs_indices=2)
+
+--metric=STRING
+\tmetric to use
+[euclidean|levenshtein|cosine]
+
+--metric_algorithm=STRING
+\tMFD algorithm to use
+[brute|approx|calipers]
+
+--parameter=FLOAT
+\tmetric FD parameter
+
+--q=INTEGER
+\tq-gram length for cosine metric
+
+--rhs_indices=INTEGER
+\tRHS column indices
+\tFor multiple values, specify multiple times 
+\t(e.g., --rhs_indices=1 --rhs_indices=2)
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages naive_afd_verifier_help'] = '''A straightforward partition-based algorithm for
+verifying whether a given approximate dependency holds. For more
+information, refer to Section 2 of “TANE : An Efficient Algorithm for
+Discovering Functional and Approximate Dependencies” by Y.Huntala et al. We
+also recommend looking into “Efficient Discovery of ApproximateDependencies" by
+S. Kruse and F. Naumann.
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--lhs_indices=INTEGER
+\tLHS column indices
+\tFor multiple values, specify multiple times 
+\t(e.g., --lhs_indices=1 --lhs_indices=2)
+
+--rhs_indices=INTEGER
+\tRHS column indices
+\tFor multiple values, specify multiple times 
+\t(e.g., --rhs_indices=1 --rhs_indices=2)
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages naive_aucc_verifier_help'] = '''A straightforward partition-based algorithm for
+verifying whether a given approximate unique column combination holds.
+For more information on partitions refer to Section 2 of “TANE : An 
+Efficient Algorithm for Discovering Functional and Approximate Dependencies”
+by Y.Huntala et al. For more information on AUCC, refer to "Efficient Discovery
+of Approximate Dependencies" by S. Kruse and F. Naumann.
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--ucc_indices=INTEGER
+\tcolumn indices for UCC verification
+\tFor multiple values, specify multiple times 
+\t(e.g., --ucc_indices=1 --ucc_indices=2)
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages naive_fd_verifier_help'] = '''A straightforward partition-based algorithm for
+verifying whether a given exact functional dependency holds on the specified
+dataset. For more information, refer to Lemma 2.2 from “TANE: An Efficient
+Algorithm for Discovering Functional and Approximate Dependencies” by
+Y.Huntala et al.
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--lhs_indices=INTEGER
+\tLHS column indices
+\tFor multiple values, specify multiple times 
+\t(e.g., --lhs_indices=1 --lhs_indices=2)
+
+--rhs_indices=INTEGER
+\tRHS column indices
+\tFor multiple values, specify multiple times 
+\t(e.g., --rhs_indices=1 --rhs_indices=2)
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages naive_gfd_verifier_help'] = '''Algorithm for verifying whether a given
+graph functional dependency holds. For more information about the primitive
+refer to “Functional Dependencies for Graphs” by Wenfei Fan et al.
+
+--gfd=STRING
+\tPath to file with GFD
+\tFor multiple values, specify multiple times 
+\t(e.g., --gfd=1 --gfd=2)
+
+--graph=STRING
+\tPath to dot-file with graph
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages naive_ucc_verifier_help'] = '''A straightforward partition-based algorithm for
+verifying whether a given unique column combination holds.
+For more information on partitions refer to Section 2 of “TANE : An 
+Efficient Algorithm for Discovering Functional and Approximate Dependencies”
+by Y.Huntala et al. For more information on UCC, refer to "Efficient Discovery
+of Approximate Dependencies" by S. Kruse and F. Naumann.
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--ucc_indices=INTEGER
+\tcolumn indices for UCC verification
+\tFor multiple values, specify multiple times 
+\t(e.g., --ucc_indices=1 --ucc_indices=2)
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages order_help'] = '''Algorithm Order efficiently discovers all n-ary lexicographical 
+order dependencies under the operator “<”. For more information, refer to the
+“Efficient order dependency detection” paper by Philipp Langer and Felix Naumann.
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages pfdtane_help'] = '''A TANE-based algorithm for discovery of probabilistic
+functional dependencies. For more information, refer to “Functional Dependency
+Generation and Applications in pay-as-you-go data integration systems” by
+Daisy Zhe Wang et al.
+
+--error=FLOAT
+\terror threshold value for Approximate FD algorithms
+
+--error_measure=STRING
+\tPFD error measure to use
+[per_tuple|per_value]
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--max_lhs=INTEGER
+\tmax considered LHS size
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages pyro_help'] = '''A modern algorithm for discovery of approximate functional
+dependencies. Approximate functional dependencies are defined in the
+“Efficient Discovery of Approximate Dependencies” paper by S.Kruse and
+F.Naumann. Capable of discovering exact dependencies too.
+
+--error=FLOAT
+\terror threshold value for Approximate FD algorithms
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--max_lhs=INTEGER
+\tmax considered LHS size
+
+--seed=INTEGER
+\tRNG seed
+
+--threads=INTEGER
+\tnumber of threads to use. If 0, then as many threads are used as the hardware can handle concurrently.
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages spider_help'] = '''A disk-backed unary inclusion dependency mining algorithm.
+For more information, refer to "Efficiently detecting inclusion dependencies"
+by J. Bauckmann et al.
+
+--error=FLOAT
+\terror threshold value for Approximate FD algorithms
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--mem_limit=INTEGER
+\tmemory limit im MBs
+
+--threads=INTEGER
+\tnumber of threads to use. If 0, then as many threads are used as the hardware can handle concurrently.
+
+'''
+
+snapshots['TestCLIHelpPages::test_algos_help_pages tane_help'] = '''A classic algorithm for discovery of exact and approximate
+functional dependencies. For more information, refer to “TANE : An Efficient
+Algorithm for Discovering Functional and Approximate Dependencies” by
+Y. Huntala et al.
+
+--error=FLOAT
+\terror threshold value for Approximate FD algorithms
+
+--is_null_equal_null=BOOLEAN
+\tspecify whether two NULLs should be considered equal
+
+--max_lhs=INTEGER
+\tmax considered LHS size
+
+'''
+
+snapshots['TestCLIHelpPages::test_main_help_page main_help'] = '''The Desbordante data profiler is designed to help users
+discover or verify various types of patterns in data. These patterns are
+various kinds of data dependencies (functional, metric, inclusion, etc),
+constraints (algebraic, denial, etc), many types of association rules and more.
+
+Each pattern type is termed a “primitive”, and a specific occurrence of this
+primitive inside a specific dataset is referred to as its “instance”. For
+example, a functional dependency is a primitive, and the “company -> email”
+functional dependency inside the sales.csv table is its instance.
+
+For each primitive, Desbordante supports two key tasks: discovery and
+verification. The discovery task discovers (mines) all relevant* primitive
+instances within a given dataset, while verification checks (validates)
+whether a given instance holds. The verification task name contains the
+“_verification” suffix; for example, the “fd” task returns all minimal and
+non-trivial functional dependencies contained in the dataset,
+and “fd_verification” checks whether a given functional dependency holds.
+
+* The notion of “relevance” depends on the definition of the primitive. The
+relevant set is usually the minimal set of instances from which the rest can
+be derived. For actual definitions, consult the related papers.
+
+Each task can be performed by one of the provided algorithms. For some
+primitives, several algorithms are available, each of which excel on a
+different type of dataset, such as “wide” or “tall” tables. See
+--task=TASK --help to view the list of all supported algorithms for TASK.
+Additionally, we also provide a default algorithm which is the best one in
+many cases.
+
+The algorithms accept two types of parameters: primitive-specific
+constraints and implementation-related settings. The first group includes
+parameters that define which instances are to discover/verify, e.g. the
+constraint on the maximum length of the left-hand side of the functional
+dependency. The second group refers to general parameters that impact
+algorithm performance, e.g. the number of threads to use, seed, buffer size
+for intermediates, etc. Note that not all algorithms, even those designed
+for the same task, support multithreading.
+
+Next, several primitives have approximate versions, which allow some records
+to deviate from the primitive definition. This is practical for dealing with
+real-life data, which may contain all kinds of imperfections. The number of
+such imperfect records is usually defined by an error threshold which is
+calculated according to a primitive-specific procedure. In this case,
+the algorithm can be parameterized by this threshold.
+
+Overall, to use the Desbordante profiler, specify the dataset file, task,
+algorithm and its parameters. The results will be written to the specified
+output file or to console, if none is specified.
+
+Currently, the console version of Desbordante supports:
+1) Discovery of exact functional dependencies
+2) Discovery of approximate functional dependencies
+3) Discovery of probabilistic functional dependencies
+4) Discovery of association rules
+5) Discovery of exact order dependencies (set-based and list-based axiomatization)
+6) Discovery of inclusion dependencies
+7) Verification of exact functional dependencies
+8) Verification of approximate functional dependencies
+9) Verification of metric dependencies
+10) Verification of exact unique column combinations
+11) Verification of approximate unique column combinations
+If you need other types, you should look into the C++ code, the Python
+bindings or the Web version.
+
+
+--task=TASK
+    specify the task to run, e.g., discovery of functional dependencies
+
+--algo=ALGORITHM
+    specify the algorithm to run, e.g., PYRO
+
+--table=TABLE
+    specify the input file to be processed by the algorithm.
+    Algorithms for some tasks (currently, only IND) accept multiple
+    input files; see --task=TASK for more information
+
+--filename=FILENAME
+    specify the file to write the results to. If none is selected, output is
+    written to the console
+
+--verbose
+    print detailed information before the result
+
+--help
+    display this help or help page of the algorithm and task options
+    (--task=TASK --help | --algo=ALGO --help); should be specified after
+    --algo|--task
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages afd_help'] = '''Discover minimal non-trivial approximate functional
+dependencies. Approximate functional dependencies are defined in the
+“Efficient Discovery of Approximate Dependencies” paper by S. Kruse and
+F. Naumann.
+
+Algorithms: PYRO, TANE
+Default: PYRO
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages afd_verification_help'] = '''Verify whether a given approximate functional
+dependency holds on the specified dataset. Approximate functional
+dependencies are defined in the “Efficient Discovery of Approximate
+Dependencies” paper by S. Kruse and F. Naumann.
+
+Algorithms: NAIVE_AFD_VERIFIER
+Default: NAIVE_AFD_VERIFIER
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages ar_help'] = '''Discover association rules. For more information, refer to
+"Frequent Pattern Mining" book by Charu C. Aggarwal and Jiawei Han.
+
+Algorithms: Apriori
+Default: Apriori
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages aucc_verification_help'] = '''Verify whether a given approximate unique column combination
+holds on the specified dataset. For more information about the primitive and 
+the algorithms, refer to "Efficient Discovery of Approximate Dependencies" by 
+S. Kruse and F. Naumann
+
+Algorithms: NAIVE_AUCC_VERIFIER
+Default: NAIVE_AUCC_VERIFIER
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages cfd_help'] = '''Discover approximate conditional functional dependencies. For
+more information about the primitive and the algorithm, refer to the “Revisiting
+Conditional Functional Dependency Discovery: Splitting the “C” from the “FD””
+paper by J. Rammelaere and F. Geerts.
+
+Algorithms: FD_FIRST
+Default: FD_FIRST
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages fd_help'] = '''Discover minimal non-trivial exact functional dependencies. For
+more information about the primitive and the algorithms, refer to the
+“Functional dependency discovery: an experimental evaluation of seven
+algorithms” paper by T. Papenbrock et al.
+
+Algorithms: PYRO, TANE, HYFD, FD_MINE, DFD, DEP_MINER, FDEP, FUN, FASTFDS, AID
+Default: HYFD
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages fd_verification_help'] = '''Verify whether a given exact functional dependency
+holds on the specified dataset. For more information about the primitive and
+algorithms, refer to the “Functional dependency discovery: an experimental
+evaluation of seven algorithms” paper by T. Papenbrock et al.
+
+Algorithms: NAIVE_FD_VERIFIER
+Default: NAIVE_FD_VERIFIER
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages gfd_verification_help'] = '''
+Algorithms: NAIVE_GFD_VERIFIER, GFD_VERIFIER, EGFD_VERIFIER
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages ind_help'] = '''Discover inclusion dependecies. For more information about
+inclusion dependecies, refer to the "Inclusion Dependency Discovery: An
+Experimental Evaluation of Thirteen Algorithms" by Falco Dürsch et al.
+Algorithms for this task accept multiple input files. You can use one of the
+following options:
+
+--tables=TABLE
+    specify input files to be processed by the algorithm.
+    For multiple values, specify multiple times
+    (e.g., --tables=TABLE_1 --tables=TABLE_2)
+
+--tables_list=FILENAME
+    specify file with list of input files (one on a line).
+    You can type --tables_list=- to use stdin
+
+--tables_directory=FILENAME, STRING, BOOLEAN
+    specify directory with input files.
+    separator and has_header are applied to all tables
+
+Algorithms: SPIDER, FAIDA
+Default: SPIDER
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages mfd_verification_help'] = '''Verify whether a given metric functional
+dependency holds on the specified dataset. For more information about the
+primitive and the algorithms, refer to “Metric Functional Dependencies” by
+N. Koudas et al.
+
+Algorithms: ICDE09_MFD_VERIFIER
+Default: ICDE09_MFD_VERIFIER
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages od_help'] = '''Discover order dependencies. For more information about the 
+primitive and algorithms, refer to the “Effective and complete discovery 
+of order dependencies via set-based axiomatization” paper by J. Szlichta 
+et al.
+
+Algorithms: FASTOD, ORDER
+Default: FASTOD
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages pfd_help'] = '''Discover minimal non-trivial probabilistic functional
+dependencies. Probabilitistic functional dependencies are defined in the
+“Functional Dependency Generation and Applications in pay-as-you-go 
+data integration systems” paper by Daisy Zhe Wang et al.
+Algorithms: PFDTANE
+Default: PFDTANE
+
+'''
+
+snapshots['TestCLIHelpPages::test_tasks_help_pages ucc_verification_help'] = '''Verify whether a given unique column combination
+holds on the specified dataset. For more information about the primitive and 
+the algorithms, refer to "Efficient Discovery of Approximate Dependencies" by 
+S. Kruse and F. Naumann
+
+Algorithms: NAIVE_UCC_VERIFIER
+Default: NAIVE_UCC_VERIFIER
+
+'''
diff --git a/cli/cli_tests/test_cli_help_pages.py b/cli/cli_tests/test_cli_help_pages.py
new file mode 100644
index 0000000000..61bbc2e48a
--- /dev/null
+++ b/cli/cli_tests/test_cli_help_pages.py
@@ -0,0 +1,40 @@
+import unittest
+
+import snapshottest
+from click.testing import CliRunner
+
+from cli import desbordante_cli, Algorithm, Task
+
+
+class TestCLIHelpPages(snapshottest.TestCase):
+    def test_main_help_page(self):
+        runner = CliRunner()
+        with self.subTest(msg=f'Testing main help page'):
+            result = runner.invoke(desbordante_cli, f'--help').output
+            self.assertMatchSnapshot(result, f'main_help')
+
+    def test_algos_help_pages(self):
+        runner = CliRunner()
+        for algo in Algorithm:
+            with self.subTest(msg=f'Testing help page for {algo}'):
+                result = runner.invoke(desbordante_cli,
+                                       f'--algo={algo} --help').output
+                self.assertMatchSnapshot(result, f'{algo}_help')
+
+    def test_tasks_help_pages(self):
+        runner = CliRunner()
+        for task in Task:
+            with self.subTest(msg=f'Testing help page for {task}'):
+                result = runner.invoke(desbordante_cli,
+                                       f'--task={task} --help').output
+                self.assertMatchSnapshot(result, f'{task}_help')
+
+
+if __name__ == '__main__':
+    import snapshottest.unittest
+    import os
+
+    update = os.getenv('UPDATE_HELP_PAGES', False)
+    if update:
+        snapshottest.unittest.TestCase.snapshot_should_update = True
+    unittest.main()
diff --git a/cli/cli_tests/test_cli_parsing.py b/cli/cli_tests/test_cli_parsing.py
new file mode 100644
index 0000000000..9f833067e3
--- /dev/null
+++ b/cli/cli_tests/test_cli_parsing.py
@@ -0,0 +1,95 @@
+import unittest
+from collections import namedtuple
+from unittest.mock import patch
+
+import desbordante
+from click.testing import CliRunner
+
+from cli import desbordante_cli, ALGOS
+
+UNFIXED_ALGOS = ['naive_gfd_verifier', 'gfd_verifier', 'egfd_verifier', 'apriori']
+
+UNFIXED_OPTS = ['table', 'tables']
+
+OptionInfo = namedtuple('OptionInfo', ['str', 'value'])
+
+OPTION_VALUES = {
+    (int,): OptionInfo('4', 4),
+    (float,): OptionInfo('0.1', 0.1),
+    (bool,): OptionInfo('True', True)
+}
+
+UNCOMMON_OPTIONS = {
+    'table': OptionInfo("'cli_tests/university.csv' , False", ''),
+    'tables': OptionInfo("'cli_tests/university.csv' , False", ''),
+    'lhs_indices': OptionInfo('0 --lhs_indices=2', [0, 2]),
+    'rhs_indices': OptionInfo('0', [0]),
+    'metric': OptionInfo('cosine', 'cosine'),
+    'metric_algorithm': OptionInfo('brute', 'brute'),
+    'ucc_indices': OptionInfo('0', [0]),
+    'error_measure': OptionInfo('per_tuple', 'per_tuple'),
+    'mem_limit': OptionInfo('16', 16),
+    'cfd_substrategy': OptionInfo('dfs', 'dfs')
+}
+
+
+def get_expected_options(algo):
+    algo_opts = algo.get_possible_options()
+    expected_options = dict()
+    for opt in algo_opts:
+        if opt not in UNCOMMON_OPTIONS.keys():
+            opt_type = algo.get_option_type(opt)
+            expected_options.update({opt: OPTION_VALUES[opt_type].value})
+        elif opt not in UNFIXED_OPTS:
+            expected_options.update({opt: UNCOMMON_OPTIONS[opt].value})
+    return expected_options
+
+
+def get_invoke_str(algo_name):
+    invoke_str = f'--algo={algo_name}'
+    algo = ALGOS[algo_name]()
+    algo_opts = algo.get_possible_options()
+    for opt in algo_opts:
+        if opt not in UNCOMMON_OPTIONS.keys():
+            opt_type = algo.get_option_type(opt)
+            value_as_str = OPTION_VALUES[opt_type].str
+        else:
+            value_as_str = UNCOMMON_OPTIONS[opt].str
+        invoke_str = f'{invoke_str} --{opt}={value_as_str}'
+    return invoke_str
+
+
+def get_algo_options(self, **kwargs):
+    return self.get_opts()
+
+
+def compare_parsing_result(algo, algo_name):
+    if algo_name == 'apriori':
+        a = 5
+    expected_result = get_expected_options(algo)
+    cli_parsing_result = algo.execute()
+    if cli_parsing_result == expected_result:
+        result = 'success'
+    else:
+        result = 'fail'
+    return result
+
+
+class TestCLIParsing(unittest.TestCase):
+    def test_algos(self):
+        runner = CliRunner()
+        with patch.multiple(desbordante.Algorithm, execute=get_algo_options):
+            with patch('cli.get_algo_result', compare_parsing_result):
+                for algo_name in ALGOS.keys():
+                    if algo_name not in UNFIXED_ALGOS:
+                        with self.subTest(
+                                msg=f'Testing options parsing for {algo_name}'):
+                            invoke_str = get_invoke_str(algo_name)
+                            result = runner.invoke(desbordante_cli, invoke_str)
+                            result_output = result.output
+                            self.assertEqual('success\n', result_output,
+                                             msg=f'Failed on {algo_name}')
+
+
+if __name__ == '__main__':
+    unittest.main()
diff --git a/cli/cli_tests/university.csv b/cli/cli_tests/university.csv
new file mode 100644
index 0000000000..c3afc981e6
--- /dev/null
+++ b/cli/cli_tests/university.csv
@@ -0,0 +1,9 @@
+Course,Classroom,Professor,Semester
+Math,512,Dr. Smith,Fall
+Physics,406,Dr. Green,Fall
+English,208,Prof. Turner,Fall
+History,209,Prof. Davis,Fall
+Math,512,Dr. Smith,Spring
+Physics,503,Dr. Gray,Spring
+English,116,Prof. Turner,Spring
+Biology,209,Prof. Light,Spring
diff --git a/cli/cli_tests/update_snapshots.sh b/cli/cli_tests/update_snapshots.sh
new file mode 100644
index 0000000000..773ec23291
--- /dev/null
+++ b/cli/cli_tests/update_snapshots.sh
@@ -0,0 +1,4 @@
+#!/usr/bin/bash
+
+export UPDATE_HELP_PAGES=true
+python3 test_cli_help_pages.py